palumbo_rsec_2016Our new article on the importance of remote sensing training is published in RSEC, lead by Ilaria Palumbo from JRC titled “Building capacity in remote sensing for conservation: present and future challenges”.

from the abstract: Remote sensing (RS) has made significant contributions to conservation and ecology; however, direct use of RS-based information for conservation decision making is currently very limited. In this paper, we discuss the reasons and challenges associated with using RS technology by conservationists and suggest how training in RS for conservationists can be improved. We present the results from a survey organized by the Conservation Remote Sensing Network to understand the RS expertise and training needs of various categories of professionals involved in conservation research and implementation. The results of the survey highlight the main gaps and priorities in the current RS data and technology among conservation practitioners from academia, institutions, NGOs and industry. We suggest training to be focused around conservation questions that can be addressed using RS-derived information rather than training pure RS methods which are beyond the interest of conservation practitioners. We highlight the importance of developing essential biodiversity variables (EBVs) and how this can be achieved by increasing the RS capacity of the conservation community. Moreover, we suggest that open-source software is adopted more widely in the training modules to facilitate access to RS data and products in developing countries, and that online platforms providing mapping tools should also be more widely distributed. We believe that improved RS capacity among conservation scientists will be essential to improve conservation efforts on the ground and will make the conservation community a key player in the definition of future RS-based products that serve conservation and ecological needs.

Palumbo, I., Rose, R. A., Headley, R. M. K., Nackoney, J., Vodacek, A. and Wegmann, M. (2016), Building capacity in remote sensing for conservation: present and future challenges. Remote Sens Ecol Conserv. doi:10.1002/rse2.31