Farideh Taripanah; Abolfazl Ranjbar; Abbasali Vali; Marzieh Mokarram
Abstract
One of the new and unique sections, especially in internal studies, is the quantitative examination of unevenness. The scientific and quantitative study of topographic position has always been one of the topics that have received little attention in domestic research. So, classification and identification ...
Read More
One of the new and unique sections, especially in internal studies, is the quantitative examination of unevenness. The scientific and quantitative study of topographic position has always been one of the topics that have received little attention in domestic research. So, classification and identification of different morphometrically distinct regions are necessary. Thus, the present study aims to classify landforms in the northwest of Fars province, Kharestan region and investigate its factors affecting. In this regard, the Topographic Position Index (TPI) method was used in the first stage to classify landforms, followed by the CORINE method to determine erosion risk classes. Additionally, Landsat 8 satellite images from June 2017 were used to determine the normalized differential vegetation index (NDVI). The next step was to determine the relationship between different types of landforms and terrestrial factors such as height, slope, slope direction, topographic wetness index (TWI), Terrain Ruggedness Index (TRI) and NDVI. Finally, the status of different landforms was determined based on erosion risk classes. Results showed ten different types of landforms existed within the study area. Small plains (1.18%) were the lowest in the study area, while waterways (27.71%) and high peaks (27.48%) were the highest. The TWI was significantly correlated with landform classes at 95% level. Most of the region (91.71%) had NDVI classes of 0.1 to 0.3. Stream and u-shaped valleys were found to have higher NDVI values. Real erosion risk was classified into three classes: low, medium, and high with areas of 31.14, 31.11, and 37.78%. There were 44, 57, and 59% erosion levels in the low, medium, and high erosion classes, respectively.
alireza mahmoodi; Marzieh Mokarramb
Abstract
Today, remote sensing is used for plant studies, such as determining nutrient levels, plant diseases, water deficiency or excess, weed identification, and so on. As electromagnetic waves strike the plants, they react in different ways (absorption, reflection or passage) based on the characteristics of ...
Read More
Today, remote sensing is used for plant studies, such as determining nutrient levels, plant diseases, water deficiency or excess, weed identification, and so on. As electromagnetic waves strike the plants, they react in different ways (absorption, reflection or passage) based on the characteristics of the plants. The quantity of nutrients in a plant can be determined through measurement science in plant studies. Since the amount of nutrients in the plant can be determined, it is possible to know how much fertilizer the plant needs. On the other hand, identified the nutrients in the plant, especially rangeland plants. A spectrometer was used to measure the plant's response to electromagnetic waves in the range of 0.3 to 1.1 m. Following that, the relationship between the amount of electromagnetic waves and the amount of nutrients in these plants was determined. The results showed that in Fagonia bruguieri b1026 nm, in Peganum harmala b1040 nm, in Ziziphus spina-christi b1046 nm, in Tecurium persicum band 1030 nm, in Vitex pesedo-negundo b400 and b1038 and in Otostegia persica band They are effective in predicting the value of P. For the prediction of Zn in F. bruguieri b1026 nm band, in P.harmala b1040 nm band, in Z. spina-christi ba1045 nm band, in T. persicum pea b1030 nm band, in V. pesedo-negundo plant b1010 nm and in O. persica band They are the most effective bands. To predict Cu, it is determined using spectral band values that in F.bruguieri band is b402 nm, in P. harmala band is b410 nm, in Z. spina-christi band is b1046 nm, in T. persicum band is b1030 nm, in V.pesedo and O. persica b1038 are the most effective bands.
Abolfazl Ranjbar; Abbasali Valia; Marzieh Mokarramb; Farideh Taripanahc
Abstract
Vegetation is one of the essential factors in structure and function of terrestrial ecosystem and it is one of the principal loops in water-soil-plant-atmosphere continuum. Several studies have demonstrated that vegetation covers are sensitive to alteration of climatic, edaphic, topographic and human ...
Read More
Vegetation is one of the essential factors in structure and function of terrestrial ecosystem and it is one of the principal loops in water-soil-plant-atmosphere continuum. Several studies have demonstrated that vegetation covers are sensitive to alteration of climatic, edaphic, topographic and human activities. Thus, alteration in vegetation and its relation with the mentioned factors are important of high importance. In order to investigation of vegetation changes and its effective factors, the current study was conducted in Kharestan region placed in Fars province, Iran. In this regard, the images obtained from ETM Landsat 7 (2000-2017) and meteorological data gained from local and 17 regional meteorological stations were used. Using these images, temporal and spatial changes NDVI and NDVI anomaly were studied. A supervised classification method was used to extract land use map. Finally, the relationship of NDVI with climatic, topographic and anthropogenic factors was investigated. Relationship between NDVI and climatic and topographic factors was estimated using GWR and OLS methods, respectively. Generally, temporal variations showed a slow increasing trend in NDVI value. NDVI anomaly was mostly negative before 2008 but it turned to positive after 2009. NDVI spatial distribution showed an increasing tendency from north toward center and continued to south-west of the study area. The study shows that the vegetation cover change was caused by both natural factors and human activities. NDVI increased in agricultural and pasture lands. Also, natural vegetation has been affected by climatic factors more than irrigated vegetation (agricultural and gardens). Furthermore, vegetation variation influenced by topographic factors likes height, slope and aspect. Also, with an altitude over than 2500 m, NDVI showed a decreasing trend, on slopes lower than 5° it increased. NDVI values in north and east directions were higher than in southern aspects. The overall trend indicates an increase in temperature and a decrease in precipitation during the study period. The maximum positive and negative correlation between mean annual precipitation and NDVI using ordinary least squares method were 0.93 and 0.83, respectively. Also the maximum negative and positive correlation between NDVI and temperature were 0.65 and 0.5, respectively. The highest local R2 values between NDVI with precipitation and temperature were 0.45 and 0.44, respectively, which was observed in the central parts of the region. According to the obtained results through the present study, it can be stated that environmental factors like precipitation, altitude, slope and aspect are the Influential factors controlling vegetation in Kharestan (Fars province, Iran).
