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Article

Fully Portraying Patch Area Scaling with Resolution: An Analytics and Descriptive Statistics-Combined Approach

by 1 and 1,2,3,*
1
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
2
State-Province Joint Engineering Laboratory of Spatial Information Technology for High-Speed Railway Safety, Southwest Jiaotong University, Chengdu 611756, China
3
National Collaborative Innovation Center for Rail Transport Safety, Southwest Jiaotong University, Chengdu 611756, China
*
Author to whom correspondence should be addressed.
Academic Editor: Wayne Myers
Land 2021, 10(3), 262; https://doi.org/10.3390/land10030262
Received: 31 January 2021 / Revised: 24 February 2021 / Accepted: 3 March 2021 / Published: 5 March 2021
(This article belongs to the Special Issue Multiscale Geospatial Approaches for Landscape Ecology)
Scale effects are inherent in spatial analysis. Quantitative knowledge about them is necessary for properly interpreting and scaling analysis results. The objective of this study was to systematically model patch area scaling and the associated uncertainty. A hybrid approach was taken to tackle the difficulty involved. Recognizing that patch’s size and shape play the key role in shaping its scaling behavior, a function model of patch area scaling based on patch morphology was first conceptually formulated. It was then substantiated by sampling and interpolating in the scale-integrated domain of patch morphology, which is characterized by a one-dimensional size index, namely the relative support range (RSR), and a compactness index, namely filling. The area scaling model obtained unveils a simple consistent scaling pattern of all patches and an overall fading range between 0.12 and 3.16 in terms of RSR. The uncertainty model built exhibits a filling-dependent pattern of the variance of patch area, which can be as large as 0.67 (i.e., 67%) in terms of standard deviation. The models were validated by using them to predict patch and class area scaling of the test patches and landscapes. This study demonstrated the basic feasibility of analytically modeling scaling behavior. It also revealed the uncertainty of scale effects is very significant due to the inevitable randomness in rasterization. View Full-Text
Keywords: scale effect; spatial aggregation; scaling model; uncertainty; patch area; land use and land cover; raster categorical data scale effect; spatial aggregation; scaling model; uncertainty; patch area; land use and land cover; raster categorical data
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MDPI and ACS Style

Zhang, Q.; Xu, Z. Fully Portraying Patch Area Scaling with Resolution: An Analytics and Descriptive Statistics-Combined Approach. Land 2021, 10, 262. https://doi.org/10.3390/land10030262

AMA Style

Zhang Q, Xu Z. Fully Portraying Patch Area Scaling with Resolution: An Analytics and Descriptive Statistics-Combined Approach. Land. 2021; 10(3):262. https://doi.org/10.3390/land10030262

Chicago/Turabian Style

Zhang, Qianning, and Zhu Xu. 2021. "Fully Portraying Patch Area Scaling with Resolution: An Analytics and Descriptive Statistics-Combined Approach" Land 10, no. 3: 262. https://doi.org/10.3390/land10030262

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