Abstract
Abstract The availability and accessibility of multispectral and radar satellite remote sensing (SRS) imagery are at an unprecedented high. These data have both become standard source of information for investigating species ecology and ecosystems structure, composition and function at large scales. Since they capture complementary aspects of the Earth's surface, synergies between these two types of imagery have the potential to greatly expand research and monitoring opportunities. However, despite the benefits of combining multispectral and radar SRS data, data fusion techniques, including image fusion, are not commonly used in biodiversity monitoring, ecology and conservation. To help close this application gap, we provide for the first time an overview of the most common SRS data fusion techniques, discussing their benefits and drawbacks, and pull together case studies illustrating the added value for biodiversity research and monitoring. Integrating and fusing multispectral and radar images can significantly improve our ability to assess the distribution as well as the horizontal and vertical structure of ecosystems. Additionally, SRS data fusion has the potential to increase opportunities for mapping species distribution and community composition, as well as for monitoring threats to biodiversity. Uptake of these techniques will benefit from more effective collaboration between remote sensing and biodiversity experts, making the reporting of methodologies more transparent, expanding SRS image processing capacity and promoting widespread open access to satellite imagery. In the context of a global biodiversity crisis, being able to track subtle changes in the biosphere across adequate spatial and temporal extents and resolutions is crucial. By making key parameter estimates derived from SRS data more accurate, SRS data fusion promises to become a powerful tool to help address current monitoring needs, and could support the development of essential biodiversity variables.
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