The overall objective of our research project is to understand the spatial inequality in health in Accra, the capital city of Ghana. We also utilize GIS technology to measure the association of adverse health and mortality outcomes with neighborhood ecology. We approached this in variety of ways, including multivariate analysis of imagery classification and census data. A key element in the res...

Web-based applications that integrate geospatial information, or the geoweb, offer exciting opportunities for remote sensing science. One such application is a Web-based system for automating the collection of reference data for producing and verifying the accuracy of land-use/land-cover (LULC) maps derived from satellite imagery. Here we describe the capabilities and technical components of th...

The problem due to differential terrain illumination on satellite imagery is experienced by most of areas which are on mountainous terrain. This may cause variations in reflectance of similar ground features which lead to a misclassification of land cover classes due to different topographic positions. This phenomenon most commonly occurred in the areas which are located on southern and norther...

Although satellite images were extensively used for the manual synoptic work since they became available, and a lot of rules and conceptual models were developed in order to allow a physical correct interpretation of these data, there are also in the time being analyses distributed by Met Centres which are obviously based on a over-simplified use of the imagery. That refers especially to surfac...

The panchromatic bands of Landsat 7, SPOT, and IRS satellite imagery provide an opportunity to evaluate the effectiveness of texture analysis of satellite imagery for mapping of land uselcover, especially forest cover. A variety of texture algorithms, including standard deviation, Ryherd-Woodcock minimum variance adaptive window, low pass etc., were applied to moving 3x3 and 7x7 pixel windows. ...

At the Naval Research Laboratory progress continues to be made in the development of an automated system, named SIAS (Satellite Image Analysis System), for the interpretation of satellite imagery (Peak and Tag, 1994a). Presented here is a report on the developments specifically related to the cloud pattern identification portion of SIAS (Bankert, 1994a). Recent developments include computation ...

1.1 Context With the development of new satellite systems and the accessibility of data from public through web services like Google Earth, remote sensing imagery, knows today an important growing which advanced and still advances researches in this area on different aspects. Especially in cartography, many studies have been conducted for multi-source satellite images classification. These stud...

The automatic interpretation of aerial and satellite imagery is one of the main research tasks in photogrammetry and related disciplines. The primary goal is the automatic extraction of visible, spatial, topographic objects from imagery. The extracted objects are one possible input for updating or creating geographic data bases. In order to simplify the task, automatic image interpretation was ...

Many image segmentation algorithms are available but most of them are not fit for interpretation of satellite images. Mean-shift algorithm has been used in many recent researches as a promising image segmentation technique, which has the speed at O(kn2) where n is the number of data points and k is the number of average iteration steps for each data point. This method computes using a brute-for...

The aim of this work was to develop a system based on modular neural networks and multi-feature texture analysis that will facilitate the automated interpretation of cloud images. This will speed up the interpretation process and provide continuity in the application of satellite imagery for weather forecasting. A series of infrared satellite images from the Geostationary satellite METEOSAT7 we...