Articles | Volume 26, issue 8
https://doi.org/10.5194/hess-26-1937-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-1937-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and validation of a new MODIS snow-cover-extent product over China
Xiaohua Hao
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Zhaojun Zheng
National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
Key Laboratory of Radiometric Calibration and Validation for Environmental satellites, China Meteorological Administration, Beijing 100081, China
Xingliang Sun
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Engineering Laboratory for National Geographic State Monitoring, Lanzhou Jiaotong University, Lanzhou 730070, China
Wenzheng Ji
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Hongyu Zhao
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Jian Wang
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Hongyi Li
Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Xiaoyan Wang
College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
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- Development and Evaluation of a Cloud-Gap-Filled MODIS Normalized Difference Snow Index Product over High Mountain Asia G. Deng et al. 10.3390/rs16010192
- Comparison of Three Different Random Forest Approaches to Retrieve Daily High-Resolution Snow Cover Maps from MODIS and Sentinel-2 in a Mountain Area, Gran Paradiso National Park (NW Alps) C. Richiardi et al. 10.3390/rs15020343
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- Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Model and Optical Satellite Data M. Wang & N. Oppelt 10.3390/rs15205016
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- Random Forest-Based Snow Cover Mapping in China Using Fengyun-3B VIRR Data Y. Xie et al. 10.1007/s13351-023-3003-z
- Spatiotemporal variation of snow cover days and influencing factors on the Loess Plateau during 2000–2019 S. Li et al. 10.1016/j.jhydrol.2023.130419
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- Multi-year mapping of flood autumn irrigation extent and timing in harvested croplands of arid irrigation district X. Qian et al. 10.1080/15481603.2022.2126342
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- Validation of Cloud-Gap-Filled Snow Cover of MODIS Daily Cloud-Free Snow Cover Products on the Qinghai–Tibetan Plateau Y. Yuan et al. 10.3390/rs14225642
- An Improved Spatiotemporal Fusion Algorithm for Monitoring Daily Snow Cover Changes With High Spatial Resolution Y. Wang et al. 10.1109/TGRS.2022.3224126
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- Quantifying regional variability of machine-learning-based snow water equivalent estimates across the Western United States D. Liljestrand et al. 10.1016/j.envsoft.2024.106053
- Estimating AVHRR snow cover fraction by coupling physical constraints into a deep learning framework Q. Zhao et al. 10.1016/j.isprsjprs.2024.08.015
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- Assessment of snow simulation using Noah-MP land surface model forced by various precipitation sources in the Central Tianshan Mountains, Central Asia T. Yang et al. 10.1016/j.atmosres.2024.107251
- Development of a Daily Cloud-Free Snow-Cover Dataset Using MODIS-Based Snow-Cover Probability for High Mountain Asia during 2000–2020 D. Yan et al. 10.3390/rs16162956
- STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China Y. Jing et al. 10.5194/essd-14-3137-2022
- The Application of SWAT Model and Remotely Sensed Products to Characterize the Dynamic of Streamflow and Snow in a Mountainous Watershed in the High Atlas S. Taia et al. 10.3390/s23031246
- Snow Cover and Climate Change and Their Coupling Effects on Runoff in the Keriya River Basin during 2001–2020 W. Yan et al. 10.3390/rs15133435
- The Arabian Sea and Bay of Bengal play a key role in extreme precipitation during the snow season over the Tibetan Plateau W. Wang et al. 10.1002/joc.8431
- Effect of Cloud Mask on the Consistency of Snow Cover Products from MODIS and VIIRS A. Liu et al. 10.3390/rs14236134
- Reconstruction of Snow Cover in Kaidu River Basin via Snow Grain Size Gap-Filling Based on Machine Learning L. Zhu et al. 10.3390/w15213726
- Harnessing Deep Learning and Snow Cover Data for Enhanced Runoff Prediction in Snow-Dominated Watersheds R. Adnan et al. 10.3390/atmos15121407
- Pattern and imprints of elevation-dependent warming on central Himalayan cryosphere as revealed by Earth Observation datasets P. Pandey et al. 10.1016/j.rines.2024.100021
- MODIS daily cloud-gap-filled fractional snow cover dataset of the Asian Water Tower region (2000–2022) F. Pan et al. 10.5194/essd-16-2501-2024
- A dataset of snow cover phenology in China based on MODIS during 2000–2020 Q. ZHAO et al. 10.11922/11-6035.ncdc.2021.0027.zh
38 citations as recorded by crossref.
- A dataset of MODIS gap-filled fractional snow cover in the source area of Yellow River during 2000–2021 Y. YANG et al. 10.11922/11-6035.ncdc.2022.0005.zh
- Atmospheric Correction Effects on the NDSI: Snow Detection Characteristics across Land Cover Types D. Jin et al. 10.7780/kjrs.2024.40.5.1.12
- A new snow cover mapping algorithm for Chinese geostationary meteorological satellite FY-4A AGRI data L. He et al. 10.1080/17538947.2024.2367086
- Development and Evaluation of a Cloud-Gap-Filled MODIS Normalized Difference Snow Index Product over High Mountain Asia G. Deng et al. 10.3390/rs16010192
- Comparison of Three Different Random Forest Approaches to Retrieve Daily High-Resolution Snow Cover Maps from MODIS and Sentinel-2 in a Mountain Area, Gran Paradiso National Park (NW Alps) C. Richiardi et al. 10.3390/rs15020343
- Mapping reveals contrasting change patterns of rain-on-snow events in China during 2001–2018 G. Zhou et al. 10.1016/j.jhydrol.2023.129089
- Performance of the WRF Model at the Convection‐Permitting Scale in Simulating Snowfall and Lake‐Effect Snow Over the Tibetan Plateau Q. Lin et al. 10.1029/2022JD038433
- Estimating Early Summer Snow Depth on Sea Ice Using a Radiative Transfer Model and Optical Satellite Data M. Wang & N. Oppelt 10.3390/rs15205016
- Development of a cloud-free MODIS NDSI dataset (2001–2020) over Northeast China H. Guo et al. 10.1080/17538947.2024.2398062
- Investigating climatic drivers of snow phenology by considering key-substage heterogeneity X. Ma et al. 10.1016/j.jhydrol.2024.132215
- Adapting an Existing Empirical Algorithm for Microwave Land Surface Temperature Retrieval in China for AMSR2 Data Q. Zhang et al. 10.3390/rs15133228
- Random Forest-Based Snow Cover Mapping in China Using Fengyun-3B VIRR Data Y. Xie et al. 10.1007/s13351-023-3003-z
- Spatiotemporal variation of snow cover days and influencing factors on the Loess Plateau during 2000–2019 S. Li et al. 10.1016/j.jhydrol.2023.130419
- Evaluating MODIS snow products using an extensive wildlife camera network C. Breen et al. 10.1016/j.rse.2023.113648
- Snow Cover Phenology Change and Response to Climate in China during 2000–2020 Q. Zhao et al. 10.3390/rs14163936
- Multi-year mapping of flood autumn irrigation extent and timing in harvested croplands of arid irrigation district X. Qian et al. 10.1080/15481603.2022.2126342
- Rolling forecast of snowmelt floods in data-scarce mountainous regions using weather forecast products to drive distributed energy balance hydrological model G. Zhou et al. 10.1016/j.jhydrol.2024.131384
- Snowmelt Runoff in the Yarlung Zangbo River Basin and Runoff Change in the Future H. Ji et al. 10.3390/rs15010055
- Detection of Wet Snow by Weakly Supervised Deep Learning Change Detection Algorithm with Sentinel-1 Data H. Gong et al. 10.3390/rs16193575
- Validation of Cloud-Gap-Filled Snow Cover of MODIS Daily Cloud-Free Snow Cover Products on the Qinghai–Tibetan Plateau Y. Yuan et al. 10.3390/rs14225642
- An Improved Spatiotemporal Fusion Algorithm for Monitoring Daily Snow Cover Changes With High Spatial Resolution Y. Wang et al. 10.1109/TGRS.2022.3224126
- Quantifying the Effects of Snow on the Beginning of Vegetation Growth in the Mongolian Plateau X. Zhang et al. 10.3390/rs15051245
- Evaluating MODIS cloud-free snow cover datasets using massive spatial benchmark data in the Tibetan Plateau Y. Gao et al. 10.1016/j.scitotenv.2024.175245
- Quantifying regional variability of machine-learning-based snow water equivalent estimates across the Western United States D. Liljestrand et al. 10.1016/j.envsoft.2024.106053
- Estimating AVHRR snow cover fraction by coupling physical constraints into a deep learning framework Q. Zhao et al. 10.1016/j.isprsjprs.2024.08.015
- Monitoring the Spatiotemporal Dynamics of Arctic Winter Snow/Ice with Moonlight Remote Sensing: Systematic Evaluation in Svalbard D. Liu et al. 10.3390/rs15051255
- What Is the Threshold Elevation at Which Climatic Factors Determine Snow Cover Variability? A Case Study of the Keriya River Basin W. Yan et al. 10.3390/rs15194725
- Assessment of snow simulation using Noah-MP land surface model forced by various precipitation sources in the Central Tianshan Mountains, Central Asia T. Yang et al. 10.1016/j.atmosres.2024.107251
- Development of a Daily Cloud-Free Snow-Cover Dataset Using MODIS-Based Snow-Cover Probability for High Mountain Asia during 2000–2020 D. Yan et al. 10.3390/rs16162956
- STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China Y. Jing et al. 10.5194/essd-14-3137-2022
- The Application of SWAT Model and Remotely Sensed Products to Characterize the Dynamic of Streamflow and Snow in a Mountainous Watershed in the High Atlas S. Taia et al. 10.3390/s23031246
- Snow Cover and Climate Change and Their Coupling Effects on Runoff in the Keriya River Basin during 2001–2020 W. Yan et al. 10.3390/rs15133435
- The Arabian Sea and Bay of Bengal play a key role in extreme precipitation during the snow season over the Tibetan Plateau W. Wang et al. 10.1002/joc.8431
- Effect of Cloud Mask on the Consistency of Snow Cover Products from MODIS and VIIRS A. Liu et al. 10.3390/rs14236134
- Reconstruction of Snow Cover in Kaidu River Basin via Snow Grain Size Gap-Filling Based on Machine Learning L. Zhu et al. 10.3390/w15213726
- Harnessing Deep Learning and Snow Cover Data for Enhanced Runoff Prediction in Snow-Dominated Watersheds R. Adnan et al. 10.3390/atmos15121407
- Pattern and imprints of elevation-dependent warming on central Himalayan cryosphere as revealed by Earth Observation datasets P. Pandey et al. 10.1016/j.rines.2024.100021
- MODIS daily cloud-gap-filled fractional snow cover dataset of the Asian Water Tower region (2000–2022) F. Pan et al. 10.5194/essd-16-2501-2024
1 citations as recorded by crossref.
Latest update: 08 Dec 2024
Short summary
We develop and validate a new 20-year MODIS snow-cover-extent product over China, which is dedicated to addressing known problems of the standard snow products. As expected, the new product significantly outperforms the state-of-the-art MODIS C6.1 products; improvements are particularly clear in forests and for the daily cloud-free product. Our product has provided more reliable snow knowledge over China and can be accessible freely https://dx.doi.org/10.11888/Snow.tpdc.271387.
We develop and validate a new 20-year MODIS snow-cover-extent product over China, which is...