object-oriented method

Erosion is a factor that severely threatens soil productivity and is one of the greatest obstacles to achieving sustainable development in agriculture and using natural resources. Land use changes can change the physical properties of the land surface and expose the soil to erosion by affecting the type of land use and its spatial patterns. Meshkinshahr County (located in Ardabil Province), due to its environmental characteristics, has a high potential for erosion risk. However, in recent years, due to the growing population and unprincipled land-use changes, the potential for this risk to occur at the county level has increased. Therefore, given the importance of the subject, in the present study, the study of land use changes and their role in the occurrence of erosion risk has been studied in the period between 2002 and 2024.

In this study, to investigate land use changes, first, Landsat satellite images from (OLI-TM) sensors for the years (2002 and 2024) were obtained from the US Geological Survey. Then, to prepare the images, geometric and atmospheric corrections were made to the images using the Flash method and Envi5.3 software. In the next stage, using the object-oriented classification method and the nearest neighbor algorithm by Ecognition software, land use maps were extracted in the two study periods. In the next stage, by identifying the effective factors involved in the erosion of the region (including; land use, slope, lithology, soil, distance from road, distance from river, and precipitation) and preparing information layers for each criterion in GIS, the valuation and standardization of the layers were carried out using the fuzzy membership function and weighting of the criteria, using the critic method. Finally; final analysis and modeling were performed using the WLC multi-criteria analysis method.

The results show that in the two time periods studied, the largest area of the area is covered by poor pastures and rainfed agriculture, and the lowest level of land use is related to snow-covered lands and water areas. According to the results of the study, during the period studied, the area of land used for irrigated agriculture, rainfed agriculture, residential areas, and water areas has increased. So in 2024, compared to 2002, rainfed agriculture increased by 203.78 square kilometers, irrigated agriculture by 63.06 square kilometers, residential areas by 54.48 square kilometers, and areas with water cover by 1.19 square kilometers. In contrast, the area of garden and forest land uses, good pastures, poor pastures, and snow-covered lands has decreased in 2024 compared to 2002. The results show that during the study period, the area of poor and good pastures has increased by: 180.95 and 118.59 square kilometers have decreased. The area of garden and forest lands in the county has decreased by 22.47 square kilometers in 2024, and snow cover has also decreased by 0.5 square kilometers.According to the results of weighting the criteria, in 2002, the criteria of slope, land use, lithology, and soil have the highest weight coefficients, respectively, and in 2024, the criteria of land use, slope, lithology, and soil have the highest weight coefficients.According to the erosion zoning map, in 2002, the area of the very high-risk and high-risk categories was 216.308 and 779.068 square kilometers, and the amount of these risk categories has increased to 600.348 and 820.228 square kilometers in 2024, respectively.

The high extent of the very high-risk and high-risk classes in both periods of study indicates the very high erosion potential of this county, given the environmental conditions prevailing in the area. Looking at the results of the analysis of land use changes and their compliance with the erosion risk potential maps, in addition to environmental conditions (such as the presence of loose soils, sensitive and erodible formations, high slope, rainfall, and abundance of the waterway network), the reduction in the area of pastures, orchards, and forest cover, and the increase in the area of agricultural lands (irrigated and dry) and residential areas can be stated as the most important reasons for the increase in soil erosion potential in Meshkinshahr County. Finally, according to the research results, to manage the land use of the county systematically, measures such as strengthening and restoring the vegetation cover of pastures, reducing the pressure of pasture exploitation by providing alternative jobs, converting low-yielding rainfed lands to forage crops, raising public awareness about the consequences of converting pasture lands to rainfed lands, familiarizing farmers with protective measures on sloping lands and how to cultivate them, and training them on methods of combating soil erosion are suggested.

Soil erosion is a global risk that seriously threatens water and soil resources, and land changes, especially the destruction and change of forests, are important factors involved in increasing the potential of its occurrence. Therefore, planners and managers must be aware of forest cover changes and their role in causing soil erosion over some time. The evidence shows that with the increase in population and to meet the needs of the residents, the extent of forest lands in the Ghaleroodkhan basin has decreased and the amount of soil erosion has increased. Based on this, the current research seeks to evaluate the effect of changes in forest cover on soil erosion in the Ghaleroodkhan Fuman basin.

In this research, to investigate land use changes (especially forest), Landsat satellite images from (OLI-TM) sensors for the years (1992-2023) were obtained from the American Geology website in August. Then, to prepare the images, geometric and atmospheric corrections were made on the images using the Flash method and Envi5.3 software. In the next step, using the object-oriented classification method and the nearest neighbor algorithm by Ecognition software, land use maps were extracted in 1992 and 2023. In the next step, by identifying the effective factors involved in the erosion of the region (including; land use, slope, lithology, soil, distance from the road, distance from the river, and rainfall) and preparing the information layers of each criterion in GIS, valuing and standardizing the layers using Fuzzy membership function and criteria weighting were done using Critique method. Eventually; The final analysis and modeling was done using MABAC multi-criteria analysis method.

It can be said that the largest area of use in 1992 is related to forest cover with an area of 222.17 square kilometers, which has decreased to 205.03 square kilometers in 2023. The next land use, which has the largest area in the Ghaleroodkhan basin, is the use of agricultural land. The amount of agricultural area in 1992 was about 161.03 square kilometers, which decreased by about 11 square kilometers in 2023 and reached 150.05 square kilometers. The land use of residential areas has changed the most in the last 30 years, in the starting year (1992) was about 33.01 square kilometers, and in 2023 it reached the area of 60.18 square kilometers.According to the obtained results, the criteria of slope, land use, and lithology, respectively; In 1992, with weight coefficients of 0.164, 0.154, and 0.145, and in 2023, with weight values of 0.169, 0.158, and 0.142, they received the highest value of weight coefficient in both studied periods. . Also, according to the erosion zoning maps of the studied basin, it can be seen that in 1992, the area of the layer with very high and high erosion potential was 98.92 and 118.19 square kilometers, respectively. in 2023 respectively; 132.39 and 119.94 square kilometers of the basin surface have very high erosion potential.

The results of the study show a decrease in the area of forest cover in the Ghaleroodkhan basin during the study period. So about 1700 hectares of the forest lands of the basin have been reduced and converted to other uses. Mainly, a large area of the forested lands of the basin has been converted into non-forested lands such as agriculture, residential, and pastures, which indicates the not very suitable situation for protecting the region.It can be acknowledged that according to the trend of land use changes during the studied period, the reduction of forest cover and its conversion to agricultural areas, pastures, and residential lands, as well as encroachment on the privacy and river bed in the form of changes in the use of the river to agriculture and residential. Along with other natural factors of the range, such as; The presence of sensitive and erodible formations, high slope, adequate rainfall, and the abundance of waterways have played the greatest role in increasing the soil erosion potential of the Ghaleroodkhan basin. Due to the severity of destruction in the study area, necessary management measures should be taken as soon as possible to prevent and reduce further damage to the forests of the area, as well as to reduce erosion. Eventually; It should be acknowledged that the use of the land use change map and the erosion risk zoning map obtained in the present study is a practical guide to know the state of forest destruction in the region and the erosion potential of the basin.

In recent years, the mutual impact of land use change and soil erosion has become a major environmental concern. Therefore, this study tried to investigate the changes in different land uses and evaluate the impacts of land use changes on soil erosion in Givi city. To achieve the goals of the research, first, a land use map was prepared using the object-oriented method for the two periods of 2000 and 2021. Then, according to the natural and human conditions of the area, other effective factors for erosion in the area were identified and the information layers of each of the criteria were prepared by the geographic information system. Evaluation and standardization of layers were done using the fuzzy membership function and weighting of the criteria was done using the CRITIC method. The final analysis and modeling were done using the MABAC method as one of the Multi-Criteria Decision-Making (MCDM) methods. The results showed that the largest area in 2000 is related to good and medium pastures, recording 313.172 and 283.144 square kilometers, respectively. In 2021, the biggest areas are related to poor pastures and barren lands, with 335.077 and 329.815 square kilometers, respectively. According to the 2000 erosion zoning map, 16.34% and 20.36% of the city and according to the 2021 erosion zoning, 22.92% and 25.58% of the city’s area are in very high and high erosions, respectively. Decreasing good and average pastures and lands with dense vegetation and turning them into agricultural areas, poor pastures, and man-made and barren lands have had the greatest impact on soil erosion.

The development and expansion of cities are one of the main factors in the land use change that have been neglected due to environmental, and socio-economic, environmental problems. The present research is aimed at a comparative study of urban development and land use change in two metropolises of Tabriz and Karaj during the period 2000 to 2017. The research is applied and descriptive-analytic. The object-oriented method and Heldern model were used to analyze data. Comparison of urban growth indicates the rapid growth of Karaj compared to Tabriz. Tabriz has grown 4.2% during this period, but Karaj has grown by 7% and this development has been 1.5%, 2%, and 0.5% respectively in Tabriz and 4%, 2%, and 1% in Karaj and the most degraded rangelands (10%) in Tabriz have had the most combined use of garden and agriculture with 4.5% of destruction. Holdern model shows that Karaj's growth has followed the growth of the population, and the high growth of the population has undermined the city's growth. Tabriz has an average of 0.55% growth due to population growth and 0.45% growth due to urban growth.

One of the environmental hazards and ecological crises that the world is facing today is the phenomenon of land use change (Mousavi et al., 2015) and awareness of land use changes over a period of time for planners and managers. It is very important (Tachizuka et al., 2002). On the other hand, soil is one of the most important natural resources that plays an important role in agricultural production and food security (Moghadasi et al., 1397) that during the erosion process, soil particles are separated from their main bed and with the help of a transfer agent to They are transported to another place (Maslink et al., 2017; Research et al., 2011). Surface soil erosion reduces the depth, reduces the moisture capacity and the loss of organic matter and nutrients and thus reduces soil fertility (Parvizi et al., 1399).

The research is an applied research and the result is the study of land use change and analysis of soil erosion potential in the basin upstream of Yamchi Dam in Ardabil province. This study is based on the use of remote sensing methods to achieve land use change over a period of 21 years and the use of ARAS multi-criteria analysis method in GIS environment to zoning the potential of soil erodibility of the basin. It is above the Yamchi Dam. ENVI, Ecognition, Arc GIS, Idrisi and Excel softwares have been used for image processing and data analysis. In order to investigate the risk of erosion in the data collection stage, first according to the natural and human conditions of the region, slope factors, lithology, land use, rainfall, distance from the communication road, distance from waterway and soil, as effective factors in Basin soil erosion was identified. In the next step, information layers related to each factor were prepared in the GIS environment. The information layers of communication routes and waterway network were prepared and measured using the map of communication lines and rivers of Ardabil province. The slope layer was prepared using a digital model of 12.5 m altitude, Alos satellite, Palsar sensor, obtained from the site (vertex.daac.asf.alaska.edu). To extract a layer of information related to lithology (resistance of rocks), from the geological map of Ardabil province; Used at a scale of 1: 100000. The precipitation map of the basin was drawn according to the data of meteorological and rainfall stations using the precipitation gradient equation (P: 0.227H-85.04).

It can be said that in the erosion map of both study periods, mainly high-risk and high-risk areas in agricultural uses, poor and medium rangelands, man-made areas and barren lands are located. According to the erosion zoning maps in the study area, in 2000, the area of high-risk and high-risk floors was 74.35 and 206.51 square kilometers, the amount of these risk classes in 2021, respectively; Increased by 79.40 and 219.98 square kilometers. The reason for the increase in areas with the risk of erosion can be considered in the reduction of good pastures, medium pastures and mountainous lands and their conversion into agricultural areas, poor pastures and man-made areas. Saffari et al. (1397), Asghari Saraskanrud et al. (1398), Miyahi et al. (1400), Santos et al. (2017), Kiden et al. (2019), Kojo et al. (2020), Lee et al. (2021), Also, increasing the area of agricultural lands, barren lands and residential areas and in contrast to reducing pastures have been mentioned as the main reasons for increasing the potential risk of soil erosion.At the level of the study basin, by the villagers of the region, most rangeland lands; They have changed the use of agricultural lands, especially low-loss land. Although rainfed fields play an important role in increasing agricultural production and food supply, but land use change due to the impact on vegetation and soil surface erosion, intensifies soil loss and surface runoff and thus soil quality It affects. This change of use, if it is combined with not paying attention to land capability and observing the correct principles of tillage, leads to the production of surface runoff and thus intensifies erosion, which ultimately results in reduced fertility and reduced yields. According to the combination of slope and land use map, most of the sloping meadows in the basin, which are the focus of erosion, are scattered in the middle half and to some extent in the southern parts on slopes of 15 to 35%. Given that most agricultural lands in particular; The meadows of the region are located on sloping slopes, so plowing in the direction of the slope, especially during heavy rains, leads to soil erosion. Thus, in parallel plowing, the water from rainfall flows more easily in the cultivation furrows and is removed from the arable land and as a result, water and soil loss increase. On the other hand, uncontrolled harvesting of forage from pastures to feed livestock in the cold season and early grazing in spring has reduced the amount of pastures and intensified runoff with the onset of the rainy season, and this affects the morphology of rivers. It also has a direct effect and leads to a change in bed behavior.

Knowing the ratio of uses and how it changes over time is one of the most important things in planning and policy making. In addition, soil erosion can be considered as one of the biggest obstacles to achieving sustainable development in agriculture and the use of natural resources. For this reason, the phenomenon of erosion has been considered globally. It can be added that land use change is one of the important factors in causing soil erosion. Therefore, in the present study, land use change and its role in soil erosion using telemetry techniques and ARAS multi-criteria analysis for the two periods of 2000 and 2021, has been investigated.

It is necessary to know about the quantity of urban tree canopy cover due to its role in air and noise pollution reduction, wind prevention, saving rain water, and runoff control. Being expensive and time consuming, the manual extraction of tree canopy has been replaced by remote sensing techniques conducted on the images, digitally. There are several parameters which must be optimized prior to use of object-oriented classification. One of these parameters is Scale affecting the segmentation results, significantly. Scale is usually set by trial and error which is an experimental approach. One of the aims of this study is to optimize Scale parameter, automatically. In addition, after segmentation process based on a proper Scale, it is required to classify the identified segments based on the attributes which are extracted from these segments. In this stage, the selection of suitable classification method fed by the proper attributes is critical. In this research, LiDAR data and aerial image acquired on Vaihingen, Germany, were utilized for segmenting the urban area. In order to identify suitable attributes, random forest feature selection was applied on the attributes derived from the identified segments. Machine learning methods including support vector machine, random forest, and decision tree were compared for classifying the segments based on their suitable attributes into two classes including tree canopy cover and others. The results indicated that Scale of 25 is the best one to segment this area. Also, the tree canopy cover map derived from support vector machine with quality index of 79.90 showed the best performance among different classifiers used in this study.

Mass movements and landslides are considered the most destructive natural hazards. The study predicts landslide location using conditional probability theory (Bayesian theorem), on the southern edge of the Ahar drainage basin (From Nasirabad to Sattar Khan dam),, on the landslide occurred in the past by the object-oriented approach extracting and identifying been conducted. Using Bayesian probability theory correlation between parameters and landslide areas (two-thirds of landslide areas) to determine the weight of all categories of parameters were obtained. According to the map obtained by any of the parameters weight class, class of high silt old alluvial terraces are in layers, average pasture land in between classes, directions north and northwest, steep grade 5-25 the distance of 270-125 meters from the river greatest impact on weight and landslides in the area. The accuracy of landslide susceptibility maps using a third (12 points slip) landslide areas were evaluated. The result showed that the model with the predictability and kappa coefficient 0/93   and 0/945 percent of high and very high risk of landslides in class acceptable accuracy in evaluating and landslide susceptibility mapping.

The impacts of human activities and natural events have changed the face of the earth. So, for the optimal management of natural areas, awareness of change of land is necessary. This study was carried out to detect changes in cover/land use of Abdanan region over a period of 25 years. For doing research, images of the years of 1985, 2000 and 2010 from sensors of TM, ETM+ and TM were used and after the corrections needed in preprocessing stage, the object-oriented classification method of images in Idrisi Selvi software, change detection maps prepared and presented results. The results show that during the years 1985 to 2010 are the trend of reduction of fair and good rangeland that indicate the general trend of deterioration in the region through replacement fair and good range by other land use as poor rangeland and barren land. Assessing the accuracy of the extracted parameters (Overall accuracy and Kappa coefficient of %95 and 0.94, respectively), indicating the high accurcy of the method of classification. The results obtained from this study show that he object-oriented classification method is also used for preparing of cover/land use maps and change detection.