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Spatiotemporal Evolution of Urban Expansion Using Landsat Time Series Data and Assessment of Its Influences on Forests

by Meng Zhang 1,2,3,†, Huaqiang Du 1,2,3,*,†, Fangjie Mao 1,2,3,†, Guomo Zhou 1,2,3, Xuejian Li 1,2,3, Luofan Dong 1,2,3, Junlong Zheng 1,2,3, Di’en Zhu 1,2,3, Hua Liu 1,2,3, Zihao Huang 1,2,3 and Shaobai He 1,2,3
1
State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China
2
Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China
3
School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this study and shared first authorship.
ISPRS Int. J. Geo-Inf. 2020, 9(2), 64; https://doi.org/10.3390/ijgi9020064
Received: 25 December 2019 / Revised: 14 January 2020 / Accepted: 19 January 2020 / Published: 21 January 2020
Analysis of urban land use dynamics is essential for assessing ecosystem functionalities and climate change impacts. The focus of this study is on monitoring the characteristics of urban expansion in Hang-Jia-Hu and evaluating its influences on forests by applying 30-m multispectral Landsat data and a machine learning algorithm. Firstly, remote sensed images were preprocessed with radiation calibration, atmospheric correction and topographic correction. Then, the C5.0 decision tree was used to establish classification trees and then applied to make land use maps. Finally, spatiotemporal changes were analyzed through dynamic degree and land use transfer matrix. In addition, average land use transfer probability matrix (ATPM) was utilized for the prediction of land use area in the next 20 years. The results show that: (1) C5.0 decision tree performed with precise accuracy in land use classification, with an average total accuracy and kappa coefficient of more than 90.04% and 0.87. (2) During the last 20 years, land use in Hang-Jia-Hu has changed extensively. Urban area expanded from 5.84% in 1995 to 21.32% in 2015, which has brought about enormous impacts on cultivated land, with 198,854 hectares becoming urban, followed by forests with 19,823 hectares. (3) Land use area prediction based on the ATPM revealed that urbanization will continue to expand at the expense of cultivated land, but the impact on the forests will be greater than the past two decades. Rationality of urban land structure distribution is important for economic and social development. Therefore, remotely sensed technology combined with machine learning algorithms is of great significance to the dynamic detection of resources in the process of urbanization. View Full-Text
Keywords: landsat data; urban expansion; LUCC; forest; Hang-Jia-Hu landsat data; urban expansion; LUCC; forest; Hang-Jia-Hu
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Zhang, M.; Du, H.; Mao, F.; Zhou, G.; Li, X.; Dong, L.; Zheng, J.; Zhu, D.; Liu, H.; Huang, Z.; He, S. Spatiotemporal Evolution of Urban Expansion Using Landsat Time Series Data and Assessment of Its Influences on Forests. ISPRS Int. J. Geo-Inf. 2020, 9, 64.

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