Integration of Remote Sensing data and GIS for prediction of land cover map
Author(s)– Samereh Falahatka et.al.,
Satellite remote sensing and geographic information system (GIS) have been widely applied in identifying and analyzing land use and land cover change. In this study, aerial photos and MSS, TM and ETM+ images of Isfahan and its environs were used to provide maps of land cover for 1955, 1972, 1990 and 2001. A hybrid method was used for image classification: a combination of supervised and unsupervised classification. Cellular automata filter facilities and Markov model were used together in a CA-Markov model for predicting land cover maps. To study the accuracy of the predicted maps and validation of the CA-Markov model, three methods were used: a calculating agreement and disagreement table, a chi-squared goodness-of-fit test and an error matrix. The results indicate that if land cover change processes are constant, the CA Markov model predicts land cover changes for the following years, for which agreement between predicted maps with actual map is less than 70% in this study area.
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Econometric modeling and sensitivity analysis of costs of inputs for sunflower production in Iran
Author(s)– S. H. Mousavi-Avval, S. Rafiee, A. Jafari, A. Mohammadi
The main objectives of the present study were to estimate the relationship between input costs and the yield value of sunflower production and to analyze the sensitivity of inputs on yield. For these purposes, an economical analysis was conducted in 95 randomly selected sunflower farms in Golestan province, the main center of oilseed production in Iran. The results revealed that land, human labor and machinery inputs had the highest share from total cost of production. Also, the benefit to cost ratio and productivity were calculated as 1.13 and 1.98 kg $-1, respectively. The results of econometric model development showed that human labor, machinery, chemicals, chemical fertilizer and water for irrigation were the most important inputs, significantly contributed to yield; while, the use of farmyard manure, seed and land inputs was inconsistent with output. Moreover, the sensitivity analysis revealed that water for irrigation, machinery and chemical fertilizer input costs had the highest marginal physical productivity and consequently the strong influence on the output variable; so that, an additional utilize of 1 $ of each of the cost of these inputs would result in increase in yield by 0.62, 0.28 and 0.12 kg, respectively.
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Study on ambient concentrations of air quality parameters (O3, SO2, CO and PM10) in different months in Shiraz city, Iran
Author(s)- Mansouri.B, Hoshyari.E, Mansouri.A
More pollutants in the air influence on human health. The air pollutants emission problem has received a lot of public attentions and academic researchers in the past decades. The objective of this study is to investigate of monthly variations of ozone (O3), sulphur dioxide (SO2), carbon monoxide (CO) and particulate matter (PM10) in Shiraz city, Iran. For this reason, data of mean monthly air pollutants from two stations of pollution monitoring stations were analyzed. The concentrations of these parameters were monitored by continuous monitoring equipment for a period of four years (from 2006 to 2009). There were significant monthly variations in concentrations of air quality parameters. Results showed that mean monthly concentration CO and PM10 were higher at station 2 than station 1, and also that concentration PM10 in warm seasons was higher than cold seasons. The air quality monitoring data collected in city center of Shiraz showed seasonal variations for sulphur dioxide (SO2), carbon monoxide (CO) and PM10 concentrations..
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Energy use and cost analysis of watermelon production under different farming technologies in Iran
Author(s)- Majid Namdari
The aims of this study were to estimate the amount of input and output energy per unit area and to make an economic analysis of watermelon production in Hamadan province, Iran. A survey was conducted using a face to face questionnaire with 85 watermelon producers. The area investigated was divided into two groups. Group I was consisted of 54 farmers (owner of machinery and high level of farming technology) and Group II of 31 farmers (non-owner of machinery and low level of farming technology). The energy ratio, energy productivity, specific energy, net energy gain, also direct, indirect, renewable and non-renewable energies were calculated for both groups. The results indicated that total energy inputs were 67674.24 MJ ha-1 for Group I and 68788.37 MJ ha-1 for Group II. Only 21.03% and 19.94% of the total energy inputs used in watermelon production was renewable in Group I and Group II respectively. Results showed energy ratio of watermelon production in Group I and Group II was 1.26 and 1.13, respectively. Cost analysis expressed that benefit–cost ratio in the surveyed groups were 2.61 and 2.06, respectively. Results revealed Group I has a better condition than Group II.
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Author(s)– Mousavi-Avval SH, Rafiee S, Jafari A
In this study source wise and operation wise energy consumption for soybean production under canal and pump irrigation system conditions were investigated. Also energy and water indicators were analyzed to better understand the main effects from utilization of different irrigation systems on water and energy use. For these purposes data were collected from 94 soybean producers in Golestan province of Iran, using a face to face questionnaire method. The results revealed that under pump and canal irrigation conditions the total energy input was 38266.71 and 17255.96 MJ ha-1, and energy use efficiency was 2.14 and 4.62, respectively. The three major energy consumer inputs under pump irrigation system were electricity, fertilizers and diesel fuel; while in canal irrigation conditions they were fertilizers, diesel fuel and indirect energy of irrigation, respectively. On the other hand, water energy use efficiency was calculated as 3.68 and 29.94 for pump and canal irrigation conditions, respectively. Water energy ratio under canal irrigation was found to be 58.23%, from which the shares of direct and indirect energies of irrigation were 49.08 % and 9.15%, respectively; while under canal irrigation conditions it was found to be 15.42% and the contribution of direct energy compared to indirect energy for irrigation was relatively low. In order to reduce energy consumption and improve energy use efficiency and water productivity, it is suggested to use canal irrigation systems, design suitable schemes for high irrigation efficiency and to improve the energy use efficiency for of water pumping systems.
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