statistics_grid_5-Zonal_Grid_Statistics

Zonal Grid Statistics

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contributed at 2018-11-06

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Geography SubjectGIScience & Remote SensingSpatial Analysis

Detailed Description

The tool calculates zonal statistics and reports these in a table. The tool can be used to create a contingency table of unique condition units (UCUs). These units are delineated from a zonal grid (e.g. sub catchments) and optional categorical grids (e.g. landcover, soil, ...). It is possible to calculate descriptive statistics (n, min, max, mean, standard deviation and sum) for each UCU from optional grids with continious data (e.g. slope; aspect must be handled specially, please use the "Aspect" input parameter for such a grid). The number of input grids is only limited by available memory.The tool has four different modes of operation:(1) only a zonal grid is used as input. This results in a simple contingency table with the number of grid cells in each zone.(2) a zonal grid and additional categorical grids are used as input. This results in a contingency table with the number of cells in each UCU.(3) a zonal grid and additional grids with continuous data are used as input. This results in a contingency table with the number of cells in each zone and some simple statistics for each zone. The statistics are calculated for each continuous grid.(4) a zonal grid, additional categorical grids and additional grids with continuous data are used as input. This results in a contingency table with the number of cells in each UCU and the corresponding statistics for each continuous grid.Depending on the mode of operation, the output table contains information about the categorical combination of each UCU, the number of cells in each UCU and the statistics for each UCU. A typical output table may look like this:

ID ZoneID 1stCatID 2ndCatCount UCUN 1stContMIN 1stContMAX 1stContMEAN 1stContSTDDEV 1stContSUM 1stCont
0 2 6 6 6 708.5 862.0 734.5 62.5 4406.8
0 3 4 106 106 829.1 910.1 848.8 28.5 89969.0

How to cite

SAGA (2018). statistics_grid_5-Zonal_Grid_Statistics, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/d0ed2a39-f7ec-41af-a263-effa862c38a0
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contributed at 2018-11-06

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