Hi,
I have two variables, Temp (T) and Latitude (L). I have a DEM (E). I need to interpolate T from point shape file to each pixel of E.
the relation is as follow:
TE1,L1 = TE0,L0 - (E1-E0)*G - (L1-L0)*P
where, TE1,L1 = new interpolated raster value of each pixel
E0 = Elevation of temperature station
E1 = Elevation of new location, which will be each pixel of raster DEM
L0 = latitude of station
L1 = latitude of each pixel of DEM
G & P = constant values to multiply
here, I am looking for R code or method to do this in ArcGIS.
any clues are appreciated.
many thanks.
Hello Madan
you can convert all variables from vectors to rasters and apply your formula to raster calculator in arcgis
Hello Madan
you can convert all variables from vectors to rasters and apply your formula to raster calculator in arcgis
Hi Madan,
I would take the value of "G" as the lapse rate (~ 9.8 degrees per km) and the value of "P" as ~ 0.7 Kelvin per degree latitude change (Reference: http://dx.doi.org/10.1175/1520-0477(1999)0802.0.CO;2). See Figure 6b - Between 20 degrees South and 60 degrees South the slope is about 0.6 while from 20 deg North to 60 deg North the slope is about 0.8. For areas between 20 degrees and equator, the slope seems is zero.
I would still think that interpolating on latitude would not affect the results too much as elevation has higher effect on temperature than latitude.
I think this could then be implemented in ArcGIS Raster calculator or R.
T(E0,L0) => One Temperature value
E1 => Elevation Raster
E0 => One elevation value
G => constant
L1 => Latitude Raster
L0 => One Latitude value
P => constant
Hi Madan,
I'll assume you already took into account what was said by Sulochan Dhungel about lapse rate and selection of important variables.
I highly suggest you to read the following articles:
1) Geostatistical modeling of topography using auxiliary maps. DOI:10.1016/j.cageo.2008.01.005. http://www.sciencedirect.com/science/article/pii/S0098300408001106
2) About regression-kriging: From equations to case studies. DOI: 10.1016/j.cageo.2007.05.001. http://www.sciencedirect.com/science/article/pii/S0098300407001008
They discuss the use of Regression Kriging, which "is a spatial interpolation technique that combines a regression of the dependent variable on auxiliary variables (such as land surface parameters, remote sensing imagery and thematic maps) with simple kriging of the regression residuals. It is mathematically equivalent to the interpolation method variously called 'Universal Kriging' (UK) and 'Kriging with External Drift' (KED), where auxiliary predictors are used directly to solve the kriging weights" (Hengl et al., 2007)
In particular, the first article discuss the use of the gstat R package to carry out the interpolations.
More info:
a) Regression Kriging: http://spatial-analyst.net/book/system/files/Regressionkriging.pdf
b) A Practical Guide to Geostatistical Mapping. http://spatial-analyst.net/book/
IHTH
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