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How to perform measurement of spectral response pattern of multispectral satellite imagery like Sentinel 2 or Landsat using ESA-SNAP software and spreadsheet programs like Microsoft Excel or Google Sheets. Spectral Response Measurement is one of the most important analysis in remote sensing because it will tell use about the spectral response behavior of the earth surface object. Thus it will helps identify landcover type on the landcover classification and analysis 

All remote sensing users must be familiar and used to playing with multispectral bands combination to get certain information from imagery. If you are deeply understand about spectral response curve of surface earth objects, you will know that certain object (vegetation for example) gaves different spectral response compared to another objects. For satellite imagery consist of more than 3 bands (RGB in digital camera), different bands combination in RGB planes gaves different emphasizes to landcover colors in the imagery. Hence they are called multispectral imagery. Most of low to medium resolution imaging satellite currently operational in the earth orbit are multispectral, like landsat, modis, noaa avhrr, and many others.  Multispectral imagery number of bands can range from 4 bands to dozens bands, but not reaching hundreds. When the bands number reached more than one hundred bands it is called hyperspectral imagery and its analysis and image processing workflow would be pretty ...

The ability to create natural color composites is common for the past of current operational earth observation satellites. Natural color composites can be described as RGB image composites that have a color composition just like our eyes perceive color. In natural color composites, water would have a blue color, vegetation is green, bare soil or built-up landcover would have brownish to reddish color. You can make natural color composites images using satellite data that has blue spectral region of the electromagnetic spectrum of the sun. Imagery from satellites such as Landsat, Sentinel-2, IKONOS, Quickbird, Worldview, Pleiades, Kompsat, Formosat, and many others have a blue band so generating natural color composites would be an easy matter.  Things are quite different if we have satellite data that didn't have Blue Band such as ASTER or SPOT. For these kinds of imagery, natural color composites generation must be simulated from the available bands. And the results sometimes woul...

Georeferencing is a process to reference geospatial data into known and standardized coordinate system. Georeferencing is part of basic task that all GIS users must have ability to do it. Georeferencing can be done in 2D plane or 3D plane, and it can be applied into raster data and vector data. For Raster data, it could be georeferencing aerial photographs, satellite imagery, or scanned maps in image format. For Vector data, georeferencing usually is called spatial adjustment. Most of GIS and remote sensing software available on the market has this georeferencing ability, either for vector data or raster data.  As I already mentioned above, Georeferencing for raster data can be classified into two kinds of raster data. First is Scanned Maps in Image/PDF format, and second is for Satellite Imagery or Aerial Photographs. For earch type of data, the georeferencing procedures are little bit different. In this article I will talks about georeferencing satellite imagery and aerial photog...