GEE-Based monitoring method of key management nodes in cotton production-Reference-Cited by-同舟云学术

GEE-Based monitoring method of key management nodes in cotton production

Published:2023-05-28 Issue:1 Volume:16 Page:1907-1922
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Yang Weiguang¹²³^ORCID,Xu Weicheng¹²³,Yan Kangtin¹²³,Cui Zongyin¹²³,Chen Pengchao¹²³,Zhang Lei²⁴³,Lan Yubin¹²³

Affiliation:

1. College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, People’s Republic of China

2. Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, People’s Republic of China

3. National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology, Guangdong, People’s Republic of China

4. College of Agriculture, South China Agricultural University, Guangzhou, People’s Republic of China

Funder

the Laboratory of Lingnan Modern Agriculture Project

China Agriculture Research System

Guangdong Technical System of Peanut and Soybean Industry

Key-Area Research and Development Program of Guangdong Province

the leading talents of Guangdong province program

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2218119

Reference41 articles.

1. Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data

2. Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine

3. Application of Google Earth Engine Cloud Computing Platform, Sentinel Imagery, and Neural Networks for Crop Mapping in Canada

4. Combination of Landsat 8 OLI and Sentinel-1 SAR Time-Series Data for Mapping Paddy Fields in Parts of West and Central Java Provinces, Indonesia

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

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