to determine the suitable indices for vegetation cover and production assessment based on the remote sensing data, simultaneous digital data with field data belonging to the spring rangeland of the semirom-isfahan province were analyzed. during two years of monitoring the annual, grass, forb, and shrub vegetation cover and the total production data from 86 were collected. the global positioning...

Cutting-edge remote sensing technology has a significant role for managing the natural resources as well as the any other applications about the earth observation. Crop monitoring is the one of these applications since remote sensing provides us accurate, up-to-date and cost-effective information about the crop types at the different temporal and spatial resolution. In this study, the potential...

Vegetation indices have been used extensively to estimate the vegetation density from satellite and airborne images for many years. In this paper we first focus on one of the most popular vegetation indices, the normalized difference vegetation index (NDVI ) [1] and introduce a statistical framework to analyze it. We propose a solution to the saturation problem of this index based on our statis...

Background: Monitoring terrestrial vegetation cover condition is important to evaluate its current condition and to identify potential vulnerabilities. Due to simplicity and low cost, point intercept method has been widely used in evaluating grassland surface and quantifying cover conditions. Field-based digital photography method is gaining popularity for the purpose of cover estimate, as it c...

This study presented a MODIS 8-day 1 km evapotranspiration (ET) downscaling method based on Landsat 8 data (30 m) and machine learning approaches. Eleven indicators including albedo, land surface temperature (LST), and vegetation indices (VIs) derived from Landsat 8 data were first upscaled to 1 km resolution. Machine learning algorithms including Support Vector Regression (SVR), Cubist, and Ra...

the occurrence of dust storms and their sources in the southern and central parts of iran during the period of 2002 to 2009 was investigated. for this purpose, the meteorological and synoptic data, data from the middle and upper atmosphere, and wind flow tracking model were used. dust storms and nddi were traced using satellite imagery from fasa, shiraz, and bushehr stations. analysis of the gr...

Crop yield models using different VIs (vegetation index) from remote sensing data show the various precision, but each of them can provide useful information related with yield. So it is very significant how to integrate the useful information of these models. In this study, a few of typical VIs, such as NDVI (Normalized Difference Vegetation Index), SR (Simple Ratio index), TCARI/OSAVI (Trans-...