Integration of Hyperion Satellite Data and A Household Social Survey to Characterize the Causes and Consequences of Reforestation Patterns in the Northern Ecuadorian Amazon

Integration of Hyperion Satellite Data and A Household Social Survey to Characterize the Causes and Consequences of Reforestation Patterns in the Northern Ecuadorian Amazon

background

This paper describes reforestation in the Northern Ecuadorian Amazon (NEA) using 2002 remotely sensed Hyperion images and 2001 Ikonos images.

Research Goals & Methods

Land-use types and conditions were spatially referenced and tracked using GPS technology on 18 farms in the NEA. Household surveys were conducted in which the farmer was asked to describe land-use changes, sketch a field map, and provide information on their land parcel to be entered into a database. The authors evaluated statistical relationships between the remotely sensed measures of reforestation and the data on socio-economics and other factors from the household surveys.

Conclusions & Takeaways

 Secondary forest on the farm was significantly negatively correlated with the presence of more males than females. The relationships between secondary forest and other factors were not significant. The results from the data analysis suggest that their is considerable potential for using Hyperion and other remote sensing techniques for distinguishing secondary and successional forests from other types. However, there are still challenges such as distinguishing coffee and cacao mixtures from secondary forest.

 

Reference: 

Walsh SJ, Shao Y, Mena CF, McCleary AL. Integration of Hyperion Satellite Data and A Household Social Survey to Characterize the Causes and Consequences of Reforestation Patterns in the Northern Ecuadorian Amazon. Photogrammetric Engineering & Remote Sensing. 2008;74:725–735. doi:10.14358/pers.74.6.725.

Affiliation: 

  • Department of Geography, University of North Carolina – Chapel Hill,Chapel Hill, North Carolina
  • Department of Geography, Michigan State University, East Lansing, Michigan
  • School of Natural Resources & Environment, University of Michigan, Ann Arbor, Michigan