Land use and environmental change analysis based on remote sensing: a case study of upper stream management of Hsin-Dian River

Wei-Chi Chen; Chih-Heng Liu; Mei-Hsin Chen; Tine-Yin Chou

doi:10.1117/12.812710

5 November 2008 Land use and environmental change analysis based on remote sensing: a case study of upper stream management of Hsin-Dian River

Wei-Chi Chen, Chih-Heng Liu, Mei-Hsin Chen, Tine-Yin Chou

Author Affiliations +

Proceedings Volume 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics; 71440K (2008) https://doi.org/10.1117/12.812710
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

Taipei Water Source Domain is established to protecting the water source which supplied approximately 5 million populations in the large Taipei living area to avoid destroy and pollution. Therefore, land management of water source domain becomes the key point to prevent these problems. Using the remote sensing technology to manage the land use is the major target in this research. We employed Supervised Classifier to classify the land use and land cover type. We utilize spatial analysis to investigate the current land use condition and employ post-classification comparison algorithm for land use types' change analysis. The classification overall accuracy of 2006 is 95.60%. The result of environmental change detection analysis of land use categories shows that vegetation goes through three period's growth tendency. However, the change analysis through 1998 to 2006 points out the area near Hsin-Dian and Ping-Lin had a magnitude change.

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Wei-Chi Chen, Chih-Heng Liu, Mei-Hsin Chen, and Tine-Yin Chou "Land use and environmental change analysis based on remote sensing: a case study of upper stream management of Hsin-Dian River", Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 71440K (5 November 2008); https://doi.org/10.1117/12.812710

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KEYWORDS

Image classification

Vegetation

Earth observing sensors

Satellite imaging

Satellites

Environmental sensing

Clouds

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