Remote Sensing in Ecology and Conservation is a fully open access journal from Wiley and the Zoological Society of London. The journal provides a forum for the rapid publication of peer-reviewed, multidisciplinary research from the interface between remote sensing science and ecology and conservation. The journal defines remote sensing in its broadest sense, including data acquisition by hand-held and fixed ground-based sensors, such as camera traps and acoustic recorders, and sensors on airplanes and satellites. The journal’s intended audience includes ecologists, conservation scientists, policy makers, managers of terrestrial and aquatic systems, remote sensing scientists, and students.
GOOD NEWS! Remote Sensing in Ecology and Conservation has been accepted for indexing in Scopus!
The RSEC blog provides a platform for authors to promote their research through written posts, podcasts, images and videos. We welcome guest posts on all aspects of remote sensing science relevant to ecology and conservation. See here for details.
Remote Sensing in Ecology and Conservation: three years on…
In 2014 we launched Remote Sensing in Ecology and Conservation, an open-access journal to support communication and collaboration among experts in remote sensing, ecology and conservation science. As we approach our second full year of publication, we thought we would reflect on how the journal has done to date, and take a look at what impact it has had, and where the journal is yet to meet its full potential. By sharing our successes and experiences with our contributors and readers, we hope to show how the journal has developed in terms of visibility and status among researchers and practitioners. So what is our record so far?
Recent studies show that LiDAR‐derived habitat variables significantly increase the performance and accuracy of species distribution models (SDMs). In particular, the structure of complex habitats such as forest can be accurately parametrized by an area‐wide, LiDAR‐based vegetation profile. However, evidence of specific applications of such models in real‐world conservation management still remains sparse. In our study, we developed a SDM for the rare hazel grouse by using LiDAR‐derived species‐specific, forest habitat parameters. The outstanding model performance suggests that small‐scale habitat suitability for hazel grouse is mainly affected by local, fine‐grained vegetation structure. Therefore, LiDAR provides the means to develop ecologically interpretable predictor variables of forest structure. They can be used to reliably map fine‐grained habitat quality at different scales. This clearly shows that regional species conservation can substantially benefit from the growing availability of airborne LiDAR data which facilitate the planning of spatially explicit habitat measures.