Arid

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Modeling relationship between land surface temperature anomaly and environmental factors using GEE and Giovanni 期刊论文
发表期刊: JOURNAL OF ENVIRONMENTAL MANAGEMENT. 出版年: 2022, 卷号: 302
作者:  Jamali, Ali Akbar;  Kalkhajeh, Reza Ghorbani;  Randhir, Timothy O.;  He, Songtang
收藏  |  浏览/下载:14/0  |  提交时间:2022/02/12
Anomaly  Land surface temperature  GEE  Giovanni  Elevation  Season  
A new global land productivity dynamic product based on the consistency of various vegetation biophysical indicators 期刊论文
发表期刊: BIG EARTH DATA. 出版年: 2022
作者:  Cui, Yuran;  Li, Xiaosong
收藏  |  浏览/下载:25/0  |  提交时间:2022/03/17
Sustainable development goals  SDG 15.3.1  vegetation parameters  confidence level  google Earth engine  
Assessment of environmentally sensitive areas to desertification in the Blue Nile Basin driven by the MEDALUS-GEE framework 期刊论文
发表期刊: SCIENCE OF THE TOTAL ENVIRONMENT. 出版年: 2022, 卷号: 815
作者:  Elnashar, Abdelrazek;  Zeng, Hongwei;  Wu, Bingfang;  Gebremicael, Tesfay Gebretsadkan;  Marie, Khadiga
收藏  |  浏览/下载:10/0  |  提交时间:2022/03/17
Land degradation and desertification  MEDALUS  Google earth engine  Spatial analysis  Cloud computing  
A Planted Forest Mapping Method Based on Long-Term Change Trend Features Derived from Dense Landsat Time Series in an Ecological Restoration Region 期刊论文
发表期刊: REMOTE SENSING. 出版年: 2022, 卷号: 14, 期号: 4
作者:  Meng, Yuanyuan;  Wei, Caiyong;  Guo, Yanpei;  Tang, Zhiyao
收藏  |  浏览/下载:32/0  |  提交时间:2022/03/17
planted forests  long-term change trend features  Landsat time series  Google Earth Engine  random forest  NDVI  
Desert landform detection and mapping using a semi-automated object-based image analysis approach 期刊论文
发表期刊: JOURNAL OF ARID ENVIRONMENTS. 出版年: 2022, 卷号: 199
作者:  Garajeh, Mohammad Kazemi;  Feizizadeh, Bakhtiar;  Weng, Qihao;  Moghaddam, Mohammad Hossein Rezaei;  Garajeh, Ali Kazemi
收藏  |  浏览/下载:50/0  |  提交时间:2022/03/17
Object-based image analysis (OBIA)  Fuzzy rule-based classification  Desert landforms  Geomorphology  Earth's landforms  
Slight change of glaciers in the Pamir over the period 2000-2017 期刊论文
发表期刊: ARCTIC ANTARCTIC AND ALPINE RESEARCH. 出版年: 2022, 卷号: 54, 期号: 1, 页码: 13-24
作者:  Li, Zhijie;  Wang, Ninglian;  Chen, An'an;  Liang, Qian;  Yang, DaQing
收藏  |  浏览/下载:17/0  |  提交时间:2022/03/17
Pamir  glacier inventory  manual delineation  debris-covered glacier  
Assessing the performance of machine learning algorithms for soil salinity mapping in Google Earth Engine platform using Sentinel-2A and Landsat-8 OLI data 期刊论文
发表期刊: ADVANCES IN SPACE RESEARCH. 出版年: 2022, 卷号: 69, 期号: 2
作者:  Aksoy, Samet;  Yildirim, Aylin;  Gorji, Taha;  Hamzehpour, Nikou;  Tanik, Aysegul;  Sertel, Elif
收藏  |  浏览/下载:28/0  |  提交时间:2022/03/17
Soil salinity  Electrical conductivity  Machine learning  Cross-validation  Google Earth Engine  
Leveraging Google Earth Engine platform to characterize and map small seasonal wetlands in the semi-arid environments of South Africa 期刊论文
发表期刊: SCIENCE OF THE TOTAL ENVIRONMENT. 出版年: 2022, 卷号: 803
作者:  Gxokwe, Siyamthanda;  Dube, Timothy;  Mazvimavi, Dominic
收藏  |  浏览/下载:14/0  |  提交时间:2021/11/19
Limpopo River Basin  Object-based classification  Machine learning algorithm  Wetland mapping  Wetland condition  
Contrasting YOLOv5, Transformer, and EfficientDet Detectors for Crop Circle Detection in Desert 期刊论文
发表期刊: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS. 出版年: 2022, 卷号: 19
作者:  Mekhalfi, Mohamed Lamine;  Nicolo, Carlo;  Bazi, Yakoub;  Al Rahhal, Mohamad Mahmoud;  Alsharif, Norah A.;  Al Maghayreh, Eslam
收藏  |  浏览/下载:11/0  |  提交时间:2022/03/17
Agriculture  Computer science  Object detection  Indexes  Detectors  Training  Internet  Aerial imagery  crop circles  detection transformers (DETRs)  efficientDet  object detection  precision farming  YOLOv5  
Land cover change detection in the Aralkum with multi-source satellite datasets 期刊论文
发表期刊: GISCIENCE & REMOTE SENSING. 出版年: 2022
作者:  Low, Fabian;  Dimov, Dimo;  Kenjabaev, Shavkat;  Zaitov, Sherzod;  Stulina, Galina;  Dukhovny, Viktor
收藏  |  浏览/下载:27/0  |  提交时间:2022/02/12
Aral sea  google earth engine  ground truth data  land cover  remote sensing  random forest