Multispectral Remote Sensing Data Analysis Based on KNNLC Algorithm and Multimedia Image

Image fusion methods based on a linear mixing model of multispectral remote sensing data

Model based analysis or explicit definition/listing of all models or assumptions used in the derivation of an image fusion method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods ‘better’ satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two...

Multispectral Remote Sensing Image Classification Using Wavelet Based Features

Multispectral remotely sensed images composed information over a large range of variation on frequencies (information) and these frequencies change over different regions (irregular or frequency variant behavior of the signal) which need to be estimated properly for an improved classification [1, 2, 3]. Multispectral remote sensing (RS) image data are basically complex in nature, which have bot...

Deriving Bathymetry from Multispectral Remote Sensing Data

The use of passive satellite sensor data in shallow waters is complicated by the combined atmospheric, water, and bottom signals. Accurate determination of water depth is important for monitoring underwater topography and detection of moved sediments and in support of navigation. A Worldview 2 (WV2) image was used to develop high-resolution bathymetric maps (four meters) that were validated usi...

Remote sensing based on hyperspectral data analysis

Drought Analysis of Alvand Boundary River Using Remote Sensing Data

Extended abstract 1- Introduction       The study of the behavior of rivers in the arid and dry areas is one of the most important tasks in the country. Because the area has increased the effects of drought due to the sensitivity of the area and rainfall shortage, it causes changes in the flow and sediment regime, water resources, agriculture, and so on. Since plants react more precisely to t...