[R-sig-Geo] [DKIM] Re: Interpolating snowfall values on a Digital Elevation Model [SEC=UNCLASSIFIED]

Tue Feb 20 23:08:39 CET 2018

The statement ‘the kriging functions in R still don't accept lat/long’ is incorrect. Please check the gstat and spm packages for details. When your data is collected from one utm, it is a good idea to project the data using utm. If the data is from two or more utms, you need to use different projection systems. The references provided demonstrated that the commonly used WGS84 is as good as relevant projection systems.

From: Dominik Schneider [mailto:dominik.schneider at colorado.edu]
Sent: Wednesday, 21 February 2018 5:02 AM
To: Li Jin
Cc: Stefano Sofia; r-sig-geo at r-project.org
Subject: Re: [DKIM] Re: [R-sig-Geo] Interpolating snowfall values on a Digital Elevation Model [SEC=UNCLASSIFIED]

The effects of spatial reference systems on interpolations and accuracy are minimal, and lat and long can be used.
Fair enough, thanks for sending the references. But, as far as I know, the kriging functions in R still don't accept lat/long.

On Mon, Feb 19, 2018 at 8:54 PM, Li Jin <Jin.Li at ga.gov.au<mailto:Jin.Li at ga.gov.au>> wrote:
The effects of spatial reference systems on interpolations and accuracy are minimal, and lat and long can be used. Please see the following studies for details.

Jiang, W., Li, J., 2013. Are Spatial Modelling Methods Sensitive to Spatial Reference Systems for Predicting Marine Environmental Variables, 20th International Congress on Modelling and Simulation: Adelaide, Australia, pp. 387-393.
Jiang, W., Li, J., 2014. The effects of spatial reference systems on the predictive accuracy of spatial interpolation methods. Record 2014/01. Geoscience Australia: Canberra, pp 33. http://dx.doi.org/10.11636/Record.2014.001.
Turner, A.J., Li, J., Jiang, W., 2017. Effects of Spatial Reference Systems on the Accuracy of Spatial Predictive Modelling along a Latitudinal Gradient, 22nd International Congress on Modelling and Simulation: Hobart, Tasmania, Australia, pp. 106-112.

-----Original Message-----
From: R-sig-Geo [mailto:r-sig-geo-bounces at r-project.org<mailto:r-sig-geo-bounces at r-project.org>] On Behalf Of Dominik Schneider
Sent: Wednesday, 14 February 2018 3:21 AM
To: Stefano Sofia
Cc: r-sig-geo at r-project.org<mailto:r-sig-geo at r-project.org>
Subject: [DKIM] Re: [R-sig-Geo] Interpolating snowfall values on a Digital Elevation Model

You can't use a lat/long coordinate system when kriging because the concept of distance is ambiguous. Convert all your data a UTM grid like you had in your first post and it should work.

Another note, It looks like you are working at 0.01 deg which is on the order of 1km resolution so you may find  other covariates such as aspect, slope, and wind sheltering/exposure, terrain roughness for estimating snow on the ground useful. see some of the earliest papers by Carroll, Cressie, and Elder.

Carroll, S. S., and N. Cressie (1996), A comparison of geostatistical methodologies used to estimate snow water equivalent, *JAWRA Journal of the American Water Resources Association*, *32*(2), 267–278, doi:10.1111/j.1752-1688.1996.tb03450.x.

Carroll, S. S., and N. Cressie (1997), Spatial modeling of snow water equivalent using covariances estimated from spatial and geomorphic attributes, *Journal of Hydrology*, *190*(1-2), 42–59.

Balk, B., and K. Elder (2000), Combining binary decision tree and geostatistical methods to estimate snow distribution in a mountain watershed, *Water Resources Research*, *36*(1), 13–26, doi:10.1029/1999WR900251.

Erxleben, J., K. Elder, and R. Davis (2002), Comparison of spatial interpolation methods for estimating snow distribution in the Colorado Rocky Mountains, *Hydrological Processes*, *16*(18), 3627–3649, doi:10.1002/hyp.1239.

Erickson, T. A., M. W. Williams, and A. Winstral (2005), Persistence of topographic controls on the spatial distribution of snow in rugged mountain terrain, Colorado, United States, *Water Resour. Res.*, *41*(4), W04014, doi:10.1029/2003WR002973.

On Tue, Feb 13, 2018 at 3:45 AM, Stefano Sofia < stefano.sofia at regione.marche.it<mailto:stefano.sofia at regione.marche.it>> wrote:

> Dear Daniel and list users,
> I tried to follow the instructions but I encountered two kinds of errors.
> This is a reproducibile code:
>
> ------------------------------------------------------------
> ---------------------------------------------------
> library(automap)
> library(ggplot2)
> library(gstat)
> library(raster)
> library(rasterVis)
> library(rgdal)
> library(maptools)
>
> ## LOADING DEM
> ita_DEM <- getData('alt', country='ITA', mask=TRUE)
> crs(ita_DEM) <- "+init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0"
> #ita_DEM <- as(ita_DEM, "SpatialGridDataFrame")
> str(ita_DEM)
>
> ## LOADING RAINFALL DATA
> rain_data <- data.frame(Cumulata=c(11.8, 9.0, 8.0, 36.6, 9.4),
> Long_Cent=c(12.61874, 12.78690, 12.96756, 13.15599, 13.28157),
> Lat_Cent=c(43.79447, 43.85185, 43.76267, 43.03470, 43.08003),
> Altitude=c(112.20, 42.93, 36.14, 747, 465))
>
> stations <- data.frame(rain_data$Long_Cent, rain_data$Lat_Cent)
> rain_data <- SpatialPointsDataFrame(stations, rain_data,
> proj4string=CRS("+init=epsg:4326"))
> stations <- SpatialPoints(stations,
> proj4string=CRS("+init=epsg:4326"))
>
> ## EXTRACT THE ELEVATION VALUES TO MY POINTS
> rain_data$ExtractedElevationValues <- extract(x=ita_DEM, y=stations)
>
> ## CREATE GRID FOR KRIGING OUTPUT
> minx <-  rain_data at bbox[1,1]
> maxx <- rain_data at bbox[1,2]
> miny <- rain_data at bbox[2,1]
> maxy <- rain_data at bbox[2,2]
> pixel <- 0.01
> grd <- expand.grid(x=seq(minx, maxx, by=pixel), y=seq(miny, maxy,
> by=pixel))
> coordinates(grd) <- ~x+y
> gridded(grd) <- TRUE
> proj4string(grd) <- CRS("+init=epsg:4326")
>
> ## KRIGING: autoKrige(YourMeasurements ~ YourExtractedElevationValues,
> YourMeasurementLocations, TargetGrid) OK_snow <- autoKrige(Cumulata ~
> rain_data$ExtractedElevationValues,
> rain_data, grd)
> ------------------------------------------------------------
> -------------------------------------------------------------------
>
> The error I get is:
> Error in autoKrige(Cumulata ~ rain_data$ExtractedElevationValues,
> rain_data,  :
>   Either input_data or new_data is in LongLat, please reproject.
>    input_data:  +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>    new_data:    +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>
> but I did pay attention to have the same reference system in
> rain_data, drg and the Digital Elevation Model.
>
> Moreover, if I impose the class of the DEM to SpatialGridDataFrame
> when I extraxt the elevation points from the DEM I get the following error:
> Error in (function (classes, fdef, mtable)  :
>   unable to find an inherited method for function ‘extract’ for
> signature ‘"SpatialGridDataFrame", "SpatialPoints"’
> Calls: extract -> <Anonymous>
>
>
> Would you please somebody help to show me where is my mistake?
>
> Thank you for all your attention
> Stefano
>
>          (oo)
> --oOO--( )--OOo----------------
> Stefano Sofia PhD
> Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> Protezione Civile - Regione Marche Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: stefano.sofia at regione.marche.it<mailto:stefano.sofia at regione.marche.it>
> ---Oo---------oO----------------
> ________________________________________
> Da: R-sig-Geo [r-sig-geo-bounces at r-project.org<mailto:r-sig-geo-bounces at r-project.org>] per conto di Daniel
> Knitter [knitter at geographie.uni-kiel.de<mailto:knitter at geographie.uni-kiel.de>]
> Inviato: lunedì 12 febbraio 2018 9.16
> A: r-sig-geo at r-project.org<mailto:r-sig-geo at r-project.org>
> Oggetto: Re: [R-sig-Geo]  Interpolating snowfall values on a Digital
> Elevation Model
>
> ...sorry, I missed one step: you need to extract the elevation values
> to your points via extract function from the raster package:
>
> YourPoints$YourExtractedElevationValues <- extract(x = DEM, y =
> YourPoints)
>
> autoKrige(YourMeasurements ~ YourExtractedElevationValues,
> YourMeasurementLocations, TargetGrid)
>
>
> Sorry for spamming.
>
> Best,
> Daniel
>
> On Mon, 12 Feb 2018 08:03:41 +0000
> Stefano Sofia <stefano.sofia at regione.marche.it<mailto:stefano.sofia at regione.marche.it>> wrote:
>
> > Dear list users,
> > I have to produce rainfall maps. I know how to create a
> > (bi-dimensional)
> grid and interpolate rainfall values (from automatic rain gauges) on
> that grid using Kriging:
> >
> > myinterpolation <- autoKrige(myrainfall_cumulate ~ 1, rain_data_UTM,
> mygrid)
> >
> > In reality I am dealing with snowfall values on mountain regions,
> > and in
> this case altitude is an important factor, the use of a Digital
> Elevation Model might make the difference.
> > Looking in the web I found some important material about accessing
> elevation data in R with the "elevatr" package (by J.W.Hollister), I
> am reading it.
> > My concern would then be to interpolate snowfall values on a Digital
> Elevation Model. Did somebody already use R for these kinds of
> calculations? Could somebody share with me some useful hints?
> >
> > Thank you for your attention
> > Stefano Sofia
> >
> >
> >          (oo)
> > --oOO--( )--OOo----------------
> > Stefano Sofia PhD
> > Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> > Protezione Civile - Regione Marche Via del Colle Ameno 5
> > 60126 Torrette di Ancona, Ancona
> > Uff: 071 806 7743
> > E-mail: stefano.sofia at regione.marche.it<mailto:stefano.sofia at regione.marche.it>
> > ---Oo---------oO----------------
> >
> > ________________________________
> >
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> --
>
> Dr. Daniel Knitter
> CRC1266 -- Scales of Transformation
> Project A2 "Integrative Modeling of Socio-Environmental Dynamics"
>
> Christian-Albrechts-Universität zu Kiel Department of Geography
> Physical Geography -- Landscape Ecology and Geoinformation
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>
> Phone: +49 431 880 2941
> Email: knitter at geographie.uni-kiel.de<mailto:knitter at geographie.uni-kiel.de>
>
> ________________________________
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