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Article

Simulation of Land-Use Changes Using the Partitioned ANN-CA Model and Considering the Influence of Land-Use Change Frequency

by 1,2,3,4,*, 1,2,3,4, 1,2,3,4 and 1,2,3,4
1
Department of Geography, Yunnan Normal University, Kunming 650500, China
2
GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Kunming 650500, China
3
Yunnan Geospatial Information Technology Engineering Research Center, Kunming 650500, China
4
Key Laboratory of Resources and Environment Remote Sensing, Yunnan University, Kunming 650500, China
*
Author to whom correspondence should be addressed.
Academic Editors: Costantino Domenica, Massimiliano Pepe and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(5), 346; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050346
Received: 22 March 2021 / Revised: 1 May 2021 / Accepted: 15 May 2021 / Published: 18 May 2021
Land-use change is a typical geographic evolutionary process characterized by spatial heterogeneity. As such, the driving factors, conversion rules, and rate of change vary for different regions around the world. However, most cellular automata (CA) models use the same transition rules for all cells in the model space when simulating land-use change. Thus, spatial heterogeneity change is ignored in the model, which means that these models are prone to over- or under simulation, resulting in a large deviation from reality. An effective means of accounting for the influence of spatial heterogeneity on the quality of the CA model is to establish a partitioned model based on cellular space partitioning. This study established a partitioned, dual-constrained CA model using the area-weighted frequency of land-use change (AWFLUC) to capture its spatial heterogeneity. This model was used to simulate the land-use evolution of the Dianchi Lake watershed. First, the CA space was divided into subzones using a dual-constrained spatial clustering method. Second, an artificial neural network (ANN) was used to automatically acquire conversion rules to construct an ANN-CA model of land-use change. Finally, land-use changes were simulated using the ANN-CA model based on data from 2006 to 2016, and model reliability was validated. The experimental results showed that compared with the non-partitioned CA model, the partitioned counterpart was able to improve the accuracy of land-use change simulation significantly. Furthermore, AWFLUC is an important indicator of the spatial heterogeneity of land-use change. The shapes of the division spaces were more similar to reality and the simulation accuracy was higher when AWFLUC was considered as a land-use change characteristic. View Full-Text
Keywords: dual-constrained spatial partition; ANN; partitioned CA; land-use dynamic simulation; Dianchi Lake watershed dual-constrained spatial partition; ANN; partitioned CA; land-use dynamic simulation; Dianchi Lake watershed
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MDPI and ACS Style

Xu, Q.; Wang, Q.; Liu, J.; Liang, H. Simulation of Land-Use Changes Using the Partitioned ANN-CA Model and Considering the Influence of Land-Use Change Frequency. ISPRS Int. J. Geo-Inf. 2021, 10, 346. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050346

AMA Style

Xu Q, Wang Q, Liu J, Liang H. Simulation of Land-Use Changes Using the Partitioned ANN-CA Model and Considering the Influence of Land-Use Change Frequency. ISPRS International Journal of Geo-Information. 2021; 10(5):346. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050346

Chicago/Turabian Style

Xu, Quanli, Qing Wang, Jing Liu, and Hong Liang. 2021. "Simulation of Land-Use Changes Using the Partitioned ANN-CA Model and Considering the Influence of Land-Use Change Frequency" ISPRS International Journal of Geo-Information 10, no. 5: 346. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050346

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