Pilot study to develop a high resolution land cover product for Colombia using Google Earth Engine computing

    Project: Research Project

    Project Details


    Land cover is defined in generic terms as the set of attributes of the Earth's surface and immediate subsoil, including biota, soil, topography, surface water and human structures. Land cover change is the variation over time between land cover classes, for example, a transition from forest to agricultural cover or vice versa (example in Figure 1). Land cover changes can occur due to different dynamics, including: expansion of the agricultural frontier, urbanization, or the creation of a surface water body (Armenteras et al., 2013; Etter et al., 2006). These changes can occur naturally (due to natural phenomena such as droughts or alluviums), result from "large-scale" anthropogenic phenomena linked to climate change, or more frequently be the result of "immediate" anthropogenic disturbances (Etter et al., 2008), such as deforestation activities. Colombia's promotion of peace paths has been accompanied by growing environmental problems: for example, the extent of deforestation has increased greatly in the last two years (IDEAM, 2018), due to the rapid expansion of the agricultural frontier, the increase in illicit crops, land speculation and illegal mining (Armenteras & Rodriguez Eraso, 2014). With its immense biodiversity, important freshwater resources, extensive forest cover and precious and fragile ecosystems, Colombia urgently needs spatially explicit and up-to-date information on its land cover and the distribution of its biotic and abiotic resources. Decision makers, academia, and non-governmental entities working in environmental management constantly need updated information from different time intervals and spatially explicit for local, regional or national assessments on natural resources and human activities as a basis for the development of solid actions and policies (Mayer&Lopez, 2011; de Leeuw et al., 2010). With this and other justifications on a global scale, several geospatial databases have been generated to provide thematic and highly accurate spatial and temporal information to different decision makers (Bartholomé &Belward, 2005; Eva et al., 2004; Friedl et al., 2010). A clear example is the spatial databases of land use and land cover Corine Land Cover (EEA, 2010), two of which are available for Colombia (years 2006, 2012). However, the Corine Land Use and Cover products for Colombia currently suffer from several limitations: i) they do not have high spatial resolution; ii) they suffer from generalizations (simplification through minimum mapping units); iii) they do not have sufficient temporal resolution; iv) they require very long and expensive supervised image interpretation work to be generated. At the national level, IDEAM is in charge of generating high resolution (30 m) layers of forests and deforestation, but neither this nor other government entities are in charge of generating other thematic classes at high resolution and of fundamental interest for environmental and planning applications (grasslands, bare soil, urban coverage, etc).


    1. Land cover geodatabase of two regions of Colombia (Andes, Amazon) at high resolution for the 2017/8 reference period.
    2. Preparation of a draft article for an international indexed journal.
    3. Internal (FCNM) and external (related institutions) socialization of the research.
    4. Training of a research assistant
    Effective start/end date11/1/196/1/20

    UN Sustainable Development Goals

    In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

    • SDG 8 - Decent Work and Economic Growth
    • SDG 9 - Industry, Innovation, and Infrastructure
    • SDG 17 - Partnerships for the Goals

    Main Funding Source

    • Competitive Funds
    • Seed Capital


    • Bogotá D.C.


    Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.