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Editorial: Integrating Remote Sensing and Ecology

June 1, 2004

Warren B. Cohen

The special section beginning on p. 511 of this issue contains six overview articles about remote sensing. The last time this journal published a collection of articles on the subject was in July/August 1986. The contributing editor at the time, David H. Greegor Jr., wrote an article introducing readers to the basic physical concepts of remote sensing and describing selected sensor systems and data analysis. Greegor ended the article by challenging researchers to use remote sensing technology to help measure and understand global ecological changes.

Eighteen years later, I need not reiterate basic information; the remarkable potential of remote sensing to help solve global environmental problems is well known. Rather, my goal is to convey how far researchers have come toward adapting remote sensing to a wide range of ecological arenas.

In coordinating this special section, I focused first on the broad scope of today’s technology. Some remote sensing tools have been with us for over 30 years (e.g., Landsat), but others are only now emerging (e.g., interferometric radar). (BioScience published an overview article on lidar [light detecting and ranging]—an extremely powerful new tool—in January 2002, so I omitted that topic in this compendium.) I then sought out scientists at the forefront of developing applications to bridge the gaps between the technologies and ecological science.

The article by Michael Wulder and colleagues (p. 511) connects the past with the future by tying aerial photography, historically the most widely used remote sensing technology, to its current digital counterpart, sometimes referred to as hyperspatial imagery. The article I wrote with Samuel Goward (p. 535) describes Landsat, the longest-running satellite technology for studying the earth. Landsat data have a rich history of use in various disciplines, but a modern summary of their use in ecology is particularly timely, given uncertainty about the continuing availability of Landsat-quality data. The promise of hyperspectral imagery is great and, as Susan Ustin and her colleagues show in their article (p. 523), it is starting to be broadly realized. The MODIS sensor, now the most important tool for global applications, is described in the article by Steven Running and colleagues (p. 547), which focuses on assessing the primary productivity of terrestrial systems. Robert Treuhaft and colleagues (p. 561) describe interferometric radar, a lesser-known—but potentially powerful—technology for characterizing vegetation structure. Their article also addresses a key trend in remote sensing: fusion of data sets. Finally, David Turner and colleagues use a variety of case studies to demonstrate, in the article beginning on p. 573, the value of integrating remote sensing and process modeling at landscape to regional scales.

We have made considerable progress toward meeting the challenge of integrating remote sensing with biological and ecological sciences. Scientists now have tremendous computing power for processing prodigious amounts of remotely sensed data, with the results often accessible through the Internet at little or no cost. In addition, more and more biophysical data products derived from remote sensing are being created. Our current challenge is to devise modeling strategies that integrate these resources to forecast the behavior of ecological systems on a global scale. I hope this special section inspires readers to accelerate the pace.

Warren B. Cohen
US Department of Agriculture, Forest Service
Pacific Northwest Research Station
Corvallis, OR 97331

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