Remote Sensing to help study biological diversity

Remote Sensing to help study biological diversity


USA, 14 May 2007: Scientists at the Woods Hole Research Center (WHRC), NASA Goddard Space Flight Center and the University of Maryland have undertaken a research to study biological diversity by making use of LiDAR technology. LiDAR data will help the researchers to prepare 3D structures of vegetation, an important aspect of habitat diversity.

Habitat heterogeneity and complexity have been shown in many places to be directly related to animal species richness, a more complex environment provides a greater number of ecological niches to be filled by different species. Using this basic principle, WHRC scientists examined the relationships between bird species richness and habitat metrics derived from LiDAR data acquired by an aircraft. They then explored the efficacy of predicting bird richness and abundance based on these metrics.

According to Scott Goetz, a senior scientist at the Center who is leading the project, “With LiDAR we now have the ability to characterize vegetation in 3D, and that has implications not only for biodiversity research but also for improved estimates of biomass and carbon stocks.”

Some of the other recent studies also involved utility of satellite remote sensing for mapping aspects of biological diversity, for most of such applications they used LANDSAT imagery to characterize horizontal variability in habitat, such as the mixture of different land cover types. Utilizing LiDAR provides information in the vertical dimension, that is, in the terms of canopy profiles describing the vertical distribution of canopy elements, like leaves and branches. This information is then translated into canopy metrics for every LiDAR pulse that penetrates through the canopy. Using this information, researchers can estimate bird diversity through its link with habitat diversity. In the Patuxent study, the LiDAR metrics proved much better with realistic circumstances when compared to prediction of biodiversity with the use of LANDSAT imagery.

Daniel Steinberg, a research assistant who is working on the project, adds, “The instrument we use to acquire the LiDAR data, known as the Laser Vegetation Imaging Sensor (LVIS), collects literally millions of data points within a small area, and using this data we can actually construct 3-dimensional images of canopy height, elevation, complexity, as well as other metrics of habitat structure.”