Hossein Arzani; Zeinolabedin Hosseini; Khosro Mirakhorlou
Volume 21, Issue 1 , June 2014, , Pages 24-31
Abstract
This study was aimed to assess the applicability of LANDSAT ETM+ satellite images for estimating vegetation production and cover. The images were digitized using topographic maps and geometrized in 1:25000 scales. Required processes such as spectral ratio measurement and vegetation indices were applied ...
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This study was aimed to assess the applicability of LANDSAT ETM+ satellite images for estimating vegetation production and cover. The images were digitized using topographic maps and geometrized in 1:25000 scales. Required processes such as spectral ratio measurement and vegetation indices were applied on the images. Collection was carried out for vegetation cover and production in various vegetation types in homogeneous units. Sampling points' locations were recorded with GPS. Sampling method was random-systematic in such a way that in each unit, a circle with 20 meters radius was considered. One and 9 sampling plots were placed on the centre and on the perimeter, respectively. The plot size was 1m * 1m. In each plot, vegetation percentage was estimated and the production was calculated using double sampling method. Then, DN values for each sampling unit (9 pixels for one unit) were elicited in respect to primary bands' images, vegetation indices and spectral ratios. Correlation and regression analyses between geo-information and satellite information (Digital numbers) were carried out. Results revealed that 7th and 5th Bands and IR1, MIRV2 and VNIR2 indices had a significant correlation with production and given parameter could be estimated through regression models. Likewise, RA, IR1 and TVI indices had a significant correlation with vegetation percentage and this parameter could be estimated through regression models.
Jahan bakhsh Pairanj; Ata... Ebrahimi; Abalfazl Ranjbar; Mohammad Hasan zadeh
Volume 18, Issue 4 , September 2012, , Pages 593-607
Abstract
Evaluation of forage production is an important issue in determining grazing capacity of rangelands. There is no doubt that all forage production in rangelands is not evenly accessible and different factors affect the accessibility of forage. In this research, factors affecting forage availability were ...
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Evaluation of forage production is an important issue in determining grazing capacity of rangelands. There is no doubt that all forage production in rangelands is not evenly accessible and different factors affect the accessibility of forage. In this research, factors affecting forage availability were studied. After a wide literature review, factors of distance from water supplies, density of shrubs, slope and land uses were identified as the main factors preventing forage accessibility. Forage production and shrub density were respectively measured using clip and weighing method in quadrates and distance method. Forage production measurements in representative area were extrapolated to the whole area using IRS satellite images. In this research, 18 vegetation indices were examined as forage production data (independent factor) were regressed against vegetation indices values (dependent factor) using SPSS. Map of forage production was created based on the best fit regression. Then, with adjusting all limiting factors, the map of accessible forage production was created based on the tables. The maps were illustrated and available forage was calculated after implementing adjustment of each factor. Statistical results showed significant differences (p≤0.05) between forage production with considering slope and shrub density and forage production based on all limiting factors of forage accessibility. While distance from water supplies and other land uses had no significant effect on forage production
Rooh... Kazemi; Hassan Yeganeh; Jamal.. Khajedin
Volume 18, Issue 1 , May 2011, , Pages 124-138
Abstract
Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climatic change, biodiversity conservation, ecosystem assessment, and environmental modeling. The aim of the present research was to study change detection of vegetation during the grazing ...
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Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climatic change, biodiversity conservation, ecosystem assessment, and environmental modeling. The aim of the present research was to study change detection of vegetation during the grazing season using multi temporal data of WiFS in Semirom region. Various preprocessing, including geometric correction were applied using topographic maps of 1:250000 with an RMSe 0.35 pixel for sensor IRS-WiFS. The atmospheric and topographic corrections were carried out using dark-object subtraction method and the Lambert method. Field data collection was started on June 2005 on 800,000 ha. Multi-temporal data of IRS-WiFS sets were used for this study. Image processing including FCC, PCA, vegetation indices and supervised classification were employed to produce the vegetation canopy cover map. Various vegetation types were sampled using stratified random sampling method. twenty random sampling points were selected and canopy cover percentage was estimated. Digital data and the indices maps were used as independent data and the field data as dependent variables. The produced models were processed and then resulted images were categorized in 5 classes. Also post classification method was used to determine change detections. Finally the produced maps were controlled for their accuracies. The results confirmed the high correlations of used WiFS indices with field data. In the current study, more than 30 percent of the study area has been affected during the grazing season. Also the NDVI, SAVI and DVI indices which employ RED and NIR bands had relatively highly correlations with rangeland data. Result showed vegetation maps produced with IRS-WiFS data set had very high accuracy.
Ali akbar Shamsi pur; Kazem Alavi panah; Hossein Mohammadi
Volume 17, Issue 3 , October 2010, , Pages 445-465
Abstract
The purpose of this study is to track and analyze the environmental effects of droughts by remote sensing indices in Kashan desert and dry zone. Temporal changes of droughts was evaluated using normal Z index in annual and seaonal (spring) scales. Spectral and thermal data from data series of NOAA-AVHRR ...
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The purpose of this study is to track and analyze the environmental effects of droughts by remote sensing indices in Kashan desert and dry zone. Temporal changes of droughts was evaluated using normal Z index in annual and seaonal (spring) scales. Spectral and thermal data from data series of NOAA-AVHRR satellite between 1998 and 2004 were used to determine the drought indices. Vegetative and thermal drought indices were calculated using NDVI, VCI and TCI values derived from NOAA-AVHRR data. Results from applying mentioned indices showed that this area had low vegetation index values as NDVI index was generally less than 0.2. According to NDVI and VCI maps, years of 2000 and 2001 were characterized as drought condition contrary to 2002 and 2004 as rainy years.However, land surface temperature (LST), TCI and VHI indices showed different temperature conditions specifically in the months of April and May. Using validation of results derived from remote sensing indices, test of significance between them and climatic indices was calculated.According to the calculations, climatic condition of the study area was more compliant with the results of vegetation indices. Also thermal condition of the environment was more accurately indicated by thermal indices. According to the results, applying remote sensing data in environmental studies of arid and desert regions like Kashan is recommended.
Mitra Shirazi; Gholam reza Zehtabian; Hamid reza Matinfar
Volume 17, Issue 2 , September 2010, , Pages 256-275
Abstract
Recently there is a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science. One of important methods for extracting information from satellites image is use of indices. In this study for enhancement ...
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Recently there is a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science. One of important methods for extracting information from satellites image is use of indices. In this study for enhancement of land cover in region of northwest Tehran near Hashtgerd some indices such as BI, MIRV2, GREENNESS, TVI, VNIR, MND، NIR, OSAVI, RA, NDVI, IR1, MSI IPV ,MSAVI, SAVI, TSAVI, PD322 ,BI, INT1, INT2, PVI, SI1, SI2, SI3, GEMI, WDVI Are used. Most of study area covers by density of vegetation (such as irrigation farming and vegetation cover around streams) and bare lands. The results have shown that TSAVI, DVI, IPVI, RA, NIR, IR1 Indices have the most effective efficiency for vegetation enhancement and SI2, BI, TVI, PVI, INT1, SI3, SI2 indices have the most effective efficiency for salinity surface. This study addressed that all of vegetation indices except DVI have correlation more than 0.8 and DVI has correlation around 0.4 with others. Meanwhile all of salinity indices have more than 0.9 correlations with each other. As conclusion, this study has shown that IRS satellites image have high accuracy for providing land cover map by use of vegetation indices, also use of salinity indices having high capability for salinity surface can be used for providing salinity maps, meanwhile vegetation indices with high correlation can be used instead each other for providing vegetation maps.
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%.