Many countries around the world are affected by the devastating consequences of drug abuse and illicit trafficking: adverse effects on health; an upsurge in crime, violence and corruption; the draining of human, natural and financial resources that might otherwise be used for social and economic development; the destruction of individuals, families and communities; and the undermining of political, cultural, social and economic structures, as expressed in the United Nations Declaration on the Guiding Principles of Drug Demand Reduction.
The production of the poppy or opium plant was introduced in Peru some years ago. Currently, there are poppy plantations in the departments of San Martín, Amazonas, Huanuco and Cajamarca (Cortegana, one of the study areas within this service).
Colombia is the location of approximately 43% of the world’s coca cultivation, although this percentage is decreasing mainly due to eradication. The majority of the cultivated area (79%) is distributed across 8 departments, one of them corresponds to a study area within this Service, Nariño. This department has the highest amount of land under coca cultivation with 24% of the total coca cultivation in the country. In contrast, the department of Antioquia represents 7% of the 2009 total coca cultivation in Colombia.
Potential areas of coca cultivation maps (Colombia) using optical or radar data, which provides indicative locations of potential coca plantations.
Potential areas of poppy cultivation maps (Peru) using optical data,which provides indicative locations of potential poppy plantations.
Mature Coca Index (MCI) using optical data is an index expressing the extent of mature coca plants on the ground.
Phenological analysis,detecting anomalous decreases in vegetation vigour as an indicator of illegal activities.
Potential areas of coca cultivation map using optical data (Colombia)
These maps are produced using Very High Resolution (VHR) optical data, for Antioquia, and High Resolution (HR) data for Surbol and Nariño East/West. The figure below corresponds to an area of Surbol (Colombia), and it shows the potential areas of coca cultivation (in yellow colour) projected on a SPOT-4 image dated on 24th July 2010. These potential areas were extracted through a semiautomatic approach (over the SPOT-4 pansharpened image): 1. Visual extraction of potential coca signatures; 2. Supervised classification using the previous training signatures over the whole AOI; 3. Photointerpretation of potential areas of coca cultivation, with the support of field data from the UNODC (user).
Potential areas of coca cultivation map using radar data (Colombia)
As the acquisition of the optical data is strongly influenced by the high cloud coverage over the Colombian study areas, the optical data is complemented with VHR radar data (TerraSAR-X). The changes are detected using the Multitemporal Coherence images (MTC).
The figure below shows a composition of the MTC image in an area in Surbol (Colombia). The MTC image was obtained with the Stripmap TSX images acquired on 9th February 2011 and 16th April 2011. The layer extracted in the above image (captioned “SPOT-4 from Surbol. Date: 24 July 2010”) has been overlapped onto the MTC (in yellow). This vector layer has been obtained from a SPOT-4 image dated on 24th July 2010. According to the MTC interpretation, red areas of the image correspond to zones where there is a loss of backscattering between February and April 2011, indicating a potential clear-cut in the vegetation. However, it is not possible to infer the type of crop or vegetation (illicit or legal) from the TSX image.
Potential areas of poppy cultivation map using optical data (Peru)
These maps are produced using VHR optical data covering a surface of 198 km2. Preliminary results for the identification of potential areas of poppy cultivation have been obtained.
These potential areas were extracted through a semiautomatic approach (over a KOMPSAT-2 multispectral image): 1. Automatic object oriented segmentation of multispectral imagery; 2. Automatic removal of non-suitable segments based on spectral and textural signatures; 3. Improvement of remaining segments by interpretation with support of field data from the user.
Mature Coca Index (MCI) using optical data
The MCI is based on the calculation of texture measures derived from the Grey-Level Co-occurrence Matrix (GLCM). It is calculated automatically, without need for field information, on panchromatic satellite images taking advantage of the textural differences between coca fields and forest areas.
The map below shows potential coca fields identified in an area in Antioquia (Colombia) from optical VHR panchromatic and multispectral data. As the available KOMPSAT-2 data was strongly affected by sensor noise, the original MCI method was combined with the NDVI (calculated on multispectral data) to identify potential coca fields in the area. These have high values in both, the texture and the NDVI measure. The mature coca fields are outlined in blue.
This analysis was intended to be performed over Colombian and Peruvian sites, but theproduction system for time series of Level 3 vegetation maps at 300m spatial resolution and processing is restricted to the areas where systematic MERIS data acquisition is available. This is principally Europe and Africa. A query was carried out using the South American AOIs but there were no MERIS data input products. A future analysis will be entirely dependant on ESA acquiring the data and loading it on to the production system.
The image below illustrates the biophysical parameter time series profile for a single map (250mx250m) grid cell. The comparison of a baseline profile with the current year profile highlights any discrepancies (marked by arrows in figure). The automatic detection of such discrepancies can be used to identify areas where plant growth is anomalous and requires further investigation using higher resolution satellite imagery.
This pilot service is coordinated by INDRA with the efforts of other partners inside the G-MOSAIC project: GISAT, Astrium Geo-Information Services and JRC.
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