nowadays the science of remote sensing and satellite data, constitute modern scientific tools,as they provide important information and make research easier in many scientific fields. this research articlepresents an integrated system for continuous monitoring of the vegetation and the human impact on the natura2000 protected areas of strofilia forest and kotychi lagoon (natura 2000 codes: gr 2...

Digital image processing is collection of techniques for the manipulation of digital images by computer and its applications. This collection of methods in remote sensing is dominantly treated as Satellite Digital Image Processing (SDIP). A spaceborne Multispectral Image Processing System (MIPS) has been used since 1960 as a traditional satellite image processing system for data analysis and ex...

introduction frost as a harmful climatologic phenomenon affects various human activities and biological processes. due to mountainous nature of kurdistan province as the study area of this research in one hand and type and diversity of effective air masses on the other, the frequency, severity and duration of this phenomenon in the province are outstanding. confronting frost could be one of the...

In this paper, grid cell based spatial statistics were used to quantify the drivers of land-cover and land-use change (LCLUC) and habitat degradation in a tropical rainforest in Madagascar. First, a spectral database of various land-cover and land-use information was compiled using multi-year field campaign data and photointerpretation of satellite images. Next, residential areas were extracted...

Extracting surface water distribution with satellite imagery has been an important subject in remote sensing. Spectral indices of water only use information from a limited number of bands, thus they may have poor performance from pixels contaminated by ice/snow, clouds, etc. The detection algorithms using information from all spectral bands, such as constrained energy minimization (CEM), could ...

Biomass can indicate plant growth status, so it is an important index for plant growth monitoring. This paper focused on the methodology of estimating the winter wheat biomass based on hyperspectral field data, including the LANDSAT TM and EOS MODIS images. In order to develop the method of retrieving the wheat biomass from remote sensed data, routine field measurements were initiated during pe...

The Australian-based ARIES Consortium (Australian Resource Information and Environment Satellite), a commercial joint venture between CSIRO and private industry, is on track for deployment of the ARIES-1 hyperspectral resource mapping satellite in the year 2001/2002. The ARIES-1 spectrometer will be an area array scanning up to 105 spectral bands between 0.4 2.5μm at 30m spatial resolution. The...

Currently available image fusion techniques are not efficient for fusing the new satellite images such as IKONOS and Landsat 7. Significant colour distortion is one of the major problems. Reasons for this distortion are analyzed in this paper. A new initial automatic solution for fusing the new images is introduced. The new solution has reached an optimum fusion result – with minimized colour d...

This paper proposes a novel spatial and spectral fusion method for satellite multispectral and hyperspectral (or high-spectral) images based on dictionary-pair learning. By combining the spectral information from sensors with low spatial resolution but high spectral resolution (LSHS) and the spatial information from sensors with high spatial resolution but low spectral resolution (HSLS), this m...

Land-use classification for hyper-spectral satellite images requires a previous step of pixel characterization. In the easiest case, each pixel is characterized by its spectral curve. The improvement of the spectral and spatial resolution in hyper-spectral sensors has led to very large data sets. Some researches have focused on better classifiers that can handle big amounts of data. Others have...