Aims & Backgrounds Desertification is one of the major challenges in today’ s world, especially in countries like Iran that are affected by arid and semi-arid climates. To prevent and slow down the desertification process and in other words, with the aim of preventing and reducing desertification speed, the first effective and necessary step is to identify the susceptible areas and the factors contributing to this phenomenon. This research aims at assessing level of desertification in Kashan plain using an Iranian model. Methodology In this comparative study with the use of IMDPA (Iranian Model of Desertification Potential assessment), an Iranian method and model, first the desertification potential of Kashan plain in 2002 and 2016 was investigated and then the conditions of the two periods were compared. The criteria used in this model were the vegetation and climate criteria. Based on this, Landsat 7 NDVI data, CHIRPS precipitation database and MODIS satellite potential evapotranspiration data were used. Findings Based on the results and findings of this study, in 2002, 3853. 1 km2 of the area was classified as moderate desertification and 3294. 8 km2 in severe desertification group. But in 2016, there were 1035. 22 km2 of moderate desertification intensity, 6019. 3 km2 of severe desertification and 124. 22 km2 of extreme desertification. Conclusion As a result, in addition to establishing a very severe desertification in 2016, the extent of the areas with severe desertification has also expanded significantly.

Risk assessment provides the possibility of planning and management to prevent and reduce the risk of desertification. The present study is aimed to assess the hazard and risk of desertification and to develop management programs in the semi-arid western regions of Golestan Province in Iran. Desertification rate was obtained using the Iranian model of desertification potential assessment. Since the rating system was considered for the indicators, data analyses were carried out according to the Mann-Whitney test. The risk of desertification was calculated based on hazard, elements at risk and vulnerability assessment maps. The intensity of desertification was estimated to be medium. Among the factors affecting desertification, agriculture by the weighted average of 3.22 had the highest effect, followed by soil, vegetation, water and wind erosion criteria by weighted averages of 2.45, 2.32, 2.15 and 1.6 respectively.Desertification risk assessment results also showed that about 78% of central and northern parts of the region, with the largest population and residential centers, surface and underground water resources, agriculture and horticulture, is confronted with a high to very high degree of risk. Management plans and control measures, based on risk values were presented in four activities (with two management priorities under critical and non-critical conditions). For the management program with the largest area. Control measures and strategies such as the establishment of halophytic and xerophytic plants, drainage networks, resilient facilities and infrastructure were proposed. Reducing the risk of desertification, could play a crucial role in the sustainable development of drylands and desert ecosystems.

Iran is mostly consisted of arid and semi-arid areas. Rudab region, Sabzevar, is indicative of an area exposed to and affected by the risk of desertification. This study accordingly is aimed at assessing the risk of desertification using ESAs model, through mapping the risk of desertification. Initially, work units’ map was prepared based on which relevant indicators were valued. Then, relevant indices were prepared based on ESAs model using GIS. Finally, ESAI index was calculated for each work unit. After mapping the risk of desertification, desertification damages were evaluated. It was found out that the risk of desertification in Rudab can be classified at three classes i.e. class I, II, and III; and subclass III1 covered the biggest surface of the study area i.e.44.48%. Based on desertification damage map, Rudab region is divided into five classes so that class III covering 35.20 percent of the area is the biggest area. Active sandy dune faces are prone to the highest risk of desertification since they entail significant risk factors and need to be paid due attention for desert greening programs.

In the response phase the most important step is to assess disaster after occurrence. By disaster assessment, we can obtain all the needed information for controlling, decision-making and also disaster planning. Lack of disaster assessment causes you to make unsuitable decisions based on limited or inadequate data which leads to imperfect disaster response. According to IFRC, disaster response operation will have an unsuitable function without disaster assessment. This paper presents the principles and concepts of disaster assessment.

Introduction Desertification is land degradation that occurs in arid, semi-arid, and dry sub-humid areas, where water is the most important limiting factor for land use in the ecosystem (19). Desertification (31) is a term used to describe the decrease in biological productivity in ecosystems of arid, semi-arid, and dry sub-humid regions caused by climate change and human activities. To provide management solutions and prevent desertification spread globally, it is necessary to evaluate the phenomenon and its changes over time. At the global level, numerous studies have been conducted to evaluate and monitor desertification using various methods and evaluate its changes over time. In recent years, there has been a lot of attention given to remote sensing in this regard. Lamchin et al. (2016) examined land cover changes and desertification in Mongolia using remote sensing indices such as NDVI, albedo, and TGSI. It was discovered that the study area has experienced an increase in desertification each year (16). Ontel et al. (2023) investigated the trend of land degradation and desertification in Romania using remote sensing indices. The research findings revealed that 60% of the limited study area (22) had been improved and restored. In Iran, the majority of the land is located in arid, semi-arid, and hyper-arid climates (4), and the duration of the warm season is increasing in 80 percent of the regions (10). These conditions will lead to the continued growth and expansion of desertification in Iran. Therefore, finding methods to assess this phenomenon, its causes, and predict its trends will become increasingly important. The management of vegetation cover and natural resources requires an assessment of the desertification process due to the semi-arid and desert climate of Kerman province. This study aims to examine the trend of desertification over time using remote sensing due to the issue's importance and the climatic conditions of Kerman province.   Material and Methods Kerman province, with an area of 183,000 square kilometers, accounts for approximately 11% of the total area of the country. Satellite images were used to calculate the intensity of desertification to achieve the set objectives. To calculate the intensity of desertification, the DDI index introduced by Pan and Li (2013) was utilized in this study. To evaluate desertification in Kerman province, the first step was to establish the target months by utilizing the monthly NDVI average. Estimates of NDVI were made on the Google Earth Engine platform from 2001 to 2022 using the MOD09A1 product layers of the MODIS sensor, and the monthly average for the study period was then determined. An average Albedo coefficient map was calculated for the period 2001 to 2022 after determining the target months and obtaining the average NDVI map from 2001 to 2022 in these months. The intensity of desertification for the target months was calculated by performing a linear regression between NDVI and Albedo coefficient in the next step. The highest intensity of desertification for every target month was determined by determining the year with the lowest DDI value at pixel level. After calculating the DDI index for the 22-year study period, to examine the trend of desertification changes, the trend of DDI index changes for the target months was calculated from 2001 to 2022 using the non-parametric Kendall test in the TerrSet software. The slope of changes in the DDI index for the target months in time units was calculated using TerrSet software for 22 years. To simulate the trend of changes, linear regression analysis can be utilized.   Results and Discussion The highest NDVI values over the 22 years are in March, April, May, and June, which indicate the highest growth and greenness of vegetation during these months, as per the results obtained. The four months with the highest NDVI values were chosen to investigate the trend of desertification changes based on the results of this section. The most severe desertification in March was 23.93% in 2012, while the lowest was 23.0% in 2016. The highest and lowest severity of desertification in April were 22.23% and 35.0% in 2012 and 2006, respectively. The most severe desertification was recorded at 20.14% and 22.42% during May and June in 2001, while the least was 32.0% and 11.0% in 2017, respectively. The results indicate that the trendless class has allotted the largest area throughout the 22-year period, with values of 82.45%, 59.83%, 49.96%, and 51.79% in March, April, May, and June, respectively. The results indicate that desertification changes with high and very high intensity mostly occur in the southwest, south, and southeast regions of Kerman province. The northwest and northeast regions of the province are also a part of this class. The vegetation cover values in March, April, May, and June were the highest in the year, as shown by the average monthly NDVI results. Behrangmanesh et al. (2019) and Alamdarloo et al. (2018) reported that the vegetation cover in most regions of Iran is at its peak during these months. The results indicated that the intensity of desertification is increasing considerably in Kerman province in all four selected months, particularly in the southern regions. The assessment of desertification changes showed that the southern regions of Kerman province are classified as high and very high in all four selected months. The effectiveness of the desertification intensity assessment method proposed by Pan and Li (2013) can be demonstrated by analyzing the results of this study in Kerman province and comparing it to previous research in this area.

About 80 percent of Iran is arid and semi-arid and about 35 percent of this area is susceptible to desertification hazard. Therefore desertification assessment and identification of the most important criteria for the assessment of risk and a basis for development of management plans is essential. This research was conducted in the semi-arid region of Agh-Band in the Golestan province, Iran with an area of 3062.5 km2 aiming at preparation of the desertification hazard and risk maps and development of various management plans to control the desertification. In this study, the IMDPA model and geomorphologic facies were used to evaluate the desertification hazard. The work units (geomorphologic facies) were defined based on geology and land use maps, satellite images and field surveys. The risk map was developed with a combination of desertification hazard intensity and hazard elements and degree of vulnerability maps using the total risk equation. Desertification management plan was developed based on four management strategies including: no plan, maintains the status quo, avoid the risk and implement the control measures. The results indicated that soil and vegetation criteria with magnitudes of 2.67 and 2.54 fall into sever desertification category (III) and other criteria are within medium class (II). The average value of degree of desertification in the study area was 2.03 (class II).

In this research, desertification intensity of saravan region was evaluated using IMDPA a the newest method of Assessment of Desertification Potential in arid and semi arid regions of Iran. For this purpose 4 criteria including climate, vegetation cover, soil and wind erosion were selected. Each criterion was assessed based on it's indices which result in qualitative mapping of each criterion based on geometric average of the indices. Then, sensitive map of region was extracted using geometric average of all criteria. Thematic databases were integrated and elaborated in a GIS. By laminate of thematic databases layers and using this formula DM=(SIA WEIA VIA CLI) 1.4 to a Calculate a the geometric mean Criteria, the desertification intensity map was obtained with analysis IMDPA Model. The result showed that 45.24% of study area was found to be in medium and about 54.39% in high class of desertification And 0.37% of the region including residential are nat in any classification. Analysis of desertification criteria in Saravan region showed, climate criteria is a major problem with a geometric average of 3.1 which shows high class while soil with a geometric average of 2.35 has lowest effect in desertification. Also vegetation covers and wind erosion criteria with a geometric average of 2.62 and 2.87 show high class desertification.

In this research, desertification intensity of sistan plain was evaluated using IMDPA the newest method of Assessment of Desertification Potential in arid and semi arid regions of Iran. For this purpose 4 criteria selected including vegetation cover, soil, climate and wind erosion. Each criterion was assessed based on the selected indices which result in qualitative mapping of each criterion cased on geometric average of the indices. Then, sensitive map of region was extracted using geometric average of all criteria. Thematic databases, with a 1:50000 scale resolution, were integrated and elaborated in a GIS based on arc/info8, arc view3.2 and especially ILWIS. By laminate of thematic databases layers and using this formula DM=(SI×WEI× VI×CLI)1/4 to Calculate the geometric mean Criteria. Then Desertification intensity map was obtained with analysis IMDPA Model. The result showed that 51.09% of study area was found to be in medium and about 45.09% in high class of desertification. And while 3.82% of the region in clouding Residential and Water tanks (CHAH NIME) there aren’t in any classification. Analysis of desertification criteria in Sistan region showed that among study criteria, wind erosion criteria is a major problem with a geometric average of 1.67 which shows high class while soil with a weighted average of 1.34 has lowest effect in desertification. Also vegetation cover and climate criteria with a geometric average of 1.51 and 1.57 show middle class desertification.

In many countries, studies to determine the severity of desertification and providing land plans to implement desertification. One of the models is modified MEDALUS or Iranian model (IMDPA), has been used in present research in order to investigate desertification situation in the Tashk region of Fars province. In this research, the modified IMDPA model used with emphasis on the water, soil and agricultural indexes, and indicators for each criterion has been considered in different value. The qualitative values of desertification indexes placed in four classes as, low, moderate sever and very sever. Among evaluated indexes, Irrigation system and drop level of groundwater have the most effects on desertification with numerical values 4 and 3.7 respectively. In the other indexes, crop yield and SAR of water have the lowest effects on regional desertification with numerical value 1 and 1.5 reactively. Analysis of result showed that the intensity of desertification obtained 2.54 on the entire of region based on 3 indexes and in the base of modified IMDPA model, the regional desertification intensity came to get medium.

Knowledge of behavior climatic indexes can be help to planning future programs Bahabad study area in the eastern part of the province of Yazd with a hot and dry climate, high potential evapotranspiration and low rainfall has a high potential for desertification. The aim of this research is evaluation of classification intensity by IMDPA model with emphasis to climate criteria. The indices included mean annual precipitation; UTI aridity index and length of drought period were applied for preparing of intensity map of desertification by using Arc Gis software. Scores of indices were recorded in different study units. At last, using the formula, CI=(a×b×c)1.3. Final Score of climate criteria (CI) was determined in the study area based on IMDPA. In this model, desertification potential classes are moderate, and high. The result showed that 68.42% of the study area is considered as medium, and 31.58% of the study area is on the high desertification intensity class.