Pressures

**Agricultural Pressure**
The Agricultural Pressure index is based on the average percentage of cropland in 1 km raster cells within protected areas of size ≥ 50 km2 extracted from the World Database on Protected Areas (WDPA). The agricultural data are IIASA-IFPRI cropland percentage map for the baseline year 2005.

The agricultural data can be downloaded from @https://www.geo-wiki.org/downloads/ The WDPA is accessible from @https://protectedplanet.net/

Reference for the agricultural data: Fritz et. al. 2015. Mapping global cropland and field size. //Global Change Biology//. @http://onlinelibrary.wiley.com/doi/10.1111/gcb.12838/abstract code format="python" import arcpy


 * 1) Check out any necessary licenses

arcpy.CheckOutExtension("spatial")


 * 1) Load required toolboxes

arcpy.ImportToolbox("Model Functions")


 * 1) Local variables:

WDPA = "WDPA"

Agri_raster = "E:\\xxx\\CROPLAND2005.tif"

agri_wdpa_all = "E:\\xxx\\agri.gdb\\agri_wdpa_all"

WDPA_wdpa_id_text = "WDPA_wdpa_id_text"

agriValue_ = "E:\\xxx\\AGRI_OUTPUT.gdb\\ele_%Value%"


 * 1) Process: Loop through the features

arcpy.IterateFeatureSelection_mb(WDPA, "wdpa_id_text #", "false")


 * 1) Process: Zonal Statistics

arcpy.gp.ZonalStatisticsAsTable_sa(WDPA_wdpa_id_text, "wdpa_id_text", Agri_raster, agriValue_, "DATA", "ALL")


 * 1) Process: Append

arcpy.Append_management("E:\\xxx\\AGRI_OUTPUT.gdb\\ele_%Value%", agri_wdpa_all, "NO_TEST", "COUNT \"COUNT\" true true false 4 Long 0 0 ,First,#,\

E:\\xxx\\AGRI_OUTPUT.gdb\\ele_%Value%,Range,-1,-1;MEAN \"MEAN\" true true false 8 Double 0 0 ,First,#, wdpa_id_text \"wdpa_id_text\" true true false 50 Text 0 0 ,First,#, \

E:\\xxx\\AGRI_OUTPUT.gdb\\ele_%Value%,wdpa_id_text,-1,-1", "") code

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Internal Road Pressure
The Internal Road Pressure index is based on the average presence of 250 m bufferized roads in 250 m raster cells within protected areas of size ≥ 50 km2 extracted from the World Database on Protected Areas (WDPA). The road data are the Global Roads Open Access Data Set (gROADS), v1 (1980 – 2010). The data is generated by the Center for International Earth Science Information Network - CIESIN - Columbia University, and Information Technology Outreach Services - ITOS - University of Georgia.

The road data are available from @http://sedac.ciesin.columbia.edu/data/set/groads-global-roads-open-access-v1 The WDPA is accessible from @https://protectedplanet.net/ code format="python" import arcpy
 * 1) Import arcpy module
 * 1) Roads Buffer (arcpy)
 * 1) Roads Buffer (arcpy)

roads_shp = "E:\\xxx\\roads.shp" roads_Buffer = "E:\\xxx\\roads_buffer.shp"
 * 1) Local variables:

arcpy.Buffer_analysis(roads_shp, roads_Buffer, "250 Meters", "FULL", "ROUND", "ALL", "")
 * 1) Process Buffer


 * 1) Rasterize Buffer using GDAL
 * 2) (-burn 100: means that you assign the value 100 to the bufferized roads and 0 where there is no roads)
 * 3) (-tr : Target resolution. The values must be expressed in georeferenced units. Both must be positive values.)
 * 1) (-burn 100: means that you assign the value 100 to the bufferized roads and 0 where there is no roads)
 * 2) (-tr : Target resolution. The values must be expressed in georeferenced units. Both must be positive values.)

gdal_rasterize -burn 100 -tr 250 250 -l buff /Users/lucabattistella/roads/roads_buffer.shp /Users/lucabattistella/roads/roads_buffer.tif


 * 1) WDPA Zonal Statistics (arcpy)
 * 1) WDPA Zonal Statistics (arcpy)

arcpy.CheckOutExtension("spatial")
 * 1) Check out any necessary licenses

arcpy.ImportToolbox("Model Functions")
 * 1) Load required toolboxes

WDPA_poly_Oct2017_50 = "E:\\xxx\\ROAD_PRESSURE\\WDPA_October2017_Public\\WDPA_Oct2017_Public.gdb\\WDPA_poly_Oct2017_50" seff_1000_rep_tif = "E:\\xxx\\ROAD_PRESSURE\\Fiinal_Road_Raster\\roads_buffer.tif" I_WDPA_poly_Oct2017_50_wdpa_id_text = "I_WDPA_poly_Oct2017_50_wdpa_id_text" InternalRoadPressure__Value_ = "E:\\xxx\\ROAD_PRESSURE\\output.gdb\\InternalRoadPressure_%Value%"
 * 1) Local variables:

arcpy.IterateFeatureSelection_mb(WDPA_poly_Oct2017_50, "wdpa_id_text #", "false")
 * 1) Process: Iterate Feature Selection

arcpy.gp.ZonalStatisticsAsTable_sa(I_WDPA_poly_Oct2017_50_wdpa_id_text, "wdpa_id_text", seff_1000_rep_tif, InternalRoadPressure__Value_, "DATA", "MEAN")
 * 1) Process: Zonal Statistics as Table

code