changes

As a dynamic system, the river always changes its location and morphological characteristics according to time, geomorphic, geological, hydrological factors and sometimes due to human intervention. Masuleh Rudkhan is one of the most important rivers in Iran that the formation of bed geometry in different periods is very different from each other. This river has a dynamic morphological behavior under the influence of various factors such as the geology of the region, the characteristics of the alluvial structure, the hydrological characteristics of its upstream basin, the structures in it and the hydraulic conditions of the flow. The purpose of this paper was to identify and extract the changes of Masouleh Rudkhan in Guilan province in the period 2000 to 2020 using satellite image processing. The images used were the images of Landsat 5 satellite on 06/06/2000 and Landsat 8 on 13/06/2020. SVM classification method and NDWI, MNDWI, AWEI and WRI indices were used for image processing. Changes in the SVM classification method showed that the river area has decreased by 314.26 hectares from 2000 to 2020. These changes mean an increase in construction on the riverbed and a decrease in the amount of water in the river. Comparing kappa coefficient and overall image processing accuracy, it was observed that AWEI index with kappa coefficient and overall accuracy of 0.93 and 0.95 in 2000 and kappa coefficient and overall accuracy of 0.94 and 0.96 in 2020 had the highest accuracy and Masouleh Rudkhan route in this index to Google earth moved. By examining the river route in a period of 20 years, it was observed that at 5 km from the beginning of the basin, the river route is 100 meters to the south, at 7.5 km, the river route is 50 meters to the south, at 29.3 km, it is 45 meters to On the south side, at km 48, it is 38 meters to the north and at km 50 to 56, it has changed continuously and the reason for this change is the high erosion in this part of Masouleh River.

Considering the ever-increasing changes in land uses and the need for managers and experts to know how changes have taken place in policy and options for solving the existing problems. Detection of changes to determine the trend over time seems necessary. On the other hand, modeling future changes is important for understanding the quality of future changes. Therefore, the full recognition of land use, its past changes and the prediction of future changes plays an important role in the sustainable management of resources. Modeling land use processes is an important tool in optimizing land use and land use planning. One of the models used to predict landslide changes is the model of artificial neural networks and Markov chain analysis. The features of the artificial neural network include the ability to learn and generalize and process information in parallel. Considering the goal of urban development during the years 2000 to 2012, satellite imagery of the years 2000 and 2012 in June has been used. After the preparation of satellite imagery and pre-processing of images, the landuse in the study area for the years 2000 and 2012 has been prepared. Then useing the LCM model landuse change patterns of changes were analyzed. Then, based on the Markov chain model, the potential for changing each use to residential use is measured. This means that each pixel was capable of showing change the image from one land use to another. Then, based on the major changes in the region in the survey, three sub-models of shifting change were identified as transforming pastures into habitat areas, converting agricultural production into settlements, and transforming dryland farming into settlements. After calculating the potential for the transfer of any land use to a settlement using descriptive data, a plan for predicting the use of land for 2025 and 2040 was then provided. Given that the purpose of the present study was to assess the development of residential areas, the extent of changes in these areas were assessed during the years 2000 to 2012. The results indicate that the residential areas increased from 8.3 square kilometers in 2000 to 12.6 square kilometers in 2012, according to the land use map, and mostly changes in the urban area of Songhor area have been made. The results of the assessment of changes indicate that the land use change from irrigated agricultural to residential use during the 12 year period was 1.9 km2, which for dryland agriculture it was 0.6 kilometers, Also 1.8 km2 of rangelands has become residential. The results of this study indicate that the irrigated agricultural lands of the city of Sangar, especially the southern regions and pastures near the urban area, have had most changes. Among the changes in other uses, about 11.5 km2 of the rangeland has been converted into rainfed farming, and about 12.3 km2 of land has also become rangelands and also, about 4.7 km2 of irrigated agricultural has become arable land or Bayer land and about 1.5 km2 of rangelands has become irrigated agricultural land. The growing population has led to an increase in the number of habitat areas and, as a result, agricultural lands and pastures have undergone changes. The growing trend of settlement development varies from region to region, and in the urban area of Songhor more are moving toward the southern regions of the urban area. Considering the geomorphologic status of the study area, a large part of the range is covered by rangelands. Irrigated agricultural lands which have a significant share, are located on the outskirts of the city of Songhor, which are undergoing further changes. According to the main objective of the research, based on descriptive data such as distance from communication, distance from urban boundaries, elevation and slope, the amount of development of residential areas for 2025 and 2040 is also projected. The results of the forecast indicate that in the case of the growing trend, the development of the settlements will reach about 18.2 km2 in 2025, and will reach 24.2 km2 in 2040, due to the high potential of the southern regions of the city of Songhor, the highest rate of development of settlements will be towards these areas. The results indicate that the increasing number of settlements in the city of Songhor will lead to the degradation of high-quality agricultural lands and pastures. If the trend is continued, the irrigated agricultural around of the city of Songhor will reach the lowest level by 2040. Also most of the pastures will also be degraded. Hence, it is necessary to identify areas suitable for the development of a settlement before increasing of rate the destruction occur, so that less prone areas for agriculture and pastures can be degraded.

In the last decades, the earth’s surface has experienced various changes due to some obscure reason being caused by human activities consisting of deforestation and cities expansion. These widespread human changes pose several adverse problems. For instance, an environmental qualitative decrease which culminates in the reduction of living quality is the result of these adverse changes. Warming of the urban environment owing to oblivious effects of unstable urban expansion, replacing of natural land cover with urbanization phenomena, inter alia, pavements, buildings, concrete and other urban constructions, are discerned as the main factors of creating heat island, which cause the vanishing of land surface cooling effects. Moreover, skyscrapers and narrow streets diminish the airflow and give rise to an increase in the environment temperature. The remote sensing images are known as an appropriate information source for preparing heat maps and also benefiting from widespread applications for the precise investigation of climate changes and urban and non-urban land use changes, due to the continuous and extensive coverage, timeliness and the ability to acquire information in the reflective and thermal range of electromagnetic waves. The population of Babol city steadily increase as a result of population growth and villagers’ emigration and bring about excessive and unplanned constructions, alteration in the physical model of the city and finally expansion of the city in various directions. Physical expansion leads to numerous changes in urban land use and suburbs agricultural uses. Consequently, several serious problems occur including adversity in uses, the urban environment disorder as well as the vanishing of suburbs agricultural lands and their land use change into urban uses (residential, industrial and etc.). One of the adverse effects of urban physical expansion, declining of green space and changing of agricultural land use into the urban land use is the rise in the surface temperature. The aim of this study was to investigate the effects of Babol city expansion on changes in temperature classes and the thermal effects of built-up and non-built-up lands on each other during the period of 1985-2015. For this purpose, multi-temporal Landsat images were used in this study. For calculating the land surface temperature, ingle channel algorithm were used, and Maximum likelihood algorithm was also applied to classify images. Therefore, land use changes and land surface temperatures (LST) were examined, and thereby the relationship between land-use changes was analyzed with the land surface temperature. Surface temperature changes map for the period of 1985-2015 was prepared and analyzed regarding land use changes map for the study area to investigate the effects of land use changes on surface temperatures changes. By using the mean and standard deviation of normalized thermal images, the area was divided into three thermal classes. The status of each land use in the specified thermal classes and the impact of surface temperature in built-up and non-built-up lands on each other were investigated. The results indicate that most land use changes in the studied area belong to the change of agricultural and green space uses into built-up use in suburbs, which are 740.52 and 472.14 hectares, respectively. As it was shown through the findings, 92% rise was observed for the built-up use area. These changes are more significant in the periphery of the city. The use of green space has risen from 1656.55 hectares in 1985 to 2036.52 hectares in 2015, which shows an increase of 23 percent. The trend of growing the use of green space on the periphery of the city is clearly characterized by the conversion of agricultural land to citrus gardens. The growth of the use of green space is less than the growth rate of built-up use. The built-up use has experienced a significant growth trend over the study period, as area of built-up use has risen from 19% in 1985 to 52.52% of the area in the studied area in 2015. The results of the LST mean survey of land use types for the study area show that the built-up lands than the other lands have the highest LST for all years. Water lands have the lowest LST owing to the high water heat capacity. In most of the years, arable land has a lower LST mean than green space land, which is mainly due to the high moisture of the arable land and the greater activity of evapotranspiration. Most changes in surface temperature of the area are related to the distance of 0-800 meters of built-up area. The main reason could be the conversion of the agricultural and green space lands into the built-up lands in the area. The most prevalent temperature class in all years is the medium temperature class which covers the suburb lands. The hot temperature class is more highlighted in the center of the city, streets and ways out of the city. Although the adjacent of the city is covered by medium temperature class, cold temperature class are located far from the built-up urban area. Cold temperature class which follows a decreasing trend, is related to lands which are far away from the city. Also, hot temperature class at which the area increases annually, is adjacent to the city core and exit ways of the town. The highest temperature changes belong to areas which transformed from the other uses into built-up use during the past 30 years. Due to human activities which produce heat, the area which has remained in the form of built-up land use during this time period has had a noticeable temperature rise. Green space and agricultural areas which have not transformed into other land uses benefit from the least temperature changes during this time period. On account of growing of built-up land use, an increase has occurred in the area of hot temperature classes and a decrease in the area of cold temperature categories. Built-up lands have direct effect on their adjacent land surface temperature. The results of the survey with regard to arable lands and green space in different temperature classes indicate that the areas of green space and arable lands, located above the upper temperature, are proportional to areas of the land that are located in lower temperature classes and they are located in the average distance closer to the built-up lands. In other words, the green space and arable lands that are located closer to the built-up lands have higher temperature relative to the green space and arable lands which are far from the built-up lands. Also, green space lands which are located in urban environments have a higher temperature in proportion to the area of the green space lands adjacent the city owing to the high temperature of their surrounding areas. Green space lands in the urban environment, which have no high area, are more affected and classified into hot temperature classes. Built-up lands, which are located in the urban environment and adjacent to the green space, also has a lower average surface temperature than the green space, and sometimes located in the middle temperature class. This refers to the effect of moderating surface temperatures in built-up lands by green space lands. As a result, non-built-up lands with higher temperature classes are in a lower average distance from built-up lands compared to those with lower temperature classes. Built-up lands in the adjacent agricultural and green space lands have lower surface temperature compared to other built-up lands. As a result, these lands are considered to be medium temperature class. The results of this study showed the importance of planning and management for preserving agricultural and green space lands and preventing them from being transformed into built-up lands which increases the surface temperature and negative environmental impacts.