Vegetation response to intensive commercial horticulture and environmental changes within watersheds in central highlands, Kenya, using AVHRR NDVI data-Reference-Cited by-同舟云学术

Vegetation response to intensive commercial horticulture and environmental changes within watersheds in central highlands, Kenya, using AVHRR NDVI data

Published:2015-09-23 Issue:1 Volume:53 Page:1-21
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Muriithi Faith K.,Yu Danlin,Robila Stefan

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

http://www.tandfonline.com/doi/pdf/10.1080/15481603.2015.1085736

Reference59 articles.

1. River Water Shortage in a Highland–Lowland System

2. NDVI anomaly patterns over Africa during the 1997/98 ENSO warm event

3. Bai, Z. G., and D. L. Dent. 2006. “Global Assessment of Land Degradation and Improvement: Pilot Study in Kenya.” Report 2006/01. Wageningen: ISRIC - World Soil Information.

4. Global evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bridging the Gap: Analyzing the Relationship between Environmental Justice Awareness on Twitter and Socio-Environmental Factors Using Remote Sensing and Big Data;Remote Sensing;2023-11-27

2. Impacts of anthropogenic activities on vegetation cover changes in the Circum-Bohai-Sea region, China;Geocarto International;2021-12-15

3. Spatiotemporal analysis of trends in vegetation change across an artificial desert oasis, Northwest China, 1975–2010;Arabian Journal of Geosciences;2020-07-29

4. Vegetation Cover Change and Relative Contributions of Associated Driving Factors in the Ecological Conservation and Development Zone of Beijing, China;Polish Journal of Environmental Studies;2019-10-23

5. Prediction of Drought on Pentad Scale Using Remote Sensing Data and MJO Index through Random Forest over East Asia;Remote Sensing;2018-11-15