Object-Based Greenhouse Classification from GeoEye-1 and WorldView-2 Stereo Imagery

Remote sensing technologies have been commonly used to perform greenhouse detection and mapping. In this research, stereo pairs acquired by very high-resolution optical satellites GeoEye-1 (GE1) and WorldView-2 (WV2) have been utilized to carry out the land cover classification of an agricultural area through an object-based image analysis approach, paying special attention to greenhouses extraction. The main novelty of this work lies in the joint use of single-source stereo-photogrammetrically derived heights and multispectral information from both panchromatic and pan-sharpened orthoimages. The main features tested in this research can be grouped into different categories, such as basic spectral information, elevation data (normalized digital surface model; nDSM), band indexes and ratios, texture and shape geometry. Furthermore, spectral information was based on both single orthoimages and multiangle orthoimages. The overall accuracy attained by applying nearest neighbor and support vector machine classifiers to the four multispectral bands of GE1 were very similar to those computed from WV2, for either four or eight multispectral bands. Height data, in the form of nDSM, were the most important feature for greenhouse classification. The best overall accuracy values were close to 90%, and they were not improved by using multiangle orthoimages

Impact of flight altitude and cover orientation on Digital Surface Model (DSM) accuracy for flood damage assessment in Murcia (Spain) using a fixed-wing UAV

Soil erosion, rapid geomorphological change and vegetation degradation are major threats to the human and natural environment. Unmanned Aerial Systems (UAS) can be used as tools to provide detailed and accurate estimations of landscape change. The effect of flight strategy on the accuracy of UAS image data products, typically a digital surface model (DSM) and orthophoto, is unknown. Herein different flying altitudes (126-235 m) and area coverage orientations (N-S and SW-NE) are assessed in a semi-arid and medium-relief area where terraced and abandoned agricultural fields are heavily damaged by piping and gully erosion. The assessment was with respect to cell size, vertical and horizontal accuracy, absolute difference of DSM, and registration of recognizable landscape features. The results show increasing cell size (5-9 cm) with increasing altitude, and differences between elevation values (10-20 cm) for different flight directions. Vertical accuracy ranged 4-7 cm but showed no clear relationship with flight strategy, whilst horizontal error was stable (2-4 cm) for the different orthophotos. In all data sets, geomorphological features such as piping channels, rills and gullies and vegetation patches could be labeled by a technician. Finally, the datasets have been released in a public repository.</p

New sensors benchmark report on Kompsat-3

The following document has been drawn up as a follow up to the Quality Control Record L [i] on the commissioning phase of the Kompsat-3 imagery, planned benchmarking tests as well as the methodology used in the tests. Benchmarking is necessary to be performed in order to estimate the usability of the imagery collected by particular sensor in The Common Agricultural Policy (CAP) image acquisition Campaign. The main requirement that should be fulfilled concerns the planimetric accuracy of the orthoimagery which should not exceed particular thresholds given in VHR Specifications [iii]. The methodologies used in the benchmarking tests were performed based on Guidelines for Best Practice and Quality Checking of Ortho Imagery [ii]. However, in addition the tests were performed according to alternative methodology, described in [i], which differs from the standard one, the GCPs selection/measurement phase i.e. image to image correlation techniques are used.JRC.H.6-Digital Earth and Reference Dat

Assessing the influence of DEM source on derived streamline and catchment boundary accuracy

Accurate DEM-derived streamlines and catchment boundaries are essential for hydrological modelling. Due to the popularity of hydrological parameters derived mainly from free DEMs, it is essential to investigate the accuracy of these parameters. This study compared the spatial accuracy of streamlines and catchment boundaries derived from available digital elevation models in South Africa. Two versions of Stellenbosch University DEMs (SUDEM5 and DEMSA2), the second version of the 30 m advanced spaceborne thermal emission and reflection radiometer global digital elevation model (ASTER GDEM2), the 30 and 90 m shuttle radar topography mission (SRTM30 and SRTM90 DEM), and the 90 m Water Research Commission DEM (WRC DEM) were considered. As a reference, a 1 m GEOEYE DEM was generated from GeoEye stereo images. Catchment boundaries and streamlines were extracted from the DEMs using the Arc Hydro module. A reference catchment boundary was generated from the GEOEYE DEM and verified during field visits. Reference streamlines were digitised at a scale of 1:10 000 from the 1 m orthorectified GeoEye images. Visual inspection, as well as quantitative measures such as correctness index, mean absolute error, root mean squares error and figure of merit index were used to validate the results. The study affirmed that high resolution (&lt;30 m) DEMs produce more accurate parameters and that DEM source and resampling techniques also play a role. However, if high resolution DEMs are not available, the 30 m SRTM DEM is recommended as its vertical accuracy was relatively high and the quality of the streamlines and catchment boundary was good. In addition, it was found that the novel Euclidean distancebased MAE and RMSE proposed in this study to compare reference and DEM-extracted raster datasets of different resolutions is a more reliable indicator of geometrical accuracy than the correctness and figure of merit indices.Keywords: hydrology, catchment delineation, digital elevation model, correctness index, figure of merit index, Euclidean distance inde

High resolution radargrammetry with COSMO-SkyMed, TerraSAR-X and RADARSAT-2 imagery: development and implementation of an image orientation model for Digital Surface Model generation

Digital Surface and Terrain Models (DSM/DTM) have large relevance in several territorial applications, such as topographic mapping, monitoring engineering, geology, security, land planning and management of Earth's resources. The satellite remote sensing data offer the opportunity to have continuous observation of Earth's surface for territorial application, with short acquisition and revisit times. Meeting these requirements, the SAR (Synthetic Aperture Radar) high resolution satellite imagery could offer night-and-day and all-weather functionality (clouds, haze and rain penetration). Two different methods may be used in order to generate DSMs from SAR data: the interferometric and the radargrammetric approaches. The radargrammetry uses only the intensity information of the SAR images and reconstructs the 3D information starting from a couple of images similarly to photogrammetry. Radargrammetric DSM extraction procedure consists of two basic steps: the stereo pair orientation and the image matching for the automatic detection of homologous points. The goal of this work is the definition and the implementation of a geometric model in order to orientate SAR imagery in zero Doppler geometry. The radargrammetric model implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione - developed at the Geodesy and Geomatic Division - University of Rome "La Sapienza") is based on the equation of radar target acquisition and zero Doppler focalization Moreover a tool for the SAR Rational Polynomial Coefficients (RPCs) generation has been implemented in SISAR software, similarly to the one already developed for the optical sensors. The possibility to generate SAR RPCs starting from a radargrammetric model sounds of particular interest since, at present, the most part of SAR imagery is not supplied with RPCs, although the RPFs model is available in several commercial software. Only RADARSAT-2 data are supplied with vendors RPCs. To test the effectiveness of the implemented RPCs generation tool and the SISAR radargrammetric orientation model the reference results were computed: the stereo pairs were orientated with the two model. The tests were carried out on several test site using COSMO-SkyMed, TerraSAR-X and RADARSAT-2 data. Moreover, to evaluate the advantages and the different accuracy between the orientation models computed without GCPs and the orientation model with GCPs a Monte Carlo test was computed. At last, to define the real effectiveness of radargrammetric technique for DSM extraction and to compare the radrgrammetric tool implemented in a commercial software PCI-Geomatica v. 2012 and SISAR software, the images acquired on Beauport test site were used for DSM extraction. It is important underline that several test were computed. Part of this tests were carried out under the supervision of Prof. Thierry Toutin at CCRS (Canada Centre of Remote Sensing) where the PCI-Geomatica orientation model was developed, in order to check the better parameters solution to extract radargrammetric DSMs. In conclusion, the results obtained are representative of the geometric potentialities of SAR stereo pairs as regards 3D surface reconstruction

Reconstructing the Past in 3D Using Historical Aerial Imgery

Historical aerial film images are a valuable record of the past, and are useful as a baseline for change detection and landcover analysis. To be useful in GIS analysis the images must be oriented to a spatial reference system. This is challenging as historical imagery is often missing flight and camera information. Traditional photogrammetric processing techniques exist to overcome these challenges, but they require specialized knowledge, time and expense to complete. Because of this, many collections of historical images are left unprocessed. This project produced a method to quickly standardize the photos, spatially orient them, correct them for distortion effects, and extract a digital surface model from the overlapping image series using Pix4D Professional. The horizontal accuracy met National Map Accuracy Standards when the Pix 4D process was combined with traditional georeferencing. The workflow was faster than traditional methods due to economies of scale in the new process