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Analysis of the Spatiotemporal Heterogeneity of Various Landscape Processes and Their Driving Factors Based on the OPGD Model for the Jiaozhou Bay Coast Zone, China
by
Hu, Yecui
, Song, Rong
, Guo, Zelian
, Wang, Wei
in
Agricultural land
/ Arable land
/ arable soils
/ China
/ Coastal zone
/ Coasts
/ Ecology
/ Fish farms
/ GDP
/ geographical detectors model
/ Grasslands
/ Gross Domestic Product
/ Heterogeneity
/ Inflow
/ land
/ Landscape
/ landscapes
/ Natural resource management
/ Natural resources
/ Outflow
/ Process controls
/ R “GD” package
/ Regression analysis
/ Remote sensing
/ Resource management
/ Sensors
/ spatiotemporal features
2022
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Analysis of the Spatiotemporal Heterogeneity of Various Landscape Processes and Their Driving Factors Based on the OPGD Model for the Jiaozhou Bay Coast Zone, China
by
Hu, Yecui
, Song, Rong
, Guo, Zelian
, Wang, Wei
in
Agricultural land
/ Arable land
/ arable soils
/ China
/ Coastal zone
/ Coasts
/ Ecology
/ Fish farms
/ GDP
/ geographical detectors model
/ Grasslands
/ Gross Domestic Product
/ Heterogeneity
/ Inflow
/ land
/ Landscape
/ landscapes
/ Natural resource management
/ Natural resources
/ Outflow
/ Process controls
/ R “GD” package
/ Regression analysis
/ Remote sensing
/ Resource management
/ Sensors
/ spatiotemporal features
2022
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Analysis of the Spatiotemporal Heterogeneity of Various Landscape Processes and Their Driving Factors Based on the OPGD Model for the Jiaozhou Bay Coast Zone, China
by
Hu, Yecui
, Song, Rong
, Guo, Zelian
, Wang, Wei
in
Agricultural land
/ Arable land
/ arable soils
/ China
/ Coastal zone
/ Coasts
/ Ecology
/ Fish farms
/ GDP
/ geographical detectors model
/ Grasslands
/ Gross Domestic Product
/ Heterogeneity
/ Inflow
/ land
/ Landscape
/ landscapes
/ Natural resource management
/ Natural resources
/ Outflow
/ Process controls
/ R “GD” package
/ Regression analysis
/ Remote sensing
/ Resource management
/ Sensors
/ spatiotemporal features
2022
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Analysis of the Spatiotemporal Heterogeneity of Various Landscape Processes and Their Driving Factors Based on the OPGD Model for the Jiaozhou Bay Coast Zone, China
Journal Article
Analysis of the Spatiotemporal Heterogeneity of Various Landscape Processes and Their Driving Factors Based on the OPGD Model for the Jiaozhou Bay Coast Zone, China
2022
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Overview
To date, various studies have analyzed changes in the landscape but there are few studies which have explored landscape processes and the corresponding driving factors. This study makes up for this deficiency in the systematic theoretical exposition and the spatiotemporal analysis of landscape processes. The results show that the amount of arable land outflow and built-up land inflow have resulted in an increase of 92,311.11 ha of built-up land that is mostly distributed around the administrative center and along the coast of Jiaozhou Bay. The outflow of ecological land is a major resource for replenishing arable land, by 37,016.19 ha, especially in terms of the grassland that is distributed in the hilly areas west of Jiaozhou Bay. The outflow of the salt-field, fish-farm and ecological land outflow have good connectivity, a large patch size, and an irregular shape. The ecological type, elevation, slope, and vegetation coverage are the four factors that have a great influence on all landscape processes. A gentler slope and lower elevation, and proximity to cities and towns land will produce more arable land outflow and built-up land inflow. However, arable land inflow and ecological land outflow are the opposite. This research will guide natural resource management for a rapidly developing coastal zone.
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