Crop Mask Title:
ASAP (Anomaly Hotspot of Agricultural Production) crop mask (area fraction)
**Coverage: **
Global
**Spatial resolution: **
ASAP crop mask resolution is 1 kilometer (0.0089286 degree resolution).
**Satellite: **
Derived from a variety of crop masks generated from a variety of satellites (MODIS, MERIS, Landsat, etc.)
**Year: **
N/A
Version:
ASAP crop mask (version 03) was updated on March 12, 2019.
**Organization: **
Food Security Unit of the Joint Research Centre-European Commission (JRC-EC).
**Resource Contact: **
Felix Rembold felix.rembold@ec.europa.eu
Resource Abstract:
Cropland and rangeland areas in Africa are identified using masks generated from the land cover/land use dataset of Vancutsem et al. (2013). For the rest of the world we used the GlobCover 2005–06 (Bicheron et al., 2008) with the exception of following countries/regions where we used more specific land use maps: Afghanistan (Land Cover of Afghanistan 1993; FAO, 1993), Argentina (Cobertura del suelo de la Republica Argentina 2006–07; Volante, 2009), Australia (National scale land use 2001–02; Bureau of Rural Sciences, 2006), Europe (Corine land cover map 2000; Bosard et al., 2000), Mexico (MODIS land cover classification; Giri and Jenkins, 2005), U.S.A. (National Land Cover Database of United States; Homer et al., 2004).
The masks, derived from cropland and rangeland maps with resolution of 250 m (Vancutsem et al., 2013), are expressed at the lower spatial resolution of NDVI data (1 km) as area fraction images (AF, i.e. the percentage of the pixel occupied by crop and rangeland, ranging from 0 to 100%).
Resource Classification Categories:
Each pixel represents the area fraction of the specific cover (i.e. percentage of the pixel with crops/rangeland). Data are scaled between 1 and 200 (50 = 25%, 100 = 50%, 150 = 75%, 200 = 100%): image values V = 0-200, scaling 0.5 - > physical value 0-100%. These layers were generated for use in ASAP combining existing data sets.
Reprocessing for MODIS-GLAM (250-meter) applications:
The 1-km ASAP crop mask was resampled to 250-meters spatial resolution for cropland data drilling on MODIS-GLAM. The resampling steps follow:
Resource URL:
https://agricultural-production-hotspots.ec.europa.eu/
Download URL:
https://agricultural-production-hotspots.ec.europa.eu/download.php
Resource Citations:
Rembold, F. et al, 2019. ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis. Agricultural Systems, Volume 168, January 2019, Pages 247-257
Perez-Hoyos, A., Rembold, F., Kerdiles, H., Gallego, J., 2017. Comparison of global land cover datasets for cropland monitoring. Remote Sens. 2017; 9(11):1118
Vancutsem C. Vancutsem, E. Marinho, F. Kayitakire, L. See, S. Fritz. 2013. Harmonizing and combining existing land cover/land use datasets for cropland area monitoring at the African continental scale Remote Sens., 5 (2013), pp. 19-41
Bicheron, P. Defourny, C. Brockmann, L. Schouten, C. Vancutsem, M. Huc, S. Bontemps, M. Leroy, F. Achard, M. Herold, F. Ranera, O. Arino GLOBCOVER: product description and validation report. Technical Report (2008) Available online, http://due.esrin.esa.int/page_globcover.php
Bosard M., J. Feranec, J. Otahel. 2000. CORINE land Cover Technical Guide - Addendum 2000European Environmental Agency Technical Report No. 40 (2000), Copenhagen, Denmark
Giri and Jenkins. 2005. Land cover mapping of greater Mesoamerica using MODIS data. Can. J. Remote. Sens., 31 (4) (2005), pp. 274-282
J.N. Volante. 2009. Monitoreo de la cobertura y el uso del suelo a partir de sensores remotos INTA technical report project PNECO (2009), p. 1643. Available online https://inta.gob.ar/sites/default/files/script-tmp-informe_tecnico_lccs.pdf
C. Homer, C. Huang, L. Yang, B. Wylie, M. Coan. 2004. Development of a 2001 National Landcover Database for the United States. Photogramm. Eng. Remote. Sens., 70 (7) (2004), pp. 829-840