Monitoring and simulating urban sprawl and its effects on land-use patterns and hydrological processes in urbanized watersheds are essential in land-use and water-resource planning and management. This study applies a novel framework to the urban growth model Slope, Land use, Excluded land, Urban extent, Transportation, and Hillshading (SLEUTH) and land-use change with the Conversion of Land use and its Effects (CLUE-s) model using historical SPOT images to predict urban sprawl in the Paochiao watershed in Taipei County, Taiwan. The historical and predicted land-use data was input into Patch Analyst to obtain landscape metrics. This data was also input to the Generalized Watershed Loading Function (GWLF) model to analyze the effects of future urban sprawl on the land-use patterns and watershed hydrology. The landscape metrics of the historical SPOT images show that land-use patterns changed between 1990–2000. The SLEUTH model accurately simulated historical land-use patterns and urban sprawl in the Paochiao watershed, and simulated future clustered land-use patterns (2001–2025). The CLUE-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 SLEUTH and CLUE-s models show the significant impact urban sprawl will have on land-use patterns in the Paochiao watershed. The historical and predicted land-use patterns in the watershed tended to fragment, had regular shapes and interspersion patterns, but were relatively less isolated in 2001–2025 and less interspersed from 2005–2025 compared with land-use pattern in 1990. During the study, the variability and magnitude of hydrological components based on the historical and predicted land-use patterns were cumulatively affected by urban sprawl in the watershed; specifically, surface runoff increased significantly by 22.0% and baseflow decreased by 18.0% during 1990–2025. The proposed approach is an effective means of enhancing land-use monitoring and management of urbanized watersheds.

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In Taiwan, earthquakes have long been recognized as a major cause of landslides that are wide spread by floods brought by typhoons followed. Distinguishing between landslide spatial patterns in different disturbance regimes is fundamental for disaster monitoring, management, and land-cover restoration. To circumscribe landslides, this study adopts the normalized difference vegetation index (NDVI), which can be determined by simply applying mathematical operations of near-infrared and visible-red spectral data immediately after remotely sensed data is acquired. In real-time disaster monitoring, the NDVI is more effective than using land-cover classifications generated from remotely sensed data as land-cover classification tasks are extremely time consuming. Directional two-dimensional (2D) wavelet analysis has an advantage over traditional spectrum analysis in that it determines localized variations along a specific direction when identifying dominant modes of change, and where those modes are located in multi-temporal remotely sensed images. Open geospatial techniques comprise a series of solutions developed based on Open Geospatial Consortium specifications that can be applied to encode data for interoperability and develop an open geospatial service for sharing data. This study presents a novel approach and framework that uses directional 2D wavelet analysis of real-time NDVI images to effectively identify landslide patterns and share resulting patterns via open geospatial techniques. As a case study, this study analyzed NDVI images derived from SPOT HRV images before and after the ChiChi earthquake (7.3 on the Richter scale) that hit the Chenyulan basin in Taiwan, as well as images after two large typhoons (xangsane and Toraji) to delineate the spatial patterns of landslides caused by major disturbances. Disturbed spatial patterns of landslides that followed these events were successfully delineated using 2D wavelet analysis, and results of pattern recognitions of landslides were distributed simultaneously to other agents using geography markup language. Real-time information allows successive platforms (agents; to work with local geospatial data for disaster management. Furthermore, the proposed is suitable for detecting landslides in various regions on continental, regional, and local scales using remotely sensed data in various resolutions derived from SPOT HRV, IKONOS, and QuickBird multispectral images.

This study uses Ordinary Kriging (OK), Sequential Gaussian Simulation (SGS) and Simulated Annealing Simulation (SAS) to relocate the completely heterotopic dataset from the locations of the Standardized Satellite Oriented Control Point System (SSOCPS) stations to the Groundwater Monitoring Networks (GMNS) stations and factorial kriging to analyze and map relationships among seven variables, including the hydraulic conductivities of three aquifers, the vertical displacements of the ground and groundwater level changes in the wells of three aquifers, and also to delineate the anomalies of multi-scale spatial variation of hydrogeological properties associated with the ChiChi earthquake, measuring 7.3 on the Richter scale, in the ChouShui River alluvial fan in Taiwan. In this study, the anomalies of spatial variation of hydrogeological properties associated with the earthquake are illustrated at micro, local and regional scales of 9, 12 and 36 km, respectively. In the study area, regionalization components associated with variation at local and regional scales are obtained and mapped by factorial kriging. Factorial Kriging Analysis (FKA) also demonstrated that the main effects of the ChiChi earthquake on the spatial variations of groundwater hydrological changes include porous media compression at micro scale, hydrogeological heterogeneousness of the sediments within the aquifer at local scale and the cyclic loading of deviatoric stress at regional scale. Finally, maps of spatial variations of regional components fully depicted all of the anomalies of spatial variation of hydrogeological changes due to the ChiChi earthquake and can be used to identify, confirm and monitor the hydrogeological properties in this study area.

Hypoxia and light illumination can both decrease oxygen consumption in the photoreceptor layers. The purpose of the present study was to investigate whether the mutual effects of hypoxia and intense illumination to the photoreceptors are additive. The a-wave of flash electroretinogram (fERG) was recorded to indirectly measure the photoreceptors function under given conditions. Six normal healthy subjects, mean age 34.0 ± 3.8 years, all of whom had high-altitude (>3,000 m) mountain hiking experience, were recruited for the study. Flash a-wave electroretinography was examined under four conditions: (1) normal (D/N); (2) systemic hypoxia induced by inhaling a mixture of O(2) and N(2) gases, which caused oxyhemoglobin saturation (SaO(2)) ≈ 80% (D/H); (3) intense light illumination, which resulted in photoreceptor bleaching (B/N); and (4) a combination of conditions b and c (B/H). Thirty light stimuli, each with a 20-ms ON and 1,980-ms OFF cycle, were given and ERG performed to probe the photoreceptor function. The results showed that a-wave at the various conditions did not respond to all stimuli. The average a-wave amplitudes were 91.4 ± 46.5, 22.8 ± 42.5, 15.5 ± 28.9, and 35.2 ± 41.1 μV for D/N, D/H, B/N, and B/H, respectively. Nonparametric Friedman test for a-wave amplitude indicated that significant differences occurred in D/N-D/H, D/N-B/N, D/N-B/H, D/H-B/H, and B/N-B/H (all p values were <0.001, but D/H-B/N was 0.264). Thus, systemic hypoxia or strong illumination to the retina can cause an absence of the ERG a-wave or change its response, although individual differences were observed. In this study, systemic hypoxia appeared to reduce photoreceptor bleaching, an interesting finding in itself. The mechanisms underlying the disappearance of the ERG a-wave following hypoxia or intense illumination to the photoreceptors seem to differ.