Geostatistical Assessment of Ice Content Distribution Within the Glacier Bonnard

The Glacier Bonnard is a rock glacier located in the State of Valais, Switzerland. It overhangs a settlement and its slow downward constant creep constitutes an environmental hazard. It is therefore important to understand the glacier’s internal structure, particularly in terms of ice content, in order to evaluate its current global dynamic and future evolution. Following preliminary geophysical investigations, several boreholes have been drilled to measure the thickness of the glaciated mass and the vertical distribution of lithology and ice content. These new data are helpful in assessing the amount of ice within the Glacier Bonnard. Two geostatistical modeling approaches are considered: a direct modeling of ice content and an indirect approach linking together lithology and ice content by the use of the plurigaussian algorithm. Comparisons between these approaches are made in terms of ice content prediction and of global ice mass within the sampled area; they underline the benefit of the geostatistical modeling and particularly the advantages of the indirect approach.     

Monitoring US agriculture: the US Department of Agriculture,National Agricultural Statistics Service,Cropland Data Layer Program

The National Agricultural Statistics Service (NASS) of the US Department of Agriculture (USDA) produces the Cropland Data Layer (CDL) product, which is a raster-formatted, geo-referenced, crop-specific, land cover map. CDL program inputs include medium resolution satellite imagery, USDA collected ground truth and other ancillary data, such as the National Land Cover Data set. A decision tree-supervised classification method is used to generate the freely available state-level crop cover classifications and provide crop acreage estimates based upon the CDL and NASS June Agricultural Survey ground truth to the NASS Agricultural Statistics Board. This paper provides an overview of the NASS CDL program. It describes various input data, processing procedures, classification and validation, accuracy assessment, CDL product specifications, dissemination venues and the crop acreage estimation methodology. In general, total crop mapping accuracies for the 2009 CDLs ranged from 85% to 95% for the major crop categories.     

Infometric and statistical diagnostics to provide artificially-intelligent support for spatial analysis: the example of interpolation

The wider uptake of GIS tools by many application areas outside GIScience means that many newer users of GIS will have high-level knowledge of the wider task, and low-level knowledge of specific system commands as given in reference manuals. However, these newer users may not have the intermediate knowledge that experts in GI science have gained from working with GI systems over several years. Such intermediate knowledge includes an understanding of the assumptions implied by the use of certain functions, and an appreciation of how to combine functions appropriately to create a workflow that suits both the data and overall goals of the geographical analysis task.

Focusing on the common but non-trivial task of interpolating spatial data, this paper considers how to help users gain the necessary knowledge to complete their task and minimise the possibility of methodological error. We observe that both infometric (or cognitive) knowledge and statistical knowledge are usually required to find a solution that jointly and efficiently meets the requirements of a particular user and data set. Using the class of interpolation methods as an example, we outline an approach that combines knowledge from multiple sources and argue the case for designing a prototype ‘intelligent’ module that can sit between a user and a given GIS.

The knowledge needed to assist with the task of interpolation is constructed as a network of rules, structured as a binary decision tree, that assist the user in selecting an appropriate method according to task-related knowledge (or ‘purpose’) and the characteristics of the data sets. The decision tree triggers exploratory diagnostics that are run on the data sets when a rule requires to be evaluated. Following evaluation of the rules, the user is advised which interpolation method might be and should not be considered for the data set. Any parameters required to interpolate the particular data set (e.g. a distance decay parameter for Inverse Distance Weighting) are also supplied through subsequent optimisation and model selection routines. The rationale of the decision process may be examined, so the ‘intelligent interpolator’ also acts as a learning tool.     

Winds and tides of Ligeia Mare,with application to the drift of the proposed time TiME (Titan Mare Explorer) capsule

We use two independent General Circulation Models (GCMs) to estimate surface winds at Titan’s Ligeia Mare (78° N, 250° W), motivated by a proposed mission to land a floating capsule in this ～500 km hydrocarbon sea. The models agree on the overall magnitude (～0.5–1 m/s) and seasonal variation (strongest in summer) of windspeeds, but details of seasonal and diurnal variation of windspeed and direction differ somewhat, with the role of surface exchanges being more significant than that of gravitational tides in the atmosphere. We also investigate the tidal dynamics in the sea using a numerical ocean dynamics model: assuming a rigid lithosphere, the tidal amplitude is up to ～0.8 m. Tidal currents are overall proportional to the reciprocal of depth—with an assumed central depth of 300 m, the characteristic tidal currents are ～1 cm/s, with notable motions being a slosh between Ligeia’s eastern and western lobes, and a clockwise flow pattern.We find that a capsule will drift at approximately one tenth of the windspeed, unless measures are adopted to augment the drag areas above or below the waterline. Thus motion of a floating capsule is dominated by the wind, and is likely to be several km per Earth day, a rate that will be readily measured from Earth by radio navigation methods. In some instances, the wind vector rotates diurnally such that the drift trajectory is epicyclic.     

Standard chemical‐based tephra extraction methods significantly alter the geochemistry of volcanic glass shards

The chemical compositions of tephra shards are widely utilised in a myriad of disciplines, including volcanology, petrology, tephrochronology, palaeoecology and climate studies. Previous research has raised concerns over the possible chemical alteration of microscopic (<100 µm) volcanic glass shards through standard extraction procedures, such as the widely used acid digestion method. This study subjects 10 samples of well‐characterised volcanic glasses ranging from basalt to rhyolite to three common methods used in the extraction of volcanic material from lake sediments and peats. The major element geochemistry of each sample was analysed and compared with a control group. The results of this test indicate that basaltic and andesitic glasses are highly susceptible to chemical alteration, particularly to the concentrated corrosive materials used in acid and base digestion techniques. PERMANOVA analysis of the variation within groups suggests that the oxides most susceptible to variation are alkalis from groups I and II (K₂O, Na₂O, CaO, MgO) and SiO₂, and the most stable oxides are Al₂O₃ and FeO. Felsic glasses are considerably less susceptible to alteration by both acidic (HCl, HNO₃, H₂SO₄) and alkaline (KOH) digestions. Our findings have important implications for interpreting the geochemistry of volcanic glasses. Copyright © 2019 John Wiley & Sons, Ltd.     

Reflective practice for marine planning: A case study of marine nature-based tourism partnerships

An essential component of ecosystem-based approaches in coastal zone management and the emerging field of marine planning are partnerships and collaborations between a range of multi-sector organisations and individuals. Ensuring that partnerships are effective is a priority for those responsible for planning and management in coastal and marine environments. Current partnership evaluation approaches, however, tend to view effectiveness as the cumulative end result of a set of variables acting in a linear process at a specific point in time. Given that governance and participation are acknowledged as non-linear and multifaceted processes, more reflective and nuanced approaches that take account of the dynamic, multidimensional and geographically embedded nature of the collaborative process are needed. This paper proposes a new framework for partnership evaluation based on policy narratives and indicators, and demonstrates the potential of the approach using three case studies of partnerships focused upon marine nature-based tourism. The insights from this research have direct relevance to the agencies and organisations responsible for delivering integrated coastal management, including marine spatial planning.     

The changing environment of fisheries policy in Europe

This paper presents how environmental concerns emanating outside the Common Fisheries Policy (CFP) are increasingly setting the stage for EU fisheries management. This is illustrated via what is termed the exogenous entrance of environmental concerns through the implementation of directives in EU policy. More endogenous entrance of environmental concerns occurs via stakeholder participation in Regional Advisory Councils (RACs) as well as market mechanisms, such as ecolabelling and traceability. This study discusses how these latter channels of environmental concern may have become a more potent and efficient way of reaching environmental goals, outside of the primacy of the CFP.     

Detecting active comets in the SDSS

Using a sample of serendipitously discovered active comets in the Sloan Digital Sky Survey (SDSS), we develop well-controlled selection criteria for greatly increasing the efficiency of comet identification in the SDSS catalogs. After follow-up visual inspection of images to reject remaining false positives, the total sample of SDSS comets presented here contains 19 objects, roughly one comet per 10 million other SDSS objects. The good understanding of selection effects allows a study of the population statistics, and we estimate the apparent magnitude distribution to r∼18, the ecliptic latitude distribution, and the comet distribution in SDSS color space. The most surprising results are the extremely narrow range of colors for comets in our sample (e.g. root-mean-square scatter of only ∼0.06 mag for the g-r color), and the similarity of comet colors to those of jovian Trojans. We discuss the relevance of our results for upcoming deep multi-epoch optical surveys such as the Dark Energy Survey, Pan-STARRS, and the Large Synoptic Survey Telescope (LSST), and estimate that LSST may produce a sample of about 10,000 comets over its 10-year lifetime.     

Assessing Data Completeness of VGI through an Automated Matching Procedure for Linear Data

New, free and fast growing spatial data sources have appeared online, based on Volunteered Geographic Information (VGI). OpenStreetMap (OSM) is one of the most representative projects of this trend. Its increasing popularity and density makes the study of its data quality an imperative. A common approach is to compare OSM with a reference dataset. In such cases, data matching is necessary for the comparison to be meaningful, and is usually performed manually at the data preparation stage. This article proposes an automated feature‐based matching method specifically designed for VGI, based on a multi‐stage approach that combines geometric and attribute constraints. It is applied to the OSM dataset using the official data from Ordnance Survey as the reference dataset. The results are then used to evaluate data completeness of OSM in several case studies in the UK.     

Accounting for Error When Modelling with Time Series Data: Estimating the Development of Crop Pests Throughout the Year

In order to attach some statement of reliability to mesoscale maps of how pest risk may develop over time, methods were developed to enable the detection and evaluation of errors in predictions that arise from the use of input data series from remote point sources. Firstly, we investigated how predicted model results may differ as a result of the ordering of the spatial interpolation and the model procedures. Principles of logic were used to detect errors occurring in the daily sequences of predicted pest development. Analyses of spatial autocorrelation within the gridded results showed that areas where a pest was predicted to reach a certain stage of development become more fragmented as a model run progressed over time. We identified that the less intensive approach of running a model only at data points and subsequently interpolating these to a grid can, in some cases, result in errors of logic and unrealistic degrees of autocorrelation. These errors occurred particularly when mapping a non-indigenous, marginal, pest at the later stages of its development. As a strategy for error evaluation, deterministic process models were run using point-based estimates of interpolated daily temperature to give RMS data errors at the sample points. This enabled us to investigate how the component of error related to sparsely distributed point data contributed to errors in the gridded estimates of pest development over time. The error detection and evaluation methods outlined are tractable and applicable to a wide variety of cases where point based models running over multiple time steps are extended to provide spatially continuous, landscape-wide, mappable results.