Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model

Yu-Pin Lin; Yun-Bin Lin; Yen-Tan Wang; Nien-Ming Hong

doi:10.3390/s8020658

Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model

Sensors (Basel). 2008 Feb 4;8(2):658-680. doi: 10.3390/s8020658.

Authors

Yu-Pin Lin¹, Yun-Bin Lin², Yen-Tan Wang³, Nien-Ming Hong⁴

Affiliations

¹ Bioenvironmental Systems Engineering Department, National Taiwan University, 1, Sec. 4, Roosevelt Rd., Da-an District, Taipei City 106, Taiwan. yplin@ntu.edu.tw.
² Recreation and Health-care Management Department, Chianan University of Pharmacy and Science, 60, Sec. 1, Erren Rd., Rende Shiang, Tainan County 71710, Taiwan. yblin@mail.chna.edu.tw.
³ Bioenvironmental Systems Engineering Department, National Taiwan University, 1, Sec. 4, Roosevelt Rd., Da-an District, Taipei City 106, Taiwan.
⁴ Department of Environmental Resources Management, The Overseas Chinese Institute of Technology, No. 100, Chiao Kwang Rd., Taichung 407, Taiwan. hong@ocit.edu.tw.

Abstract

Monitoring and simulating urban sprawl and its effects on land-use patterns andhydrological processes in urbanized watersheds are essential in land-use and waterresourceplanning and management. This study applies a novel framework to the urbangrowth model Slope, Land use, Excluded land, Urban extent, Transportation, andHillshading (SLEUTH) and land-use change with the Conversion of Land use and itsEffects (CLUE-s) model using historical SPOT images to predict urban sprawl in thePaochiao watershed in Taipei County, Taiwan. The historical and predicted land-use datawas input into Patch Analyst to obtain landscape metrics. This data was also input to theGeneralized Watershed Loading Function (GWLF) model to analyze the effects of futureurban sprawl on the land-use patterns and watershed hydrology. The landscape metrics ofthe historical SPOT images show that land-use patterns changed between 1990-2000. TheSLEUTH model accurately simulated historical land-use patterns and urban sprawl in thePaochiao watershed, and simulated future clustered land-use patterns (2001-2025). TheCLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTHand CLUE-s models show the significant impact urban sprawl will have on land-usepatterns in the Paochiao watershed. The historical and predicted land-use patterns in thewatershed tended to fragment, had regular shapes and interspersion patterns, but wererelatively less isolated in 2001-2025 and less interspersed from 2005-2025 compared withland-use pattern in 1990. During the study, the variability and magnitude of hydrologicalcomponents based on the historical and predicted land-use patterns were cumulativelyaffected by urban sprawl in the watershed; specifically, surface runoff increasedsignificantly by 22.0% and baseflow decreased by 18.0% during 1990-2025. The proposedapproach is an effective means of enhancing land-use monitoring and management ofurbanized watersheds.

Keywords: Assessment; hydrological modeling; land-use change modeling; landscape ecology; remote sensing data; watershed land-use management.