New answers tagged statistics
You can use an adaptation of the next code (by using the path of your particular raster): from osgeo import gdal import numpy as np raster = "/home/zeito/pyqgis_data/utah_demUTM2.tif" dataset = gdal.Open(raster) band = dataset.GetRasterBand(1) print "rows = %d columns = %d" % (band.YSize, band.XSize) BandType = gdal.GetDataTypeName(band.DataType) print ...
As @whuber states: "Unless the study region was determined a priori, this "area" input is arbitrary, making the tool practically worthless--and even deceiving". This is advice work heeding. The nearest neighbor index is the ratio of the observed and expected mean neighbor distances. The expected is a function of the area and the number of observations. ...
In ESRI parlance, systematic quadrats are referred to as a fishnet. You can perform the analysis you are describing by first using the "Arctoolbox > Data Management Tools > Feature Class > Create Fishnet" tool. You will have to define the parameters of the quadrat sizes as there is no sensible default. Once you have the fishnet polygons created you can ...
You should look at the output. In the toolbox window click on the results tab at the bottom (and if necessary, uncollapse the Average Nearest Neighbor entry). The NNI ratio, p value, expected and observed are all reported. You need to interpret the actual statistic and not rely in ESRI's GUI interpretation. A random or uniform distribution would be near ...
You cannot use the Moran's I on an unmarked process. The values, at each location, are what the statistic is based on and therefore cannot be absent or uniform. Your only real option, in ArcGIS, for evaluating the spatial process (dispersion/clustering) of an unmarked point process is the Nearest Neighbor Index (Average Nearest Neighbor Tool).
The Modifiable Aerial Unit Problem (MAUP) is a change of support issue associated with arbitrary aggregate units. Two classic examples are census tracks and wildlife game units. These have been found to be arbitrary political units and the underlying statistical response in demography acts independent of the unit. Because of this, the unit is not an accurate ...
Open your table in ArcMAP, click the button in the upper left corner of the table and select "create graph", plot k against distance as a point or line graph. This could also be done in a spreadsheet program.
Just do a dissolve on Trip, then in the Statistics Field(s) just add the fields and the statistic type you want to be added to the attribute table. http://pro.arcgis.com/en/pro-app/tool-reference/data-management/dissolve.htm This has the added benefit of keeping the geometries for your data.
You can use the summarize tool on the field Trip, and in the summary statistics, select the relevant fields to calculate statistics for, like ave, min, max etc. The result is a table with a row for each trip, and a column for each statistic.
Use the Summary Statistics tool: This is the output:
You need to use layer.source() to get the paths of the rasters which is required by the zonal_stats module. Your code should look like: from rasterstats import zonal_stats layers = QgsMapLayerRegistry.instance().mapLayers().values() for layer in layers: stats = zonal_stats("/home/myshape.shp", layer.source())
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