نتایج جستجو برای: landsat land surface temperature lst
تعداد نتایج: 1128966 فیلتر نتایج به سال:
A C++ language-based software tool for retrieving land surface temperature (LST) from the data of Landsat TM/ ETM+ band6 is developed. It has two main functional modules: (1) Three methods to compute the ground emissivity based on land use/cover classification image, NDVI image and the ratio values of vegetation and bare ground and (2) Converting digital numbers (DNs) from TM/ETM+ band6 to LST....
Land Surface Temperature (LST) is one of the key inputs for Soil-Vegetation-Atmosphere transfer modeling in terrestrial ecosystems. In the frame of BIOSPEC (Linking spectral information at different spatial scales with biophysical parameters of Mediterranean vegetation in the context of global change) and FLUXPEC (Monitoring changes in water and carbon fluxes from remote and proximal sensing in...
This paper proposes a practical split-window algorithm (SWA) for retrieving land surface temperature (LST) from Landsat-8 Thermal Infrared Sensor (TIRS) data. This SWA has a universal applicability and a set of parameters that can be applied when retrieving LSTs year-round. The atmospheric transmittance and the land surface emissivity (LSE), the essential SWA input parameters, of the Landsat-8 ...
Here, our objective was to develop a spatio-temporal image fusion model (STI-FM) for enhancing temporal resolution of Landsat-8 land surface temperature (LST) images by fusing LST images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS); and implement the developed algorithm over a heterogeneous semi-arid study area in Jordan, Middle East. The STI-FM technique consisted of t...
Accurate inversion of land surface geo/biophysical variables from remote sensing data for earth observation applications is an essential and challenging topic for the global change research. Land surface temperature (LST) is one of the key parameters in the physics of earth surface processes from local to global scales. The importance of LST is being increasingly recognized and there is a stron...
Land surface temperature (LST) is an important parameter to study in urban climate. The understanding of the influence of biophysical factors could improve the establishment of modeling urban thermal landscape. It is well established that climate hold a great influence on the urban landscape. However, it has been recognize that climate has a low priority in urban planning process, due to the co...
Urbanization through rapid constructions, is the main cause of high heat absorption in urban centers. In addition, the accumulation of heat energy resulted by removal of vegetation cover, has contributed to formation of urban heat islands (UHIs). The spatial distribution of heat intensity in Tehran Metropolitan Area was studied, and the influence of land use and green cover were analyzed in the...
Urbanization through rapid constructions, is the main cause of high heat absorption in urban centers. In addition, the accumulation of heat energy resulted by removal of vegetation cover, has contributed to formation of urban heat islands (UHIs). The spatial distribution of heat intensity in Tehran Metropolitan Area was studied, and the influence of land use and green cover were analyzed in the...
This paper compares the normalized difference vegetation index (NDVI) and percent impervious surface as indicators of surface urban heat island effects in Landsat imagery by investigating the relationships between the land surface temperature (LST), percent impervious surface area (%ISA), and the NDVI. Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data were used to estim...
Remotely sensed imagery has been increasingly used to study the urban heat island phenomenon by deriving and analyzing land surface temperatures. The technology of remote sensing has the advantage of providing a time-synchronized dense grid of temperature data over a whole city region and distinctive temperature measurements for individual buildings. Moreover, some remote sensing images have hi...
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