Skip to main content
U.S. Department of Energy
Office of Scientific and Technical Information

Deforestation measured by LANDSAT: steps toward a method

Technical Report ·
OSTI ID:5900289
The magnitude of the annual carbon flux due to deforestation is a function of the rate of deforestation and biotic factors including biomass, soil organic matter, and the fraction of the stock of organic matter oxidized following disturbance. Immediate improvement in estimation of the carbon flux to the atmosphere depends on reducing the uncertainty in estimates of rates of deforestation. The greatest potential for new data lies in the use of remote sensing, especially satellite. The LANDSAT system determines net change in the area of forests, and therefore in the amount of carbon held in terrestrial systems, globally. The work required development of a model based on forest succession, the MBL-TCM, designed to accommodate changes in area of forests regionally as well as successional changes following disturbance or the abandonment of land. Three approaches to the use of LANDSAT data for this purpose seemed possible. First, if a sufficiently detailed classification of vegetation can be made from a single LANDSAT image, an estimate of net flux is possible through use of a model. This is the single image approach. Second, LANDSAT imagery might be used to construct two classification inventories of the amount of carbon in the vegetation at different dates. Fianlly, the technique of change detection using satellite imagery might be applied by substracting the digital information in a later image from a former image to produce a third data set that records only the changes.
Research Organization:
Marine Biological Lab., Woods Hole, MA (USA). Ecosystems Center; New Hampshire Univ., Durham (USA). Complex Systems Research Center; General Electric Co., Lanham, MD (USA). Space Systems Div.
DOE Contract Number:
AC02-80EV10468
OSTI ID:
5900289
Report Number(s):
DOE/EV/10468-1; ON: DE83016645
Country of Publication:
United States
Language:
English