Abstract
AbstractDuring the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi‐resolution information for analysis. Climate change, land‐use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high‐density, and high‐resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio‐Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross‐site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio‐environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data.
Highlights
Pressing societal challenges at the intersection of human and natural systems, such as climate change, food insecurity, and biodiversity loss, have made the need to holistically analyze socioenvironmental problems more relevant than ever before
The mosaics of high spatial resolution orthorectified RGB camera imagery offer additional information of the type that is increasingly used for various applications extending far beyond ecology, including mapping crop type and yield (Jain et al 2019), flood mapping (Bonafilia et al 2020), infrastructure and transportation (Tan 2020), and economic indicators (Jean et al 2016)
Another important aspect of AOP data is that the light detection and ranging (LiDAR), imaging spectroscopy, and high spatial resolution RGB measurements are all collocated and collected concurrently, enabling direct comparison and integration of data streams, providing a powerful opportunity to derive additional information and data products (Table 1)
Summary
Pressing societal challenges at the intersection of human and natural systems, such as climate change, food insecurity, and biodiversity loss, have made the need to holistically analyze socioenvironmental problems more relevant than ever before. Mounted on an appropriate platform (unmanned aircraft system, aircraft, satellite), LiDAR and imaging spectroscopy data can be collected at a chosen scale that is relevant for a given SES research question Because these technologies advanced relatively recently and are costly to employ, a rich temporal and spatial archive of data similar to that provided by other remote sensing datasets (e.g., the Landsat series of satellites, in operation since the mid-1980s) remains lacking. NEON AOP data offer high spatial resolution information repeated regularly (minimum of once per year) at preselected sites that cover regional scales (~100 km2) These data include LiDAR- and hyperspectral-derived measurements of ecosystem structure and function (e.g., vegetation height or leaf nitrogen concentrations), which have the potential to be of great value to SES researchers, despite the ecological focus of the network’s design. The lack of availability of these types of data has prohibited inquiries in the past
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