Proximate Causes of Land-Use and Land-Cover Change in Bannerghatta National Park: A Spatial Statistical Model
Land change modeling has become increasingly important in evaluating the unique driving factors and proximate causes that underlie a particular geographical location. In this article, a binary logistic regression analysis was employed to identify the factors influencing deforestation and simultaneou...
Main Authors: | Sanchayeeta Adhikari, Timothy Fik, Puneet Dwivedi |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-09-01
|
Series: | Forests |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4907/8/9/342 |
Similar Items
-
Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing Approach
by: Sanchayeeta Adhikari, et al.
Published: (2012-10-01) -
An Adaptive Sampling Strategy for Land Cover Change Information and Its Accuracy Characterization
by: MEI Yingying, et al.
Published: (2018-05-01) -
Spectral and Spatial-Based Classification for Broad-Scale Land Cover Mapping Based on Logistic Regression
by: Georgios Mallinis, et al.
Published: (2008-12-01) -
Assessing the Spatial Drivers of Land Use and Land Cover Change in the Protected and Communal Areas of the Zambezi Region, Namibia
by: Jonathan M. Kamwi, et al.
Published: (2018-11-01) -
Spatial Modelling of Landscape and Land Cover Pattern at Semarang City
by: Kurniawati Sugiyo, et al.
Published: (2020-01-01)