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...

Currently, observations of an agricultural land system (ALS) largely depend on remotely-sensed images, focusing on its biophysical features. While social surveys capture the socioeconomic features, the information was inadequately integrated with the biophysical features of an ALS and the applications are limited due to the issues of cost and efficiency to carry out such detailed and comparable...

Polar areas are the most sensitive targets of climate change. From this perspective, continuous monitoring cryosphere represents a critical need, which, now, we can only partially supply with specific satellite missions. The integration between remote-sensed multi-spectral images and field data is crucial to validate retrieval algorithms climatological models. optical behavior snow, at differen...

Analysis of the multi–spectral remotely sensed images of the areas destructed by an earthquake is proved to be a helpful tool for construction assessments. In this paper, we propose a new fast and reliable fuzzy change detection method for multi–spectral images. The proposed fuzzy change detection method is mathematically and experimentally investigated and shown to be efficient and effective.

Change Detection using multi-temporal satellite images of same area is an established as well as actively pursued research problem. Most of the change detection techniques use algebraic or transform methods to do a pixel by pixel comparison of change detection. These techniques heavily depend upon the correct choice of threshold value to segregate the real changed pixels from the apparent chang...

Shape analysis has not been considered in remote sensing as extensively as in other pattern recognition applications. However, shapes such as those of geometric patterns in agriculture and irregular boundaries of lakes can be extracted from the remotely sensed imagery even at relatively coarse spatial resolutions. This paper presents a procedure for efficiently retrieving and representing shape...

The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar) images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four opt...

Biodiversity is important in maintaining ecosystem viability, and the availability of adequate biodiversity data is a prerequisite for the sustainable management of natural resources. As such, there is a clear need to map biodiversity at high spatial resolutions across large areas. Airborne and spaceborne optical remote sensing is a potential tool to provide such biodiversity data. The spectral...

Tropical Storm Debby brought severe flooding to portions of southwestern Florida during the summer of 2012. Remotely-sensed images were collected to document the flooding and test the results of Hydrologic and Hydraulic (H & H) storm water models constructed by the Southwest Florida Water Management District (SWFWMD). One image, a satellite, multi-band SPOT image was provided to the SWFWMD by t...