Resource Details

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

Literature: Journal Articles Available at NO COST

Walsh, S.J., Yang, S., Mena, C.F. & Mccleary, A.L. 2008,"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 and remote sensing, vol. 74, no. 6, pp. 725-735.

Contact Info

Corresponding Author: swalsh@email.unc.edu

Affiliations

  • Department of Geography, University of North Carolina – Chapel Hill,Chapel Hill, North Carolina 27599-3220
  • Department of Geography, Michigan State University, East Lansing, Michigan 48824-1117
  • School of Natural Resources & Environment, University of Michigan, Ann Arbor, Michigan 48109-1041

Link(s)

Available at No Cost:

http://www.asprs.org/PE-RS-Journals-Past-Issues/PE-RS-Journals/PE-RS-Past-Issues/PE-RS-Journals-2008/PE-RS-June-2008.html

In PDF 

 

Description

  • This paper describes a study of reforestation in the Northern Ecuadorian Amazon (NEA) using 2002 remotely sensed Hyperion images and 2001 Ikonos images.
  • Land-use types and conditions were spatially referenced and tracked using GPS technology on 18 farms in the NEA.
  • Then 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 tested their abilities to characterize secondary succession forests using remote sensing.
  • Additionally, they evaluated statistical relationships between the remotely sensed measures of reforestation and the data on socio-economics and other factors from the household surveys.
  • The authors found that secondary forest on the farm was significantly negatively correlated with the presence of more males than females on a farm.
  • 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.

Geographical Region

  • Amazon Basin
  • Country

  • Ecuador
  • This database is a work in progress, and we need your input to keep it up to date. Feel free to contact ELTI at elti@yale.edu to provide information on your own work as well as other projects and literature currently missing from the database.

     

    ELTI is a joint initiative of:
    Yale School of Forestry & Environmental Studies Smithsonian Tropical Research Institute