جستجوی مقالات مرتبط با کلیدواژه « شاخص ndvi » در نشریات گروه « جغرافیا »

The role of climate in the study of urban environments is important in terms of its impact on climate change in urban environments. The heat island is one of the hazards that has recently affected the environmental conditions of cities due to urban development.

For this purpose, Landsat ETM satellite images were used during the period 1990-2019. In this regard, LST and NDVI indices, urban coverage and land use were used. Geographical area of research The city of Isfahan has been considered in this study. 

Results and discussion: 

The results showed that the high temperature is mostly in the central core of Isfahan and the surrounding city is covered by the middle temperature class. Most of the low temperature class also includes agricultural use due to high humidity. Parks and green spaces in the city are among the middle temperature classes due to the impact of high and very high temperature areas around them.

In general, it can be said that in the last three periods, the highest area has been related to the average temperature, and this trend will continue in the coming years. Due to the reduction of agricultural land use and the physical expansion of the city, the area of heat islands in the upper range has increased. On the one hand, the reasons for the increase in high temperatures are the increase in population, the increase in industries and the number of cars in the city, the multiplication of traffic volumes, the increase in asphalt levels and urban and interurban roads, and the increase in wasteland due to grazing. He pointed to overcrowding and damage to pastures, as well as clearing of green lands and deforestation.

The risk of wildfire in Iran has increasingly become a serious risk throughout the year and is no longer limited to a few months of the year. Accordingly, forest monitoring for identifying areas prone to fires is an effective step for the development of early warning systems. This research was conducted to see the relationship between the vegetation indices with the occurrence of fire in the vegetation areas of Iran. The MODIS sensor data of the Terra satellite, including the active fire product (MOD14A2) and vegetation indices NDVI and EVI (MOD13A3) were used from 2001 to 2020. The results showed that the maximum occurrence of wildfire in the vegetation areas of Iran occurs from the end of spring to the beginning of autumn. The increasing trend of wildfire occurrence in the warm period of the year is related to the increase in temperature, decrease in humidity, and early melting of snow in the spring season and the autumn season, simultaneously with the fall of vegetation and the late start of autumn precipitation. The maximum average height of wildfire occurrences in the Arsbaran vegetation area is 1791 meters in October and the maximum height of wildfire occurrences in the Irani-Turani area is 1565 meters in August. Spatial distribution of NDVI and EVI indices showed that the density of vegetation is effective in the intensity and spread of wildfire and provides the conditions for the spread of wildfire in such a way that barren areas with low vegetation cover the center, east, and southeast of Iran. Almost no wildfire occurred and the maximum number of active fires was observed in the north, west, and northwest of Iran.

Geomorphological features play an essential role in changing the reactions of a basin and they can have significant effects on the erosion and sedimentation potential of watersheds. Meanwhile, the influence of geomorphological facies is significant in changing the amount of soil erosion, and its effects are manifested in the amount of sediment production. Establishing a relationship between the morphology of waterways and the active processes in them helps to correctly understand and predict their response to natural and human changes. Therefore, it is necessary to identify geomorphological phenomena that can influence the structure of waterways. Today, with the use of computers and the existence of capable remote sensing software and geographic information systems, the necessary calculations can be performed with high speed and accuracy. The purpose of this research is to compare the waterway network extracted from digital models of different heights.

Using the algorithms available in the software, a flow direction grid was created and a cumulative flow grid layer was extracted from it. For each cell, the current accumulation layer determines and ranks the number of cells that direct their current to the mentioned cell according to which the cells with the highest numerical values ​​correspond to the concave lines and the cells with values ​​close to zero and zero correspond to the ridge lines. To extract the waterway network from the studied area, DEMs 10, 30, and obtained DEM were used by ARCHYDRO software, which finally produced three maps. The waterway network was extracted from the three mentioned DEMs. In this study, the drainage network map, extracted from the digital topographic maps provided by the country's mapping organization, was used as a measure close to the ground reality. Based on the constructed waterways, the border of the main closed rivers and the area and perimeter of the main basin were obtained.

According to the results of the total length of the waterways, it can be seen that the cell size of 10 meters has the largest value so that the model calculates the length of the waterways more accurately. According to the drainage density values, it is observed that the amount of drainage density decreases with the increase in cell size. This problem indicates that with the increase in the cell size, the lower ranking waterways are removed, and considering that the drainage density is obtained from formula (1) and in this formula, the number of waterways and their lengths have great effects on the drainage density, so it can be seen that as the cell size of the height digital model increases, the drainage density decreases. The drainage density obtained using a cell size of 10 meters is the closest value to reality. Using DEM10 and Arc hydro software, the waterway network map was extracted and compared with the reference map (waterway network map of the Mapping Organization) of the country.

According to the obtained results, by increasing the cell size of the digital elevation model, small details are not considered and the accuracy of the model decreases; as the pixel size increases, the sub-channels are removed, which affects the output parameters. This model reduces the length of waterways and the density of drainage, which is consistent with the results of Davari and Hack's research. As the cell size increases, the length of the main waterway decreases which confirms the results obtained by Ashurlo et al. (2008). However, the drainage density obtained using a cell size of 10 meters is the closest value to reality. Govan et al. (2001) and Hosseinzadeh and Nadaf Sangani (2013) also achieved similar results in their research. The results showed that with the increase in the cell size, the calculation of the length of the waterways is associated with error to the extent that with the increase of the cell size by more than 10 meters, the error rate becomes more significant and far from the actual amount. The parameters obtained from digital height models with a cell size of 10 meters in the Arc hydro model had the closest results to the real standard. Based on this, Zhang and Montgomery (1994) and Yang et al. (2010) considered 10 meters as an appropriate index in their research. According to the mentioned cases, the correctness of this theorem can also be visually verified in the waterway network maps obtained from the digital models of 10 and 30 meters height, as well as the waterway network obtained from the topographic map 1: 50,000 regions compared to control waterway network map (the waterway network of the country's mapping organization). It was also observed that the smaller the cell size, the more accurate waterway network of the region can be obtained. The results of satellite image processing show that among the three indices of NDVI, NIR and LWC, the NIR index shows a more accurate waterway network pattern. This index showed that 90% of waterways created by this index are consistent with waterway network. Also, in the surveys that were conducted in the plains and mountains separately, it was shown that 94% of the created waterways in the plains and 91% in the mountainous areas are the same as the control waterways, which confirms the high ability of this index to detect waterways in plain areas and to prevent the occurrence of errors in the identification of waterways.

Drought is a mysterious phenomenon whose effects, unlike earthquakes and floods, are not sudden and cover wide areas. Understanding this phenomenon can increase the resilience of human societies and reduce its consequences. Otherwise, drought leads to imbalance and anomaly in social and ecological systems. In this research, Fars province (9 selected stations) has been selected to investigate the drought during a statistical period of 28 years (1994-2021), and the SPI and PNPI indices and the NDVI index have been used to verify the validity of these indices and the consequences of drought. The results showed that climatic droughts continued during this period with the difference that the index (SPI) shows the severity of drought better and emphasizes minimum ranges, and the PNPI index displays the maximum ranges while providing a better classification of drought severity. According to the results, the severity of droughts is inclined from the south to the northern parts of the region. The results of the vegetation cover index showed that there are many changes in the density and extent of vegetation cover during the period of about 30 years, which confirms the evaluation of the drought indicators in this research.

Vegetation plays an essential role in regional and global ecosystem stability. The change in terrestrial net carbon uptake is principally affected by varying vegetation productivity and the Earth’s climate is regulated by vegetation through evapotranspiration, surface albedo, and roughness. The purpose research is monitoring the trend of vegetation changes (NDVI) in Najaf abad County using Time Series Images and Mann-Kendall test (2003-2019). In this study, 16-day data of normalized vegetation difference index (NDVI) of MODIS Aqua in time interval 2003- 2019 temporal resolution of 500 meters have been used. Mann-Kendall test used for assessing trend of the index in Najafabad County. The results showed that in the first period (2003- 2013) the amount trend of vegetation is moderate and increasing. The peak of amount increase in vegetation 2005-2007. From 2013- 2016 year the increasing- decline trend shows itself in the same way, until from 2016- 2019 year, decline intense trend witness and once in amount of vegetation in this area, once land use changes and climate fluctuations and drought can be considered one of the main reasons the declining trend vegetation in Najafabad County. The greatest trend of declining vegetation in the southern and southeastern as occurred in urban areas, this trend can indicate high urban growth and land use change from vegetation to construction in this county. Aa well as, irrigated cultivation in the county has during the study period intense decline faced, this issue leads to change land use from irrigated cultivation to other uses in the area.

The release of isoprene from plants is the largest known source of non-methane volatile organic compounds in the world, indicating a direct transfer of carbon and a reaction of plants to the atmosphere. It is estimated that more than 90% of isoprene emissions from plants occur during peak hours of photosynthesis (11 to 20). Given that isoprene is an ozone precursor and its direct effect on ozone release is further determined in the biosphere; the main purpose of this study is to identify the generating areas of this pre-pollutant in vegetated areas by monitoring tropospheric ozone data. Ozone data were prepared from air pollution measuring stations and monitoring stations of the Environment Organization from 2002 to 2018, and after producing the NDVI map of Tehran, an analysis based on the correlation method between variables was performed. The results showed that from 11 to 20 o'clock in areas where the vegetation index is higher within a radius of one kilometer of each station, the amount of emitted ozone is higher and there is a significant relationship between the two, indicating the production of isoprene by the dominant tree and shrub species. در is in such areas. Isoprene is mainly produced from fast-growing trees such as spruce, willow, eucalyptus, acacia, sycamore, etc., which can increase ozone pollution in the earth's surface; Therefore, before developing a new green space, the municipalities of different areas of Tehran metropolis are recommended to accurately identify the species suitable for the urban environment and the effect of their pollution in a completely scientific manner and, if necessary, plant such trees in some areas. Assume that they are not exposed to isoprene production catalyst conditions.

In some metropolises of Iran, Thermal Islands is somewhat generalization and observable. Existence of tall buildings, traffic, population density in the hub centers and especially in the central part of the city cause the creation of a Thermal island in the city. In this research, the time-spatial identification of the thermal islands of the cold season during the years 1985 to 2019 and the analysis of the factors influencing their formation were done with an emphasis on changes in land use, texture, high-rise construction, land cover and climatic variables in the Tehran city. The current research, which is based on the extraction of Landsat satellite images, produced maps of the mentioned indices using NDVI, LSE, ISA and LST indices, which became the basis of the analyses. The results of the research show that high LST values are spread in areas of Tehran where the NDVI index is relatively low and the ISA index is high. Although the formation of Thermal islands in winter is a little far from expected, small parts of the north, northwest, south and southwest of the city (zones 1, 5 and 18) are permanently exposed to Thermal islands, which are in step with dense land use and areas free of vegetation. The scattered hot spots in the mentioned areas with a temperature cover above 20 degrees Celsius in the middle of the average temperature of the city, which is lower than 17 degrees Celsius during the cold period of the year, is indicative of this fact.

Introduction :

Jazmourian basin in southeastern Iran includes parts of Kerman and Sistan, and Baluchestan provinces. This region is one of the sources of dust production in southeastern Iran. The maximum dust emissions in the Sistan region occur in eastern Iran, southwestern Afghanistan, and Pakistan in the summer, and these storms load dust from local scales to regions. Vegetation and its type also play an important role in the severity of dust. There is positive feedback between precipitation and dust emission from the surface; This means that the dust from desert areas reduces rainfall and decreases rainfall, causes the soil to dry out, and further increases dust. In addition to the effect on rainfall, the presence of dust is also effective in its spatial distribution.

 In this study, first, using the optical depth data of the MISR sensors of Terra satellite with a horizontal separation of 0.5 degrees, the monthly and seasonal average optical depth of the aerators in the Jazmourian basin is determined. In order to study the trend of AOD change, the average AOD regions of TODRA satellite MODIS sensor are shown annually in the period 2000 to 2020, and the regression line slope was calculated by age estimation method and Mann-Kendall method with 95% and 99% confidence levels. The amount of vegetation changes in the region has been studied using the annual average of the NDVI index in the Jazmourian region. Since precipitation is one of the factors affecting the occurrence of dust events, the average annual precipitation rates of the TRMM satellite have also been studied. Finally, to investigate the effect of vegetation change on dust, the correlation between the average annual data of AOD and NDVI data and the correlation between the average annual rainfall data and NDVI was calculated to investigate the effect of annual rainfall on vegetation.

Results :

 The monthly average values of the optical depth of air vents were in the period 2000 to 2020. In January, AOD values in the center of the Jazmourian Basin, located on the border of Sistan and Baluchestan and Kerman provinces, are slightly higher than in other parts. From February to July, an increase in AOD is observed in the region so that in large parts of the Jazmourian Basin, the average optical depth of air vents in this month has reached about 0.6. Since August, AOD values have gradually decreased until December; only in the central areas of the basin, small amounts of AOD are observed. As expected, the maximum AOD in this region is observed in summer, and then in spring is in second place. The amount of AOD has decreased significantly in autumn and winter. According to the results, NDVI values were low in years when the mean optical depth of the particles was high. For example, in 2008 and 2012, when AOD values were higher than in other years, the average annual NDVI values decreased. Interestingly, the average annual values of optical particle depth in 2020 and 2017 were lower than in other years, but in the same years, the average annual NDVI values are higher than in neighboring years. The results show that in the years when there is an increase in rainfall in the region, an increase in vegetation and a relative decrease in AOD compared to previous years are also observed. It should be noted that in some years, with increasing rainfall and vegetation, the amount of AOD has not decreased much that it can be said that the amount of AOD, in addition to the activity of local dust sources, is due to dust particles from other areas to the study area and AOD changes only Not due to changes in rainfall and vegetation in the area.

The average monthly light depth values of air vents in the period from 2000 to 2020 show that in January, the AOD values in the center of Jazmourian Basin, located on the border of Sistan and Baluchestan and Kerman provinces, are slightly higher than other sectors. From February to July, an increase in AOD is observed in the region so that in large parts of the Jazmourian Basin, the average optical depth of air vents in this month has reached about 0.6. From August, when small amounts of AOD were observed only in the central areas of the basin, AOD values gradually decreased until December. Also, the average monthly AOD values in the region in the period 2000 to 2020 show that the highest AOD values in July are related to 2003 and 2001, and in June are related to 2008, which is significantly different from other years. Examination of the seasonal average values of the optical depth of air vents in the period under study shows that the maximum amount of AOD in this region is observed in summer and then spring, and AOD values in the autumn and winter seasons have decreased significantly.

Awareness of the status of vegetation, land use change and surface temperature in each region, and the timing and location of their changes over time are important for micro and macro planning. In order to make optimal use of land, knowledge of land use changes is necessary, which is usually possible by detecting and predicting land use changes. Measuring the role of researches and researchers has been instrumental in the study of natural resources, especially vegetation, surface temperature and user variations in each location, as well as the availability of information for different times for valuable studies. In this study, ETM and OLI were used to study the process of land use change, vegetation cover, surface temperature, and hazards caused by them in perennial seasons. The results show that the area of use changes over the period 2000-2010 has decreased the area of use of the developed area, agricultural and growing gardens and the area of land and rangelands. Artificial vegetation has risen in aggregate and rangeland lands are showing a decreasing trend. Due to the importance of vegetation and its role in reducing the temperature of the earthchr('39')s surface, the trend has been decreasing in regions with intensive vegetation and high temperature. Also, in the period from 2010 to 2017, the range was further increased and the citychr('39')s growth continued sporadically, causing environmental changes and rising temperatures in the city. The change in the citychr('39')s increased range has increased environmental risks, including the loss of good agricultural land and the increase in the temperature of the city. Due to the fact that most agricultural land is located in the vicinity of the city under cultivation of saffron, which in the warm seasons does not have surface coatings, changes in the type of cultivation can also affect the temperature of the earth.

Drought is one of climate hazards that over time brings a lot of damage on human life and natural ecosystems. Commonly Droughts are divided to four main groups of meteorological, hydrologic, agricultural and socio-economic .All Types of droughts are different from each other significantly. In another sense, the occurrence of an event of drought would be the cause of another draught. Various methods have been used for the analysis and assessment of drought and its impacts on human activities and natural resources. Statistics, Synoptic, Remotely sensed methods, and several types of models such spatial, dynamic and statistics models can be seen in the most studies related to drought. The zoning of drought using spatial-statistics indices and generally the spatial zoning and regional distribution of dry periods is one of important features that makes a better understanding towards the phenomenon of drought and a closer consideration of the effects of it. In the past four decades remote sensing widely provide drought monitoring tools, and many drought monitoring model is presented, which is generally based on vegetation and thermal indices especially Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), moisture and reflection at the visible and infrared areas. Golestan province is located in the North East of Iran in the neighborhood of the Caspian Sea and the northern slopes of the Alborz Mountains, Which following local conditions of the Caspian coast line and high peaks, with increasing altitude, vegetation diversity there are certain bands. From the peaks over 1500 meters to foothills is covered with dense forest broadleaf. Field craps are the dominant vegetation’s From Foothills to the plain. From North Gorganrood to border of Turkmenistan due to rare moisture Resources vegetation is thinner than the southern and central provinces. The research in terms of nature and methods in theoretical basis is parts of the descriptive researches and due to relationship and impact is an applied one. In the present study for following meteorological drought and ecological in Golestan province, two types of data were used. 72 pluviometry stations on monthly rainfall data (period 1971-2010) and remote sensing data in the three periods (July, 1975, 1987 and 2000), derived from Landsat satellite images. Standard Precipitation Index (SPI) is used to identify and to zoning meteorological drought and the Normalized Difference Vegetation Index (NDVI) is used for the detection of the plant tension that were affected by drought. In the following the results of two parameters and their relationships were compared to each other.  Examining maps of drought frequency and severity of droughts indicates that most of frequency droughts of stations occurred in the North and North-East Province. And gradually the intensity and frequency of droughts reduced to the South and South West. The most severe drought that can be seen in parts of the North East belongs to the Hutan station. However the lowest number has occurred in the central and western regions of Golestan province. According to table (3) correlation between both NDVI and SPI are positive in three years. In all the years of study SPI index-correlation with NDVI was fairly good together. Overall the parts of Northern Province and East Sea have most drough in the selected three years. While most of the wet years are related to the southern part of the province (northern slopes of the Alborz mountain range).  According to conducted research either in the country or abroad, it seems that the use of SPI index as representative of meteorological drought and NDVI index as representative of indicators satellite drought are appropriate for monitoring this kind of droughts. According to the study, two SPI drought index and NDVI due to adaptation with each other are proposed for drought monitoring and meteorological satellite in Golestan province.

One of the most important concerns in the world today is the debate over climate change and its consequences. In this study, in order to investigate the level of wheat and barley cultivation in past and future climatic conditions, first rainfall, average temperature, minimum and maximum temperature data in the statistical period (1998-2018) were received from the Meteorological Organization. The Kendall Mann test was used to study the trend of changes in meteorological elements. After that, the cultivation calendar was extracted from Landsat 8 images using the NDVI index and then using Tm, Etm, Oli, and Sentinel-1 sensor images in the Google Earth engine system by calculating the index. Monthly NDVI and SVM classification process Estimated crop area in different years was estimated. Finally, the SDSM model was used to simulate and predict meteorological elements by 2040.

According to the wheat and barley cultivation calendar, the cultivation of these crops in Izeh city starts in January and reaches its peak of greenery and growth in April, and finally from June the crop is harvested from agricultural lands. In Izeh city, there is an almost direct relationship between rainfall and cultivation area. With increasing rainfall, the area under cultivation increases. With increasing temperatures, the amount of cultivation area decreases to some extent. In the future climate conditions, all three scenarios predict an increase in the minimum and maximum temperature by 2040 by 0.7 degrees Celsius. In the rainy conditions of the past climate, in two decades, the area of ​​cultivation will decrease by about 7.4square kilometers, and in the conditions of the future climate, it will decrease by about 11.4 to 15 square رkilometers.That is the cultivated area decreased by 8 square kilometers per decade

Among all Earth’s ecosystems, arid and semi-arid regions (about 30% of the Earth’s land) have experienced significant degradation over the past century due to the intensive land use practices and the increasing effects of droughts and climate changes (Maynard et al., 2016). Remote sensing is capable of detecting several groups of disturbances and changes, and has been widely used as a toolto identify long-term changes. Recent technological advancements in the methodology of mapping and monitoring land cover changesprovide new opportunities for the utilization of satellite imageries with high temporal frequency. Image fusion technique has been applied in different fields of environmental science, such asmapping crop growth, studying daily pollution of water resources, studying patterns of short-time ecological changes, determining regions with short-term erosion risk, etc. Image fusion algorithms include color combinations in three bands ofRGBimages, statistical and multi-scale methods. The present study seeks toevaluate the efficiency of image fusion algorithms and select the best algorithm for mapping vegetation in SouthKhorasan Province.

Following the pre-processing ofLandsat 8 and MODIS images, six image fusion algorithms, including NNDiffuse, HPF, Brovey, Gram-Schmidt, PC and CN, were studied and evaluated usingdifferent statistical criteria. Three statistical indices, including Root MeanSquare Error(RMSE), Mean Absolute Error(MAE) and Mean Error (MEB)were usedto evaluate the aforementioned algorithms.Then, the best image fusion algorithm was used to merge two different images received from Landsat8 (30m) and MODIS (250m). Finally, two vegetation indices, including NDVI and HVCI, were usedto map vegetation in SouthKhorasan Province. 

Results indicate that all six algorithms used in the present research can improvespatial resolution of the merged images. Compared to other 5 algorithms, NNDiffusecan merge thered and NIR bands of Landsat 8 and MODISwith a relatively higher accuracy. Therefore,NDVI extracted from this algorithm has the lowest RMSE and MAE compared to the original Landsat 8images. NDVI obtained from thefusion algorithms used in systematic-random transects of three land uses (including agricultural, urban and pastures) indicate that the index obtained from NNDiffuse algorithm has a better conformitywith the NDVI obtained from the original Landsat 8image. Then,redand NIR bands of Landsat8 and MODIS were combined forsimultaneous mapping of NDVI and HVCI in the case study area. Overall, a great part of SouthKhorasan Province has a vegetation cover of less than 10% and 40-50%, vegetation cover is only limited to small parts of the study area (agricultural land use and gardens). 

Generally, accessing simultaneous satellite images with high spatial resolutions, such as the Landsat series, is considered to be a challenge in vast area. The present study took advantage of different algorithms for image fusion and vegetation mapping in South Khorasan Province. Image fusion techniques, such as integration of Landsat and MODIS images, can be very useful for mapping purposes. Evaluation of 6image fusion techniques indicated thatNNDiffuse algorithm is the most suitable method for mapping vegetation in the study area.

Land surface temperature (LST) is controlled by the equilibrium of ground and atmosphere energy, as well as superficial and sub-surface thermal properties, and is considered as an important parameter in many environmental models. Knowing the extent of LST contributes to a wide range of issues related to earth sciences, such as the urban climate, global environmental changes, and the study of human-environment interactions. Land use and land cover information are recognized as an essential and important component of data used in various aspects of regional planning, research on global change, and applications in the field of environmental monitoring. On a global scale, changes in land use / land cover resulted in changes in regional and local temperature regimes. Land use patterns affect LST and can be considered as an indicator for the trend process. Using LST, everyone can find useful information about the physical and physical characteristics of the earth and climate that play a significant role in environmental processes. LST is an important factor in many fields of study such as global climate change, hydrology, agriculture, and land use / land cover.

The aim of this study was the investigating the relationship between surface temperature and vegetation cover and land use in Gorgan plain using remote sensing data. In the first step, the Landsat 8 image of the year 2018 was pre-processed and prepared and the land use / land cover map was prepared in 8 classes. Then, to measure the surface temperature of the thermal bonding of the image and the related equations were used. Finally, the normalized difference vegetation index or NDVI was used to calculate surface mapping and the LST surface temperature map was created. In order to neutralize the effect of altitude on LST, selected pixels from the elevation points were selected in each land use. All LST computational steps and the NDVI index were performed using the ArcGIS10.4.1 software and the 2018 land use was created using the Idrisi software. In this research, the linear regression method was used to obtain the effect of NDVI and its effects on LST. Evaluation of LST extracted from meteorological stations It should be noted that the surface temperature, which indicates the surface heat of the body, is slightly different from that of the air contained in that body. Using the following equation, the air temperature can be obtained from the values of LST:Equation (1)
 In order to prove the accuracy of the work for the preparation of the surface temperature map, the temperature values measured by the three synoptic stations (Kordb ku-Blok, Gorgan and Nomal-Dam Kowsar) were compared on the same date with the obtained values of air temperature from the surface temperature values.

The results showed that bare land class has a higher temperature (45.96 ° C) due to lack of protective cover. Since the vegetation is very limited and dispersed in the bare land areas, the Earth is more exposed to solar waves. On the other hand, the surface of the bare solid ground is bright, which affects energy absorption and increases surface temperature. While the use of irrigated agriculture and water resources was 29.95 and 34.33 degrees Celsius, the lowest average temperature was observed among other classes. Considering the time taken to get the image of products cultivated in agriculture, they had an acceptable level of growth and greenness (high NDVI index highlighted the greenery of arable crops on this date) and by influencing evaporation reduction and maintaining soil moisture in effective thermal modification Which have led to less solar heat absorption and eventually reduced temperature. Water resources also reduce the surrounding air due to its high heat capacity and low solar energy absorption. Since forest class is at higher altitudes, its surface temperature was studied separately. The comparison of the surface temperature of the pixels related to the use of forest and the forestry sector showed that the LST in the forestry sector was about 5 degrees Celsius above the forest class. According to the results, the correlation between the NDVI index and the surface temperature is 0.65. The negative correlation obtained between this index and the surface temperature indicates an inverse relationship between this index and the surface temperature, and it can be deduced that in areas with high vegetation density such as forest use, surface temperature is much lower than other uses, which suggests a type of relationship Usage with surface temperature. According to Sig, this correlation is significant at 95% confidence level. Evaluation of surface temperature map prepared with ground data The results of the correlation test between the surface temperature of Landsat 8 and the air temperature of the meteorological station as well as the correlation between the air temperature and the existing stations were both obtained at 0.99, which confirmed the accuracy of equation (1) used to convert the LST data to the data Air temperature. The difference in LST between stations in the area indicates that stations are located in different environmental conditions due to environmental factors such as elevation, slope, direction, distance from the sea on LST.

In this study, to determine the relationship between land use and LST, the surface temperature map of the area was prepared and the surface temperature of the area between 14 and 51 degrees Celsius was estimated. Since the height parameter has an effective effect on temperature, the samples were selected from the height points of each land use. Thus, the effect of height factor on the results of the research was neutralized. In areas where vegetation is dense, such as forest, surface temperatures are far lower than other uses. Also, the irrigated agriculture class, which had a higher density than rangelands, showed lower temperatures. On the other hand, the bare lands had the highest surface temperature. Therefore, it can be concluded that vegetation is a major factor in surface temperature, especially in areas where this coating is denser. The effect is more obvious.

Heat island phenomenon occurs when the land surface temperature and the air temperature in urban areas are higher than that of the surrounding areas. This temperature difference is shown as the urban heat islands on thermal maps. Information obtained from the urban heat islands can be a useful source in urban planning applications. The availability of reliable information about the urban heat islands plays an important role in predicting and preventing the occurrence of many heating risks in urban areas. One of the common methods of calculating heat islands intensity in urban areas is the use of two temperature sensors installed in the city and around it. Given the limited temperaturemeasuring stations, there is no accurate estimate of the urban heat islands. With the introduction of Remote Sensing technology into the space arena, and with the help of satellite images processing, a precise map can be produced for the land surface temperature, i.e. a precise estimation of the urban heat islands is obtained by calculating the pixels temperature difference at the urban areas and around them. Therefore, one of the important issues in such studies is to detect the urban and non-urban pixels and to separate them from each other.

The most important reason for the occurrence of the heat island phenomenon is the change in land use from rural to urban, which is well exhibited in the urban cover index maps.In this paper, in order to measurethe intensity of surface urban heat islands, a method based on generating the urban percentage map was proposed by combining the Land Surface Temperature (LST) map, the Normalized Difference Built-up Index (NDBI) map and the Normalized Difference Vegetation Index (NDVI) map.Considering the relationship between the land surface temperature and the land cover type, it can be said that the relationship between the land surface temperature and the urban percentage map follows a linear function which can be fitted to the land surface temperature graph in terms of land cover type. Finally, the Urban Heat Island Intensity (UHII) map was calculatedfrom the slope of the fitted line.In order to evaluate the strengths and weaknesses of the proposed method, a classification-based method was used to separate the urban and non-urban pixels and to calculate the urban heat island intensity. The proposed method was implemented on the Landsat-7 ETM + satellite data in the city of Rasht and on the Landsat-8 OLI / TIR satellite data in the city of Langroud.

The results of the classification-based method indicated a large difference between the maximum and the minimum temperature of the urban areas, which led to a high-temperature changein all land cover typesin the study area. Therefore, the use of the average temperature of each class to calculate the heat island intensity is not a suitable method and the accuracy of the heat islands maps is not high and they cannot be used in applications that require high precision.Although, this problem can be solved by increasing the number of classes, increasing the number of classes requires more training data and a sensor with higher spatial resolution. By contrast, the results indicated that the proposed method (based on the urban percentage map) had a high accuracy for calculating the urban heat island intensity which was similar for both study areas. Also, fitting a linear function to the values of land surface temperature and the urban percentage map led to decreasing the effect of suspicious pixels (noisy pixels) on the overall accuracy of the estimation of the urban heat island intensity. Meanwhile, the results obtained on two datasets indicated that this method did not require any training data or any other background information about the study area and it can be applied for many satellite images having thermal band with any spatial resolution. However, because of the ineffectiveness of urban cover indicators in desert areas, the heat islands intensity in these regions was underestimated.

In applications that do not require high accuracy in calculating the urban heat island intensity, and there are high spatial resolution satellite imagery and sufficient training data in a region, the use of a classification-based approach seems to be suitable. Since the collection of such data and information is costly, a new method based on the urban percentage map was proposed in this paper by fitting a line to the LST parameter diagram in terms of the NDBI index for measuring the heat island intensity. The results indicated the higher efficiency and accuracy of the proposed method compared to the conventional classification-based methods for calculating the urban heat island intensity.

With the development of urbanization, large amounts of agricultural and forest areas are replaced with houses, industrial areas and other infrastructure. The warming of the urban environment is one of the unintentional impacts of unsustainable urban development, which is called the "urban thermal island." In this research, the thermal islands of Mashhad, one of the most important populated tourist centers of Iran that has had a rapid development during the last few decades has been studied. Using OLI and TIRS data from Landsat 8 and a two-window algorithm based on the amount of ground temperature and the amount of vegetation cover, which is calculated based on vegetation cover index of ground level [1] and vegetation cover on the earth's surface, the thermal level map of Mashhad city was calculated. The results showed that there is a relationship between vegetation index and surface temperature of the earth, which helps us to predict the surface temperature. Using vegetation index and separate window algorithm, it is found that the area 6 has the highest temperature and the lowest green space, and region 12 has the lowest temperature and the highest green space (vegetation). In this research, we tried to use a satellite image processing method to determine the surface temperature of the areas in the comprehensive plan of Mashhad. For this purpose, after performing the preprocessing on the image and the necessary corrections to determine the type of usage, the supervised classification method and the maximum probability algorithm were used. In this classification method each pixel is assigned to a class that has the most probability of belonging to that class (Fatemi & Rezaee, 2010). In fact, in this method, the variance and covariance of classes are used and each pixel of the image is assigned to the class that most closely resembles it (Alavi Panah, 2002).
The images used in this research are related to Landsat 8 and TRS sensors (bands 10 and 11) and OLI (bands 1 through 9) on 2017.6.6 (1396.3.6). The ground surface temperature was calculated based on the two-window algorithm method. The two-window algorithm calculates the surface temperature of the earth based on the Land Surface Earth (LSE) and Fractional Vegetation Cover (FVC). The results of this study indicate that the surface temperature of the earth is affected by the use of different land surface areas. Also, the results show that by establishing a relationship between the vegetation index such as NDVI and FVC, we can predict ground temperatures to obtain better results. With regard to surface temperature estimation, it is possible to use high-bandwidth resolution image sensors (Feizizadeh & Dedehban, 2015). Accordingly, the use of a separate window algorithm due to the use of 2 thermal bands is more accurate than the single-window method. In addition to thermal bands, other criteria also affect this algorithm which is based on mathematical relations. As previous studies have indicated, surface temperatures are higher in areas with less vegetation (Feizizadeh.B, Blaschke.T, Nazmfar,H ,Akbari,E and Kohbanani,H,R, 2012) as well as asphalt beds and roofing coatings with a darker color than those of bright colors (green roofs). In summary the results of this research can be summarized as follows:In the study of the relationship between land use land surface temperature and vegetation, it was determined that the use of green space at 11 ° C and the use of water at 8 ° C had the lowest surface temperature and residential use at 21 ° C and asphalt coating at 23 ° C Maximum surface temperature. Asphalt pavement agent has a great influence on the creation of thermal islands. The northern parts of Mashhad, the airport, and highways where the amount of asphalt used is high has a higher temperature.
Area 6 has the highest temperature and the lowest green space indicating a high density housing area without vegetation and area 12 has the lowest temperature and most green space. By moving from downtown to the foothills around Mashhad factors such as wind and vegetation can lead to lower temperature.
The most prominent urban green spaces of Mellat Park are in area 9 and Kouh Sangi in area 8, and due to the remoteness of these green spaces from the industrial areas and the vast areas of Mashhad, the surface temperature is very low.
In area 9 of Mashhad (Ab o Bargh Mountains) and the green belt around Mashhad, there is a part of the vegetation of the pastures and grasslands which include a natural vegetation and are better restored by the enclosure and prevented from degradation.

The role of green spaces in urban development is highly significant, to the extent that it is considered as an index of sustainable development. Through the perspective of urbanism, an urban green space is regarded as a part of cities’ anatomy and morphology. In other words, green spaces along with the physical structure of the city indicate its overall body and appearance (Hosseinzadeh Dalir, 1992). The physical and natural impacts of these spaces in urban systems as well as their ecological, social, and economic efficiencies in the structure of societies are undeniable. As a part of cities’ overall appearance, green spaces are considered as natural phenomena and a subject to which humans are constantly exposed. The ever-growing population has led to the extension of cities and excessive population density, intensifying the need to increase functional services, especially green spaces (Saeedinia, A. 2000).
Having an urban green area of 774.5 acres, Yazd city has a population of 582682 people. This city consists of three regions in which many districts from regions 1 and 2 are a part of the primary and old core of the city. During the past few decades, the city has witnessed a rather rapid growth toward industrialization. The study and investigation of vegetation require conducting extensive field operations and often involve a set of limitations including costs, time, facilities, and equipment; subsequently, the most suitable method would be remote evaluation and its useful techniques for assessing urban environments such as green spaces. Therefore, many researchers have employed data collected from remote evaluations in order to examine vegetation, making the technique a proper approach for conducting these types of studies (Huete, 2004). As a matter of fact, the use of remote evaluation indices is the new, prevalent view in the area of examining vegetation (Drysdale & Metternicht, 2003). To demonstrate the changes in Yazd city’s green spaces, the information collected from TM and ETM sensors of landsat satellite bands in the years 1987, 1999, and 2015 were used; then, the NDVI index was calculated for the aforementioned years in all three regions of the city. Following the indication of NDVI index on images, the total area of green spaces in Yazd was calculated twice, whilst taking into account the gardens, and vice versa. In order to conduct an accurate analysis, five parks including The Great City Park, Qadir Park, Daneshjou Park, Haft-e-Tir Park, and Azadegan Park were selected as the field data for sampling, once by points (four corners and the center of the park) and once as a whole (park’s area). In order to identify and separate the gardens, areas with such functions were found in each region using Yazd’s zoning map as well as considering the 1987 image as the basis; then, garden zones in all three regions were identified and separated using Google Earth.
The results of the study showed that regions 3 and 2 encompassed the smallest and largest green areas in 1987, respectively. Given such results, changes in green spaces of region 3 have been positive as the growth of green areas mostly included urban green spaces rather than gardens. Furthermore, the extents of urban green space area, changes in use, transformation of gardens into residential regions, and other urban uses were reduced by 271.71 acres during the past thirty years; meanwhile, 332124 people have been added to the population of Yazd during such time. The highest reduction in green spaces during these years is 205 acres which has occurred in region 2. According to the results, the green spaces in regions 1 and 2 have been decreasing during these years. Meanwhile, the development of such spaces in region 1 has been growing since 2005. There has been fewer changes in green spaces of region 2, in which gardens and green environments are of considerable importance due to their old age. In region 3 however, green spaces have been growing with the highest increase of green environments per capita taking place in 2015.
Given their considerable importance, gardens should be unrestricted and a set of budgets and policies should be assigned for their maintenance and conservation; this way, gardens are revived and become more effective in the organization of urban landscape. The presence of correct planning and policies is necessary for the development and conservation of urban green spaces. In general, adherence to a set of principles such as improving the public’s role through education, the society’s use of urban green environments, their ecological efficiency, and refining legal policy making and financial frameworks could guarantee the success of urban green environment management mechanism. As a result, it is necessary to increase green areas in addition to a proper distribution and developmental planning in line with conserving gardens while increasing green space per capita, especially in regions 1 and 3.

The study of drought has important significance in water resources studies. Meteorological drought indices that are calculated directly based on meteorological data, such as rainfall, In the absence of such data, will not be useful in monitoring drought. The remote sensing techniques can be considered a useful tool in monitoring drought. In this research, using MODIS sensor data, Normalized Difference Vegetation Index Change during the years 2000 to 2008 were reviewed. In addition to vegetation, NDVI index can also be effective for drought monitoring, especially for dry farming.Considering this indicator, the vegetation cover was classified into 4 groups and areas were calculated for each class. Finally, SPI and NDVI were compared. The result of calculation of SPI shows severe droughts in 2008 and moderate drought in 2000 and 2008, respectively. NDVI index in the three years indicated that the poor vegetation cover is significantly increased. High level Pearson correlations (.704) observed between SPI and NDVI in significant level of 0.01. However, the results of the effect of precipitation on NDVI index showed, there is no simultaneous occurrence of meteorological and agriculture droughts for all year. For 2006, despite the fact that precipitation was higher than average rainfall, but in this year, agricultural drought (reducing the value of the index (NDVI) occurred. Conversely, in 2002 and 2004, which precipitation less than 2006, but dry farming and pasture conditions were better than in 2006. And also in 2003 by a margin of 2 mm in precipitation than 2002, NDVI index value dropped too much. The results emphasize on the definition of the index that show all of this issue.

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. Therefore, recognizing this phenomenon is very important. In this research, the Landsat satellite images 5 and 8 used as studies base for studying region desertification. Moreover, the topography maps 250000 and 50000 and geology maps used as complement too. After completing the information data base, first, the soil salinity and vegetation NDVI indices exerted on the satellite images. According to artificial neural network MLP method, the usage recognized in the studied region, according to controlled categorize method Fuzzy ARTMAP. According to studied satellite images Isfahan have been grown about 260 km2. During this 29 years’ periods, the eastern and southeast regions of Isfahan indicate the most decline in vegetation that have been encountered to decline about 60% relative to the first year of study. This decline amount is considerable in the north region of Isfahan too. With decreasing the vegetation in these regions, onset of saline and desert lands is visible that displaced to regions with vegetation. This increasing amount in saline and desert regions is about 580 km2 that represent decreasing the ecologic and biologic potential of region.

In this study, meteorological data and remote sensing were used to investigate the effect of drought on vegetation in Semnan province. At first, the Standard Precipitation Index (SPI) for the years 2006-2015 was calculated at Semnan station. In the next step, based on 30 Aqua MODIS images from the platform in April, May and June, the normalized difference vegetation index (NDVI) was calculated. Considering this index, the vegetation was classified into four groups including lack of vegetation, thin vegetation, semi-dense vegetation, and dense vegetation. Then, the area of each class was calculated. Finally, the NDVI and SPI indices were compared. The results of the study showed a reverse relationship between NDVI and SPI on one hand and the rainfall in the thin and semi-dense vegetation on the other hand. During all the three spring months, with an increase in the amount of rainfall and the SPI value, the vegetation on the thin floor grew to be semi-dense. Conversely, as SPI and precipitation reduced, the area of semi-dense vegetation reduced and turned into thin vegetation. This is what usually occurs in the case of droughts. With regard to the considerable size of these two vegetation areas, which account for 93 percent of the whole province area, droughts can cause irreparable damages. As it was found, the desertification process invariably turns semi-dense vegetation into poor vegetation. If this process is not stopped, desertification will go on in the region.