Remote sensing represents a powerful tool to derive quantitative and qualitative information about ecosystem biodiversity. In particular, since plant species richness is a fundamental indicator of biodiversity at the community and regional scales, attempts were made to predict species richness (spatial heterogeneity) by means of spectral heterogeneity. The possibility of using spectral variance...

Merging of different data sets is often used in digital image processing to improve the visual and analytical quality of the data. The analyst may need to merge different types of data. In this process, different data such as satellite imagery from the same sensor but with different resolution, satellite imagery from different sensors with varying resolution, digitized aerial photography and sa...

We provide and evalúate a fusión algorithm of remotely sensed images, i.e. the fusión of a panchromatic (PAN) image with a multi-spectral (MS) image using bilateral filtering, applied to images of three different sensors: SPOT 5, Landsat ETM+ and Quickbird. To assess the fusión process, we use six quality indexes, that confirm, along with visual analysis, good overall results for the three sens...

This paper presents a comparison of Earth Observing 1 (EO-1) Advanced Land Imager (ALI) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) images collected over an agricultural region in northwest Mexico. Across 115 fields with a range of cover types, radiance measurements collected by ALI were within 3% of ETM+ for all five common bands. Crop discrimination was significantly improved with ALI ...

The analysis of rapid environment changes requires orbital sensors with high frequency of data acquisition to minimize cloud interference in the study of dynamic processes such as Amazon tropical deforestation. Moreover, a medium to high spatial resolution data is required due to the nature and complexity of variables involved in the process. In this paper we describe a multiresolution multitem...

Based on canonical correlation analysis the iteratively re-weighted multivariate alteration detection (MAD) method is used to successfully perform unsupervised change detection in bi-temporal Landsat ETM+ images covering an area with villages, woods, agricultural fields and open pit mines in North RhineWestphalia, Germany. A link to an example with ASTER data to detect change with the same meth...

Given quantization and clustering classification of the deviations between TM and ETM+ multibandwidth images based on approved thresholds, a calibration algorithm for the correlation coefficient in multi-bandwidth images is suggested in this paper. This experiment detected strong and proportional correlation relationship between the highest area of land surface temperature and the lowest area o...

A new super resolution Bayesian method for pansharpening multispectral images which incorporates sensor characteristics to model the observation process of both the panchromatic and the multispectral images is presented in this paper. The quality of the pansharpened images is assessed both qualitatively and quantitatively. Preliminary results are very promising: the method succeeded in preservi...

In Beijing, some crop field is similar to urbanized area in spectral space of ETM+ image, and this is an obstacle to extract urbanized area of Beijing from ETM+ image. Furthermore, classical texture such as variance can not improve the seperability of such two landcovers. This article proposed a skewness based framework to extract the profile of urbanized area, while skewness was seldom applied...

The present work aims at identifying favorable locations for groundwater resources harvesting and extraction along the Wadi Feiran basin, SW Sinai Peninsula, Egypt, in an effort to facilitate new development projects in this area. Landsat ETM+, Radarsat-1 and PALSAR images of Wadi Feiran basin were used in this work to perform multisource data fusion and texture analysis, in order to classify t...