Desertification Index Research Articles

ASSESSMENT, MONITORING AND EARLY WARNING SYSTEM FOR DESERTIFICATION BASED ON WATER CRITERION (CASE TUDY: KASHAN, IRAN)

Abstract. Desertification is the third most important global challenge after crisis of water shortage and drought in the 21st century. Many countries, especially developing countries, are faced this phenomenon. Identifying the regions exposed to this phenomenon is so important for combating desertification. Regarding to the importance of this phenomenon, in this study, we assessed desertification in Kashan, Iran, using IMDPA model and GIS software. According to the region condition, water was selected as the criterion and some indices were identified for it. For monitoring, the effect of criterion and indices changes was investigated during 1966–1974, 1974–1992, 1992–2002 and 2002–2011. Finally, for providing the desertification early warning system, data related to the criterion and indices were collected during 2003–2011 and the threshold of each index was determined. The results showed that the class of desertification based on Electrical Conductivity index was very severe in the study area, so this index is one of the most important desertification indices in arid areas in Iran.

Integración de imágenes del sensor MODIS y cartografía temática para la simulación de modelos geoespaciales para obtener zonas propensas a desertificación en el Estado de Sinaloa, México

La desertificación es un proceso complejo, involucra factores ambientales y antro- pogénicos dentro de un contexto climático seco. Dispone de una importancia glo- bal, dado que reduce la productividad y el valor de los suelos ocasionando un impacto sobre el territorio y su población. Las Tecnologías de Información ayudan a identificar zonas propensas a desertificación a través de indicadores geoespaciales y cuantitativos. En esta investigación se planteó como objetivo el desarrollo de una propuesta metodológica que permita modelar las variables de entrada obtenidas a partir de datos del sensor MODIS, cartografía temática e información estadística, que posteriormente se integran a partir de evaluación multicriterio con la técnica sumatoria lineal ponderada. Se consideraron las siguientes variables de entrada: aumento de albedo, disminución de biomasa, deforestación, zonas con escasa vegetación y con vegetación, contenido de humedad en el suelo, precipitación, tempera- tura superficial, distancias a asentamientos humanos, zonas agrícolas, redes hidro- lógicas, zonas con degradación y erosión de suelos. La ponderación se realizó con el método de comparación por pares de Saaty. Para dar robustez al modelo genera- do, se procedió a realizar una validación de los resultados utilizando mapas de uso de suelo y vegetación, climas y humedad, índice de aridez e intensidad de degrada- ción de suelos. Los resultados obtenidos muestran que las zonas más vulnerables a desertificación son en la zona norte del Estado de Sinaloa y se reduce acorde del avance hacia el sur.

A Combined AHP- and TOPSIS-Based Approach in the Assessment of Desertification Disaster Risk

In this study, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) methods were used to determine, prioritize, and assess the most effective desertification indices. A list of 32 influential indices was identified using existing literature in Iran and around the globe through questionnaires. Criteria for evaluating indices were weighted using Shannon entropy, and then TOPSIS ranking method was applied to determine the most effective desertification assessment to deal with this issue in Kashan region, Isfahan province. Indices were weighed and prioritized by analytics hierarchy process. Finally, the Mediterranean Desertification and Land Use (MEDALUS) model was used to assess the intensity and develop a desertification risk map. The results asserted that sensitivity to minor changes with a weight of 0.341 has the highest importance, while time and cost with a weight of 0.11 has the least importance for the evaluation of indices. Among the 32 ranked indices, 20 of which were identified as the most effectual indices including annual precipitation, salinity, and vegetation, to name a few. The results also showed that the land use change index with a weight of 0.217 and annual rainfall with a weight of 0.166 have the highest priority among human and natural indices that should be prioritized in managing and controlling desertification. The average weight of quantitative desertification intensity for the whole area was 1.391 placed in critical (1) class of desertification. Among the six considered desertification criteria, the climate and the destruction of water resources were the most important criteria.

Monitoring the long-term desertification process and assessing the relative roles of its drivers in Central Asia

Desertification is one of the main ecological environmental problems in Central Asia. To prevent and eradicate this problem, it is extremely urgent to monitor the long-term desertification process and assess the relative roles of its drivers. Based on an analytical hierarchy process, in this research, the spatiotemporal features of the desertification process were surveyed from 1982 to 2012 using four indicators. Further analysis was focused on determining the relative importance of multiple driving factors causing desertification in different ecosystems. The results revealed significant desertification expansion in the western part of Central Asia, with the most severe desertification occurring in eastern Xinjiang Province and the Ustyurt Plateau, with mean desertification indexes (DIs) as high as 0.8. According to a change-year analysis, mutation years of desertification were observed from 1993 to 2002 for most vegetation types. The desertification process for different vegetation types results from different major driving factors. Climatic factors, including decreased precipitation, increased temperature and drought, were the main drivers of desertification, especially for grasslands, forests and sparse vegetation. The desertification process of sparse vegetation and croplands was expanded and triggered by human activities: oil and gas exploration in the southern Ustyurt Plateau and agricultural abandonment in northern Kazakhstan. The results also indicated that after the collapse of the Soviet Union, rangeland abandonment in eastern Kazakhstan triggered desertification reversion in grasslands. Furthermore, due to inefficient irrigation water use, severe salt accumulation in croplands of the Amu Darya River delta resulted in desertification expansion in this region. In Central Asia, the desertification process in forests and areas of sparse vegetation was extremely sensitive to climatic variations, while that in croplands and grasslands was vulnerable to human activities. Therefore, regional governments should strive to reverse desertification to protect and improve this fragile, arid ecological environment.

Study of the desertification index based on the albedo-MSAVI feature space for semi-arid steppe region

Desertification has been listed as the top of ten major problems affecting global environmental changes, and represents one of the important reasons of semi-arid grassland degradation. It is therefore crucial to understand ecological environment of semi-arid grasslands and temporal and spatial changes in real time for regional and local environmental protection and management. At present, remote sensing technology is being widely used in monitoring and evaluation of land desertification due to its wide observation range, large amount of information, fast data updating and high accuracy. It represents an advanced method for remote sensing monitoring of desertification by extracting various indicators and constructing feature space. Based on this, this study used Landsat images and field survey data to establish a desertification index (SASDI) model based on the albedo-MSAVI (Modified Soil Adjusted Vegetation Index) feature space and analyze the relationship between desertification and surface quantitative parameters in semi-arid grassland area. Results show that the SASDI model has a high correlation (R2 = 0.7585) with the organic matter in the soil surface and makes full use of multi-dimensional remote sensing information. The index reflects the surface cover, water, and heat combination as well as changes of the desertification land, with a clear biophysical significance. Moreover, the index is simple and easy to obtain, facilitating to quantitative analysis and continuous monitoring of desertification in semi-arid grasslands.

Assessment of Environmental Sensitivity to Desertification in Katsina State, Nigeria

Land degradation and Desertification (LDD) are critical issues facing most states in northern Nigeria, with severe consequences for national food security. Land degradation refers to total loss of the productive capacity of the soils for present and future use while desertification is seen as a process whereby the productivity of arid or semi-arid land falls by 10% or more. The Environmental Sensitivity to Desertification Index (ESDI) is the most frequently applied indicator-based system for accessing Land Degradation and Desertification. The research reported here adopted the MEDALUS (Mediterranean Desertification and Land Use) approach for identifying environmentally sensitive areas (ESA) to desertification in Katsina State, Nigeria based on Soil Quality Index (SQI), Climate Quality Index (CQI) and Vegetation Quality Index (VQI). The findings from each of these indicators show the variability between the northern and southern parts of Katsina State. The northern part of Katsina state was found to be the most vulnerable area to desertification and is covered by soil having the highest sand depth while the southern part of the state was found to be the least affected by desertification. This result specifically highlights areas in the State that requires urgent attention and remediation. Findings from this research can be used to support informed decision-making and policy development to focus on sustaining the environment, as well as the livelihood of the communities in the affected local government areas in the northern part of the State, given the high sensitivity of the area to desert conditions.

Quantification of land degradation sensitivity areas in Southern and Central Southeastern Europe. New results based on improving DISMED methodology with new climate data

Land degradation is considered to be a major environmental problem of the European continent, especially in the Mediterranean region. This study aims to deliver new results in terms of the actual land sensitivity to degradation in the southern and central southeastern areas of Europe, by improving the results of the DISMED (Desertification Information System for the Mediterranean) project, initiated by the European Environment Agency (EEA) after 2000. The methodology is based on updating the SDI (Sensitivity Desertification Index), which was obtained in the DISMED project based on three biophysical parameters, i.e. Climate Quality Index (CQI), Soil Quality Index and Vegetation Quality Index. This approach proposes to improve the SDI by replacing the initial CQI with a new one based on revised climate aridity data, superior to what was initially used in terms of spatial, temporal and methodological accuracy. Given the fact that land aridity expansion was found to be 70% greater than previously estimated, results showed there are lands with high and very high sensitivity to degradation that total >400,000km2 (~25% of the total area of ~1.7milkm2), ~75% more (~177,000km2) than the initial DISMED data. Nationally, while Spain is the most severely threatened (~240,000km2 of highly/very highly susceptible lands to degradation, 49% of the total country area) there are also major concerns for Greece (~42,000km2, 34%), Bulgaria (~32,000km2, 29%), Italy (~28,000km2, 10%), Romania (~27,000km2, 11%) and Portugal (~24,000km2, 28%). This situation is alarming due to the magnitude of changes resulting from the replacement of even a single dataset – climate data –, which are however the most dynamic and, as a result, the most important to consider for improving the DISMED model. Against the background of the findings prompted by this update based on the original scheme of DISMED method, we call on the EEA to reconsider the current status of lands that are critically threatened by degradation/desertification in Europe, and to provide updated information to policymakers (like European Commission or United Nations Convention to Combat Desertification) in order to prioritize the appropriate policies for combating/mitigating the negative effects of this process.

Desertification Assessment Using MEDALUS Model in Watershed Oued El Maleh, Morocco

Along with being a dynamic process that affects large areas, desertification is also one of the most serious problems in many countries. The effects of this phenomenon threaten the sustainability of natural resources, namely water resources, agricultural production and major basic infrastructure, specifically roads and habitations. Several factors exacerbate this phenomenon such as the climate dryness, the geological and morphological characteristics of the terrain, the irrational use of space, population growth and the over-exploitation of vegetation and water resources. This work aims to evaluate the desertification index in the Oued-El-Maleh watershed, through the integration of key factors involved in the MEDALUS model (Mediterranean Desertification and Land Use) within a GIS. The model includes among its indexes: climate, vegetation, soil and management. Each index was obtained by the combination of sub-indexes. All the factors, measured and integrated into a geographic information system, enabled us to spatialize, on a synthetic map, the degree of the desertification effect throughout the watershed. This map is a managing tool available for decision-making regarding the selection of priority areas in the fight against desertification. High sensitivity to desertification class represents only 35% of the watershed. This class is concentrated in the north of the study area that corresponds to plains and low altitude. This could be explained by the dominance of agro-pastoral activity and the presence of a big population pressure.

An Integrated Desertification Vulnerability Index for Khorasan-Razavi, Iran

In recent decades' desertification as objectively the degradation of the ecosystems in arid, semi-arid, and dry sub-humid areas of the wide range of Iran with area more than 85 percent arid and semi-arid area is derived. The purpose of this study is to present an integrated index for vulnerability assessment of desertification based on imagery data at Khorasan Razavi province. At the first was prepared a land cover map of the province for two periods; 2000 and 2013, which was classified in 6 class involving agricultural, pasture, shrub lands, residential areas, desert, and forest. We applied remotely-sensor indices regarding the enhanced vegetation index (EVI), precipitation, soil salinity (SI), evapotranspiration, soil moisture, and land surface temperature (LST), to create an integrated desertification index (IDI). The degree of desertification vulnerability was considered along 14 years from 2000-2014. The results showed that more than 60 percent area of the province is very high and high vulnerable to desertification. Approximately 22% are resistant ecosystems and about 18% classified in medium vulnerable class. Results indicated that vegetation cover changes are a most effective index for desertification process. Evapotranspiration index shows maximum fluctuations during studied periods. The kappa coefficient was measured about 0.75 which confirm the validity of results.

Monitoring the trends of aeolian desertified lands based on time-series remote sensing data in the Horqin Sandy Land, China

Aeolian desertification is one of the most significant environmental and socio-economic problems, represents a major component of land degradation, and seriously harms the ecological environment, leading to adverse impacts on human society. Monitoring aeolian desertification and identifying the driving factors behind it are crucial for developing prevention and management strategies to combat this issue. The objectives of this study were to monitor the trends of aeolian desertification in Horqin Sandy Land by using time-series MODIS-NDVI remote sensing data for the period of 2000–2013. A dimidiate pixel model was chosen to calculate the Vegetation Coverage Index (VCI), while a unary linear regression analysis was used for a temporal trend analysis of the Aeolian Desertification Index (ADI) and selected climate factors. The Sen's slope estimator and the Mann-Kendall statistical test were used to analyze the spatial trends of the ADI. (1) The temporal trend of ADI showed three stages: reversion during the period of 2000–2005 and 2009–2013, and development during the period of 2005–2009. For the five classes of ADI, the areas of non-aeolian desertified lands (N) showed an increasing trend and the slight (SL), moderate (M), serious (S), and very serious aeolian desertified lands (VS) showed decreasing trends, with the decline in areas of SL and M contributing to the reversion of aeolian desertification. (2) The spatial distribution showed that the VS was mainly distributed in the southwestern portion, and the S was mainly distributed around the VS portion. The SL and M formed a straight line from the southwest to the northeast, bisecting the two areas of S. The N was mainly distributed in the northwestern portion and the eastern edges of the study area. (3) The spatial trends showed that areas of decreasing and significantly decreasing ADI trends occupied 78.44%, while areas with increasing and significantly increasing ADI trends only occupied 21.56% of the study area over the period of 2000–2013, indicating that aeolian desertification in Horqin Sandy Land is decreasing overall and advancing in certain portions. (4) The driving factors of aeolian desertification were analyzed from the perspectives of two groups: climate and anthropogenic factors. We found that the desertification control measures and favorable climate condition have played key roles in the process of desertification reversion; and climate fluctuations, reclamation and livestock pressure have led to the desertification development. The results can provide meaningful information for the prevention and control of aeolian desertification in Horqin Sandy Land.

The dynamic monitoring of aeolian desertification land distribution and its response to climate change in northern China.

Aeolian desertification is poorly understood despite its importance for indicating environment change. Here we exploit Gaofen-1(GF-1) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to develop a quick and efficient method for large scale aeolian desertification dynamic monitoring in northern China. This method, which is based on Normalized Difference Desertification Index (NDDI) calculated by band1 & band2 of MODIS reflectance data (MODIS09A1). Then we analyze spatial-temporal change of aeolian desertification area and detect its possible influencing factors, such as precipitation, temperature, wind speed and population by Convergent Cross Mapping (CCM) model. It suggests that aeolian desertification area with population indicates feedback (bi-directional causality) between the two variables (P < 0.05), but forcing of aeolian desertification area by population is weak. Meanwhile, we find aeolian desertification area is significantly affected by temperature, as expected. However, there is no obvious forcing for the aeolian desertification area and precipitation. Aeolian desertification area with wind speed indicates feedback (bi-directional causality) between the two variables with significant signal (P < 0.01). We infer that aeolian desertification is greatly affected by natural factors compared with anthropogenic factors. For the desertification in China, we are greatly convinced that desertification prevention is better than control.

Quantitative Mapping and Assessment of Environmentally Sensitive Areas to Desertification in Central Iran

AbstractDesertification is one of the main environmental and also social and economic problems facing Iran. Seventeen out of 31 Iranian provinces, which are home to approximately 70% of the total population, are affected by desertification. This study aimed to use geographic information system (GIS) and fuzzy logic for mapping environmentally sensitive areas to desertification based on Mediterranean Desertification and Land Use approach in Isfahan province, central Iran. Six desertification indicators including climate, soil, vegetation, soil erosion, groundwater, and management and policy quality were used to determine various types of environmentally sensitive areas to desertification. Seventeen desertification indices affecting the quality of each indicator were spatially mapped and assigned a value between 0 and 1 using a fuzzy logic option of ArcSDM3 software in GIS environment. Results showed that a 21·7% of the study area was classified as critical, 70% as fragile and 5·5% as potential, and 2·9% of the area was not affected by desertification. In the town of Borkhar, 64·2% of the area was classified as critical, followed by the towns of Isfahan and Nayin with 40·2% and 31·8%, respectively. Results at provincial scale indicated that the climate indicator and humidity index with a weighting mean of 0·71 and 0·77 were the most affective factors in the desertification of the study area. The developed model in this study can be used for mapping desertification status in other 16 provinces that contain desert areas. These assessments provide a GIS‐based desertification database that Iran as a member of the United Nation Convention to Combat Desertification can use to report the condition of desertification at national scale. Copyright © 2013 John Wiley &amp; Sons, Ltd.

A Research on Technogenic Desertification Indices (Case Study: Yazd)

There have been different indices identified for desertification. Among these is technogenic desertification index which seems much more efficient. In this study, some of technogenic desertification indices were studied and evaluated. First land use maps of the region were taken from IRS-PAN satellite image and aerial photos analysis. After evaluating the area of different uses, lands that had productions (like agricultural and horticultural lands) were taken apart. The ration of production per surface unit was also calculated. The region roads map was also derived from satellite image. Finally per capita production, road and mine density and per capita green space indices were used. The per capita production index 9.1, population pressure with 59, road and mine density with 3.6 km/km2 and green space with 18.2 m2 for each person were the other indices calculated. According to the proposed table on these indices, per capita production and per capita green space in the region show very high level of desertification but road and mine density identifies lower level.

Application of Numerical Taxonomy Analysis in Sustainable Development Planning of Combating Desertification

Due to increasing importance of desertification challenges and its consequences the necessity of sustainabledevelopment achievement in arid and semi-arid regions is essential in order to avoid limited sources asting, increase the efficiency of controlling, reclamation and restoration projects of natural areas. Based on the iterature review, it has been recognized that combating desertification projects in Iran were yet inconsequential and incomprehensive. It is essential to achieve sustainable and comprehensive development in combating desertification issue. In relation to the mentioned case, investigation and ranking of current status of development indices of combating desertification process in different areas, is crucial which will determine the level of, budgeting and manpower polices. Therefore, numerical taxonomy model was recognized as a suitable tool for determination of ranking and classification of combating desertification indices. The study model is used for investigating and ranking of existing situation of combating desertification in the urban areas of Yazd province during the period of 2002-2007. The model evaluatesdevelopment and extension of combating desertification indices in the urban areas using analytical structure and the final results are shown as the assessment Maps. The results show that Yazd, Taft, Mehriz and Khatam urban areas with expansion score of 0.89 from total combating desertification indices have unsuitable situation while Bafgh, Sadough and Tabas with expansion score of 0.44, 0.45 and 0.49, respectively had better situation. Moreover, it is recognized that budgeting and future development planning of the urban areas from combating desertification on the basis of the obtained results and raking of this research.

Spatial assessment of desertification in north Sinai using modified MEDLAUS model

This study aims to use spatial analyses and a geographic information system (GIS) to assess the environmental sensitivity for desertification in the north Sinai Peninsula, Egypt. Based on the Mediterranean Desertification and Land Use (MEDALUS) approach and the characteristics of the study area, a regional model was developed using GIS. Five main indicators of desertification including soil, climate, erosion, plant cover, and management were considered for estimating the environmental sensitivity to desertification. A spatial analyst extension Arc-GIS 10 software was used for matching the thematic layers and assessing the desertification index, of which the map of environmentally sensitive areas of the north Sinai Peninsula is produced. The obtained data reveals that 65 % of north Sinai is characterized by very severe sensitivity to desertification while the low sensitive one exhibits only 1.2 %. The moderately sensitive area occupies approximately 23 % of the study area. ETM+ and SPOT images are recommended to monitor sensitivity. The MEDALUS model was developed under the Egyptians to assess desertification sensitivity.

Application of remote sensing and GIS in the study of environmental sensitivity to desertification: a case study in Basrah Province, southern part of Iraq

This research utilizes the integrated remote sensing and geographic information systems (GIS) in the southern part of Iraq (Basrah Province was taken as a case) to assess the environmentally sensitivity area to desertification. The thematic layers of soil, vegetation, climate, and extent of sand movement are the main data required for estimating the desertification sensitivity index. These layers were extracted and manipulated from the available topographic map data, geologic map, satellite image (TM in 1990 and ETM+ in 2003), and field survey data analyses. Spatial analyst function in ArcGIS 9.3 software was used for matching the thematic layers and assessing the desertification index. The obtained data on change detection reveal that the area of active sand movement has increased from 4,118.3 to 4,558.1 km2, and the highly sensitive areas for sandy desertification are located in the western–southern parts of Basrah Province, representing 61.9% of the area belonging to class 5. The rest of the southern parts of the study location exhibit moderately sensitive areas for desertification, representing 18.9% of the total area belonging to class 4. The northern parts of the study location are characterized by a very low and low sensitivity for desertification, representing 8.5% and 10.7% of the total area, respectively. It is recommended that there is a need to establish a professional arid environment center, which can be coordinated with government sectors and different universities in southern part of Iraq to solve various environmental problems.

A multi-component GIS framework for desertification risk assessment by an integrated index

This study describes a GIS-based software tool for the qualitative assessment of desertification risk. The tool integrates results from several land degradation models into ArcGIS using the object-oriented programming language Visual Basic. The integration of GIS and models is based on different coupling approaches. The proposed methodology was developed and tested on Sardinia Island (Italy). Six driving factors of desertification (overgrazing, vegetation productivity, soil fertility, water erosion, wind erosion and seawater intrusion) were model-simulated over two time periods to investigate the spatio-temporal evolution pattern of desertification-prone areas. Model results were normalized, weighted and combined into an Integrated Desertification Index (IDI) ranging from 0 to 1 (representing the best and the worst conditions, respectively), and classified into five desertification risk levels. The implementation, performance of the methodology and benefits provided by the modelling approach to land management authorities for monitoring processes of land degradation are fully described in the paper.

THE REMOTE SENSING SYNTHETIC INDEX MODEL FOR DESERTIFICATION DETECTION

Based on experiments and theoretical reasoning, the authors have analyzed quantitatively the relationship between the desertification and vegetation index (NDVI) and the land surface temperature (LST). The combined information contained in the LST-NDVI space is extracted to form a new index, namely difference index of desertification (DDI), which is then used to identify the severity of desertification. With this index, we can easily get to know biophysical properties of the land surface.

Agro-ecological field vulnerability evaluation and climate change impacts in Souma area (Iran), using MicroLEIS DSS

Soil erosion and contamination are two main desertification indices or land degradation agents in agricultural areas. Global climate change consequence is a priority to predict global environmental change impacts on these degradation risks. This agro-ecological approach can be especially useful when formulating soil specific agricultural practices based on the spatial variability of soils and related resources to reverse environmental degradation. Raizal and Pantanal models within the new MicroLEIS framework, the Ero&Con package, are database/expert system evaluation approach for assessing limitations to land use, or vulnerability of the land to specified agricultural degradation risks. This study was performed in Souma area with approximately 4100 ha extension in the North-West of Iran (west Azarbaijan). Based on 35 sampling soils, Typic Xerofluvents, Typic Calcixerepts, Fluventic Haploxerepts and Fluventic Endaquepts were classified as main subgroups. Climatological data, referred to temperature and precipitation of more than 36 consecutive years were collected from Urmieh station reports and stored in monthly Climate Database CDBm, as a major component of MicroLEIS DSS (CDBm) program. Climate data for a hypothetical future scenario were collected from the Intergovernmental Panel on Climate Change (IPCC) reports for the 2080s period. The evaluation approach predicts that attainable water erosion vulnerability classes were none (V1) very low (V2) and moderately low (V4) in the total of 72%, 13% and 15% of the Souma area, respectively and they will not affected by climate change. On contrary, attainable wind erosion vulnerability classes will increase. Also, phosphorous and heavy metal contamination vulnerability risks will not differ in two compared scenarios while nitrogen and pesticides vulnerability classes will be improved.

THE ROLE OF LAND USE CHANGES ON DESERTIFICATION IN IMAM KHOMEINI AIRPORT REGION-IRAN FROM 1956 TO 2003

The kind of land use and intensity of its change is considered as important desertification indices in different models. Land use change is one of the main anthropogenic factors in the desertification. The current research was carried out around Imam Khomeini airport, with an area of 32000 km2, in order to evaluate mentioned area's land use changes effects during 1955-2003 on desertification. To study the changes, aerial photos of 1955 (1:55000) and 2003 (1:40000), in addition to IRS (Pan and LISS III) and ETM images of 2003 were used. Boundaries of different land uses were determined based on aerial photos and satellite images. In the next stage, boundaries were controlled in the field. Five kinds of land uses including agricultural land, abandoned agricultural lands, rangelands, industrial regions and complex, were distinguished in the study area. The extent of land uses areas, except to complex, has been changed during the 48 years. Rangeland has least change (1.5%), while 14% of agricultural areas have been changed into abandoned and industrial areas. This research showed that biomass has been decreased to 24355.6 ton during the last 48 years. This leads to the decrease of organic matter and decline of soil quality, which in turn causes a 32.9% increase of area regions with severe and very severe desertification intensities.