With the increasing role that unmanned aerial systems (UAS) are playing in data collection for environmental studies, two key challenges relate to harmonizing and providing standardized guidance for data collection, and also establishing protocols that are applicable across a broad range of environments and conditions. In this context, a network of scientists are cooperating within the framework of the Harmonious Project to develop and promote harmonized mapping strategies and disseminate operational guidance to ensure best practice for data collection and interpretation. The culmination of these efforts is summarized in the present manuscript. Through this synthesis study, we identify the many interdependencies of each step in the collection and processing chain, and outline approaches to formalize and ensure a successful workflow and product development. Given the number of environmental conditions, constraints, and variables that could possibly be explored from UAS platforms, it is impractical to provide protocols that can be applied universally under all scenarios. However, it is possible to collate and systematically order the fragmented knowledge on UAS collection and analysis to identify the best practices that can best ensure the streamlined and rigorous development of scientific products.

Determining the timing of post-Caledonian brittle faulting in northern Norway is important for the understanding of the extensional tectonic evolution of the north

Colour aerial photography and multi-spectral imagery acquired from airborne platforms for the River Tummel, Scotland, was used in conjunction with field survey to assess the feasibility of monitoring hydromorphology and human alteration within the river corridor. The study was undertaken to investigate the possibility of remotely sensing the physical status of a nation's rivers at the national scale to comply with the requirement of the European Water Framework Directive. Visual assessment and unsupervised and supervised automated classifications of the imagery were undertaken and compared with field survey data.In the absence of overhanging vegetation canopies most features above the water line of interest were visible on the imagery. Below the water line, morphology and substrate composition together with bank materials on vertically cut banks are less easily detected. The overall accuracy of automated classification procedures, compared to field survey, was 60% for the colour aerial photography and 68% for the multi-spectral imagery. Supervised classification was superior to unsupervised classification procedures. Sun glint on water surfaces and shadows caused by high banks, trees and buildings were observed as the cause of most misclassification of features.Overall, the study demonstrates that remotely sensed digital imagery has the potential to allow panoptic mapping of river hydromorphology and human impacts. The possibilities and constraints, in light of the findings of this study, are discussed. In the context of new legislation which requires environmental protection agencies to have robust tools for monitoring the physical status, as part of meeting the objective of good ecological status, of rivers across an entire nation, remote sensing appears to provide a way forward.

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Mining typically involves extensive areas where environmental monitoring is spatially sporadic. New remote sensing techniques and platforms such as Structure from Motion (SfM) and unmanned aerial vehicles (UAVs) may offer one solution for more comprehensive and spatially continuous measurements. We conducted UAV campaigns in three consecutive summers (2015)(2016)(2017) at a sub-Arctic mining site where production was temporarily suspended. The aim was to monitor a 0.5 km 2 tailings impoundment and measure potential subsidence of tailings. SfM photogrammetry was used to produce yearly topographical models of the tailings surface, which allowed the amount of surface displacement between years to be tracked. Ground checkpoints surveyed in stable areas of the impoundment were utilized in assessing the vertical accuracy of the models. Observed surface displacements were linked to a combination of erosion, tailings settlement, and possible compaction of the peat layer underlying the tailings. The accuracy obtained indicated that UAV-assisted monitoring of tailings impoundments is sufficiently accurate for supporting impoundment management operations and for tracking surface displacements in the decimeter range.

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Treatment peatlands are water purification systems located on existing mires. They are commonly used to treat different types of waters, ranging from municipal wastewaters to mine effluent. This study evaluated the capacity of unmanned aerial vehicle (UAV)-based thermal infrared (TIR) imaging, color infrared imaging, and stable water isotopes as a combined method for monitoring the functioning of a treatment peatland purifying mine process effluent water under boreal conditions in northern Finland. The results showed that TIR was an efficient tool for pinpointing cold groundwater seepage points in the peatland area that were not otherwise visible. Color infrared imaging was used to define Normalized Difference Vegetation Index (NDVI), as an indicator of plant health in the treatment area. A NDVI map of the area, measured on a day representing the main growing season (summer, +12 °C day temperature), revealed areas with stressed coniferous trees. This was probably due to excess water in these areas, resulting from successful spread of the process effluent water to the treatment peatland. Stable water isotopes were able to spatially differentiate the treated process effluent water, surface waters, and groundwater in different parts of the treatment peatland. This first attempt at combining these methods in monitoring of treatment peatlands was promising, as the results obtained with different methods complemented each other. While they produce only a snapshot of prevailing conditions, all three methods, singly and in combination, could be valuable tools in treatment peatland management.