Aerosol Optical Depth (AOD) is an important indicator of air quality. Through satellite observation, we can obtain comprehensive information on AOD in broad spatial distribution. Since the characteristics of aerosols are both short-lived and regional, the research aim to revise the Spatial-Temporal Adaptive Reflectance Fusion Model (STARFM) to get high spatial and temporal resolution images at top of atmosphere. Moreover, we use an algorithm called Simultaneous Radiation Solution (SRS) to retrieve AOD. To correct the limitation of SRS, which is only applicable for low surface reflectance area, we modify the SRS in this research and further apply it on a higher surface reflectance area. In short, we get high spatial and temporal AOD information through STARFM and SRS. After applying the improved high spatial and temporal algorithm on air pollution events in Taiwan, the result shows well consistence of spatial distribution with MODIS Dark Target AOD product in 3km resolution and similar trend with AOD retrieved from ground based AERONET data. The validation of AOD retrievals showed that there are 63% and 80% of retrieved AOD for each case located in expected error respectively. It indicates that the proposed approach equips with the high potential for providing AOD with both high spatial resolution and high temporal resolution from satellite observations.

Since the fisheye lens has its own specific type of imaging formation, using collinearity equation attached by additional lens distortion parameters cannot set up a sufficient model. To achieve the relevant requirements of the metric measurement, this study adopts the rigorous object-image corresponding model to include geometric projection model for fisheye lens calibration. The discrepancy between the ideal image point and the actual image point is treated as the effect of lens distortion and modeled by additional parameters. This study aims to tackle effective implementation. It is revealed from the experimental results that the object-to-image correspondence of fisheye lens based on the proposed model offers satisfactory geometric calibration quality. Strategically, the bundle adjustment with self-calibration for fisheye lens can be realized under sub-pixel image measurement quality at the expense of only 20 well-distributed coded targets and acquiring two images at appropriate locations to achieve the sub-pixel level of object point positioning. Thus, it is verified that the proposed methods and procedures can effectively and accurately implement the fisheye lens calibration. At the same time, the calibration result is also sufficient to support the mission of object point determination up to sub-pixel level quality.

With the gradual maturity of geographic information system (GIS) technology, through the combination of GIS and historical data, the study of humanities and society in small-scale spatial regions is more common, but the spatial relationship between various regions in Tainan County is rarely discussed. Therefore, this research digitized the built-up area of Tainan County identified in the 1904 and 1989 historical topographic maps through the WMTS service function of the "Taiwan Centurial Historical Map" developed by the Academia Sinica. Then customize the different types of built-up areas as the basic data for the method of spatial analysis, landscape pattern analysis, and correlation analysis. This research method used kernel density estimation and hotspot analysis to explore the spatial distribution characteristics and differences of the built-up areas in each region. Besides, the landscape metrics can be used to calculate the number, area, spatial scale and type characteristics of the patch of the built-up areas. Also, the correlation strength and significance between the use of historical statistics and the analysis of analytical results have led to a more explanatory power in the discussion. In conclusion, the built-up areas in the eastern part of Tainan County are generally small and fragmented cold spots, while the western plains are hot spots with large areas. Moreover, the built-up area is highly correlated with the building land of the historical statistical data, indicating that the historical image has high explanatory power for various types of analysis.

Interferometric Synthetic Aperture Radar (InSAR) is one of the techniques used to extract three-dimensional ground surface information from the phase data recorded in radar images. InSAR technique is often applied to generate digital elevation models (DEMs). Although this technique has been developed maturely for a long time, it is found that the capability to produce high-accuracy DEM is limited. There are two aims in our research: the first is the discussion of using different seasonal dataset to generate DEMs, and the second is the observation the necessity of using multi-look processing in InSAR processing procedure. The result has shown that no matter if the multi-look processing is applied, using winter image pair is helpful to improve the accuracy up to 66.57%. For summer image pair, the accuracy could be enhanced by 15.14% to 31.59% if multi-look processing is applied, while for winter pair, the accuracy is degraded up to 23.17% if multi-look processing is applied.