Showing 2 results for Landsat Etm
N. Yaghmaeian Mahabadi, M. Naderi Khorasgani, J. Givi,
Volume 15, Issue 58 (3-2012)
Abstract
Remote sensing has been considered as an appropriate tool for temporal monitoring of some natural phenomena. Ardestan Region is prone to land degradation and masked by sand sheets, sand dunes, clay flats, desert pavement and different kinds of salt crust due to dry climate. To study the trends of land degradation in last three decades, four satellite data sets of Landsat MSS, Landsat TM, Landsat ETM+ and IRS acquired in 1976, 1990, 2001 and 2008, respectively were analyzed. The time series analysis revealed that the bare clayflats have decreased and clayflats with vegetation cover have expanded over 32 years. During this period, the areas which are covered by gravel have decreased 13 percent and both the area covered by salt crusts and aeolians have extended 2 percent. Puffy grounds have developed by 2001 but their magnitudes have decreased between 2001 and 2008 as they have been masked by the moving sand ripples. Reduction of 13 percent of sand sheets between 1990 and 2008 indicates that soil conservation practices have efficiently controlled land degradation and desertification in the area.
Sh. Mahmoudi, M. Naderi, J. Mohammadi,
Volume 17, Issue 63 (6-2013)
Abstract
This research was carried out to determine spatial distribution of heavy metals concentration in soil particle size classes using Landsat ETM+ reflectance in Southern Isfahan city in the vicinity of Bama mine. To fulfill this goal, 100 compound soil surface samples were collected randomly from the area. The samples were air dried and soil particle size classes 250-500, 125-250, 75-125, 50-75 and <50 μm were determined using appropriate sieves after dispersion of the bulk samples of soil using ultrasonic apparatus. Total Zn, Pb and Cd concentrations were measured using Atomic Absorption Spectrophotometer after wet digestion of samples in acid nitric. The results indicated significant negative correlation coefficients between heavy metals concentrations of soil particle size classes and soil spectral reflectance in the visible, near infrared and panchromatic bands of Landsat ETM+ satellite. Stepwise multiple regression models were used for estimating heavy metals concentration in soil particle classes through satellite data. Furthermore, spatial distributions of heavy metals were mapped using stepwise multiple regression equations. Results also showed heavy metals concentrations in all soil particle size classes were maximum close to the mines and decreased by increasing the distance from these sources.
