Forest area was estimated using AVHRR data and dot count procedures.

Tropical habitats may contain more than a third of the world's plant and animal species; Costa Rica alone is home to one of the highest levels of biodiversity per unit area in the world, and stands at center stage in worldwide conservation efforts. Within such regions, the use of state-of-the-art digital mapping technologies—sophisticated techniques that are relatively inexpensive and accessible—represents the future of conservation planning and policy. These methods, which employ satellites to obtain visual data on landscapes, allow environmental scientists to monitor encroachment on indigenous territories, trace park boundaries through unmarked wilderness, and identify wildlife habitats in regions where humans have limited access. Focusing on the rich biodiversity of Costa Rica, the contributors demonstrate the use of geographic information systems (GIS) to enhance conservation efforts. They give an overview of the spatial nature of conservation and management and the current status of digital mapping in Costa Rica; a review of the basic principles behind digital mapping technologies; a series of case studies using these technologies at a variety of scales and for a range of conservation and management activities; and the results of the Costa Rican gap analysis project. GIS Methodologies for Developing Conservation Strategies provides powerful tools for those involved in decision-making about the natural environment, particularly in developing nations like Costa Rica where such technologies have not yet been widely adopted. For specialists in such areas as geography, conservation biology, and wildlife and natural resource management, the combination of conceptual background and case examples make the book a crucial addition to the literature.

The U.S. Department of Agriculture, Forest Service, Southcm Research Station, appointed a remote-sensing team to develop an image-processing methodology for mapping forest lands over large geographic areds. The team has presented a repeatable methodology, which is based on regression modeling of Advanced Very High Resolution Radiometer (AVHRR) and Landsat Thematic Mapper (TM) data. It is a methodology that Forest inventory and Analysis (FIA) survey personnel can implement in any region or area. The term repeatable implies objectivity. Studies in the conterminous United States, Central America and Mexico, and west Texas and Oklahoma have provided valuable insights that address the subjective nature of some of the steps taken in mapping large forest areas. The team has identified seven such steps. They have reduced or eliminated subjectivity in four of the steps and identified two steps in which objectivity can be enhanced.