Showing 16 results for Vegetation
N. Zahedifard, S. J. Khajeddin, A. Jalalian,
Volume 8, Issue 2 (7-2004)
Abstract
Satellite data use is finding global applications because they provide repeated cover, broad information, high electromagnetic spectral resolution, and software-hardware compatibilities. This study aims to evaluate of the Landsat TM data capabilities in land-use mapping of Bazoft River basin (Chahar Mahale Bakhtiary Province). Six spectral bands of the Landsate TM were employed to produce land-use map of the Region. The date of image acquisition was May 5th, 1998. Performance of the geometric correction completed with RMSE= 1.008 pixels. Various image enhacement methods (e.g. FCC, filtering and Vegetation Indices) were used to study the different land-covers. Field investigations were carried out using a GPS, 1:50000 scale topographic map and false color composites images. Heterogeneous land-use units were studied in 62 sample sites estimating percentage of vegetation cover. A regression analysis was performed between percentage vegetation covers and vegetation indices values of NDVI, RVI, SAVI, DVI, TSAVI1, NRVI and MSAVI2. Results show that NDVI, SAVI, TSAVI1, NRVI and MSAVI2 have high correlation coefficients. But RVI, DVI and PVI have low correlation coefficients. The resulting values of vegetation cover were density sliced to produce the land-cover map. After supervised classifications and density slicing of Vegetation Indices, classifacation accuracy was assessed and, finally, land-use map of the study area was produced with Hybrid classification method. Supervised classification with maximum likelihood method was the best technique for land-use mapping in the study area the total Kappa index was %87. In general, detection of some land-use classes through single date TM data is not feasible, these include: scattered forest trees with cultivated understory, annual grasses, and fallow lands. Also TM digital data are incapable of distinguishing small and separated rural constructions or soil-covered routes.
K. Solaimani, R. Tamartash, F. Alavi, S. Lotfi,
Volume 11, Issue 40 (7-2007)
Abstract
In order to manage the rangeland resources, remote sensing data is able to provide a sensible role of different cases in flora community such as biomass. The study area in SefidAb subbasin of the Lar Dam basin is located in central Alborz, where the climatic condition is semihumid and near to moderate. For the assessment of the sattelite data and their capability in estimation of the range production, Landsat-TM data with different bands was used. In this research, the field data was collected using random-systematic method in 20 sampling units of 200 plots. For geographic coordinates of the sampling units and related pixels in digital data, GPS and also existing benchmark data of the nearest points were used. Then correlation between ground data and vegetation index from different band combination was investigated and the reasonble vegetation indices were obtained. Finally, the best models were extracted for this purpose, which showed sensible relation between the field data and vegetation index. Therefor, it is possible to estimate range production using Landsat TM data related to ground control.
J. Abdollahi, N. Baghestani, M.h. Saveqebi, M.h. Rahimian,
Volume 12, Issue 44 (7-2008)
Abstract
The present study discusses a method used to produce updated information about vegetation cover in arid and semi-arid zones, using RS data and GIS technique. In this method, Landsat ETM+ data in 2002 was collected in an area of about 60000 ha in Nodoushan basin, Yazd, Iran. To collect the necessary ground data, 50 sites of different vegetation types were selected and the percentage of vegetation cover in each one was determined. Also, different vegetation and soil indices were derived and crossed with located sampling points using ILWIS software capabilities. To get the best fitted curve, the relationship between vegetation cover, as a dependent variable, and satellite data bands, vegetation indices and environmental factors, as independent variables were assessed. Therefore, a multiple linear regression model was established for the prediction of vegetation cover percentage in the studied area. Finally, a vegetation cover map with high a precision was produced. As a conclusion, it can be said that mapping of vegetation cover via remote sensing is possible even if its vegetation cover is sparse.
A Masjedi, M Fathi Moghadam, B Shomalnasab,
Volume 12, Issue 46 (1-2009)
Abstract
Tamarix sricta plant grows in riversides of Karun river. Outer body plant in the flood times causes decrease in water velocity, preventing erosion. One of the factors by which the hydraulic resistance is expressed is the roughness coefficient. Measurement of roughness coefficient of the existing plants in these riversides and floodplains, and surveying their effects on the velocity decrease and shear stress of the flow are important. The present research studies roughness coefficient of the plants manning existing in the riverside. Tamaix sricta was studied in non-submerged and sub-critical conditions in a flume with the length of 12.6 m, width of 0.5 m and height of 0.6 m in different velocity, discharge and depth ranges. The height of plants in this study was 35 cm with a natural arrangement in a bench of 2.8 m in length put in the bed of the flume. The total number of the experiments is 22. The results of this study show that roughness coefficients of plants are functions of velocity, depth, hydraulic radius and type of plants. Roughness coefficients in non-submerge condition change nonlinearly with changes in velocity, depth, Reynolds number, submerge depth and (VR) in natural conditions.
A. H. Gharehsheikhloo, M. R. Vahabi, H. R. Karimzadeh ,
Volume 14, Issue 53 (10-2010)
Abstract
The purpose of this study was to compare the physical and chemical characteristics of soils covered with vegetation and soils without vegetation in Dagh-e- Sorkh Ardestan area.To achieve the goal, first the vegetation was classified using physiognomic method, and for each vegetation type, the distinctive area was specified for soil and vegetation sampling. Vegetation sampling was done by stratified random sampling. Alongside pursuing the case, twenty two soil physical and chemical factors were investigated also for each growth type and area without vegetation. In the next step, to investigate the similarities and dissimilarities of the soils of desert areas by means of PC-ORD software, the cluster analysis was performe. After simplifying the one-way ANOVA, the most important soil factors which were effective in causing differences in the area’s soils were identified. Results show that the soils of area covered with vegetation differed much from the soils without vegetation physically in such a way that, the soil texture became heavier and gravel percentage became less in the areas without vegetation. Regarding the chemical characteristics, the frequencies of sodium, magnesium, calcium and chlorines and electrical conductivity were highly different. Because of topographic condition of land without vegetation, runoff is directed to this place and deposits salts there. Also, high groundwater level and capillary flowing salts are the important reasons for the salinity of this place. These are the limiting factors for the vegetation establishment in the desert areas of Ardestan.
S. Soltani , L. Yaghmaei , M. Khodagholi , R. Saboohi ,
Volume 14, Issue 54 (1-2011)
Abstract
The temporal and spatial vegetation dynamics is highly dependent on many different environmental and biophysical factors. Among these, climate is one of the most important factors that influence the growth and condition of vegetation. Of the abiotic factors affecting the geographic distribution of vegetation type, climate is probably the most important. Ecological research has traditionally aimed to generalize vegetation types that are assumed to be homogenous. Most of climatic classifications related to bioclimate are focused on limited climatic factors such as temperatue, precipitation and combination of them. As climate is a compound phenomena using limited factors cannot show the climate of a region, and as a result most climatic factors must be considered in bioclimatic classification. Therefore, a climatic study using various climatic factors could reveal the effective factors in distribution of vegetation. In order to determine bioclimatic zones in Chahar-Mahal & Bakhtiari province using multivariate statistical method, 71 climatic variables, which were more important in plant ecological conditions, were selected and evaluated by the factor analysis. The factor analysis revealed that the first three factors which explain %91.8 of total variance among the selected variables were temperature, precipitation, and radiation. According to results and using hierarchical cluster analysis in Ward’s method, bioclimatic classification in Chahar-Mahal province was carried out and 5 bioclimatic zones were found. In addition, Chahar-Mahal province was classified by 4 traditional climatic classification methods (Koppen, Gaussen, Emberger and De Martonne) and those classes were compared to climatic classes obtained by multivariate statistical method. The latter comparison was suggestive of the fact that multivariate statistical method provides a more appropriate classification in comparison to the traditional methods, specially because more dominant vegetation species could be defined for each of the newly described climatic classes. Furthermore, dominant species were determined for each climatic region.
L. Parviz , M. Kholghi, Kh. Valizadeh,
Volume 15, Issue 56 (7-2011)
Abstract
The determination of air temperature is important in the energy balance calculation, hydrology and meteorological studies. In this regard, the limited number of meteorological stations is one of the serious problems for air temperature determination on a large spatial scale. The remote sensing technique by covering large areas and using updated satellite images might be appropriate for estimation of this parameter. In this research, the negative correlation between land surface temperature and vegetation index (NDVI) has been used for air temperature estimation through TVX method in which the inference of air temperature is based on the hypothesis that the temperature of the dense vegetation canopy is close to air temperature. For investigation the performance of TVX method, images of MODIS sensor have been applied for the Sefidrod River basin in the years 1381- 1382-1384. The spilt window technique which was developed by Price has been used for land surface temperature calculation. The mean difference between observed and estimated land surface temperature using Price algorithm was about 6.2Co. This error can affect the air temperature values. Because of using NDVI index in TVX method, this method has the sensitivity to the vegetation density, though in the parts with sparse vegetation, the value of error increases. 4 percent variation of air temperature against the 0.05 increasing of maximum NDVI indicates the high performance of TVX method for air temperature estimation in large areas.
L. Khodakarami , A. Soffianian,
Volume 16, Issue 59 (4-2012)
Abstract
Precision farming aims to optimize field-level management by providing information on production rate, crop needs, nutrients, pest/disease control, environmental contamination, timing of field practices, soil organic matter and irrigation. Remote sensing and GIS have made huge impacts on agricultural industry by monitoring and managing agricultural lands. Using vegetation indices have been widely used for quantifying net annual production on different scales. The aim of this study was to find a rapid method with acceptable precision for the identification and classification of agricultural lands under cultivation (wheat and barley, alfalfa and potatoes). We used multi-temporal AWiFS data and applied Boolean logic and unsupervised classification.
Results indicated that Boolean logic approach had a higher accuracy and precision in comparison to unsupervised classification, although it is more complicated and time consuming.
F. Imani, M. Moradi, R. Basiri,
Volume 20, Issue 77 (11-2016)
Abstract
This study was done to evaluate the effect of afforestation in sand dunes at the vicinity of Shush, because of the importance of soil protection and wind erosion in sand dunes, also sand dunes afforestation as an effective and long lasting fixation mechanism. The study site was covered by petroleum mulch about 20 years ago and afforested by Prosopis juliflora. To study the effects of afforestation on sand dunes, two 10 ha afforested sites (25-50 and 75-100 percent canopy coverage) and control were selected. In each of studied site 15 plots were established and soil physiochemical properties were determined. Our result indicated that afforestation caused soil texture to change from sandy to sandy-loam. Also, soil phosphorus, potassium, organic carbon and nitrogen increased in 0-5 cm soil depth by afforestation that could be because of nutrient absorption from soil depth and returning to the surface by litter fall compared to the control. This study revealed that 25-50 percent canopy coverage resulted in better soil physiochemical properties compared to control site. In conclusion, sand dunes afforestation not only resulted in sand dunes fixation but also soil fertility and long lasting fixation.
F. Jalilian, B. Behmanesh, M. Mohammad Esmaeili, P. Gholami,
Volume 21, Issue 2 (8-2017)
Abstract
In this study, different indices of vegetation cover variations and different physicochemical properties of soil in three treatments of flood spreading, enclosure and grazing (control) were investigated and compared in in the region of Peshert in Mazandaran province. In order to measure different soil characteristics, 18 soil samples (six withdrawals at any treatment) from a depth of zero to 30 cm were taken from the desired treatments. In order to investigate different vegetation indices, a total of 90 plots (nine transects of 100 m) were run using systematic random sampling in the studied treatments and the necessary measurements were done (30 plots at any treatment). Then, in each of these plots, canopy coverage percentage was determined separately for each species and to evaluate and assess the diversity and richness in all three treatments, Shannon-Wiener and Simpson diversity indices and Menhink and Margalef richness indices were used. Finally, the data obtained from both sections of soil and vegetation in three studied treatments were compared and analyzed using one-way ANOVA and Duncan test. The results showed that floodwater spreading and enclosure significantly increased the percentage of sand and total Nitrogen, and significantly reduced the percentage of silt and potassium compared to control treatment. Also, percentage of clay and organic matter, soil pH levels, conductivity and soil phosphorus showed no significant differences in the treatments under study. The results of variance analysis of various indices of diversity, richness and species evenness showed that all indicators had significant responses in three treatments and the highest diversity and species richness were observed in flood spreading and enclosure treatments. Due to changes in soil properties and vegetation in flood spreading and enclosure treatments compared to the control treatment, it can be stated that operations of floodwater spreading and enclosure in the studied region has had positive effect on modification of soil texture, increasing the permeability of the soil and ultimately improvement of the vegetation.
M. Kazemi, H. Karimzadeh, M. Tarkesh Esfahani, H. Bashari,
Volume 22, Issue 4 (3-2019)
Abstract
Evaluating the possible relationships between vegetation and environmental characteristics can assist managers to identify effective factors influencing plants establishment and to characterize various vegetation communities. This study was aimed to evaluate the effects of long term grazing exclusion ( more than 33 years) and the controlled grazing system (resting – rotation grazing system) on the vegetation distribution and some soil properties in the Hamzavi research station in Hanna area-Semirom, Isfahan. Six transects (three parallel transects and three transects perpendicular to the general slope of the area) were established in each area and 10 square plots with the size of 2m2 were placed along each transect; then, the cover percentage, production and list of all plant species were recorded. In each area, eighteen plots were collected randomly and in each plot, five soil samples were collected from 0-30 cm of the soil and then the samples were mixed and one sample of the compound was selected as an evidence plot. Soil properties such as pH, EC, CaCO3, organic carbon, absorbable phosphor, total nitrogen, K, Ca, Mg, soil saturated percentage, cation exchange capacity, soil clay, silt, sand and fine sand contents were measured in the soil laboratory. The independent t test was used to compare the vegetation characteristics in two areas. Cation exchange capacity, CaCO3, gravel percentage, soil phosphor content and grazing management were identified as the most discriminative factors in separating vegetation communities based on Canonical correspondence analysis (CCA) and cluster analysis. Controlled grazing management significantly modified some soil characteristics and increased the production (352 versus 184.2 kg/ha) and vegetation cover percentage (25.46 versus 18.37), as compared to the exclusion area (α= 5%). The vegetation density was increased significantly in the exclusion rather than controlled grazing area (3.03 versus 2.02 plant/m2). This study, therefore, revealed that controlled grazing management was more effective on improving some soil quality and vegetation characteristics rather than p long term grazing exclusion in the semi-arid ecosystems. So, avoiding long term grazing exclusion in semi-arid rangelands is suggested.
R. Jafari, H. Sanati,
Volume 25, Issue 3 (12-2021)
Abstract
The southern regions of Kerman Province have repeatedly encountered dust storms. Therefore, the objective of this study was to identify dust sources using effective parameters such as vegetation cover, land surface temperature, soil moisture, soil texture, and slope as well as to detect dust storms originating from these regions based on 31 MODIS images in 2016 and SRTM data. After normalizing parameters, the dust source map was prepared by fuzzy logic and assessed with an error matrix and available dust source map. Results showed that 30.5% of the study area was classified as a low source of dust, 39.55% as moderate, and 29.85% as severe-very severe. The overall accuracy of the produced map was about 70% and the producer and user accuracy of the severe-very severe class was more than 87%. The detection of dust storms originated from the identified dust sources also confirmed a crisis situation in the region. Due to the repeatability and continuity of obtained dust source map at pixel scale, it can be used to update available dust source maps and manage dust crisis in the region, properly.
M. Abdi, H. Sharifan, H. Jafari, Kh. Ghorbani,
Volume 26, Issue 2 (9-2022)
Abstract
The irrigation schedule of crops is the most effective way to increase agricultural water use efficiency. In irrigation planning, determining the irrigation time is more important and difficult than determining the depth of irrigation water. Among all methods of determining the irrigation time of crops, the methods which used plants are more accurate than other methods. In this study, the wheat water stress index has been used which is based on the air vapor pressure deficit and the difference between vegetation and air temperature (Tc-Ta). First of all, the diagram and the relationship between the top and bottom baselines were extracted, then the water stress index of wheat was drawn in the Karaj region. Secondly, to determine the optimal water stress index of wheat, four treatments including I1: 30% of maximum allowable depletion of moisture, I2: 45% of maximum allowable depletion of moisture, I3: 60% of maximum allowable depletion of moisture, I4: 75% of maximum allowable depletion of moisture were performed in four replications. The amount of water stress index of each treatment was calculated during the season separately, and the CWSI of the treatment with the highest water use efficiency was used to determine the irrigation time of wheat. The results showed that the relationship between the upper and lower baseline for wheat in the Karaj region is Tc-Ta = 3.6 0c and
Tc-Ta = -0.27VPD - 2.64, respectively. The treatment of 45% of maximum allowable depletion of moisture had the highest water use efficiency and the optimal water stress index for wheat was obtained at 0.36 in the Karaj region.
V. Habibi Arbatani, M. Akbari, Z. Moghaddam, A.m. Bayat,
Volume 26, Issue 4 (3-2023)
Abstract
In recent years, indirect methods such as remote sensing and data mining have been used to estimate soil salinity. In this research, the electrical conductivity of 94 soil samples from 0 to 100 cm was measured using the Hypercube technique in the Saveh plain. 23 types of input data were used in the form of topographic and spectral categories. Land area parameters such as the Topographic Wetness Index (TWI), Terrain Classification Index (TCI), Stream Power Index (STP), Digital Elevation Model (DEM), and Length of Slope (LS) were considered as topographic inputs using Arc-GIS and SAGA software. Also, salinity spatial and vegetation indices were extracted from Landsat 8 images and were considered spectral inputs. The GMDH neural network was used to model salinity with a ratio of 70% for training and 30% for validation. The results showed that the soil salinity values were between 0.1 and 18 with mean and standard deviation of 5 and 4.7 dS/m, respectively. Also, the results of modeling indicated that the statistical parameters R2, MBE, and NRMSE in the training step were 0.80, 0.06, and 42.1%, respectively. The same values in the validation step were 0.79, 0.13, and 48.7%, respectively. Therefore, the application of spectral, topographic, and GMDH neural network indices for modeling soil salinity is effective.
H. Jafari,
Volume 27, Issue 2 (9-2023)
Abstract
The ability of remote sensing (RS) in irrigation scheduling has been accepted in the world due to the collection of data on a large scale and the determination of water stress indicators with greater speed and less cost. Crop Water Stress Index (CWSI) and Water Deficit Index (WDI) are components of the most recognized water stress indices. Despite the accuracy and precision of the CWSI index that has been proven in plant irrigation scheduling, the lack of complete density of vegetation, especially in the early stages of growth, is one of the most important defects of using this method in crop irrigation scheduling. While estimating the water deficit index using remote sensing technology does not have these limitations. An experiment was performed in the crop year 98-99 in the city of Karaj to check the accuracy of this index. The amount of WDI and CWSI in a wheat field with optimized irrigation management was determined and compared and evaluated using statistical parameters. The results showed that the coefficient of explanation between these two indicators in the months of April, May, and June is 0.77, 0.85, and 0.71, respectively.
S. Afshari, H. Yazdian, A. Rezaei,
Volume 27, Issue 3 (12-2023)
Abstract
Awareness of the types of vegetation changes and human activities in different parts has particular importance as basic information for different planning. It is very difficult and expensive to collect information about the continuous changes in vegetation cover by conventional methods. Therefore, the use of new technologies such as remote sensing is very beneficial. The objective of the present research was to introduce the appropriate vegetation index and determine the vegetation cover of the Abshar network. NDVI, EVI, SAVI, and MSAVI vegetation indices were calculated from 2000 to 2021 every year and monthly in the Google Earth Engine system using Landsat 7 satellite images of the ETM+ sensor. Also, the SPI drought index was calculated using the precipitation statistics of Kohrang station in Excel software. The results of the comparison of four indices showed the superiority and higher performance of NDVI compared to the other three indices for detecting vegetation changes. Then, vegetation changes were calculated. The results showed that the trend of agricultural development in the Abshar network is downward and has a direct relationship with precipitation and the SPI drought index. Also, the results indicated that the SPI drought index was equal to -1.73in 2008, which showed a severe drought in the region. Comparing these results with the vegetation area showed that the vegetation area was 35721 hectares in this year and the year after the drought (2009), the vegetation area was 22950 hectares. Therefore, there was a decrease in precipitation and a sharp decrease in the SPI index in 2008, which led to a sharp decrease of 35% in the vegetation area in 2009.
