Remote sensing baseline analysis for the Caminos de Liderazgo Program

About 80% of the territory in the Osa Peninsula is under some category of protection, with varying levels of land use restrictions. In this context, ecotourism can potentially provide an alternative income source to the local communities. The collaborative Caminos de Liderazgo Program in this area is designed as an example of sustainable development with ecotourism functioning as the main engine for both development and environmental stewardship (http://www.grupo-rba.com/#!caminosdeosa/c178u; http://inogo.stanford.edu/news-events/news-press-releases/local/caminos-...).

Expected long-term results of the Caminos program include improved social conditions among participating communities, reflecting increased economic opportunities and income over time, with no negative consequences to the natural environment in the area. The backbone of Caminos is the opening of three trails that cross the Caminos “focal area” (the geographic reach of Caminos), where existing or planned touristic activities (hiking, accommodation, restaurants, birdwatching, etc.) will be carried out. Avoiding or minimizing negative impacts arising from these activities on the local ecosystems is a priority for the initiative.

Baseline (2011 census-based) measures of select socio-economic indicators among households falling within the geographic reach of the Caminos program are provided in a series of INOGO reports. A complementary analysis of landscape and spectral index indicators was conducted using remote-sensing data as a basis for measuring long-term environmental effects of program interventions. Landscape metrics are relevant as they assess habitat extent and fragmentation, both of which provide indications of human pressure in and around protected areas. Spectral indices provide an indication of ecosystem state and a means of measuring change over time in that state. The rationale for using remote sensing, its advantages and limitations, as the basis for long term Caminos environmental monitoring is described in a separate report.

Important factors that influence landscape metrics obtained through analysis of remote-sensing data include: the spatial resolution of the data, the definition of the landscape extent and the classification scheme used. Two types of data with different spatial resolution were used in this INOGO- sponsored study: i) a time series of images from Landsat satellites spanning 40 years with a spatial 30 m resolution and ii) RapidEye satellite image data over 3 months in 2012 with a a spatial resolution of 5 m. Metrics were extracted for the whole Caminos focal area (landscape level) and also at the sub-landscape (community) level. Land cover classes used considered those incorporated in a similar analysis of the larger INOGO study area comprising all of Osa and Golfito cantons, (http://inogo.stanford.edu/resources/INOGOMapas?language=en) to allow for comparisons between the two.