We present a methodology to detect terrain mobilization in the years following a fire using multitemporal Landsat TM imagery. Furthermore, we show the spectral evolution of the land cover since fire occurrence, and analyze the feasibility of detecting the type of land cover a number of years after fire occurrence. The methodology developed here is a spectral change identification technique base...

Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those requ...

This study aims to provide trypanosomiasis-affected countries with standardized datasets and methodologies for mapping the habitat of the tsetse fly (Glossina spp., the disease vector) by customizing and integrating state-of-the-art land cover maps on different spatial scales. Using a combination of inductive and deductive approaches, land cover and fly distribution maps are analysed in a geogr...

Remotely sensed multi-spectral and -spatial data facilitates the study of mosquito-borne disease vectors and their response to land use and cover composition in the urban environment. In this study we assess the feasibility of integrating remotely sensed multispectral reflectance data and LiDAR (Light Detection and Ranging)-derived height information to improve land use and land cover classific...

during the time, land cover and as a result land use patterns go through fundamental changes and human factors can have the most important role in this process. knowing these changes could be of great help to the future management of this region. according to this, the main purpose of this study is to monitor the land use-cover changes in the hamedan province area during the three recent decade...

Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory’s climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysic...

An artificial neural network is a system based on the operation of biological neural networks, in other words, is an emulation of biological neural system. Artificial Neural Networks or simply Neural Networks are powerful general purpose computing tools. They have become popular in the analysis of remotely sensed data, particularly in classification or feature extraction from image data more ac...

Land-cover and climate change are both expected to alter species distributions and contribute to future biodiversity loss. However, the combined effects of land-cover and climate change on assemblages, especially at the landscape scale, remain understudied. Lowland tropical amphibians may be particularly susceptible to changes in land cover and climate warming because many species have narrow t...

ocal and regional land-use and land-cover change is an important ingredient in the larger problem of global environmental change. Land-use patterns, driven by a variety of social processes, result in land-cover changes that affect biodiversity, water and radiation budgets, trace-gas emissions, and other factors that, cumulatively, alter the global climate and biosphere. Most research on global ...