Petra Helmholz

Semi-automatic quality control of topographic data sets

The usefulness and acceptance of geo-information systems are mainly depends on the quality of the underlying geo-data. This paper describes a novel system for semiautomatic quality control of existing topographic geo-spatial data via automatic image analysis. The goal is to reduce the manual effort for quality control of a GIS database to a minimum. The core of the system is a semantic network in which different image analysis operators can be included. The image analysis operators are created for specific applications, i.e., the quality control of specific object classes which are most relevant. Images which can be used in the system are aerial images, high-resolution satellite imagery, and low-resolution satellite imagery. A prototype of the system has been in use for several years at public mapping organizations. From the experience gained during this time, we give a detailed report on the system performance and an evaluation of the results.

Automatic qualtiy control of cropland and grasland GIS objects using IKONOS satellite imagery

As a consequence of the wide-spread application of digital geo-data in Geoinformation Systems (GIS), quality control has become increasingly important. A high degree of automation is required in order to make quality control efficient enough for practical application. In order to achieve this goal we have designed and implemented a semi-automatic technique for the verification of cropland and grassland GIS objects using 1 m pan-sharpened multispectral IKONOS imagery. The approach compares the GIS objects and compares them with data derived from high resolution remote sensing imagery using image analysis techniques. Textural, structural, and spectral features are assessed in a classification based on Support Vector Machines (SVM) in order to check whether a cropland or grassland object in the GIS is correct or not. The approach is explained in detail, and an evaluation is presented using reference data. Both the potential and the limitations of the system are discussed.

Initiating an undiagnosed diseases program in the Western Australian public health system

BackgroundNew approaches are required to address the needs of complex undiagnosed diseases patients. These approaches include clinical genomic diagnostic pipelines, utilizing intra- and multi-disciplinary platforms, as well as specialty-specific genomic clinics. Both are advancing diagnostic rates. However, complementary cross-disciplinary approaches are also critical to address those patients with multisystem disorders who traverse the bounds of multiple specialties and remain undiagnosed despite existing intra-specialty and genomic-focused approaches. The diagnostic possibilities of undiagnosed diseases include genetic and non-genetic conditions. The focus on genetic diseases addresses some of these disorders, however a cross-disciplinary approach is needed that also simultaneously addresses other disorder types. Herein, we describe the initiation and summary outcomes of a public health system approach for complex undiagnosed patients - the Undiagnosed Diseases Program-Western Australia (UDP-WA).ResultsBriefly the UDP-WA is: i) one of a complementary suite of approaches that is being delivered within health service, and with community engagement, to address the needs of those with severe undiagnosed diseases; ii) delivered within a public health system to support equitable access to health care, including for those from remote and regional areas; iii) providing diagnoses and improved patient care; iv) delivering a platform for in-service and real time genomic and phenomic education for clinicians that traverses a diverse range of specialties; v) retaining and recapturing clinical expertise; vi) supporting the education of junior and more senior medical staff; vii) designed to integrate with clinical translational research; and viii) is supporting greater connectedness for patients, families and medical staff.ConclusionThe UDP-WA has been initiated in the public health system to complement existing clinical genomic approaches; it has been targeted to those with a specific diagnostic need, and initiated by redirecting existing clinical and financial resources. The UDP-WA supports the provision of equitable and sustainable diagnostics and simultaneously supports capacity building in clinical care and translational research, for those with undiagnosed, typically rare, conditions.

Semiautomatic quality control of topographic reference datasets

The usefulness and acceptance of spatial information systems are mainly dependent on the quality of the underlying geodata. This paper describes a system for semiautomatic quality control of existing geospatial data via automatic image analysis using aerial images, high-resolution satellite imagery (IKONOS and RapidEye) and low-resolution satellite imagery (Disaster Monitoring Constellation, DMC) with monoand multi-temporal approaches focusing on objects which cover most of the area of the topographic dataset. The goal of the developed system is to reduce the manual efforts to a minimum. We shortly review the system design and then we focus on the automatic components and their integration in a semiautomatic workflow for verification and update. A prototype of the system has been in use for several years. From the experience gained during this time we give a detailed report on the system performance in its application as well as an evaluation of the results.

Pilbara rock art: Laser scanning, photogrammetry and 3D photographic reconstruction as heritage management tools

Recording techniques such as laser scanning, photogrammetry and photographic reconstruction are not new to archaeology. However as technology evolves and becomes more readily available such methods are being more regularly employed within a cultural heritage management context, often by people with little experience in using these technologies for heritage applications. For most cultural heritage management practitioners, the awe and lure of technology and the ease with which it can bring archaeology to life can distract from the end game of managing the site on the ground. This paper examines the advantages and disadvantages of laser scanning, photogrammetry and photographic reconstruction in recording, managing and interpreting rock art sites with an emphasis on its practical applications to the field of heritage management. Using a case study from West Angelas in the East Pilbara region of Western Australia, we will examine how these technologies assist in the practical management of heritage sites, and the significant outputs achieved for Aboriginal stakeholder groups in remote access to, and the interpretation of indigenous heritage sites.

3-Dimensional Facial Analysis—Facing Precision Public Health

Precision public health is a new field driven by technological advances that enable more precise descriptions and analyses of individuals and population groups, with a view to improving the overall health of populations. This promises to lead to more precise clinical and public health practices, across the continuum of prevention, screening, diagnosis, and treatment. A phenotype is the set of observable characteristics of an individual resulting from the interaction of a genotype with the environment. Precision (deep) phenotyping applies innovative technologies to exhaustively and more precisely examine the discrete components of a phenotype and goes beyond the information usually included in medical charts. This form of phenotyping is a critical component of more precise diagnostic capability and 3-dimensional facial analysis (3DFA) is a key technological enabler in this domain. In this paper, we examine the potential of 3DFA as a public health tool, by viewing it against the 10 essential public health services of the “public health wheel,” developed by the US Centers for Disease Control. This provides an illustrative framework to gage current and emergent applications of genomic technologies for implementing precision public health.

Ground truthing protocols for biomass estimation in rangeland environments

Remote sensing for the assessment and mapping of total standing biomass relies on accurate ground data for calibration and validation. The spatial heterogeneity of rangelands pose challenges in sampling methodologies, demanding a large number of replicate measurements that are expensive and labour demanding when working on the scale of pastoral stations. In this paper we present a ground truthing protocol that can be used for biomass estimation in heterogeneous rangeland environments, important for the development of assessments based on remote sensing or growth modelling. The protocol is based on a combination of visual estimates, crop circle NDVI, and disk-plate meter height recordings. Relationships between these indirect measurements and biomass were specific for either season or vegetation type. A combination of these measurements in a multivariate regression provided an accurate alternative, while strongly reducing the number of cuts required.

Semantically enhanced 3D building model reconstruction from terrestrial laser-scanning data

AbstractIn recent years, three-dimensional (3D) models have been used in a large variety of applications, and the steadily growing capacity in both quality and quantity is increasing demand. To app...

Non-parametric belief propagation for mobile mapping sensor fusion

Abstract Many different forms of sensor fusion have been proposed each with its own niche. We propose a method of fusing multiple different sensor types. Our approach is built on the discrete belief propagation to fuse photogrammetry with GPS to generate three-dimensional (3D) point clouds. We propose using a non-parametric belief propagation similar to Sudderth et al’s work to fuse different sensors. This technique allows continuous variables to be used, is trivially parallel making it suitable for modern many-core processors, and easily accommodates varying types and combinations of sensors. By defining the relationships between common sensors, a graph containing sensor readings can be automatically generated from sensor data without knowing a priori the availability or reliability of the sensors. This allows the use of unreliable sensors which firstly, may start and stop providing data at any time and secondly, the integration of new sensor types simply by defining their relationship with existing sensors. These features allow a flexible framework to be developed which is suitable for many tasks. Using an abstract algorithm, we can instead focus on the relationships between sensors. Where possible we use the existing relationships between sensors rather than developing new ones. These relationships are used in a belief propagation algorithm to calculate the marginal probabilities of the network. In this paper, we present the initial results from this technique and the intended course for future work.

MLS-assisted validation of WorldView-2 panchromatic image for estimating Pinus sylvestris crown height

High spatial resolution satellite imaging has the advantages of both fine scale and large coverage that indicate the potential for measuring forest morphologies. However, because of the aerial view, imaging has limited capacity of explicitly deriving the under-crown structural parameters. A possible solution is to explore the relationships between this kind of variables such as crown height (CH) and the feature parameters readily derived from the satellite images. However, field sampling of the training data is not a trivial task. To handle this issue, this study attempted the state-of-the-art remote sensing technology of vehicle-based mobile laser scanning (MLS) for collecting the sample data. Evaluation for the case of the Scots pine (Pinus sylvestris) trees has preliminarily validated the plan. That is, MLS mapping enabled the parameter of CH to be estimated from WorldView-2 panchromatic images.