pixelcooker

Area and length measurement is very basic task in GIS. Almost every GIS software can do that. Things become harder if we want to calculate polygon volume in GIS. until few years ago, there is no simple and direct way to calculate polygon volume in GIS. Some GIS and Remote sensing software provide built in tool to do that, but these software usually have certain data format that is not easily converted into standard GIS format. Today the game has changed. Some developer has built a simple and intuitive plugin to calculate polygon volume using DEM as reference, and the most awesome aspect is, they made it in Quantum GIS / QGIS environment. This is a life saver because QGIS is a free software!. And here is my experience when I try those new developed plugin to calculate polygon volume in QGIS. ArcGIS doesnt have this luxury.  

Working in GIS using free software like QGIS is a something, but integrate it with the most popular data science language is something else. Almost all of Remote Sensing and GIS software have implemented Python integration these days, but sometimes those features hidden in the user interface. If you are familiar with python, you must be know that python has something GIS software cant provide. And this state we have an urge to why not use both of them?, here is how to install thid party python libraries to QGIS which is sometimes not all of available python libraries already installed in default QGIS python configuration. 

Google Earth Engine is a revolutionary Remote Sensing Analysis platform that changed the remote sensing data processing landscape in extreme way. This platform is powered by Cloud Computing hosted by Google and you know, by the means of cloud computing now you are enabled to process and analyze tons of satellite data without sacrificing your computer hardware. You dont have to procure high end computer to enabling the robust and sophisticated remote sensing and digital image analysis workflow. You just need a browser to run all the complex processing. You only needs a good knowledge of javascript programming to make google earth engine works for you. On the other side, may be you are asking about what if I didnt have enough knowledge of javascript. What I am doing all the time is python programming. Dont worry my friends, now Google Earth Engine is also provides Python engine for you to use. You can run Google Earth Engine in the Google Colaboratory Environment, or you can also do it i...

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 ...