The rapid Land Use and Land Cover change analysis using the Sentinel-2 images in Google Earth Engine: A Case Study of Xiong’an New Area from 2017 to 2020

Author(s):  
Jiansong Luo ◽  
Rujin Yuan ◽  
Yujia Cao ◽  
Min Xie ◽  
Yikai Wang
Tropics ◽  
2004 ◽  
Vol 13 (4) ◽  
pp. 235-248 ◽  
Author(s):  
Ahmad Jailani Muhamed YUNUS ◽  
Nobukazu NAKAGOSHI ◽  
Ab Latif IBRAHIM

Author(s):  
Crismeire Isbaex ◽  
Ana Margarida Coelho

Mapping land-cover/land-use (LCLU) and estimating forest biomass using satellite images is a challenge given the diversity of sensors available and the heterogeneity of forests. Copernicus program served by the Sentinel satellites family and the Google Earth Engine (GEE) platform, both with free and open services accessible to its users, present a good approach for mapping vegetation and estimate forest biomass on a global, regional, or local scale, periodically and in a repeated way. The Sentinel-2 (S2) systematically acquires optical imagery and provides global monitoring data with high spatial resolution (10–60 m) images. Given the novelty of information on the use of S2 data, this chapter presents a review on LCLU maps and forest above-ground biomass (AGB) estimates, in addition to exploring the efficiency of using the GEE platform. The Sentinel data have great potential for studies on LCLU classification and forest biomass estimates. The GEE platform is a promising tool for executing complex workflows of satellite data processing.


Author(s):  
Lokeshwari Navalgund ◽  
Keshava Joshi ◽  
G Srinikethan ◽  
Vinayaka B Shet ◽  
Satish N Hosamane

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