Jalal Abdolahi; Mohammad hasan Rahimian; Mohammad hosein Savaqebi
Volume 14, Issue 3 , January 2007, , Pages 289-301
Abstract
Today, various indices have been developed for monitoring of vegetation cover in different climatic condition, which cause variation in aspect and spectral reflectance. Therefore, an index can give different values in different conditions. In addition, sparse vegetation and soil background are the other ...
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Today, various indices have been developed for monitoring of vegetation cover in different climatic condition, which cause variation in aspect and spectral reflectance. Therefore, an index can give different values in different conditions. In addition, sparse vegetation and soil background are the other limitations. Hence, combination of some indices can provide sufficient real information in such areas. Contribution of each parameter can be obtained from a statistical method. However, there is no guarantee that the high correlation coefficients would get a good vegetation cover map. It depends on the originality of each predictor variable. The main objective of this study was to identify some probable limitations of Landsat ETM+ images for mapping of vegetation cover in arid and semi-arid zones, especially in drought conditions. In addition, it suggests a method for mapping of sparse vegetation cover in such areas. For this purpose, vegetation cover percentages were measured in two dry and rainy years (2000 and 2002) in the Nodoushan basin, Yazd, Iran. Afterwards, Landsat ETM+ images of two mentioned dates were acquired and different indices were derived. In addition, some environmental factor maps were generated and aligned with other variables (e.g. DEM, Slope and Aspect maps). These data were analyzed using a multiple linear regression method and built regression equations of the form: vegetation cover (%) =1X1+2X2+…+ for each year. Xi’s are independent variables (Satellite data bands, different indices and environmental factors) and’s are regression coefficients and is a constant. According to the equations, vegetation cover maps were generated using ILWIS software capabilities. Then, their accuracies were determined. Results show that the 2002 map (rainy year) is more reliable than the 2000 map (dry year). It was also found that if a drought was occurred in the arid zones, soil background would be dominant and therefore, vegetation indices would not be able to estimate vegetation cover confidently
Jalal Abdollahi; Mohammad hasan Rahimian
Volume 14, Issue 2 , January 2007, , Pages 156-170
Abstract
Remotely sensed data are able to monitor some characteristics of the environment and also their spatial structure. The latter one is the first and main step in field data interpolations. Therefore, spatial analysis of some field data is possible by employing of related satellite data bands. In this study, ...
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Remotely sensed data are able to monitor some characteristics of the environment and also their spatial structure. The latter one is the first and main step in field data interpolations. Therefore, spatial analysis of some field data is possible by employing of related satellite data bands. In this study, as an example, Landsat ETM+ thermal band (band 6) was acquired to determine the spatial structure of surface temperature distribution. For the purpose of evaluation and selection of the best interpolation model, the band 6 data was crossed with a regular sampling grid and therefore, a dataset was constructed. Using geo-statistical analysis, empirical semi-variogram was calculated and various mathematical models were fitted to its points (e.g. gaussian, exponential, circular and spherical). Afterwards, the fitted models were applied to generate different temperature distribution maps using kriging interpolation approach. Finally, the optimum model which could better predict temperature changes and distribution was recognized. Result of the study shows that the exponential model would be better to predict and estimate surface temperature in un-sampled locations in the area of studied. So, the model can be used for interpolation of field temperature data with a high confidence level. The represented method can be developed for all the other environmental factors which could better characterized by remotely sensed data, like minimum and maximum temperature, evapotranspiration and so on.
Jalal Abdollahi; Hosein Arzani; Naser Baghestani; Mohammad Hasan Rahimian
Volume 13, Issue 3 , February 2006, , Pages 162-171
Abstract
Remote sensing is a method to produce updated information in vast area. Describing the model for utilization and processing satellite data in regard to developing a method for mapping forage production of arid regions were the purpose for this study. For this purpose Landsat ETM+ data used at Nodushan ...
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Remote sensing is a method to produce updated information in vast area. Describing the model for utilization and processing satellite data in regard to developing a method for mapping forage production of arid regions were the purpose for this study. For this purpose Landsat ETM+ data used at Nodushan area in 2002 . The study area covers about 60000 hectares and the annual precipitation is about 140-300 mm. in order to correct the necessary data 50 sites with different vegetation types using 25 quadrant of 1*2 m size and then awareged were used. To study the dependent variable of vegetation relations with independent variables of satellite data, vegetation indices and environmental factors; multiple linear regression analysis were manipulated using SPSS software. Then a suitable model was selected which caried predict the vegetation properties of the study area. Finally, production map was produced using ILWIS software. According to the results, mapping of forage production via remote sensing is possible even when its vegetation cover is less than 25%.
Jalal Abdollahi; Hosein Arzani; Naser Baghestani; Fakhr.... MirAskarshahi
Volume 13, Issue 2 , February 2006, , Pages 74-81
Abstract
An optimal planning system for managing the range and maintaining it’s vegetation is highly influenced by the humidity and rainfall of the range. In this research, the reactions of the seidlitzia rosmarinous species to the fluctuation of precipitation and under ground water were studied at Chah-Afzal ...
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An optimal planning system for managing the range and maintaining it’s vegetation is highly influenced by the humidity and rainfall of the range. In this research, the reactions of the seidlitzia rosmarinous species to the fluctuation of precipitation and under ground water were studied at Chah-Afzal in Ardakan-Yazd. Regarding the amount of collecting data after five years, by applying Minitab software, using linear regression, an equation between the amount of the production and precipitation was obtained with a high correlation coefficient (r=0.93). The results showed that the variation of the plant production was due to the fluctuation of the annual precipitation. Moreover, result of another analysis was demonstrated a lack of agreement between the cover and density of the se.rosmarinous species with the amount of precipitation. In addition, the results state that the downward trend in the percentage of canopy cover and the density of the se.rosmarinous species in the region are highly influenced (r=0.94 and r=0.99 respectively) by the discharge of ground water table. Thus, the gradual decrease of this source in the coming years might bring out negative effects on the cover, density and finally on the condition of the range in Chah-Afzal. Also, Interaction between the effect of ground water table changes on the amount of forage production was not significant.