How to perform Land Use Land Cover Change Detection in Python?
I want to see the change in various features like vegetation, water bodies, urban area, wetland etc. I have Landsat images. How do I perform this change detection using Python?
There are several ways to do so. The simplest one would be to classify the two images and then compare them so that the output is binary in nature (same land use or not). Gdal and numpy are useful libraries to achieve this.
For the purpose of classification, use machine learning algorithm where you provide a trained spectral signature or index value for each land use type and then perform supervised classification (using, for example, random forest algorithm).
There are several ways to do so. The simplest one would be to classify the two images and then compare them so that the output is binary in nature (same land use or not). Gdal and numpy are useful libraries to achieve this.
For the purpose of classification, use machine learning algorithm where you provide a trained spectral signature or index value for each land use type and then perform supervised classification (using, for example, random forest algorithm).
What are the requirements for Land Use Land Cover Classification in terms of satellite data? Is it required to have the satellite image atmospherically corrected one?
Land use and land cover changes are local and place specific, occurring incrementally in ways that often escape our attention. This study sought to detect changes in land cover in the Tema Metropolis of Ghana from 1990 to 2010. Multispectral Landsat Thematic Mapper data sets of 1990, 2000 and 2007 were acquired, pre-processed and enhanced. Unsuperv...
Wetland, as one of the weakest ecosystems in the world, is deteriorating rapidly in many regions. Longfeng wetland is the biggest urban wetland in China, located in the inner of Daqing city, Heilongjiang Province. It is divided into two areas by Wolong road, the east is provincial natural reserve and the west is unprotected. This paper describes a...