Remote Sensing (RS) and Geographic Information System (GIS) have been established as indispensable tools in the assessment of Land use / cover (LULC) change. RS GIS are important for monitoring, modelling mapping land changes across a range spatial temporal scales, order to assess extent, direction, causes, effects changes. Change detection has provided suitable wide-ranging information various...

Wind erosion is a complex process influenced by different factors. Most of these factors are stable over time, but land use/cover and land management practices are changing gradually. Therefore, this research investigates the impact of changing land use/cover and land management on wind erosion potential in southern Iran. We used remote sensing data (Landsat ETM+ and Landsat 8 imagery of 2004 a...

Impervious surface area (ISA) is a key factor for monitoring urban environment and land development. Automatic mapping of impervious surfaces has attracted growing attention in recent years. Spectral built-up indices are considered promising to map ISA distributions due to their easy, parameter-free implementations. This study explores the potentials of impervious surface indices for ISA mappin...

Forest disturbances such as harvesting, wildfire and insect infestation are critical ecosystem processes affecting the carbon cycle. Because carbon dynamics are related to time since disturbance, forest stand age that can be used as a surrogate for major clear-cut/fire disturbance information has recently been recognized as an important input to forest carbon cyclemodels for improving predictio...

The applicability of a land surface temperature (LST)-evapotranspiration (ET) regression model to estimate ET fraction (ETrF) was tested in the temperate maritime climate of Central Ireland. In this study, the Mapping ET at high Resolution and with Internalized Calibration (METRIC) model was applied to calculate evapotranspiration from a mixed land cover area in Central Ireland. The ETrF values...

Algorithms for estimating green leaf area index in C3 and C4 crops for MODIS, Landsat TM/ETM+, MERIS, Sentinel MSI/OLCI, and Venμs sensors Anthony L. Nguy-Robertson & Anatoly A. Gitelson a Center for Advanced Land Management Information Technologies, School of Natural Resources, University of Nebraska–Lincoln, Lincoln, Nebraska, USA b Faculty of Civil and Environmental Engineering, Israel Insti...

A new super resolution Bayesian method for pansharpening multispectral images which incorporates sensor characteristics to model the observation process of both the panchromatic and the multispectral images is presented in this paper. The quality of the pansharpened images is assessed both qualitatively and quantitatively. Preliminary results are very promising: the method succeeded in preservi...

In this study we tested whether AVIRIS data allowed for improved land use classification over synthetic Landsat ETM+ data for a location on the urban-rural fringe of Colorado. After processing the AVIRIS image and creating a synthetic Landsat image, we used standard classification and post-classification procedures to compare the data sources for land use mapping. We found that, for this locati...