Emergent Challenges for Science sUAS Data Management: Fairness through Community Engagement and Best Practices Development

Abstract

The use of small Unmanned Aircraft Systems (sUAS) as platforms for data capture has rapidly increased in recent years. However, while there has been significant investment in improving the aircraft, sensors, operations, and legislation infrastructure for such, little attention has been paid to supporting the management of the complex data capture pipeline sUAS involve. This paper reports on a four-year, community-based investigation into the tools, data practices, and challenges that currently exist for particularly researchers using sUAS as data capture platforms. The key results of this effort are: (1) sUAS captured data—as a set that is rapidly growing to include data in a wide range of Physical and Environmental Sciences, Engineering Disciplines, and many civil and commercial use cases—is characterized as both sharing many traits with traditional remote sensing data and also as exhibiting—as common across the spectrum of disciplines and use cases—novel characteristics that require novel data support infrastructure; and (2), given this characterization of sUAS data and its potential value in the identified wide variety of use case, we outline eight challenges that need to be addressed in order for the full value of sUAS captured data to be realized. We conclude that there would be significant value gained and costs saved across both commercial and academic sectors if the global sUAS user and data management communities were to address these challenges in the immediate to near future, so as to extract the maximal value of sUAS captured data for the lowest long-term effort and monetary cost.

Characterising Termite Mounds in a Tropical Savanna with UAV Laser Scanning

“…Moreover, the flexibility and limited regulation of UAVs compared to aerial acquisitions from aeroplanes makes them very attractive to use. Because the use of UAVs for remote sensing is a relatively new advancement, it nevertheless comes with its challenges, especially concerning data management, which often lacks standardized protocols [19]. Other current limitations of UAVs are the limited battery life and the limited carry-on weight.…”

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra

“…First, simultaneous collection of data on multiple properties (e.g., spectral, structural, thermal, etc.) remains challenging due to technical issues (e.g., payload and data management) related to assembling multiple types of off-the-shelf instrumentations on a single UAS [61,62]. Second, the Arctic is characterized by remote and harsh environments, which leads to a high risk and cost for operating UASs.…”

Making Drone Data FAIR Through a Community-Developed Information Framework

“…Small Uncrewed Aircraft Systems (sUAS) -commonly known as drones -are an increasingly important tool for data collection in many scientific fields. However, best practices for sUAS data capture and management are still being developed, and require further refinement and adoption 1 . Researchers in fields such as wildlife monitoring 2 , vegetation monitoring 3 , atmospheric sciences 4 , and in the assessment of built environments and energy infrastructure 5 have all called for the development of sUAS data and metadata best practices.…”

“…Despite broad consensus that data and metadata best practices are needed, there is still much work to be done developing new standards or practices that address the complex data pipeline and products typical of a sUAS project (see Wyngaard et al. 1 for a detailed discussion of this and Figure 1 for a high level view of a typical sUAS research workflow). Furthermore, while practices, standards, ontologies, and tools of relevance and value exist due to prior work and parallel advances; none are either sufficient or directly reusable in addressing the practical needs of all aspects of sUAS data management, nor has any collection of these become a common or standardise approach to addressing all aspects of sUAS workflows and data products.…”