LEIPZIG, Germany, Jan. 30, 2017 — Remote sensing methods, which have been used to measure biological diversity for about 30 years, show even greater potential for assisting biodiversity research in the future.
A key task of this research is to record the current state of diversity, study processes within ecosystems and identify possible changes.
“To do this we need reliable data across large areas and close periods of time,” said Angela Lausch, Landscape Ecologist PD at Helmholtz Centre for Environmental Research-UFZ. “Various remote sensing methods already meet these requirements in a remarkable way.”
Using satellite images, the distribution of a plant species, for example, can be determined based on its growth habit or leaf shape over large areas and over time. A satellite’s spectral sensors can help distinguish and record plant species or plant communities based on their specific biochemical properties.
Remote sensing techniques are used along with field studies, which provide crucial data that cannot be recorded via remote sensing. Field studies are also necessary for evaluating and interpreting the remote sensing data.
“One is not possible without the other,” said Lausch. “Biodiversity can only be measured more accurately . . . by combining in-situ studies and remote sensing.”
The role of remote sensing in detecting and predicting biodiversity was investigated by an international research team spearheaded by UFZ. The team looked at how examples of spectral traits and spectral trait variations found through remote sensing applications could be used to quantify taxonomic, functional and structural diversity; and examined how different remote sensing techniques could be used to monitor biodiversity and habitat quality.
The researchers believe that remote sensing methods represent an affordable, repeatable and comparable method for measuring, describing, explaining and modelling biodiversity; and that upcoming sensor developments such as the hyperspectral satellite Environmental Mapping and Analysis Program (EnMAP) will provide opportunities to quantify spectral traits not detectable with current methods, helping to describe biodiversity in more detail.
EnMAP, due to be launched in 2018, will provide image data with very high spectral resolution. Hyperspectral remote sensing could then be used to measure many more biochemical parameters, such as nitrogen, phosphate or the water content in leaf tissue.
“EnMAP will significantly improve the identification of species and plant communities via remote sensing. However, the greatest potential offered by hyperspectral remote sensing lies in measuring processes and disturbances within ecosystems over large areas,” said Lausch.
“The data produced by the EnMAP satellite will be freely available to all users,” she added “We, in biodiversity research, should therefore be prepared to recognize and leverage the potential of the new generation of satellites.”
Compared with climate change, the data on changes in biodiversity is fairly thin; and there are still very few uniform standards worldwide for measuring the data. For the study of biodiversity to gain maximum value from Earth Observation sensor networks, the researchers believe that the link between field and remote sensing data must be optimized to make it easier to aggregate large, complex, heterogeneous volumes of data, thus making it easier to evaluate the data and transfer it to models.
The research was published in Ecological Indicators (doi:10.1016/j.ecolind.2016.06.022).