In recent years, the rate of urban growth has increased rapidly especially in Egypt, due to the increase in population growth. The Egyptian government has set up new cities and established large factories, roads and bridges in new places to solve this trouble. This paper investigates the change monitoring of land surface temperature, urban and agricultural area in Egypt especially Kafr EL-Sheikh city as case study using high resolution satellite images. Nowadays, satellite images are playing an important role in detecting the change of urban growth. In this paper, cadastral map for Kafr El-Sheikh city with scale 1:5000, images from Landsat 7 with accuracy 30 meters; images from Google Earth with accuracy 0.5 meter; and images from SAS Planet with accuracy 0.5 m are used where all images are available during the study period (for year’s 2003, 2006, 2009, 2012, 2015 and 2017). The analysis has been performed in a platform of Geographical Information System (GIS) configured with Remote Sensing system using ArcGIS 10.3 and ERDAS Imagine image processing software. From the processing and analysis of the specified images during the studied time period, it is found that the building area was increased by 28.8% from year 2003 up to 2017 from Google Earth images and increased by percentage 34.4% from year 2003 up to year 2017 from supervised Landsat 7 images but for unsupervised Landsat 7 images, the building area was increased by percentage 35.9%. In this study, land surface temperature (LST) was measured also from satellite images for different years through 2003 until 2017. It is deduced that the increase in the building area (urban growth) in the specified city led to increase the land surface temperature (LST) which will affect some agricultural crops. Depending on the results of images analysis, Forecasting models using different algorithms for the urban and agricultural area was built. Finally, it is deduced that integration of spacebased remote sensing technology with GIS tools provide better platform to perform such activities.

The difficulties of access and detailed measurements of land surface temperature (LST) and water surface temperature (WST) especially in wetlands made the use of remote sensing data as one of the sources and techniques to estimate many climate elements including surface temperature and surface emissivity (ɛ). This study aims to estimate the surface tempera-ture of the wetland of Lake Oubeira located in northeastern Algeria and their spatiotemporal evolution in both land and wa-ter. Landsat OLI-TIRS images in two dates (April and September 2016) obtained from the USGS have been used in this work, and forms the basis of a series of operations to obtain the final LST: development of the normalized difference vegeta-tion index (NDVI), conversion of the digital number (DN) of the thermal infrared band (TIR) into spectral radiance as well as the calculation of the effective luminosity temperature of the sensor from the spectral radiation and surface emissivity (ɛ). The results show that the LST varies in space and time (from 16 to 31°C in April and from 24 to 41°C in September). This implies that the absorption of the equilibrium temperature at land cover depends on the optical properties of the sur-face, which are essentially determined by its water content, colour and morphology. At the same time, the water surface is the lowest land cover temperature, which also has a spatial variation (from 19 to 25°C in April and from 26 to 34.5°C in September) induced by atmospheric temperature, wind direction and speed and the depth of the lake.