The pressing issue of global warming is particularly evident in urban areas, where thermal islands amplify the effect. Understanding land surface temperature (LST) changes crucial mitigating and adapting to effect heat islands, ultimately addressing broader challenge warming. This study estimates LST city Yazd, Iran, field high-resolution image data are scarce. assessed through parameters (indices) available from Landsat-8 satellite images for two contrasting seasons—winter summer 2019 2020,...

Land surface temperature (LST) is a basic parameter in energy exchange between the land and atmosphere, frequently used many sciences such as climatology, hydrology, agriculture, ecology, etc. Time series of satellite LST data have usually deficient, missing, unacceptable caused by presence clouds images, dust sensor failure. In this study, singular spectrum analysis (SSA) algorithm was to resolve problem missing outlier cloud cover. The region studied present research included an image...

Climate change stressors like rising and warmer seas, increased storms droughts, acidifying oceans are rapidly threatening coastal zones, which the world’s most densely inhabited places. This research assesses effects of Palm Jumeirah Island (PJI) construction on its surrounding water quality temperature, using Landsat-7 8 spectral thermal bands for years 2001, 2014, 2016, 2019, 2020. To aid in this goal, changes reflectance was observed interpreted, based previous measurements, to discover...

Water scarcity is a critical abiotic stress factor for plants in arid and semi-arid regions, impacting crop development production yield quality. Monitoring water at finer scales (e.g., farm plant), requires multispectral imagery with thermal capabilities centimeter resolution. This study investigates drought pistachio trees located Yazd province, Iran, by using Unmanned Aerial Vehicle (UAV) images to quantify evapotranspiration assess individual trees. Images were captured on 10 July 2022,...

In dry regions, gardens and trees within the urban space are of considerable significance. These facing harsh weather conditions environmental stresses; on other hand, due to high value land in areas, they constantly subject destruction use change. Therefore, identification monitoring areas regions their impact ecosystem aims this study. The data utilized aerial Sentinel-2 images (2018–2022) for Yazd Township Iran. Several satellite image fusion methods were employed compared. root mean...

Monitoring vegetation changes over time is very important in dry areas such as Iran, given its pronounced drought-prone agricultural system. Vegetation indices derived from remotely sensed satellite imageries are successfully used to monitor at various scales. Atmospheric dust well airborne particles, particularly gases and clouds, significantly affect the reflection of energy surface, especially visible, short infrared wavelengths. This results with missing data (gaps) outliers while change...

Water is crucial for enduring horticultural productivity, but high water-use requirements and declining water supplies with the changing climate challenge economic viability, environmental sustainability, social justice. While scholarly literature pertaining to management in horticulture abounds, knowledge of practices technologies that optimize use scarce. Here, we review scientific relating crops, impacts on resources, opportunities improving water- transpiration-use efficiency. We find...

In this study, Geopotential Height (between 500 and 1000 hPa) precipitation data were obtained from the NCEP/NCAR IRIMO (Iran Meteorological Organization) for 60 years (1950–2010), respectively. Descriptive features of Atmospheric Thickness (hereafter AT) calculated analyzed by using Mann-Kendall method. The results showed that maximum AT was recorded in summer because dominance dynamic, hot subtropical high pressure. Furthermore, upper latitudes experienced more variations terms AT. trend...

Climate change affects plant dynamics and functioning of terrestrial ecosystems. This study aims to investigate temporal changes in global vegetation coverage biomes during the past three decades. We compared historic annual NDVI time series (1982, 1983, 1984 1985) with recent ones (2015, 2016, 2017 2018), captured from NOAA-AVHRR satellite observations. To correct for missing data outliers, we applied Harmonic Analysis Time Series (HANTS) algorithm. The were decomposed their significant...

Land surface temperature (LST) is a significant environmental factor in many studies. LST estimation methods require various parameters, such as emissivity, temperature, atmospheric transmittance and water vapor. Uncertainty these parameters can cause error estimation. The present study shows how the moderate resolution imaging spectroradiometer (MODIS) vapor imagery improve accuracy of Landsat 8 different land covers arid regions Yazd province Iran. For this purpose, variation analyzed for...

Thermal monitoring of different regions is usually limited to meteorological data in ground stations. Meteorological networks are arid and semi-arid areas, where climatic conditions not possible. The aim this study estimate the land surface temperature (LST) hourly for Yazd-Ardakan plain by modeling diurnal cycle (DTC) using LST imagery moderate resolution imaging spectroradiometer (MODIS). First, MODIS reconstructed multi-channel singular spectrum analysis, complete time series without...

Prioritization of pathways to perform asphalt pavement operations has always been one the most important concerns for municipalities, which, currently there is no specific planning and pattern. In present study, using (Unmanned Aerial Vehicle) UAV images, a land cover map case study was prepared. For this purpose, accuracy various object-based classification methods including Bayes method, Support Vector Machine (SVM), K nearest neighbor (KNN), Decision tree (DT), Random (RT) investigated....

One of the main problems in developing countries is unplanned urban growth and land use change. Timely identification new constructions can be a good solution to mitigate some environmental social problems. This study examined possibility identifying areas using images from unmanned aerial vehicles (UAV), Google Earth Sentinel-2. The accuracy cover map obtained these was investigated pixel-based processing methods (maximum likelihood, minimum distance, Mahalanobis, spectral angle mapping...

The soil thermal properties (soil conductivity, heat capacity and diffusivity) are the main parameters in applications that need quantitative information on transfer. Conventionally, these either measured situ or estimated by semi-empirical models using fractions of constituents. use such methods over large heterogeneous areas, however, is often costly, timeconsuming sometimes impractical. This thesis proposes evaluates a new approach to estimate inverse modelling Spectral Soil Thermal...

Abstract Classifying satellite images with medium spatial resolution such as Landsat, it is usually difficult to distinguish between plant species, and impossible determine the area covered weeds. In this study, a Landsat 8 image along UAV was used separate pistachio cultivars weed from trees. order use high of images, fusion carried out through high-pass filter, wavelet, principal component transformation, BROVEY, IHS Gram Schmidt methods, ERGAS, RMSE correlation criteria were applied...