ANALYSIS OF SPATIAL-TEMPORAL VARIATION OF LAND SURFACE TEMPERATURE, VEGETATION AND SNOW COVER IN LAR NATIONAL PARK OF IRAN

Changes in land surface reflectance measured by remote sensing data can be useful in climate change studies. This study attempts to analyze the spatial-temporal extent change of vegetation greenness, Land Surface Temperature (LST), and Normalized Difference Snow Index (NDSI) in late spring at the Lar National Park of Iran using Landsat data. Vegetation indices (VIs), LST, and NDSI maps were calculated for each date (1985, 1994, 2010, and 2015). All VIs have shown an increasing trend from 1985 to 2015 which depicted increase of vegetation. Spectral reflectance of all bands is declining from 1985 to 2015 except in near-infrared (NIR) bands. High reflectance in NIR bands is due to increased vegetation greenness. The reduction was seen in the visible bands that show increased vegetation photosynthetic activity. In the short-wave infrared bands (SWIR) were observed reduced trend from 1985 to 2015 which is indicate increased vegetation. Also, in the mid-wave infrared (MWIR) bands were observed a declining trend which is the result of decreasing soil fraction from 1985 to 2015. LST has increased from 23.27 degrees C in 1985 to 27.45 degrees C in 2015. Snow patches were decreased over the study period. In conclusion, VIs and surface reflectance bands are considered the main tool to display vegetation change. Also, high VIs values showed healthy and dense vegetation. The results of our study will provide valuable information in preliminary climate change studies

ANALYSIS OF SPATIAL-TEMPORAL VARIATION OF LAND SURFACE TEMPERATURE, VEGETATION AND SNOW COVER IN LAR NATIONAL PARK OF IRAN

Changes in land surface reflectance measured by remote sensing data can be useful in climate change studies. This study attempts to analyze the spatial-temporal extent change of vegetation greenness, Land Surface Temperature (LST), and Normalized Difference Snow Index (NDSI) in late spring at the Lar National Park of Iran using Landsat data. Vegetation indices (VIs), LST, and NDSI maps were calculated for each date (1985, 1994, 2010, and 2015). All VIs have shown an increasing trend from 1985 to 2015 which depicted increase of vegetation. Spectral reflectance of all bands is declining from 1985 to 2015 except in near-infrared (NIR) bands. High reflectance in NIR bands is due to increased vegetation greenness. The reduction was seen in the visible bands that show increased vegetation photosynthetic activity. In the short-wave infrared bands (SWIR) were observed reduced trend from 1985 to 2015 which is indicate increased vegetation. Also, in the mid-wave infrared (MWIR) bands were observed a declining trend which is the result of decreasing soil fraction from 1985 to 2015. LST has increased from 23.27 °C in 1985 to 27.45 °C in 2015. Snow patches were decreased over the study period. In conclusion, VIs and surface reflectance bands are considered the main tool to display vegetation change. Also, high VIs values showed healthy and dense vegetation. The results of our study will provide valuable information in preliminary climate change studies

AGRICULTURE AND BIOLOGY JOURNAL OF NORTH AMERICA Land use/cover change detection based on remote sensing data (A case study; Neka Basin)

ABSTRACT Several regions around the world are currently under rapid, wide-ranging changes of land cover. Satellite remote sensing techniques have proven to be cost efficient in extensive land cover changes. This study illustrates the effect of land use/cover change in Neka river of Iran using topographic maps and multi-temporal remotely sensed data from 1975 to 2001. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect land use/cover change. Post-classification change detection technique was used to produce an image through cross-tabulation. Changes among different land use/cover classes were assessed. The overall accuracy of land cover change maps, generated from Landsat data 1975 and 2001, ranged from 99.44% and 97.08% with Kappa statistics of 85% and 83%, respectively. The analysis indicated that the urban and agricultural land expansion of Neka river was increased resulted in the considerable reduction of forest area. The maps showed that between 1987 and 2001 the agricultural land and built-up areas increased approximately 59.86km 2 (9.16%) and 7.35(1.13%), respectively. While forest decreased 67.91 km 2 (10.29%). The study quantified the patterns of land use/cover change for the last 13 years for Neka river that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning