[GIS] land Use land cover classification

arcgis-desktopclassificationerdas-imagineland-coverremote sensing

I am working on Land Use/Land Cover Classification of the Hindon river(India) watershed extracted using Aster DEM. Landsat 8 scenes had been used and mosaicked for the required AOI using the Watershed shapefile. I am facing a lot of troubles in the Unsupervised Classification, ISODATA method as I am getting numerous mixed pixels which are difficult to label. I had also tried histogram equalization before clustering but the recoding & labelling issues persist. Kindly suggest me some procedure to overcome the difficulties faced in labelling the classes.

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If you use QGIS, there is a plugin named "semi automatic classification". It may not take too much time to utilize the plugin because you might be familiar with the RS analysis methods. I have used it for 1 week and have been pleased. The plugin is also capable of downloading landsat's photos. Here's the link of classification tutorial. https://youtu.be/nZffzX_sMnk

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[GIS] Machine Learning Algorithms for Land Cover Classification

I would have to say that the most complete software environment for Machine Learning and nonparametric modeling is R. This is a big field in statistics, spanning K-NN, Kernel smoothing, General Additive Models, weak learners, support vectors, neural nets, semi-parametric spline regression, imputation, etc... I would highly recommend reading: Hastie, T., R. Tibshirani, J. Friedman (2009) The Elements of Statistical Learning: Data Mining, Inference and Prediction. Springer Series in Statistics.

Besides R, commercial software by Salford Systems has Random Forests, Multivariate Adaptive Regression Splines, CART and Gradient Boosting (TreeNet) available in a GUI environment. RuleQuest is still selling See5/C5 which is an updated version of the C4/ID3 CART algorithm. The University of Waikato's Weka 3 is an open source GUI/Commandline Java effort with a large number of models available.

[GIS] Land use land cover change post- classification in ArcGIS for cross- tabulation

The way to do it is to use the Tabulate Area tool:

Spatial Analyst Tools --> Zonal --> Tabulate Area

The output is the cross-tabulted areas between 2 rasters.

Give the first raster as the input raster or feature zone raster, the zone field is the land cover class field, the second raster is your second input raster.

The result will be in areas not in amount of cells, but to arrive to the number of cells, you just need to divide it by your raster resolution (e.g, if the raster is 1kmx1km, divide the output by the resoltion in meters: 1000x1000)

The vertical will be your first raster cell values (FROM), the horizontal your second raster cells values (TO).

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[GIS] Machine Learning Algorithms for Land Cover Classification

[GIS] Land use land cover change post- classification in ArcGIS for cross- tabulation

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