land use may be regarded as one of the most important factors affecting theenvironment with respect to human activities. so far, destroying the rangelands andchanging them into the waste lands and poor rangelands has been proposed as the mostsignificant variations of land use done by human beings. this paper has been conducted toevaluate the variations of vegetation percentage and land uses in ...

the aim of this study is to determine the area affected by dust storms in different wind speeds using satelliteimages. in the first step, windy conditions of the sistan plain were analyzed using wind statistics data. next, fivestormy days of zabol city, indicating different wind speeds and horizontal visibilities during those storms, wereselected. then, high temporal resolution modis data was u...

the growing population and increasing socio-economic necessities creates a pressure on land use/land cover. nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. this study investigates the land use changes in part of hableh rood watershed of iran using landsat 7 and 8 (sensor etm+ and oli) ...

A key variable controlling the global carbon, water and energy cycles is the leaf area index (LAI), which thus has an important role in current biosphere-atmosphere research. Several international networks promote the development of remote sensing techniques for global assessment of LAI. We present results from the VALERI (VAlidation of Land European Remote sensing Instruments) network’s test s...

this study was aimed to assess wheat-grown fields health in gharessoo basin, golestan province, iran, using 79 fields in 8 villages in 2010. the samples were taken by quadrates. the number and the type of weeds were recorded at genera and species levels. in parallel, management data were recorded by questionnaire. species richness was defined as species number and shannon-wiener index, simpson’...

Hyperspectral remote sensing is widely used for analyzing and estimating the severity of soil salinity in arid and semi-arid regions, throughout the world. The present study is an attempt to map the various soil salinity severity classes using different hyperspectral indices generated using EO-1 Hyperion data and Support Vector Machine (SVM) method, in the Mathura region of Indo-Gangetic plain ...

Hemispheric ozone variability indices derived from satellite observations and as diagnostics for coupled chemistry-climate models T. Erbertseder, V. Eyring, M. Bittner, M. Dameris, and V. Grewe German Remote Sensing Data Center, DFD, German Aerospace Center, DLR, Germany Institute for Atmospheric Physics, German Aerospace Center, DLR, Germany Received: 4 April 2006 – Accepted: 24 May 2006 – Pub...

We propose a new method to simultaneously detect shadows and vegetation in remote sensing images. Several shadow and vegetation indices are merged with the Dempster-Shafer (DS) theory so as to increase the reliability and accuracy of the segmentation. The per-pixel DS fusion is incorporated in a Markovian context to obtain an optimal and regularized segmentation result. Evaluation on aerial ima...

This paper presents two novel spectral soil area indices to identify bare and distinguish it more accurately from the urban impervious surface (ISA). study designs these based on medium spatial resolution remote sensing data Landsat 8 OLI dataset. Extracting or ISA is challenging than extracting water bodies vegetation in multispectral Remote Sensing (RS). Bare often were mixed because of their...