Satellite remote sensing of regional and global ecology has limitations in terms of space and time resolutions and restraints on the spectral discrimination possible in regard to ecological species. Typically, remote sensing is best suited for the monitoring of relatively large spatial scales and somewhat homogeneous ecological zones. Thus, the fine features of highly heterogeneous ecological zones and complex issues concerning species composition and diversity will require detailed in situ observations and investigations to complement satellite observations. The challenge that faces both the scientific community of researchers, and the community of operational planners and managers who oversee and protect environmental and ecological resources, is to develop techniques to optimize the benefit obtainable from both in situ and remote sensing observational platforms. Beyond the scope of this article are issues involved with regard to the sustainability of the natural environment and ecosystem, a subject that entails a multitude of social, economic, cultural, and political factors or forces. Biodiversity, an important aspect of ecological studies, is also somewhat outside the capabilities of satellite remote sensing, though some features of species succession, adaptation, and movement may be captured.
We suggest here that space-based remote sensing should be viewed as an indispensable and powerful tool to observe, understand, monitor, and model global ecosystems when integrated with more detailed in situ observations. Another aspect for which satellite sensing technology has proved to be indispensable is in monitoring a large number of parameters that govern the geophysical, dynamic, thermodynamic, radiative, energetic, and chemical and biological environments that interact with or even determine the character of global and regional ecosystems. Space-based satellite observations, combined with in situ measurements, have the ability to provide a more comprehensive and holistic view of the Earth/climate system. Unprecedented advances have occurred over the past decade in satellite observing technology as well as in complex coupled models, data assimilation, and data fusion methods. The future is yet to unfold.
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