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Found 2 results

  1. I am attempting to downscale a plethora of temperatures points over a high resolution DEM, and have hit several roadblocks. On further research, I have found a method in which to execute this task, but am stuck on how to execute within ArcMap. The weighted linear function I plan to use is as follows `y=Bx+C` Where y=predicted temperature, B and C are coefficients, and x is the DEM layer. There are also several complex weighted functions that determine the influence of the station on the regression model as the specific DEM cell gains altitude away from the station and proximity away from the coastline. I've also attached the thesis in which this mirrors, which goes more in depth on the equations in question. http://www.int-res.com/articles/cr2002/22/c022p099.pdf Any help would be great, thank you! Eric
  2. Hi, For a research project I have collected a square grid of soil samples along with a GPS co-ordinate at each location, I have tested the soils to find results such as pH, Organic Matter Content and the likes. I then took random samples within the Grid to test the accuracy of GIS when predicting soil characteristics. I am wondering which GIS method to use , i.e Interpolation, Kriging , Co-Kriging or any other method. The software I have available is ArcGIS 10.3. I was going to compare the results of the actual random samples compared to what the GIS predicted values would give. Thanks, Stephen
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