Journal of RS and GIS for Natural Resources
Year:2018 | Volume:9 | Issue:2 (31) |Papers Count:11

Drought as a natural hazard has always affected some parts of the country. Nowadays, it is possible to study drought using remote sensing techniques through its effects on the plants and achieve more accurate and efficient results for drought modelling. This study aims to investigate the relationship between meteorological, hydrological and agricultural drought using drought indices and remote sensing method in Gharehsou watershed. For this purpose, MODIS images (satellite Terra, product MODO9Q1) and rainfall and discharge data of five meteorological and hydrometric stations for 2000 to 2015 time period were used. The results of the comparison of meteorological, hydrological and agricultural drought represent conformity of the three types of drought in the years 2000, 2001, 2004, 2005, 2007, 2009, 2010, 2011, 2012, 2013, 2014 and 2015. Although the SPI and NDVI values were positive in the years 2002, 2003 and 2008, SDI index showed the occurrence of hydrological drought (negative values). In the year 2006 despite the rainfall increase, but this year has been facing the agricultural and hydrological drought. So the results simultaneity of drought there does not exist in all the years. The results of Pearson correlation showed there is a high correlation between mean NDVI and SPI and SDI indices equal to 0.706 and 0.788 respectively at the significance level of 0.01. Generally, the results of SDI and SPI indices largely confirm the results of the NDVI index.

Desertification is one of the most complex environmental threats with negative effects on the socioeconomic that play an increasing role in the severity of land degradation over the times. This study was carried out to monitoring the spatiotemporal variability of the criteria and indices effective on desertification in an arid region in the south of Khorasan Razavi province. Primary data, such as climatic parameters, vegetation, geology, soil, groundwater and surface water, agriculture and socioeconomic data were collected and introduced into the GIS environment, and a geobiofacies unit map was prepared. Then, desertification intensity was calculated by using the Iranian Model for Desertification Potential Assessment (IMDPA). Evaluations of indices were done based on available data and maps, expert opinions and satellite imagery in a GIS environment.The results showed the desertification severity being in two classes of medium and severe with 77% and 22%, respectively. Periodic monitoring of the effective indices on desertification also showed that low precipitation over the past 25 years 1984-2009 has caused increasing drylands and droughts. Assessment of land use changes during 10 years 2001-2011 indicated decreasing 6% in rangelands and an increase in agriculture, which was mainly due to 1.5% population growth rate during the years 1986 to 2011.The excessive removal of groundwater aquifers also caused a 10% drop in the wells water levels, resulting in increased land salinity as well as an increase in wind erosion in more than 93% of the study area.

Due to the costs of natural resources projects, detailed studies are necessary, because the lack of positive response of plans will follow the loss of human capital and funds and lack of trust in anchors plan and natural resources departments of residents’ watersheds.The purpose of this research was locating corrective operations and recovery using Geographic Information System and Boolean method and comparing the results with the implemented projects in the watershed Maikhoran in 2006. Locating the corrective operations were done based on a map of rainfall, slope, soil and rangeland condition and then with incorporating the maps of the forecast operations for all applicable operations were introduced suitable places map. This map was included seed planting 4.761, Field strip cropping 6.973, heap planting 15.154, pitting 0.127, rippering 0.455, seed spraying 10.046 and transformation of low- yielding farms to pastures 17.977 square kilometres and exclosure throughout the entire basin. The implemented design in the spring of 1385 had a heap planting in 3.004, selling in 7.675, management, grazing in 51.717, protection of sensitive lands and transformation of low- yielding farms to pasture in 15.271 and 2.067 square kilometres of rangelands. Then, by matching the two maps obtained the kappa coefficient 0.27 that represents low matching between two maps.This result represents disproportion between located operations with implementing operations, according to the current situation in the region too.

Development requires land, and the most obvious feature of the development, land use change, and hence pollution of the land's landscape. For an investigation into the effect of disturbance on the landscape, land use map, using Landsat satellite image of 2016, is produced. Calculating the LPI, LSI, MPS and SHDI metrics, the two viewpoints are considered in the case study area. The height of the observer is applied to the DSM map of this region and a visible zone of these points is determined. Therefore, the visual disturbance criterion is examined. According to the man-made and natural uses, this criterion is quantified, considering the above-mentioned metrics. LSI value changes from one to infinity. At the first viewpoint, amounts of the LSI are 21.32, 19 and 2.35 for forest, pasture and mine respectively. Also, in the second one, 7.27, 26.91, 22.24, 1.66, 3.90 and 13.78 are obtained for residential land, forest, pasture, aquaculture, agriculture and rocks. Small LSI numbers of mine, aquaculture and agriculture, being about one, indicates the presence of a human in these areas. The results of MPS and SHDI metrics show that the natural land use of pasture and forest are cut by the manmade of mine. From the second viewpoint, forest, pasture and rocks, having large and close MPS numbers, give a natural face to the landscape. The presence of agriculture, residential and aquaculture with small MPS values, being different from the natural land use, causes a lack of naturalness and disturbance in this part of the region. This study could develop the new and basic method for the understanding of landscape changes in the planning and management fields.

Green space has an important role in the quality of urban environments. The purpose of this study was to investigate the relationships between urban green space, air and noise pollution and temperature in Tehran using landscape metrics approach. For this purpose, the green space map was prepared and updated and then landscape metrics were calculated. Then, through interpolated of annual mean data, the air and noise pollution maps were extracted, while the temperature map was prepared by the regression method.Finally, the required information from the prepared maps was extracted for 52 study units and was analyzed using structural equations modelling. The results indicated green space has a decreasing effect on air and noise pollution and temperature. As per unit increase in standard deviation of green space, 0.509 units in the standard deviation of temperature, 0.462 units in the standard deviation of noise pollution and also 0.831 units in the standard deviation of air pollution decrease were observed. For green space construct, the indices of cohesion and patch density had the highest role and the area index had the lowest role in decreasing air and noise pollution and temperature. The highest and lowest amounts of green space construct effect on the air pollution were related to particles less than 2.5 microns and sulfur dioxide, respectively. The Cronbach's Alpha value was 0.807 and the Composite Reliability coefficient of 0.808 indicates high reliability and Average Variance Extracted of 0.523 represents a high convergence validity in the air pollution constructs. In the green space construct, the variance inflation factor value indicates a noncollinearity error.

Study spectral reflectance through spectral indices allows the optimal use of the wide range of spectral wavelengths in hyperspectral data. The purpose of this study was to introduce and evaluate the performance of spectral indices to discriminate dominant orchard species in Chaharmahal Bakhtiari province. In this study, 150 spectral curves were measured in the range of 350 to 2500 mm, from grapes, walnuts and almond trees.After the initial correction, 30 of the most important spectral indices were extracted.Analysis of variance and comparisons of meanings was applied to identify the optimal indices for species discrimination at a 99% confidence level. Then, an artificial neural network (ANN) and support vector machine (SVM) approaches were used to evaluate the performance of indices in species discrimination. ANOVA results indicated that the Moisture Stress Index (MSI), Band ratio at 1, 200 nm, normalized phaepophytiniz index (NPQI) and cellulose absorption index (CAI) indices are optimal for discrimination of the studied species. The performance evaluation of the introduced indicators in some of the ANN and SVM enhancement structures has been associated with 100% accuracy in both education and testing, which shows the effectiveness of these studies in distinguishing orchard species. The performance evaluation of the introduced indicators has been validated at 100% in both training and testing stages. This result emphasizes the necessity of performing spectroscopic studies to separate the orchard species beforeanalyzing the hyperspectral images due to their large data volume, high cost and huge data analysis.

The availability of suitable maps of terrain features is very important because these complications and the process governing them are the sources of many environmental hazards and resources. The purpose of this research, compare the optic and radar data for terrain feature extraction. A panchromatic band of Landsat 8 (OLI) as an optical image and two C-band Sentinel-1 satellite radar images with a resolution of 22×20 m per pixel were used. Two radar images (radar-1 and 2) in two different acquisition directions with different look angels were visually interpreted. In order to reduce the geometric and radiometric effects of the topography, the radar images were corrected using 3-second SRTM data (modified radar). In this study, four feature types were extracted by visual interpretation, which is: valleys, blades, alluvial fans, and debris fans and the results were compared with the World Imagery layer. The accuracy, completeness, quality, kappa, and z-test were calculated for every interpretation. The results showed that the highest accuracies in recognition of valleys and blades using Landsat image were 83.90% and 87.88%, respectively, and the highest accuracies of alluvial fan and the debris fan of the modified radar image were 82.76% and 83.72% respectively. The highest kappa coefficient related to the modified radar data was calculated at 54.72% (Landsat 49.74%) and the highest z-text related to Landsat-radar 1 was calculated 0.9871 (Modified Radar-Landsat 0.6443%).

In order to create sustainable development in the tourism industry, the proper understanding of environmental potentials and its sensitivity to human activities is very important. This study has identified and prioritized the potential of ecotourism sites in the Kojur basin of Mazandaran province. Physiographies criteria, including slope, direction, and elevation, as well as criteria of distance from road, river, village, sliding locations and canopy percent, were selected as the appropriate index. The criteria were evaluated and fuzzy by the experts and Analytic hierarchy process (AHP) method.Subsequently, using the Ordered weighted average (OWA) scenarios, the appropriate ecotourism site was selected. To reduce risk and increase managerial power, Boolean logic was used. The results showed that the landslide and the roads had a maximum value of 0.315 and 0.238, respectively. The output maps of the OWA scenarios have shown that the northeastern range of the cougar basin is the most optimal location for the establishment of the ecotourism site, and the northern region was ranked next. In the scenario of the low-risk level and non-compensated, and low-risk level and low compensation scenario, 83 hectares of land were recognized for the appropriate ecotourism site. While, average risk and complete compensation, high risk and low compensation, average risk and non-compensation and high risk and no compensation, were 3179, 1255, 1909, and 2577 hectares respectively for ecotourism sites. The Boolean logic output showed that about 47 hectares of northeastern lands of Kojour basin are an appropriate ecotourism site.