Identifying and mapping individual plants in a highly diverse high-elevation ecosystem using UAV imagery and deep learning
ISPRS Journal of Photogrammetry and Remote Sensing, Volume 169, November 2020, Pages 280-291
Ce Zhang, Peter M.Atkinson, Charles George, Zhaofei Wen, Mauricio Diazgranados, France Gerard
The identification of P谩ramo plant individuals is essential for environmental monitoring and management. Traditional remote sensing approaches, however, are unsuitable for identifying and mapping individual P谩ramo plants because they can be very small laterally relative to their height and can be both clustered and highly dispersed.
Recent research in UAV (unmanned aerial vehicle) and machine learning led by Zhang et al. (2020) has shown great potential and promise in automating the process with high accuracy.
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A concerted research effort to advance the hydrological understanding of tropical p谩ramos
Journal of Hydrological Processes, September 2020
Alicia Correa, Boris F Ochoa鈥怲ocachi, Christian Birkel, Ana Ochoa鈥怱谩nchez, Charles Zogheib, Carolina Tovar, Wouter Buytaert
Despite the importance of p谩ramos for water security, carbon storage, biodiversity, and other ecosystem services, they are highly vulnerable to human activities. However, just three decades ago, p谩ramos were severely understudied. An increasing awareness of the need for socio-eco-hydrological evidence to guide sustainable management of p谩ramos prompted action for generating data and for filling long鈥恠tanding knowledge gaps. This article by Correa et al. (2020) discusses the converging science and policy efforts happening in the p谩ramos, and outlines future research directions for the sustainable long鈥恡erm data collection that can foster their responsible conservation.
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