Urban growth detection of Jilin City using multi-temporal remote sensing

Yunfei Bao; Shengbo Chen; Linda Meng

doi:10.1117/12.651399

2 December 2005 Urban growth detection of Jilin City using multi-temporal remote sensing

Yunfei Bao, Shengbo Chen, Linda Meng

Proceedings Volume 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications; 604525 (2005) https://doi.org/10.1117/12.651399
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China

Abstract

Urban land use/land cover patterns change rapidly in response to economic, social, and environmental forces. Remote sensing offers an important means of detecting and analyzing temporal changes occurring in urban area. Effective detection of urban change using remote sensing data is essential for urban environmental research, urban planning, and natural resources management. Jilin City is the second biggest city in Jilin Province, Northeast China. Recently, Jilin City has been grown quickly with the economic development. As an example, the growth of Jilin City is detected using multi-temporal Landsat Thematic Mapper (TM) data acquired on 25 October 1987 and 30 August 1996, and Landsat Enhanced Thermatic Mapper plus (ETM +) data acquired on 18 September 2000. Many digital algorithms have been developed for change detecting purposes. These include image overlay, image differencing, image regression, image ratioing, vegetation index differencing, principal components analysis, and so on. Four change detection techniques (image differencing, image regression, Kauth-Thomas transformation, and Chi square transformation) were examined in Jilin City with the aforementioned Landsat TM/ETM+ data. Sixteen change images of Jilin City were achieved with different accuracies of urban growth by these four change detection techniques. And the regression and differencing of TM/ETM + band 3 images are the most accurate for urban growth detection. Therefore, the image differencing technique was performed to get two urban growth images of Jilin City during the period of 1987-1996 and 1996-2000 using TM/ETM + band 3 images in 1987, 1996, and 2000. To be surprised, the Jilin City in the period of 1987-1996 grew as quick as it in the period of 1996-2000.

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Yunfei Bao, Shengbo Chen, and Linda Meng "Urban growth detection of Jilin City using multi-temporal remote sensing", Proc. SPIE 6045, MIPPR 2005: Geospatial Information, Data Mining, and Applications, 604525 (2 December 2005); https://doi.org/10.1117/12.651399

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KEYWORDS

Earth observing sensors

Landsat

Remote sensing

Data acquisition

Environmental sensing

Algorithm development

Detection and tracking algorithms

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