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
import arcpy
 
# Check out any necessary licenses
 
arcpy.CheckOutExtension("spatial")
 
# Load required toolboxes
 
arcpy.ImportToolbox("Model Functions")
 
# 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%"
 
 
# Process: Loop through the features
 
arcpy.IterateFeatureSelection_mb(WDPA, "wdpa_id_text #", "false")
 
 
# Process: Zonal Statistics
 
arcpy.gp.ZonalStatisticsAsTable_sa(WDPA_wdpa_id_text, "wdpa_id_text", Agri_raster, agriValue_, "DATA", "ALL")
 
 
# 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", "")


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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/
# Import arcpy module
import arcpy
# ---------------------------------------------------------------------------
# Roads Buffer (arcpy)
# ---------------------------------------------------------------------------
 
# Local variables:
roads_shp = "E:\\xxx\\roads.shp"
roads_Buffer = "E:\\xxx\\roads_buffer.shp"
 
# Process Buffer
arcpy.Buffer_analysis(roads_shp, roads_Buffer, "250 Meters", "FULL", "ROUND", "ALL", "")
 
 
 
# ---------------------------------------------------------------------------
# Rasterize Buffer using GDAL
# ---------------------------------------------------------------------------
# (-burn 100: means that you assign the value 100 to the bufferized roads and 0 where there is no roads)
# (-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
 
# ---------------------------------------------------------------------------
# WDPA Zonal Statistics (arcpy)
# ---------------------------------------------------------------------------
 
# Check out any necessary licenses
arcpy.CheckOutExtension("spatial")
 
# Load required toolboxes
arcpy.ImportToolbox("Model Functions")
 
 
# Local variables:
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%"
 
# Process: Iterate Feature Selection
arcpy.IterateFeatureSelection_mb(WDPA_poly_Oct2017_50, "wdpa_id_text #", "false")
 
# Process: Zonal Statistics as Table
arcpy.gp.ZonalStatisticsAsTable_sa(I_WDPA_poly_Oct2017_50_wdpa_id_text, "wdpa_id_text", seff_1000_rep_tif, InternalRoadPressure__Value_, "DATA", "MEAN")