Showing 18 results for Modis
Mr Ebrahim Bairanvand, Dr Amir Gandomkar, Dr Alireza Abbasi, Dr Morteza Khodaghoi,
Volume 0, Issue 0 (3-1921)
Abstract
The occurrence of torrential rains in April 2017 in Lorestan province was a clear example of heavy rains that left very heavy damage to agricultural, urban, transportation and communications infrastructure. The purpose of this study is to investigate and reveal the relationship between the physical structure of clouds producing two waves of heavy rainfall in April 2017 in the Doroud catchment area of Boroujerd. In this regard, the statistical characteristics of two precipitation waves on March 25 and April 1, 2019 were analyzed. The supernatural properties of the clouds producing these two heavy rainfall waves were investigated using the Madis superconductor product, MOD06. 4 Microphysical factors of generating clouds These two waves of heavy rainfall in the Doroud-Borujerd basin, including cloud peak temperature (CTT), cloud peak pressure (CTO), optical cloud thickness (COT) and cloud cover ratio (CF) were analyzed. Statistics of these two waves of heavy rainfall showed that in the first wave of heavy rainfall, ie the wave of March 25, 2019, (5 April 1398) 15% of the total annual rainfall and in the second wave, the wave of April 1, 2019 (April 12, 1398) 20% of the total The total average annual rainfall of the region was recorded in these two days. The results of analyzing the microphysical structure of the generating clouds of these two precipitation waves using the MODSI cloud sensor product data showed that the four microphysical factors of the cloud showed a significant spatial correlation with the recorded precipitation values of these two heavy precipitation waves. The two factors of temperature and pressure of cloud peak, which show a vertical expansion of clouds in the area, showed a significant inverse relationship with the amount of precipitation in the basin, while the two factors of cloud ratio and cloud optical thickness have a direct and significant spatial correlation with values. Recorded rainfall showed. The results of this study showed that in these two events of heavy rainfall, a significant and strong relationship was established between the microphysical structure of the cloud and the amount of rainfall recorded in the region.
Mr Danesh Nasiri, Dr Reza Borna, Dr Manigheh Zohorian Pordel,
Volume 0, Issue 0 (3-1921)
Abstract
Widespread and frequent droughts in recent decades in Khuzestan province have become one of the most important challenges of this province. The use of remote sensing products in temporal and spatial monitoring of drought can play a key role in managing this risk and reducing and adjusting its destructive effects. The main goal of this research is to provide a remote sensing index for temporal and spatial monitoring of drought in Khuzestan province and its validation using station meteorological drought indices. In this research, by using the products of vegetation (MOD13C2) and land surface temperature (MOD11C3) of MODIS sensor, a drought index based on vegetation called VHI plant health index was produced. SPI Meteorological Drought Index, which was based on station rainfall data during the statistical period of 2000-2012, was used to evaluate and quantify this index. The comparison of VHI drought index with three-month SPI meteorological drought index values showed a significant correlation between 0.68 and 0.75. By identifying 4 years with widespread and relatively severe drought in Khuzestan province (based on both VHI and SPI indices), which included the years 2000, 2005, 2012, 2015, the spatial distribution pattern of meteorological drought and VHI plant drought to In general, it indicated that the northern parts of the province were generally involved in mild to moderate droughts and the southern parts were generally involved in moderate to severe droughts. The spatial correlation matrix based on the number of 2500 pixels with dimensions of 5x5 km, which included VHI and SPI values of selected drought years, indicated the existence of a significant spatial correlation between the two mentioned indicators. In the widespread drought of 2000, at the level of Khuzestan province, two drought indices VHI and SPI, the correlation was equal to 0.47, and in 2005, equal to 0.35, and
Mrs. Zeinab Zaheri Abdehvand, Dr. Mostafa Kabolizadeh,
Volume 0, Issue 0 (3-1921)
Abstract
In vast areas, the possibility of simultaneous access to satellite images with appropriate spatial resolution, such as Landsat images, is always a challenge. In addition, the temporal resolution of the Landsat satellite does not provide the possibility of examining short-term changes in phenomena such as vegetation. The aim of this research is to use the temporal and spatial fusion techniques of Landsat-8 and MODIS satellite images in preparing the Normalized Vegetation Detection Index (NDVI) map. For this purpose, six image fusion algorithms, including NNDiffuse (Nearest Neighbor Diffusion), PC (Principal Component), Brovey, CN (Color Normalized), Gram-Schmidt, and SFIM, have been used in an experimental area in Khuzestan province. After evaluating the results of the algorithms and choosing the most appropriate fusion algorithm, based on the statistical indicators of the spectral (correlation coefficient) and spatial (Laplacen filter) criteria of each of the algorithms, the spectral and spatial information of the reflection of red and near-infrared of 8 mosaicked Landsat-8 images (30 m) were combined with the red and near-infrared bands of one MODIS image (250 m). In order to investigate the vegetation cover, the NDVI was prepared with the fused satellite image in the Khuzestan province. The results of the research have shown that the NNDiffuse integration fusion algorithm has a very good accuracy among other algorithms in terms of the spatial evaluation index and spectral quality criteria. Therefore, this algorithm was recruited to combine the red and near-infrared bands of Landsat-8 and MODIS images. Compared to the original Landsat-8 image, the NDVI map prepared by this algorithm has the lowest statistical error of RMSE (0.1234) and MAE (0.081), respectively.
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Volume 8, Issue 6 (12-2008)
Abstract
Majid Vazifedoust, Nima Fayaz, Shahab Araghinejad,
Volume 15, Issue 37 (9-2015)
Abstract
Variation of snow cover area (SCA) in small to large scale catchment can be studied using MODIS snow products on daily to montly time step since the year 2000. However, one of the major problems in applying the MODIS snow products is cloud obscuration which limits the utilization of these products. In the current study, variation of SCA was investigated in Karoun basin, western part of Iran, using MODIS 8-day snow cover product (MOD10A2). More over in order to overcome the cloud barrier in application of snow cover products, a simultaneous employment of the images from both MODIS optical sensor and AMSR-E microwave sensor was recommended. Meeting our target, the combination of MODIS and AMSR-E daily images was exercised to accomplish snow cover area in daily interval and afterwards, a comparison was made between the result and those which had been obtained by the sole utilization of either of them while the weather had been either cloudy and not been overcast. Validation of snow cover gained by combined images was additionally compared with the discharge of one of the catchments existing in Karoun basin. The results demonstrate that regardless of the fact that microwave data, featuring a coarse spatial resolution, can penetrate the cloud cover, on average, AMSR-E images approximately show 16% more snow cover in comparison to MODIS images. The results also illustrate that the correlation existing between snow cover rate of AMSR-E and MODIS images during cloudless days, the difference of average snow cover area decreases from 16% to 5%. Moreover, the upshot of validation by the exercise of daily discharge data indicates that by possessing a correlation coefficient of 0.66, the correlation of snow cover and discharge in combined images features a higher accuracy in comparison to MODIS images with a correlation coefficient of 0.55.
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Volume 16, Issue 41 (6-2016)
Abstract
Drought phenomenon with different goals including planning, water sources management and dealing with the problems due to water shortage has been investigated by most scholars. This research examined the relationship between drought and the normalized difference vegetation index (NDVI)in Qorveh and Dehgolan region in Kurdistan, Iran. To determine years with meteorological drought, index of Standard Z during a 20 year period time (1387-1368) has been applied. The results of the statistical data in Ghorveh station in 2008 with total annual rainfall of 155 mm and Z index of -2.31, in 2000 with total rainfall of 253.1 and Z index of -1.5 and in 2001 with 239.5 rainfall and Z index of -1.22. Were determined as drought indeces. MODIS satellite images were used to assess the ecological drought. Associated with each image to a randomly selected sample of 500 places in the software ERDAS, NDVI values were calculated for these images. satellite image processing results and Normalized Difference Vegetation Index (NDVI) indicates a low index values in the years 2000, 2001 and 2008 Were determined as ecological drought years of 2001 samples had the lowest NDVI and central parts of the area under irrigation has almost lost its vegetation.
Dr Javad Sadidi, Dr Hani Rezayan, Mr Mohammad Reza Barshan,
Volume 17, Issue 47 (12-2017)
Abstract
Due to the complexity of air pollution action, artificial intelligence models specifically, neural networks are utilized to simulate air pollution. So far, numerous artificial neural network models have been used to estimate the concentration of atmospheric PMs. These models have had different accuracies that scholars are constantly exceed their efficiency using numerous parameters. The current research aims to compare Elman and Jordan recurrent networks for error distribution and validation to estimate atmospheric particular matters concentration in Ahvaz city. The used parameters are relative humidity, air pressure, and temperature and aerosol optical depth. The latter one is extracted from MODIS sensor images and air pollution monitoring stations. The results show that Jordan model with RMSE of 219.9 milligram per cubic meter has more accuracy rather than Elman model with RMSE of 228.5. The value of R2 index that shows the linear relation between the estimated from the model and observed values for Jordan is equal to 0.5 that implies 50% estimation accuracy. The value is because of MODIS spatial resolution, inadequacy in numbers as well as spatial distribution of meteorological station inside the study area. According to the results of the current research, it seems that air pollution monitoring stations have to increase in terms of numbers and suitable spatial distribution. Also, other ancillary data like volunteer geographic air pollution data entry using mobile connected cheap sensors as portable stations may be used to implement more accurate simulation for air pollution.
Mr Sirous Hashemi Darebadami, Dr Ali Darvishi Boloorani, Dr Seyed Kazem Alavipanah, Mr Mohammad Maleki, Mr Reza Bayat,
Volume 19, Issue 52 (3-2019)
Abstract
The term urban heat island (UHI), described the phenomenon of climate change in urban areas compared with surrounding rural areas. UHI effects include: increasing in energy and water consumption, air pollution expansion and interfering in thermal comfort. Surface urban heat island (SUHI) contains patterns of land surface temperature (LST) in urban areas that has interaction with UHI in urban canopy layer and urban boundary layer and investigate with thermal remote sensing. SUHI has diurnal and seasonal variations so requires multi-temporal data to analysis SUHI. In this study, the multi-temporal MODIS (Aqua and Terra) data product were used to analyze the SUHI in day and night in Tehran metropolitan. Physical and biophysical surface properties such as: land cover/land use (LULC), elevation, albedo, vegetation index (NDVI) and impervious surfaces index (NDBI) were used to interpretation of the LST and SUHI changes. The results showed that SUHI in Tehran, has spatial-temporal diurnal and seasonal variation. So that during warm days the surface urban cool island (SUCL) is formed in Tehran. At night times, SUHI index values was different between 2 and 5 ° C (maximum in the spring). The results also showed that different of land cover thermal properties, albedo and elevation was the most important factors is the diurnal changes of SUHI while phonological changes of vegetation and albedo, was the most important factors in seasonal changes of SUHI.
Dr Parviz Zeaiean Firoozabadi,
Volume 20, Issue 59 (12-2020)
Abstract
Various satellite remote sensing data, images and products have proven their place in drought, drought and agriculture studies since the production of this type of information resource. Visible, near-infrared and thermal bands are among the most widely used in the production of products such as vegetation and surface temperature. In this study, from MODIS sensor data to investigate and find the coefficients of spatial relationship between vegetation-surface temperature index (NDVI-TS) and NDVI-ΔTS to extract the time of agricultural drought from June to October 2007 to 2010 in the catchment Siminehrood has been extracted from the Temperature-Vegetation Condition Index (VTCI) and the Water Lack Index (WDI), which are able to detect drought stress on a regional scale. The results of this study showed that in both indicators, the drought stress situation was higher in 2007 and 2008. Also based on the NDVI-TS space relationship in all the years 2007 to 2010 the high slope of the triangular space for the hot edge is negative. This means that with increasing NDVI, the LST level decreases while for the cold edge the slope is positive. In addition, the slope obtained from the NDVI-ΔTS space relationship is negative for the dry line, ie the dry line or the minimum transpiration-sweat line (ETR) shows a negative correlation with NDVI. While for the wet line, especially in 2010, the slope is positive and in other years, no significant change is seen. The present study showed that the VTCI threshold for drought stress was severe in 2007 and 2008.
Dr. Ali Bayat, Mr. Ahmad Assar Enayati , Mrs. Azimeh Toshani,
Volume 21, Issue 62 (9-2021)
Abstract
In this paper, aerosol optical depth measured by Caliop, MODIS, MISR, and OMI satellite sensors is compared with Sun-photometer data located in the Institute for Advanced Studies in Basic Sciences (IASBS) from December 2009 to December 2013 over Zanjan city. We computed figures for root mean square error (RMSE), mean absolute error (MAE) and root mean bias (RMB) between space-born and ground-based sensor measurements. The results show that the Caliop and MISR sensors have the highest correlation (0.61 and 0.54), respectively, with Sun-photometer measurements over Zanjan area. MISR, Caliop, and OMI sensors have the closest aerosol optical depth data to the Sun-photometer measurements (the fitted line slope is 0.68, 0.61 and 0.59, respectively) which represents the appropriate model used in the sensors to extract the aerosol optical depth. The variable monthly AOD figures obtained with different sensors indicate underestimation by MODIS and Caliop instruments (0.32 and 0.83 respectively) over Zanjan city relative to the Sun-photometer data, and overestimation by OMI and MISR instruments (1. 23 and 1.08 respectively).
Msc Taraneh Mirgheidari, Dr Behzad Rayegani, Dr Javad Bodagh-Jamali,
Volume 22, Issue 65 (6-2022)
Abstract
This study was conducted with the aim of providing a remotely sensed water quality index in Assaluyeh port using remote sensing technology. so, according to the region conditions, studying of scientific resources and access to satellite data, the parameters of heavymetals, dissolved ions, SST, chlorophyll-a and pH were selected. Then, by reviewing sources, the product MYD091km, MYD021km, MOD021km, MOD091km and level2 images of chlorophyll-a and SST of MODIS sensor were used after preprocessing operations. Also In-situ data were collected Simultaneously with the capture of satellite images in August 2014. Then, the relationships between the water quality parameters and MODIS data, with (R2) from 0.59 to 0.94 and (RMSE) from 0.07 to 0.1 were obtained. Next the images of the MODIS sensor from 2015 to 2017 were prepared and the models were applied to them, then the layers were standardized by fuzzy logic. Also time series of SST data from 2003 to 2017 were prepared and for each month the average pixel values were calculated and based on this, from 2015 to 2017, the variation of this parameter was standardized. Finally, an effective index for assessing the quality of coastal waters was provided by time series of satellite images and the waters of Assaluyeh port were zoned. The results showed that the water quality in 2015 and 2016 has shifted from poor to very poor status in 2017. Based on the results, with the development of a proposed index, in future studies a continuous assessment of environmental monitoring is possible.
Mrs Zahra Ebadi Nehari, Dr Mahdi Erfanian, Mrs Sima Kazempour Choursi,
Volume 23, Issue 68 (3-2023)
Abstract
Drought is a complex phenomenon caused by the breaking of water balance and it has always an impact on agricultural, ecological and socio-economic spheres. Although the drought indices deriving from remote sensing data have been used to monitor meteorological or agricultural drought, there are no indices that can suitably reflect the comprehensive information of drought from meteorological to agricultural aspects. In this study, the synthesized drought index (SDI) as a synthesized index from the vegetation condition index (VCI), temperature condition index (TCI) and precipitation condition index (PCI) were used for comprehensive drought monitoring in the Urmia Lake Basin (ULB) based on the Principal Component Analysis (PCA). For this purpose, MOD13A3, MOD11A2 and TRMM 3B43 data series were downloaded y for the period of 2001–2012. After initial processing, drought indicators were calculated using LST NDVI and TRMM data, and monthly drought severity maps were prepared. In order to validate SDI index, the Correlation relationship between SDI and SPI indices was obtained in the 3 month period during the growing season. As well as, SDI correlation relationships were investigated with wheat and barley crop yields. The results indicate that drought occurred in 2008 and 2001 in the ULB. The results of validation show that there is a correlation of 80% between the two SDI and SPI indicators. Also, the results of this study showed that the SDI index, as a comprehensive index of drought monitoring, reflects the effects of drought on agriculture.
Dr. Ruhallah Moradhaseli, Dr. Ali Bayat, Mrs. Fateme Radmehri,
Volume 23, Issue 70 (9-2023)
Abstract
Aerosol optical depth in 550 nm and angstrom exponent measurements with MODIS have been studied with 1-degree resolution for the period 2006-2017 in the middle east. Moreover, tropospheric aerosol optical depth and depolarization ratios measured at 532 nm with CALIOP have been studied for same area and same period of time too. These parameters have been classified seasonally. Optical depth results show high values for the region especially in spring and summer seasons. During the cold seasons, optical depth values are much less compared with their values at warm seasons. At spring, dust sources located in northern Iraq and those located in central and northern parts of Arabian Peninsula are much more active. Sources located in southern parts of Arabian Peninsula get more active by summer. Angstrom exponent results show that in arid and semi-arid parts of middle east, aerosol sizes are mainly in coarse mode. In arid parts of Iraq and Arabian Peninsula coarse mode particles are dominant during 4 seasons, but for arid parts inside Iran coarse mode is dominant during warm seasons and a modification in suspended particle sizes can be seen during cold seasons. Depolarization measurements of CALIOP show that almost in all seasons, non-spherical particles are ready in middle east atmosphere which is usual for an area inside the dust belt.
Kaveh Mohammadpour, Mohammad Saligheh, Tayeb Raziei, Ali Darvishi Bloorani,
Volume 24, Issue 72 (3-2024)
Abstract
Mineral Dust, the most important type of aerosol, has a significant direct and indirect role in weather and climate. In this case, it intend to investigate the capability and capability of MACC model validated by MODIS for detection of dust episodes in the Kurdistan province during 2003-2012. To achieve that, we analysis satellite and model data using Man-Kendall trend and statistical tests. The results of the temporal distribution indicated that the mean Aerosol Optical depth (AOD) in 2008 was 0.36 and its lowest was 29.04 for 2004. In addition, average AOD in menthioned year was 0.036, 0.335, 0.385, 0.377 and 0.3368 for the cities of Sanandaj, Saqez, Ghorveh, Kamyaran, Marivan, respectively. The spatial distribution of AOD average in different seasons showed that winter and autumn had the lowest amount and spring, and summer season had the highest AOD. AOD's monthly spatial distribution showed that high dust belonging to April-August period to covers completely interested area.The results of the Man-Kendall test showed that the area had a significant positive trend in the spring season throughout the province and the summer season in the east of the province. Therefore, the spring season in the area known Extreme Season and June 19, 2009 between the five days of the dust extreme is as an extreme episode with an average AOD of 1.16 and a horizontal visibility of less than two kilometers that it have the highest and most widespread mineral dust. In general, the results of the MACC with multidimensional approach showed that optical depth (AOD, DOD) is a more appropriate criterion than horizontal visibility in determining dust storm.
Mr Danesh Nasiri, Dr Reza Borna, Dr Manijeh Zohourian Pordel,
Volume 24, Issue 72 (3-2024)
Abstract
Knowledge of supernatural microphysical properties and revealing its relationship with the spatial temporal distribution of precipitation can significantly increase the accuracy of precipitation predictions. The main purpose of this study is to reveal the relationship between the Cloud microphysical structure and the distribution of precipitation in Khuzestan province. In this regard, first 3 inclusive rainfall events in Khuzestan province were selected and their 24-hour cumulative rainfall values were obtained. The rainfall event of 17December2006, was selected as a sample of heavy rainfall, 25 March 2019, as a medium rainfall case, and finally 27 October 2018, as a light rainfall case. Microphysical factors of clouds producing these precipitations were obtained from MODIS (MOD06) cloud product. These factors included temperature, pressure, and cloud top height, optical thickness, and cloud fraction. Finally, by generating a matrix with 64000 information codes, and performing spatial correlation analysis at a confidence level of 0.95, the relationship between the Cloud microphysical structure and the spatial values and distribution of selected precipitates was revealed. The results showed that in the case study of heavy and medium rainfall, the spatial average of 24-hour cumulative rainfall in the province was 36 and 12 mm, respectively. A fully developed cloud structure with a cloud ratio of more than 75% and a vertical expansion of 6 to 9 thousand meters, with an optical thickness of 40 to 50, has led to the occurrence of these widespread and significant rainfall in the province. While in the case of light rain, a significant discontinuation was seen in the horizontal expansion of the cloud cover in the province and the cloud cover percentage was less than 10%. In addition, the factors related to the vertical expansion of the cloud were much lower, so that the height of the cloud peak in this rainfall was between 3 to 5 thousand meters. The results of this study showed that in heavy and medium rainfall cases, a significant spatial correlation was observed at a confidence level of 0.95 between MOD06 Cloud microphysical factors and recorded precipitation values, while no significant spatial correlation was observed in light rainfall case.
Ms Akram Alinia, Dr Amir Gandomkar, Dr Alireza Abasi,
Volume 24, Issue 75 (12-2024)
Abstract
The main goal of this research is to analyze the time series trend of fire events in natural areas and reveal the relationship between these fire events and vegetation levels in Lorestan province. In this regard, the data of the fire product of the Madis sensor (MOD14A1) and the vegetation product (MOD13A3) of the Madis sensor were used during the statistical period of 2000-2020. The monthly and annual spatial distribution of fires in Lorestan province was investigated. Cross-information matrix analysis and spatial correlation matrix were used to reveal the relationship between fire occurrences and vegetation. The results showed that more than 70% of the total frequency of fire occurrences in natural resources fields (fires with code 2) in Lorestan province is related to June and then July. In terms of the long-term trend, the 21-year trend of the frequency of fire incidents in the province showed that the frequency of incidents in the natural resources areas of the province has generally increased with an annual slope of 3 incidents. The results of the correlation analysis between the monthly vegetation cover and the annual frequency of fire occurrences showed that the fire occurrences in the province showed a significant correlation with the vegetation cover changes in 4 months of the growing period, i.e. from May to August. Cross-matrix analysis between the spatial distribution of fire occurrence foci and NDVI index, both of which were products of MODIS measurement, indicated that, in general, the highest frequency of fire occurrences in Lorestan province in the period from May to August corresponds to Greenness range was 0.15 to 0.22. This range of vegetation generally corresponded to rainfed lands, weak pastures and low-density forest patches
Mr Masihollah Mohammadi, Prof Behrooz Sobhani,
Volume 25, Issue 76 (3-2025)
Abstract
Relative humidity is considered to be one of the most important climatic parameters and atmospheric phenomena. The purpose of the present study is to evaluate the regional algorithms for estimating relative humidity using remote sensing data in Hormozgan province. To this end, MOD05 and MOD07 products were employed to estimate total perceptible water, air temperature, and sea-level pressure Additionally, MOD35 was used for cloud verification, , resulting in the identification of 2190 cloudless images with 95% confidence level for analysis. radiosound data of Bandar Abbas ststion and synoptic stations Covering entire Hormozgan Province. were used to evaluate the results. The findings demonstrated high accuracy of the algorithms and experimental model, with acceptable R² and RMSE values between Modis product and ground data. These results align well with ground station measurements. The province's climate was determined to be semi-desert with a long warm season and a short cool period. Further analysis revealed a strong correlation between sea-level pressure and total perceptible water (TPW) with the region's topography. Maximum TPW and sea-level pressure values were recorded in coastal lowlands, while minimum values occurred in the highlands. Based on zoning maps, Hormozgan province can be divided into four regions based on relative humidity: from very dry conditions with less than 20% relative humidity in the highlands to humid areas with over 65% relative humidity along the coast.
Moslem Seydi, Kamal Omidvar, Gholamali Mozafari, Ahmad Mazidi,
Volume 25, Issue 77 (6-2025)
Abstract
Abstract
Climate change is an important environmental issue because the melting processes of glaciers and snow density are sensitive to climate change. Today, a variety of satellite sensors such as AVHRR, MODIS, GEOS, MERIS are available for snow monitoring and are widely used to investigate and investigate the fluctuations and changes in snow cover globally. Modis sensor has been considered more because of its global spatial coverage with suitable spatial accuracy and frequent temporal coverage on different scales , Therefore, in the present study, snow products of this sensor were used. In this study, after collecting statistics and data on snow-related days during the statistical period (1989-2018) in three provinces of Kermanshah, Ilam and Lorestan, they were processed using Modis snow cover data in middle Zagros as well as remote sensing techniques, Finally, the snow cover changes in the study area were studied in detail. NDSI index was used in MODIS sensor products to detect snow cover. Consequently, in order to differentiate pixels and identify different phenomena, the received images were processed in GIS environment. . Investigation of snow cover changes in different seasons using Modis sensor images shows that most of the studied area has a significant decreasing trend, especially in the elevated areas of the study area And only in the western and southwestern regions of the study area, there is no specific decreasing trend. Also, the study of snow covered days during the study period indicates a decrease in middle Zagros snow cover and these changes have been intensified in recent years, especially in snow-covered areas of the region. Also, changes in winter and snow-capped and elevated areas were more and more severe than other seasons and other regions in the study area.
