Remote Sensing Training in Ecology and Conservation – challenges and potential

Martin Wegmann, Department of Remote Sensing, Ecology and Conservation Research, University of Würzburg, Germany.

Over recent decades remote sensing (RS) has made valuable contributions to ecology and conservation. However, despite its clear value, the potential of RS has not yet been fully realized, and training in the tools and applications for RS is limited. While collection of and access to data are becoming ever cheaper and easier, limited analytical expertise hinders their wider use. Furthermore, the interdisciplinary nature of the research at the interface between remote sensing, ecology and conservation presents its own challenges. It is essential that we standardise not only the techniques for handling the complex spatial data but also the training required to utilise these techniques to the best advantage.

In this Special Issue of Remote Sensing in Ecology and Conservation we highlight some of the barriers to training in RS and suggest how a number of the challenges can be addressed. Every paper describes a clear need to increase training, as well as drawing attention to issues related to the cost for data and software, and the logistical problems of Internet access and capacity building. In addition, dedicated training is vitally important for complex techniques and data sets, such as time-series analysis, and hyperspectral, LiDAR and radar data as applied to ecology and conservation science. It is important that RS data are provided in common formats and consistent final processing levels, as pre-processing procedures or data conversion can become an obstacle to the successful implementation of RS techniques.

RS training forest

Training in remote sensing will enable researchers to use RS data and methods in their daily work and, more importantly, to interpret such data and approaches proficiently. Widespread understanding of RS data, tools and applications can yield high rewards for conservation science and management, but training is the key. Identifying and removing the barriers that hinder the implementation of RS tools are a priority, and lack of training is a significant barrier. Improved training is crucial if we are to bridge the gaps between disciplines, share our knowledge and realize the full potential of RS science for ecology and conservation.

Martin Wegmann teaches MSc courses in the EAGLE graduate program ( and Global Change Ecology study program (, focusing on applied remote sensing data analysis for environmental challenges. Principally, Martin uses open-source software and open-access data, and all courses are interdisciplinary and international. Martin has experienced both the potential for training to support the application of remote sensing in ecology and conservation, and the challenges of training across a range of disciplines. Martin is an Associate Editor for RSEC and Editor of this special issue.


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