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Showing 5 results for Desertification

Ali Ahmadabadi, Abdolah Seif, Somaye Khosravi, Amanalah Fathnia,
Volume 2, Issue 2 (7-2015)
Abstract

Land degradation in arid, semi-arid and sub-humid areas, leads to  desertification and land degradation is a concept that refers to any reduction of soil potentials. In Iran, that 85 percent of its area is classified in arid and semi-arid climates, and  one percent per annum growth rate of desertification and its increasing trends, finding ways to evaluate this phenomenon and its causes in the form of models seems essential. In Iran, especially southern areas due to their arid climatic conditions, are considered to be areas prone to desertification. This study aims to evaluate and analyze the vulnerability of desertification in the Mond watershed located in the northern coast of the Persian Gulf.

     In order to evaluate the potentials of desertification in the Mond watershed, geological, the erosion (water erosion potential), rainfall, slope, elevation levels and land use maps are used.  To identify vegetation cover conditions Landsat ETM + sensor data and normalized vegetation index (NDVI) are used.

     Where in reflected in the near-infrared band (Band 4, Landsat ETM+) and the reflection in the visible band (band 3 sensor ETM+) respectively. Overlaps and combines the above criteria is done using E-VIKOR (VIKOR developed) a method of multi-criteria decision-making models (MCDM). This method is based on a compromise plan proposed in the compromise solution is justified determines solutions that are as close to the ideal solution and has been created through special credit decision-makers. VIKOR use linear approach normal. The normal value in VIKOR  is not related method unit of measure. Also standardization effective indicators of desertification has been done using a linear scale.

      In this study, the ANP method (Analytical Network Process) was used for weighting criteria. Analysis method Network, is one of the popular methods of multi-criteria decision problems. This method complex relationship between and among the elements of the decision by replacing hierarchical network structure considers. Table 1 shows the weights of the effective criteria in desertification. In this study 7 criteria are used that results show criteria’s of climate and vegetation, have the most effective measures in the area of desertification and erosion (water and wind) have the least amount of importance in the region.

Table 1: weight criteria of effectivein desertification

criteria

vegetation

erosion

Precipitation

Landuse

Geology

Slope

Elevation levels

weight(W)

0.21

0.18

0.15

0.14

0.13

0.11

0.08

    After mapping the effective indicators in evaluating desertification separately, Standardization of maps, weighting the index, To obtain amount and   , Finally, the amount of , was produced Zoning map of desertification that in it Mond watershed in the province Bushehr in terms of desertification is divided into five ratio and the area is provided in Table 2.

Table 1: Percentage and  area zone of desertification

amount vulnerabilities

Area (ha)

Area (in percent)

Very low

516300

11

low

598900

13

Average

1438025

30

High

2168675

46

Very High

40825

1

    Studies show that more than half of the Mond basin have on the surface with average risk of desertification and In the continuation of the current trend of soil degradation, desertification prone zones and will be reduced all lead to the deterioration of the natural ecosystems and human life quality.


Amir Hossien Halabian, Mahmod Soltanian,
Volume 3, Issue 4 (1-2017)
Abstract

One of the most important calamities that affect the arid and semi- arid regions and is taken into account as threatening factors for human- life and destroying the natural resources is desertification, so recognizing and forecasting this phenomenon is very important. Desertification is a complex phenomenon, which as environmental, socio-economical, and cultural impacts on natural resources. In recent years, the issues of desertification and desert growth have been stated as important debate on global, regional and national levels and extensive activities have been carried out to control and reduce the its consequences. Desertification is considered as the third important global challenge in the 21th century after two challenges of climate change and scarcity of fresh water. At present, desertification as a problem, involves many countries, especially developing countries and includes some processes that caused by natural factors as well as human incorrect activities. In the other word, Desertification is the ecological and biological reduction of land that maybe occur naturally or unnaturally. The desertification process influences the arid and semiarid regions essentially and decrease the lands efficiency with increment speeds. The study area is located in the east and south of Isfahan. This region has been faced to increasing rate of desertification, because of drought, vegetation removal, change of rangelands to dry farming lands, water and wind erosion and lack of proper land management over previous years. Hence, aim of this research is monitor and forecasting of desertification changes in the east and south of Isfahan during the period of (1986-2016). In this research, the Landsat satellite images used as studies base for studying region desertification. Therefore, at first, satellite images of the study area were extracted from United States geological survey(USGS)website during the period of (1986-2016) and data and satellite images of TM5, ETM+ 7 and LDCM8 sensors of Landsat satellite were used which include thermal and spectral bands. In this relation, for studying the desertification condition in the south and east region of Isfahan, the Landsat satellite images of 4, 7 and 8 during 5 periods of 1986, 1994, 2000, 2008 and 2016 have been utilized. After completing the information data base, first, the soil salinity(S1, S2 and S3) and vegetation NDVI indices exerted on the satellite images. According to Fuzzy ARTMAP method, the land use changes during the period of (1986-2016) recognized in the studied region. In the other word, the vegetation NDVI and soil salinity (S1, S2 and S3) indices have been utilized for identifying vegetation and the desert and salty regions. For preparing the region land use map, the Fuzzy ARTMAP supervised classification method have been utilized and 5 land uses(desert and salty lands, vegetation, city, arid and Gavkhouni) in the region were identified by TerrSet software. The changes calculation in region uses during 5 periods accomplished by LCM model. Also, the Markov chain and Cellular automata synthetic model have been utilized for changes forecasting. This research results indicated that the greatest changes during studied period belonged to vegetation. This volume of change had been during 1986- 1994 that indicate 1062 km2 desertification. In the other hand, the greatest intensity of increasing the salty and desert regions have been occurred during 1994-2000 which indicate 495 km2 increasing. The CA- Markov synthetic method have been utilized for forecasting the land uses changes trend, too. In this relation, for assessing the forecast accuracy, the Kappa coefficient have been utilized which indicate 78%. Finally, it has been specified that the greatest changes during 2016-2024 will be in vegetation which about 60% of region vegetation will disappear and arid lands will be replace them. The salty and desert lands will disappear about 1% of vegetation, 3.3% of arid land and less than 0.01% of city and Gavkhouni. During 2016-2024 about 32% of Gavkhouni lagoon area will disappear and arid lands will be replace them.


Sayedenegar Hasheminasab, Reza Jafari,
Volume 5, Issue 3 (12-2018)
Abstract

Introduction

Trend of increasing natural resource degradation in many parts of the world, is a serious threat to humanity. Desertification is one of the manifestations of the damage that has already suffered as a scourge of many countries, including developing countries are. At present, remote sensing is one of technologies with timeliness data and accuracy suitable for monitoring land use changes in the areas of natural resources. Desertification monitoring and tracking changes, which seeks to desertification that the change could be for any reason and also collect and analyze data from activities, projects, plans and programs that may desertification range condition assessment and reporting to provide them. The purpose of this study was to evaluate changes in land use on desertification monitoring using remote sensing techniques to the agricultural lands around zayandeh rood in the East region of Isfahan.

materials and methods

In this study, the image sensor of TM to date 1987, 1998, ETM+ to date 2002 and  OLI to date 2014 related to the Landsat 5,7 and 8 to obtain the land use map used and then was performed radiometric and geometric correction.Then was used the color combination, the main component analysis, vegetation index and supervised classification method for detection of complications and the maximum likelihood algorithm as the most appropriate method for supervised classification in classes 9 of land cover. After production the land use map correctness evaluating operations with calculation error matrix and then was performed detection operations for these maps. Finally, for desertification of monitoring, land use years 27 changes around zayandeh rood  using the comparison method  is paid changes to identify and was obtained the area of each use.

Results and discussion

For investigate the the process of desertification, land use changes in the period of 27 years. In order to select the appropriate bands in supplying the best color composite satellite images and operations classified in order to reconstruct the images, index optimization factor was applied. The results of accuracy assessment shows that For all the images above the 80% overall accuracy and Kappa statistics indicate that almost 80 percent. Generally good agreement between the classification and classes of users on the ground there. By comparing bit images specified land use changes in the period of 27 years, riverbank has the greatest changes during this period. So during these 27 years the river high Zayandehrood degradation, which could be due to the expansion of agricultural activities in rivers. This degradation is generally represents gradual drying of the river and go surrounding cultivated by farmers. This degradation process in the margins of the river and the gradual drying of the river towards the desertification situation in the region shows.

Conclusion

In year 27 time period, Zayandeh Rood neighboring rivers has changed dramatically, so 86.43% of neighboring rivers was destroyed due to the expansion of agricultural activities vicinity of the river and drying river. Another significant changes, loss of agricultural land is notable such that 64% of this land has been reduced compared to 1987. Of reasons for the loss of agricultural land will be noted the region drought and Zayandeh Rood river drying up and Low rainfall, land use change and the proximity of the region desert. Also, has become about hectares 324.99 Of salt marsh lands to agricultural land. Moreover, the developed urban areas to its development contributed agricultural land and rangeland. Bayer lands around Zayandeh Rood Increase and also in region of rangeland lands Low and has increased Bayer lands  and somewhat until agricultural land which inappropriate use of this land shows in order to the agricultural. That this is the desertification progress in the region. Generally desertification process in this period years 27 has been a growing trend.Therefore multi-temporal and multi-spectral satellite data for enhancement, especially for desertification monitoring was large capability and classification after comparison method is helpful for determine the type and direction of changes occurred. Since the development of desertification, limited to a small area and is not recommended range is therefore more effective, in addition to work sheets, other sheets around the area also evaluate the process of desertification is to allow for planning and management in the field of combating desertification exist.


Miss Soraya Yaghobi, Mr Kamran Karimi, Dr Marzaban Faramarzi,
Volume 7, Issue 2 (8-2020)
Abstract

The study and Comparison of desertification process on the basis of climate Criterion (Case Study: Abbas and Dehloran Plains, Ilam)
Soraya Yaghoobi, Kamran Karimi, Marzban Faramarzi
Abstract:
Nowdays desertification is a disaster in many countries , especially in developing countries. This problem includes natural factors and improper human activities. According to the expansion of desertification, providing the appropriate management methods will be reduced desertification intensity and its expansions. In this way, knowledge of processes of desertification and factors causing and  the intensifier it and also awareness of intensity and Weakness the processes and factors that are important and necessary   that should review and evaluate. Recognition criteria and indicators for provide a model to show the process of desertification and for determine one of the  best reason effective factors for prevent the spread of desertification factors is necessary. To knowledge and Trend of desertification and separation of  vulnerable  areas versus degradation factors .we should indentifi and evaluat  criteria and indicators affecte  at desertification. Therefore in this study of  the Iranian model IMDPA to assess trends and Comparison of desertification in recent years has used.
The studied area of  Dehloran plain is located in southeast of Ilam province (47 02′ 16″ to 47 25′ 07″ E and 32 48′ 33″ to 32 18′ 48″N) with an area of 54252  hectares, With precipitation  average 251.6 mm and Abbas plain is located in south of Ilam province(47 37′ 55″ to 47◦  50′ 57″ E and  3217′ 77″ to 3229′ 25″N) with an area of 34104 hectares With precipitation  average 227.1mm. In this study, in dehloran plain of six stations in this Inside and outside the area also in Abbas plain of five  stations outside the area  used to measure the amount of rainfall in different seasons of year. In this study, to assessment  and Comparison of desertification in two study area of the Iranian model IMDPA used. In this study, of climate criteria, were used. which according to the IMDPA model for this criteria, indexes are considered for evaluation e.t.c: Climate criteria: (1) the amount of annual rainfall 2-drought indexe(SPI) 3. continuing drought In IMDPA model  All measurements  do in this work  units. To this end, first, working unit maps (geomorphologic facies) were created using slope, geology, and land use maps. a map was generated for each index according to assigned weights, such that the qualitative map of the desired criteria were obtained using the geometric mean of indicators.
The results earn  of  evaluation  of desertification  showed that  in the period  2005-2009  weight average of climate criteria is same with 1.50 all of the region are in the classe Middle sub class 1 and class low sub class3 . in the period  2010-2014  Also  weight average of climate criteria is same with 1.88 in classe Middle sub classes 2 and 3.  Also weight average of climate criteria in Abbas plain In the first period is same with 1.92  in the classe Middle sub classe2. Also In the second period with weight average is same 2.3 in classe Middle sub classes 2 and 3. The results showed that SPI index, as the most effective indexes, in plain Abbas In the first and second periods with the weighted average 3.04and 3.2 in the intense class under class 2 and 3. in front in Dehloran plain SPI index in the first and second periods with weighted average of 1.93 and 2.25 in the moderate classe and sub-classes 1, 2 and 3 and intense sub-classe 1.
In this study, to assess and Comparison of desertification Dehloran and Abbas Plains to provide regional model has done. . In this way  of  a criteria, also important and effective indexes belonging to this criteria of desertification used in dehloran and Abbas plains . The obtained results of the analysis criteria and Indexes indicated that in dehloran and Abbas plains in the first period ( 2005-2009) And second period (2010-2014)  between  indexes  the amount of annual rainfall, standard precipitation index (SPI) and drought duration Evaluated on the areas respectively standard precipitation index (SPI),  rainfall and drought duration index the most important factors in exacerbating desertification. Can be concluded that the intensity of desertification in Abbas plain compared to dehloran plain terms of climate is In more adverse conditions. In general, it can be concluded that desertification would intensify in future decades.
Keywords: Desertification, IMDPA, Climate, Abbas Plain, DehloranPlain
 
Mrs Ziba Yousefi, Dr Hossein Jahantigh, Dr Farhad Zolfaghari,
Volume 10, Issue 4 (12-2023)
Abstract

 Investigation and monitoring of desertification in arid and semi-arid regions is a major concern for societies and governments due to its increasing rate. It is essential to identify areas at risk of desertification to manage and control this phenomenon in the shortest possible time and at minimum cost. The objective of this study is to create a map of desertification intensity in the MoradAbad plain of Saravan using the Albedo-NDVI model, which is based on remote sensing. Two Albedo and NDVI indicators were extracted from Landsat 8 satellite images in Erdas Imaging software after necessary corrections. A linear regression was formed between the two indicators by selecting 200 pixels corresponding to each indicator. Based on the slope coefficient of the line obtained from linear regression, the equation for determining the intensity of desertification was obtained. A map of the intensity of desertification was prepared based on Jenks’ natural refractive index. To evaluate the accuracy of the model, a clutter matrix was formed between 100 corresponding points. The results of linear regression between NDVI and Albedo indices showed that these two indices have a high negative correlation with each other (R = -0.85). The results of the desertification severity classification based on this model showed that 35% of the area is in the very severe class and only 5% of the area is without degradation. The model’s accuracy value was obtained with a kappa coefficient equal to 0.58, indicating good accuracy of the model.
 

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