Articles | Volume 16, issue 10
https://doi.org/10.5194/essd-16-4389-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-4389-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
01 Oct 2024
Data description paper |
| 01 Oct 2024
| 01 Oct 2024
Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation (NVDI) with MODIS NDVI
Fenner School of Environment & Society, Australian National University, Canberra, ACT, Australia
Sami W. Rifai
School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia
Luigi J. Renzullo
Hydrology Science, Bureau of Meteorology, Canberra, ACT, Australia
Albert I. J. M. Van Dijk
Fenner School of Environment & Society, Australian National University, Canberra, ACT, Australia
Related authors
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
Short summary
Short summary
Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yi Y. Liu, Albert I. J. M. van Dijk, Patrick Meir, and Tim R. McVicar
Biogeosciences, 21, 2273–2295, https://doi.org/10.5194/bg-21-2273-2024, https://doi.org/10.5194/bg-21-2273-2024, 2024
Short summary
Short summary
Greenness of the Amazon forest fluctuated during the 2015–2016 drought, but no satisfactory explanation has been found. Based on water storage, temperature, and atmospheric moisture demand, we developed a method to delineate the regions where forests were under stress. These drought-affected regions were mainly identified at the beginning and end of the drought, resulting in below-average greenness. For the months in between, without stress, greenness responded positively to intense sunlight.
Jiawei Hou, Albert I. J. M. Van Dijk, Luigi J. Renzullo, and Pablo R. Larraondo
Earth Syst. Sci. Data, 16, 201–218, https://doi.org/10.5194/essd-16-201-2024, https://doi.org/10.5194/essd-16-201-2024, 2024
Short summary
Short summary
The GloLakes dataset provides historical and near-real-time time series of relative (i.e. storage change) and absolute (i.e. total stored volume) storage for more than 27 000 lakes worldwide using multiple sources of satellite data, including laser and radar altimetry and optical remote sensing. These data can help us understand the influence of climate variability and anthropogenic activities on water availability and system ecology over the last 4 decades.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
Short summary
Short summary
Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Marina Corrêa Scalon, Imma Oliveras Menor, Renata Freitag, Karine S. Peixoto, Sami W. Rifai, Beatriz Schwantes Marimon, Ben Hur Marimon Junior, and Yadvinder Malhi
Biogeosciences, 19, 3649–3661, https://doi.org/10.5194/bg-19-3649-2022, https://doi.org/10.5194/bg-19-3649-2022, 2022
Short summary
Short summary
We investigated dynamic nutrient flow and demand in a typical savanna and a transition forest to understand how similar soils and the same climate dominated by savanna vegetation can also support forest-like formations. Savanna relied on nutrient resorption from wood, and nutrient demand was equally partitioned between leaves, wood and fine roots. Transition forest relied on resorption from the canopy biomass and nutrient demand was predominantly driven by leaves.
Jiawei Hou, Albert I. J. M. van Dijk, Hylke E. Beck, Luigi J. Renzullo, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 26, 3785–3803, https://doi.org/10.5194/hess-26-3785-2022, https://doi.org/10.5194/hess-26-3785-2022, 2022
Short summary
Short summary
We used satellite imagery to measure monthly reservoir water volumes for 6695 reservoirs worldwide for 1984–2015. We investigated how changing precipitation, streamflow, evaporation, and human activity affected reservoir water storage. Almost half of the reservoirs showed significant increasing or decreasing trends over the past three decades. These changes are caused, first and foremost, by changes in precipitation rather than by changes in net evaporation or dam release patterns.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
Short summary
Short summary
We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Songyan Yu, Hong Xuan Do, Albert I. J. M. van Dijk, Nick R. Bond, Peirong Lin, and Mark J. Kennard
Hydrol. Earth Syst. Sci., 24, 5279–5295, https://doi.org/10.5194/hess-24-5279-2020, https://doi.org/10.5194/hess-24-5279-2020, 2020
Short summary
Short summary
There is a growing interest globally in the spatial distribution and temporal dynamics of intermittently flowing streams and rivers. We developed an approach to quantify catchment-wide flow intermittency over long time frames. Modelled patterns of flow intermittency in eastern Australia revealed highly dynamic behaviour in space and time. The developed approach is transferable to other parts of the world and can inform hydro-ecological understanding and management of intermittent streams.
Jiawei Hou, Albert I. J. M. van Dijk, Luigi J. Renzullo, Robert A. Vertessy, and Norman Mueller
Earth Syst. Sci. Data, 11, 1003–1015, https://doi.org/10.5194/essd-11-1003-2019, https://doi.org/10.5194/essd-11-1003-2019, 2019
Short summary
Short summary
Hydromorphological data including temporal and spatial river width dynamics, flow regime, and river gradient for 1.4 x 106 Australian river reaches are presented. We propose a parameter which can be used to classify reaches by the degree to which flow regime tends towards permanent, frequent, intermittent, or ephemeral. This dataset provides fundamental information for understanding hydrological, biogeochemical, and ecological processes in floodplain–river systems.
Siyuan Tian, Luigi J. Renzullo, Albert I. J. M. van Dijk, Paul Tregoning, and Jeffrey P. Walker
Hydrol. Earth Syst. Sci., 23, 1067–1081, https://doi.org/10.5194/hess-23-1067-2019, https://doi.org/10.5194/hess-23-1067-2019, 2019
Hylke E. Beck, Ming Pan, Tirthankar Roy, Graham P. Weedon, Florian Pappenberger, Albert I. J. M. van Dijk, George J. Huffman, Robert F. Adler, and Eric F. Wood
Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, https://doi.org/10.5194/hess-23-207-2019, 2019
Short summary
Short summary
We conducted a comprehensive evaluation of 26 precipitation datasets for the US using the Stage-IV gauge-radar dataset as a reference. The best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for reporting times. Our findings can be used as a guide to choose the most suitable precipitation dataset for a particular application.
Jiawei Hou, Albert I. J. M. van Dijk, Luigi J. Renzullo, and Robert A. Vertessy
Hydrol. Earth Syst. Sci., 22, 6435–6448, https://doi.org/10.5194/hess-22-6435-2018, https://doi.org/10.5194/hess-22-6435-2018, 2018
Short summary
Short summary
Satellite-based river gauging can be constructed based on remote-sensing-derived surface water extent and modelled discharge, and used to estimate river discharges with satellite observations only. This provides opportunities for monitoring river discharge in the absence of a real-time hydrological model or gauging stations.
Albert I. J. M. van Dijk, Jaap Schellekens, Marta Yebra, Hylke E. Beck, Luigi J. Renzullo, Albrecht Weerts, and Gennadii Donchyts
Hydrol. Earth Syst. Sci., 22, 4959–4980, https://doi.org/10.5194/hess-22-4959-2018, https://doi.org/10.5194/hess-22-4959-2018, 2018
Short summary
Short summary
Evaporation from wetlands, lakes and irrigation areas needs to be measured to understand water scarcity. So far, this has only been possible for small regions. Here, we develop a solution that can be applied at a very high resolution globally by making use of satellite observations. Our results show that 16% of global water resources evaporate before reaching the ocean, mostly from surface water. Irrigation water use is less than 1% globally but is a very large water user in several dry basins.
Anouk I. Gevaert, Luigi J. Renzullo, Albert I. J. M. van Dijk, Hans J. van der Woerd, Albrecht H. Weerts, and Richard A. M. de Jeu
Hydrol. Earth Syst. Sci., 22, 4605–4619, https://doi.org/10.5194/hess-22-4605-2018, https://doi.org/10.5194/hess-22-4605-2018, 2018
Short summary
Short summary
We assimilated three satellite soil moisture retrievals based on different microwave frequencies into a hydrological model. Two sets of experiments were performed, first assimilating the retrievals individually and then assimilating each set of two retrievals jointly. Overall, assimilation improved agreement between model and field-measured soil moisture. Joint assimilation resulted in model performance similar to or better than assimilating either retrieval individually.
Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, https://doi.org/10.5194/hess-21-6201-2017, 2017
Short summary
Short summary
This study represents the most comprehensive global-scale precipitation dataset evaluation to date. We evaluated 13 uncorrected precipitation datasets using precipitation observations from 76 086 gauges, and 9 gauge-corrected ones using hydrological modeling for 9053 catchments. Our results highlight large differences in estimation accuracy, and hence, the importance of precipitation dataset selection in both research and operational applications.
Yoshihide Wada, Marc F. P. Bierkens, Ad de Roo, Paul A. Dirmeyer, James S. Famiglietti, Naota Hanasaki, Megan Konar, Junguo Liu, Hannes Müller Schmied, Taikan Oki, Yadu Pokhrel, Murugesu Sivapalan, Tara J. Troy, Albert I. J. M. van Dijk, Tim van Emmerik, Marjolein H. J. Van Huijgevoort, Henny A. J. Van Lanen, Charles J. Vörösmarty, Niko Wanders, and Howard Wheater
Hydrol. Earth Syst. Sci., 21, 4169–4193, https://doi.org/10.5194/hess-21-4169-2017, https://doi.org/10.5194/hess-21-4169-2017, 2017
Short summary
Short summary
Rapidly increasing population and human activities have altered terrestrial water fluxes on an unprecedented scale. Awareness of potential water scarcity led to first global water resource assessments; however, few hydrological models considered the interaction between terrestrial water fluxes and human activities. Our contribution highlights the importance of human activities transforming the Earth's water cycle, and how hydrological models can include such influences in an integrated manner.
Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, https://doi.org/10.5194/essd-9-389-2017, 2017
Short summary
Short summary
The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Hylke E. Beck, Albert I. J. M. van Dijk, Ad de Roo, Emanuel Dutra, Gabriel Fink, Rene Orth, and Jaap Schellekens
Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, https://doi.org/10.5194/hess-21-2881-2017, 2017
Short summary
Short summary
Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.
Lan T. Ha, Wim G. M. Bastiaanssen, Ann van Griensven, Albert I. J. M. van Dijk, and Gabriel B. Senay
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-251, https://doi.org/10.5194/hess-2017-251, 2017
Preprint withdrawn
Short summary
Short summary
The paper shows a new approach in calibrating hydrological model using remote sensing data from open access sources. The innovation is that the parameters of the soil-vegetation processes were optimized that will make SWAT a useful tool for optimizing water conservation, agricultural outputs, and ecosystem services such as reduced soil erosion, better water quality standards, carbon sequestration, micro-climate cooling and appraising scenarios of green growth.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, https://doi.org/10.5194/hess-21-589-2017, 2017
Short summary
Short summary
MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
Caitlin E. Moore, Tim Brown, Trevor F. Keenan, Remko A. Duursma, Albert I. J. M. van Dijk, Jason Beringer, Darius Culvenor, Bradley Evans, Alfredo Huete, Lindsay B. Hutley, Stefan Maier, Natalia Restrepo-Coupe, Oliver Sonnentag, Alison Specht, Jeffrey R. Taylor, Eva van Gorsel, and Michael J. Liddell
Biogeosciences, 13, 5085–5102, https://doi.org/10.5194/bg-13-5085-2016, https://doi.org/10.5194/bg-13-5085-2016, 2016
Short summary
Short summary
Australian vegetation phenology is highly variable due to the diversity of ecosystems on the continent. We explore continental-scale variability using satellite remote sensing by broadly classifying areas as seasonal, non-seasonal, or irregularly seasonal. We also examine ecosystem-scale phenology using phenocams and show that some broadly non-seasonal ecosystems do display phenological variability. Overall, phenocams are useful for understanding ecosystem-scale Australian vegetation phenology.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
Short summary
Short summary
In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
Lan Wang-Erlandsson, Wim G. M. Bastiaanssen, Hongkai Gao, Jonas Jägermeyr, Gabriel B. Senay, Albert I. J. M. van Dijk, Juan P. Guerschman, Patrick W. Keys, Line J. Gordon, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 20, 1459–1481, https://doi.org/10.5194/hess-20-1459-2016, https://doi.org/10.5194/hess-20-1459-2016, 2016
Short summary
Short summary
We present an "Earth observation-based" method for estimating root zone storage capacity – a critical parameter in land surface modelling that represents the maximum amount of soil moisture available for vegetation. Variability within a land cover type is captured, and a global model evaporation simulation is overall improved, particularly in sub-humid to humid regions with seasonality. This new method can eliminate the need for unreliable soil and root depth data in land surface modelling.
A. I. J. M. van Dijk, L. J. Renzullo, Y. Wada, and P. Tregoning
Hydrol. Earth Syst. Sci., 18, 2955–2973, https://doi.org/10.5194/hess-18-2955-2014, https://doi.org/10.5194/hess-18-2955-2014, 2014
N. Andela, Y. Y. Liu, A. I. J. M. van Dijk, R. A. M. de Jeu, and T. R. McVicar
Biogeosciences, 10, 6657–6676, https://doi.org/10.5194/bg-10-6657-2013, https://doi.org/10.5194/bg-10-6657-2013, 2013
H. E. Beck, L. A. Bruijnzeel, A. I. J. M. van Dijk, T. R. McVicar, F. N. Scatena, and J. Schellekens
Hydrol. Earth Syst. Sci., 17, 2613–2635, https://doi.org/10.5194/hess-17-2613-2013, https://doi.org/10.5194/hess-17-2613-2013, 2013
Related subject area
Domain: ESSD – Land | Subject: Biogeosciences and biodiversity
VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring
Crop-specific management history of phosphorus fertilizer input (CMH-P) in the croplands of the United States: reconciliation of top-down and bottom-up data sources
A synthesized field survey database of vegetation and active-layer properties for the Alaskan tundra (1972–2020)
Gas exchange velocities (k600), gas exchange rates (K600), and hydraulic geometries for streams and rivers derived from the NEON Reaeration field and lab collection data product (DP1.20190.001)
A spectral-structural characterization of European temperate, hemiboreal and boreal forests
TCSIF: a temporally consistent global Global Ozone Monitoring Experiment-2A (GOME-2A) solar-induced chlorophyll fluorescence dataset with the correction of sensor degradation
National forest carbon harvesting and allocation dataset for the period 2003 to 2018
Spatial mapping of key plant functional traits in terrestrial ecosystems across China
HiQ-LAI: a high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2022
EUPollMap: the European atlas of contemporary pollen distribution maps derived from an integrated Kriging interpolation approach
Reference maps of soil phosphorus for the pan-Amazon region
Mapping 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020
Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022
Investigating limnological processes and modern sedimentation at Lake Żabińskie, northeast Poland: a decade-long multi-variable dataset, 2012–2021
Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020
Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022
CLIM4OMICS: a geospatially comprehensive climate and multi-OMICS database for maize phenotype predictability in the United States and Canada
Quantifying exchangeable base cations in permafrost: a reserve of nutrients about to thaw
Routine monitoring of western Lake Erie to track water quality changes associated with cyanobacterial harmful algal blooms
The Portuguese Large Wildfire Spread database (PT-FireSprd)
Thirty-meter map of young forest age in China
GRiMeDB: the Global River Methane Database of concentrations and fluxes
A gridded dataset of a leaf-age-dependent leaf area index seasonality product over tropical and subtropical evergreen broadleaved forests
Fire weather index data under historical and shared socioeconomic pathway projections in the 6th phase of the Coupled Model Intercomparison Project from 1850 to 2100
A remote-sensing-based dataset to characterize the ecosystem functioning and functional diversity in the Biosphere Reserve of the Sierra Nevada (southeastern Spain)
A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT
A global database on holdover time of lightning-ignited wildfires
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake
Mammals in the Chornobyl Exclusion Zone's Red Forest: a motion-activated camera trap study
Maps with 1 km resolution reveal increases in above- and belowground forest biomass carbon pools in China over the past 20 years
AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America
TiP-Leaf: a dataset of leaf traits across vegetation types on the Tibetan Plateau
Forest structure and individual tree inventories of northeastern Siberia along climatic gradients
Global climate-related predictors at kilometer resolution for the past and future
A daily and 500 m coupled evapotranspiration and gross primary production product across China during 2000–2020
Global land surface 250 m 8 d fraction of absorbed photosynthetically active radiation (FAPAR) product from 2000 to 2021
Rates and timing of chlorophyll-a increases and related environmental variables in global temperate and cold-temperate lakes
Harmonized gap-filled datasets from 20 urban flux tower sites
Holocene spatiotemporal millet agricultural patterns in northern China: a dataset of archaeobotanical macroremains
The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil
Airborne SnowSAR data at X and Ku bands over boreal forest, alpine and tundra snow cover
The Landscape Fire Scars Database: mapping historical burned area and fire severity in Chile
Aridec: an open database of litter mass loss from aridlands worldwide with recommendations on suitable model applications
LegacyPollen 1.0: a taxonomically harmonized global late Quaternary pollen dataset of 2831 records with standardized chronologies
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
Short summary
Short summary
VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Peiyu Cao, Bo Yi, Franco Bilotto, Carlos Gonzalez Fischer, Mario Herrero, and Chaoqun Lu
Earth Syst. Sci. Data, 16, 4557–4572, https://doi.org/10.5194/essd-16-4557-2024, https://doi.org/10.5194/essd-16-4557-2024, 2024
Short summary
Short summary
This article presents a spatially explicit time series dataset reconstructing crop-specific phosphorus fertilizer application rates, timing, and methods at a 4 km × 4 km resolution in the United States from 1850 to 2022. We comprehensively characterized the spatio-temporal dynamics of P fertilizer management over the last 170 years by considering cross-crop variations. This dataset will greatly contribute to the field of agricultural sustainability assessment and Earth system modeling.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
Short summary
Short summary
The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Kelly S. Aho, Kaelin Cawley, Robert Hensley, Robert O. Hall Jr., Walter Dodds, and Keli Goodman
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-330, https://doi.org/10.5194/essd-2024-330, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
In streams, gas exchange is fundamental to many biogeochemical processes. Gas exchange depends on the degree of saturation and the gas transfer velocity (k). Currently, k is harder to measure than concentration. NEON conducts tracer-gas experiments at 22 streams. Here, we present our processing pipeline to estimate k from these experiments. This dataset (n = 339) represents the largest compilation of standardized k estimates available and captures substantial within- and across-site variability.
Miina Rautiainen, Aarne Hovi, Daniel Schraik, Jan Hanuš, Petr Lukeš, Zuzana Lhotáková, and Lucie Homolová
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-154, https://doi.org/10.5194/essd-2024-154, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Radiative transfer models play a key role in monitoring vegetation using remote sensing data such as satellite or airborne images. The development of these models has been hindered by a lack of comprehensive ground reference data on structural and spectral characteristics of forests. Here, we reported datasets on the structural and spectral properties of temperate, hemiboreal, and boreal European forest stands. We anticipate that these data will have wide use in remote sensing applications.
Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu
Earth Syst. Sci. Data, 16, 2789–2809, https://doi.org/10.5194/essd-16-2789-2024, https://doi.org/10.5194/essd-16-2789-2024, 2024
Short summary
Short summary
To obtain a temporally consistent satellite solar-induced chlorophyll fluorescence
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
Daju Wang, Peiyang Ren, Xiaosheng Xia, Lei Fan, Zhangcai Qin, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data, 16, 2465–2481, https://doi.org/10.5194/essd-16-2465-2024, https://doi.org/10.5194/essd-16-2465-2024, 2024
Short summary
Short summary
This study generated a high-precision dataset, locating forest harvested carbon and quantifying post-harvest wood emissions for various uses. It enhances our understanding of forest harvesting and post-harvest carbon dynamics in China, providing essential data for estimating the forest ecosystem carbon budget and emphasizing wood utilization's impact on carbon emissions.
Nannan An, Nan Lu, Weiliang Chen, Yongzhe Chen, Hao Shi, Fuzhong Wu, and Bojie Fu
Earth Syst. Sci. Data, 16, 1771–1810, https://doi.org/10.5194/essd-16-1771-2024, https://doi.org/10.5194/essd-16-1771-2024, 2024
Short summary
Short summary
This study generated a spatially continuous plant functional trait dataset (~1 km) in China in combination with field observations, environmental variables and vegetation indices using machine learning methods. Results showed that wood density, leaf P concentration and specific leaf area showed good accuracy with an average R2 of higher than 0.45. This dataset could provide data support for development of Earth system models to predict vegetation distribution and ecosystem functions.
Kai Yan, Jingrui Wang, Rui Peng, Kai Yang, Xiuzhi Chen, Gaofei Yin, Jinwei Dong, Marie Weiss, Jiabin Pu, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 1601–1622, https://doi.org/10.5194/essd-16-1601-2024, https://doi.org/10.5194/essd-16-1601-2024, 2024
Short summary
Short summary
Variations in observational conditions have led to poor spatiotemporal consistency in leaf area index (LAI) time series. Using prior knowledge, we leveraged high-quality observations and spatiotemporal correlation to reprocess MODIS LAI, thereby generating HiQ-LAI, a product that exhibits fewer abnormal fluctuations in time series. Reprocessing was done on Google Earth Engine, providing users with convenient access to this value-added data and facilitating large-scale research and applications.
Fabio Oriani, Gregoire Mariethoz, and Manuel Chevalier
Earth Syst. Sci. Data, 16, 731–742, https://doi.org/10.5194/essd-16-731-2024, https://doi.org/10.5194/essd-16-731-2024, 2024
Short summary
Short summary
Modern and fossil pollen data contain precious information for reconstructing the climate and environment of the past. However, these data are only achieved for single locations with no continuity in space. We present here a systematic atlas of 194 digital maps containing the spatial estimation of contemporary pollen presence over Europe. This dataset constitutes a free and ready-to-use tool to study climate, biodiversity, and environment in time and space.
João Paulo Darela-Filho, Anja Rammig, Katrin Fleischer, Tatiana Reichert, Laynara Figueiredo Lugli, Carlos Alberto Quesada, Luis Carlos Colocho Hurtarte, Mateus Dantas de Paula, and David M. Lapola
Earth Syst. Sci. Data, 16, 715–729, https://doi.org/10.5194/essd-16-715-2024, https://doi.org/10.5194/essd-16-715-2024, 2024
Short summary
Short summary
Phosphorus (P) is crucial for plant growth, and scientists have created models to study how it interacts with carbon cycle in ecosystems. To apply these models, it is important to know the distribution of phosphorus in soil. In this study we estimated the distribution of phosphorus in the Amazon region. The results showed a clear gradient of soil development and P content. These maps can help improve ecosystem models and generate new hypotheses about phosphorus availability in the Amazon.
Mengyao Zhu, Junhu Dai, Huanjiong Wang, Juha M. Alatalo, Wei Liu, Yulong Hao, and Quansheng Ge
Earth Syst. Sci. Data, 16, 277–293, https://doi.org/10.5194/essd-16-277-2024, https://doi.org/10.5194/essd-16-277-2024, 2024
Short summary
Short summary
This study utilized 24,552 in situ phenology observation records from the Chinese Phenology Observation Network to model and map 24 woody plant species phenology and ground forest phenology over China from 1951 to 2020. These phenology maps are the first gridded, independent and reliable phenology data sources for China, offering a high spatial resolution of 0.1° and an average deviation of about 10 days. It contributes to more comprehensive research on plant phenology and climate change.
Jiabin Pu, Kai Yan, Samapriya Roy, Zaichun Zhu, Miina Rautiainen, Yuri Knyazikhin, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 15–34, https://doi.org/10.5194/essd-16-15-2024, https://doi.org/10.5194/essd-16-15-2024, 2024
Short summary
Short summary
Long-term global LAI/FPAR products provide the fundamental dataset for accessing vegetation dynamics and studying climate change. This study develops a sensor-independent LAI/FPAR climate data record based on the integration of Terra-MODIS/Aqua-MODIS/VIIRS LAI/FPAR standard products and applies advanced gap-filling techniques. The SI LAI/FPAR CDR provides a valuable resource for researchers studying vegetation dynamics and their relationship to climate change in the 21st century.
Wojciech Tylmann, Alicja Bonk, Dariusz Borowiak, Paulina Głowacka, Kamil Nowiński, Joanna Piłczyńska, Agnieszka Szczerba, and Maurycy Żarczyński
Earth Syst. Sci. Data, 15, 5093–5103, https://doi.org/10.5194/essd-15-5093-2023, https://doi.org/10.5194/essd-15-5093-2023, 2023
Short summary
Short summary
We present a dataset from the decade-long monitoring of Lake Żabińskie, a hardwater and eutrophic lake in northeast Poland. The lake contains varved sediments, which form a unique archive of past environmental variability. The monitoring program was designed to capture a pattern of relationships between meteorological conditions, limnological processes, and modern sedimentation and to verify if meteorological and limnological phenomena can be precisely tracked with varves.
Sen Cao, Muyi Li, Zaichun Zhu, Zhe Wang, Junjun Zha, Weiqing Zhao, Zeyu Duanmu, Jiana Chen, Yaoyao Zheng, Yue Chen, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4877–4899, https://doi.org/10.5194/essd-15-4877-2023, https://doi.org/10.5194/essd-15-4877-2023, 2023
Short summary
Short summary
The long-term global leaf area index (LAI) products are critical for characterizing vegetation dynamics under environmental changes. This study presents an updated GIMMS LAI product (GIMMS LAI4g; 1982−2020) based on PKU GIMMS NDVI and massive Landsat LAI samples. With higher accuracy than other LAI products, GIMMS LAI4g removes the effects of orbital drift and sensor degradation in AVHRR data. It has better temporal consistency before and after 2000 and a more reasonable global vegetation trend.
Muyi Li, Sen Cao, Zaichun Zhu, Zhe Wang, Ranga B. Myneni, and Shilong Piao
Earth Syst. Sci. Data, 15, 4181–4203, https://doi.org/10.5194/essd-15-4181-2023, https://doi.org/10.5194/essd-15-4181-2023, 2023
Short summary
Short summary
Long-term global Normalized Difference Vegetation Index (NDVI) products support the understanding of changes in vegetation under environmental changes. This study generates a consistent global NDVI product (PKU GIMMS NDVI) from 1982–2022 that eliminates the issue of orbital drift and sensor degradation in Advanced Very High Resolution Radiometer (AVHRR) data. More accurate than its predecessor (GIMMS NDVI3g), it shows high temporal consistency with MODIS NDVI in describing vegetation trends.
Parisa Sarzaeim, Francisco Muñoz-Arriola, Diego Jarquin, Hasnat Aslam, and Natalia De Leon Gatti
Earth Syst. Sci. Data, 15, 3963–3990, https://doi.org/10.5194/essd-15-3963-2023, https://doi.org/10.5194/essd-15-3963-2023, 2023
Short summary
Short summary
A genomic, phenomic, and climate database for maize phenotype predictability in the US and Canada is introduced. The database encompasses climate from multiple sources and OMICS from the Genomes to Fields initiative (G2F) data from 2014 to 2021, including codes for input data quality and consistency controls. Earth system modelers and breeders can use CLIM4OMICS since it interconnects the climate and biological system sciences. CLIM4OMICS is designed to foster phenotype predictability.
Elisabeth Mauclet, Maëlle Villani, Arthur Monhonval, Catherine Hirst, Edward A. G. Schuur, and Sophie Opfergelt
Earth Syst. Sci. Data, 15, 3891–3904, https://doi.org/10.5194/essd-15-3891-2023, https://doi.org/10.5194/essd-15-3891-2023, 2023
Short summary
Short summary
Permafrost ecosystems are limited in nutrients for vegetation development and constrain the biological activity to the active layer. Upon Arctic warming, permafrost degradation exposes organic and mineral soil material that may directly influence the capacity of the soil to retain key nutrients for vegetation growth and development. Here, we demonstrate that the average total exchangeable nutrient density (Ca, K, Mg, and Na) is more than 2 times higher in the permafrost than in the active layer.
Anna G. Boegehold, Ashley M. Burtner, Andrew C. Camilleri, Glenn Carter, Paul DenUyl, David Fanslow, Deanna Fyffe Semenyuk, Casey M. Godwin, Duane Gossiaux, Thomas H. Johengen, Holly Kelchner, Christine Kitchens, Lacey A. Mason, Kelly McCabe, Danna Palladino, Dack Stuart, Henry Vanderploeg, and Reagan Errera
Earth Syst. Sci. Data, 15, 3853–3868, https://doi.org/10.5194/essd-15-3853-2023, https://doi.org/10.5194/essd-15-3853-2023, 2023
Short summary
Short summary
Western Lake Erie suffers from cyanobacterial harmful algal blooms (HABs) despite decades of international management efforts. In response, the US National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) and the Cooperative Institute for Great Lakes Research (CIGLR) created an annual sampling program to detect, monitor, assess, and predict HABs. Here we describe the data collected from this monitoring program from 2012 to 2021.
Akli Benali, Nuno Guiomar, Hugo Gonçalves, Bernardo Mota, Fábio Silva, Paulo M. Fernandes, Carlos Mota, Alexandre Penha, João Santos, José M. C. Pereira, and Ana C. L. Sá
Earth Syst. Sci. Data, 15, 3791–3818, https://doi.org/10.5194/essd-15-3791-2023, https://doi.org/10.5194/essd-15-3791-2023, 2023
Short summary
Short summary
We reconstructed the spread of 80 large wildfires that burned recently in Portugal and calculated metrics that describe how wildfires behave, such as rate of spread, growth rate, and energy released. We describe the fire behaviour distribution using six percentile intervals that can be easily communicated to both research and management communities. The database will help improve our current knowledge on wildfire behaviour and support better decision making.
Yuelong Xiao, Qunming Wang, Xiaohua Tong, and Peter M. Atkinson
Earth Syst. Sci. Data, 15, 3365–3386, https://doi.org/10.5194/essd-15-3365-2023, https://doi.org/10.5194/essd-15-3365-2023, 2023
Short summary
Short summary
Forest age is closely related to forest production, carbon cycles, and other ecosystem services. Existing stand age products in China derived from remote-sensing images are of a coarse spatial resolution and are not suitable for applications at the regional scale. Here, we mapped young forest ages across China at an unprecedented fine spatial resolution of 30 m. The overall accuracy (OA) of the generated map of young forest stand ages across China was 90.28 %.
Emily H. Stanley, Luke C. Loken, Nora J. Casson, Samantha K. Oliver, Ryan A. Sponseller, Marcus B. Wallin, Liwei Zhang, and Gerard Rocher-Ros
Earth Syst. Sci. Data, 15, 2879–2926, https://doi.org/10.5194/essd-15-2879-2023, https://doi.org/10.5194/essd-15-2879-2023, 2023
Short summary
Short summary
The Global River Methane Database (GRiMeDB) presents CH4 concentrations and fluxes for flowing waters and concurrent measures of CO2, N2O, and several physicochemical variables, plus information about sample locations and methods used to measure gas fluxes. GRiMeDB is intended to increase opportunities to understand variation in fluvial CH4, test hypotheses related to greenhouse gas dynamics, and reduce uncertainty in future estimates of gas emissions from world streams and rivers.
Xueqin Yang, Xiuzhi Chen, Jiashun Ren, Wenping Yuan, Liyang Liu, Juxiu Liu, Dexiang Chen, Yihua Xiao, Qinghai Song, Yanjun Du, Shengbiao Wu, Lei Fan, Xiaoai Dai, Yunpeng Wang, and Yongxian Su
Earth Syst. Sci. Data, 15, 2601–2622, https://doi.org/10.5194/essd-15-2601-2023, https://doi.org/10.5194/essd-15-2601-2023, 2023
Short summary
Short summary
We developed the first time-mapped, continental-scale gridded dataset of monthly leaf area index (LAI) in three leaf age cohorts (i.e., young, mature, and old) from 2001–2018 data (referred to as Lad-LAI). The seasonality of three LAI cohorts from the new Lad-LAI product agrees well at eight sites with very fine-scale collections of monthly LAI. The proposed satellite-based approaches can provide references for mapping finer spatiotemporal-resolution LAI products with different leaf age cohorts.
Yann Quilcaille, Fulden Batibeniz, Andreia F. S. Ribeiro, Ryan S. Padrón, and Sonia I. Seneviratne
Earth Syst. Sci. Data, 15, 2153–2177, https://doi.org/10.5194/essd-15-2153-2023, https://doi.org/10.5194/essd-15-2153-2023, 2023
Short summary
Short summary
We present a new database of four annual fire weather indicators over 1850–2100 and over all land areas. In a 3°C warmer world with respect to preindustrial times, the mean fire weather would increase on average by at least 66% in both intensity and duration and even triple for 1-in-10-year events. The dataset is a freely available resource for fire danger studies and beyond, highlighting that the best course of action would require limiting global warming as much as possible.
Beatriz P. Cazorla, Javier Cabello, Andrés Reyes, Emilio Guirado, Julio Peñas, Antonio J. Pérez-Luque, and Domingo Alcaraz-Segura
Earth Syst. Sci. Data, 15, 1871–1887, https://doi.org/10.5194/essd-15-1871-2023, https://doi.org/10.5194/essd-15-1871-2023, 2023
Short summary
Short summary
This dataset provides scientists, environmental managers, and the public in general with valuable information on the first characterization of ecosystem functional diversity based on primary production developed in the Sierra Nevada (Spain), a biodiversity hotspot in the Mediterranean basin and an exceptional natural laboratory for ecological research within the Long-Term Social-Ecological Research (LTSER) network.
Shengli Tao, Zurui Ao, Jean-Pierre Wigneron, Sassan Saatchi, Philippe Ciais, Jérôme Chave, Thuy Le Toan, Pierre-Louis Frison, Xiaomei Hu, Chi Chen, Lei Fan, Mengjia Wang, Jiangling Zhu, Xia Zhao, Xiaojun Li, Xiangzhuo Liu, Yanjun Su, Tianyu Hu, Qinghua Guo, Zhiheng Wang, Zhiyao Tang, Yi Y. Liu, and Jingyun Fang
Earth Syst. Sci. Data, 15, 1577–1596, https://doi.org/10.5194/essd-15-1577-2023, https://doi.org/10.5194/essd-15-1577-2023, 2023
Short summary
Short summary
We provide the first long-term (since 1992), high-resolution (8.9 km) satellite radar backscatter data set (LHScat) with a C-band (5.3 GHz) signal dynamic for global lands. LHScat was created by fusing signals from ERS (1992–2001; C-band), QSCAT (1999–2009; Ku-band), and ASCAT (since 2007; C-band). LHScat has been validated against independent ERS-2 signals. It could be used in a variety of studies, such as vegetation monitoring and hydrological modelling.
Jose V. Moris, Pedro Álvarez-Álvarez, Marco Conedera, Annalie Dorph, Thomas D. Hessilt, Hugh G. P. Hunt, Renata Libonati, Lucas S. Menezes, Mortimer M. Müller, Francisco J. Pérez-Invernón, Gianni B. Pezzatti, Nicolau Pineda, Rebecca C. Scholten, Sander Veraverbeke, B. Mike Wotton, and Davide Ascoli
Earth Syst. Sci. Data, 15, 1151–1163, https://doi.org/10.5194/essd-15-1151-2023, https://doi.org/10.5194/essd-15-1151-2023, 2023
Short summary
Short summary
This work describes a database on holdover times of lightning-ignited wildfires (LIWs). Holdover time is defined as the time between lightning-induced fire ignition and fire detection. The database contains 42 datasets built with data on more than 152 375 LIWs from 13 countries in five continents from 1921 to 2020. This database is the first freely-available, harmonized and ready-to-use global source of holdover time data, which may be used to investigate LIWs and model the holdover phenomenon.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
Short summary
Short summary
Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Nicholas A. Beresford, Sergii Gashchak, Michael D. Wood, and Catherine L. Barnett
Earth Syst. Sci. Data, 15, 911–920, https://doi.org/10.5194/essd-15-911-2023, https://doi.org/10.5194/essd-15-911-2023, 2023
Short summary
Short summary
Camera traps were established in a highly contaminated area of the Chornobyl Exclusion Zone (CEZ) to capture images of mammals. Over 1 year, 14 mammal species were recorded. The number of species observed did not vary with estimated radiation exposure. The data will be of value from the perspectives of effects of radiation on wildlife and also rewilding in this large, abandoned area. They may also have value in future studies investigating impacts of recent Russian military action in the CEZ.
Yongzhe Chen, Xiaoming Feng, Bojie Fu, Haozhi Ma, Constantin M. Zohner, Thomas W. Crowther, Yuanyuan Huang, Xutong Wu, and Fangli Wei
Earth Syst. Sci. Data, 15, 897–910, https://doi.org/10.5194/essd-15-897-2023, https://doi.org/10.5194/essd-15-897-2023, 2023
Short summary
Short summary
This study presented a long-term (2002–2021) above- and belowground biomass dataset for woody vegetation in China at 1 km resolution. It was produced by combining various types of remote sensing observations with adequate plot measurements. Over 2002–2021, China’s woody biomass increased at a high rate, especially in the central and southern parts. This dataset can be applied to evaluate forest carbon sinks across China and the efficiency of ecological restoration programs in China.
Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão
Earth Syst. Sci. Data, 15, 345–358, https://doi.org/10.5194/essd-15-345-2023, https://doi.org/10.5194/essd-15-345-2023, 2023
Short summary
Short summary
The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
Yili Jin, Haoyan Wang, Jie Xia, Jian Ni, Kai Li, Ying Hou, Jing Hu, Linfeng Wei, Kai Wu, Haojun Xia, and Borui Zhou
Earth Syst. Sci. Data, 15, 25–39, https://doi.org/10.5194/essd-15-25-2023, https://doi.org/10.5194/essd-15-25-2023, 2023
Short summary
Short summary
The TiP-Leaf dataset was compiled from direct field measurements and included 11 leaf traits from 468 species of 1692 individuals, covering a great proportion of species and vegetation types on the highest plateau in the world. This work is the first plant trait dataset that represents all of the alpine vegetation on the TP, which is not only an update of the Chinese plant trait database, but also a great contribution to the global trait database.
Timon Miesner, Ulrike Herzschuh, Luidmila A. Pestryakova, Mareike Wieczorek, Evgenii S. Zakharov, Alexei I. Kolmogorov, Paraskovya V. Davydova, and Stefan Kruse
Earth Syst. Sci. Data, 14, 5695–5716, https://doi.org/10.5194/essd-14-5695-2022, https://doi.org/10.5194/essd-14-5695-2022, 2022
Short summary
Short summary
We present data which were collected on expeditions to the northeast of the Russian Federation. One table describes the 226 locations we visited during those expeditions, and the other describes 40 289 trees which we recorded at these locations. We found out that important information on the forest cannot be predicted precisely from satellites. Thus, for anyone interested in distant forests, it is important to go to there and take measurements or use data (as presented here).
Philipp Brun, Niklaus E. Zimmermann, Chantal Hari, Loïc Pellissier, and Dirk Nikolaus Karger
Earth Syst. Sci. Data, 14, 5573–5603, https://doi.org/10.5194/essd-14-5573-2022, https://doi.org/10.5194/essd-14-5573-2022, 2022
Short summary
Short summary
Using mechanistic downscaling, we developed CHELSA-BIOCLIM+, a set of 15 biologically relevant, climate-related variables at unprecedented resolution, as a basis for environmental analyses. It includes monthly time series for 38+ years and 30-year averages for three future periods and three emission scenarios. Estimates matched well with station measurements, but few biases existed. The data allow for detailed assessments of climate-change impact on ecosystems and their services to societies.
Shaoyang He, Yongqiang Zhang, Ning Ma, Jing Tian, Dongdong Kong, and Changming Liu
Earth Syst. Sci. Data, 14, 5463–5488, https://doi.org/10.5194/essd-14-5463-2022, https://doi.org/10.5194/essd-14-5463-2022, 2022
Short summary
Short summary
This study developed a daily, 500 m evapotranspiration and gross primary production product (PML-V2(China)) using a locally calibrated water–carbon coupled model, PML-V2, which was well calibrated against observations at 26 flux sites across nine land cover types. PML-V2 (China) performs satisfactorily in the plot- and basin-scale evaluations compared with other mainstream products. It improved intra-annual ET and GPP dynamics, particularly in the cropland ecosystem.
Han Ma, Shunlin Liang, Changhao Xiong, Qian Wang, Aolin Jia, and Bing Li
Earth Syst. Sci. Data, 14, 5333–5347, https://doi.org/10.5194/essd-14-5333-2022, https://doi.org/10.5194/essd-14-5333-2022, 2022
Short summary
Short summary
The fraction of absorbed photosynthetically active radiation (FAPAR) is one of the essential climate variables. This study generated a global land surface FAPAR product with a 250 m resolution based on a deep learning model that takes advantage of the existing FAPAR products and MODIS time series of observation information. Direct validation and intercomparison revealed that our product better meets user requirements and has a greater spatiotemporal continuity than other existing products.
Hannah Adams, Jane Ye, Bhaleka D. Persaud, Stephanie Slowinski, Homa Kheyrollah Pour, and Philippe Van Cappellen
Earth Syst. Sci. Data, 14, 5139–5156, https://doi.org/10.5194/essd-14-5139-2022, https://doi.org/10.5194/essd-14-5139-2022, 2022
Short summary
Short summary
Climate warming and land-use changes are altering the environmental factors that control the algal
productivityin lakes. To predict how environmental factors like nutrient concentrations, ice cover, and water temperature will continue to influence lake productivity in this changing climate, we created a dataset of chlorophyll-a concentrations (a compound found in algae), associated water quality parameters, and solar radiation that can be used to for a wide range of research questions.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
Short summary
Short summary
We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Keyang He, Houyuan Lu, Jianping Zhang, and Can Wang
Earth Syst. Sci. Data, 14, 4777–4791, https://doi.org/10.5194/essd-14-4777-2022, https://doi.org/10.5194/essd-14-4777-2022, 2022
Short summary
Short summary
Here we presented the first quantitative spatiotemporal cropping patterns spanning the Neolithic and Bronze ages in northern China. Temporally, millet agriculture underwent a dramatic transition from low-yield broomcorn to high-yield foxtail millet around 6000 cal. a BP under the influence of climate and population. Spatially, millet agriculture spread westward and northward from the mid-lower Yellow River (MLY) to the agro-pastoral ecotone (APE) around 6000 cal. a BP and diversified afterwards.
Kailiang Yu, Johan van den Hoogen, Zhiqiang Wang, Colin Averill, Devin Routh, Gabriel Reuben Smith, Rebecca E. Drenovsky, Kate M. Scow, Fei Mo, Mark P. Waldrop, Yuanhe Yang, Weize Tang, Franciska T. De Vries, Richard D. Bardgett, Peter Manning, Felipe Bastida, Sara G. Baer, Elizabeth M. Bach, Carlos García, Qingkui Wang, Linna Ma, Baodong Chen, Xianjing He, Sven Teurlincx, Amber Heijboer, James A. Bradley, and Thomas W. Crowther
Earth Syst. Sci. Data, 14, 4339–4350, https://doi.org/10.5194/essd-14-4339-2022, https://doi.org/10.5194/essd-14-4339-2022, 2022
Short summary
Short summary
We used a global-scale dataset for the surface topsoil (>3000 distinct observations of abundance of soil fungi versus bacteria) to generate the first quantitative map of soil fungal proportion across terrestrial ecosystems. We reveal striking latitudinal trends. Fungi dominated in regions with low mean annual temperature (MAT) and net primary productivity (NPP) and bacteria dominated in regions with high MAT and NPP.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
Short summary
Short summary
The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Alejandro Miranda, Rayén Mentler, Ítalo Moletto-Lobos, Gabriela Alfaro, Leonardo Aliaga, Dana Balbontín, Maximiliano Barraza, Susanne Baumbach, Patricio Calderón, Fernando Cárdenas, Iván Castillo, Gonzalo Contreras, Felipe de la Barra, Mauricio Galleguillos, Mauro E. González, Carlos Hormazábal, Antonio Lara, Ian Mancilla, Francisca Muñoz, Cristian Oyarce, Francisca Pantoja, Rocío Ramírez, and Vicente Urrutia
Earth Syst. Sci. Data, 14, 3599–3613, https://doi.org/10.5194/essd-14-3599-2022, https://doi.org/10.5194/essd-14-3599-2022, 2022
Short summary
Short summary
Achieving a local understanding of fire regimes requires high-resolution, systematic and dynamic data. High-quality information can help to transform evidence into decision-making. Taking advantage of big-data and remote sensing technics we developed a flexible workflow to reconstruct burned area and fire severity data for more than 8000 individual fires in Chile. The framework developed for the database can be applied anywhere in the world with minimal adaptation.
Agustín Sarquis, Ignacio Andrés Siebenhart, Amy Theresa Austin, and Carlos A. Sierra
Earth Syst. Sci. Data, 14, 3471–3488, https://doi.org/10.5194/essd-14-3471-2022, https://doi.org/10.5194/essd-14-3471-2022, 2022
Short summary
Short summary
Plant litter breakdown in aridlands is driven by processes different from those in more humid ecosystems. A better understanding of these processes will allow us to make better predictions of future carbon cycling. We have compiled aridec, a database of plant litter decomposition studies in aridlands and tested some modeling applications for potential users. Aridec is open for use and collaboration, and we hope it will help answer newer and more important questions as the database develops.
Ulrike Herzschuh, Chenzhi Li, Thomas Böhmer, Alexander K. Postl, Birgit Heim, Andrei A. Andreev, Xianyong Cao, Mareike Wieczorek, and Jian Ni
Earth Syst. Sci. Data, 14, 3213–3227, https://doi.org/10.5194/essd-14-3213-2022, https://doi.org/10.5194/essd-14-3213-2022, 2022
Short summary
Short summary
Pollen preserved in environmental archives such as lake sediments and bogs are extensively used for reconstructions of past vegetation and climate. Here we present LegacyPollen 1.0, a dataset of 2831 fossil pollen records from all over the globe that were collected from publicly available databases. We harmonized the names of the pollen taxa so that all datasets can be jointly investigated. LegacyPollen 1.0 is available as an open-access dataset.
Cited articles
Beck, H. E., McVicar, T. R., van Dijk, A. I., Schellekens, J., de Jeu, R. A., and Bruijnzeel, L. A.: Global evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery, Remote Sens. Environ., 115, 2547–2563, 2011.
Beringer, J., Moore, C. E., Cleverly, J., Campbell, D. I., Cleugh, H., De Kauwe, M. G., Kirschbaum, M. U., Griebel, A., Grover, S., and Huete, A.: Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network, Glob. Change Biol., 28, 3489–3514, 2022.
Bessenbacher, V., Seneviratne, S. I., and Gudmundsson, L.: CLIMFILL v0.9: a framework for intelligently gap filling Earth observations, Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, 2022.
Broich, M., Huete, A., Tulbure, M. G., Ma, X., Xin, Q., Paget, M., Restrepo-Coupe, N., Davies, K., Devadas, R., and Held, A.: Land surface phenological response to decadal climate variability across Australia using satellite remote sensing, Biogeosciences, 11, 5181–5198, https://doi.org/10.5194/bg-11-5181-2014, 2014.
Burton, C.: cbur24/AusENDVI: First release for publication, Zenodo [code], https://doi.org/10.5281/zenodo.13831836, 2024.
Burton, C., Rifai, S., Renzullo, L., and Van Dijk, A.: AusENDVI: A long-term NDVI dataset for Australia (0.2.0), Zenodo [data set], https://doi.org/10.5281/zenodo.10802703, 2024.
Byrne, G., Broomhall, M., Walsh, A. J., Thankappan, M., Hay, E., Li, F., McAtee, B., Garcia, R., Anstee, J., and Kerrisk, G.: Validating Digital Earth Australia NBART for the Landsat 9 Underfly of Landsat 8, Remote Sens., 16, 1233, https://doi.org/10.3390/rs16071233, 2024.
Canadell, J. G., Meyer, C., Cook, G. D., Dowdy, A., Briggs, P. R., Knauer, J., Pepler, A., and Haverd, V.: Multi-decadal increase of forest burned area in Australia is linked to climate change, Nat. Commun., 12, 6921, https://doi.org/10.1038/s41467-021-27225-4, 2021.
Cawley, G. C. and Talbot, N. L.: On over-fitting in model selection and subsequent selection bias in performance evaluation, J. Mach. Learn. Res., 11, 2079–2107, 2010.
Chambers, L. E., Altwegg, R., Barbraud, C., Barnard, P., Beaumont, L. J., Crawford, R. J., Durant, J. M., Hughes, L., Keatley, M. R., and Low, M.: Phenological changes in the southern hemisphere, PloS one, 8, e75514, https://doi.org/10.1371/journal.pone.0075514, 2013.
Chen, B.: Comparison of the Two Most Common Phenology Algorithms Imbedded in Land Surface Models, J. Geophys. Res.-Atmos., 127, e2022JD037167, https://doi.org/10.1029/2022JD037167, 2022.
Cortés, J., Mahecha, M. D., Reichstein, M., Myneni, R. B., Chen, C., and Brenning, A.: Where are global vegetation greening and browning trends significant?, Geophys. Res. Lett., 48, e2020GL091496, https://doi.org/10.1029/2020GL091496, 2021.
Donohue, R. J., McVICAR, T. R., and Roderick, M. L.: Climate-related trends in Australian vegetation cover as inferred from satellite observations, 1981–2006, Glob. Change Biol., 15, 1025–1039, 2009.
Donohue, R. J., Roderick, M. L., McVicar, T. R., and Farquhar, G. D.: Impact of CO2 fertilization on maximum foliage cover across the globe's warm, arid environments, Geophys. Res. Lett., 40, 3031–3035, 2013.
Dusenge, M. E., Duarte, A. G., and Way, D. A.: Plant carbon metabolism and climate change: elevated CO2 and temperature impacts on photosynthesis, photorespiration and respiration, New Phytologist, 221, 32–49, 2019.
Fensholt, R. and Proud, S. R.: Evaluation of earth observation based global long term vegetation trends – Comparing GIMMS and MODIS global NDVI time series, Remote Sens. Environ., 119, 131–147, 2012.
Franch, B., Vermote, E. F., Roger, J.-C., Murphy, E., Becker-Reshef, I., Justice, C., Claverie, M., Nagol, J., Csiszar, I., and Meyer, D.: A 30+ year AVHRR land surface reflectance climate data record and its application to wheat yield monitoring, Remote Sens., 9, 296, https://doi.org/10.3390/rs9030296, 2017.
Frankenberg, C., Yin, Y., Byrne, B., He, L., and Gentine, P.: Comment on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”, Science, 373, eabg2947, https://doi.org/10.1126/science.abg2947, 2021.
Gerber, F., de Jong, R., Schaepman, M. E., Schaepman-Strub, G., and Furrer, R.: Predicting missing values in spatio-temporal remote sensing data, IEEE T. Geosci. Remote, 56, 2841–2853, 2018.
Giglio, L. and Roy, D.: On the outstanding need for a long-term, multi-decadal, validated and quality assessed record of global burned area: Caution in the use of Advanced Very High Resolution Radiometer data, Sci. Remote Sens., 2, 100007, https://doi.org/10.1016/j.srs.2020.100007, 2020.
Gorman, A. and McGregor, J.: Some considerations for using AVHRR data in climatological studies: II. Instrument performance, Remote Sens., 15, 549–565, 1994.
Haverd, V., Raupach, M. R., Briggs, P. R., Canadell, J. G., Isaac, P., Pickett-Heaps, C., Roxburgh, S. H., van Gorsel, E., Viscarra Rossel, R. A., and Wang, Z.: Multiple observation types reduce uncertainty in Australia's terrestrial carbon and water cycles, Biogeosciences, 10, 2011–2040, https://doi.org/10.5194/bg-10-2011-2013, 2013.
Head, L., Adams, M., McGregor, H. V., and Toole, S.: Climate change and Australia, Wiley Interdisciplinary Reviews: Climate Change, 5, 175–197, 2014.
Hoffmann, A. A., Rymer, P. D., Byrne, M., Ruthrof, K. X., Whinam, J., McGeoch, M., Bergstrom, D. M., Guerin, G. R., Sparrow, B., and Joseph, L.: Impacts of recent climate change on terrestrial flora and fauna: Some emerging Australian examples, Austral Ecology, 44, 3–27, 2019.
Hope, P. K., Drosdowsky, W., and Nicholls, N.: Shifts in the synoptic systems influencing southwest Western Australia, Clim. Dynam., 26, 751–764, 2006.
Hopper, S. D. and Gioia, P.: The southwest Australian floristic region: evolution and conservation of a global hot spot of biodiversity, Annu. Rev. Ecol. Evol. Syst., 35, 623–650, 2004.
Huang, Z., Zhou, L., and Chi, Y.: Spring phenology rather than climate dominates the trends in peak of growing season in the Northern Hemisphere, Glob. Change Biol., 29, 4543–4555, 2023.
Hughes, L.: Climate change and Australia: key vulnerable regions, Reg. Environ. Change, 11, 189–195, 2011.
Hutchison, M., Kesteven, J., and Xu, T.: ANUClimate collection [data set], https://dapds00.nci.org.au/thredds/catalogs/gh70/catalog.html, 2014.
Krause, C., Dunn, B., Bishop-Taylor, R., Adams, C., Burton, C., Alger, M., Chua, S., Phillips, C., Newey, V., Kouzoubov, K., Leith, A., Ayers, D., and Hicks, A.: DEA Notebooks contributors, Digital Earth Australia notebooks and tools repository, Geoscience Australia, Canberra [code], https://doi.org/10.26186/145234, 2021.
Li, F., Jupp, D. L., Reddy, S., Lymburner, L., Mueller, N., Tan, P., and Islam, A.: An evaluation of the use of atmospheric and BRDF correction to standardize Landsat data, IEEE J. Sel. Top. Appl. Earth Obs., 3, 257–270, 2010.
Li, M., Cao, S., Zhu, Z., Wang, Z., Myneni, R. B., and Piao, S.: Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022, Earth Syst. Sci. Data, 15, 4181–4203, https://doi.org/10.5194/essd-15-4181-2023, 2023a.
Li, M., Cao, S., Zhu, Z., Wang, Z., Myneni, R. B., and Piao, S.: Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022 (V1.2) (V1.2), Zenodo [data set], https://doi.org/10.5281/zenodo.8253971, 2023b.
Liao, Z., Van Dijk, A. I., He, B., Larraondo, P. R., and Scarth, P. F.: Woody vegetation cover, height and biomass at 25-m resolution across Australia derived from multiple site, airborne and satellite observations, Int. J. Appl. Earth Obs., 93, 102209, https://doi.org/10.1016/j.jag.2020.102209, 2020.
Liu, Y., Wu, C., Wang, X., Jassal, R. S., and Gonsamo, A.: Impacts of global change on peak vegetation growth and its timing in terrestrial ecosystems of the continental US, Global Planet. Change, 207, 103657, https://doi.org/10.1016/j.gloplacha.2021.103657, 2021.
Lundberg, S.: A unified approach to interpreting model predictions, arXiv [preprint], arXiv:1705.07874, 2017.
Ma, X., Huete, A., Yu, Q., Coupe, N. R., Davies, K., Broich, M., Ratana, P., Beringer, J., Hutley, L. B., and Cleverly, J.: Spatial patterns and temporal dynamics in savanna vegetation phenology across the North Australian Tropical Transect, Remote Sens. Environ., 139, 97–115, 2013.
Ma, X., Huete, A., Moran, S., Ponce-Campos, G., and Eamus, D.: Abrupt shifts in phenology and vegetation productivity under climate extremes, J. Geophys. Res.-Biogeo., 120, 2036–2052, 2015.
Ma, X., Huete, A., and Tran, N. N.: Interaction of seasonal sun-angle and savanna phenology observed and modelled using MODIS, Remote Sens., 11, 1398, https://doi.org/10.3390/rs11121398, 2019.
Meyer, H. and Pebesma, E.: Machine learning-based global maps of ecological variables and the challenge of assessing them, Nat. Commun., 13, 1–4, 2022.
Moore, C. E., Brown, T., Keenan, T. F., Duursma, R. A., van Dijk, A. I. J. M., Beringer, J., Culvenor, D., Evans, B., Huete, A., Hutley, L. B., Maier, S., Restrepo-Coupe, N., Sonnentag, O., Specht, A., Taylor, J. R., van Gorsel, E., and Liddell, M. J.: Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography, Biogeosciences, 13, 5085–5102, https://doi.org/10.5194/bg-13-5085-2016, 2016.
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A., and Kent, J.: Biodiversity hotspots for conservation priorities, Nature, 403, 853–858, 2000.
O'Donnell, J., Gallagher, R. V., Wilson, P. D., Downey, P. O., Hughes, L., and Leishman, M. R.: Invasion hotspots for non-native plants in a ustralia under current and future climates, Glob. Change Biol., 18, 617–629, 2012.
Park, T., Chen, C., Macias-Fauria, M., Tømmervik, H., Choi, S., Winkler, A., Bhatt, U. S., Walker, D. A., Piao, S., and Brovkin, V.: Changes in timing of seasonal peak photosynthetic activity in northern ecosystems, Glob. Change Biol., 25, 2382–2395, 2019.
Peters, J. M., López, R., Nolf, M., Hutley, L. B., Wardlaw, T., Cernusak, L. A., and Choat, B.: Living on the edge: A continental-scale assessment of forest vulnerability to drought, Glob. Change Biol., 27, 3620–3641, 2021.
Piao, S., Liu, Q., Chen, A., Janssens, I. A., Fu, Y., Dai, J., Liu, L., Lian, X., Shen, M., and Zhu, X.: Plant phenology and global climate change: Current progresses and challenges, Glob. Change Biol., 25, 1922–1940, 2019.
Pinzon, J. E. and Tucker, C. J.: A non-stationary 1981–2012 AVHRR NDVI3g time series, Remote Sens., 6, 6929–6960, 2014.
Pitman, A., Narisma, G., Pielke Sr, R., and Holbrook, N.: Impact of land cover change on the climate of southwest Western Australia, J. Geophys. Res.-Atmos., 109, 2004.
Poulter, B., Frank, D., Ciais, P., Myneni, R. B., Andela, N., Bi, J., Broquet, G., Canadell, J. G., Chevallier, F., and Liu, Y. Y.: Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle, Nature, 509, 600–603, 2014.
Privette, J., Fowler, C., Wick, G., Baldwin, D., and Emery, W.: Effects of orbital drift on AVHRR products: normalized difference vegetation index and sea surface temperature, Remote Sens. Environ., 53, 164–177, 1995.
Rifai, S. W., De Kauwe, M. G., Ukkola, A. M., Cernusak, L. A., Meir, P., Medlyn, B. E., and Pitman, A. J.: Thirty-eight years of CO2 fertilization has outpaced growing aridity to drive greening of Australian woody ecosystems, Biogeosciences, 19, 491–515, https://doi.org/10.5194/bg-19-491-2022, 2022.
Schaaf, C. and Wang, Z.: MCD43A4 MODIS/Terra+Aqua BRDF/Albedo Nadir BRDF Adjusted RefDaily L3 Global – 500 m V006, NASA EOSDIS Land Processes DAAC [data set], https://doi.org/10.5067/MODIS/MCD43A4.006, 2015.
Shen, H., Li, X., Cheng, Q., Zeng, C., Yang, G., Li, H., and Zhang, L.: Missing information reconstruction of remote sensing data: A technical review, IEEE Geosci. Remote Sens. Mag., 3, 61–85, 2015.
Steffen, W., Sims, J., Walcott, J., and Laughlin, G.: Australian agriculture: coping with dangerous climate change, Reg. Environ. Change, 11, 205–214, 2011.
Tian, F., Fensholt, R., Verbesselt, J., Grogan, K., Horion, S., and Wang, Y.: Evaluating temporal consistency of long-term global NDVI datasets for trend analysis, Remote Sens. Environ., 163, 326–340, 2015.
Tian, J. and Luo, X.: Conflicting changes of vegetation greenness interannual variability on half of the Global vegetated surface, Earth's Future, 12, e2023EF004119, https://doi.org/10.1029/2023EF004119, 2024.
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W., Mahoney, R., Vermote, E. F., and El Saleous, N.: An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote Sens., 26, 4485–4498, 2005.
Ukkola, A. M., Prentice, I. C., Keenan, T. F., Van Dijk, A. I., Viney, N. R., Myneni, R. B., and Bi, J.: Reduced streamflow in water-stressed climates consistent with CO2 effects on vegetation, Nat. Clim. Change, 6, 75–78, 2016.
Vermote, E. F., El Saleous, N. Z., and Justice, C. O.: Atmospheric correction of MODIS data in the visible to middle infrared: first results, Remote Sens. Environ., 83, 97–111, 2002.
Wang, S., Zhang, Y., Ju, W., Chen, J. M., Cescatti, A., Sardans, J., Janssens, I. A., Wu, M., Berry, J. A., and Campbell, J. E.: Response to Comments on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”, Science, 373, eabg7484, https://doi.org/10.1126/science.abg7484, 2021.
Wang, Z., Wang, H., Wang, T., Wang, L., Liu, X., Zheng, K., and Huang, X.: Large discrepancies of global greening: Indication of multi-source remote sensing data, Glob. Ecol. Conserv., 34, e02016, https://doi.org/10.1016/j.gecco.2022.e02016, 2022.
Xie, Q., Moore, C. E., Cleverly, J., Hall, C. C., Ding, Y., Ma, X., Leigh, A., and Huete, A.: Land surface phenology indicators retrieved across diverse ecosystems using a modified threshold algorithm, Ecol. Ind., 147, 110000, https://doi.org/10.1016/j.ecolind.2023.110000, 2023.
Ye, W., van Dijk, A. I., Huete, A., and Yebra, M.: Global trends in vegetation seasonality in the GIMMS NDVI3g and their robustness, Int. J. Appl. Earth Obs., 94, 102238, https://doi.org/10.1016/j.jag.2020.102238, 2021.
Zeng, C., Shen, H., Zhong, M., Zhang, L., and Wu, P.: Reconstructing MODIS LST based on multitemporal classification and robust regression, IEEE Geosci. Remote Sens. Lett., 12, 512–516, 2014.
Short summary
Understanding vegetation response to environmental change requires accurate, long-term data on vegetation condition (VC). We evaluated existing satellite VC datasets over Australia and found them lacking, so we developed a new VC dataset for Australia, AusENDVI. It can be used for studying Australia's changing vegetation dynamics and downstream impacts on the carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change.
Understanding vegetation response to environmental change requires accurate, long-term data on...
Altmetrics
Final-revised paper
Preprint