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GOOGLE_EARTH: 作品数：1417被引量：3896H指数：29; 导出分析报告; 相关作者：贾明明马明国田佳冯浩李晶更多>>; 相关机构：中国科学院中国科学院大学成都理工大学华东师范大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金中国科学院战略性先导科技专项中央高校基本科研业务费专项资金国家科技支撑计划更多>>

Towards understanding the environmental and climatic changes and its contribution to the spread of wildfires in Ghana using remote sensing tools and machine learning (Google Earth Engine)被引量：2: 《International Journal of Digital Earth》2023年第1期1300-1331,共32页Kueshi Sémanou Dahan Raymond Abudu Kasei Rikiatu Husseini Mohammed Y.Said Md.Mijanur Rahman; Data processing and climate characterisation to study its impact is becoming difficult due to insufficient and unavailable data,especially in developing countries.Understanding climate’s impact on burnt areas in Ghan...; 关键词：Climate change Google Earth Engine mitigation machine learning WILDFIRE Ghana

Machine learning-based prediction of sand and dust storm sources in arid Central Asia: 《International Journal of Digital Earth》2023年第1期1530-1550,共21页Wei Wang Alim Samat Jilili Abuduwaili Philippe De Maeyer Tim Van de Voorde; supported by the National Natural Science Foundation of China(42171014);the UNEPNSFC International Cooperation Project(42161144004);the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20060301);National Natural Science Foundation of China(42071424);the China Scholarship Council(202104910412).; With the emergence of multisource data and the development of cloud computing platforms,accurate prediction of event-scale dust source regions based on machine learning(ML)methods should be considered,especially accou...; 关键词：Susceptibility mapping event scale google earth engine(GEE) remote sensing

GEE-Based monitoring method of key management nodes in cotton production: 《International Journal of Digital Earth》2023年第1期1907-1922,共16页Weiguang Yang Weicheng Xu Kangtin Yan Zongyin Cui Pengchao Chen Lei Zhang Yubin Lan; supported by the Laboratory of Lingnan Modern Agriculture Project[grant number NT2021009];China Agriculture Research System[grant number CARS-15-22];Guangdong Technical System of Peanut and Soybean Industry[grant number 2019KJ136-05];Key-Area Research and Development Program of Guangdong Province[grant number 2019B020214003];the leading talents of Guangdong province program[grant number 2016LJ06G689].; The high-temporal-resolution monitoring of key management nodes in cotton management via agricultural remote sensing is vital forfield cotton macro-statistics,particularly for predicting cotton production and obtainin...; 关键词：Google Earth Engine cotton production crop monitoring classification abandoned cropland detection

Spatial-temporal variation and attribution of salinization in the Yellow River Basin from 2015 to 2020: 《International Journal of Digital Earth》2023年第1期446-463,共18页Hong Mengmeng Wang Juanle Han Baomin; Under the pressure of SDG15.3.1 compliance,it is imperative to solve the land salinization degradation problem in the Yellow River Basin as China’s granary.From the view of geographical scale,six zoning units were di...; 关键词：SALINIZATION land degradation Yellow River Basin Google Earth Engine feature space sustainable development goals 15

Automated and refined wetland mapping of Dongting Lake using migrated training samples based on temporally dense Sentinel 1/2 imagery: 《International Journal of Digital Earth》2023年第1期3199-3221,共23页Yawen Deng Weiguo Jiang Ziyan Ling Xiaoya Wang Kaifeng Peng Zhuo Li; supported by the National Natural Science Foundation of China(grant numbers 42071393,U1901219 and U21A2022).; Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated an...; 关键词：Wetland classification continuous change detection algorithm sample migration time series Dongting Lake wetland Google Earth Engine

A fully automatic and high-accuracy surface water mapping framework on Google Earth Engine using Landsat time-series被引量：2: 《International Journal of Digital Earth》2023年第1期210-233,共24页Linwei Yue Baoguang Li Shuang Zhu Qiangqiang Yuan Huanfeng Shen; supported by the National Natural Science Foundation of China[grants numbers 42171375 and 41801263].; Efficient and continuous monitoring of surface water is essential for water resource management.Much effort has been devoted to the task of water mapping based on remote sensing images.However,few studies have fully c...; 关键词：Water mapping automatic training samples temporal correction Google Earth Engine

A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform被引量：1: 《International Journal of Digital Earth》2023年第1期988-1007,共20页Jie Zhou Massimo Menenti Li Jia Bo Gao Feng Zhao Yilin Cui Xuqian Xiong Xuan Liu Dengchao Li; supported by the National Natural Science Foundation of China(grant number 42171371 and No.41701492);Massimo Menenti acknowledges the support of the MOST High Level Foreign Expert program(grant number G2022055010L);the Chinese Academy of Sciences President s International Fellowship Initiative(grant number 2020VTA0001).; Spatiotemporal residual noise in terrestrial earth observation products,often caused by unfavorable atmospheric conditions,impedes their broad applications.Most users prefer to use gap-filled remote sensing products w...; 关键词：Time series reconstruction remote sensing Google Earth Engine HANTS GAP-FILLING

HiLPD-GEE:high spatial resolution land productivity dynamicscal culation tool using Landsat and MODIS data: 《International Journal of Digital Earth》2023年第1期671-690,共20页Tong Shen Xiaosong Li Yang Chen Yuran Cui Qi Lu Xiaoxia Jia Jin Chen; supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant numbers XDA19090124 and XDA19030104].; Land productivity is one of the sub-indicators for measuring SDG 15.3.1.Land Productivity Dynamics(LPD)is the most popular approach for reporting this indicator at the global scale.A major limitation of existing produ...; 关键词：SDG 15.3.1 land productivity dynamics GF-SG Great Green Wall Google Earth Engine

Estimation of 30 m land surface temperatures over the entire Tibetan Plateau based on Landsat-7 ETM+data and machine learning methods被引量：2: 《International Journal of Digital Earth》2022年第1期1038-1055,共18页Xian Wang Lei Zhong Yaoming Ma; supported by the Second Tibetan Plateau Scientifc Expedition and Research(STEP)Program[grant number:2019QZKK0103];Strategic Priority Research Program of Chinese Academy of Sciences[grant number:XDA20060101];National Natural Science Foundation of China[grant number 41875031,41522501,41275028,91837208];The Chinese Academy of Sciences[grant number QYZDJSSW-DQC019];CLIMATE-TPE[grant number:32070]in the framework of the ESA-MOST Dragon 4 Programme.; Land surface temperature(LST)is an important parameter in land surface processes.Improving the accuracy of LST retrieval over the entire Tibetan Plateau(TP)using satellite images with high spatial resolution is an imp...; 关键词：Google Earth Engine remote sensing machine learning land surface temperature random forest

Time-series surface water reconstruction method(TSWR)based on spatial distance relationship of multi-stage water boundaries: 《International Journal of Digital Earth》2022年第1期2335-2354,共20页Mingyang Li Shanlong Lu Cong Du Yong Wang Chun Fang Xinru Li Hailong Tang Muhammad Hasan Ali Baig Harrison Odion Ikhumhen; The research was funded by the National Natural Science Foundation of China[grant no 42171283];the Major Science and Technology Projects of Qinghai Province[grant no 2021-SF-A6];the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)[grant number 2019QZKK0202];Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA19090120].; Spatiotemporal continuity of surface water datasets widely known for its significance in the surface water dynamic monitoring and assessments,are faced with drawbacks like cloud influence,which hinders the direct extr...; 关键词：Google earth engine sentinel-2 surface water reconstruction time-series surface water data

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