Articles | Volume 16, issue 1
https://doi.org/10.5194/essd-16-161-2024
© 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-16-161-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A coarse pixel-scale ground “truth” dataset based on global in situ site measurements to support validation and bias correction of satellite surface albedo products
Fei Pan
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Xiaodan Wu
CORRESPONDING AUTHOR
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610031, China
Qicheng Zeng
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Rongqi Tang
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Jingping Wang
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Xingwen Lin
College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China
Dongqin You
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Jianguang Wen
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Qing Xiao
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
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Yibo Sun, Bilige Sude, Xingwen Lin, Bing Geng, Bo Liu, Shengnan Ji, Junping Jing, Zhiping Zhu, Ziwei Xu, Shaomin Liu, and Zhanjun Quan
Atmos. Meas. Tech., 16, 5659–5679, https://doi.org/10.5194/amt-16-5659-2023, https://doi.org/10.5194/amt-16-5659-2023, 2023
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Unoccupied aerial vehicles (UAVs) provide a versatile platform for eddy covariance (EC) flux measurements at regional scales with low cost, transport, and infrastructural requirements. This study evaluates the measurement performance in the wind field and turbulent flux of a UAV-based EC system based on the data from a set of calibration flights and standard operational flights and concludes that the system can measure the georeferenced wind vector and turbulent flux with sufficient precision.
Rongqi Tang, Xiaodan Wu, Jingping Wang, Dujuan Ma, Qicheng Zeng, Jianguang Wen, and Qing Xiao
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-282, https://doi.org/10.5194/amt-2022-282, 2022
Publication in AMT not foreseen
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The vertical distribution characteristics of ozone in China have not been fully understood. This study first identified the vertical sensitivity of AIRS in detecting trends and verified the sensitivity in the near ground using in-situ measurements. Then a consistent ozone datasets dating back to the 1970s was constructed. we found that the spatiotemporal variation of ozone in the stratosphere shows a strong dependence on altitudes, and opposite results can be found at different altitudes.
Xiaodan Wu, Kathrin Naegeli, Valentina Premier, Carlo Marin, Dujuan Ma, Jingping Wang, and Stefan Wunderle
The Cryosphere, 15, 4261–4279, https://doi.org/10.5194/tc-15-4261-2021, https://doi.org/10.5194/tc-15-4261-2021, 2021
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We performed a comprehensive accuracy assessment of an Advanced Very High Resolution Radiometer global area coverage snow-cover extent time series dataset for the Hindu Kush Himalayan (HKH) region. The sensor-to-sensor consistency, the accuracy related to snow depth, elevations, land-cover types, slope, and aspects, and topographical variability were also explored. Our analysis shows an overall accuracy of 94 % in comparison with in situ station data, which is the same with MOD10A1 V006.
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Domain: ESSD – Land | Subject: Energy and Emissions
Meteorological, snow and soil data, CO2, water and energy fluxes from a low-Arctic valley of Northern Quebec
Systematically tracking the hourly progression of large wildfires using GOES satellite observations
GloCAB: global cropland burned area from mid-2002 to 2020
Greenhouse gas emissions and their trends over the last 3 decades across Africa
Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5)
Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution
An adapted hourly Himawari-8 fire product for China: principle, methodology and verification
A GeoNEX-based high-spatiotemporal-resolution product of land surface downward shortwave radiation and photosynthetically active radiation
Mapping photovoltaic power plants in China using Landsat, random forest, and Google Earth Engine
Florent Domine, Denis Sarrazin, Daniel F. Nadeau, Georg Lackner, and Maria Belke-Brea
Earth Syst. Sci. Data, 16, 1523–1541, https://doi.org/10.5194/essd-16-1523-2024, https://doi.org/10.5194/essd-16-1523-2024, 2024
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The forest–tundra ecotone is the transition region between the boreal forest and Arctic tundra. It spans over 13 000 km across the Arctic and is evolving rapidly because of climate change. We provide extensive data sets of two sites 850 m apart, one in tundra and one in forest in this ecotone for use in various models. Data include meteorological and flux data and unique snow and soil physics data.
Tianjia Liu, James T. Randerson, Yang Chen, Douglas C. Morton, Elizabeth B. Wiggins, Padhraic Smyth, Efi Foufoula-Georgiou, Roy Nadler, and Omer Nevo
Earth Syst. Sci. Data, 16, 1395–1424, https://doi.org/10.5194/essd-16-1395-2024, https://doi.org/10.5194/essd-16-1395-2024, 2024
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To improve our understanding of extreme wildfire behavior, we use geostationary satellite data to develop the GOFER algorithm and track the hourly fire progression of large wildfires. GOFER fills a key temporal gap present in other fire tracking products that rely on low-Earth-orbit imagery and reveals considerable variability in fire spread rates on diurnal timescales. We create a product of hourly fire perimeters, active-fire lines, and fire spread rates for 28 fires in California.
Joanne V. Hall, Fernanda Argueta, Maria Zubkova, Yang Chen, James T. Randerson, and Louis Giglio
Earth Syst. Sci. Data, 16, 867–885, https://doi.org/10.5194/essd-16-867-2024, https://doi.org/10.5194/essd-16-867-2024, 2024
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Crop-residue burning is a widespread practice often occurring close to population centers. Its recurrent nature requires accurate mapping of the area burned – a key input into air quality models. Unlike larger fires, crop fires require a specific burned area (BA) methodology, which to date has been ignored in global BA datasets. Our global cropland-focused BA product found a significant increase in global cropland BA (81 Mha annual average) compared to the widely used MCD64A1 (32 Mha).
Mounia Mostefaoui, Philippe Ciais, Matthew J. McGrath, Philippe Peylin, Prabir K. Patra, and Yolandi Ernst
Earth Syst. Sci. Data, 16, 245–275, https://doi.org/10.5194/essd-16-245-2024, https://doi.org/10.5194/essd-16-245-2024, 2024
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Our aim is to assess African anthropogenic greenhouse gas emissions and removals by using different data products, including inventories and process-based models, and to compare their relative merits with inversion data coming from satellites. We show a good match among the various estimates in terms of overall trends at a regional level and on a decadal basis, but large differences exist even among similar data types, which is a limit to the possibility of verification of country-reported data.
Yang Chen, Joanne Hall, Dave van Wees, Niels Andela, Stijn Hantson, Louis Giglio, Guido R. van der Werf, Douglas C. Morton, and James T. Randerson
Earth Syst. Sci. Data, 15, 5227–5259, https://doi.org/10.5194/essd-15-5227-2023, https://doi.org/10.5194/essd-15-5227-2023, 2023
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Using multiple sets of remotely sensed data, we created a dataset of monthly global burned area from 1997 to 2020. The estimated annual global burned area is 774 million hectares, significantly higher than previous estimates. Burned area declined by 1.21% per year due to extensive fire loss in savanna, grassland, and cropland ecosystems. This study enhances our understanding of the impact of fire on the carbon cycle and climate system, and may improve the predictions of future fire changes.
Mark Omara, Ritesh Gautam, Madeleine A. O'Brien, Anthony Himmelberger, Alex Franco, Kelsey Meisenhelder, Grace Hauser, David R. Lyon, Apisada Chulakadabba, Christopher Chan Miller, Jonathan Franklin, Steven C. Wofsy, and Steven P. Hamburg
Earth Syst. Sci. Data, 15, 3761–3790, https://doi.org/10.5194/essd-15-3761-2023, https://doi.org/10.5194/essd-15-3761-2023, 2023
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We acquire, integrate, and analyze ~ 6 million geospatial oil and gas infrastructure data records based on information available in the public domain and develop an open-access global database including all the major oil and gas facility types that are important sources of methane emissions. This work helps fulfill a crucial geospatial data need, in support of the assessment, attribution, and mitigation of global oil and gas methane emissions at high resolution.
Jie Chen, Qiancheng Lv, Shuang Wu, Yelu Zeng, Manchun Li, Ziyue Chen, Enze Zhou, Wei Zheng, Cheng Liu, Xiao Chen, Jing Yang, and Bingbo Gao
Earth Syst. Sci. Data, 15, 1911–1931, https://doi.org/10.5194/essd-15-1911-2023, https://doi.org/10.5194/essd-15-1911-2023, 2023
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The Himawari-8 fire product is the mainstream fire product with the highest temporal resolution, yet it presents large uncertainties and is not suitable for reliable real-time fire monitoring in China. To address this issue, we proposed an adaptive hourly NSMC (National Satellite Meteorological Center) Himawari-8 fire product for China; the overall accuracy increased from 54 % (original Himawari product) to 80 %. This product can largely enhance real-time fire monitoring and relevant research.
Ruohan Li, Dongdong Wang, Weile Wang, and Ramakrishna Nemani
Earth Syst. Sci. Data, 15, 1419–1436, https://doi.org/10.5194/essd-15-1419-2023, https://doi.org/10.5194/essd-15-1419-2023, 2023
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There has been an increasing need for high-spatiotemporal-resolution surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) data for ecological, hydrological, carbon, and solar photovoltaic research. This study produced a new 1 km hourly product of land surface DSR and PAR from the enhanced GeoNEX new-generation geostationary data. Our validation indicated that the GeoNEX DSR and PAR product has a higher accuracy than other existing products.
Xunhe Zhang, Ming Xu, Shujian Wang, Yongkai Huang, and Zunyi Xie
Earth Syst. Sci. Data, 14, 3743–3755, https://doi.org/10.5194/essd-14-3743-2022, https://doi.org/10.5194/essd-14-3743-2022, 2022
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Photovoltaic (PV) power plants have been increasingly built across the world to mitigate climate change. A map of the PV power plants is important for policy management and environmental assessment. We established a map of PV power plants in China by 2020, covering a total area of 2917 km2. Based on the derived map, we found that most PV power plants were situated on cropland. In addition, the installation of PV power plants has generally decreased the vegetation cover.
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Short summary
To effectively tackle the challenges posed by spatial-scale differences and spatial heterogeneity, this paper presents a distinctive coarse pixel-scale ground “truth" dataset by upscaling sparsely distributed in situ measurements. This dataset is a valuable resource for validating and correcting global surface albedo products, enhancing reference data accuracy by 6.04 %. Remarkably, it substantially enhances 17.09 % in regions with strong spatial heterogeneity.
To effectively tackle the challenges posed by spatial-scale differences and spatial...
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