The Cerro Grande/Los Alamos forest fire devastated over 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos and the adjoining Los Alamos National Laboratory. The need to measure the continuing impact of the fire on the local environment has led to the application of a number of remote sensing technologies. During and after the fire, remote-sens...

An ever increasing population associated with various other factors has put tremendous pressure on the environment and its respective resources. Hence it has become necessary to study the human interactions with its surrounding environment to facilitate sustainable developmental plans. Land use and land cover is the most dominant factor to study these interactions. Remote Sensing technology has...

Digital image classification is generally performed to produce land cover maps from remote sensing data, particularly for large areas. The performance of image classifiers that utilize only the remote sensing data may deteriorate, especially in mountainous regions, due to the presence of shadows of high peaks. In this study, a multisource classification approach to map land cover in Himalayan r...

Land cover is a critical variable in epidemiology and can be characterized remotely. A framework is used to describe both the links between land cover and radiation recorded in a remotely sensed image, and the links between land cover and the disease carried by vectors. The framework is then used to explore the issues involved when moving from remotely sensed imagery to land cover and then to v...

Fuzzy methods in remote sensing have received growing interest for their particular value in situations where the geographical phenomena are inherently fuzzy. A fuzzy approach is investigated for the classi® cation of sub-urban land cover from remote sensing imagery and the evaluation of classi® cation accuracy. Under the fuzzy strategy, fuzziness, intrinsic to both remotely sensed data and gro...

In Australia, remotely sensed Landsat data is routinely used for mapping and monitoring changes in the extent of woody perennial vegetation. Time series remotely sensed satellite imagery and ground information is used to form multi-temporal classifications of presence/absence of woody cover. Two broad-scale operational land cover change and monitoring projects are based on a series of algorithm...

remote sensing and aerial photographs are used to produce medium to small scale images. however, for detailed information especially to estimate rangeland vegetation canopy cover there is a need to larger scale images. it is therefore necessary to study the technical applicability of different devices such as short range light airplanes, kites, gliders and balloons. in this research, we focused...

This article discusses how computational intelligence techniques are applied to fuse spectral images into a higher level image of land cover distribution for remote sensing, specifically for satellite image classification. We compare a fuzzy-inference method with two other computational intelligence methods, decision trees and neural networks, using a case study of land cover classification fro...

Change detection is the measure of the distinct data framework and thematic change information that can guide to more tangible insights into underlying process involving land cover and land use changes than the information obtained from continuous change. Digital change detection is the process that helps in determining the changes associated with landuse and land cover properties with referenc...