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Keywords:

  • Amazonia;
  • georeferencing;
  • IKONOS;
  • reduced-impact logging;
  • remote sensing;
  • tropical moist forests

Summary

  • 1
    Until very recently there have been no digital data from satellites for studying events that occur at scales of 10–1000 m2 over large areas (100–100 000 ha). Many phenomena of interest to ecologists, such as impacts of selective logging on forest processes, occur over large extents but at local scales. Here we report results from a pilot project to evaluate through visual interpretation the potential of newly available 1-m panchromatic and 4-m multi-spectral data from the IKONOS satellite, for studying forest structure, dynamics and logging impacts in logged and old-growth tropical moist forest.
  • 2
    The study area, the Mil Madeireira Itacoatiara Ltda site of Precious Woods Amazon, near Itacoatiara, Amazonas, Brazil, is managed using reduced-impact logging practices to minimize environmental impacts, and thus represents a lower bound for logging impacts in tropical rain forests.
  • 3
    The IKONOS image was georeferenced using uncorrected global positioning system (GPS) locations for 10 control trees whose crowns were clearly visible in the image. The root mean square error (RMSE) of the geometric transformation was 4 m, while the mean crown diameter of 50 randomly chosen trees in old-growth forest was 9·4 m. The fact that the RMSE was less than half the average crown diameter implies that it will usually be possible to locate from the ground crowns that are distinct on the image, given sufficiently accurate GPS locations.
  • 4
    IKONOS data are well suited for evaluating and monitoring logging impacts. Many impacts of logging were clearly observable in the image, including major and some minor roads, logging patios and larger logging gaps. Smaller extraction roads and logging gaps were not observable.
  • 5
    Many individual trees were distinct on the IKONOS image, indicating that it is now feasible to conduct demographic studies of tropical rain forest canopy trees based on repeated satellite observations. Linking these remotely sensed data to ground data will require improved GPS positions, because it is currently difficult to obtain accurate GPS readings in tropical rain forest understoreys.
  • 6
    Synthesis and applications. IKONOS 1-m and 4-m data were found to be useful for identifying individual trees as well as some logging management features in a tropical moist forest in central Amazonia. These data will have many applications for research and management of intervened and old-growth tropical forests, including planning and assessment of logging activities, as well as monitoring adherence to certification criteria such as those of the Forest Stewardship Council. Rapid development of these applications will come from building on existing data on forest structure and function, and by fostering collaborations between remote sensing scientists, ecologists and natural resource managers.