land use

This research was conducted with the aim of identifying the factors affecting the unauthorized change of agricultural land use in Azarshahr city. The current research is applied based on its purpose and descriptive-correlational in terms of its nature and method, which used structural equation modeling and was carried out using causal-relational method and covariance-variance matrix analysis. In this research, information was collected from 220 people as a sample size using the purposeful sampling method. The participants included university professors, local informants and researchers in the field of agricultural development and extension. The data obtained from the research was analyzed at two levels of descriptive and inferential statistics using SPSS statistical software and then structural equation modeling was done in Lisrel software. To calculate the validity, content and face validity methods and techniques were used, and Cronbach's alpha method was used to measure the reliability of the research questionnaire. Cronbach's alpha coefficient for analyzing the structural effects was 0.77, which indicates the reliability of the questionnaire. In the analysis of data in the Lisrel program environment, the presented model was compatible with the experimental data at the optimal level and the indicators had a good fit. In this study, the incorrect location of nuisance services from the environmental dimension, land speculation from the economic dimension, the expansion of collective spaces from the social dimension, and the diversity and mixing of uses from the physical-spatial dimension were identified as factors affecting the change of unauthorized uses in Azarshahr city.

PirBazar River is one of the most important rivers leading to Anzali Wetland. It is considered as one of the most polluted rivers in Iran due to the entry of a huge volume of industrial and urban sewage and leachate. Accordingly, about 50% of the pollution and sediment load leading to the Anzali Wetland comes from this river. The aim of this article is to investigate the trend of land use changes in the PirBazar watershed and its effects on the levels of pollution in the rivers of this area (Zardjob and Gohroud). In this study, the process of changes from 1990 to 2021 (30 years) was investigated using Landsat series satellite images (Landsat 5 and 8). 5 categories including urban, industrial, forest, agricultural and water land use were classified through vector machine algorithm and neural network. Also, the changes of each land use type in the area were examined through the LCM model. Results of the changes showed that the urban land use has been increasing in the study period. Moreover, the water quality index (NSFWQI) was directly related to the increasing trend of the residential land use and decreasing trend of the agricultural land use. According to the study results, the control of wastewater from residential areas can be an effective solution to reduce the pollution load of PirBazar River.

Examining the trends and characteristics of the affected areas is essential to effectively control and contain wind and dust erosion. This study focuses on Sarakhs County and aims to achieve this by integrating remote sensing and ground-based data. The trend of vegetation changes was analyzed using Landsat satellite images and the MSAVI index from 1995 to 2023 within the Terrst2020 environment. The intensity of wind erosion in the affected areas, including sand extraction, transport, and deposition, was identified and classified using satellite images and field surveys based on sand dune origination guidelines. By integrating the maps obtained from these steps, the location and characteristics of the degraded lands were determined. The study revealed that the average MSAVI index decreased from 0.209 in 1995 to 0.137 in 2004, indicating a decline in vegetation cover. The harvesting, transportation, and sedimentation areas accounted for 50.1%, 24.6%, and 2.4% of the degraded areas, respectively. Most of the degraded regions (88%) were in agricultural lands, primarily low-yield rainfed lands. Only 6% of the degraded areas were in pasture lands, while 48.4% were in man-made forests. It is evident that land use changes, particularly the conversion of pastures to low-yield rainfed lands, are the main drivers of land degradation and desertification, leading to increased wind erosion and dust in Sarakhs County. Therefore, practical solutions should prioritize the management of low-yield drylands through conservation agriculture and restoring degraded rangelands with the participation of local communities.

Lakes, as one of the most important aquatic ecosystems, are a coherent and interconnected set of aquatics or water-dependent plants, and the interference of natural and unnatural factors can disrupt this coherence and quality. One of the efficient methods of monitoring the changes in these ecosystems is remote sensing, which helps to monitor the changes caused by nature and human activities on lakes. The current research was conducted to study the consequences of climate and land use changes on the surface of Bakhtegan Lake over 18 years (2000 to 2017). To monitor the surface fluctuations of Bakhtegan Lake, Landsat satellite images were used in the research period, in the months with the highest surface (May and June) and the lowest surface (August and September). Lake surface and various land use areas have been extracted through a multi-band classification method and using the Support Vector Machine (SVM) method. Then, statistical methods were used to determine of impact of each variable on changes in the lake's surface. Results indicated that the surface of Bakhtegan Lake has experienced periodic fluctuations during different years and precipitation and evaporation variables have an impact on the lake surface.

Dust particles originating from internal and external sources have adverse effects on public health and the environment. Considering the unknown contribution of the mentioned resources to dust production, it is very important to investigate this issue in different regions of Iran. In addition, the analysis of spatial and temporal changes of events with different origins can be an effective step toward identifying areas more sensitive to the phenomenon of wind erosion and reducing the risks caused by its occurrence in the affected areas. The present study was conducted considering the mentioned topics as the main objectives. For this purpose, internal (codes 07-09, 98 and 30-35) and external (code 06) dust phenomenon statistics recorded in 11 synoptic stations of Kerman province in the common time frame of 2002-2020 were used. After calculating the frequency of events, the contribution of internal and external dust sources in different regions of Kerman province was determined. Using the classified map of the dust events occurrence frequency and Mann-Kendall test were respectively analyzed their spatial and temporal changes. The results showed that in the three cities of Jiroft, Anar, and Sirjan, the contribution of external events was higher than other regions of the province, about 80%, 53.8%, and 53.2%, respectively. The contribution of internal events in Shahrbabak, Rafsanjan, Shahdad, and Baft was more than 73% and in Zarand, Kerman, Bam and Kohnuj more than 52%. On average, the share of internal and external events in Kerman province was estimated to be 60.6% and 39.4%, respectively. The spatial distribution pattern of internal and external dusts showed that Bam and Jiroft were the most sensitive areas to wind erosion in the study period. In the study period, the events originating inside and outside the station in Shahdad and Zarand had a significantly increasing trend. A significant increasing trend of events with internal origin was observed in Kohnouj, Rafsanjan and Anar, and an increasing trend of dust originating outside the station was also observed in Sirjan (Z>+1.96).

Groundwater pollution is severely affected by different land uses, so that it is created widespread contamination in different areas in groundwater and endangers the health of human, livestock and other living organisms. In this study, the nitrate content of 55 water sources in Sirjan plain aquifer was investigated. Then, 5 types of land use were identified in Sirjan plain. Then, the polygon of Sirjan plain was mapped based on 5 types of land use to determine the role of each land use in the amount of groundwater nitrate in Sirjan plain. Then the amount of area and nitrate of different land uses were divided into 7 classes. The results showed that range land use in Sirjan plain has the highest level in aquifer and the lowest level of planting forests in Sirjan plain aquifer. Considering the minimum and maximum nitrate distance in Sirjan plain, the results showed that range land use has a lot of nitrate spatial variability compared to other land uses, and industrial land use has the least spatial variation in nitrate compared to other uses. In general, according to the mean amount of nitrate in Sirjan plain aquifer, the results showed that the minimum nitrate mean in different land uses of Sirjan plain is related to agricultural land use with 7.53 ppm and the maximum nitrate mean in different land uses of Sirjan plain is related to industrial land use with 10.24 ppm and the average nitrate level in planted forests, range and residential land uses with small changes is between agricultural and industrial land uses. In general, among all nitrate classes in Sirjan plain, the results showed that range land use has the highest percentage of land area, and industrial and planted forests land uses have the lowest percentage of land area.

Population growth, need to produce food and limitation of suitable agricultural lands, increase the importance of land use planning and optimization. Considering the increase in demand for groundwater resources due to the development of agriculture in Khanmirza region, optimizing of land use and water consumption is necessary as an effective strategy to conserve resources and achieving sustainable development. The purpose of this research is Optimization of cultivated area in order to Less use of water and land inputs along with more profitability from agriculture. Needed data of cultivated area, amount of water consumption, amount of production, yield and related costs were obtained from 24 major crops cultivated in the region. optimization equations with the two goals of reducing water consumption and increasing income was formulated considering three scenarios and then the optimization equations were solved. Based on the results, optimization aimed at reducing water consumption in three defined scenarios predicted a 39%, 59% and 54% reduction in water consumption, respectively. Optimization aimed at increasing income and reducing water consumption predicted respectively 43%, 45% and 39% of the current water consumption for three mentioned scenarios. It is expected that the optimal combination, having the aim of increasing profit and reducing water consumption will be 3, 3.2 and 3.2 times more profitable than the current combination.

Sustainable agriculture is achievable by establishing a balance between plant and soil, and depends on the ability of soil and plant to support native and diverse microorganisms such as mycorrhizal fungi. These fungi by increasing the growth of the host plant and the development and stimulation of root secretions especially glomalin, plays an important role in considerable stability in soil ecosystem. Changing rangelands to agricultural uses can affect the symbiosis of these fungi and endanger the stability of ecosystems. This study was conducted in an area of 310 km2 in Sarab plain, The wheat, alfalfa, and potato fields were considered as agricultural uses of neighboring rangelands as control soils. From each land use, 30 samples were taken from the rhizosphere soil and roots of the plants and a total of 120 samples were taken. The percentage of mycorrhizal colonization and the amount of root glomalin and some soil properties were measured.

The root colonization was the highest in alfalfa compared to other land uses. Root glomalin was not statistically different between land uses. Soil available phosphorus had positive effect on root colonization at lower content (< 50 mg kg-1) while colonization percent showed a marked decrease above this level.

Colonization of perennial plants was more than annual plants and available phosphorus was the most important soil property that had an effect on fungal colonization of plant roots. However, no significant relationship was observed between contents of root glomalin and soil available phosphorus in different land uses.

In order to make decisions for regional planning and achieve sustainable development, it is necessary to quantify land use and land cover changes. In this study, the land use and land cover maps of the Zayandehrood Dam watershed were prepared for the period of 1991 to 2021, using Landsat satellite images, and the changes that occurred in this period were revealed. Using the land change modeler (LCM), land use and land cover and their future changes for 2051 were modeled and predicted. The results showed that in the period between 1991 and  2021, the coverage of poor rangelands with 51,871 hectares of change had the largest decreasing trend, and the agricultural class had the largest increasing trend with 71,478 hectares of change. The largest decline in the period from 2021 to 2051 is related in the coverage of the fair rangelands class with 66192 hectares, and the agricultural class potentially has the largest increasing trend with 70328 hectares of change. The findings of this research will be useful for policymakers and planners. They can use the findings of this study for spatial planning in the region, managing the process of land use and land cover changes for sustainable development.

Land use/cover change is one of the main factors in environmental changes. The changes directly affect the value of ecosystem services. The purpose of this research is to evaluate the effect of land use/land cover change in the Kashkan area on its ecosystem services. This research was carried out in three stages, including the analysis of land cover changes, prediction of changes, and carbon storage and sequestration. Landsat satellite images of TM, ETM+, and OLI sensors were used to prepare land cover maps in three periods of 1370, 1385, and 1400. In the TerrSet software environment, LCM modeler was used to predict land cover change in 1430 and ESM modeler was used for carbon storage and sequestration. Carbon storage data were extracted from IPCC emissions. Validity was evaluated using an error matrix. The results show that forest ecosystems have had the most land cover changes and the most hot spots of carbon loss are in forests. In 1370, about 44.35% of the area, equivalent to 4113.8 square kilometers, was made up of forest ecosystems, while in 1400, it decreased to 26%, equivalent to 2411.7 square kilometers. According to the future study scenario in 1430, about 1205.8 square kilometers of the area will be forest ecosystems, and between 1400 and 1430, about 158,000 mg of carbon will be released. The results can be used by environmental planners and managers to improve and protect the natural covers, especially forests, to protect ecosystem services and their continuity.

This study was conducted to investigate the expansion of Farmland in the protected area of Kavir. In order to achieve this approach, an area of ​​33933 ha was selected in the northern part of the region, where Farmlands are only expanded in this part. Land use maps were prepared for 1986, 1994, 2002, 2013 and 2020 using the images of Landsat's TM and OLI sensors and SVM algorithm by coding in Google Earth Engine. LUCC were calculated by the LCM model. The land use map for 2054 was predicted by CA Markov. Finally, the habitat changes were evaluated by landscape metrics. The results showed that the validation coefficient of SVM was more than 0.98. The land uses were divided into three classes: Farmlands, desert scrublands, and shrub pastures. The area of ​​Farmland increased from 434.5 ha in 1986 to 4,243 ha in 2020, which has increased by 3,809 ha, of which 3,067 ha were related to the conversion of shrublands to agriculture and 822 ha were related to the conversion of shrub pastures to agriculture. Farmland has been extended towards the center of the district and along the Golu River. The most changes and increase in the cultivated area were related to the period from 2002 to 2013 (2104 ha). The forecast results for the year 2054 also indicate that the Farmlands will expand downstream along the Golu River and compared to 2020, about 2787 hectares of Farmlands will grow, of which about 2010 hectares are related to bush conversion. Shrublands to agriculture and 725 ha of it will be related to the conversion of shrub pastures to agriculture. The number and weighted profile of the shape of patches of shrubland and shrub meadows increases, the average area, contiguity and size of the patches decreases, which indicates destruction and decomposition.

In this study, the efficiency of two fuzzy methods and the integrated desertification index in Torbat-e-Heydariyeh, Khorasan Razavi province, have been compared using enhanced vegetation indices, vegetation condition index, salinity index, synthetized drought index, and temperature index for 2000 and 2020. The indices were normalized using maximum-minimum and fuzzy methods and weighted by analytical hierarchical method (AHP). Next, by weighted overlay combination and IDI method, the intensity of desertification was determined. The results showed that in the fuzzy method, 45% (1676 Km2) of the region suffers from severe and very severe desertification, and a major section (ie 55%, 2048 sq. Km) has mild and moderate intensity. In comparison, in the IDI method, no area fell into the very severe class, but at the same time, 67% (2496 Km2) of the total area fell into the extreme class. Accordingly, although the two methods have classified the area at risk of desertification, but this classification in the fuzzy method has been much stricter than the IDI method. The IDI method tends to overestimate desertification conditions. The comparison between the measured field data and similar values ​​in the obtained maps showed that the IDI method (kappa index of 0.73) was more compatible with the ground truth than the fuzzy method (kappa index of 0.54). Therefore, it can be concluded that the IDI method, although more efficient, has also overestimated the desertification in the region. Finally, this method is proposed to evaluate desertification in the region against the fuzzy method.

Soil erosion is a natural and global threat to water and soil resources. One of the most important effective factors in increasing soil erosion is changes in land use due to human activities. In this study, the impact of land use change on soil erosion in the town of Behbahan was studied using the RUSLE model in the Geographic Information System (GIS). In order to extract the final soil erosion map, the parameters of the RUSLE model consisting of R, K, L, S, C and P were first prepared for the years 2000 and 2021. These parameters were then converted into GRID format and the soil erosion map was obtained at the pixel level in the area by several of the parameters. Results from the erosion map in 2000 and 2021 indicated that the extent of soil erosion has increased over time. In 2021, the highest amount of erosion using the RUSLE model prediction is more exclusive to streams and rivers, although there is erosion across the region in different forms. The largest area in the region is classified as low erosion risk, which should be considered in planning. Among the effective erosion factors, the rain-induced erosion factor was high in the northern parts of the upstream region. Land use maps also show reduced vegetation at the soil surface. It causes a change in the number of efficient parameters in the model and thereby affects the amount of erosion in the region. Vegetation cover decreased from 2000 to 2021. The area of residential and agricultural land has increased, resulting in a reduction in natural land surface cover, and as a consequence, soil erosion conditions due to the impact of raindrops are increasing.