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TitleUse of Remote Sensing and GIS Techniques in Modeling Net Primary Productivity
AuthorLiu, J; Chen, J M; Cihlar, J; Park, W M
SourceThe Ninth Conference on Astronautics, Ottawa, Ontario, Canada, 12-15 November; 1996.
Alt SeriesEarth Sciences Sector, Contribution Series 20042849
SubjectsNature and Environment; Plants
AbstractNet primary productivity (NPP) is the difference between total carbon uptake through photosynthesis and losses through respiration by green plants per unit time and space. NPP provides useful information to policy makers for sustainable development of natural resources. It also plays an important role in the global climate system because of its effect on the atmospheric concentration of CO2.

In this study, a simulation system, Boreal Ecosystem Productivity Simulator (BEPS), is developed. The spatial information on vegetation and soil is retrieved with remote sensing and GIS techniques. This makes it possible to scale up a biologically based stand-level model (FOREST-BGC) to a large region. A time series of leaf area index (LAI), which is one of the most important parameters controlling NPP, is derived from the satellite data of the Advanced Very High Resolution Radiometers (AVHRR) with 1 km resolution. This dataset, combined with daily meteorological data, enables us to detect seasonal and interannual variances of NPP with BEPS.

The spatial and temporal distributions of NPP in Quebec, Saskatchewan and Manitoba will be displayed. The other components in the carbon and water balances, such as evapotranspiration and respiration, will also be discussed.


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