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update readme
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‎README.md

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<!-- badges: start -->
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[![Lifecycle:
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experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
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<!-- badges: end -->
@@ -13,9 +14,6 @@ spatio-temporal extent to your local machine. This package is at an
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experimental state and currently only supports the download of raster
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files.
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**Disclaimer**
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This package is in no way associated with the WaPOR portal or the FAO.
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To install the package run:
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```r
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library(wapoR)
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collections = wapor_collections()
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collections
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```
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## code
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## 1 AQUAMAPS
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## 2 ASIS
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## 3 C2ATLAS
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## 4 CHIRPS
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## 5 DLMF
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## 6 FAOSTAT
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## 7 GAEZ_2015
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## 8 GLW
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## 9 NASA
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## 10 NATURAL_EARTH
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## 11 NMME
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## 12 RDMS
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## 13 RICCAR
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## 14 RICCAR_2
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## 15 RVF
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## 16 WAPOR
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## 17 WAPOR_2
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## 18 WPOP
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## caption
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## 1 Global spatial database on water and agriculture
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## 2 Agriculture Stress Index System
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## 3 Climate Change ATLAS
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## 4 Climate Hazard group InfraRed Precipitation with Stations (CHIRPS)
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## 5 Desert Locust Monitoring and Forecasting
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## 6 FAO Corporate Statistical Database
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## 7 Global Agro-Ecological Zones (2015)
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## 8 Gridded Livestock of the World
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## 9 National Aeronautics and Space Administration (NASA)
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## 10 Natural Earth
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## 11 North American Multi-Model Ensemble (NMME)
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## 12 Regional Drought Monitoring System
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## 13 Regional Arab Climate Change Assessment Report
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## 14 Regional Arab Climate Change Assessment Report
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## 15 Rift Valley Fever
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## 16 FAO Water Productivity Open-access portal (WaPOR)
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## 17 FAO Water Productivity Open-access portal (WaPOR)
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## 18 WorldPop project
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## code
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## 1 AQUAMAPS
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## 2 ASIS
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## 3 C2ATLAS
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## 4 CHIRPS
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## 5 DLMF
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## 6 FAOSTAT
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## 7 GAEZ_2015
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## 8 GLW
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## 9 NASA
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## 10 NATURAL_EARTH
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## 11 NMME
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## 12 RDMS
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## 13 RICCAR
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## 14 RICCAR_2
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## 15 RVF
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## 16 WAPOR
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## 17 WAPOR_2
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## 18 WPOP
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## caption
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## 1 Global spatial database on water and agriculture
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## 2 Agriculture Stress Index System
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## 3 Climate Change ATLAS
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## 4 Climate Hazard group InfraRed Precipitation with Stations (CHIRPS)
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## 5 Desert Locust Monitoring and Forecasting
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## 6 FAO Corporate Statistical Database
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## 7 Global Agro-Ecological Zones (2015)
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## 8 Gridded Livestock of the World
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## 9 National Aeronautics and Space Administration (NASA)
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## 10 Natural Earth
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## 11 North American Multi-Model Ensemble (NMME)
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## 12 Regional Drought Monitoring System
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## 13 Regional Arab Climate Change Assessment Report
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## 14 Regional Arab Climate Change Assessment Report
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## 15 Rift Valley Fever
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## 16 FAO Water Productivity Open-access portal (WaPOR)
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## 17 FAO Water Productivity Open-access portal (WaPOR)
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## 18 WorldPop project
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```
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In its current state, the package mainly supports products from the
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WAPOR collections. For some other collection it is also possible to
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query and download raster datasets. However, for some of the collections
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errors will be returned if queried. Currently, you might run into errors
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for these collections:
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- C2ATLAS
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- DLMF
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- NASA
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- NATURAL\_EARTH
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for these collections: - C2ATLAS - DLMF - NASA - NATURAL\_EARTH
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To query the available products within the collections we can run
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\`wapor\_products(“<collection_name>”)\`.
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\`wapor\_products(“<collection_name>”).
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```r
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products = wapor_products("WAPOR_2")
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length(products)
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## [1] 196
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str(products[1:3], max.level = 2)
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```
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## [1] 196
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## List of 3
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## $ L1_GBWP_A:List of 2
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## ..$ product:'data.frame': 1 obs. of 3 variables:
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## ..$ meta :'data.frame': 1 obs. of 12 variables:
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## $ L1_NBWP_A:List of 2
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## ..$ product:'data.frame': 1 obs. of 3 variables:
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## ..$ meta :'data.frame': 1 obs. of 12 variables:
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## $ L1_AETI_A:List of 2
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## ..$ product:'data.frame': 1 obs. of 3 variables:
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## ..$ meta :'data.frame': 1 obs. of 12 variables:
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## List of 3
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## $ L1_GBWP_A:List of 2
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## ..$ product:'data.frame': 1 obs. of 3 variables:
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## ..$ meta :'data.frame': 1 obs. of 12 variables:
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## $ L1_NBWP_A:List of 2
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## ..$ product:'data.frame': 1 obs. of 3 variables:
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## ..$ meta :'data.frame': 1 obs. of 12 variables:
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## $ L1_AETI_A:List of 2
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## ..$ product:'data.frame': 1 obs. of 3 variables:
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## ..$ meta :'data.frame': 1 obs. of 12 variables:
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```
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In the WAPOR\_2 collection we have a total number of 196. As you can see
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from the structured output, each element in the list object represents
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object you will get some general information about the specific product.
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```r
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products[[1]]$product
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kable(products[[1]]$product)
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```
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<table>
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```r
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str(products[[1]]$meta)
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```
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## 'data.frame': 1 obs. of 12 variables:
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## $ format : chr "Raster Dataset"
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## $ unit : chr "kg/m³ is the ratio of kg of dry matter per cubic meter of water transpired by vegetation in one hectare"
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## $ dataType : chr "Int32 (32bit Integer)"
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## $ conversionFactor : chr "the pixel value in the downloaded data must be multiplied by 0.001"
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## $ noDataValue : int -9999
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## $ spatialResolution : chr "250m (0.00223 degree)"
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## $ spatialExtent : chr "Africa and Near East"
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## $ spatialReferenceSystem: chr "EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)"
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## $ temporalResolution : chr "from January 2009 to present"
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## $ temporalExtent : chr "Annual"
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## $ nearRealTime : chr "New dekadal data layers are released approximately 5 days after the end of a dekad."| __truncated__
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## $ methodology : chr "The calculation of gross biomass water productivity (GBWP) is as follows: GBWP ="| __truncated__
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## 'data.frame': 1 obs. of 12 variables:
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## $ format : Factor w/ 1 level "Raster Dataset": 1
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## $ unit : Factor w/ 1 level "kg/m³ is the ratio of kg of dry matter per cubic meter of water transpired by vegetation in one hectare": 1
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## $ dataType : Factor w/ 1 level "Int32 (32bit Integer)": 1
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## $ conversionFactor : Factor w/ 1 level "the pixel value in the downloaded data must be multiplied by 0.001": 1
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## $ noDataValue : int -9999
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## $ spatialResolution : Factor w/ 1 level "250m (0.00223 degree)": 1
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## $ spatialExtent : Factor w/ 1 level "Africa and Near East": 1
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## $ spatialReferenceSystem: Factor w/ 1 level "EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)": 1
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## $ temporalResolution : Factor w/ 1 level "from January 2009 to present": 1
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## $ temporalExtent : Factor w/ 1 level "Annual": 1
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## $ nearRealTime : Factor w/ 1 level "New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of"| __truncated__: 1
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## $ methodology : Factor w/ 1 level "The calculation of gross biomass water productivity (GBWP) is as follows: GBWP = TBP/ETIa Where TBP is annual T"| __truncated__: 1
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```
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With these information combined, we can start downloading some data.
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Let’s say we are interested in the Gross Biomass Water Productivity
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product = "L2_GBWP_S" # product code
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begin = as.Date("2015-01-01") # begin date is inclusive
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end = as.Date("2016-01-01") # end date is exclusive
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dimensions = list(SEASON = "S1") # GBWP only has dimension SEASON - S1 and S2
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dimensions = list(SEASON = c("S1", "S2")) # GBWP only has dimension SEASON - S1 and S2
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key = "<your_personal_API_Key" # can be obtained in the profile section of the WAPOR website
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# at https://wapor.apps.fao.org
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# run the query command - see ?wapor_queryRaster() for more information
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wapor_queryRaster(collection = collection,
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product = product,
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dimensions = dimensions,
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aoi = ugn,
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begin = begin,
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end = end,
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APIkey = APIkey,
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outdir = ".",
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cutline = FALSE,
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tiled = TRUE,
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compressed = TRUE,
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overviews = TRUE)
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product = product,
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dimensions = dimensions,
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aoi = ugn,
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begin = begin,
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end = end,
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APIkey = APIkey,
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outdir = ".",
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cutline = FALSE,
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tiled = TRUE,
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compressed = TRUE,
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overviews = TRUE)
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```

‎README.rmd

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product = "L2_GBWP_S" # product code
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begin = as.Date("2015-01-01") # begin date is inclusive
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end = as.Date("2016-01-01") # end date is exclusive
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dimensions = list(SEASON = "S1") # GBWP only has dimension SEASON - S1 and S2
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dimensions = list(SEASON = c("S1", "S2")) # GBWP only has dimension SEASON - S1 and S2
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key = "<your_personal_API_Key" # can be obtained in the profile section of the WAPOR website
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# at https://wapor.apps.fao.org
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