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.German Federal Agency for Cartography and Geodesy (BKG

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

Grammar-based Automatic 3D Model Reconstruction from Terrestrial Laser Scanning Data

The automatic reconstruction of 3D buildings has been an important research topic during the last years. In this paper, a novel method is proposed to automatically reconstruct the 3D building models from segmented data based on pre-defined formal grammar and rules. Such segmented data can be extracted e.g. from terrestrial or mobile laser scanning devices. Two steps are considered in detail. The first step is to transform the segmented data into 3D shapes, for instance using the DXF (Drawing Exchange Format) format which is a CAD data file format used for data interchange between AutoCAD and other program. Second, we develop a formal grammar to describe the building model structure and integrate the pre-defined grammars into the reconstruction process. Depending on the different segmented data, the selected grammar and rules are applied to drive the reconstruction process in an automatic manner. Compared with other existing approaches, our proposed method allows the model reconstruction directly from 3D shapes and takes the whole building into account

Empirical investigation of a Stochastic model based on intensity values for terrestrial laser scanning

Stochastic information of measurements has always been an important part in the field of geodesy. Especially for engineering tasks like deformation monitoring the knowledge of achieved precision is of vital importance. For more than a decade terrestrial laser scanners have been used for high precise measurement applications, however there has been a lack of focus in the literature of an adequate stochastic model for terrestrial laser scanning. This contribution presents a comprehensive empirical experiment containing numerous laser scans at various scan configurations in order to examine a stochastic model based on intensity values. The results confirm the fundamental suitability of intensity values for a stochastic modelling but also point out certain problems concerning scanning geometry. High incidence angles in laser scanning can lead to an improvement of the precision in object's surface normal direction, which agrees with a previously proposed theoretical model for positional uncertainty of laser scan 3D points and should not be ignored in further development of a stochastic model based on intensity values. Based on these results a stochastic model was estimated and the precision of 3D points explicitly expressed as function of intensity and incidence angle

Evaluation of vegetation indices for rangeland biomass estimation in the Kimberley area of Western Australia

The objective of this paper is to test the relationships between Above Ground Biomass (AGB) and remotely sensed vegetation indices for AGB assessments in the Kimberley area in Western Australia. For 19 different sites, vegetation indices were derived from eight Landsat ETM+ scenes over a period of two years (2011–2013). The sites were divided into three groups (Open plains, Bunch grasses and Spinifex) based on similarities in dominant vegetation types. Dry and green biomass fractions were measured at these sites. Single and multiple regression relationships between vegetation indices and green and total AGB were calibrated and validated using a "leave site out" cross validation. Four tests were compared: (1) relationships between AGB and vegetation indices combining all sites; (2) separate relationships per site group; (3) multiple regressions including selected vegetation indices per site group; and (4) as in 3 but including rainfall and elevation data. Results indicate that relationships based on single vegetation indices are moderately accurate for green biomass in wide open plains covered with annual grasses. The cross-validation results for green AGB improved for a combination of indices for the Open plains and Bunch grasses sites, but not for Spinifex sites. When rainfall and elevation data are included, cross validation improved slightly with a Q2 of 0.49–0.72 for Open plains and Bunch grasses sites respectively. Cross validation results for total AGB were moderately accurate (Q2 of 0.41) for Open plains but weak or absent for other site groups despite good calibration results, indicating strong influence of site-specific factors

Non-parametric belief propagation for mobile mapping sensor fusion

© 2016 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group. 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

Increasing level of detail of buildings for improved simulation of 4D urban digital twin

Buildings represent a crucial component of urban morphology, and their accurate modeling is essential for a number of applications involving Urban Digital Twins. With respect to thermal simulation aiming to identify Urban Heat Islands, a trade-off between accurate modeling of a single building type and large-scale reconstruction of virtual city models needs to be found. In the proposed paper, we analyzed an Australian suburb containing approximately 1700 residential buildings with challenging roof structures. Building outlines are provided by geo-information data and converted into prismatic models of LOD1. Using airborne sensor data (digital orthophotos, high-resolution images, and digital surface models), we identified two ways to increase the LOD and thus, the accuracy of the simulation. Firstly, we used common Computer Aided Graphics software to model interactively a few selected buildings, a process denoted as geo-specific modeling. Here, the outlines were used as foundations for constructing the ground-level walls. We relied on airborne data to retrieve building heights and roof structures. Number of floors and positions of façade elements were modeled on standard typological assumptions and building practices. We developed an interface to import automatically LOD1- based data and to export LOD3 buildings into the simulation. Secondly, we reproduce these models to model other buildings of the dataset. For this so-called geo-typical modeling, a similarity measure based on the outlines was implemented. The final scene consists of triangles modeling LOD3 buildings, terrain, and trees, retrieved using machinelearning- based methods on land cover classification. Together with the semantic class, we store the geometrical and physical properties of every triangle. The environmental data (e.g., cloud coverage, air temperature) is available by means of the weather services. Surface temperature is modeled by considering conductive, convective, and radiative heat transfer. The simulation of updated LOD3 buildings shows a significantly increased realism of the temperature distribution in an urban area. It can used to verify sustainable design of appropriate morpho-typologies for a particular precinct in a given context

Increasing level of detail of buildings for improved simulation of 4D urban digital twin.

Buildings represent a crucial component of urban morphology, and their accurate modelling is essential for a number of applications involving Urban Digital Twins. With respect to thermal simulation aiming to identify Urban Heat Islands, a trade-off between accurate modelling of a single building type and large-scale reconstruction of virtual city models needs to be found. In the proposed paper, we analyzed an Australian suburb containing approximately 1700 residential buildings with challenging roof structures. Building outlines are provided by geo-information data and converted into prismatic models of LOD1. Using airborne sensor data (digital orthophotos, high-resolution images, and digital surface models), we identified two ways to increase the LOD and thus, the accuracy of the simulation. Firstly, we used common Computer-Aided Graphics software to model interactively a few selected buildings, a process denoted as geo-specific modelling. Here, the outlines were used as foundations for constructing the ground-level walls. We relied on airborne data to retrieve building heights and roof structures. A number of floors and positions of façade elements were modelled on standard typological assumptions and building practices. We developed an interface to import automatically LOD1- based data and export LOD3 buildings into the simulation. Secondly, we reproduce these models to model other buildings in the dataset. For this so-called geo-typical modelling, a similarity measure based on the outlines was implemented. The final scene consists of triangles modelling LOD3 buildings, terrain, and trees, retrieved using machine-learning-based methods on land cover classification. Together with the semantic class, we store the geometrical and physical properties of every triangle. The environmental data (e.g., cloud coverage, air temperature) is available by means of the weather services. Surface temperature is modelled by considering conductive, convective, and radiative heat transfer. The simulation of updated LOD3 buildings shows a significantly increased realism of the temperature distribution in an urban area. It can be used to verify the sustainable design of appropriate morpho-typologies for a particular precinct in a given context

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 mono- and 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

Verifikation von Ackerland- und Grünlandobjekten eines topographischen Datensatzes mit monotemporalen Bildern

[no abstract