A Range of Earth Observation Techniques for Assessing Plant Diversity

AbstractVegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation diversity using RS

Using high-resolution LiDAR data to quantify the three-dimensional structure of vegetation in urban green space

The spatial arrangement and vertical structure of vegetation in urban green spaces are key factors in determining the types of benefits that urban parks provide to people. This includes opportunities for recreation, spiritual fulfilment and biodiversity conservation. However, there has been little consideration of how the fine-scale spatial and vertical structure of vegetation is distributed in urban parks, primarily due to limitations in methods for doing so. We addressed this gap by developing a method using Light Detection and Ranging (LiDAR) data to map, at a fine resolution, tree cover, vegetation spatial arrangement, and vegetation vertical structure. We then applied this method to urban parks in Brisbane, Australia. We found that parks varied mainly in their amount of tree cover and its spatial arrangement, but also in vegetation vertical structure. Interestingly, the vertical structure of vegetation was largely independent of its cover and spatial arrangement. This suggests that vertical structure may be being managed independently to tree cover to provide different benefits across urban parks with different levels of tree cover. Finally, we were able to classify parks into three distinct classes that explicitly account for both the spatial and vertical structure of tree cover. Our approach for mapping the three-dimensional vegetation structure of urban green space provides a much more nuanced and functional description of urban parks than has previously been possible. Future research is now needed to quantify the relationships between vegetation structure and the actual benefits people derive from urban green space.</p