From pixels to grixels: a unified functional model for geographic-object-based image analysis

Geographic Object-Based Image Analysis (GEOBIA) aims to better exploit earth remotely sensed imagery by focusing on building image-objects resembling the real-world objects instead of using raw pixels as basis for classification. Due to the recentness of the field, concurrent and sometimes competing methods, terminology, and theoretical approaches are evolving. This risk of babelization has been identified as one of the central threats for GEOBIA, as it could hinder scientific discourse and the development of a generally accepted theoretical framework. This paper contributes to the definition of such ontology by proposing a general functional model of the remote sensing image analysis. The model compartmentalizes the remote sensing process into six stages: (i) sensing the earth surface in order to derive pixels which represent incomplete data about real-world objects; (ii) pre-processing the pixels in order to remove atmospheric, geometric, and radiometric distortions; (iii) grouping the pre-processed pixels (prixels) to produce image-objects (grouped pixels or grixels) at one or several scales; (iv) feature analysis to examine and measure relevant spectral, geometric and contextual properties and relationships of grixels in order to produce feature vectors (vexcels) and decision rules for subsequent discrimination; (v) assignation of grixels to pre-defined qualitative or quantitative land cover classes, thus producing pre-objects (preliminary objects); and (vi) post-processing to refine the previous results and output the geographic objects of interest. The grouping stage may be analized from two different perpectives: (i) discrete segmentation which produces well-defined image-objects, and (ii) continuous segmentation which produces image-fields with indeterminate boundaries. The proposed generic model is applied to analyze two specific GEOBIA software implementations. A functional decomposition of discrete segmentation is also discussed and tested. It is concluded that the proposed framework enhances the evaluation and comparison of different GEOBIA approaches and by this is helping to establish a generally accepted ontology

Fuzzy segmentation for geographic object-based image analysis

Image segmentation partitions remote sensing images into image objects before assigning them to categorical land cover classes. Current segmentation methods require users to invest considerable time and effort in the search for meaningful image objects. As an alternative method we propose 'fuzzy' segmentation that offers more flexibility in dealing with remote sensing uncertainty. In the proposed method, original bands are processed using regression techniques to output fuzzy image regions which express degrees of membership to target land cover classes. Contextual properties of fuzzy regions can be measured to indicate potential spectral confusion. A 'defuzzification' process is subsequently conducted to produce the categorical land cover classes. This method was tested using data sets of both high and medium spatial resolution. The results indicate that this approach is able to produce classification with satisfying accuracy and requires very little user interaction

Multi-temporal airborne remote sensing of intertidal sediment dynamics

Coastal remote sensing applications are regularly confined to single image 'snapshot' approaches which do not resolve the dynamic processes in the required temporal resolution. This paper reports the results of a project in which the dynamics of tidal sedimentation were monitored by multi-temporal airborne remote sensing in 10 minute time steps. The radiance data was then converted to estimates of suspended particulate matter loading by the inversion of a hydro-optical analytical model. The results demonstrate that multi-temporal coastal remote sensing can provide information about such dynamic processes that realistically can not be obtained by field-based research methods

Monitoring mixed sand and gravel beaches using unmanned aerial systems

Mixed sand-gravel beaches act as an efficient natural sea defence and are increasingly managed by beach recharge, which can alter the sediment size composition of such beaches and their profile response. This creates an urgent need for better information about the behaviour of mixed sand and gravel beaches after recharge. UAS promise to be a promising novel tool in this context. To test their suitability for routine surveying, we aligned an experimental UAS survey along the standard monitoring schedule that was in operation for a mixed beach in East Sussex, UK. High wind speeds at the time of deployment significantly affected the data collection, but it was possible to generate (i) a surface model using Structure-from-Motion-based photogrammetry and (ii) an image mosaic that clearly identifies the spatial patterns of the sand-gravel mix of the beach. This indicates that UAS offer substantial potential for beach monitoring. However, an unclear legal framework acts and the sensitivity of platforms to high winds sets clear limits for UAS to serve as a stand-alone monitoring tool for beach environments at the present time

Topological challenges in multispectral image segmentation

Land cover classification from remote sensing multispectral images has been traditionallyconducted by using mainly spectral information associated with discrete spatial units (i.e. pixels).Geometric and topological characteristics of the spatial context close to every pixel have been either not fully treated or completely ignored.This article provides a review of the strategies used by a number of researchers in order to include spatial and topological properties in image segmentation.­­­It is shown how most of researchers have proposed to perform -previous to classification- a grouping or segmentation of nearby pixels by modeling neighborhood relationships as 4-connected, 8-connected and (a, b) – connected graphs.In this object-oriented approach, however, topological concepts such as neighborhood, contiguity, connectivity and boundary suffer from ambiguity since image elements (pixels) are two-dimensional entities composing a spatially uniform grid cell (i.e. there are not uni-dimensional nor zero-dimensional elements to build boundaries). In order to solve such topological paradoxes, a few proposals have been proposed. This review discusses how the alternative of digital images representation based on Cartesian complexes suggested by Kovalevsky (2008) for image segmentation in computer vision, does not present topological flaws, typical of conventional solutions based on grid cells. However, such a proposal has not been yet applied to multispectral image segmentation in remote sensing. This review is part of the PhD in Engineering research conducted by the first author under guidance of the second one. This review concludes suggesting the need to research on the potential of using Cartesian complexes for multispectral image segmentation

Age-related efficiency loss of household refrigeration appliances: Development of an approach to measure the degradation of insulation properties

Despite the omnipresence of household refrigeration appliances, there is still a lack of knowledge about their age-related efficiency loss over time. Past studies provide basic evidence for increasing electricity consumption of cooling appliances with ageing but fail to investigate the associated technical wear. Concentrating on the degradation of the thermal insulation, we first determined the ageing process of sealed samples of polyurethane rigid foam by investigating changes in cell gas composition and thermal conductivity over time. Simultaneously, the main challenge was to develop an approach that investigates the age-related efficiency loss of the insulation without its destruction. This testing procedure is referred to as the Bonn method. The non-destructive Bonn method was applied to varying refrigerator models in a series of successive experiments to evaluate the insulation degradation over time. Subsequently, the physical relationship between the test value of the Bonn method and the heat transfer through the multi-layered compartment walls of domestic refrigeration appliances was established, ultimately characterising the degrading insulation in terms of increasing heat transfer. Our results give substantiated evidence that the efficiency loss of cooling appliances is greatly influenced by insulation degradation over time. The ageing of sealed samples of polyurethane rigid foam indicates a large initial increase of thermal conductivity by 15% within the first year, corresponding to a change in cell gas composition. These results are in line with those of the Bonn method, emphasising an increasing heat flow through the multi-layered compartment walls of domestic refrigerators with ageing. Therewith, the present study is of significance to a wide range of stakeholders and forms the basis for future research.BMWi, 03ET1544, ALGE: Alterungsmechanismen von Haushaltskältegeräte

Comparative beach surveys using an unmanned aerial system, ground-based GPS, terrestrial laser scanning, and airborne laser scanning

Profiles and sediment size distribution on mixed sand and gravel beaches are highly variable, both spatially and temporally, and cost-effective high-resolution monitoring schemes are needed to capture this variability. The potential for the use of UAS for coastal monitoring remains relatively untested in comparison to established remote sensing techniques. This paper reports on a field experiment in Pevensey Bay, East Sussex, England, in which simultaneous measurements were carried out using UAV-based photogrammetry, RTK-GPS, and both terrestrial and airborne laser scanning. The central objective of this research was to compare the accuracy of the TLS, ALS, and UAV-based surface modelling to draw conclusions for operational beach monitoring. The analysis was carried out through point cloud inter-comparison, comparison of point cloud performance against RTK-GPS transect data, and evaluation of differences between elevation models that were generated based on the point clouds. The point cloud comparison focused on the vertical differences between respective data sets, and showed that the UAV-based point cloud had positive offsets of 9cm (RMS 10cm) and 6cm (RMS 8cm) compared to the TLS and ALS point clouds, respectively. Analysis was also carried out to evaluate the extent to which surface sediment characteristics affected measurement accuracy of the different methods. Data comparison on beach gravel, beach sand, cobble, foreshore dry sand, foreshore wet sand and soft mud showed the best agreement between UAV, TLS and ALS data on gravel beach sections. For nearly all surface types UAV and ALS data showed better agreement than UAV to TLS data

Continental-scale assessment of the African offshore wind energy potential: spatial analysis of an under-appreciated renewable energy resource

Offshore wind energy is rapidly becoming a technology that developing countries could consider because project costs have recently fallen substantially. Further reductions are expected as the industry matures. For most African coastal states, specific information about their offshore wind potential is not available. This study aims to address this shortcoming by evaluating the technical offshore wind potential of the entire continent using spatially explicit models and long-term satellite data. Two different scenarios were developed to reflect different levels of technological maturity in the wind industry: The shallow-water, near-coast scenario 1 represented the conservative assumption that technology will not improve beyond what is available already now. The deep-water, full-exclusive economic zone (EEZ) scenario 2 assumes the operational availability of floating platforms that would allow it to access wind resources at much deeper water depths across the entire EEZ. It is emphasized that the model results are subject to a number of uncertainties and therefore should be treated as first order estimates only. Both scenarios indicate very good technical offshore wind energy potential for one third of the African coastal states, with Mozambique, South Africa, Somalia, Madagascar and Morocco exhibiting particularly good resources. More than 90% of the offshore wind resources are concentrated in coastal zones associated to three African Power Pools. These are the Southern African Power Pool (SAPP), the Eastern African Power Pool (EAPP), and the Comité Maghrébin de l'Electricité (COMELEC). A joint and integrated development within these power pools could offer a promising approach to utilising offshore wind energy in Africa

Using the second-mover advantage: how Asia could leverage a decade of European offshore wind developments

Offshore wind energy is maturing quickly and on the verge of becoming one of the most competitive renewable energy technologies. European projects in the North and Baltic Seas have pioneered the industry and the learning curve has been steep. Progress in project management and spatial marine planning approaches have led to substantial drops in both CAPEX and OPEX. Of central importance in this context is the identification of the best wind resources and to link this data to other relevant parameters such as bathymetry, sea bed condition, distance to terrestrial grid connections and potential conflicts with other marine uses such as shipping and fishing. This talk will illustrate how Asian countries could leverage their “second mover advantage” when developing their offshore wind energy potential by building on European experiences from early generation projects