Stuart Marsh

Assessment of Glacier Volume Change Using ASTER-Based Surface Matching of Historical Photography

Glaciated regions are known to be particularly sensitive to climate change. Historical archives of glacier volume change are important, as they provide context for present-day changes. Although photogrammetric archives exist for many regions, their usefulness is often limited by a lack of contemporary ground control. High quality digital elevation models (DEMs) underpin a range of change analysis activities. This paper presents a cost-effective solution which utilizes Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEMs as control for the scaling and orientation of archival data sets. Instead of relying upon ground-control points, a robust surface matching algorithm is employed to automatically determine the transformation required to register two overlapping DEMs. Through application to the Slakbreen glacier system in Svalbard, Norway, the strategy is assessed by first matching an ASTER DEM to a fixed lidar reference surface. This demonstrates that ASTER DEMs are effectively correct in scale, supporting their use as a control surface. The second stage of the research implements this by matching an aerial photogrammetric DEM to an ASTER reference surface. Resultant volumetric and annual elevation change rates are compared to those derived from lidar data, which are considered in this paper as a truth data set. ASTER-based matching produced a mean annual elevation change rate of -4.12 ma-1, compared to a value of -4.11 ma-1 derived from the lidar data. In volumetric terms, this equates to a difference of 0.6%. A major advantage of this approach is the near-global coverage offered by ASTER data and the opportunity that this presents for remote glacial change analysis over regional extents.

Mexico City land subsidence in 2014–2015 with Sentinel-1 IW TOPS: Results using the Intermittent SBAS (ISBAS) technique

Differential Interferometric Synthetic Aperture Radar (DInSAR) can be considered as an efficient and cost effective technique for monitoring land subsidence due to its large spatial coverage and high accuracy provided. The recent commissioning of the first Sentinel-1 satellite offers improved support to operational surveys using DInSAR due to regular observations from a wide-area product. In this paper we show the results of an intermittent small-baseline subset (ISBAS) time-series analysis of 18 Interferometric Wide swath (IW) products of a 39,000 km2 area of Mexico acquired between 3 October 2014 and 7 May 2015 using the Terrain Observation with Progressive Scans in azimuth (TOPS) imaging mode. The ISBAS processing was based upon the analysis of 143 small-baseline differential interferograms. After the debursting, merging and deramping steps necessary to process Sentinel-1 IW roducts, the method followed a standard approach to the DInSAR analysis. The Sentinel-1 ISBAS results confirm the magnitude and extent of the deformation that was observed in Mexico City, Chalco, Ciudad Nezahualcoyotl and Iztapalapa by other C-band and L-band DInSAR studies during the 1990s and 2000s. Subsidence velocities from the Sentinel-1 analysis are, in places, in excess of -24 cm/year along the satellite line-of-sight, equivalent to over ~-40 cm/year vertical rates. This paper demonstrates the potential of Sentinel-1 IW TOPS imagery to support wide-area DInSAR surveys over what is a very large and diverse area in terms of land cover and topography.

Seamless pedestrian positioning and navigation using landmarks

Many navigation services, such as car navigation services, provide users with praxic navigational instructions (such as “turn left after 200 metres, then turn right after 150 metres”), however people usually associate directions with visual cues (e.g. “turn right at the square”) when giving navigational instructions in their daily conversations. Landmarks can play an equally important role in navigation and routing services. Landmarks are unique and easy-to-recognise and remember features; therefore, in order to remember when exploring an unfamiliar environment, they would be assets. In addition, Landmarks can be found both indoors and outdoors and their locations are usually fixed. Any positioning techniques which use landmarks as reference points can potentially provide seamless (indoor and outdoor) positioning solutions. For example, users can be localised with respect to landmarks if they can take a photograph of a registered landmark and use an application for image processing and feature extraction to identify the landmark and its location. Landmarks can also be used in pedestrian-specific path finding services. Landmarks can be considered as an important parameter in a path finding algorithm to calculate a route passing more landmarks (to make the user visit a more tourist-focussed area, pass along an easier-to-follow route, etc.). Landmarks can also be used as a part of the navigational instructions provided to users; a landmark-based navigation service makes users sure that they are on the correct route, as the user is reassured by seeing the landmark whose information/picture has just been provided as a part of navigational instruction. This paper shows how landmarks can help improve positioning and praxic navigational instructions in all these ways.

A Robust Surface Matching Technique for Integrated Monitoring of Coastal Geohazards

At the dynamic coastal fringe, numerous processes interact with local morphology. In soft-cliff environments, this can often lead to the occurrence of coastal geohazards. These can pose a major threat to property and cultural heritage, and an effective monitoring strategy is therefore essential. While contemporary monitoring techniques have been applied, these are often unsuitable in isolation. This paper presents an integrated approach, with the development of weighted surface matching software enabling reliable dataset fusion and multi-temporal change detection, even where significant surface differences exist. Evaluation of this approach is presented and discussed.

Identification of materials related to acid mine drainage using multi-source spectra at S. Domingos Mine, southeast Portugal

Imaging spectroscopy (IS) can identify target materials at both mineralogical and geochemical levels. Therefore, in environmental applications, it can be used to assess contamination derived from mining activities, moving from contamination sources along pathways to receptors as acid mine drainage (AMD). This can be based on the spectra of specific assemblages of minerals from spectral libraries, which can indicate pH values at the time of their generation and the subsequent acid-generating potential. Alternatively, field spectral measurements can be used as input data for mapping algorithms. This study presents a new methodological approach to improving the results for mapping contamination sources and pathways, by combining multisource spectra from both these approaches at different scales. In addition to the mineralogical libraries and field spectra already mentioned, additional end-member spectra that are extracted from IS data are used so as to highlight particular site phenomena otherwise undetected by the two previous approaches. The highly correlated spectra are then used as input to the Spectral Angle Mapper algorithm, to establish a map of local field spectra and also one from image end-members. The intersection of the two maps results in an improved map, assigned in terms of correlation ≥0.8 of mineralogical assemblages focused on AMD indicators. This methodology was tested in the abandoned S. Domingos Mine, in southeast Portugals Iberian Pyrite Belt, with AMD caused by long-term exploitation of volcanogenic massive sulphide deposits. Data from the HyMap™ sensor covered the area, and field spectroradiometric measurements were undertaken and analysed for mineralogical and geochemical content. A flightline containing the open pit was processed according to the aforementioned methodology, focusing directly on the target of interest and minimizing errors. The final map displays the mineralogical assemblage correlations ≥0.8 of variable pH indicators, particularly isolating a low-pH combination of significance to the contamination in the area.

Remote thermal IR surveying to detect abandoned mineshafts in former mining areas

In former mining areas it is critical to locate unknown, abandoned mineshafts prior to the development of a site. Abandoned mineshafts are ground disturbances that have very localized effects on the morphology and the physical, chemical, drainage and moisture properties of the surface geological materials and thus thermo-physical properties. Remotely sensed thermal IR surveys provide the potential for a rapid, inexpensive and non-intrusive technique for mineshaft detection. The key parameters of thermal IR radiation and the application of remote thermal IR surveys to planning are described, using case histories from former mining areas in Lancashire, Yorkshire and Nottinghamshire. Field-measured IR temperature differences correlated well with different ground conditions caused by changes in vegetation, disturbance, compaction and moisture-drainage regimes. A thermal anomaly over an area of c. 6 m2 above a known mineshaft was characterized by traces of methane and temperatures higher by 0.5–1 °C than those of the adjacent ground surface. Using thermal IR images, collected with the Daedalus 1260 Airborne Thematic Mapper, a scheme was developed to classify and map mineshafts with and without any observed visual characteristics. When applied using thermal imagery obtained from commercial flights the scheme identified several potential sites of abandoned mineshafts in an area designated for the redevelopment of the Nottingham Business Park, East Midlands. The thermal anomalies were associated with minor topographic features such as mounds, depressions and dereliction, as well as compositional features caused by coal enrichment and Coal Measures mudstone infill. These features had very little surface expression and were confirmed only using soil stripping.

Elevation Models for Geoscience

Elevation data are a critical element in most geoscience applications. From geological mapping to modelling Earth systems and processes geologists need to understand the shape of the Earths surface. Vast amounts of digital elevation data exist, from large-scale global to smaller scale regional datasets, and many datasets have been merged to improve scale and accuracy. For each application, decisions are made on which elevation data to use driven by cost, resolution and accuracy. This publication shows the current status of available digital elevation data and illustrates the key applications. The types of data assessed include: ASTER stereo satellite imagery, Shuttle Radar Topographic Mapping data, airborne laser and radar such as NEXTMap, and Multibeam Bathymetry. Applications covered include: glacial deposits, landslides, coastal erosion and other geological hazards. Technical issues discussed include: accuracy analysis, derived product creation, software comparisons and copyright considerations. This volume is a comprehensive look at elevation models for geoscience.

Small Baseline Subset (SBAS) pixel density vs. geology and land use in semi-arid regions in Syria

36 ENVISAT ASAR images acquired in 2002 to 2010 along descending passes with nominal revisiting time of 35 days were processed over the whole region of Homs, western Syria, by implementing the low-pass Small Baseline Subset (SBAS) technique. More than 280,000 coherent pixels with ~100m ground resolution were obtained. We analysed pixel spatial distribution in respect of local geology and land use, to assess to what extent these factors can influence the performance of an interferometric deformation analysis in semi-arid environment. Filtering out the amount of pixels associated with the urban fabric of Homs and surrounding villages, it is apparent that limestone and marl units are less prone to generate coherent pixels if compared with the basalt units in the north-western sector of the processed region. The latter resulted in pixel density of ~50-60 pixels/km2, which is comparable with that found over urban settlements and man-made structures.

Low pH detection in SPECIM EAGLE-HAWK using field spectra at S. Domingos Mine, SE Portugal: Preliminary results

To detect the Acid Mine Drainage (AMD) in Imaging Spectroscopy (IS) data, field spectral measurements gathered contemporaneously were selected in function of their high correlation with relevant minerals of standard spectral libraries. Working as a spectra selector, the high correlation values at threshold ≥0.8 are inputted to a full pixel based classifier measuring the angle between spectra (Spectral Angle Mapper, SAM). This methodology is applied to SPECIM EAGLE-HAWK captured over old S. Domingos mine area in 2007. Field measurements were undertaken with an ASDFieldSpecPro spectroradiometer for calibration and on materials previously known as AMD indicators. The mining history dates back to pre-roman times, with an intensive exploitation of Volcanogenic Massive Sulphide deposits, leading to a significant environmental footprint. The isolation of mineralogical assemblages of pH<3 delineates the hot spots at threshold ≥ 0.8, mostly confined to acidic ponds and specific waste piles.

Comparing experts and novices in Martian surface feature change detection and identification

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided “expert” data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who want to use crowd-sourcing for similar scientific purposes, particularly for the supervised training of computer algorithms, and inform the scope and design of future projects.