Point clouds captured from Unmanned Aerial Systems are increasingly relied upon to provide information describing the structure of forests. The quality of the information derived from these point clouds is dependent on a range of variables, including the type and structure of the forest, weather conditions and flying parameters. A key requirement to achieve accurate estimates of height based metrics describing forest structure is a source of ground information. This study explores the availability and reliability of ground surface points available within point clouds captured in six forests of different structure (canopy cover and height), using three image capture and processing strategies, consisting of nadir, oblique and composite nadir/oblique image networks. The ground information was extracted through manual segmentation of the point clouds as well as through the use of two commonly used ground filters, LAStools lasground and the Cloth Simulation Filter. The outcomes of these strategies were assessed against ground control captured with a Total Station. Results indicate that a small increase in the number of ground points captured (between 0 and 5% of a 10 m radius plot) can be achieved through the use of a composite image network. In the case of manually identified ground points, this reduced the root mean square error (RMSE) error of the terrain model by between 1 and 11 cm, with greater reductions seen in plots with high canopy cover. The ground filters trialled were not able to exploit the extra information in the point clouds and inconsistent results in terrain RMSE were obtained across the various plots and imaging network configurations. The use of a composite network also provided greater penetration into the canopy, which is likely to improve the representation of mid-canopy elements.

Marine plastic debris (MPD) is a globally relevant environmental challenge, with an estimated 8 million tons of synthetic debris entering the marine environment each year. Plastic has been found in all parts of the marine environment, including the surface layers of the ocean, within the water column, in coastal waters, on the benthic layer and on beaches. While research on detecting MPD using remote sensing is increasing, most of it focuses on detecting floating debris in open waters, rather than detecting MPD on beaches. However, beaches present challenges that are unique from other parts of the marine environment. In order to better understand the spectral properties of beached MPD, we present the SWIR reflectance of weathered MPD and virgin plastics over a sandy substrate. We conducted spectral feature analysis on the different plastic groups to better understand the impact that polymers have on our ability to detect synthetic debris at sub-pixel surface covers that occur on beaches. Our results show that the minimum surface cover required to detect MPD on a sandy surface varies between 2–8% for different polymer types. Furthermore, plastic composition affects the magnitude of spectral absorption. This suggests that variation in both surface cover and polymer type will inform the efficacy of beach litter detection methods.

Floating and washed ashore marine plastic debris (MPD) is a growing environmental challenge. It has become evident that secluded locations including the Arctic, Antarctic, and remote islands are being impacted by plastic pollution generated thousands of kilometers away. Optical remote sensing of MPD is an emerging field that can aid in monitoring remote environments where in-person observation and data collection is not always feasible. Here we evaluate MPD spectral features in the visible to shortwave infrared regions for detecting varying quantities of MPD that have accumulated on beaches using a spectroradiometer. Measurements were taken from a range of in situ MPD accumulations ranging from 0.08% to 7.94% surface coverage. Our results suggest that spectral absorption features at 1215 nm and 1732 nm are useful for detecting varying abundance levels of MPD in a complex natural environment, however other absorption features at 931 nm, 1045 nm and 2046 nm could not detect in situ MPD. The reflectance of some in situ MPD accumulations was statistically different from samples that only contained organic debris and sand between 1.56% and 7.94% surface cover; however other samples with similar surface cover did not have reflectance that was statistically different from samples containing no MPD. Despite MPD being detectable against a background of sand and organic beach debris, a clear relationship between the surface cover of MPD and the strength of key absorption features could not be established. Additional research is needed to advance our understanding of the factors, such as type of MPD assemblage, that contribute to the bulk reflectance of MPD contaminated landscapes.

A field spectroscopy metadata standard is defined as those data elements that explicitly document the spectroscopy dataset and field protocols, sampling strategies, instrument properties and environmental and logistical variables. Standards for field spectroscopy metadata affect the quality, completeness, reliability, and usability of datasets created in situ. Currently there is no standardized methodology for documentation of in situ spectroscopy data or metadata. This paper presents results of an international experiment comprising a web-based survey and expert panel evaluation that investigated critical metadata in field spectroscopy. The survey participants were a diverse group of scientists experienced in gathering spectroscopy data across a wide range of disciplines. Overall, respondents were in agreement about a core metadataset for generic campaign metadata, allowing for a prioritization of critical metadata elements to be proposed including those relating to viewing geometry, location, general target and sampling properties, illumination, instrument properties, reference standards, calibration, hyperspectral signal properties, atmospheric conditions, and general project details. Consensus was greatest among individual expert groups in specific application domains. The results allow the identification of a core set of metadata fields that enforce long term data storage and serve as a foundation for a metadata standard. This paper is part one in a series about the core elements of a robust and flexible field spectroscopy metadata standard.

Reproducibility is widely regarded as crucial for scientific studies, yet there is still a lack of reproducibility in geospatial research. New sources of crowdsourced geoinformation provide new opportunities, but also complicate the reproducibility situation. Consequently, there is untapped potential in the domain of disaster response to reuse scientific methodology. Shared, executable scientific workflows can help in improving reproducibility. In this paper, we created reproducible scientific workflows for disaster response from three published studies using geosocial media sources. They have been adapted to a scientific workflow management system to investigate and evaluate their suitability for the creation of geospatial footprints of wildfire events from Twitter data. We investigated how scientific workflows adapt to various analytical processes and compared their performance using MODIS active fires data as ground truth. A systematic qualitative and quantitative evaluation demonstrated that scientific workflows can help increase the reproducibility of geospatial analytics.

This paper presents the proposed criteria for measuring the quality and completeness of field spectroscopy metadata in a spectral archive. Definitions for metadata quality and completeness for field spectroscopy datasets are introduced. Unique methods for measuring quality and completeness of metadata to meet the requirements of field spectroscopy datasets are presented. Field spectroscopy metadata quality can be defined in terms of (but is not limited to) logical consistency, lineage, semantic and syntactic error rates, compliance with a quality standard, quality assurance by a recognized authority, and reputational authority of the data owners/data creators. Two spectral libraries are examined as case studies of operationalized metadata policies, and the degree to which they are aligned with the needs of field spectroscopy scientists. The case studies reveal that the metadata in publicly available spectral datasets are underperforming on the quality and completeness measures. This paper is part two in a series examining the issues central to a metadata standard for field spectroscopy datasets.