Assessment of a photogrammetric approach for urban DSM extraction from tri-stereoscopic satellite imagery

Built-up environments are extremely complex for 3D surface modelling purposes. The main distortions that hamper 3D reconstruction from 2D imagery are image dissimilarities, concealed areas, shadows, height discontinuities and discrepancies between smooth terrain and man-made features. A methodology is proposed to improve automatic photogrammetric extraction of an urban surface model from high resolution satellite imagery with the emphasis on strategies to reduce the effects of the cited distortions and to make image matching more robust. Instead of a standard stereoscopic approach, a digital surface model is derived from tri-stereoscopic satellite imagery. This is based on an extensive multi-image matching strategy that fully benefits from the geometric and radiometric information contained in the three images. The bundled triplet consists of an IKONOS along-track pair and an additional near-nadir IKONOS image. For the tri-stereoscopic study a densely built-up area, extending from the centre of Istanbul to the urban fringe, is selected. The accuracy of the model extracted from the IKONOS triplet, as well as the model extracted from only the along-track stereopair, are assessed by comparison with 3D check points and 3D building vector data

Guidelines for Best Practice and Quality Checking of Ortho Imagery

For almost 10 years JRC's ¿Guidelines for Best Practice and Quality Control of Ortho Imagery¿ has served as a reference document for the production of orthoimagery not only for the purposes of CAP but also for many medium-to-large scale photogrammetric applications. The aim is to provide the European Commission and the remote sensing user community with a general framework of the best approaches for quality checking of orthorectified remotely sensed imagery, and the expected best practice, required to achieve good results. Since the last major revision (2003) the document was regularly updated in order to include state-of-the-art technologies. The major revision of the document was initiated last year in order to consolidate the information that was introduced to the document in the last five years. Following the internal discussion and the outcomes of the meeting with an expert panel it was decided to adopt as possible a process-based structure instead of a more sensor-based used before and also to keep the document as much generic as possible by focusing on the core aspects of the photogrammetric process. Additionally to any structural changes in the document new information was introduced mainly concerned with image resolution and radiometry, digital airborne sensors, data fusion, mosaicking and data compression. The Guidelines of best practice is used as the base for our work on the definition of technical specifications for the orthoimagery. The scope is to establish a core set of measures to ensure sufficient image quality for the purposes of CAP and particularly for the Land Parcel Identification System (PLIS), and also to define the set of metadata necessary for data documentation and overall job tracking.JRC.G.3-Agricultur

Unmanned Aerial Vehicle (UAV) for monitoring soil erosion in Morocco

This article presents an environmental remote sensing application using a UAV that is specifically aimed at reducing the data gap between field scale and satellite scale in soil erosion monitoring in Morocco. A fixed-wing aircraft type Sirius I (MAVinci, Germany) equipped with a digital system camera (Panasonic) is employed. UAV surveys are conducted over different study sites with varying extents and flying heights in order to provide both very high resolution site-specific data and lower-resolution overviews, thus fully exploiting the large potential of the chosen UAV for multi-scale mapping purposes. Depending on the scale and area coverage, two different approaches for georeferencing are used, based on high-precision GCPs or the UAV’s log file with exterior orientation values respectively. The photogrammetric image processing enables the creation of Digital Terrain Models (DTMs) and ortho-image mosaics with very high resolution on a sub-decimetre level. The created data products were used for quantifying gully and badland erosion in 2D and 3D as well as for the analysis of the surrounding areas and landscape development for larger extents

The application of time-series MODIS NDVI profiles for the acquisition of crop information across Afghanistan

We investigated and developed a prototype crop information system integrating 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data with other available remotely sensed imagery, field data, and knowledge as part of a wider project monitoring opium and cereal crops. NDVI profiles exhibited large geographical variations in timing, height, shape, and number of peaks, with characteristics determined by underlying crop mixes, growth cycles, and agricultural practices. MODIS pixels were typically bigger than the field sizes, but profiles were indicators of crop phenology as the growth stages of the main first-cycle crops (opium poppy and cereals) were in phase. Profiles were used to investigate crop rotations, areas of newly exploited agriculture, localized variation in land management, and environmental factors such as water availability and disease. Near-real-time tracking of the current years’ profile provided forecasts of crop growth stages, early warning of drought, and mapping of affected areas. Derived data products and bulletins provided timely crop information to the UK Government and other international stakeholders to assist the development of counter-narcotic policy, plan activity, and measure progress. Results show the potential for transferring these techniques to other agricultural systems

Mapping and classification of ecologically sensitive marine habitats using unmanned aerial vehicle (UAV) imagery and object-based image analysis (OBIA)

Nowadays, emerging technologies, such as long-range transmitters, increasingly miniaturized components for positioning, and enhanced imaging sensors, have led to an upsurge in the availability of new ecological applications for remote sensing based on unmanned aerial vehicles (UAVs), sometimes referred to as “drones”. In fact, structure-from-motion (SfM) photogrammetry coupled with imagery acquired by UAVs offers a rapid and inexpensive tool to produce high-resolution orthomosaics, giving ecologists a new way for responsive, timely, and cost-effective monitoring of ecological processes. Here, we adopted a lightweight quadcopter as an aerial survey tool and object-based image analysis (OBIA) workflow to demonstrate the strength of such methods in producing very high spatial resolution maps of sensitive marine habitats. Therefore, three different coastal environments were mapped using the autonomous flight capability of a lightweight UAV equipped with a fully stabilized consumer-grade RGB digital camera. In particular we investigated a Posidonia oceanica seagrass meadow, a rocky coast with nurseries for juvenile fish, and two sandy areas showing biogenic reefs of Sabelleria alveolata. We adopted, for the first time, UAV-based raster thematic maps of these key coastal habitats, produced after OBIA classification, as a new method for fine-scale, low-cost, and time saving characterization of sensitive marine environments which may lead to a more effective and efficient monitoring and management of natural resource

Determining the Effect of Mission Design and Point Cloud Filtering on the Quality and Accuracy of SfM Photogrammetric Products Derived from sUAS Imagery

This research investigates the influence that various flight plan and mission design strategies for collecting small unmanned aerial system (sUAS) imagery have on the accuracy of the resulting three-dimensional models to find an optimal method to achieve a result. This research also explores the effect that using gradual selection to reduce the sparse point cloud has on product accuracy and processing details. Imagery was collected in the spring of 2018 during leaf-off conditions at six field sites along the North Fork of the White River. The aerial imagery was collected using a DJI Phantom Pro 4 sUAS. Four different image acquisition missions were flown at each of the sites. Each of the base mission imagery sets were processed individually and in various combinations. The commercial Structure-from-Motion (SfM) photogrammetry software known as Agisoft PhotoScan was used to process the data and generate the Digital Elevation Models (DEMs) and orthophotos. Due to the high number of processing iterations required in this research, a script was developed to automate the point cloud filtering gradual selection process. Profile views were used to assess the differences between each mission design and to visualize systematic errors. In this investigation, the imagery set which consistently performed with high relative accuracy and low relative processing times was the NS Oblique imagery set utilizing automated gradual selection. Imagery sets created by combining two or more of the base mission photosets generally produced results with accuracy levels similar to or worse than the results of the NS Oblique imagery set and the other base mission imagery sets. Results produced with and without gradual selection were similar in most cases, however, gradual selection reduced dense cloud processing time by an average of 37%

Semi-automatic city model extraction from tri-stereoscopic VHR satellite imagery

In this paper a methodology and results of semi-automatic city DSM extraction from an Ikonos triplet, is introduced. Built-up areas are known as being complex for photogrammetric purposes, mainly because of the steep changes in elevation caused by buildings and urban features. To make surface model extraction more robust and to cope with the specific problems of height displacement, concealed areas and shadow, a multi-image based approach is followed. For the VHR tri-stereoscopic study an area extending from the centre of Istanbul to the urban fringe is chosen. Research concentrates on the development of methods to optimize the extraction of a surface model from the bundled Ikonos triplet over an urban area, without manual plotting of buildings. Optimal methods need to be found to improve the radiometry and geometric alignment of the multi-temporal imagery, to optimize the semi-automatical derivation of DSMs from an urban environment and to enhance the quality of the resulting surface model and especially to reduce smoothing effects by applying spatial filters

DEM shading method for the correction of pseudoscopic effect on multi-platform satellite imagery

This is an Accepted Manuscript of an article published by Taylor & Francis in GIScience & Remote Sensing on 2014, available online: http://www.tandfonline.com/10.1080/15481603.2014.988433The pseudoscopic effect in satellite imagery causes perception problems for rugged terrain. The topographic relief is perceived in reverse in images with southeast illumination because of the position of land shadows and the mechanisms of human vision and depth perception. This article presents a correction method for false topographic perception phenomena. Superposition of the orthoimage and the correctly shaded digital elevation model (DEM) provides the correct three-dimensional visualization of the relief. This study demonstrates the applicability of this processing technique for the correction of such effects to provide cartography with a more useful interpretation. The resolution of the DEM employed should be in accordance with the spatial resolution of each image. The opacity level proposed for the overlapping DEM is 50%, 30% and 45% for each image type. The selection of the most appropriate local incidence angle is determined by the level of terrain roughness in the work areaWe want to thank the Galician Territorial Information System (SITGA) for the images and the cartographic material provided for the realization of this workS