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1 Ergebnisse
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Agricultural cropland extent and areas of South Asia derive..:
Murali Krishna Gumma
;
Prasad S. Thenkabail
;
Pardhasaradhi G. Teluguntla
...
http://dx.doi.org/10.1080/15481603.2019.1690780. , 2020
Link:
https://doi.org/10.1080/15481603.2019.1690780
RT Journal T1
Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:5fa1776ca95a4394a98a2779c6425e86&Exemplar=1&LAN=DE A1 Murali Krishna Gumma A1 Prasad S. Thenkabail A1 Pardhasaradhi G. Teluguntla A1 Adam Oliphant A1 Jun Xiong A1 Chandra Giri A1 Vineetha Pyla A1 Sreenath Dixit A1 Anthony M Whitbread PB Taylor & Francis Group YR 2020 K1 google earth engine K1 random forest K1 landsat K1 cloud computing K1 30m-south asia croplands K1 Mathematical geography. Cartography K1 GA1-1776 K1 Environmental sciences K1 GE1-350 JF http://dx.doi.org/10.1080/15481603.2019.1690780 LK http://dx.doi.org/https://doi.org/10.1080/15481603.2019.1690780 DO https://doi.org/10.1080/15481603.2019.1690780 SF ELIB - SuUB Bremen
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