Urbanization is significantly increasing in Taiwan recently because of economic development. The basin Yan-Shoei creek is chosen as the study area to investigate the influence of urbanizing on runoff hydrograph and flood storage ability. 1972 LANDSAT MSS and 2000 SPOT satellite imageries are applied to identify the land use types by using the method that the image was classified by sub-pixel and supervised classification after the thematic maps were first cut off. The results showed building area increases about 1600 acres from 1972 to 2000. Due to the terrain of study area contains flat area and mountains; we tried to connect the tank model for flat area with the grid-based distributed rainfall-runoff model, which is based on kinematic wave approach for hilly area. Calibration from 12 storm events concluded that the model proposed in this work can well simulate the rainfall-runoff relationship. The model is further applied to investigate the impact of land use change on runoff. The return period 10-year flood was found to be increased around 10%, which reveals that changes the probability of flooding. The adaptation measures are necessarily proposed to reduce damage.

Simulation of extreme rainfall-runoff events is the key issue for flood mitigation. The accuracy of flood forecasting driven by models is usually dependent on whether the upstream precipitation information is sufficient or not. In the past, such information was provided by ground measurements. The development of remotely sensed technology enables researchers to realize the spatial distribution of rainfall. Remote sensing data provide more useful information than ground measurements. The GA was applied to merging different precipitation products through various input combinations. Finally, the ANFIS was conducted to build three quantitative precipitation forecast models by feeding different input combinations, which are1) three precipitation products, 2) merged precipitation generated by QPESUMS and ground measurements, and 3) merged precipitation generated by PERSIANN-CCS, QPESUMS and ground measurements, respectively. The improvement rate of model 3) over model 1) for quantitative precipitation forecast is 28% at t+1.The results show the model merging ground measurements, QPESUMS and PERSIANN-CCS produced the best precision for quantitative precipitation forecast.

Taiwan ranks top one of the world in the ratios of population and area that are threatened by more than three natural disasters. Among various types of disasters, the landslide occurred in mountainous areas is the major one. To gain an insight of the mechanism and the long-term trend of landslide, we need a detailed landslide inventory of Taiwan generated from the same source of data, using the same interpreting method, with a comparable precision. Formosat-2 images of Taiwan area taken from 2005 to 2012 are processed by Formosat-2 automatic image processing system (F-2 AIPS). This system is able to digest the raw data of Gerald format, apply the basic radiometric and geometric correction, output the level-1A product, conduct the rigorous band-to-band coregistration, automatic orthorectification, multi-temporal image geometrical registration, multi-temporal image radiometric normalization, spectral summation intensity modulation pan-sharpening, edge enhancement and adaptive contrast enhancement, and the absolute radiometric calibration. The expert landslide and shaded area delineation system (ELSADS) is then used to produce the shadow and landslide inventory. Based on the concept of minimum catchment, all landslide polygons are grouped to investigate their annual variations. The accuracy of landslide inventory is carefully validated with the manual interpretations from aerial images (25cm), and the mean accuracy is 98%.

Total Suspended Matter (TSM) concentration in nearshore waters plays a very important role to the coastal water quality management, oceanic primary production and coral reef conservation. However, traditional approach provides limited information in terms of spatial and temporal coverage for monitoring TSM concentration in nearshore waters. The MODerate resolution Imaging Spectroradiometers (MODIS) on board Terra and Aqua satellite can provide abundant spectral information for rigorous atmospheric correction and retrieving TSM concentrations from the observation of ocean color in a large scale (250 m resolution). With the advantage of daily-revisit characteristics of Formosat-2 satellite (FS-2), the Remote Sensing Instrument (RSI) onboard FS-2 provide high-tempospatial data (8 m resolution), however, insufficient spectral information to resolve the water color. With an intention to well understand the dynamic and spatial patterns of TSM concentration in the Goaping river, this study presents a multi-satellite sensor approach that integrate both the advantage of MODIS and RSI to generate high resolution map of TSM concentration on FS-2 imagery. Firstly, a 250m resolution TSM regression model named MODIS-GP-TSM was established using MODIS Band 1 reflectance and concurrent TSM concentration measured at Gaoping River mouth. Secondly, with the TSM data derived from two MODIS images and MODIS-GP-TSM, an 8m resolution TSM retrieval model named FS2-GP-TSM was developed on the corresponding FS-2 images. The FS2-GP-TSM was verified to another set of field data taken from the river mouth to Lamey Island, with a good agreement between derived and observed TSM concentrations. This study encourages the use of multi-satellite approaches to extend the application of the FS-2 imagery on monitoring costal and nearshore waters where high resolution information is required.

Tropical countries nowadays are at the economic developing stage. They are facing the rapid land use/ land cover change and increasing water demand for agriculture and industry. Therefore, hydrological issue becomes more and more important in these regions than ever before. In this study, we used thermal inertia approach with remote sensing technique to estimate the root zone soil moisture content, which plays a key role of hydrological cycle, in the tropical watershed of northern Thailand. The main purposes are focused on monitoring soil moisture content change which is part of an alert system for water supply and understanding the water distribution pattern corresponding to above land cover type and that is useful for land-use planning in the future. We analyzed different depths including 10cm, 100cm and 200cm root zone soil moisture contents (SMC) derived from the modified apparent thermal inertia approach (ATI) with Moderate Resolution Imaging Spectroradiometer (MODIS) imagery from 2002 to 2009. The results showed that the Pearson correlation coefficient and Nash-Sutcliffe efficiency coefficient between ground truth and retrieved SMC under all different land cover sites for three depths were respective above 0.80, 0.84, 084 and 0.57, 0.537, 0.492. The retrieved precision referred to Root Mean Square Error (RMSE) value were 0.055, 0.025 and 0.029 (m3. m-3) for respective three depths. The 100cm depth root zone SMC showed the optimal estimation in response to the upper precipitation characteristics and various land cover types. The successful root zone SMC estimation by using optical remote sensing data will still have a strong contribution for the tropical or subtropical mountain studies in the future.