This paper describes a method to improve a given segmentation result in order to produce a new, refined and more accurate segmented image. The method consists of three phases: shrinking of the input partitions, filtering of the input imagery leading to a mask image, and expansion of the shrunk partitions within the filtered image. The concept is illustrated for the enhancement of a land cover d...

This paper is an analytical study of the performance governing factors of the biogeography based land cover feature extraction technique which is characterized by its ability to perform differently on different natural terrain features contained in a satellite image. From the discussion, we establish the fact that the classification efficiency of BBO for a given land cover feature is inversely ...

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced ep...

A methodology is proposed for extracting information on land cover based on hyperspectral reflectance data derived from satellite image, without supervising with ground truth. The reflectance percentage, being a characteristic feature of the ground object acts as an indirect guidance to the classification and hence the method is named semi-supervised classification. It is tried with IRS LISS IV...

We investigated the Classification of satellite images and multispectral remote sensing data .we focused on uncertainty analysis in the produced land-cover maps .we proposed an efficient technique for classifying the multispectral satellite images using Support Vector Machine (SVM) into road area, building area and green area. We carried out classification in three modules namely (a) Preprocess...

Small satellites have limited payload and their attitudes are sometimes difficult to determine from the limited onboard sensors alone. Wrong attitudes lead to inaccurate map projections and measurements that require post-processing correction. In this study, we propose an automated and robust scheme that derives the satellite attitude from its observation images and known satellite position by ...

lineaments are the most important phenomena of geological exploration of hydrocarbon reservoirs . concepts in order to map the contours of land need so much time and money. one of the most famous methods in lineaments extraction is satellite image processing. in this paper, an overview of lineament extraction methods and a new method based on canny edge detection algorithm is raised. the result...

Orthogonal subspace projection (OSP) approach has shown success in hyperspectral image classification. Recently, the feasibility of applying OSP to multispectral image classification was also demonstrated via SPOT (Satellite Pour 1'Observation de la Terra) and Landsat (Land Satellite) images. Since an MR (magnetic resonance) image sequence is also acquired by multiple spectral channels (bands),...

Geomatics is a useful new term for the use of advanced information technologies for the recording, storage, manipulation and analysis of geographical imagery. It includes remote sensing, global positioning systems and computer-based image manipulation and analysis. While high technology geomatics has tended to concentrate analytical power, recently developed, affordable systems now permit land-...

This paper aims to introduce and discuss six challenges and issues facing the development of SDIs which will be able to meet the sustainable development objectives of society. These issues and challenges include: SDI to facilitate spatially enabled government Role of government, private and academic sectors Development of SDI vision, mission and road map – where are we heading? SDI to facilitat...