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.
Highlights
Understanding how land-use changes are associated with growth demands and the desire to preserve natural resources is critical to building livable [1] and sustainable environments
Statistical matrices of goodness-of-fit (Table 1), for SLEUTH modeling in this study were 0.94, 0.64, 0.93, 0.92, 0.71, and 0.91 for metrics of Compare, Population, Edges, Clusters, Lee-Sallee, and F-Match, respectively
This phenomenon indicates that the SLUETH model, which simulates urban sprawl based on regulating the state of grid cells in the vicinity of land-uses
Summary
Understanding how land-use changes are associated with growth demands and the desire to preserve natural resources is critical to building livable [1] and sustainable environments. Urban sprawl is a special land-use change [2] which must be monitored and predicted to preserve natural resources in urbanized areas. Effectively monitoring and simulating urban sprawl and its effects on land-use patterns and hydrological processes in an urbanized watershed are essential to effective land-use and water resource planning and management. Remote sensing techniques have already shown their value in mapping urban areas, and as data sources for analyzing and modeling urban growth and land-use change [3,4,5,6] and hydrology. An integrated approach coupled with urban sprawl and hydrological modeling using remote sensing data that simulates and assess land-use changes, land-use patterns and their effects on hydrological processes at the watershed level is crucial to land-use and water resource planning and management in an urbanized watershed
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