Textural analysis of coca plantations using remotely sensed data with resolution of 1 metre

The detection of surfaces cultivated with coca plants is essential to all activities related to monitoring and combating the production of illicit drugs such as cocaine. Moreover, deforestation processes can often be associated with the presence of coca plantations in the Andean region. In this context, the use of remote sensing technologies has proven to be effective for building an operational monitoring capacity, but more effort is needed to establish a robust computational frame for automatic detection procedures. This paper contributes to this effort by analysing the discrimination power of different textural measures and by proposing a new Mature Coca Index (MCI) derived from the textural analysis of 1-m resolution satellite imagery. The approach can be applied to the latest generation optical sensors such as IKONOS and QUICKBIRD, and improves the current state-of-the-art of recognition procedures for satellite data based on radiometric discrimination. The paper describes the MCI concept, its implementation, and application to a data sample derived from the IKONOS sensor.