Journal of Spatial Analysis

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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.

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Deforestation or vegetation degradation is one of the main drivers of global earth changes, which has significant consequences in terms of ecosystem performance and biodiversity conservation. One of the ways for studying vegetation changes as the most important indicator of land degradation is remote sensing. In this study, in order to monitor the vegetation degradation trend in Ilam Province.After obtaining and preparing the required data (410 downloaded images) in the ArcGIS and Surfer software, the multiplication, mosaic and georeferencing operations are made. Converting format of images into ASCII is the next stage of the study. By converting this format, the total number of 953552 pixels is studied within the range; after removing the lost and negative values, 328042 pixels are analyzed. Besides, using parametric statistical method of the classical linear regression and programming in R software, the trend of slope variations and significance of slope variations of vegetations are obtained for the 17-year period (2000-2016). Results of this study show that the focus of the highest trend of declining slope variations (trend of negative slop variations) is in the NDVI index across the western half of the studied area and the focus of the highest trend of increasing slope variations (trend of positive slop variations) is in the NDVI index in the center and east. Significance of the trend of slope variations also approves this claim. Thus, the focus of the highest trend of slope variations (negative) in the west and southwest of the studied area along with the highest trend of slope variations (positive) in the center and east is significant at the probable level of 0.05
 

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The effect of climatic parameters on vegetation distribution in central Iran
Introduction
Climate or climate reflects the daily weather conditions in a particular place for a long time. Most climatic elements are closely related to ecological factors, which is why the analysis of the relationship between climate and plant distribution patterns has been discussed in scientific and research circles for many years. And in recent years, scientists have been using a combination of climatic characteristics with other environmental factors to describe vegetation around the world. Climate change and atmosphere condition will change the content and composition of many plant communities.

The Study Area
The geographic coordinates of the studied area are between latitudes 29°32’ to 33°59’ and 51°27’ to 55°5’. The position of the selected provinces of central Iran compared to the neighboring provinces are shown in Figure 1 The annual data of 8 stations have been analyzed during the stations period determined by the National Meteorological Organization. The stations characteristics including latitude, longitude, elevation and specific statistical period are shown in Table 3.

Data and research methods
In this study, the role of temperature changes and relative humidity on vegetation in Central Iran has been investigated using statistical models of analysis of the main components and hierarchical clustering. This research is applied and its method is slightly analytical. In order to investigate the climatic fluctuations of the center of Iran with respect to urban green space, statistical data related to average temperature and relative humidity during the 32-year period (1986 to 2018) selected central stations of Iran to come and statistical deficiencies such as Data loss was performed by reconstructing differential equations using SPSS software. The criterion for selecting stations is the availability of long-term statistics. Using statistical methods and Geographic Information System (GIS), vegetation classification was performed for Central Iran. ArcGIS, Minitab, SPSS and EXCEL software are used in this research. After identifying the stations, climatic variables including temperature and relative humidity were selected from the data of 8 meteorological stations and were analyzed using the techniques mentioned above. Then, using statistical regression analysis, the impact (topography, average temperature and average relative humidity) on how to distribute and distribute vegetation was investigated. Kendall-man non parametric test was used to investigate changes in the vegetation index trend.

Results and discussion
Analysis of temporal changes in climatic parameters and NDVI index
The results show that the distribution of relative humidity in Abadeh and Kerman stations has decreased by 3% and the temperature distribution in these stations has increased by more than one percent. Relative humidity changes in Kashan and Sirjan stations have a weak decreasing trend, while the relative humidity distribution in Isfahan station has decreased by about 2%.The temperature distribution of Shiraz and Yazd stations increased by 3%, Abadeh station increased by 2% and also Isfahan and Kerman stations increased by 1%. The distribution of vegetation in Yazd and Khor Biyabank stations has decreased by one percent, while the growth of vegetation in Isfahan, Abadeh and Sirjan stations is increasing by less than one percent.

Distribution of NDVI vegetation index in Central Iran using cluster analysis
The stations are located in three distinct areas in terms of distribution of vegetation, each group having the same climatic characteristics in the distribution of similar vegetation. Based on this, three climatic zones in the study area can be identified.

Conclusion
The aim of this study was to investigate the effect of climatic parameters (average temperature and relative humidity) on the distribution of vegetation in Central Iran using comparison of statistical models; by examining the distribution and density of vegetation, eight factors were identified. Among the factors, the first and second factors, with 81.57% of the total vegetation variance, have played the most important role in determining the climatic diversity of Central Iran. In total, these eight factors have justified about 100% of the vegetation behavior in the area Also, according to the analysis of images of Modis satellite measuring satellites from the vegetation situation in the last 5 years, Central Iran, the value of NDVI index in Central Iran varies between 0.2 to 0.64, the northwestern parts of Fars province have the highest vegetation density and The central parts of Isfahan, especially Yazd, lack vegetation. Based on the results, altitude has a direct and significant relationship with temperature distribution in plants, especially in the study area. However, the height of Iran's central regions has affected the distribution of vegetation.

Keywords:  climatic parameters, vegetation distribution, central Iran

 

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Changes in ground surface temperature in the city of Halle and its relationship with changes in the NDVI index
abstract
The temperature of the urban environment is one of the parameters that citizens are in contact with at any moment. Studies show that the global temperature is constantly increasing due to environmental changes. One of these parameters that affect the increase in temperature; The physical growth of the city and its consequent destruction and loss of vegetation. In this study, using Landsat satellite images for the years 2001, 2011 and 2021; and the implementation of the single-channel algorithm, the surface temperature of the ground in the Iraqi city of Halla was calculated and its changes were investigated and analyzed. On the other hand, the NDVI index was calculated as a vegetation index on the mentioned dates and its changes were analyzed with the temperature changes of the earth's surface. The general results of this research showed that the area of the city of Halle has doubled during the study period, and this has caused a decrease in the amount of vegetation and an increase in the temperature of the earth's surface. In the end, the correlation between the surface temperature and the NDVI index was calculated, which was equal to 46.92, 44.35 and 52.98% for the years 2001, 2011 and 2021, respectively. This issue shows the strong relationship between these two parameters and the effect of the reduction of vegetation on the increase in the temperature of the earth's surface.

Key words: Earth surface temperature, vegetation, NDVI, city growth, Halle city
 

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 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.