O-LCMapping: a Google Earth Engine-based web toolkit for supporting online land cover classification-Reference-Cited by-同舟云学术

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O-LCMapping: a Google Earth Engine-based web toolkit for supporting online land cover classification

Published:2021-01-05 Issue:1 Volume:14 Page:529-541
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Xing Huaqiao,Hou Dongyang,Wang Siyuan,Yu Mingyang,Meng Fei

Funder

National Natural Science Foundation of China

Doctoral Research Fund of Shandong Jianzhu University

Yunnan Fundamental Research Projects

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

http://link.springer.com/content/pdf/10.1007/s12145-020-00562-6.pdf

Reference47 articles.

1. Azzari G, Lobell D (2017) Landsat-based classification in the cloud: an opportunity for a paradigm shift in land cover monitoring. Remote Sens Environ 202:64–74

2. Chen J et al (2015) Global land cover mapping at 30 m resolution: a POK-based operational approach. ISPRS J Photogramm Remote Sens 103:7–27

3. Chen B, Xiao X, Li X, Pan L, Doughty R, Ma J, Dong J, Qin Y, Zhao B, Wu Z, Sun R, Lan G, Xie G, Clinton N, Giri C (2017) A mangrove forest map of China in 2015: analysis of time series Landsat 7/8 and sentinel-1A imagery in Google earth engine cloud computing platform. ISPRS J Photogramm Remote Sens 131:104–120

4. Feyisa GL, Meilby H, Fensholt R, Proud SR (2014) Automated water extraction index: a new technique for surface water mapping using Landsat imagery. Remote Sens Environ 140:23–35

5. Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80:185–201

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