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פותח על ידי קלירמאש פתרונות בע"מ -
Time series analysis of vegetation-cover response to environmental factors and residential development in a dryland region
Year:
2019
Source of publication :
GIScience and Remote Sensing
Authors :
פז-כגן, טרין
;
.
Volume :
56
Co-Authors:

Ohana-Levi, N., The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, 84990, Israel, Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization, Gilat Research Center85280, Israel, Centre for Supply Chain Improvement, The University of Derby, Derby, United Kingdom;  Panov, N., The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, 84990, Israel; Peeters, A., TerraVision Lab, Sede Boker, 84990, Israel; Tsoar, A., Israel Nature and Parks Authority, Omer, Israel; Karnieli, A., The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, 84990, Israel

Facilitators :
From page:
362
To page:
387
(
Total pages:
26
)
Abstract:

Land-use changes as a result of residential development often lead to degradation and alter vegetation cover (VC). Although these are worldwide phenomena, sufficient knowledge about anthropogenic effects caused by various populated areas in dryland ecosystems is lacking. This study explored anthropogenic development in rural areas and its effects on the conservation of protected areas in drylands, focusing on the change in VC, the reasons, extent, and the drivers of change. We propose a novel framework for exploring VC change (VCC) as a function of environmental and human-driven factors including different types of populated areas in drylands. As a case study, we used a 30-year time series of Landsat satellite images over the arid region of Israel to analyze spatiotemporal VCC. The temporal analysis involved the Contextual Mann-Kendall significance test and spatial analysis to model clustering of VCC. A Gradient Boosted Regression machine learning algorithm was applied to study the relative influence of environmental and human-driven factors on VCC. In addition, we used ANOVA to examine differences between the effects of three types of populated areas on the spatiotemporal trends of VC. The results show that the most influential environmental variable on VCC was elevation (relative contribution of 17%), followed by slope (14.8%) and distance from populated areas (14.6%). Moreover, different types of populated areas affected VC differently with varying distances from residential centroids. The nature reserves increased VC positively and significantly, while livestock settlements had a negative effect. Change in vegetation was mostly confined to the stream network and occurred in lower elevations. The study demonstrates how different land-use practices alter the landscape in terms of VC and differ in their extents, patterns, and effects. With the expected growth in population and residential development worldwide, the proposed framework may assist conservation managements and policy makers in minimizing environmental degradation in drylands. © 2018, © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Note:
Related Files :
agricultural settlements
Drylands
Grazing
protected area
remote sensing
spatial analysis
עוד תגיות
תוכן קשור
More details
DOI :
10.1080/15481603.2018.1519093
Article number:
0
Affiliations:
Database:
סקופוס
Publication Type:
מאמר
;
.
Language:
אנגלית
Editors' remarks:
ID:
37393
Last updated date:
02/03/2022 17:27
Creation date:
03/10/2018 14:46
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Time series analysis of vegetation-cover response to environmental factors and residential development in a dryland region
56

Ohana-Levi, N., The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, 84990, Israel, Institute of Soil, Water and Environmental Sciences, Agricultural Research Organization, Gilat Research Center85280, Israel, Centre for Supply Chain Improvement, The University of Derby, Derby, United Kingdom;  Panov, N., The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, 84990, Israel; Peeters, A., TerraVision Lab, Sede Boker, 84990, Israel; Tsoar, A., Israel Nature and Parks Authority, Omer, Israel; Karnieli, A., The Remote Sensing Laboratory, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boker, 84990, Israel

Time series analysis of vegetation-cover response to environmental factors and residential development in a dryland region

Land-use changes as a result of residential development often lead to degradation and alter vegetation cover (VC). Although these are worldwide phenomena, sufficient knowledge about anthropogenic effects caused by various populated areas in dryland ecosystems is lacking. This study explored anthropogenic development in rural areas and its effects on the conservation of protected areas in drylands, focusing on the change in VC, the reasons, extent, and the drivers of change. We propose a novel framework for exploring VC change (VCC) as a function of environmental and human-driven factors including different types of populated areas in drylands. As a case study, we used a 30-year time series of Landsat satellite images over the arid region of Israel to analyze spatiotemporal VCC. The temporal analysis involved the Contextual Mann-Kendall significance test and spatial analysis to model clustering of VCC. A Gradient Boosted Regression machine learning algorithm was applied to study the relative influence of environmental and human-driven factors on VCC. In addition, we used ANOVA to examine differences between the effects of three types of populated areas on the spatiotemporal trends of VC. The results show that the most influential environmental variable on VCC was elevation (relative contribution of 17%), followed by slope (14.8%) and distance from populated areas (14.6%). Moreover, different types of populated areas affected VC differently with varying distances from residential centroids. The nature reserves increased VC positively and significantly, while livestock settlements had a negative effect. Change in vegetation was mostly confined to the stream network and occurred in lower elevations. The study demonstrates how different land-use practices alter the landscape in terms of VC and differ in their extents, patterns, and effects. With the expected growth in population and residential development worldwide, the proposed framework may assist conservation managements and policy makers in minimizing environmental degradation in drylands. © 2018, © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

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