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geostatistical analyst-kriging

juliaDa

Hi all,

I am using IDW and Kriging in ArcGIS to explore the distribution of forest carbon stock using 183 ground sample points. The data is not normal and there is trend, so I have transformed the data. However after running kriging, the cross-validation result shows root mean square standardized: 0.98, root mean square and average standardized error: 127.7 and 128.89 respectively and the main problem is the predicted and error plot is not 1:1. Can anyone please suggest what can be the issue and how can I address this. Any helpful suggestions will be highly appreciated.

Thanks in advance!

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juliaDa

Yes i have thought of partitioning but in certain region there are not enough sample points. I am trying to look at the spatial distribution of forest carbon in whole watershed, so I thought of using kriging in whole area, and also based on some literature review. I couldn't think of any other method, any suggestion!

DanPatterson_Retired

Before getting into the spatial interpolation methods, did inferential tests between landscapes yield any valuable information? Had you considered partitioning the landscape into discrete areas prior to kriging? since I am not sure why you would do that if there are inherent differences in the landscape to begin with (ie forest vs agri. low vs high elevations). I am just trying to get a sense why kriging is being applied to the whole area?

juliaDa

Dan thank you for the reply

Yes the sample points are numbers, the study area is watershed of about 8000 ha, and with wide elevation range from low mid 200 to high 1900 m. The main landuse in this area are forest and agriculture, there are some agricultural patches in between the forest area where there is no sample points.

DanPatterson_Retired

Ok they are the numbers...what is the area like from a qualitative perspective?

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