Monitoring and Simulation of Dynamic Spatiotemporal Land Use/Cover Changes

Abstract

Changes in land use/cover are among the most prominent impacts that humans have on the environment. Therefore, exploring land use/cover change is of great significance to urban planning and sustainable development. In this study, we preprocessed multiperiod land use and socioeconomic data, combined with spatial zoning, multilayer perception (MLP) artificial neural network, and Markov chain (MC), to construct a cellular automaton model of spatial zoning. Moreover, with the help of ArcGIS 10.2 and TerrSet 18.07 software, we explore the current status of land use and predict future changes. The results showed that drastic changes have occurred among different land use classes in Jinzhou District over the past 13 years owing to the impact of economic development and reclamation projects. Construction land, arable land, and waters have changed by +85.09, −24.42, and −23.62 km2, respectively. By comparing the FoM and Kappa coefficients, we concluded that the prediction accuracy of partitioned MLP-MC is better than that of unpartitioned MLP-MC. Therefore, using the spatial zoning approach to identify the conversion rules among land use classes in different zones can more effectively predict future land use changes and provide a reference for urban planning and policy making.

Complexity of Functional Urban Spaces Evolution in Different Aspects: Based on Urban Land Use Conversion

“…e study of urban functions has always attracted the attention of academia. Most scholars are committed to using new data or methods to identify the types of urban function [31][32][33][34][35][36][37][38], but they have not continued to use the research results for functional urban spaces evolution research. We have not only adopted a new perspective but also investigated the scale differences and complexity of functional urban spaces evolution.…”

“…Urban boundaries, urban landscape structures, and urban morphological structures are topical issues in the study of the complexity of urban system structures [25][26][27]. e mathematical model and scenario simulation of urban spatial structure evolution are the key points of urban spatial structure evolution research [28][29][30][31][32][33].…”

CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City

“…The results of the fuzzy overlay with a range of 0-1 will be utilized to estimate land cover using CA-MC (Figure 3). The (Guo, Zhang, and Hao 2020).…”

Classification Method and Determination of Mountainous Area Types at Township Scales: A Case Study of Yuxi City, Yunnan Province

“…Since there is no reference in existing studies to the classification method of mountainous area and plain area types based on the township scale, this study refers to the method of mountain area proportion based on the county scale, but there are improvements to two indicators of flatland-farmland area proportions, and number of flatlands (area ≥ 100 km 2 ) [39]. With the rapid development of the social economy and constant increases of urbanization levels, large amounts of flatland cultivated land have been occupied by construction [42,43]. erefore, there is a certain deficiency when using only the proportion of flatland cultivated land for evaluations.…”