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

Tue Feb 20 19:02:23 CET 2018

>
> 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> 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] On Behalf Of
> Dominik Schneider
> Sent: Wednesday, 14 February 2018 3:21 AM
> To: Stefano Sofia
> Cc: 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> 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$ExtractedElevationValues,
> > rain_data,  :
> >   Either input_data or new_data is in LongLat, please reproject.
> >    input_data:  +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> > +ellps=WGS84 +towgs84=0,0,0
> >    new_data:    +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> > +ellps=WGS84 +towgs84=0,0,0
> >
> > but I did pay attention to have the same reference system in
> > rain_data, drg and the Digital Elevation Model.
> >
> > Moreover, if I impose the class of the DEM to SpatialGridDataFrame
> > when I extraxt the elevation points from the DEM I get the following
> error:
> > Error in (function (classes, fdef, mtable)  :
> >   unable to find an inherited method for function ‘extract’ for
> > signature ‘"SpatialGridDataFrame", "SpatialPoints"’
> > Calls: extract -> <Anonymous>
> >
> >
> > Would you please somebody help to show me where is my mistake?
> >
> > Thank you for all your attention
> > Stefano
> >
> >          (oo)
> > --oOO--( )--OOo----------------
> > Stefano Sofia PhD
> > Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> > Protezione Civile - Regione Marche Via del Colle Ameno 5
> > 60126 Torrette di Ancona, Ancona
> > Uff: 071 806 7743
> > E-mail: stefano.sofia at regione.marche.it
> > ---Oo---------oO----------------
> > ________________________________________
> > Da: R-sig-Geo [r-sig-geo-bounces at r-project.org] per conto di Daniel
> > Knitter [knitter at geographie.uni-kiel.de]
> > Inviato: lunedì 12 febbraio 2018 9.16
> > A: r-sig-geo at r-project.org
> > Oggetto: Re: [R-sig-Geo]  Interpolating snowfall values on a Digital
> > Elevation Model
> >
> > ...sorry, I missed one step: you need to extract the elevation values
> > to your points via extract function from the raster package:
> >
> > YourPoints$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> 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
> > > ---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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> >
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