JWSS - Journal of Water and Soil Science

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The aim of this study was to detect change of the forest area in the north of Iran between 1994 and 2001. The study area was covered by a 1:25000 topographic map (about 15000 ha) in Babol forests. The forest map of 1994 was extracted from 1:25000 topographic digital map. Landsat 7 ETM+ image dated July 30, 2001 was analyzed to produce the forest map for the end of the period. Since the evaluation of the image quality illustrated it less than ±1DN in the ETM 2, 4, 5, the rectification of the stripping distortion was ignored. There were also duplicate scan lines and sweep distortions in all the spectral bands. Orthorectification was implemented using ephemeris data and digital elevation model. Several spectral transformations such as rationing, PCA, Tasseled cap and image fusion (using Color space transformation and Spectral response method) were performed on the ETM+ data. The sample ground-truth map was prepared using GPS in 3% of the study area. In order to classify the image, hybrid classification method (digital and visual), using original and synthetic bands, was employed. At first the image was classified using maximum likelihood classifier. The most accurate map (overall accuracy and kappa coefficient equal to 94.56% and 0.89, respectively) was converted to the vector format and then it was edited on the basis of various color composites, fused images and other ancillary data. The obtained map showed overall accuracy and kappa coefficient equal to 96.39% and 0.927, respectively. The comparison of the classified map with the forest map of 1994, illustrated that 751 ha of forest area (equal to 8.2% of the previous forest area), were decreased. This includes a 417 ha increase (mostly reforested areas) and a 1168 ha decrease over the study period. The findings indicate the high potential of ETM+ data in forest mapping and change detection over the whole extent of the northern forest of Iran.

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This study was designed to investigate the possibility of using the surface energy balance algorithm for land (SEBAL) and mapping evapotranspiration at high resolution with internalized calibration (METRIC) models to estimate evapotranspiration (ET) in Shahrekord  plain (Chaharmahal va Bakhtiari province, Iran). Two sets of Landsat ETM+ data dated June 30^th and August 21^st, 1999 were provided to estimate and compare reference evapotranspiration (alfalfa) at regional scale using Landsat ETM+ data to ET estimations by five mathematical methods (experimental and combined) known as standardized Penman-Monteith by American Society of Civil Engineers (ASCE-stPM), Penman-Monteith (F56PM), Blaney-Cridle (F24BC), Hargreaves-Samani (HS) and evaporation pan (F24P). Results showed that ET at cold anchor pixel for SEBAL were 6.97 and 6.77 millimeters per day and for METRIC were 10.27 and 9.31 millimeters per day, on days when the satellite passed over. Hargreaves-Samani ET values, as the suitable mathematical model for the studied area, were 8.0 and 7.5 millimeters per day, respectively, on two satellite passes. Results showed that, in the first pass all statistical indices for SEBAL were less than the second pass, maybe due to higher air temperature and wind speed. On the other way, statistical indices in METRIC on the alternate pass, however, showed higher values over the corresponding values in SEBAL. ET values on two satellite passes for anchor pixels were 5.65 and 5.93 mm/day in SEBAL, and 5.22 and 6.65 mm/day in METRIC, respectively. ET values on the same days of satellite overpass for Hargreaves – Samani (HS) were 8.0 and 7.5 mm/day. Consequently, based on the results, both RS-ET models were comparable to empirical models such as (HS). Generally, the results showed that SEBAL had higher accuracy than METRIC, presumably due to lack of accurate weather data (hourly data), so SEBAL is recommended in similar conditions. Generally, the results showed that SEBAL had higher accuracy in comparison to HS and lysimeters data than METRIC, so SEBAL is recommended in similar conditions.