Assessment of forest restoration with multitemporal remote sensing imagery.

Climate variability and man-made impacts have severely damaged forests around the world in recent years, which calls for an urgent need of restoration aiming toward long-term sustainability for the forest environment. This paper proposes a new three-level decision tree (TLDT) approach to map forest, shadowy, bare and low-vegetated lands sequentially by integrating three spectral indices. TLDT requires neither image normalization nor atmospheric correction, and improves on the other methods by introducing more levels of decision tree classification with inputs from the same multispectral imagery.

A New Approach Using AHP to Generate Landslide Susceptibility Maps in the Chen-Yu-Lan Watershed, Taiwan.

This paper proposes a new approach of using the analytic hierarchy process (AHP), in which the AHP was combined with bivariate analysis and correlation statistics to evaluate the importance of the pairwise comparison. Instead of summarizing expert experience statistics to establish a scale, we then analyze the correlation between the properties of the related factors with the actual landslide data in the study area. In addition, correlation and dependence statistics are also used to analyze correlation coefficients of preparatory factors.

Development and evaluation of a genetic algorithm-based ocean color inversion model for simultaneously retrieving optical properties and bottom types in coral reef regions.

This work presents a novel approach that integrates a shallow water semi-analytical (SSA) model and a genetic algorithm (GA) to retrieve water column inherent optical properties (IOPs) and identify bottom types simultaneously from measurement of subsurface remote sensing reflectance. This GA-SSA approach is designed based on the assumption that each pixel is homogeneous with regard to the bottom type when viewed at small (centimeter) scales, and it is validated against a synthetic data set (N=11,250) that consists of five types of bottom, three levels of bottom depth, 15 concentrations of chlorophyll-a (Chl-a), and a wide range of modeled IOP variations in clear and optically complex waters representing the coral reef environment. The results indicate that the GA-SSA approach is accurate and robust in the retrieval of IOPs and its success rate in identifying the real bottom type is limited by the level of Chl-a and bottom depth.

Monitoring reservoir water quality with Formosat-2 high spatiotemporal imagery.

Water reservoirs are the primary source of freshwater for most cities around the world. To monitor the dynamic changes in reservoir water quality, however, we need an innovative platform that is able to observe the entire reservoir with both high-spatial- and high-temporal-resolution. Formosat-2 is the first commercial satellite dedicated to site surveillance with a high-spatial-resolution sensor placed in a daily revisit orbit (2 m in panchromatic and 8 m in multispectral).

Automatic extraction of ground control regions and orthorectification of remote sensing imagery.

We develop a fast and accurate method that is able to automatically select and match a large amount of ground control regions (GCRs) for orthorectifying remote sensing imagery. This new method is comprised of four modules, namely automatic extraction of GCRs, fast image-to-image matching, iterating and filtering of GCRs, and rigorous orthorectification. We assess the accuracy of this new method by processing the high-temporal- and high-spatial-resolution Formosat-2 imagery.

Surface Heat Balance Analysis of Tainan City on March 6, 2001 Using ASTER and Formosat-2 Data.

The urban heat island phenomenon occurs as a mixed result of anthropogenic heat discharge, decreased vegetation, and increased artificial impervious surfaces. To clarify the contribution of each factor to the urban heat island, it is necessary to evaluate the surface heat balance. Satellite remote sensing data of Tainan City, Taiwan, obtained from Terra ASTER and Formosat-2 were used to estimate surface heat balance in this study.

Integrating semianalytical and genetic algorithms to retrieve the constituents of water bodies from remote sensing of ocean color.

This work presents a novel GA-SA approach to retrieve the constituents of water bodies from remote sensing of ocean color. This approach is validated and compared to the existing algorithms using the same synthetic and in-situ datasets compiled by the International Ocean Color Coordinate Group. Comparing to the other methods, the GA-SA approach provides better retrievals for both the inherent optical properties and various water constituents.

Fast and accurate model of underwater scalar irradiance for stratified Case 2 waters.

This paper is devoted to the derivation of a fast and accurate model of scalar irradiance for stratified Case 2 waters. Five strategies are formulated and employed in the new model, including (1) reallocating the sky radiance, (2) approximating the influence of the air-water interface, (3) constructing a look-up table of average cosine based on the single-scattering albedo and the backscatter fraction, (4) calculating the phase function of surrogate particles in Case 2 waters, and (5) using the average cosine as an index to cope with stratified waters. A comprehensive model-to-model comparison shows that the new model runs more than 1,400 times faster than the commercially-available Hydrolight model, while it limits the percentage error to 2.

Fast and accurate model of underwater scalar irradiance.

A spectral model of scalar irradiance with depth is applied to calculations of photosynthetically available radiation for a vertically homogeneous water column. The model runs more than 14,000 times faster than the full Hydrolight code, while it limits the percentage error to 2.20% and the maximum error to less than 4.