diff --git a/.gitignore b/.gitignore
index 807ea25..f860853 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,15 @@
.Rproj.user
.Rhistory
.RData
+ESP2_msk_alt.grd
+ESP2_msk_alt.gri
+ESP2_msk_alt.vrt
+ESP_msk_alt.grd
+ESP_msk_alt.gri
+ESP_msk_alt.vrt
+occs.dbf
+occs.prj
+occs.shp
+occs.shx
+wc10
+GISwithR-figure
diff --git a/GISwithR.Rmd b/GISwithR.Rmd
new file mode 100644
index 0000000..e975ab6
--- /dev/null
+++ b/GISwithR.Rmd
@@ -0,0 +1,234 @@
+GIS with R: slides for the unconverted
+========================================================
+author: Francisco Rodriguez-Sanchez
+date: @frod_san
+2015-11-14
+
+
+R: not only for stats
+=====================
+
+![](images/R.jpg)
+
+
+R can make beautiful maps
+=========================
+type: section
+
+
+
+Made in R
+==========
+
+![](images/bike_ggplot.png)
+
+http://spatial.ly/2012/02/great-maps-ggplot2/
+
+
+Made in R
+=========
+
+![](images/facebook_map.png)
+
+http://paulbutler.org/archives/visualizing-facebook-friends/
+
+
+Made in R
+=========
+
+![](images/airMadrid_stamen.png)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+Made in R
+=========
+
+![](images/cft.png)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+Made in R
+=========
+
+![](images/vLine.svg)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+And it's very easy!
+===================
+type: section
+
+
+Map species occurrences in 2 lines of code
+==========================================
+
+```{r echo=FALSE}
+library(knitr)
+library(dismo)
+data(acaule)
+acaule <- acaule[acaule$continent == "South America", ]
+acaule <- acaule[!is.na(acaule$lat) | !is.na(acaule$lon), ]
+acaule <- subset(acaule, select = c("species", "lon", "lat"))
+crs.geo <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84")
+occs <- acaule
+acaule.sp <- acaule
+coordinates(acaule.sp) <- c("lon", "lat")
+crs(acaule.sp) <- crs.geo
+occdata <- Mercator(acaule.sp)
+```
+
+```{r fig.keep = "last"}
+plot(gmap(occdata, type = "satellite"))
+points(occdata, col = "red", pch=20, cex = 2)
+```
+
+
+
+Let's go step by step
+=====================
+type: section
+
+
+A dataframe of species occurrences
+==================================
+
+```{r echo=FALSE}
+kable(head(occs))
+```
+
+
+Make it a spatial object
+========================
+
+```{r}
+coordinates(occs) <- c("lon", "lat")
+str(occs, 2)
+```
+
+
+Specify projection (CRS)
+========================
+
+```{r}
+crs(occs) <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84")
+```
+
+See http://spatialreference.org
+
+
+Project to Mercator and plot
+============================
+
+```{r fig.keep = "last"}
+plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+```
+
+
+Alternatively, load shapefile
+=============================
+
+```{r echo = FALSE}
+shapefile(occs, filename = "occs.shp", overwrite = TRUE)
+```
+
+```{r fig.keep = "last"}
+occs <- shapefile("occs.shp")
+plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+```
+
+
+Using ggmap
+===========
+
+```{r eval=TRUE}
+library(ggmap)
+map <- get_map(bbox(occs), maptype = "watercolor", source = "stamen")
+ggmap(map) +
+ geom_point(aes(x = coords.x1, y = coords.x2), data = as.data.frame(coordinates(occs)),
+ colour = "red", size = 4)
+```
+
+
+Raster data
+===========
+type: section
+
+
+Download elevation data
+==========================
+
+```{r}
+elevation <- getData("alt", country = "ESP")
+```
+
+```{r}
+library(rasterVis)
+levelplot(elevation)
+```
+
+
+
+Dynamic interactive maps with leaflet
+=====================================
+
+```{r}
+library(mapview)
+mapView(occs)
+```
+
+
+
+Remote sensing growing fast
+===========================
+
+e.g. RStoolbox
+
+![](images/rstoolbox.png)
+
+
+Doing GIS in R: main advantages
+===============================
+incremental: true
+
+- Fully-reproducible scripts
+
+- **Harness all R stats power**
+
+ - Data wrangling
+
+ - Modelling
+
+ - Dataviz
+
+- Easy!
+
+
+
+
+Calling GIS from R
+==================
+
+- Grass: [`spgrass6`](http://www.rdocumentation.org/packages/spgrass6)
+- SAGA: [`RSAGA`](http://www.rdocumentation.org/packages/RSAGA)
+- ArcGIS: https://github.com/R-ArcGIS
+![](images/R_ArcGis.png)
+
+Includes calling R from ArcGIS too
+
+
+
+
+To read more
+============
+
+http://pakillo.github.io/R-GIS-tutorial
+
+
+
+
+
diff --git a/GISwithR.Rpres b/GISwithR.Rpres
new file mode 100644
index 0000000..e975ab6
--- /dev/null
+++ b/GISwithR.Rpres
@@ -0,0 +1,234 @@
+GIS with R: slides for the unconverted
+========================================================
+author: Francisco Rodriguez-Sanchez
+date: @frod_san
+2015-11-14
+
+
+R: not only for stats
+=====================
+
+![](images/R.jpg)
+
+
+R can make beautiful maps
+=========================
+type: section
+
+
+
+Made in R
+==========
+
+![](images/bike_ggplot.png)
+
+http://spatial.ly/2012/02/great-maps-ggplot2/
+
+
+Made in R
+=========
+
+![](images/facebook_map.png)
+
+http://paulbutler.org/archives/visualizing-facebook-friends/
+
+
+Made in R
+=========
+
+![](images/airMadrid_stamen.png)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+Made in R
+=========
+
+![](images/cft.png)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+Made in R
+=========
+
+![](images/vLine.svg)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+And it's very easy!
+===================
+type: section
+
+
+Map species occurrences in 2 lines of code
+==========================================
+
+```{r echo=FALSE}
+library(knitr)
+library(dismo)
+data(acaule)
+acaule <- acaule[acaule$continent == "South America", ]
+acaule <- acaule[!is.na(acaule$lat) | !is.na(acaule$lon), ]
+acaule <- subset(acaule, select = c("species", "lon", "lat"))
+crs.geo <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84")
+occs <- acaule
+acaule.sp <- acaule
+coordinates(acaule.sp) <- c("lon", "lat")
+crs(acaule.sp) <- crs.geo
+occdata <- Mercator(acaule.sp)
+```
+
+```{r fig.keep = "last"}
+plot(gmap(occdata, type = "satellite"))
+points(occdata, col = "red", pch=20, cex = 2)
+```
+
+
+
+Let's go step by step
+=====================
+type: section
+
+
+A dataframe of species occurrences
+==================================
+
+```{r echo=FALSE}
+kable(head(occs))
+```
+
+
+Make it a spatial object
+========================
+
+```{r}
+coordinates(occs) <- c("lon", "lat")
+str(occs, 2)
+```
+
+
+Specify projection (CRS)
+========================
+
+```{r}
+crs(occs) <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84")
+```
+
+See http://spatialreference.org
+
+
+Project to Mercator and plot
+============================
+
+```{r fig.keep = "last"}
+plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+```
+
+
+Alternatively, load shapefile
+=============================
+
+```{r echo = FALSE}
+shapefile(occs, filename = "occs.shp", overwrite = TRUE)
+```
+
+```{r fig.keep = "last"}
+occs <- shapefile("occs.shp")
+plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+```
+
+
+Using ggmap
+===========
+
+```{r eval=TRUE}
+library(ggmap)
+map <- get_map(bbox(occs), maptype = "watercolor", source = "stamen")
+ggmap(map) +
+ geom_point(aes(x = coords.x1, y = coords.x2), data = as.data.frame(coordinates(occs)),
+ colour = "red", size = 4)
+```
+
+
+Raster data
+===========
+type: section
+
+
+Download elevation data
+==========================
+
+```{r}
+elevation <- getData("alt", country = "ESP")
+```
+
+```{r}
+library(rasterVis)
+levelplot(elevation)
+```
+
+
+
+Dynamic interactive maps with leaflet
+=====================================
+
+```{r}
+library(mapview)
+mapView(occs)
+```
+
+
+
+Remote sensing growing fast
+===========================
+
+e.g. RStoolbox
+
+![](images/rstoolbox.png)
+
+
+Doing GIS in R: main advantages
+===============================
+incremental: true
+
+- Fully-reproducible scripts
+
+- **Harness all R stats power**
+
+ - Data wrangling
+
+ - Modelling
+
+ - Dataviz
+
+- Easy!
+
+
+
+
+Calling GIS from R
+==================
+
+- Grass: [`spgrass6`](http://www.rdocumentation.org/packages/spgrass6)
+- SAGA: [`RSAGA`](http://www.rdocumentation.org/packages/RSAGA)
+- ArcGIS: https://github.com/R-ArcGIS
+![](images/R_ArcGis.png)
+
+Includes calling R from ArcGIS too
+
+
+
+
+To read more
+============
+
+http://pakillo.github.io/R-GIS-tutorial
+
+
+
+
+
diff --git a/GISwithR.html b/GISwithR.html
new file mode 100644
index 0000000..316e094
--- /dev/null
+++ b/GISwithR.html
@@ -0,0 +1,1201 @@
+
+
+
+
+
+ GIS with R: slides for the unconverted
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+GIS with R: slides for the unconverted
Francisco Rodriguez-Sanchez
@frod_san
+
+
+
+
+
+R: not only for stats
+
+
+
+
+
+
+
+R can make beautiful maps
+
+
+
+
+
+
+
+
+
+
+
+And it's very easy!
+
+
+
+
+
+
+Map species occurrences in 2 lines of code
+
+
plot(gmap(occdata, type = "satellite"))
+points(occdata, col = "red", pch=20, cex = 2)
+
+
+
+
+
+
+
+
+Let's go step by step
+
+
+
+
+
+
+A dataframe of species occurrences
+
+
+
+ |
+species |
+lon |
+lat |
+
+
+
+1 |
+Solanum acaule Bitter |
+-66.10 |
+-21.90 |
+
+
+2 |
+Solanum acaule Bitter |
+-71.00 |
+-13.50 |
+
+
+52 |
+Solanum acaule Bitter |
+-66.43 |
+-24.22 |
+
+
+53 |
+Solanum acaule Bitter |
+-72.07 |
+-13.35 |
+
+
+54 |
+Solanum acaule Bitter |
+-68.97 |
+-15.23 |
+
+
+55 |
+Solanum acaule Bitter |
+-64.95 |
+-17.75 |
+
+
+
+
+
+
+
+Make it a spatial object
+
+
coordinates(occs) <- c("lon", "lat")
+str(occs, 2)
+
+
+
Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots
+ ..@ data :'data.frame': 49 obs. of 1 variable:
+ ..@ coords.nrs : int [1:2] 2 3
+ ..@ coords : num [1:49, 1:2] -66.1 -71 -66.4 -72.1 -69 ...
+ .. ..- attr(*, "dimnames")=List of 2
+ ..@ bbox : num [1:2, 1:2] -72.5 -24.2 -64.7 -12.5
+ .. ..- attr(*, "dimnames")=List of 2
+ ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
+
+
+
+
+
+
+
+Project to Mercator and plot
+
+
plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+
+
+
+
+
+
+
+
+Alternatively, load shapefile
+
+
occs <- shapefile("occs.shp")
+plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+
+
+
+
+
+
+
+
+Using ggmap
+
+
library(ggmap)
+map <- get_map(bbox(occs), maptype = "watercolor", source = "stamen")
+ggmap(map) +
+ geom_point(aes(x = coords.x1, y = coords.x2), data = as.data.frame(coordinates(occs)),
+ colour = "red", size = 4)
+
+
+
+
+
+
+
+
+
+Download elevation data
+
+
elevation <- getData("alt", country = "ESP")
+
+
+
library(rasterVis)
+levelplot(elevation)
+
+
+
+
+
+
+
+
+Dynamic interactive maps with leaflet
+
+
library(mapview)
+mapView(occs)
+
+
+
+
+
+
+Remote sensing growing fast
+
+
e.g. RStoolbox
+
+
+
+
+
+
+
+Doing GIS in R: main advantages
+
+
+
+
+Calling GIS from R
+
+
+
+
Includes calling R from ArcGIS too
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/GISwithR.md b/GISwithR.md
new file mode 100644
index 0000000..0e6f5eb
--- /dev/null
+++ b/GISwithR.md
@@ -0,0 +1,257 @@
+GIS with R: slides for the unconverted
+========================================================
+author: Francisco Rodriguez-Sanchez
+date: @frod_san
+2015-11-14
+
+
+R: not only for stats
+=====================
+
+![](images/R.jpg)
+
+
+R can make beautiful maps
+=========================
+type: section
+
+
+
+Made in R
+==========
+
+![](images/bike_ggplot.png)
+
+http://spatial.ly/2012/02/great-maps-ggplot2/
+
+
+Made in R
+=========
+
+![](images/facebook_map.png)
+
+http://paulbutler.org/archives/visualizing-facebook-friends/
+
+
+Made in R
+=========
+
+![](images/airMadrid_stamen.png)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+Made in R
+=========
+
+![](images/cft.png)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+Made in R
+=========
+
+![](images/vLine.svg)
+
+http://oscarperpinan.github.io/spacetime-vis/
+
+
+And it's very easy!
+===================
+type: section
+
+
+Map species occurrences in 2 lines of code
+==========================================
+
+
+
+
+```r
+plot(gmap(occdata, type = "satellite"))
+points(occdata, col = "red", pch=20, cex = 2)
+```
+
+![plot of chunk unnamed-chunk-2](GISwithR-figure/unnamed-chunk-2-1.png)
+
+
+
+Let's go step by step
+=====================
+type: section
+
+
+A dataframe of species occurrences
+==================================
+
+
+| |species | lon| lat|
+|:--|:---------------------|------:|------:|
+|1 |Solanum acaule Bitter | -66.10| -21.90|
+|2 |Solanum acaule Bitter | -71.00| -13.50|
+|52 |Solanum acaule Bitter | -66.43| -24.22|
+|53 |Solanum acaule Bitter | -72.07| -13.35|
+|54 |Solanum acaule Bitter | -68.97| -15.23|
+|55 |Solanum acaule Bitter | -64.95| -17.75|
+
+
+Make it a spatial object
+========================
+
+
+```r
+coordinates(occs) <- c("lon", "lat")
+str(occs, 2)
+```
+
+```
+Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots
+ ..@ data :'data.frame': 49 obs. of 1 variable:
+ ..@ coords.nrs : int [1:2] 2 3
+ ..@ coords : num [1:49, 1:2] -66.1 -71 -66.4 -72.1 -69 ...
+ .. ..- attr(*, "dimnames")=List of 2
+ ..@ bbox : num [1:2, 1:2] -72.5 -24.2 -64.7 -12.5
+ .. ..- attr(*, "dimnames")=List of 2
+ ..@ proj4string:Formal class 'CRS' [package "sp"] with 1 slot
+```
+
+
+Specify projection (CRS)
+========================
+
+
+```r
+crs(occs) <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84")
+```
+
+See http://spatialreference.org
+
+
+Project to Mercator and plot
+============================
+
+
+```r
+plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+```
+
+![plot of chunk unnamed-chunk-6](GISwithR-figure/unnamed-chunk-6-1.png)
+
+
+Alternatively, load shapefile
+=============================
+
+
+
+
+```r
+occs <- shapefile("occs.shp")
+plot(gmap(occs, type = "satellite"))
+points(Mercator(occs), col = "red", pch = 20, cex = 2)
+```
+
+![plot of chunk unnamed-chunk-8](GISwithR-figure/unnamed-chunk-8-1.png)
+
+
+Using ggmap
+===========
+
+
+```r
+library(ggmap)
+map <- get_map(bbox(occs), maptype = "watercolor", source = "stamen")
+ggmap(map) +
+ geom_point(aes(x = coords.x1, y = coords.x2), data = as.data.frame(coordinates(occs)),
+ colour = "red", size = 4)
+```
+
+![plot of chunk unnamed-chunk-9](GISwithR-figure/unnamed-chunk-9-1.png)
+
+
+Raster data
+===========
+type: section
+
+
+Download elevation data
+==========================
+
+
+```r
+elevation <- getData("alt", country = "ESP")
+```
+
+
+```r
+library(rasterVis)
+levelplot(elevation)
+```
+
+![plot of chunk unnamed-chunk-11](GISwithR-figure/unnamed-chunk-11-1.png)
+
+
+
+Dynamic interactive maps with leaflet
+=====================================
+
+
+```r
+library(mapview)
+mapView(occs)
+```
+
+![plot of chunk unnamed-chunk-12](GISwithR-figure/unnamed-chunk-12-1.png)
+
+
+
+Remote sensing growing fast
+===========================
+
+e.g. RStoolbox
+
+![](images/rstoolbox.png)
+
+
+Doing GIS in R: main advantages
+===============================
+incremental: true
+
+- Fully-reproducible scripts
+
+- **Harness all R stats power**
+
+ - Data wrangling
+
+ - Modelling
+
+ - Dataviz
+
+- Easy!
+
+
+
+
+Calling GIS from R
+==================
+
+- Grass: [`spgrass6`](http://www.rdocumentation.org/packages/spgrass6)
+- SAGA: [`RSAGA`](http://www.rdocumentation.org/packages/RSAGA)
+- ArcGIS: https://github.com/R-ArcGIS
+![](images/R_ArcGis.png)
+
+Includes calling R from ArcGIS too
+
+
+
+
+To read more
+============
+
+http://pakillo.github.io/R-GIS-tutorial
+
+
+
+
+
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new file mode 100644
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diff --git a/images/bike_ggplot.png b/images/bike_ggplot.png
new file mode 100644
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diff --git a/images/facebook_map.png b/images/facebook_map.png
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diff --git a/images/rstoolbox.png b/images/rstoolbox.png
new file mode 100644
index 0000000..45a2e9a
Binary files /dev/null and b/images/rstoolbox.png differ
diff --git a/images/vLine.svg b/images/vLine.svg
new file mode 100644
index 0000000..e888476
--- /dev/null
+++ b/images/vLine.svg
@@ -0,0 +1,448 @@
+
+
\ No newline at end of file