chulund / himawari-superclustering

Python and arcpy based bushfire hotspots superclustering for Himawari-8 satellite dataset.

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himawari-8 superclustering script

The script in this respotitory are the simplified version for hotspot superclustering (and determining the point of origin of the supercluster) using arcpy. Although simplified, it should be sufficient for hotspot superclustering and determining the point of origin.

It should be noted there is no extended version for the python/arcgis based superclustering since the superclustering was mostly done via model-builder and also FME. The Matlab version of the script is also included in this repository. However, it is not recommended to use the matlab script, since the scripts haven't been cleaned and properly documented. Besides, the python script is faster than the matlab script.

Folder explanation

There are several folder in this repository. When running the script it is advised to keep the folder location as it is.

  • Script : contains the actual script for the superclustering. The environment should be setup properly before running the script.
  • Data : the input ascii data should be put here. More info on the data format see Input section.
  • Output: the output cluster shapefile will be put in here.
  • Arcgisfile: contains the neccessary arcgis .aprx file as well as the location for the filegeodatabase to be created, which contains the intermediate results.
  • Other : zipped file containing scripts for matlab based superclustering, plotting, gridding, and many other matlab functions.

Environment

The IDE environment should be setup properly in order for the script to work properly. The script was tested only in interpreter Python 3.7 (arcgispro-py3). If arcgis pro is installed, the python excecutable should be located in the following folder: ...\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\python.exe

Input

The input file for the script, the format is similar to Chermelle usual output. The folder contains the Kangaroo Island hotspots file (kangarooisland.csv) for sample. Here is the snippet of the file

datetime,longitude,latitude,x,y,mir,tir,albedo,frp,state
20191221000000,136.939453,-35.703125,2585,4534,368.5625,296.875,0.179688,-999, SA
20191224000000,137.032227,-35.677734,2589,4533,340.125,300.5,0.210938,78.47, SA
20191224000000,137.007812,-35.703125,2588,4534,364.125,299.125,0.179688,278.13, SA
20191224000000,137.03125,-35.703125,2589,4534,397.3125,307.625,0.171875,799.62, SA
20191224000000,137.053711,-35.702148,2590,4534,354.8125,306,0.109375,186.81, SA

defined variables

The first part of the script contains the following variable, which can be changed:

out_folder = "D:/Research/2021/Githubing/Output"
work_folder = "D:/Research/2021/Githubing/Arcgisfile"
aprx_input = r"D:/Research/2021/Githubing/Arcgisfile/Clustering.aprx"
csv_input = r"D:/Research/2021/Githubing/Data/kangarooIsland.csv"
buffer_size = "2000 Meters"
time_threshold = "2 Hours"

The rest of the script is commented and should be self explanatory.

@Nur Trihantoro - 30 June 2021

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Python and arcpy based bushfire hotspots superclustering for Himawari-8 satellite dataset.


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