Paper Info
Title
Spatial Quantitative Model of Human Activity Disturbance Intensity and Land Use Intensity Based on GF-6 Image, Empirical Study in Southwest Mountainous County, China
Abstract
Vigorous human activities have strengthened the development and utilization of land, causing huge damage to the earth's surface, while mining the disturbance pattern of human activities can capture the influence process and spatial interaction between human activities and land use. Therefore, in order to explore the inherent relationship between human activities and land use in mountainous counties, a spatial quantitative model of human activity disturbance intensity and land use intensity was proposed based on GF-6 image, traffic data, and socioeconomic data. The model can quantitatively evaluate the disturbance intensity of human activity and land use intensity from "production-living-ecological space", and unfold the correlation between human activity disturbance intensity and land use intensity with Pearson correlation coefficient and bivariate spatial autocorrelation method. Our study presents several key findings: (1) the spatial difference of human activity disturbance is significant in Mianzhu City, and it has steady aggregation (Moran's I index is 0.929), showing a decreasing trend from the southeast to the northwest area; (2) there is a strong positive correlation between the disturbance intensity of human activity and the intensity of land use with Pearson value 0.949; (3) among the eight selected factors, the proportion of construction land area plays a leading role in the disturbance intensity of human activity in Mianzhu City, while the township final account data have the least impact. The study results can provide an important reference for the quantitative identification and evaluation of human disturbances in similar cities and the coordinated development of the human-land relationship.
Year
DOI
Venue
2022
10.3390/rs14184574
REMOTE SENSING
Keywords
DocType
Volume
GF-6 image, land use, human activity, mountainous area, spatial quantitative model
Journal
14
Issue
ISSN
Citations 
18
2072-4292
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Xuedong Zhang100.34
Xuedi Wang200.34
Zexu Zhou300.34
Mengwei Li400.34
Changfeng Jing500.34