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

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

Li Jin
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:[hidden email]] On Behalf Of Dominik Schneider
Sent: Wednesday, 14 February 2018 3:21 AM
To: Stefano Sofia
Cc: [hidden email]
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 < [hidden email]> 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$ExtractedElevationValues <- extract(x=ita_DEM, y=stations)
>
> ## CREATE GRID FOR KRIGING OUTPUT
> minx <-  rain_data@bbox[1,1]
> maxx <- rain_data@bbox[1,2]
> miny <- rain_data@bbox[2,1]
> maxy <- rain_data@bbox[2,2]
> pixel <- 0.01
> grd <- expand.grid(x=seq(minx, maxx, by=pixel), y=seq(miny, maxy,
> by=pixel))
> coordinates(grd) <- ~x+y
> gridded(grd) <- TRUE
> proj4string(grd) <- CRS("+init=epsg:4326")
>
> ## KRIGING: autoKrige(YourMeasurements ~ YourExtractedElevationValues,
> YourMeasurementLocations, TargetGrid) OK_snow <- autoKrige(Cumulata ~
> rain_data$ExtractedElevationValues,
> rain_data, grd)
> ------------------------------------------------------------
> -------------------------------------------------------------------
>
> The error I get is:
> Error in autoKrige(Cumulata ~ rain_data$ExtractedElevationValues,
> rain_data,  :
>   Either input_data or new_data is in LongLat, please reproject.
>    input_data:  +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>    new_data:    +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>
> but I did pay attention to have the same reference system in
> rain_data, drg and the Digital Elevation Model.
>
> Moreover, if I impose the class of the DEM to SpatialGridDataFrame
> when I extraxt the elevation points from the DEM I get the following error:
> Error in (function (classes, fdef, mtable)  :
>   unable to find an inherited method for function ‘extract’ for
> signature ‘"SpatialGridDataFrame", "SpatialPoints"’
> Calls: extract -> <Anonymous>
>
>
> Would you please somebody help to show me where is my mistake?
>
> Thank you for all your attention
> Stefano
>
>          (oo)
> --oOO--( )--OOo----------------
> Stefano Sofia PhD
> Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> Protezione Civile - Regione Marche Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: [hidden email]
> ---Oo---------oO----------------
> ________________________________________
> Da: R-sig-Geo [[hidden email]] per conto di Daniel
> Knitter [[hidden email]]
> Inviato: lunedì 12 febbraio 2018 9.16
> A: [hidden email]
> Oggetto: Re: [R-sig-Geo]  Interpolating snowfall values on a Digital
> Elevation Model
>
> ...sorry, I missed one step: you need to extract the elevation values
> to your points via extract function from the raster package:
>
> YourPoints$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 <[hidden email]> 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: [hidden email]
> > ---Oo---------oO----------------
> >
> > ________________________________
> >
> > AVVISO IMPORTANTE: Questo messaggio di posta elettronica può
> > contenere
> informazioni confidenziali, pertanto è destinato solo a persone
> autorizzate alla ricezione. I messaggi di posta elettronica per i
> client di Regione Marche possono contenere informazioni confidenziali e con privilegi legali.
> Se non si è il destinatario specificato, non leggere, copiare,
> inoltrare o archiviare questo messaggio. Se si è ricevuto questo
> messaggio per errore, inoltrarlo al mittente ed eliminarlo
> completamente dal sistema del proprio computer. Ai sensi dell’art. 6
> della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> urgenza, la risposta al presente messaggio di posta elettronica può essere visionata da persone estranee al destinatario.
> > IMPORTANT NOTICE: This e-mail message is intended to be received
> > only by
> persons entitled to receive the confidential information it may contain.
> E-mail messages to clients of Regione Marche may contain information
> that is confidential and legally privileged. Please do not read, copy,
> forward, or store this message unless you are an intended recipient of
> it. If you have received this message in error, please forward it to
> the sender and delete it completely from your computer system.
> >
> > --
> > This message was scanned by Libra ESVA and is believed to be clean.
> >
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > [hidden email]
> > <a href="https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%">https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%
> 2Fmailman%2Flistinfo%2Fr-sig-geo&e=52342f8a&h=f7d4a649&f=y&p=y
>
>
> --
>
> 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
> Ludewig-Meyn-Str. 14, room 109 D - 24118 Kiel, Germany
>
> Phone: +49 431 880 2941
> Email: [hidden email]
>
> ________________________________
>
> AVVISO IMPORTANTE: Questo messaggio di posta elettronica può contenere
> informazioni confidenziali, pertanto è destinato solo a persone
> autorizzate alla ricezione. I messaggi di posta elettronica per i
> client di Regione Marche possono contenere informazioni confidenziali e con privilegi legali.
> Se non si è il destinatario specificato, non leggere, copiare,
> inoltrare o archiviare questo messaggio. Se si è ricevuto questo
> messaggio per errore, inoltrarlo al mittente ed eliminarlo
> completamente dal sistema del proprio computer. Ai sensi dell’art. 6
> della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> urgenza, la risposta al presente messaggio di posta elettronica può essere visionata da persone estranee al destinatario.
> IMPORTANT NOTICE: This e-mail message is intended to be received only
> by persons entitled to receive the confidential information it may contain.
> E-mail messages to clients of Regione Marche may contain information
> that is confidential and legally privileged. Please do not read, copy,
> forward, or store this message unless you are an intended recipient of
> it. If you have received this message in error, please forward it to
> the sender and delete it completely from your computer system.
>
> --
> This message was scanned by Libra ESVA and is believed to be clean.
>
> _______________________________________________
> R-sig-Geo mailing list
> [hidden email]
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>

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

dschneiderch
>
> 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 <[hidden email]> 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:[hidden email]] On Behalf Of
> Dominik Schneider
> Sent: Wednesday, 14 February 2018 3:21 AM
> To: Stefano Sofia
> Cc: [hidden email]
> 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 <
> [hidden email]> 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$ExtractedElevationValues <- extract(x=ita_DEM, y=stations)
> >
> > ## CREATE GRID FOR KRIGING OUTPUT
> > minx <-  rain_data@bbox[1,1]
> > maxx <- rain_data@bbox[1,2]
> > miny <- rain_data@bbox[2,1]
> > maxy <- rain_data@bbox[2,2]
> > pixel <- 0.01
> > grd <- expand.grid(x=seq(minx, maxx, by=pixel), y=seq(miny, maxy,
> > by=pixel))
> > coordinates(grd) <- ~x+y
> > gridded(grd) <- TRUE
> > proj4string(grd) <- CRS("+init=epsg:4326")
> >
> > ## KRIGING: autoKrige(YourMeasurements ~ YourExtractedElevationValues,
> > YourMeasurementLocations, TargetGrid) OK_snow <- autoKrige(Cumulata ~
> > rain_data$ExtractedElevationValues,
> > rain_data, grd)
> > ------------------------------------------------------------
> > -------------------------------------------------------------------
> >
> > The error I get is:
> > Error in autoKrige(Cumulata ~ rain_data$ExtractedElevationValues,
> > rain_data,  :
> >   Either input_data or new_data is in LongLat, please reproject.
> >    input_data:  +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> > +ellps=WGS84 +towgs84=0,0,0
> >    new_data:    +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> > +ellps=WGS84 +towgs84=0,0,0
> >
> > but I did pay attention to have the same reference system in
> > rain_data, drg and the Digital Elevation Model.
> >
> > Moreover, if I impose the class of the DEM to SpatialGridDataFrame
> > when I extraxt the elevation points from the DEM I get the following
> error:
> > Error in (function (classes, fdef, mtable)  :
> >   unable to find an inherited method for function ‘extract’ for
> > signature ‘"SpatialGridDataFrame", "SpatialPoints"’
> > Calls: extract -> <Anonymous>
> >
> >
> > Would you please somebody help to show me where is my mistake?
> >
> > Thank you for all your attention
> > Stefano
> >
> >          (oo)
> > --oOO--( )--OOo----------------
> > Stefano Sofia PhD
> > Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> > Protezione Civile - Regione Marche Via del Colle Ameno 5
> > 60126 Torrette di Ancona, Ancona
> > Uff: 071 806 7743
> > E-mail: [hidden email]
> > ---Oo---------oO----------------
> > ________________________________________
> > Da: R-sig-Geo [[hidden email]] per conto di Daniel
> > Knitter [[hidden email]]
> > Inviato: lunedì 12 febbraio 2018 9.16
> > A: [hidden email]
> > Oggetto: Re: [R-sig-Geo]  Interpolating snowfall values on a Digital
> > Elevation Model
> >
> > ...sorry, I missed one step: you need to extract the elevation values
> > to your points via extract function from the raster package:
> >
> > YourPoints$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 <[hidden email]> 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: [hidden email]
> > > ---Oo---------oO----------------
> > >
> > > ________________________________
> > >
> > > AVVISO IMPORTANTE: Questo messaggio di posta elettronica può
> > > contenere
> > informazioni confidenziali, pertanto è destinato solo a persone
> > autorizzate alla ricezione. I messaggi di posta elettronica per i
> > client di Regione Marche possono contenere informazioni confidenziali e
> con privilegi legali.
> > Se non si è il destinatario specificato, non leggere, copiare,
> > inoltrare o archiviare questo messaggio. Se si è ricevuto questo
> > messaggio per errore, inoltrarlo al mittente ed eliminarlo
> > completamente dal sistema del proprio computer. Ai sensi dell’art. 6
> > della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> > urgenza, la risposta al presente messaggio di posta elettronica può
> essere visionata da persone estranee al destinatario.
> > > IMPORTANT NOTICE: This e-mail message is intended to be received
> > > only by
> > persons entitled to receive the confidential information it may contain.
> > E-mail messages to clients of Regione Marche may contain information
> > that is confidential and legally privileged. Please do not read, copy,
> > forward, or store this message unless you are an intended recipient of
> > it. If you have received this message in error, please forward it to
> > the sender and delete it completely from your computer system.
> > >
> > > --
> > > This message was scanned by Libra ESVA and is believed to be clean.
> > >
> > >
> > >       [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > R-sig-Geo mailing list
> > > [hidden email]
> > > <a href="https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%">https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%
> > 2Fmailman%2Flistinfo%2Fr-sig-geo&e=52342f8a&h=f7d4a649&f=y&p=y
> >
> >
> > --
> >
> > 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
> > Ludewig-Meyn-Str. 14, room 109 D - 24118 Kiel, Germany
> >
> > Phone: +49 431 880 2941
> > Email: [hidden email]
> >
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Re: [DKIM] Re: Interpolating snowfall values on a Digital Elevation Model [SEC=UNCLASSIFIED]

Li Jin
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:[hidden email]]
Sent: Wednesday, 21 February 2018 5:02 AM
To: Li Jin
Cc: Stefano Sofia; [hidden email]
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 <[hidden email]<mailto:[hidden email]>> 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:[hidden email]<mailto:[hidden email]>] On Behalf Of Dominik Schneider
Sent: Wednesday, 14 February 2018 3:21 AM
To: Stefano Sofia
Cc: [hidden email]<mailto:[hidden email]>
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 < [hidden email]<mailto:[hidden email]>> 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$ExtractedElevationValues <- extract(x=ita_DEM, y=stations)
>
> ## CREATE GRID FOR KRIGING OUTPUT
> minx <-  rain_data@bbox[1,1]
> maxx <- rain_data@bbox[1,2]
> miny <- rain_data@bbox[2,1]
> maxy <- rain_data@bbox[2,2]
> pixel <- 0.01
> grd <- expand.grid(x=seq(minx, maxx, by=pixel), y=seq(miny, maxy,
> by=pixel))
> coordinates(grd) <- ~x+y
> gridded(grd) <- TRUE
> proj4string(grd) <- CRS("+init=epsg:4326")
>
> ## KRIGING: autoKrige(YourMeasurements ~ YourExtractedElevationValues,
> YourMeasurementLocations, TargetGrid) OK_snow <- autoKrige(Cumulata ~
> rain_data$ExtractedElevationValues,
> rain_data, grd)
> ------------------------------------------------------------
> -------------------------------------------------------------------
>
> The error I get is:
> Error in autoKrige(Cumulata ~ rain_data$ExtractedElevationValues,
> rain_data,  :
>   Either input_data or new_data is in LongLat, please reproject.
>    input_data:  +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>    new_data:    +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>
> but I did pay attention to have the same reference system in
> rain_data, drg and the Digital Elevation Model.
>
> Moreover, if I impose the class of the DEM to SpatialGridDataFrame
> when I extraxt the elevation points from the DEM I get the following error:
> Error in (function (classes, fdef, mtable)  :
>   unable to find an inherited method for function ‘extract’ for
> signature ‘"SpatialGridDataFrame", "SpatialPoints"’
> Calls: extract -> <Anonymous>
>
>
> Would you please somebody help to show me where is my mistake?
>
> Thank you for all your attention
> Stefano
>
>          (oo)
> --oOO--( )--OOo----------------
> Stefano Sofia PhD
> Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> Protezione Civile - Regione Marche Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: [hidden email]<mailto:[hidden email]>
> ---Oo---------oO----------------
> ________________________________________
> Da: R-sig-Geo [[hidden email]<mailto:[hidden email]>] per conto di Daniel
> Knitter [[hidden email]<mailto:[hidden email]>]
> Inviato: lunedì 12 febbraio 2018 9.16
> A: [hidden email]<mailto:[hidden email]>
> Oggetto: Re: [R-sig-Geo]  Interpolating snowfall values on a Digital
> Elevation Model
>
> ...sorry, I missed one step: you need to extract the elevation values
> to your points via extract function from the raster package:
>
> YourPoints$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 <[hidden email]<mailto:[hidden email]>> 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: [hidden email]<mailto:[hidden email]>
> > ---Oo---------oO----------------
> >
> > ________________________________
> >
> > AVVISO IMPORTANTE: Questo messaggio di posta elettronica può
> > contenere
> informazioni confidenziali, pertanto è destinato solo a persone
> autorizzate alla ricezione. I messaggi di posta elettronica per i
> client di Regione Marche possono contenere informazioni confidenziali e con privilegi legali.
> Se non si è il destinatario specificato, non leggere, copiare,
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> messaggio per errore, inoltrarlo al mittente ed eliminarlo
> completamente dal sistema del proprio computer. Ai sensi dell’art. 6
> della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> urgenza, la risposta al presente messaggio di posta elettronica può essere visionata da persone estranee al destinatario.
> > IMPORTANT NOTICE: This e-mail message is intended to be received
> > only by
> persons entitled to receive the confidential information it may contain.
> E-mail messages to clients of Regione Marche may contain information
> that is confidential and legally privileged. Please do not read, copy,
> forward, or store this message unless you are an intended recipient of
> it. If you have received this message in error, please forward it to
> the sender and delete it completely from your computer system.
> >
> > --
> > This message was scanned by Libra ESVA and is believed to be clean.
> >
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > [hidden email]<mailto:[hidden email]>
> > <a href="https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%">https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%<https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%25>
> 2Fmailman%2Flistinfo%2Fr-sig-geo&e=52342f8a&h=f7d4a649&f=y&p=y
>
>
> --
>
> 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
> Ludewig-Meyn-Str. 14, room 109 D - 24118 Kiel, Germany
>
> Phone: +49 431 880 2941
> Email: [hidden email]<mailto:[hidden email]>
>
> ________________________________
>
> AVVISO IMPORTANTE: Questo messaggio di posta elettronica può contenere
> informazioni confidenziali, pertanto è destinato solo a persone
> autorizzate alla ricezione. I messaggi di posta elettronica per i
> client di Regione Marche possono contenere informazioni confidenziali e con privilegi legali.
> Se non si è il destinatario specificato, non leggere, copiare,
> inoltrare o archiviare questo messaggio. Se si è ricevuto questo
> messaggio per errore, inoltrarlo al mittente ed eliminarlo
> completamente dal sistema del proprio computer. Ai sensi dell’art. 6
> della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> urgenza, la risposta al presente messaggio di posta elettronica può essere visionata da persone estranee al destinatario.
> IMPORTANT NOTICE: This e-mail message is intended to be received only
> by persons entitled to receive the confidential information it may contain.
> E-mail messages to clients of Regione Marche may contain information
> that is confidential and legally privileged. Please do not read, copy,
> forward, or store this message unless you are an intended recipient of
> it. If you have received this message in error, please forward it to
> the sender and delete it completely from your computer system.
>
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Re: [DKIM] Re: Interpolating snowfall values on a Digital Elevation Model [SEC=UNCLASSIFIED]

Michael Sumner-2
Some thoughts.


On Wed, 21 Feb 2018 at 09:09 Li Jin <[hidden email]> wrote:

> 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:[hidden email]]
> Sent: Wednesday, 21 February 2018 5:02 AM
> To: Li Jin
> Cc: Stefano Sofia; [hidden email]
> 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.
>
>
>

Any such advice is completely dependent on the study area, and the goals of
the study. UTM is really bad advice generally, it's just a simplistic
system we've inherited and is used way too much, a self-fulfilling
prophecy. Whether standard tools should or shouldn't accept data as given
is a crux philosophical point, no tool in R is smart enough to know whether
it's "correct enough" to assume one way or another. You can't assume any
measurement represents reality in any projection, it depends how far, how
much, how large - you can't traverse from local neighbourhood scales to
continental, for example - you'd make different choices regarding
compromises at *some such point*.

Please don't ever advise use of UTM without specific caveats about the
scope and extent of the research - which is impossible in general - learn
to use map projections with the compromises they entail, there's nothing
stopping creating a local new one, from any of the main families with
PROJ.4, and with many variants of compromises on area, length, shape and
scale.

I tend not to say anything about this topic in this environment, but this
time the back and forth is particularly misleading IMO.

We actually have the worst of worlds at the moment, with many softwares
opinionatedly preventing one from making educational mistakes. There's no
real authority, lots of opinion and habit. lots of exploration but not
enough pushing and argument - I advise keeping an open mind and exploring
deeply.

Cheers, Mike.

>
> On Mon, Feb 19, 2018 at 8:54 PM, Li Jin <[hidden email]<mailto:
> [hidden email]>> 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:[hidden email]<mailto:
> [hidden email]>] On Behalf Of Dominik Schneider
> Sent: Wednesday, 14 February 2018 3:21 AM
> To: Stefano Sofia
> Cc: [hidden email]<mailto:[hidden email]>
> 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 <
> [hidden email]<mailto:[hidden email]>>
> 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$ExtractedElevationValues <- extract(x=ita_DEM, y=stations)
> >
> > ## CREATE GRID FOR KRIGING OUTPUT
> > minx <-  rain_data@bbox[1,1]
> > maxx <- rain_data@bbox[1,2]
> > miny <- rain_data@bbox[2,1]
> > maxy <- rain_data@bbox[2,2]
> > pixel <- 0.01
> > grd <- expand.grid(x=seq(minx, maxx, by=pixel), y=seq(miny, maxy,
> > by=pixel))
> > coordinates(grd) <- ~x+y
> > gridded(grd) <- TRUE
> > proj4string(grd) <- CRS("+init=epsg:4326")
> >
> > ## KRIGING: autoKrige(YourMeasurements ~ YourExtractedElevationValues,
> > YourMeasurementLocations, TargetGrid) OK_snow <- autoKrige(Cumulata ~
> > rain_data$ExtractedElevationValues,
> > rain_data, grd)
> > ------------------------------------------------------------
> > -------------------------------------------------------------------
> >
> > The error I get is:
> > Error in autoKrige(Cumulata ~ rain_data$ExtractedElevationValues,
> > rain_data,  :
> >   Either input_data or new_data is in LongLat, please reproject.
> >    input_data:  +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> > +ellps=WGS84 +towgs84=0,0,0
> >    new_data:    +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> > +ellps=WGS84 +towgs84=0,0,0
> >
> > but I did pay attention to have the same reference system in
> > rain_data, drg and the Digital Elevation Model.
> >
> > Moreover, if I impose the class of the DEM to SpatialGridDataFrame
> > when I extraxt the elevation points from the DEM I get the following
> error:
> > Error in (function (classes, fdef, mtable)  :
> >   unable to find an inherited method for function ‘extract’ for
> > signature ‘"SpatialGridDataFrame", "SpatialPoints"’
> > Calls: extract -> <Anonymous>
> >
> >
> > Would you please somebody help to show me where is my mistake?
> >
> > Thank you for all your attention
> > Stefano
> >
> >          (oo)
> > --oOO--( )--OOo-------------
> <https://maps.google.com/?q=--oOO--(+)--OOo-------------&entry=gmail&source=g>
> ---
> > Stefano Sofia PhD
> > Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> > Protezione Civile - Regione Marche Via del Colle Ameno 5
> > 60126 Torrette di Ancona, Ancona
> > Uff: 071 806 7743
> > E-mail: [hidden email]<mailto:
> [hidden email]>
> > ---Oo---------oO----------------
> > ________________________________________
> > Da: R-sig-Geo [[hidden email]<mailto:
> [hidden email]>] per conto di Daniel
> > Knitter [[hidden email]<mailto:
> [hidden email]>]
> > Inviato: lunedì 12 febbraio 2018 9.16
> > A: [hidden email]<mailto:[hidden email]>
> > Oggetto: Re: [R-sig-Geo]  Interpolating snowfall values on a Digital
> > Elevation Model
> >
> > ...sorry, I missed one step: you need to extract the elevation values
> > to your points via extract function from the raster package:
> >
> > YourPoints$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 <[hidden email]<mailto:
> [hidden email]>> 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
> <https://maps.google.com/?q=somebody+share+with+me+some&entry=gmail&source=g>
> 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: [hidden email]<mailto:
> [hidden email]>
> > > ---Oo---------oO----------------
> > >
> > > ________________________________
> > >
> > > AVVISO IMPORTANTE: Questo messaggio di posta elettronica può
> > > contenere
> > informazioni confidenziali, pertanto è destinato solo a persone
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> > urgenza, la risposta al presente messaggio di posta elettronica può
> essere visionata da persone estranee al destinatario.
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> > that is confidential and legally privileged. Please do not read, copy,
> > forward, or store this message unless you are an intended recipient of
> > it. If you have received this message in error, please forward it to
> > the sender and delete it completely from your computer system.
> > >
> > > --
> > > This message was scanned by Libra ESVA and is believed to be clean.
> > >
> > >
> > >       [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > R-sig-Geo mailing list
> > > [hidden email]<mailto:[hidden email]>
> > > <a href="https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%">https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%<
> https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%25>
> > 2Fmailman%2Flistinfo%2Fr-sig-geo&e=52342f8a&h=f7d4a649&f=y&p=y
> >
> >
> > --
> >
> > 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
> > Ludewig-Meyn-Str. 14, room 109 D - 24118 Kiel, Germany
> >
> > Phone: +49 431 880 2941 <+49%20431%208802941>
> > Email: [hidden email]<mailto:
> [hidden email]>
> >
> > ________________________________
> >
> > AVVISO IMPORTANTE: Questo messaggio di posta elettronica può contenere
> > informazioni confidenziali, pertanto è destinato solo a persone
> > autorizzate alla ricezione. I messaggi di posta elettronica per i
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> con privilegi legali.
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> > messaggio per errore, inoltrarlo al mittente ed eliminarlo
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> > della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> > urgenza, la risposta al presente messaggio di posta elettronica può
> essere visionata da persone estranee al destinatario.
> > IMPORTANT NOTICE: This e-mail message is intended to be received only
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> contain.
> > E-mail messages to clients of Regione Marche may contain information
> > that is confidential and legally privileged. Please do not read, copy,
> > forward, or store this message unless you are an intended recipient of
> > it. If you have received this message in error, please forward it to
> > the sender and delete it completely from your computer system.
> >
> > --
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> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > [hidden email]<mailto:[hidden email]>
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>
>         [[alternative HTML version deleted]]
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Re: [DKIM] Re: [DKIM] Re: Interpolating snowfall values on a Digital Elevation Model [SEC=UNCLASSIFIED]

Li Jin
In reply to this post by Li Jin
Agreed, Michael. Please the refs provided for some demonstrations at a latitudinal gradient.

From: Michael Sumner [mailto:[hidden email]]
Sent: Thursday, 22 February 2018 11:26 PM
To: Li Jin
Cc: Dominik Schneider; [hidden email]
Subject: [DKIM] Re: [R-sig-Geo] [DKIM] Re: Interpolating snowfall values on a Digital Elevation Model [SEC=UNCLASSIFIED]

Some thoughts.


On Wed, 21 Feb 2018 at 09:09 Li Jin <[hidden email]<mailto:[hidden email]>> wrote:
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:[hidden email]<mailto:[hidden email]>]
Sent: Wednesday, 21 February 2018 5:02 AM
To: Li Jin
Cc: Stefano Sofia; [hidden email]<mailto:[hidden email]>
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.



Any such advice is completely dependent on the study area, and the goals of the study. UTM is really bad advice generally, it's just a simplistic system we've inherited and is used way too much, a self-fulfilling prophecy. Whether standard tools should or shouldn't accept data as given is a crux philosophical point, no tool in R is smart enough to know whether it's "correct enough" to assume one way or another. You can't assume any measurement represents reality in any projection, it depends how far, how much, how large - you can't traverse from local neighbourhood scales to continental, for example - you'd make different choices regarding compromises at *some such point*.

Please don't ever advise use of UTM without specific caveats about the scope and extent of the research - which is impossible in general - learn to use map projections with the compromises they entail, there's nothing stopping creating a local new one, from any of the main families with PROJ.4, and with many variants of compromises on area, length, shape and scale.

I tend not to say anything about this topic in this environment, but this time the back and forth is particularly misleading IMO.

We actually have the worst of worlds at the moment, with many softwares opinionatedly preventing one from making educational mistakes. There's no real authority, lots of opinion and habit. lots of exploration but not enough pushing and argument - I advise keeping an open mind and exploring deeply.

Cheers, Mike.

On Mon, Feb 19, 2018 at 8:54 PM, Li Jin <[hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>> 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:[hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>] On Behalf Of Dominik Schneider
Sent: Wednesday, 14 February 2018 3:21 AM
To: Stefano Sofia
Cc: [hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>
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 < [hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>> 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$ExtractedElevationValues <- extract(x=ita_DEM, y=stations)
>
> ## CREATE GRID FOR KRIGING OUTPUT
> minx <-  rain_data@bbox[1,1]
> maxx <- rain_data@bbox[1,2]
> miny <- rain_data@bbox[2,1]
> maxy <- rain_data@bbox[2,2]
> pixel <- 0.01
> grd <- expand.grid(x=seq(minx, maxx, by=pixel), y=seq(miny, maxy,
> by=pixel))
> coordinates(grd) <- ~x+y
> gridded(grd) <- TRUE
> proj4string(grd) <- CRS("+init=epsg:4326")
>
> ## KRIGING: autoKrige(YourMeasurements ~ YourExtractedElevationValues,
> YourMeasurementLocations, TargetGrid) OK_snow <- autoKrige(Cumulata ~
> rain_data$ExtractedElevationValues,
> rain_data, grd)
> ------------------------------------------------------------
> -------------------------------------------------------------------
>
> The error I get is:
> Error in autoKrige(Cumulata ~ rain_data$ExtractedElevationValues,
> rain_data,  :
>   Either input_data or new_data is in LongLat, please reproject.
>    input_data:  +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>    new_data:    +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs
> +ellps=WGS84 +towgs84=0,0,0
>
> but I did pay attention to have the same reference system in
> rain_data, drg and the Digital Elevation Model.
>
> Moreover, if I impose the class of the DEM to SpatialGridDataFrame
> when I extraxt the elevation points from the DEM I get the following error:
> Error in (function (classes, fdef, mtable)  :
>   unable to find an inherited method for function ‘extract’ for
> signature ‘"SpatialGridDataFrame", "SpatialPoints"’
> Calls: extract -> <Anonymous>
>
>
> Would you please somebody help to show me where is my mistake?
>
> Thank you for all your attention
> Stefano
>
>          (oo)
> --oOO--( )--OOo-------------<https://maps.google.com/?q=--oOO--(+)--OOo-------------&entry=gmail&source=g>---
> Stefano Sofia PhD
> Area Meteorologica e  Area nivologica - Centro Funzionale Servizio
> Protezione Civile - Regione Marche Via del Colle Ameno 5
> 60126 Torrette di Ancona, Ancona
> Uff: 071 806 7743
> E-mail: [hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>
> ---Oo---------oO----------------
> ________________________________________
> Da: R-sig-Geo [[hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>] per conto di Daniel
> Knitter [[hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>]
> Inviato: lunedì 12 febbraio 2018 9.16
> A: [hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>
> Oggetto: Re: [R-sig-Geo]  Interpolating snowfall values on a Digital
> Elevation Model
>
> ...sorry, I missed one step: you need to extract the elevation values
> to your points via extract function from the raster package:
>
> YourPoints$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 <[hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>> 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<https://maps.google.com/?q=somebody+share+with+me+some&entry=gmail&source=g> 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: [hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>
> > ---Oo---------oO----------------
> >
> > ________________________________
> >
> > AVVISO IMPORTANTE: Questo messaggio di posta elettronica può
> > contenere
> informazioni confidenziali, pertanto è destinato solo a persone
> autorizzate alla ricezione. I messaggi di posta elettronica per i
> client di Regione Marche possono contenere informazioni confidenziali e con privilegi legali.
> Se non si è il destinatario specificato, non leggere, copiare,
> inoltrare o archiviare questo messaggio. Se si è ricevuto questo
> messaggio per errore, inoltrarlo al mittente ed eliminarlo
> completamente dal sistema del proprio computer. Ai sensi dell’art. 6
> della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> urgenza, la risposta al presente messaggio di posta elettronica può essere visionata da persone estranee al destinatario.
> > IMPORTANT NOTICE: This e-mail message is intended to be received
> > only by
> persons entitled to receive the confidential information it may contain.
> E-mail messages to clients of Regione Marche may contain information
> that is confidential and legally privileged. Please do not read, copy,
> forward, or store this message unless you are an intended recipient of
> it. If you have received this message in error, please forward it to
> the sender and delete it completely from your computer system.
> >
> > --
> > This message was scanned by Libra ESVA and is believed to be clean.
> >
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > [hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>
> > <a href="https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%">https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%<https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%25><https://urlsand.esvalabs.com/?u=https%3A%2F%2Fstat.ethz.ch%25>
> 2Fmailman%2Flistinfo%2Fr-sig-geo&e=52342f8a&h=f7d4a649&f=y&p=y
>
>
> --
>
> 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
> Ludewig-Meyn-Str. 14, room 109 D - 24118 Kiel, Germany
>
> Phone: +49 431 880 2941<tel:+49%20431%208802941>
> Email: [hidden email]<mailto:[hidden email]><mailto:[hidden email]<mailto:[hidden email]>>
>
> ________________________________
>
> AVVISO IMPORTANTE: Questo messaggio di posta elettronica può contenere
> informazioni confidenziali, pertanto è destinato solo a persone
> autorizzate alla ricezione. I messaggi di posta elettronica per i
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> Se non si è il destinatario specificato, non leggere, copiare,
> inoltrare o archiviare questo messaggio. Se si è ricevuto questo
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> della DGR n. 1394/2008 si segnala che, in caso di necessità ed
> urgenza, la risposta al presente messaggio di posta elettronica può essere visionata da persone estranee al destinatario.
> IMPORTANT NOTICE: This e-mail message is intended to be received only
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