Latest Contributions by Elijah

Hi Eric, I was searching to know how exactly the (ArcGIS) software back-transforms log-normalized data into the original scale. I am particularly interested in how this is handled in EBK, in case it's handled differently in other models. Please, can you explain to the extent possible? Thanks Elijah ... View more

Thanks Johaness. I will try to see how to manage the codes. I appreciate. ... View more

@Scott, EBK or EBK regression prediction typically outperforms other interpolation techniques, may be, apart from some other ML techniques. However, EBK and EBKRP can't work here using ArcGIS since I guess the minimum number of samples it can handle is 20. If you have covariates with noise, you can try co-kriging since. Adding covariates may help improve the prediction. If not, advise from SteveLynch is most appropriate. Try as many as may appear reasonable, than compare the error stats. ... View more

Dear Eric, Again, I quite appreciate your answers. I need a few more insight if possible. You have well-dealt with possible number of samples implied by 'small'. However, knowing that the number of samples is not linearly related to sampling density, is there anything specifically advantageous about using EBKRP, for instance, in low sampling density scenarios? Generally, interpolation accuracies are affected by the sampling density and distribution. I will like to know if, perhaps by means of estimating the semi-variogram through the process of sub-setting and repeated simulations, EBKRP can achieve better result than other kriging models, in low sampling density setting. The whole idea is to say or not, that, in a data-scarce (sparse) / low density sampling situation setting (not necessarily small number of samples), EBKRP will perform better than other kriging models, based on its intrinsic characteristics.   Thanks in advance. ... View more

Hi Eric, Your answer is very much appreciated. Many thanks. ... View more

Hi Dan, Thanks for your reply.  Yes, I mean the last 2 bullet points contained in the 'Advantages of Empirical Bayesian Kriging' as found here https://pro.arcgis.com/en/pro-app/latest/help/analysis/geostatistical-analyst/what-is-empirical-bayesian-kriging-.htm . I am particularly interested in understanding what is referred to 'as small data set' and how EBK is more accurate than other kriging options when using 'small data sets'. How small is small, for example? Perhaps, looking at sampling density, etc?. It will be good to see (case) studies proving EBK's superior performance in a 'small data set' setting. I am just curious. I can't yet see such articles or demonstrations yet. Thanks a lot ... View more

This is an important issue. It is widely regarded that there is no significant difference between the 2 sensors in what the NDVIs should be given your context. However, research result in this area is not very consistent. Having said that, some factor that may complicate matters are the projection and preprocessing. You may need to be sure that these preprocessing follows same procedure and projections are accurate.  I have dropped below comments from this source which I think may help your decision in this regard.  https://www.researchgate.net/post/Is-it-possible-to-have-NDVI-equivalence-between-images-from-Landsat-5-and-Landsat-8 ... View more