Majid Kazemzadeh; Zahra Nouri; Majid Rahmani; Asghar Bayat; Salma Saedi Farkoush
Articles in Press, Accepted Manuscript, Available Online from 11 May 2025
Abstract
Background and objective: In recent years, extensive watershed management measures including biological, mechanical and biomechanical measures have been carried out with the aim of flood, erosion and sediment control and water storage in the different sections of research, study and implementation ...
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Background and objective: In recent years, extensive watershed management measures including biological, mechanical and biomechanical measures have been carried out with the aim of flood, erosion and sediment control and water storage in the different sections of research, study and implementation in the country. Evaluation of watershed management plans in order to analyze the performance of implemented watershed management measures and develop basic solutions is one of the basic needs in watershed management. Therefore, the aim of this research is to quantitatively and qualitatively evaluate the effects of biological and biomechanical measures of watershed management on the vegetation cover changes in Azimieh watershed, Karaj, Alborz province.Materials and methodsIn this study, vegetation changes were determined using Landsat series 5, 7 and 8, satellite images, and NDVI index in a period of 20 years (2000-2019). Then, by using the polytrend model, the trend of linear and non-linear changes and the effect of water management measures implemented in the watershed on the vegetation cover in the Azimieh Karaj watershed, Alborz province, were investigated. Also, in order to evaluate the accuracy of the results and satellite images, field measurements were also used. Also, in order to investigate the effect of climatic factors on vegetation changes, drought index and rainfall data of Karaj station were used.ResultsResults of trend showed that 41.9% of changes were significant over 20 years. 88.3% of the significant changes in vegetation were increasing. The results of Polytrend method showed that the changes in vegetation were cubic, linear and quadratic with values of 63.4%, 27.8% and 8.8%, respectively. Evaluation of the effects of implemented measures to improving the vegetation status of the watershed showed that the percentage of canopy in the watershed was on average 28% before implementing the watershed management measures, which has increased to 34% after the implementation of watershed management measures. Of the total area of biological operations in Azimiyeh watershed (2724 hectares), in 70% of the area, changes in the vegetation status of the rangeland have been nonlinear and these changes were in projects such as seeding and tree planting and terrace. Also, the vegetation in a parts of the downstream areas of Azimiyeh watershed have been destroyed by non-linear trends due to the growth and development of residential areas and civil works such as the construction of Hemmat Highway.ConclusionThe performance evaluation of watershed management projects in Azimieh Karaj watershed showed that watershed management measures have caused a significant increase in vegetation in the region. On the other hand, development and urbanization in the downstream areas of the watershed has caused the loss and destruction of vegetation over the past years. The evaluation of watershed management plans can show the positive and negative results of the measures implemented over the years, and in this way, steps can be taken to solve their obstacles and problems.
Vahid Veisi; Mansoureh Ghavam; Omolbanin bazrafshan
Volume 26, Issue 3 , September 2019, , Pages 704-716
Abstract
Rangeland vegetation is one of the most important components of arid ecosystems and it is necessary to determine changes in rangeland vegetation under drought and wet years. The present study aimed to investigate the relationship between satellite indices and SPI index in Qom ...
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Rangeland vegetation is one of the most important components of arid ecosystems and it is necessary to determine changes in rangeland vegetation under drought and wet years. The present study aimed to investigate the relationship between satellite indices and SPI index in Qom rangelands. For this purpose, the SPI index was calculated in moving averages of 1, 3, 5 and 7 years. In the next step, using Landsat images and after making the necessary adjustments to the images, the vegetation map was prepared using NDVI, MSAVI and EVI indices. Finally, correlation coefficients were used to investigate the relationship between satellite image indices and SPI index. The results showed a moderate and good correlation between MSAVI satellite indices and SPI index at peak vegetation growth months with a one month moving average of SPI index. The results of this study show that to estimate agricultural drought through remote sensing, the MSAVI index is a very suitable method and can be used for estimating drought in areas where meteorological stations are scattered (or nonexistent). Because the number of sampling points in satellite images is far greater than the number of meteorological stations.
Saiedeh Nateghi; Ahmad Nohegar; Amir Houshang Ehsani; Omolbanin Bazrafshan
Volume 24, Issue 4 , January 2018, , Pages 778-790
Abstract
The monitoring of vegetation changes has a fundamental role in planning and management of environment. There are various methods to determine the changes in a region using satellite images that each has advantages and limitations. The use of vegetation indices is one of the methods to detect the changes. ...
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The monitoring of vegetation changes has a fundamental role in planning and management of environment. There are various methods to determine the changes in a region using satellite images that each has advantages and limitations. The use of vegetation indices is one of the methods to detect the changes. The aim of this study was to evaluate four vegetation indices including NDVI, SAVI, RVI and WAVI. This research was performed in Qeshm Island using Landsat images during 2001 and 2014. In this research, ETM+ and OLI data were used. After calculating each indicator, 100 sample training points were used to assess the accuracy of indicators by ENVI.5.3. Four classes including bare land, mangrove forests, agriculture and water were classified. Based on Dlapyan & Smith method, the product accuracy and user accuracy for each class were evaluated. The results showed that the SAVI index with the highest kappa coefficient, 0.93 in 2014 and 0.83 in 2001, had the best results and WAVI index with the lowest kappa coefficient, 0.43 in 2001 and 0.81 in 2014, had the weakest results. To evaluate the changes, crosstab method was used .The results showed that during 13 years the area of mangrove forests and agricultural lands and natural vegetation of Qeshm Island increased up to 21% and 60%, respectively.
ardavan ghorbani; ardashir pournemati; mohsen panahande
Volume 24, Issue 1 , May 2017, , Pages 165-180
Abstract
The aim of this study was to estimate and map the plant group and total aboveground phytomass using Landsat 8 images in the rangelands of Sabalan Mountain. Images were selected on the 19th of July 2013 and field data were collected in April and July based on maximum matching with the phenology of the ...
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The aim of this study was to estimate and map the plant group and total aboveground phytomass using Landsat 8 images in the rangelands of Sabalan Mountain. Images were selected on the 19th of July 2013 and field data were collected in April and July based on maximum matching with the phenology of the study area and in the closest date to the time of image acquisition. Twenty-four sampling sites on six vegetation types were determined. In each site, 9 sampling plots, based on previous studies, which are required for minimum sample number according to the variance of vegetation distribution, were determined in a systematic-random method, and the aboveground phytomass of vegetation groups, such as grasses, forbs, shrubs and total, were determined using the harvesting method. Initially, to calculate vegetation indices, the averages of 16 pixel values of the location of sample units from the corrected images were derived and transferred to the software environment. The correlation matrices between the derived pixel values and field collected data for the 24 selected vegetation indices were calculated and used for the estimation of grasses, forbs, shrubs and total aboveground phytomass. The results showed that indices such as RVI, TNDVI and GNDVI had the highest correlation with the aboveground phytomass of grasses, PD312, IO and PD311 with the aboveground phytomass of forbs, RDVI, DVI and RVI with the shrubs, and PD311, PD321 and PD312 with the total aboveground phytomass (P <0.01). In the second stage, three of the indices, having the highest correlation with the aboveground phytomass of each group and entire previous stage, were selected, and Landsat8 images were used to calculate the aboveground phytomass of each vegetation group and the total aboveground phytomass was calculated. The aboveground phytomass maps of each group and the total aboveground phytomass were controlled with sampling points to assess the accuracy. The results of this study showed that the best maps were obtained using the TNDVI index for grasses aboveground phytomass, PD312 for forbs, RVI for shrubs groups and PD311 for the total aboveground phytomass. Moreover, some indices, such as PD311 and RVI, could be used for all growth forms and estimation of total aboveground phytomass (P<0.01) and (P<0.01). In general, Landsat 8 data could be used to estimate and map the aboveground phytomass of vegetation groups and to determine the carrying capacity of the total aboveground phytomass in Sabalan rangelands, having advantages based on cost, time and the ability to monitor large areas with repeatability potential in comparison with the ground-based methods.
Saeedeh Nateghi; ahmad Nohegar; Amir Houshang Ehsani; Omolbanin Bazrafshan
Volume 23, Issue 2 , September 2016, , Pages 416-404
Abstract
Monitoring the land use and land cover change detection is one of the most important issues in the field of planning and management. Change Vector Analysis technique is one of the common methods to detect the changes. This method is based on radiometric changes between two time series satellite data ...
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Monitoring the land use and land cover change detection is one of the most important issues in the field of planning and management. Change Vector Analysis technique is one of the common methods to detect the changes. This method is based on radiometric changes between two time series satellite data and threshold level method. For this purpose, the satellite images of Landsat ETM + (2001) and OLI (2014) were used for the Qeshm Island. The FLAASH method was used to perform atmospheric correction. Then, the vegetation indices (NDVI، WAVI، RVI, SAVI و BI) were calculated and the correlation between indices was evaluated. The results showed that the SAVI index with a correlation coefficient of 95% in 2014 and 92% in 2001 had a high correlation with BI index; therefore, the SAVI index provides better results in studying the vegetation changes in arid and semi-arid regions. The results also showed that during the study period (2001-2014), 150 km² of the lands around and between the mangrove forests were submerged, and at the same time, the area of mangrove forests decreased to 30.63 km², mostly occurring in the margins of Qeshm mangrove forests and the eastern shores of Khamir Port. As well, the area of agricultural lands and vegetation of the island decreased about 8.2 km² in central, eastern, and southeastern island.
Akbar Fakhireh; Ahmad Pahlevanravi; Mahmoud Najafi zilaee; Mohsen Moradzadeh; Soheila Nouri
Volume 19, Issue 3 , December 2012, , Pages 457-468
Abstract
Detailed studies of vegetation in desert areas are almost difficult due to the limitations and conditions of these areas. Remote sensing technology with numerous capabilities can be used as an efficient method in these areas. This study was aimed to determine an appropriate vegetation index to assess ...
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Detailed studies of vegetation in desert areas are almost difficult due to the limitations and conditions of these areas. Remote sensing technology with numerous capabilities can be used as an efficient method in these areas. This study was aimed to determine an appropriate vegetation index to assess vegetation changes in the desert area of West Karkheh over a period of 18 years using satellite images of TM (1991) and ASTER (2008). After measuring the canopy cover, geometric and atmospheric corrections, different methods of detection and classification were applied on the images with maximum likelihood method. Results showed that PVI2 index was the best indicator to produce vegetation changes map during the study. So based on this index, final map of desertification was produced in the three classes with no changes and rehabilitation. The results showed that canopy cover increased up to 17.5% of the total area during the study period due to the implementation of desertification projects in some parts of the region and combined cultivation. These changes were classified in two classes of rehabilitation (69.8%) and desertification (30.2%).
Mahmood Goudarzi; Mahdi Farahpour; Alireza Mosav
Volume 13, Issue 3 , February 2006, , Pages 265-277
Abstract
In Iran, like many other developing countries, high population growth rate causes unfairly uses of natural resources and consequently land cover change. Therefore, detection of land cover (rangelands, irrigated and rainfed agricultural lands, urban areas…) changes can influence local planning ...
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In Iran, like many other developing countries, high population growth rate causes unfairly uses of natural resources and consequently land cover change. Therefore, detection of land cover (rangelands, irrigated and rainfed agricultural lands, urban areas…) changes can influence local planning and natural resource management. Present study efforts to find a rapid and exact method of recognition different land covers using Landsat satellite data. Methods used in this research were image enhancement, false color composite (FCC), principal components analysis (PCA) and Image classification, i.e. normalized different vegetation index (NDVI) and supervised classification. A GIS environment, ILWIS software, was used. Results showed that irrigated agriculture, rainfed agriculture, rock out crop, rangeland classes (fair, moderate, poor condition) could be separated with overall accuracy of 89%.