Mapping irrigated, rainfed and paddy croplands from time-series Sentinel-2 images by integrating pixel-based classification and image segmentation on Google Earth Engine-Reference-Cited by-同舟云学术

Mapping irrigated, rainfed and paddy croplands from time-series Sentinel-2 images by integrating pixel-based classification and image segmentation on Google Earth Engine

Published:2022-05-22 Issue:26 Volume:37 Page:13291-13310
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Xing Huaqiao¹²,Chen Bingyao¹²,Feng Yongyu³,Ni Yuanlong³,Hou Dongyang⁴,Wang Xue³,Kong Yawei²

Affiliation:

1. School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, Shandong, China;

2. The Key Laboratory of Digital Simulation in Spatial Design of Architecture and Urban-Rural, Shandong Provincial Education Department, Jinan, Shandong, China

3. Shandong Geographical Institute of Land Spatial Data and Remote Sensing Technology Center, Jinan, Shandong, China

4. School of Geosciences and Info-Physics, Central South University, Changsha, Hunan, China

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2022.2076923

Reference58 articles.

1. GLC2000: a new approach to global land cover mapping from Earth observation data

2. Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis

3. Mapping smallholder and large-scale cropland dynamics with a flexible classification system and pixel-based composites in an emerging frontier of Mozambique