GRASS GIS for the distinction of vegetation from buildings using LiDAR altimetric data

La tecnología LiDAR (Light Detection and Ranging), basada en el escaneado del territorio por un telémetro láser aerotransportado, permite la construcción de Modelos Digitales de Superficie (DSM) mediante una simple interpolación, así como de Modelos Digitales del Terreno (DTM) mediante la identificación y eliminación de los objetos existentes en el terreno (edificios, puentes o árboles). El Laboratorio de Geomática del Politécnico de Milán – Campus de Como- desarrolló un algoritmo de filtrado de datos LiDAR basado en la interpolación con splines bilineares y bicúbicas con una regularización de Tychonov en una aproximación de mínimos cuadrados. Sin embargo, en muchos casos son todavía necesarios modelos más refinados y complejos en los cuales se hace obligatorio la diferenciación entre edificios y vegetación. Este puede ser el caso de algunos modelos de prevención de riesgos hidrológicos, donde la vegetación no es necesaria; o la modelización tridimensional de centros urbanos, donde la vegetación es factor problemático. (...)

LiDAR data filtering with GRASS GIS for the determination of digital terrain models

In the last years, the use of every type of Digital Elevation Models has iimproved. The LiDAR (Light Detection and Ranging) technology, based on the scansion of the territory b airborne laser telemeters, allows the construction of digital Surface Models (DSM), in an easy way by a simple data interpolation

Benchmarking 2D hydraulic models for urban flooding

This paper describes benchmark testing of six two-dimensional (2D) hydraulic models (DIVAST, DIVASTTVD, TUFLOW, JFLOW, TRENT and LISFLOOD-FP) in terms of their ability to simulate surface flows in a densely urbanised area. The models are applied to a 1·0 km × 0·4 km urban catchment within the city of Glasgow, Scotland, UK, and are used to simulate a flood event that occurred at this site on 30 July 2002. An identical numerical grid describing the underlying topography is constructed for each model, using a combination of airborne laser altimetry (LiDAR) fused with digital map data, and used to run a benchmark simulation. Two numerical experiments were then conducted to test the response of each model to topographic error and uncertainty over friction parameterisation. While all the models tested produce plausible results, subtle differences between particular groups of codes give considerable insight into both the practice and science of urban hydraulic modelling. In particular, the results show that the terrain data available from modern LiDAR systems are sufficiently accurate and resolved for simulating urban flows, but such data need to be fused with digital map data of building topology and land use to gain maximum benefit from the information contained therein. When such terrain data are available, uncertainty in friction parameters becomes a more dominant factor than topographic error for typical problems. The simulations also show that flows in urban environments are characterised by numerous transitions to supercritical flow and numerical shocks. However, the effects of these are localised and they do not appear to affect overall wave propagation. In contrast, inertia terms are shown to be important in this particular case, but the specific characteristics of the test site may mean that this does not hold more generally.

Unsupervised segmentation using Gabor wavelets and statistical features in LIDAR data analysis

In this paper, we address issues in segmentation Of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contain 2.5 dimensional (2.5D) terrain surface height information, e.g. houses, vegetation, flat field, river, basin, etc. Our aim in this paper is to segment ground (flat field)from non-ground (houses and high vegetation) in hilly urban areas. By projecting the 2.5D data onto a surface, we obtain a texture map as a grey-level image. Based on the image, Gabor wavelet filters are applied to generate Gabor wavelet features. These features are then grouped into various windows. Among these windows, a combination of their first and second order of statistics is used as a measure to determine the surface properties. The test results have shown that ground areas can successfully be segmented from LIDAR data. Most buildings and high vegetation can be detected. In addition, Gabor wavelet transform can partially remove hill or slope effects in the original data by tuning Gabor parameters.

Physical interpretation of the correlation between multi-angle spectral data and canopy height

Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally.

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Surface roughness is an important geomorphological variable which has been used in the Earth and planetary sciences to infer material properties, current/past processes, and the time elapsed since formation. No single definition exists; however, within the context of geomorphometry, we use surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter`s behavior at different spatial scales and data-set resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenization of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography highlighted local features and did not detect regional relief. Standard deviation of elevation correctly identified breaks of slope and was good at detecting regional relief. Standard deviation of slope (SD(slope)) also correctly identified smooth sloping areas and breaks of slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks of slope, although not as strongly as SD(slope), and it is sensitive to noise and spurious data. In general, SD(slope) offered good performance at a variety of scales, while the simplicity of calculation is perhaps its single greatest benefit.

Predição de sombras de edifícios sobre vias urbanas com base em modelos digitais de elevações e dados de imagens aéreas de alta resolução

This research presents a methodology for prediction of building shadows cast on urban roads existing on high-resolution aerial imagery. Shadow elements can be used in the modeling of contextual information, whose use has become more and more common in image analysis complex processes. The proposed methodology consists in three sequential steps. First, the building roof contours are manually extracted from an intensity image generated by the transformation of a digital elevation model (DEM) obtained from airborne laser scanning data. In similarly, the roadside contours are extracted, now from the radiometric information of the laser scanning data. Second, the roof contour polygons are projected onto the adjacent roads by using the parallel projection straight lines, whose directions are computed from the solar ephemeris, which depends on the aerial image acquisition time. Finally, parts of shadow polygons that are free from building perspective obstructions are determined, given rise to new shadow polygons. The results obtained in the experimental evaluation of the methodology showed that the method works properly, since it allowed the prediction of shadow in high-resolution imagery with high accuracy and reliability.

Predição de sombras de edifícios sobre vias urbanas com base em um modelo digital de elevações e dados de imagens aéreas de alta-resolução

Pós-graduação em Ciências Cartográficas - FCT

Aplicação de técnicas de processamento e análise de imagens para detecção de edificações e vegetação a partir de dados LiDAR

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

ICESat Measurements Reveal Complex Pattern of Elevation Changes on Siple Coast Ice Streams, Antarctica

We compare ICESat data (2003-2004) to airborne laser altimetry data (1997-98 and 1999-2000) to monitor surface changes over portions of Van der Veen (VdVIS), Whillans (WIS) and Kamb ice streams (KIS) in the Ross Embayment of the West Antarctic Ice Sheet. The spatial pattern of detected surface changes is generally consistent with earlier observations. However, important changes have occurred during the past decade. For example, areas on the VdVIS and WIS, where large thinning was detected by the airborne surveys, are now closer to being in balance. The upper trunk of KIS continues to build up with thickening rates reaching 0.4 m/year. Our results provide new evidence that the overall mass balance of the region is becoming more positive, but a significant spatial variability exists. They also demonstrate the potential of ICESat data for detecting spatial patterns of surface elevation change in Antarctica.

Digital elevation model (DEM) of the ice sheet in western Dronning Maud Land, Antarctica

In this paper, a new digital elevation model (DEM) is derived for the ice sheet in western Dronning Maud Land, Antarctica. It is based on differential interferometric synthetic aperture radar (SAR) from the European Remote Sensing 1/2 (ERS-1/2) satellites, in combination with ICESat's Geoscience Laser Altimeter System (GLAS). A DEM mosaic is compiled out of 116 scenes from the ERS-1 ice phase in 1994 and the ERS-1/2 tandem mission between 1996 and 1997 with the GLAS data acquired in 2003 that served as ground control. Using three different SAR processors, uncertainties in phase stability and baseline model, resulting in height errors of up to 20 m, are exemplified. Atmospheric influences at the same order of magnitude are demonstrated, and corresponding scenes are excluded. For validation of the DEM mosaic, covering an area of about 130,000 km**2 on a 50-m grid, independent ICESat heights (2004-2007), ground-based kinematic GPS (2005), and airborne laser scanner data (ALS, 2007) are used. Excluding small areas with low phase coherence, the DEM differs in mean and standard deviation by 0.5 +/- 10.1, 1.1 +/- 6.4, and 3.1 +/- 4.0 m from ICESat, GPS, and ALS, respectively. The excluded data points may deviate by more than 50 m. In order to suppress the spatially variable noise below a 5-m threshold, 18% of the DEM area is selectively averaged to a final product at varying horizontal spatial resolution. Apart from mountainous areas, the new DEM outperforms other currently available DEMs and may serve as a benchmark for future elevation models such as from the TanDEM-X mission to spatially monitor ice sheet elevation.

Ice thickness distribution and glacier bed of Hallstätter Gletscher

Hallstätter Glacier is the northernmost glacier of Austria. Appendant to the northern Limestone Alps, the glacier is located at 47°28'50'' N, 13°36'50'' E in the Dachstein-region. At the same time with its advance linked to the Little Ice Age (LIA), research on changes in size and mass of Hallstätter glacier was started in 1842 by Friedrich Simony. He observed and documented the glacier retreat related to its last maximum extension in 1856. In addition, Hallstätter Glacier is a subject to scientific research to date. In this thesis methods and results of ongoing mass balance measurements are presented and compared to long term volume changes and meteorological observations. The current mass balance monitoring programm using the direct glaciological method was started 2006. In this context, 2009 the ice thickness was measured with ground penetrating radar. The result are used with digital elevation models reconstucted from historical maps and recent digital elevation models to calculate changes in shape and volume of Hallstätter Glacier. Based on current meteorological measurements near the glacier and longtime homogenized climate data provided by HISTALP, time series of precipitation and temperature beginning at the LIA are produced. These monthly precipitation and monthly mean temperature data are used to compare results of a simple degree day model with the volume change calculated from the difference of the digital elevation models. The two years of direct mass balance measurements are used to calibrate the degree day model. A number of possible future scenarios are produced to indicate prospective changes. Within the 150-year-period between 1856 and 2007 the Hallstätter Glacier lost 1940 meters of its length and 2.23 km**2 in area. 37% of the initial volume of 1856 remained. This retreat came along with a change in climate. The application of a running avarage of 30 years shows an increase in precipitation of 18.5% and a warming of 1.3°C near the glacier between 1866 and 1993. The mass loss was continued in the hydrological years 2006/2007 and 2007/2008 showing mean specific mass balance of -376 mm and -700 mm, respectively. Applying a temperature correction for the different minimum elevations of the glacier, the degree day approach based on the two measured mass balances can reproduce sign and order of magnitude of the volume change of Hallstätter Glacier since 1856. Nevertheless, the relative deviation is significant. Future scenarios show, that 30% of the entire glacier volume remains after subtracting the elevation changes between the digital elevation models of 2002 and 2007 ten times from the surface of 2007. The past and present mass changes of Hallstätter Glacier are showing a retreating glacier as a consequence of rising temperatures. Due to high precepitation, increased with previous warming, the Hallstätter Glacier can and will exist in lower elevation compared to inner alpine glaciers.

The third glacier inventory of North Tyrol, Austria, for 2006

A new, third, glacier inventory (GI3) is presented for North Tyrol, which is based on Airborne Laser Scanning for the year 2006. 447 glaciers covering 235 km**2 are included. 4 small, formerly neglected glaciers have been added. Basic quantities such as size, maximum, minimum and median elevation show large variances. Very recent glacier changes between the former inventory (GI2: 1998) and GI3 show a strong reduction in area (-8%) and mean thickness (-7 m). An asymmetry of mean maximum, minimum and median elevation is quantified with approximately 200 m higher values for south-exposed glaciers. Rates of changes are around 1% per year and 1 m per year between GI2 and GI3. The strongest volume losses occurred for glaciers between 5 and 10 km**2.

(Table 1) Summary statistics of in situ sea-ice characteristics of Ice Station Belgica sites Fabra, Patria/Liège and Brussels in October 2007

Three ice type regimes at Ice Station Belgica (ISB), during the 2007 International Polar Year SIMBA (Sea Ice Mass Balance in Antarctica) expedition, were characterized and assessed for elevation, snow depth, ice freeboard and thickness. Analyses of the probability distribution functions showed great potential for satellite-based altimetry for estimating ice thickness. In question is the required altimeter sampling density for reasonably accurate estimation of snow surface elevation given inherent spatial averaging. This study assesses an effort to determine the number of laser altimeter 'hits' of the ISB floe, as a representative Antarctic floe of mixed first- and multi-year ice types, for the purpose of statistically recreating the in situ-determined ice-thickness and snow depth distribution based on the fractional coverage of each ice type. Estimates of the fractional coverage and spatial distribution of the ice types, referred to as ice 'towns', for the 5 km**2 floe were assessed by in situ mapping and photo-visual documentation. Simulated ICESat altimeter tracks, with spot size ~70 m and spacing ~170 m, sampled the floe's towns, generating a buoyancy-derived ice thickness distribution. 115 altimeter hits were required to statistically recreate the regional thickness mean and distribution for a three-town assemblage of mixed first- and multi-year ice, and 85 hits for a two-town assemblage of first-year ice only: equivalent to 19.5 and 14.5 km respectively of continuous altimeter track over a floe region of similar structure. Results have significant implications toward model development of sea-ice sampling performance of the ICESat laser altimeter record as well as maximizing sampling characteristics of satellite/airborne laser and radar altimetry missions for sea-ice thickness.

Topographic model of Greenland (elevation lines in PanMap and ASCII format)

In this paper, a new high-resolution elevation model of Greenland, including the ice sheet as well as the ice free regions, is presented. It is the first published full coverage model, computed with an average resolution of 2 km and providing an unprecedented degree of detail. The topography is modeled from a wide selection of data sources, including satellite radar altimetry from Geosat and ERS 1, airborne radar altimetry and airborne laser altimetry over the ice sheet, and photogrammetric and manual map scannings in the ice free region. The ice sheet model accuracy is evaluated by omitting airborne laser data from the analysis and treating them as ground truth observations. The mean accuracy of the ice sheet elevations is estimated to be 12-13 m, and it is found that on surfaces of a slope between 0.2° and 0.8°, corresponding to approximately 50% of the ice sheet, the model presents a 40% improvement over models based on satellite altimetry alone. On coastal bedrock, the model is compared with stereo triangulated reference points, and it is found that the model accuracy is of the order of 25-35 m in areas covered by stereo photogrammetry scannings and between 200 and 250 m elsewhere.