multi-spectral remotely sensed data is useful information source for the detection of surface changes and change detection is a major application of the remotely sensed data. this study is conducted to investigate capability of sensor liss-iii of irs-p6resource satellite data for providing land cover map, in najm abad of savojbolagh region with 20000 ha area. the images of 26th june, 2006 were ...

application of satellite imagery and remote sensing techniques in agriculture and other natural resources has been approved by many studies. in this study two etm+ imagery data for may and september 2012 of astan ghods razavi great farm were acquired to identify the boundaries of lands cultivated with different crops coverage and to create crops maps of that farm. . to classify the images, the ...

Images from the GOES 8 satellite were used along with auxiliary information such as snow cover to produce an hourly solar radiation database on a 0.1° grid for the Pacific Northwest from 1998 through 2002[1]. Both global and beam irradiance values were derived from the satellite images and diffuse values were calculated from the beam and global values. Data from the University of Oregon Solar R...

The radiometric normalization of multi-temporal satellite optical images of the same terrain is necessary for land cover change detection e.g. relative differences. In previous studies, ground reference data or pseudo invariant features (PIFs) were used in the radiometric rectification of multi-temporal images. Ground reference data are costly and difficult to acquire for most satellite remotel...

Land use patterns are fragile and sophisticated in Taiwan. In order to rapidly derive detail information of land use/land cover, it is necessary to employ remote sensing techniques because of its broad area coverage and fast data acquirement. The purposes of this research are to use high-resolution satellite images, such as IKONOS, to obtain urban land use information, and to apply fuzzy algori...

The reflections recorded on satellite images have been affected by various environmental factors. In these images, some of these factors are combined with other environmental factors that cannot be distinguished. Therefore, it seems wise to model these environmental phenomena in the form of hybrid indicators. In this regard, satellite imagery and machine learning methods can play a unique role ...

A set of high-resolution multi-spectral satellite images were collected and processed to estimate the sediment concentration in the sea-breaking zone. The value of Total Suspended Matter (TSM) is empirically related to the sea surface reflectance. However, in order to obtain accurate reflectance measurements from the satellite images, the effect of the atmosphere needs to be accounted for. A se...

Remote sensing has changed modern oceanography by proving synoptic periodic data which can be processed. Since the satellite data are usually too much and nonlinear, in most cases, it is difficult to distinguish the patterns from these images. In fact, SOM (Self-Organizing Maps) model is a type of ANN (Artificial Neural Network) that has the ability to distinguish the efficient patterns from th...