Time-Critical Rendering of Huge Ecosystems Using Discrete and Continuous Levels of Detail

2004 ◽  
Vol 13 (6) ◽  
pp. 656-667
Author(s):  
Christopher Zach ◽  
Stephan Mantler ◽  
Konrad Karner

We present a novel level-of-detail selection method for real-time rendering, which works on hierarchies of discrete and continuous representations. We integrate smoothly represented, point-rendered objects with discrete polygonal geometry and demonstrate our approach in a terrain-flyover application. In this testing application the digital elevation model is augmented with forests in accordance with satellite data. The vegetation is rendered as a continuous sequence of splats generated from a procedural description. Further, we discuss enhancements to our basic method to improve its scalability.

Author(s):  
K. Chaidas ◽  
G. Tataris ◽  
N. Soulakellis

Abstract. In recent years 3D building modelling techniques are commonly used in various domains such as navigation, urban planning and disaster management, mostly confined to visualization purposes. The 3D building models are produced at various Levels of Detail (LOD) in the CityGML standard, that not only visualize complex urban environment but also allows queries and analysis. The aim of this paper is to present the methodology and the results of the comparison among two scenarios of LOD2 building models, which have been generated by the derivate UAS data acquired from two flight campaigns in different altitudes. The study was applied in Vrisa traditional settlement, Lesvos island, Greece, which was affected by a devastating earthquake of Mw = 6.3 on 12th June 2017. Specifically, the two scenarios were created by the results that were derived from two different flight campaigns which were: i) on 12th January 2020 with a flying altitude of 100 m and ii) on 4th February 2020 with a flying altitude of 40 m, both with a nadir camera position. The LOD2 buildings were generated in a part of Vrisa settlement consisted of 80 buildings using the footprints of the buildings, Digital Surface Models (DSMs), a Digital Elevation Model (DEM) and orthophoto maps of the area. Afterwards, a comparison was implemented between the LOD2 buildings of the two different scenarios, with their volumes and their heights. Subsequently, the heights of the LOD2 buildings were compared with the heights of the respective terrestrial laser scanner (TLS) models. Additionally, the roofs of the LOD2 buildings were evaluated through visual inspections. The results showed that the 65 of 80 LOD2 buildings were generated accurately in terms of their heights and roof types for the first scenario and 64 for the second respectively. Finally, the comparison of the results proved that the generation of post-earthquake LOD2 buildings can be achieved with the appropriate UAS data acquired at a flying altitude of 100 m and they are not affected significantly by a lower one altitude.


2002 ◽  
Vol 34 ◽  
pp. 355-361 ◽  
Author(s):  
Frank Paul ◽  
Andreas Kääb ◽  
Max Maisch ◽  
Tobias Kellenberger ◽  
Wilfried Haeberli

AbstractA new Swiss glacier inventory is to be compiled from satellite data for the year 2000. The study presented here describes two major tasks: an accuracy assessment of different methods for glacier classification with Landsat Thematic Mapper (TM) data and a digital elevation model (DEM); the geographical information system (GIS)-based methods for automatic extraction of individual glaciers from classified satellite data and the computation of three-dimensional glacier parameters (such as minimum, maximum and median elevation or slope and orientation) by fusion with a DEM. First results obtained by these methods are presented in Part II of this paper (Kääb and others, 2002). Thresholding of a ratio image from TM4 and TM5 reveals the best-suited glacier map. The computation of glacier parameters in a GIS environment is efficient and suitable for worldwide application. The methods developed contribute to the U. S. Geological Survey-led Global Land Ice Measurements from Space (GLIMS) project which is currently compiling a global inventory of land ice masses within the framework of global glacier monitoring (Haeberli and others, 2000).


2002 ◽  
Vol 57 (3) ◽  
pp. 170-183 ◽  
Author(s):  
S. Wunderle ◽  
M. Droz ◽  
H. Kleindienst

Abstract. A method to derive the snow line elevation using NOAA-AVHRR satellite data in combination with a digital elevation model is presented. The AVHRR sensor enables the frequent Observation of snow cover with a sufficiently high temporal resolution. The definition of the snow line and the impact of geocoding errors, as well as errors due to misclassification, are discussed. A comparison of the NOAA-AVHRR data with data from the higher resolution IRS-WiFS indicates that even at a spatial resolution of 1.1 km, a quantitative analysis of the snow line elevation is possible. The influence of different winter conditions in Switzerland on the elevation of the snow line is reflected in satellite data from 1990,1996 and 1999. The results of the investigation were, firstly the presentation of the spatial pattern of the average snow line elevation, secondly the derivation of snow line signatures for three regions. These were then compared with the Overall alpine snow line signature.


2009 ◽  
Vol 3 (1) ◽  
pp. 113-123 ◽  
Author(s):  
J. A. Griggs ◽  
J. L. Bamber

Abstract. We have developed a new digital elevation model (DEM) of Antarctica from a combination of satellite radar and laser altimeter data. Here, we assess the accuracy of the DEM by comparison with airborne altimeter data from four campaigns covering a wide range of surface slopes and ice sheet regions. Root mean squared (RMS) differences varied from 4.75 m, when compared to a densely gridded airborne dataset over the Siple Coast region of West Antarctica to 33.78 m when compared to a more limited dataset over the Antarctic Peninsula where surface slopes are high and the across track spacing of the satellite data is relatively large. The airborne data sets were employed to produce an error map for the DEM by developing a multiple linear regression model based on the variables known to influence errors in the DEM. Errors were found to correlate highly with surface slope, roughness and density of satellite data points. Errors ranged from typically ~1 m over the ice shelves to between about 2 and 6 m for the majority of the grounded ice sheet. In the steeply sloping margins, along the Peninsula and mountain ranges the estimated error is several tens of metres. Less than 2% of the area covered by the satellite data had an estimated random error greater than 20 m.


Resources ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 126 ◽  
Author(s):  
Keisuke Yoshida ◽  
Keijiro Okuoka ◽  
Alessio Miatto ◽  
Liselotte Schebek ◽  
Hiroki Tanikawa

Despite ever-increasing material extraction on the global scale, very few studies have focused on the relationship between mining activities, overburden, and landfilling. This is mainly due to the lack of statistical data. Yet, large mining activities cause environmental strain to the natural environment, and are often cause of irreversible alterations to the natural landscape. To circumvent this problem, we develop a methodology that employs the digital elevation model and land cover to detect and analyze mining and landfilling site over time. We test our methodology with the case of Germany for the years 2000–2010. We then confront our results with statistically available data, to verify whether this methodology can be applied to other countries. Results from the analysis of satellite data give 15.3 Pg of extracted materials and 7.8 Pg of landfilled materials, while statistics report 29.4 Pg and 1.8 Pg, respectively. This large difference was likely due to the different frequency of recording, where satellite data was updated after 10 years, while statistics were reported yearly. The analysis of the anthropogenic disturbance with spatial information can effectively contribute to observe, analyze, and quantify mining activities, overburden, and landfills, and can thus provide policy makers with useful and practical information regarding resource usage and waste management.


2008 ◽  
Vol 2 (5) ◽  
pp. 843-872 ◽  
Author(s):  
J. A. Griggs ◽  
J. L. Bamber

Abstract. We have developed a new digital elevation model (DEM) of Antarctica from a combination of satellite radar and laser altimeter data. Here, we assess the accuracy of the DEM by comparison with airborne altimeter data from four campaigns covering a wide range of surface slopes and ice sheet regions. RMS differences varied from 4.84 m, when compared to a densely gridded airborne dataset over the Siple Coast region of West Antarctica to 29.28 m when compared to a more limited dataset over the Antarctic Peninsula where surface slopes are high and the across track spacing of the satellite data is relatively large. The airborne data sets were employed to produce an error map for the DEM by developing a multiple linear regression model based on the variables known to influence errors in the DEM. Errors were found to correlate highly with surface slope, roughness and density of satellite data points. Errors ranged from typically ~1 m over the ice shelves to between about 4 and 10 m for the majority of the grounded ice sheet. In the steeply sloping margins, along the Peninsula and mountain ranges the estimated error is several tens of metres. Slightly less than 7% of the area covered by the satellite data had an estimated random error greater than 20 m.


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