High-resolution Stereo Imagery Research Articles

Brief communication: Glacier mapping and change estimation using very high-resolution declassified Hexagon KH-9 panoramic stereo imagery (1971–1984)

Abstract. The panoramic cameras (PCs) on board Hexagon KH-9 (KH-9PC) satellite missions from 1971–1984 captured very high-resolution stereo imagery with up to 60 cm spatial resolution. This study explores the potential of this imagery for glacier mapping and change estimation. We assess KH-9PC imagery using data from the KH-9 mapping camera (KH-9MC), KH-4PC, and SPOT and Pléiades satellite imagery. The high resolution of KH-9PC leads to higher-quality DEMs, which better resolve the accumulation region of the glaciers in comparison to the KH-9MC. On stable terrain, KH-9PC DEMs achieve an elevation accuracy of <4 m with respect to SPOT and Pléiades DEMs. While the estimated geodetic mass balances using PC and MC data are similar after outlier filtering, the elevation change data show superior spatial coverage and considerably less noise when using KH-9PC data.

A New Stereo Pair Disparity Index (SPDI) for Detecting Built-Up Areas from High-Resolution Stereo Imagery

Within-class spectral variation and between-class spectral confusion in remotely sensed imagery degrades the performance of built-up area detection when using planar texture, shape, and spectral features. Terrain slopes and building heights extracted from auxiliary data, such as Digital Surface Models (DSMs) however, can improve the results. Stereo imagery incorporates height information unlike single remotely sensed images. In this study, a new Stereo Pair Disparity Index (SPDI) for indicating built-up areas is calculated from stereo-extracted disparity information. Further, a new method of detecting built-up areas from stereo pairs is proposed based on the SPDI, using disparity information to establish the relationship between two images of a stereo pair. As shown in the experimental results for two stereo pairs covering different scenes with diverse urban settings, the SPDI effectively differentiates between built-up and non-built-up areas. Our proposed method achieves higher accuracy built-up area results from stereo images than the traditional method for single images, and two other widely-applied DSM-based methods for stereo images. Our approach is suitable for spaceborne and airborne stereo pairs and triplets. Our research introduces a new effective height feature (SPDI) for detecting built-up areas from stereo imagery with no need for DSMs.

Reflections on a decade of autonomous underwater vehicles operations for marine survey at the Australian Centre for Field Robotics

This paper describes insights gained from a decade of autonomous marine systems development at the University of Sydney’s Australian Centre for Marine Robotics. Over the course of this time, we have deployed numerous vehicles and imaging platforms in support of applications in engineering science, marine ecology, archaeology and geoscience. We have operated an Australia-wide benthic observing program designed to deliver precisely navigated, repeat imagery of the seafloor. This initiative makes extensive use of Autonomous Underwater Vehicles (AUVs) to collect high-resolution stereo imagery, multibeam sonar and water column measurements on an annual or semi-annual basis at sites around Australia, spanning the full latitudinal range of the continent from tropical reefs in the north to temperate regions in the south. We have also contributed to expeditions to document coral bleaching, cyclone recovery, submerged neolithic settlement sites, ancient shipwrecks, methane seeps and deepwater hydrothermal vents. We briefly consider how automated tools for working with this imagery have facilitated the resulting science outcomes.

Detection of geometric change in railway curves caused by earthquakes, using high-resolution stereo satellite images

Rapid change detection of railway curves is crucial for the damage assessment of unexpected disasters such as earthquakes. Detection of the geometric change in railway curves involves the measurement of the shape change by comparing the pre- and post-seismic railway curves. This paper proposes an approach for change detection in railway curves by the use of a pre-seismic digital topographic map and post-seismic stereo IKONOS images. The proposed approach consists of four main components, they are as follows: (1) The geometric parameters of the pre-seismic railway curves are first estimated based on the digitized points from the digital topographic map by the use of least squares adjustment. (2) The feature points on the post-seismic railway curves are then extracted from the high-resolution stereo satellite imagery, and the ground coordinates of these points are further refined by the use of rational function polynomial coefficients bundle adjustment. (3) Five change detection models—the shift model, the scale and shift model, the affine model, the second-order polynomial model, and the similarity model—are introduced to describe the geometric change between the pre- and post-seismic railway curves. Based on this, an objective function is formulated to minimize the squared distances between the transformed points from the post-seismic points refined from the high-resolution stereo imagery, based on the change detection model and the pre-seismic railway curves. An empirical experiment in change detection in railway curves as a result of the 2008 Wenchuan earthquake in Dujiangyan City, China, was conducted. The experimental results showed the feasibility of the proposed geometric change detection method, they are as follows: (1) The root-mean-square error of the geometric parameter estimation of the pre-seismic railway curve was 0.068 m, which showed that the proposed least squares approach could recover the geometric curve of the pre-event railway with a centimeter-level accuracy by the use of the digital topographic map. (2) The result of the refinement of the ground control points extracted from the pre-seismic high-resolution satellite imagery by the use of the four bias compensation models showed that the second-order polynomial model achieved the highest geo-positioning accuracy of 0.788 and 0.701 m in the x- and y-directions. This result indicated that the second-order polynomial model was the best bias compensation model for improving the accuracy of ground points extracted from the post-event stereo image pairs. (3) A comparison of the five change detection models, in terms of displacement between the pre- and post-seismic railway curves, showed that the affine model obtained the highest accuracy of 0.318 m. This result showed that the geometric change in railway curves due to earthquakes could be detected with a decimeter-level accuracy by the use of the proposed change detection approach, based on a pre-seismic digital topographic map and post-seismic IKONOS stereo images.

Detecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm

In this paper, we propose a decision tree algorithm to characterize spatial extent and spectral features of invasive plant species (i.e., guava, Madagascar cardamom, and Molucca raspberry) in tropical rainforests by integrating datasets from passive and active remote sensing sensors. The decision tree algorithm is based on a number of input variables including matching score and infeasibility images from Mixture Tuned Matched Filtering (MTMF), land-cover maps, tree height information derived from high resolution stereo imagery, polarimetric feature images, Radar Forest Degradation Index (RFDI), polarimetric and InSAR coherence and phase difference images. Spatial distributions of the study organisms are mapped using pixel-based Winner-Takes-All (WTA) algorithm, object oriented feature extraction, spectral unmixing, and compared with the newly developed decision tree approach. Our results show that the InSAR phase difference and PolInSAR HH–VV coherence images of L-band PALSAR data are the most important variables following the MTMF outputs in mapping subcanopy invasive plant species in tropical rainforest. We also show that the three types of invasive plants alone occupy about 17.6% of the Betampona Nature Reserve (BNR) while mixed forest, shrubland and grassland areas are summed to 11.9% of the reserve. This work presents the first systematic attempt to evaluate forest degradation, habitat quality and invasive plant statistics in the BNR, and provides significant insights as to management strategies for the control of invasive plants and conversation in the reserve.

COMPARISON OF TWO FUSION BASED BUILDING CHANGE DETECTION METHODS USING SATELLITE STEREO IMAGERY AND DSMS

Abstract. Digital Surface Models (DSMs) can assist building change detection in a variety of approaches. Limited to the quality of DSMs from satellite stereo imagery, it is hard to reach precise change detection results using only DSMs. Therefore, DSMs should be used in combination with the spectral information from original stereo imagery. For that purpose, two fusion based methods, one using feature level fusion and the other using decision level fusion are proposed in our previous research. In this paper, these two methods are further evaluated and compared based on two different data sets. One test site features a typical urban environment which is captured by two pairs of very high resolution stereo imagery (IKONOS and WorldView-2). The other test site is located in an industrial area, the corresponding stereo imagery of the two dates are both from Cartosat-1. Quantitative and qualitative experiment results obtained from each dataset are analyzed in detail. Over all, the proposed feature fusion model give better results for the industrial area, while the decision fusion method works much better for the urban environment based on very high resolution imagery.

Variability in mesophotic coral reef communities along the Great Barrier Reef, Australia

The composition of sessile benthic megafauna communities on mesophotic coral reefs (50 to 65 m depth) was investigated at 3 sites (Noggin Pass, Viper Reef and Hydrographers Passage) over 500 km of the Great Barrier Reef (GBR) shelf-edge, Australia. High-resolution stereo imagery was collected in 4 separate autonomous underwater vehicle (AUV) surveys and used to characterise the substratum and megafauna at each site (2 surveys from Viper Reef, and one from each of Noggin Pass and Hydrographers Passage). Random sampling of 100 images from a 100 × 100 m area at each site indicated that non-reef habitats predominated and that megafauna were largely confined to reef habitats, while a more detailed investigation of these reef substrata revealed diverse benthic megafaunal communities that varied significantly both within and between study sites. There were consistent patterns in the functional ecological groups occupying particular finer-scale habitat types, with phototrophic taxa dominating the flatter tops of submerged reefs and heterotrophic suspension- feeders occupying steeper habitats. Slope angle, water clarity and productivity best explained the distribution of megafauna on reef habitats. Reduced photosynthetically active radiation (PAR) likely excludes most phototrophic taxa from steeper slopes. These results suggest that the extensive sub- merged reefs on the outer-shelf of the GBR harbour diverse mesophotic reef communities. Given these results, GBR mesophotic coral ecosystems deserve further study, not only of their benthic megafauna but also their fish and mobile invertebrate communities.

Multi-resolution topographic data extraction from Martian stereo imagery

The acquisition of high resolution topographic data such as Digital Terrain Models (DTMs) and orthoimages from various Martian stereo imagery is now readily available. The very successful European Space Agency (ESA) Mars Express mission includes the High Resolution Stereo Camera (HRSC) which has provided, since March 2004, an increasingly global set of along-track stereo coverage at relatively high spatial resolution (<100 m, mainly 12.5–25 m) over the Martian surface. Previous DTM generation was only accomplished with planned or serendipitous Viking Orbiter and more recently from Mars Orbiter Camera Narrow Angle (MOC-NA) stereo-pairs. Neither system was designed for stereo photogrammetric DTM generation. Recently, the NASA Mars Reconnaissance Orbiter (MRO) deployed two major optical pushbroom CCD cameras which are capable of across-track stereo targeting. Both Context Camera (CTX) and High Resolution Imaging Science Experiment (HiRISE) provide very high resolution stereo imagery at 6 m and submetre, respectively. A stereo processing chain has been developed which uses a non-rigorous sensor model with geodetic control derived from a reference stereo data source (HRSC) and is here shown to be successfully applied to CTX and HiRISE stereo imagery for 3 test areas. This processing chain is here demonstrated to generate excellent quality DTMs (up to a maximum grid spacing of 0.7 m with HiRISE and 10 m with CTX) and associated ortho images. The photogrammetric quality of these products is here verified using inter-comparisons with HRSC and Mars Orbiter Laser Altimeter (MOLA) data sets and shows good agreement.

Automated urban area building extraction from high resolution stereo imagery

This paper describes a new automated building extraction algorithm developed for high resolution stereo imagery. The problems of urban area imagery for stereo matching were investigated. Buildings were found to create isolated regions and many blunders. To overcome the problem of isolated regions, a pyramidal matching algorithm with automatic seed points using a tile-based control strategy was developed. To remove possible blunders and extract buildings from other background objects, a series of ‘smart’ operations using linear elements from buildings was applied. A quantitative analysis of the accuracy of the algorithm was assessed in comparison with a previous algorithm and shown to have an RMS error of 3.65m in elevation compared to 13.46m.