Articles | Volume 15, issue 2
https://doi.org/10.5194/essd-15-821-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-15-821-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Feb 2023
Data description paper |
| 14 Feb 2023
A 250 m annual alpine grassland AGB dataset over the Qinghai–Tibet Plateau (2000–2019) in China based on in situ measurements, UAV photos, and MODIS data
Huifang Zhang
Institute of Fragile Eco-environment, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang
West Road, Lanzhou 730000, China
Zhonggang Tang
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Binyao Wang
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Hongcheng Kan
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Yi Sun
Institute of Fragile Eco-environment, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Yu Qin
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang
West Road, Lanzhou 730000, China
Baoping Meng
Institute of Fragile Eco-environment, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Meng Li
Institute of Fragile Eco-environment, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Jianjun Chen
College of Geomatics and Geoinformation, Guilin University of
Technology, 12 Jiangan Road, Guilin 541004, China
Yanyan Lv
Institute of Fragile Eco-environment, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Jianguo Zhang
Institute of Fragile Eco-environment, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
Shuli Niu
Key Laboratory of Ecosystem Network Observation and Modeling,
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
Institute of Fragile Eco-environment, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
School of Geographic Science, Nantong University, 999 Tongjing Road, Nantong, Jiangsu 226007, China
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Junxiao Pan, Jinsong Wang, Dashuan Tian, Ruiyang Zhang, Yang Li, Lei Song, Jiaming Yang, Chunxue Wei, and Shuli Niu
SOIL, 8, 687–698, https://doi.org/10.5194/soil-8-687-2022, https://doi.org/10.5194/soil-8-687-2022, 2022
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We found that climatic, edaphic, plant and microbial variables jointly affect soil inorganic carbon (SIC) stock in Tibetan grasslands, and biotic factors have a larger contribution than abiotic factors to the variation in SIC stock. The effects of microbial and plant variables on SIC stock weakened with soil depth, while the effects of edaphic variables strengthened. The contrasting responses and drivers of SIC stock highlight differential mechanisms underlying SIC preservation with soil depth.
Shuang Ma, Lifen Jiang, Rachel M. Wilson, Jeff P. Chanton, Scott Bridgham, Shuli Niu, Colleen M. Iversen, Avni Malhotra, Jiang Jiang, Xingjie Lu, Yuanyuan Huang, Jason Keller, Xiaofeng Xu, Daniel M. Ricciuto, Paul J. Hanson, and Yiqi Luo
Biogeosciences, 19, 2245–2262, https://doi.org/10.5194/bg-19-2245-2022, https://doi.org/10.5194/bg-19-2245-2022, 2022
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The relative ratio of wetland methane (CH4) emission pathways determines how much CH4 is oxidized before leaving the soil. We found an ebullition modeling approach that has a better performance in deep layer pore water CH4 concentration. We suggest using this approach in land surface models to accurately represent CH4 emission dynamics and response to climate change. Our results also highlight that both CH4 flux and belowground concentration data are important to constrain model parameters.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Erqian Cui, Chenyu Bian, Yiqi Luo, Shuli Niu, Yingping Wang, and Jianyang Xia
Biogeosciences, 17, 6237–6246, https://doi.org/10.5194/bg-17-6237-2020, https://doi.org/10.5194/bg-17-6237-2020, 2020
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Mean annual net ecosystem productivity (NEP) is related to the magnitude of the carbon sink of a specific ecosystem, while its inter-annual variation (IAVNEP) characterizes the stability of such a carbon sink. Thus, a better understanding of the co-varying NEP and IAVNEP is critical for locating the major and stable carbon sinks on land. Based on daily NEP observations from eddy-covariance sites, we found local indicators for the spatially varying NEP and IAVNEP, respectively.
X. C. Lin, J. J. Chen, and P. Q. Lou
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W10, 747–753, https://doi.org/10.5194/isprs-archives-XLII-3-W10-747-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W10-747-2020, 2020
J. Liu, J. J. Chen, X. N. Zhao, and H. Z. Zhang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W10, 755–762, https://doi.org/10.5194/isprs-archives-XLII-3-W10-755-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W10-755-2020, 2020
H. Z. Zhang, J. J. Chen, X. N. Zhao, and J. Liu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W10, 49–55, https://doi.org/10.5194/isprs-archives-XLII-3-W10-49-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W10-49-2020, 2020
Q. T. Qin and J. J. Chen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W10, 479–485, https://doi.org/10.5194/isprs-archives-XLII-3-W10-479-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W10-479-2020, 2020
M. H. Huang and J. J. Chen
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3-W10, 705–712, https://doi.org/10.5194/isprs-archives-XLII-3-W10-705-2020, https://doi.org/10.5194/isprs-archives-XLII-3-W10-705-2020, 2020
Yu Qin, Shuhua Yi, Yongjian Ding, Wei Zhang, Yan Qin, Jianjun Chen, and Zhiwei Wang
Biogeosciences, 16, 1097–1109, https://doi.org/10.5194/bg-16-1097-2019, https://doi.org/10.5194/bg-16-1097-2019, 2019
Shuhua Yi, Yujie He, Xinlei Guo, Jianjun Chen, Qingbai Wu, Yu Qin, and Yongjian Ding
The Cryosphere, 12, 3067–3083, https://doi.org/10.5194/tc-12-3067-2018, https://doi.org/10.5194/tc-12-3067-2018, 2018
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Coarse-fragment soil on the Qinghai–Tibetan Plateau has different thermal and hydrological properties to soils commonly used in modeling studies. We took soil samples and measured their physical properties in a laboratory, which were used in a model to simulate their effects on permafrost dynamics. Model errors were reduced using the measured properties, in which porosity played an dominant role.
Lihui Luo, Zhongqiong Zhang, Wei Ma, Shuhua Yi, and Yanli Zhuang
Geosci. Model Dev., 11, 2475–2491, https://doi.org/10.5194/gmd-11-2475-2018, https://doi.org/10.5194/gmd-11-2475-2018, 2018
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Based on the current situation of permafrost modeling in the Qinghai–Tibet Plateau (QTP), a software PIC was developed to evaluate the temporal–spatial change trends of permafrost, which allows us to automatically compute permafrost indices with daily weather and atmospheric forcing datasets. The main features include computing, visualization, and statistics. The software will serve engineering applications and can be used to assess the impact of climate change on permafrost over the QTP.
Bing Song, Jian Sun, Qingping Zhou, Ning Zong, Linghao Li, and Shuli Niu
Biogeosciences, 14, 3947–3956, https://doi.org/10.5194/bg-14-3947-2017, https://doi.org/10.5194/bg-14-3947-2017, 2017
Yiqi Luo, Zheng Shi, Xingjie Lu, Jianyang Xia, Junyi Liang, Jiang Jiang, Ying Wang, Matthew J. Smith, Lifen Jiang, Anders Ahlström, Benito Chen, Oleksandra Hararuk, Alan Hastings, Forrest Hoffman, Belinda Medlyn, Shuli Niu, Martin Rasmussen, Katherine Todd-Brown, and Ying-Ping Wang
Biogeosciences, 14, 145–161, https://doi.org/10.5194/bg-14-145-2017, https://doi.org/10.5194/bg-14-145-2017, 2017
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Climate change is strongly regulated by land carbon cycle. However, we lack the ability to predict future land carbon sequestration. Here, we develop a novel framework for understanding what determines the direction and rate of future change in land carbon storage. The framework offers a suite of new approaches to revolutionize land carbon model evaluation and improvement.
Shuhua Yi, Jianjun Chen, Yu Qin, and Gaowei Xu
Biogeosciences, 13, 6273–6284, https://doi.org/10.5194/bg-13-6273-2016, https://doi.org/10.5194/bg-13-6273-2016, 2016
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Plateau pika is common on the Qinghai-Tibet Plateau (QTP). Since pika dig burrows and graze on grassland to compete with yaks and sheep, they are believed to be a pest. They have been killed by humans since the 1950s. However, there are no serious studies that quantitatively evaluate the grazing and excavating effects of pika on grassland. With the advancement of UAV technology, we did a pilot study to evaluate the grazing and burying effects of pika.
S. Yi, K. Wischnewski, M. Langer, S. Muster, and J. Boike
Geosci. Model Dev., 7, 1671–1689, https://doi.org/10.5194/gmd-7-1671-2014, https://doi.org/10.5194/gmd-7-1671-2014, 2014
S. Yi, J. Chen, Q. Wu, and Y. Ding
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-4703-2013, https://doi.org/10.5194/tcd-7-4703-2013, 2013
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Economic statistics are frequently produced at an administrative level that lacks detail to examine development patterns and the exposure to natural hazards. This paper disaggregates national and subnational administrative statistics of agricultural GDP into a global dataset at the local level using satellite-derived indicators. As an illustration, the paper estimates that the exposure of areas with extreme drought to agricultural GDP is USD 432 billion, where nearly 1.2 billion people live.
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We present a new hierarchical fuel classification system with a total of 85 fuels that is useful for preventing fire risk at different spatial scales. Based on this, we developed a European fuel map (1 km resolution) using land cover datasets, biogeographic datasets, and bioclimatic modelling. We validated the map by comparing it to high-resolution data, obtaining high overall accuracy. Finally, we developed a crosswalk for standard fuel models as a first assignment of fuel parameters.
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Earth Syst. Sci. Data, 15, 791–808, https://doi.org/10.5194/essd-15-791-2023, https://doi.org/10.5194/essd-15-791-2023, 2023
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Earth Syst. Sci. Data, 15, 681–695, https://doi.org/10.5194/essd-15-681-2023, https://doi.org/10.5194/essd-15-681-2023, 2023
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Earth Syst. Sci. Data, 15, 133–153, https://doi.org/10.5194/essd-15-133-2023, https://doi.org/10.5194/essd-15-133-2023, 2023
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Earth Syst. Sci. Data, 15, 113–131, https://doi.org/10.5194/essd-15-113-2023, https://doi.org/10.5194/essd-15-113-2023, 2023
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Furong Li, Marie-José Gaillard, Xianyong Cao, Ulrike Herzschuh, Shinya Sugita, Jian Ni, Yan Zhao, Chengbang An, Xiaozhong Huang, Yu Li, Hongyan Liu, Aizhi Sun, and Yifeng Yao
Earth Syst. Sci. Data, 15, 95–112, https://doi.org/10.5194/essd-15-95-2023, https://doi.org/10.5194/essd-15-95-2023, 2023
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The objective of this study is present the first gridded and temporally continuous quantitative plant-cover reconstruction for temperate and northern subtropical China over the last 12 millennia. The reconstructions are based on 94 pollen records and include estimates for 27 plant taxa, 10 plant functional types, and 3 land-cover types. The dataset is suitable for palaeoclimate modelling and the evaluation of simulated past vegetation cover and anthropogenic land-cover change from models.
Jose Luis Gómez-Dans, Philip Edward Lewis, Feng Yin, Kofi Asare, Patrick Lamptey, Kenneth Kobina Yedu Aidoo, Dilys Sefakor MacCarthy, Hongyuan Ma, Qingling Wu, Martin Addi, Stephen Aboagye-Ntow, Caroline Edinam Doe, Rahaman Alhassan, Isaac Kankam-Boadu, Jianxi Huang, and Xuecao Li
Earth Syst. Sci. Data, 14, 5387–5410, https://doi.org/10.5194/essd-14-5387-2022, https://doi.org/10.5194/essd-14-5387-2022, 2022
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We provide a data set to support mapping croplands in smallholder landscapes in Ghana. The data set contains information on crop location on three agroecological zones for 2 years, temporal series of measurements of leaf area index and leaf chlorophyll concentration for maize canopies and yield. We demonstrate the use of these data to validate cropland masks, create a maize mask using satellite data and explore the relationship between satellite measurements and yield.
Chunling Sun, Hong Zhang, Lu Xu, Ji Ge, Jingling Jiang, Lijun Zuo, and Chao Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-392, https://doi.org/10.5194/essd-2022-392, 2022
Revised manuscript accepted for ESSD
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Over 90 % of the world’s rice is produced in the Asia-Pacific Region. In this study, a rice mapping method based on Sentinel-1 synthetic aperture radar data for mainland Southeast Asia is proposed. A combination of spatio-temporal features with strong generalization is selected and input into the U-Net model to obtain a 20-meter resolution rice map of mainland Southeast Asia in 2019. The accuracy of the proposed method is 92.20 %. The rice map is concordant with statistics and other rice maps.
Zhen Yu, Jing Liu, and Giri Kattel
Earth Syst. Sci. Data, 14, 5179–5194, https://doi.org/10.5194/essd-14-5179-2022, https://doi.org/10.5194/essd-14-5179-2022, 2022
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We developed a 5 km annual nitrogen (N) fertilizer use dataset in China, covering the period from 1952 to 2018. We found that previous FAO-data-based N fertilizer products overestimated the N use in low, but underestimated in high, cropland coverage areas in China. The new dataset has improved the spatial distribution and corrected the existing biases, which is beneficial for biogeochemical cycle simulations in China, such as the assessment of greenhouse gas emissions and food production.
Femke van Geffen, Birgit Heim, Frederic Brieger, Rongwei Geng, Iuliia A. Shevtsova, Luise Schulte, Simone M. Stuenzi, Nadine Bernhardt, Elena I. Troeva, Luidmila A. Pestryakova, Evgenii S. Zakharov, Bringfried Pflug, Ulrike Herzschuh, and Stefan Kruse
Earth Syst. Sci. Data, 14, 4967–4994, https://doi.org/10.5194/essd-14-4967-2022, https://doi.org/10.5194/essd-14-4967-2022, 2022
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SiDroForest is an attempt to remedy data scarcity regarding vegetation data in the circumpolar region, whilst providing adjusted and labeled data for machine learning and upscaling practices. SiDroForest contains four datasets that include SfM point clouds, individually labeled trees, synthetic tree crowns and labeled Sentinel-2 patches that provide insights into the vegetation composition and forest structure of two important vegetation transition zones in Siberia, Russia.
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
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Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Raphaël d'Andrimont, Momchil Yordanov, Laura Martinez-Sanchez, Peter Haub, Oliver Buck, Carsten Haub, Beatrice Eiselt, and Marijn van der Velde
Earth Syst. Sci. Data, 14, 4463–4472, https://doi.org/10.5194/essd-14-4463-2022, https://doi.org/10.5194/essd-14-4463-2022, 2022
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Between 2006 and 2018, 875 661 LUCAS cover (i.e. close-up) photos were taken over a systematic sample of the European Union. This geo-located photo dataset has been curated and is being made available along with the surveyed label data, including land cover and plant species.
Han Su, Bárbara Willaarts, Diana Luna-Gonzalez, Maarten S. Krol, and Rick J. Hogeboom
Earth Syst. Sci. Data, 14, 4397–4418, https://doi.org/10.5194/essd-14-4397-2022, https://doi.org/10.5194/essd-14-4397-2022, 2022
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There are over 608 million farms around the world but they are not the same. We developed high spatial resolution maps showing where small and large farms were located and which crops were planted for 56 countries. We checked the reliability and have the confidence to use them for the country level and global studies. Our maps will help more studies to easily measure how agriculture policies, water availability, and climate change affect small and large farms.
Kandice L. Harper, Celine Lamarche, Andrew Hartley, Philippe Peylin, Catherine Ottlé, Vladislav Bastrikov, Rodrigo San Martín, Sylvia I. Bohnenstengel, Grit Kirches, Martin Boettcher, Roman Shevchuk, Carsten Brockmann, and Pierre Defourny
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-296, https://doi.org/10.5194/essd-2022-296, 2022
Revised manuscript accepted for ESSD
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We built a spatially explicit annual PFT dataset for 1992–2020 exhibiting intraclass spatial variability in PFT fractional cover at 300 m. For each year, 14 maps of PFTs percentage cover are produced: bare soil, water, permanent snow/ice, built, managed grasses, natural grasses, and trees and shrubs each split into leaf type and seasonality. ORCHIDEE and JULES model simulations indicate significant differences in simulated carbon, water, and energy fluxes in some regions using this new PFT set.
Zhen Qian, Min Chen, Yue Yang, Teng Zhong, Fan Zhang, Rui Zhu, Kai Zhang, Zhixin Zhang, Zhuo Sun, Peilong Ma, Guonian Lü, Yu Ye, and Jinyue Yan
Earth Syst. Sci. Data, 14, 4057–4076, https://doi.org/10.5194/essd-14-4057-2022, https://doi.org/10.5194/essd-14-4057-2022, 2022
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Roadside noise barriers (RNBs) are important urban infrastructures to ensure a city is liveable. This study provides the first reliable and nationwide vectorized RNB dataset with street view imagery in China. The generated RNB dataset is evaluated in terms of two aspects, i.e., the detection accuracy and the completeness and positional accuracy. The method is based on a developed geospatial artificial intelligence framework.
Matthias Demuzere, Jonas Kittner, Alberto Martilli, Gerald Mills, Christian Moede, Iain D. Stewart, Jasper van Vliet, and Benjamin Bechtel
Earth Syst. Sci. Data, 14, 3835–3873, https://doi.org/10.5194/essd-14-3835-2022, https://doi.org/10.5194/essd-14-3835-2022, 2022
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Because urban areas are key contributors to climate change but are also susceptible to multiple hazards, one needs spatially detailed information on urban landscapes to support environmental services. This global local climate zone map describes this much-needed intra-urban heterogeneity across the whole surface of the earth in a universal language and can serve as a basic infrastructure to study e.g. environmental hazards, energy demand, and climate adaptation and mitigation solutions.
Xin Huang, Jie Yang, Wenrui Wang, and Zhengrong Liu
Earth Syst. Sci. Data, 14, 3649–3672, https://doi.org/10.5194/essd-14-3649-2022, https://doi.org/10.5194/essd-14-3649-2022, 2022
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Using more than 2.7 million Sentinel images, we proposed a global ISA mapping method and produced the 10-m global ISA dataset (GISA-10m), with overall accuracy exceeding 86 %. The inter-comparison between different global ISA datasets showed the superiority of our results. The ISA distribution at urban and rural was discussed and compared. For the first time, courtesy of the high spatial resolution, the global road ISA was further identified, and its distribution was discussed.
Charles H. Simpson, Oscar Brousse, Nahid Mohajeri, Michael Davies, and Clare Heaviside
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-259, https://doi.org/10.5194/essd-2022-259, 2022
Revised manuscript accepted for ESSD
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Adding plants to the roofs of buildings can reduce both indoor and outdoor temperatures, so can reduce urban overheating which is expected to increase due to climate change and urban growth. To better understand the effect this has on the urban environment, we need data on how many buildings have green roofs already. We used a computer vision model to find green roofs in aerial imagery in London, producing a dataset identifying what buildings have green roofs and improving on previous methods.
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Short summary
The accuracy of regional grassland aboveground biomass (AGB) is always limited by insufficient ground measurements and large spatial gaps with satellite pixels. This paper used more than 37 000 UAV images as bridges to successfully obtain AGB values matching MODIS pixels. The new AGB estimation model had good robustness, with an average R2 of 0.83 and RMSE of 34.13 g m2. Our new dataset provides important input parameters for understanding the Qinghai–Tibet Plateau during global climate change.
The accuracy of regional grassland aboveground biomass (AGB) is always limited by insufficient...
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