I don't think your problem is orthorectification for what you want to perform.
Before you can do classification and change detection you need to do:
Convert DN to radiance Convert radiance to reflectance Then you can do NDVI, Classification, change detection, comparison etc. between sensors and temporal resolutions
The centrograpic tools and global statistic tools (mean, standard distance, directional distribution, NNI and Getis-Ord General(Gearys C)) will tell you if there is patterns and clusters in your data and how significant they are but NOTHING about where and why.
You might need to manipulate/change/add your data before you can perform a Getis-Ord Gi* test (also one with automatic rendering). This tool will tell you WHERE your coldspots are and your hotspots are and the area that is 'not significant' and it will do it at a 90-95-99% confidence level and give you values about observed distance and expected distance and other values that is statistical proven.
KDE and Hotspot analysis is two different things and therefore NOT comparable although MANY police forces uses the KDE. The KDE will hide your coldspots.....depending on your threshold it will increase/decrease your density.....if use over different polygons/areas it will give you different outputs that are not in the same scale but only relevant to the dataset.....Getis-Ord Gi* does NOT do this. Intended or unintended you could lead he user/reader into misinterpretation with a KDE......this would be almost impossible with the Gi*
A good reference is the 'Understanding hotspot' by Chainey et al and published by NIJ in 2005 (National Institute of Justice)
Well a KDE is NOT a hotspot (although many think so and use it as)....It only shows you a relative density and has NO statistic footing....If you want a hotspot/coldspot output that is statistically worthy and reliable you need to use the centrographic tools in Spatial Statistical and especially the Getis-Ord Gi*
Hi out there,
I have been tasked to do comment on the quality of a LIDAR product. But the only thing I've got is a "point cloud" as a shapefile and no other information. There is no metadata or text in the description.
How do I do the QA/QC then ??
What kind of data do you have to begin with ?
As I think you need one with "obstacles" and one without.....then it would be (obstacles - without)....but they have to have the same resolution then, otherwise you must resample fist
Hi there,
What is the best open source software out-there to do Supervised/unsupervised image classification and can be compared to same procedures in ArcGIS, ENVI and ERDAS ?
I used these when I started, so try them.....learn a bit from them and search Google.
http://help.arcgis.c...500000033000000
https://docs.google....WdfpowlFZ5Fihaw