Using multitemporal Landsat imagery to monitor and model the influences of landscape pattern on urban expansion in a metropolitan region

被引:16
|
作者
Yang, Yetao [1 ,2 ]
Wong, Louis Ngai Yuen [2 ]
Chen, Chao [1 ]
Chen, Tao [1 ]
机构
[1] China Univ Geosci, Inst Geophys & Geomat, Wuhan 430074, Peoples R China
[2] Nanyang Technol Univ, Sch Civil & Environm Engn, Singapore 639798, Singapore
来源
基金
中国国家自然科学基金;
关键词
change detection; urban expansion; landscape metrics; interaction of pattern and process; SPATIOTEMPORAL PATTERNS; GRADIENT ANALYSIS; SPATIAL-PATTERN; DYNAMICS; SPRAWL; GROWTH; AREA; VALLEY; CHINA;
D O I
10.1117/1.JRS.8.083639
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Studying the interaction between landscape patterns and temporal land-use changes in a metropolitan area can improve understanding of the urbanization process. Multitemporal remote sensing imagery is widely used to map the urbanization-caused temporal land-use dynamics, which mainly appear as built-up growth. Remote sensing integrated with landscape metrics is also used to quantitatively describe the landscape pattern of the urban area in recent literature. However, few studies have focused on the interaction between the pattern and the process of urbanization in a metropolitan area. We propose a grid-based framework to analyze the influence of the landscape pattern on the built-up growth by using the multitemporal Landsat imagery. Remote sensing classification method is used to obtain thematic land-use maps. Built-up growth is then extracted from the multitemporal classification results by a postclassification change detection. Landscape pattern, which is quantitatively described by landscape metrics, is derived from the thematic land-use maps. A grid-based method is used to analyze the spatial variation of landscape pattern and its related built-up growth. Finally, the spatial relationship between the landscape pattern and the built-up growth characters is assessed and modeled by using the mathematical regression method. The present study shows that an apparent correlation between landscape pattern and built-up growth exists. The correlation reflects the inherent influences of landscape pattern on urban expansion. The landscape pattern indicates the land development stage, while the urbanization stage determines the speed and style of the following built-up growth. Scales, including temporal scale and spatial scale, are important to modeling the landscape pattern effects on the built-up growth. The proposed analysis framework is efficient in detecting and modeling the landscape pattern effects on the built-up growth. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Prediction of Greenhouse Area Expansion in an Agricultural Hotspot Using Landsat Imagery, Machine Learning and the Markov-FLUS Model
    Inalpulat, Melis
    SUSTAINABILITY, 2024, 16 (19)
  • [32] Using Landsat satellite imagery to monitor the spatial and temporal dynamics of aquatic weed extent in Lakes Chivero and Manyame, located in an urban catchment of Zimbabwe
    Shekede, Munyaradzi Davis
    Gondo, Takudzwa
    Mavhenge, Melisa Matavire
    Mazhindu, Aldridge Nyasha
    WATER SA, 2023, 49 (01) : 46 - 55
  • [33] Assessment of land surface temperature in relation to landscape metrics and fractional vegetation cover in an urban/peri-urban region using Landsat data
    Zhang, Youshui
    Odeh, Inakwu O. A.
    Ramadan, Elnazir
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2013, 34 (01) : 168 - 189
  • [34] A Methodology for the Multitemporal Analysis of Land Cover Changes and Urban Expansion Using Synthetic Aperture Radar (SAR) Imagery: A Case Study of the Aburrá Valley in Colombia
    Cardona-Mesa, Ahmed Alejandro
    Vasquez-Salazar, Ruben Dario
    Parra, Juan Camilo
    Olmos-Severiche, Cesar
    Travieso-Gonzalez, Carlos M.
    Gomez, Luis
    REMOTE SENSING, 2025, 17 (03)
  • [35] Simulation of urban expansion and encroachment using cellular automata and multi-agent system model-A case study of Tianjin metropolitan region, China
    Tian, Guangjin
    Ma, Bingran
    Xu, Xinliang
    Liu, Xiaoping
    Xu, Linyu
    Liu, Xiaojuan
    Xiao, Lin
    Kong, Lingqiang
    ECOLOGICAL INDICATORS, 2016, 70 : 439 - 450
  • [36] Simulating spatial pattern of urban growth using GIS-based SLEUTH model: a case study of eastern corridor of Tehran metropolitan region, Iran
    Hashem Dadashpoor
    Mahboobeh Nateghi
    Environment, Development and Sustainability, 2017, 19 : 527 - 547
  • [37] Dynamic monitoring of land-use/land-cover change and urban expansion in Shenzhen using Landsat imagery from 1988 to 2015
    Dou, Peng
    Chen, Yangbo
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 38 (19) : 5388 - 5407
  • [38] Simulating spatial pattern of urban growth using GIS-based SLEUTH model: a case study of eastern corridor of Tehran metropolitan region, Iran
    Dadashpoor, Hashem
    Nateghi, Mahboobeh
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2017, 19 (02) : 527 - 547
  • [39] Applying object-based approach to monitor urban expansion in Ha Long city, Vietnam, during 2000-2023 from multi-date Landsat satellite imagery
    Vu, Anh Tuan
    Ngo, Duc Anh
    Nguyen, Thi Phuong Hao
    Nguyen, Cong Giang
    EUROPEAN JOURNAL OF REMOTE SENSING, 2024, 57 (01)
  • [40] Multitemporal Analysis of Soil Sealing and Land Use Changes Linked to Urban Expansion of Salamanca (Spain) Using Landsat Images and Soil Carbon Management as a Mitigating Tool for Climate Change
    Criado, Marco
    Santos-Frances, Fernando
    Martinez-Grana, Antonio
    Sanchez, Yolanda
    Merchan, Leticia
    REMOTE SENSING, 2020, 12 (07)