Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine-Reference-Cited by-同舟云学术

Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

Published:2017-10-19 Issue:10 Volume:9 Page:1065
ISSN:2072-4292
Container-title:Remote Sensing
language:en
Short-container-title:Remote Sensing

Author:

Xiong Jun,Thenkabail Prasad,Tilton James,Gumma Murali,Teluguntla Pardhasaradhi,Oliphant Adam,Congalton Russell,Yadav Kamini,Gorelick Noel

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Link

http://www.mdpi.com/2072-4292/9/10/1065/pdf

Reference93 articles.

1. A Holistic View of Global Croplands and Their Water Use for Ensuring Global Food Security in the 21st Century through Advanced Remote Sensing and Non-remote Sensing Approaches

2. Comparison of global and regional land cover maps with statistical information for the agricultural domain in Africa

3. Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets

4. Improved global cropland data as an essential ingredient for food security

5. Crop mapping in countries with small-scale farming: a case study for West Shewa, Ethiopia

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