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Showing 3 results for Hybrid Method

Z. Khosravani, S. J. Khajeddin, A. Soffianian, M. Mohebbi, A. H. Parsamehr,
Volume 16, Issue 59 (4-2012)
Abstract

LISS IV sensor's data from IRS-P6 satellite was used to produce land use map of eastern region of Isfahan, the studied part of which has an area of 22121 hectares. Its three band data, namely band 2 (Green), band 3 (Red) and band 4 (Near infra red) of LISS-IV sensor images with 5.8 m ground resolution were georeferenced by nearest neighbor method and first-order polynomial model to the DEM map of 1:25000, where the RMSE was equal to 0.3 pixel. To analyze the satellite data, various image processing methods such as supervised and unsupervised classification methods, principal component analysis, NDVI vegetation index and filtering were applied to the satellite data. Finally, the land use map was produced with hybrid method. The final map detected 6 land uses very clearly, which are: Agricultural lands, barren lands, disturbed lands, cultivated Haloxylon amodendron, roads, residential areas and industrial locations. The kappa of land use map is 0.89 and the overall precision is 0.92. The barren lands have a very poor natural vegetation and are considered as natural deserts. Disturbed lands have been formed because of brick kiln activities, and the vegetation cover of these areas has disappeared completely The LISS IV data has a high ability to detect the various studied land-uses especially to digitize the roads. They can be used to update the 1:25000 topographic maps, as well.
M. Goodarzi, J. Abedi Koupai, M. Heidarpour, H. R. Safavi,
Volume 19, Issue 73 (11-2015)
Abstract

Due to the time and space changes of hydrological events in the arid and semi-arid regions, recharge measurement in these areas is very difficult. Hence, groundwater recharge is a complicated phenomenon for which there is not a fixed method to determine. The aim of this research was to develop a method for estimation of groundwater recharge based on a hybrid method. In this study, a hybrid method for calculating recharge was presented by combining empirical methods with a mathematical model, MODFLOW, and AHP analysis. The results showed that the most important parameters affecting groundwater recharge are soil properties, unsaturated thickness, land cover, land slope, irrigation and precipitation, from which the soil properties and precipitation are most important. The results showed that the overall impact of small changes in precipitation and temperature significantly affect the groundwater recharge, and heavy soils are much more sensitive to these changes than light soils. By changing 10% precipitation, the recharge rate is changed between 16% and 77% and by changing 1ºC temperature, the recharge rate is changed between 6% and 42%. Also, results showed that precipitation and evapotranspiration changes in four months including December, January, February and March had significant effects on annual recharge rate. Using the results of this research, the vulnerable areas of the plain, appropriate places and time for artificial recharge could be identified. Overall, the results of this study can be useful in various aspects of groundwater management.


M. Pajoohesh, M. Mohammad Yousefi, A. Honarbakhsh, H. R. Reyahi Bakhtyari,
Volume 24, Issue 1 (5-2020)
Abstract

In order to plan and manage the land and its changes, it is necessary to identify and evaluate the factors affecting it. Land use / cover changes are one of the main factors in global environmental change that is defined as a change in the type of land use; it is one of the major factors changing hydrologic flow, land erosion and destruction of biodiversity. The main purpose of this study was to assess the trends of land use changes in Beheshtabad Watershed of Chaharmahal and Bakhtiari Province with an area about 3847 square kilometers by using remote sensing and GIS during a 25-year period. In this research, first, analyzing and pre-processing the satellite images of Landsat 5 TM sensors from 1991 and 2008 were done, and Landsat 8 of OLI sensor of 2016 was applied. Then, by using the hybrid classification method, 5 land use classes including pasture lands, urban-building lands, agricultural lands, garden lands and bare lands, land use maps for the three time periods were prepared. The overall accuracy of the obtained land use maps for 1991, 2008 and 2016, was 92.17%, 94.29% and 93.41%, respectively, indicating the acceptable accuracy of the maps. Then, the process of land use change and the contribution of each land use classes and the percentage of changes in each land use class were determined in two study periods. The results of this study showed some changes occurred in the studied watershed. The total area of pasture lands during two periods indicated the decreasing trend, but urban-building and garden lands during two periods represented the increasing one. Agricultural lands during the first period indicated the decreasing trend and during the second period showed the increasing trend, while bare lands during the first period showed the increasing trend and during the second period, reflected the decreasing trend. In general, it should be noted that in the Beheshtabad watershed, we could see an increase in the replacement of pastures by urban-building class, rainfed agriculture, gardens, and bare lands, the incidence of destruction in the region.


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