ANALYSIS OF THE EFFICIENCY OF DELINEATING WORK UNITS IN SUSTAINABLE FOREST MANAGEMENT USING REMOTE SENSING

Abstract

Background: Forest microzoning is fundamental to the efficiency of sustainable forest management plans in the Amazon because it guides the delineation of work units. Traditionally, this process was based on field collections and required a significant amount of time, human resources, and financial resources. Thus, remote sensing emerges as an alternative that can optimize this stage, reducing costs and increasing operational efficiency. The objective of this study was to evaluate the quality of Work Unit delimitations in management areas in the state of Pará by comparing three scenarios: field data, remote sensing data, and integrated data. To this end, geographic data were collected in the field, and then delimitations were generated using geospatial data. Finally, a model combining both types of data was tested. Quality was assessed using an index proposed in the study.
Results: The scenario based solely on remote sensing identified a greater number of watercourses, expanding the Permanent Preservation Areas and reducing the Effective Management Area. The field model had methodological limitations in the first area analyzed, but the integrated model overcame these limitations. The integrated model kept the area of the work units close to ideal and respected the hydrography. In the second area, the integrated model achieved a higher quality index.
Conclusions: The exclusive use of remote sensing overestimates the drainage network, whereas the field model ensures greater accuracy, albeit at a high cost. Therefore, integrating both methods proved to be the most efficient and accurate methodology for forest planning and exploitation.