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I am extracting data using the tabulate area tool. The data has too many duplicates for each plot. However, when extracting these plots with duplicates separately, I do not see the duplicate values. In other words, I get different values. With respect to duplicate values, these different plots cannot surely have same values at precision 6 decimal places. Which means something is wrong with my batch area extraction of classes by plot.

The general steps I used are as follows:

  1. Classified my image into three class, Spatial reference: WGS_1984 (Output file=MLClass.tif)

  2. Created polygons over the image, with project coordinate system (WGS_1984_UTM_Zone_36S) (Output file=Field Plots.shp)

  3. Convert Field Plots.shp to raster using: Feature to raster/polygon to raster tools Environmental settings [Snap Raster (MLClass.tif)] (Output file=Feature_Field_Plots)

  4. Tabulate Area (Spatial Analyst)>> Input zone=Feature_Field_Plots; input Class=MLClass.tif. (I selected attributes of interest in each case) (Output file=Tabulate_Feature)

Can someone help figure what is it I am doing wrong?

  • What software are you using? And could you expand on what you mean by this: However, when extracting these plots with duplicates separately, I do not see the duplicate values. In other words, I get different values. With respect to duplicate values, these different plots cannot surely have same values at precision 6 decimal places. – MaryBeth Aug 11 '17 at 14:56
  • For the start I suggest to project MLclass.tif, not other way around, because using degrees based spatial reference system will result in non-sense results from tabulate area tool – FelixIP Aug 12 '17 at 3:37
  • Hie MaryBeth. I am using ArcGIS 10.1. Below is an attribute with these duplicates for different plots. My worry is sometimes I am getting same value for more than 10 different plot I am doing batch processing. However when I extract data for each plot manually I get different values which are making sense when I visually explore the classified image for the respective plots DRY_CANOPY 0.015788764 0.015788764 0.015788764 0.059130468 0.059130468 0.059130468 – Richard Aug 14 '17 at 15:26
  • Hie Felix!! When I projected the MLClass.tif image, I am getting an error message that say "Inconsitent extent..., re-projecting data in such a layer may lead to an unexpected behaviour." So I am wondering whether this approach works. – Richard Aug 14 '17 at 15:59

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