Optical Trick Inspired By Blue Morpho Butterfly

http://www.fastcompany.com/biomimicry/never-before-seen-optical-trick-creates-ultra-secure-cash

Topographic Laser Ranging and Scanning: Principles and Processing - Book Review

Reviewed by
Jason A. Tullis, Assistant Professor, Department of Geosciences, University of
Arkansas, Fayetteville, Arkansas

"Topographic Laser Ranging and Scanning: Principles and Processing targets a multidisciplinary environmental research audience with a detailed discussion of topographic lidar, including its history, technology, calibration, quality, and management as well as a variety of techniques for lidar-assisted information extraction. This book is organized into 19 chapters, with 29 contributors from academic, commercial, and governmental organizations in the United States, Finland, Canada, Germany, Australia, Austria, China, France, and the United Kingdom. A signifi cant number of grayscale fi gures, tables, and equations are complemented by chapter-level references, 12 color fi gures, an index, and a key to abbreviations. The 19 chapters are logically organized into four parts...."

more information and source: http://www.asprs.org/publications/pers/2009journal/october/review.pdf

Underwater 3D shape reconstruction by fringe projection - CAA

Hallo everybody!

Sorry for the long time...

My second fovourite presentatiton was from CAA: "Underwater 3D shape reconstruction by fringe projection"
Great research at the University of Calabria, Italy (Bianco, G., Bruno, F., Muzzupappa, M., Luchi, M.L.).
Our Institute accomplished a big camera calibration project for underwater archaeological documentation, which was an interesting topic.


Part of Introcuction:

"....In this work, we have tested the effectiveness of a
whole-field structured light technique, based on
fringe projection, in underwater environment. The
Fringe Projection Technique (FPT) is widely used in
air (RASTOGI and GORTHI, 2010), and consists of
projection and acquisition of sinusoidal patterns on
the object (in the simplest case, one pattern is
enough). The system is composed by a video
projector and a digital camera, and the geometrical
setup is based on the principle of optical
triangulation. The recorded images are analyzed to
evaluate the phase-map of the object - which contains
the height information - with a signal processing
technique such as Fourier Transform (FT) , Wavelet
Transform (WT) , Windowed Fourier Transform
(WFT) , Spatial Phase Detection (SPD) or Phase
Stepping (PS). Any of these techniques of phase
measurement provides a discontinuous phase map of
the object (wrapped): so it becomes necessary to use
phase unwrapping in order to obtain a continuous
phase distribution (SURREL, 1998). By knowing the
intrinsic (focal distances, coordinates of the principal
points, and distortions) and extrinsic (relative
positions between the optical devises) parameters,
one can calculate the point clouds from the
triangulation between a optical ray of the camera (at
i,j pixel with phase value φi,j) and the relative plane
in the projector frame at the same phase value...."

TerraFormatics Live Report CAA, Granada

Hallo everybody,

we will send on next week some information from CAA. The program of the congress is very interesting, lot of laser scanning case studies, great meeting!

First day

Tuesday great workshops: Laser Scanner systems for Archeological surveys, Digital Documentation in Archaeology, Use of 3D techniques in Cultural Heritage……

More news later!

Program on this website: http://www.caa2010.org/

The International LiDAR Mapping Forum 2010 - Denver, USA

"How LiDAR is being used in Haiti

A new last minute addition to the International LiDAR Mapping Forum conference program will include two presentations on how LiDAR is being used in Haiti to assess the damage from the recent earthquake and the future probability of subsequent earthquakes.

Imagery of the region damaged by the M 7 Haiti earthquake, including high-resolution photography and airborne LiDAR, has revealed a variety of ground failure that resulted from shaking. Surprisingly, the Enriquillo Fault seems to have not ruptured at the ground surface, so the negative result obtained from imagery has significant implications. The USGS issued a statement, based on imagery analysis, that because it is clear that the rupture of the Enriquillo Fault was clearly farther west than Port-au-Prince, and because rupture was buried deep on the fault, there is a significant risk of not only regular aftershocks, but also the threat of a subsequent large event that could occur even closer to Port-au-Prince. The probability of one or more subsequent earthquakes of M 7 or greater increased by about 3% for the 30 days following 21 January 2010. Although this is a low probability, it would be a potentially very high impact event. High-resolution imagery was crucial to this assessment." - source: www.lidarmap.org

Program: http://www.lidarmap.org/conference/ILMF10_ConferenceProgram.pdf

New Book: Airborne and Terrestrial Laser Scanning

"Written by a team of international experts, this book provides a comprehensive overview of the major applications of airborne and terrestrial laser scanning. The book focuses on principles and methods and presents an integrated treatment of airborne and terrestrial laser scanning technology."


link: http://www.librario.com/2472

Mapping Riparian Vegetation with Lidar Data

Combining GIS and lidar data enabled predictive mapping for riparian areas for a portion of the Sierra Nevada mountain range. Riparian areas pose many problems for vegetation modeling because of their narrow width, dendritic pattern, and the sensitivity of plant species to subtle changes in topography that cannot be easily recorded by coarse-scale digital elevation models (DEMs). Vegetation mapping and monitoring in riparian areas have relied heavily on field-based surveys that record the distribution of plant communities along transects perpendicular to the river. Typically, these studies also collect ancillary variables, such as stage elevation or height above the river (HAR), soil texture, and soil moisture, that are used to predict the distribution of vegetation types. However, these methods are extremely time consuming and do not allow for the development of predictive maps because the data collected cannot easily be extrapolated to a larger region. GIS and lidar data provide an opportunity to derive variables, such as HAR, for large areas, making wall-to-wall predictive mapping a possibility.“

Interesting paper, authors: By Thomas E. Dilts, Jian Yang, and Peter J. Weisberg, University of Nevada, Reno

ArcGIS Spatial Analyst extension was used, good example to create a model with ArcGIS from LiDAR dataset.

Link: http://www.esri.com/news/arcuser/0110/files/mapping-with-lidar.pdf

AN INTEGRATED WORKFLOW FOR LIDAR / OPTICAL DATA MAPPING FOR SECURITY APPLICATIONS

SECURITY APPLICATIONS:

"ABSTRACT:

This paper elucidates the potential of LiDAR data for information generation for security applications. The study is embedded in the EU Network of Excellence GMOSS. General, security applications cover a large area from infrastructure monitoring (e.g. power stations, pipelines) or border monitoring to less tangible threats like terrorism and civil security / homeland security. It is demonstrated that for those security applications where the birds eye view can generally provide useful information LiDAR data are increasingly a valuable source of information, either stand alone or – preferable – in combination with optical data. The empirical work focuses on the extraction of some buildings and power lines. It is demonstrated that aggregated grid data in form of a DTM and DSM are only partially suitable to extract linear and point-type features such as power lines or small power transformation stations. Detectability clearly depends on the spatial resolution but generally 3D point clouds from first and last pulse information allow more sophisticated object extraction methods."

Full paper:

http://earth.definiens.com/sites/default/files/319_139_full.pdf

Integration of regional to outcrop digital data: 3D visualisation

A very interesting paper....

"Abstract

Multi-scale geological models contain three-dimensional, spatially referenced data, typically spanning at least six orders of magnitude from outcrop to regional scale. A large number of different geological and geophysical data sources can be combined into a single model. Established 3D visualisation methods that are widely used in hydrocarbon exploration and production for sub-surface data have been adapted for onshore surface geology through a combination of methods for digital data acquisition, 3D visualisation, and geospatial analysis. The integration of georeferenced data across a wider than normal range in scale helps to address several of the existing limitations that are inherent in traditional methods of map production and publishing. The primary advantage of a multi-scale approach is that spatial precision and dimensionality (which are generally degraded when data are displayed in 2D at a single scale) can be preserved at all scales. Real-time, immersive, interactive software, based on a ‘‘3D geospatial’’ graphical user interface (GUI), allows complex geological architectures to be depicted, and is more inherently intuitive than software based on a standard ‘‘desktop’’ GUI metaphor. The continuing convergence of different kinds of geo-modelling, GIS, and visualisation software, as well as industry acceptance of standardised middleware, has helped to make multi-scale geological models a practical reality. Thisis illustrated with two case studies from NE England and NW Scotland."

More on this website:

http://www.dur.ac.uk/r.r.jones/Downloads/C&G2008_Jones_etal_Vis_Multi-scale_Models.pdf

Building of robust multi-scale representations of LiDAR-based digital terrain model based on scale-space theory

DTMs are the most important products of airborne laser scanning systems. I search frequently the new methods….here is an example (title...) from Tarig A. Ali, very interesting research! More in "Optics and Lasers in Engineering" - 03. 2010

Until march....

And what is scale-space theory?

http://www.cs.jhu.edu/~misha/Fall07/Papers/intro-to-scalespace.pdf

Virtual Archaeologists Recreate Parts of Ancient Worlds

Hallo everybody!

Happy New Year! Sorry for the long time...December was not the best month. :)

My favorite new paper from Michael Bawaya:

"Archaeologists are using computers to recreate the environment and conditions of the past, including objects, buildings, and landscapes with human actors, such as ancient battles. The field is a natural evolution of archaeology in the digital age. And although virtual archaeology arose in the mid-1990s, it is only now going mainstream, as archaeologists realize the benefits of using computers to make the most of their necessarily incomplete data and as costs go down. Archaeologists argue that virtual worlds offer the best way to test complex hypotheses. The field also gets a boost from the entertainment industry: The technology is the same as that used in video games and movie special effects, and many universities have recently added 3D modeling programs......."

http://www.sciencemag.org/cgi/content/full/327/5962/140

Full-Waveform filtering

Next generation scanners are integrated with full-waveform data acquisitions properties. Every single return pulse is documented. We can research the vertical conditions of the forest areas. Tree, bush, grass...different data class.


Interesting paper about full-waveform datasets....

INTEGRATION OF FULL-WAVEFORM INFORMATION INTO
THE AIRBORNE LASER SCANNING DATA FILTERING PROCESS
Y. -C. Lin and J. P. Mills

"ABSTRACT
Terrain classification of current discrete airborne laser scanning data requires filtering algorithms based on the spatial relationship between neighbouring three-dimensional points. However, difficulties commonly occur with low vegetation on steep slopes and when abrupt changes take place in the terrain. This paper reports on the integration of additional information from latest generation full-waveform data into a filtering algorithm in order to achieve improved digital terrain model (DTM) creation. Prior to a filtering procedure, each point was given an attribute based on pulse width information. A novel routine was then used to integrate pulse width information into the progressive densification filter developed by Axelsson. The performance was investigated in two areas that were found to be problematic when applying typical filtering algorithms. The derived DTM was found to be up to 0.7 m more accurate than the conventional filtering approach. Moreover, compared to typical filtering algorithms, dense low vegetation points could be removed more effectively. Overall, it is recommended that integrating waveform information can provide a solution for areas where typical filtering algorithms cannot perform well. Full-waveform systems are relatively cost-effective in terms of providing additional information without the need to fuse data from other sensors.

CONCLUSIONS
This study set out to investigate whether information derived from the latest generation full-waveform, small-footprint airborne laser scanning data could improve digital terrain modelling. A novel routine was designed to integrate waveform information into a commonly used filtering algorithm. The preliminary results have demonstrated that integrating pulse width information can provide a solution for areas where conventional filtering algorithms cannot perform well. On the top of an artificial mound, points rejected (Type I error) by a typical filtering algorithm can be correctly included in the developed routine. More low vegetation can also be correctly removed. However, rough or steep terrains with low vegetation cover, as well as forest terrain, still require further investigation and detailed validation. In addition, although identifying vegetation points becomes easier with the help of waveform information, it may be the case that in some densely vegetated areas insufficient “true” ground points exist for high-resolution DTM generation. In such cases, it might still be better to assume that the lowest point within a specified or adaptive window size is a ground point. The performance of existing filtering algorithms depends on the type of landscape (Sithole and Vosselman, 2004). Such approaches may require that users determine which type of landscape is being processed and then specify optimal parameters. As demonstrated in this paper, by using waveform information it is possible to automatically determine the landscape characteristics and then use the optimal parameter set for that specific landscape type. This will improve the automation of filtering procedures since less effort is required by users. Moreover, compared to ALS intensity values, pulse width information is easier to apply to different surveys since neither prior calibration or normalization procedures are required. Using full-waveform ALS data provides valuable physical and geometric information simultaneously. Such systems are relatively cost-effective in terms of providing multiple-information without the need to fuse data from other sensors."

Pathway detection with LiDAR

Mapping of pathways is very difficult. We don't know exactly, where are the hidden ways in the forest, because we don't see through the trees on the aerial photos. :)....but, with LiDAR datasets that kind of mapping is possible.....important information is this, military reasons etc..




PATHWAY DETECTION AND GEOMETRICAL DESCRIPTION FROM ALS DATA IN
FORESTED MOUNTANEOUS AREA
Nicolas David, Cl´ement Mallet, Thomas Pons, Adrien Chauve, Fr´ed´eric Breta


"ABSTRACT:
In the last decade, airborne laser scanning (ALS) systems have become an alternative source for the acquisition of altimeter data. Compared to high resolution orthoimages, one of the main advantages of ALS is the ability of the laser beam to penetrate vegetation and reach the ground underneath. Therefore, 3D point clouds are essential data for computing Digital Terrain Models (DTM) in natural and vegetated areas. DTMs are a key product for many applications such as tree detection, flood modelling, archeology or road detection. Indeed, in forested areas, traditional image-based algorithms for road and pathway detection would partially fail due to their occlusion by the canopy cover. Thus, crucial information for forest management and fire prevention such as road width and slope would be misevaluated. This paper deals with road and pathway detection in a complex forested mountaneous area and with their geometrical parameter extraction using lidar data. Firstly, a three-step image-based methodology is proposed to detect road regions. Lidar feature orthoimages are first generated. Then, road seeds are both automatically and semi-automatically detected. And, a region growing algorithm is carried out to retrieve the full pathways from the seeds previously detected. Secondly, these pathways are vectorized using morphological tools, smoothed, and discretized. Finally, 1D sections within the lidar point cloud are successively generated for each point of the pathways to estimate more accurately road widths in 3D. We also retrieve a precise location of the pathway borders and centers, exported as vector data.

CONCLUSION
A full workflow for the pathway detection on mountainous area, from raw ALS data to vector database objects, have been proposed. With the increasing use of ALS data for DTM generation, such workflow should enabled to decrease the data acquisition cost for mapping institute. The detected pathways could also be used both for improving DTM generation and as features for strip adjustment and registration. The results show the feasibility of generating and updating pathway databases from ALS data, but their quality is still insufficient to be used on a production context for mapping agencies. In order to tackle the mentioned issues, it has been draw perspectives to improve robustness and automaticity of pathway detection."

Geography and LiDAR II.

Interesting paper from Australia....
mapping of rivers from LiDAR datasets is very popular too....flood risk management.....

OPERATIONAL MAPPING OF THE ENVIRONMENTAL CONDITION OF RIPARIAN
ZONES OVER LARGE REGIONS FROM AIRBORNE LIDAR DATA
K. Johansen, L. Arroyo and S. Phinn

"ABSTRACT:
Riparian zones maintain water quality, support multiple geomorphic processes, contain significant biodiversity and also maintain the aesthetics of the landscape. Australian state and national government agencies responsible for managing riparian zones are planning missions for acquiring remotely sensed data covering the main streams in Victoria, New South Wales, and parts of Queensland and South Australia. The objectives of this paper are to: (1) assess the ability of LiDAR data for mapping the environmental condition of riparian zones; and (2) provide specifications for capturing and analyzing the LiDAR data for riparian zone mapping at large spatial extents (> 1000 km of stream length). LiDAR derived digital elevation models, terrain slope, intensity, fractional cover counts and canopy height models were used for mapping riparian condition indicators using simple algorithms and more complex objectoriented image analysis. The results showed that LiDAR data can be used to accurately map: water bodies (producer’s accuracy = 93%); streambed width (Root Mean Square Error (RMSE) = 3.3 m); bank-full width (RMSE = 6.1 m); riparian zone width (RMSE = 7.0 m); width of vegetation (RMSE = 5.6 m); plant projective cover (RMSE = 12%); vegetation height classes (vertical accuracy < r2 =" 0.40)."> 100,000 km of stream length."

Geography and LiDAR

researches at forest areas are a very popular part of the LiDAR know-how....

One of my favorite paper is from ISPRS Laserscanning '09.....very useful and innovative ideas, we need that kind of work, and not the discussions of RMS faults....how can I correct another mm-s....


A DECIDIOUS-CONIFEROUS SINGLE TREE CLASSIFICATION AND INTERNAL
STRUCTURE DERIVATION USING AIRBORNE LIDAR DATA
C. Ko, G. Sohn, T. K. Remmel

"ABSTRACT:
This project has two main purposes; the first is to perform deciduous-coniferous classification for 65 trees by using the leaf-on single flight LiDAR data. It was done by looking at the geometrical properties of the crown shapes (spherical, conical or cylindrical), these shapes were developed by a rule-driven method Lindenmayer Systems (L systems). Two more parameters that are data driven (convex hull analysis and buffer analysis) were developed to further capture the geometrical differences between deciduous and coniferous trees. Proposed methods are scale independent and arithmetically simple, they were developed simply by looking at the geometrical differences between the two types of trees. The classification rate was cross-validated and trees are 85% - 88% correctly classified. The second part of the project is to derive the internal structures of the LiDAR tree according to the results obtained from the first part. Internal structures include bole and branches; the location and orientation of the bole was done by connecting the geographic centres of horizontal slices of the tree. The branches were derived by k-means clustering techniques, different types of trees will yield a different type of branching structures for better visualization.

DISCUSSION / CONCLUSION
There are two major types of LiDAR systems for research and commercial use, full waveform and discrete returns. This paper has used only the discrete returns of the range data, and by studying the geometry of the crown shape properties, we classified the different crowns into two major classes, deciduous and coniferous. From the classified results, bole and branching structures were reconstructed according to the type of tree. The shape of the tree crown is inherited in the gene (adaptation) and therefore a certain species will have the similar crown shape and branching structures. The other factor affecting crown shape and branching structure is the growing strategies, which is adopted by the growing neighbour environment and those are more difficult to model (Horn, 1971). As a result, crown geometry is believed to be an important piece of information for species classification. By using just the three geometrical shapes (sphere, cone and cylinder), results were improved from 65% to 67% when the outliers were removed. If other parameters are included (area to volume ratio of convex hull and point to polygon buffering analysis), results were improved from 85% to 88%. Using crown shapes to classify trees is an intuitive method, but in this study it did not show promising results. By looking at the other geometrical properties, the results for classification increased considerably. Although different from what was expected, it is still believed crown shape and internal structure are good indicators for classifying trees, and future studies should be conducted in this direction. This method of classification is quite simple to produced and arithmetically easy. Tree bole and branches reconstructions are for visualization, but can also be used to study growth behaviour and to provide insight regarding why trees grow in a particular directions. These results are useful in many types of studies. For example, it can be used to study the potential hazards of a tree growing into structures, by classifying trees into deciduous and coniferous provide a better growth estimates."

Outcrop Modeling

I like geography...our "terra" is so complex system, I think we shold be happy, that we here live....I open a beer....:)





Second paper about photogrammetry and LiDAR:

TERRESTRIAL LASER SCANNING COMBINED WITH PHOTOGRAMMETRY FOR
DIGITAL OUTCROP MODELLING
S. J. Buckley, E. Schwarz, V. Terlaky, J. A. Howell, R. W. C. Arnott


"ABSTRACT:
The integration of 3D modelling techniques is often advantageous for obtaining the most complete and useful object coverage for many application areas. In this paper, terrestrial laser scanning and digital photogrammetry were combined for the purposes of modelling a geological outcrop at Castle Creek, British Columbia, Canada. The outcrop, covering approximately 2.5 km2, comprised a smooth, scoured surface where recent glacial retreat had left the underlying sedimentary rocks exposed. The outcrop was of geological interest as an analogue to existing hydrocarbon reservoirs, and detailed spatial data were required to be able to map stratigraphic surfaces in 3D over the extent of the exposure. Aerial photogrammetry was used to provide a 2.5D digital elevation model of the overall outcrop surface. However, because the sedimentary strata were vertically orientated, local vertical cliffs acted as cross-sections through the geology, and these were surveyed using a terrestrial laser scanner and calibrated digital camera. Digital elevation models (DEMs) created from both methods were registered and merged, with the fused model showing a higher fidelity to the true topographic surface than either input technique. The final model was texture mapped using both the aerial and terrestrial photographs, using a local triangle reassignment to ensure that the most suitable images were chosen for each facet. This photorealistic model formed the basis for digitising the geological surfaces in 3D and building up a full 3D geocellular volume using these surfaces as input constraints. Because of the high resolution and accuracy of the input datasets, and the efficacy of the merging method, it was possible to interpret and track subtle surface separations over the larger extents of the outcrop.

CONCLUSIONS
Terrestrial laser scanning and digital aerial photogrammetry were combined to create a digital elevation model of the Castle Creek outcrop, British Columbia, Canada. The integration of the two techniques proved to be essential to capture both the large outcrop surface and the near-vertical cliff sections which were essential for being able to recreate the 3D orientation of geological surfaces. Use of surface matching allowed the aerial photogrammetric DEM to be accurately registered, without the problems of collecting a conventional photocontrol point arrangement in a rugged and remote area. Texture mapping with aerial and terrestrial images resulted in a photorealistic model that could be used by geologists for interpretation, education and quantitative analysis. This model demonstrated the application of geomatics for geological outcrop analogue modelling, allowing the spatial accuracy and resolution to be enhanced. A geocellular volume was created from digitised features, which will be used by geologists to improve the geological understanding of the Castle Creek outcrop."

Integration Approach of Photogrammetric and LiDAR

There are a lot of discussions, photogrammetric or LiDAR....I think, for this question difficult to find the answers, different projects, different solutions....maybe photogrammetric and LiDAR...we must use every opportunity to complete our work...


Here is a paper about integration techniques:

NEW INTEGRATION APPROACH OF PHOTOGRAMMETRIC AND LIDAR
TECHNIQUES FOR ARCHITECTURAL SURVEYS
F. Nex, F. Rinaudo

"ABSTRACT:
In the last few years, LIDAR and image-matching techniques have been employed in many application fields because of their quickness in point cloud generation. Nevertheless, these techniques do not assure complete and reliable results, especially in complex applications such as architectural surveys: laser scanning techniques do not allow the correct position of object breaklines to be extracted while image matching results require an accurate editing and they are not acceptable for bad-textured images. For this reason several authors have already suggested overcoming of these problems through a combination of LIDAR and photogrammetric techniques. These works considers the integration as the possibility to share point clouds generated by these techniques; however, a complete and automatic integration, in order to achieve more complete information, has never been implemented. In this paper, a new integration approach is proposed. This integration is focused on the possibility of overcoming the problems of each technique. In this approach LIDAR and multi-image matching techniques combine and share information in order to extract building breaklines in the space, perform the point cloud segmentation and speed up the modelling process in an automatic way. This integration is still an ongoing process: the algorithm workflow and first performed tests on real facades are presented in this paper, in order to evaluate the reliability of the proposed method; finally, an overview on the future developments is offered.

CONCLUSIONS AND FUTURE DEVELOPMENTS
The performed tests have allowed a first evaluation to be made of the potentiality of the proposed method, even though this analysis is not complete yet and further tests and changes have to be defined. Nevertheless, the results have already shown the reliability of the algorithm. In general, the results depend on the image taking configuration: almost normal case images are weak in the matching of edges parallel to epipolar lines. This problem could be overcome by just using more than three images and an ad hoc taking geometry. Images acquired at different heights allow epipolar lines with different direction to be obtained (Figure 9); instead, convergent images (more than 20°) could be subject to problems due to affine deformations. The taking distance should be chosen according to the degree of detail requested in the survey: in general, a 15 m distance can be considered the maximum for architectural objects to be drawn at 1:50 scale. The algorithm has shown that it can achieve good results for repetitive patterns, particularly if more than three images are used. The number of mismatches is usually low and decreases as the number of images increases. Glass, however, must always be deleted from all the images, in order to avoid mismatches. Dense point clouds in the LIDAR acquisition are not strictly necessary during the matching process while they are necessary instead in the filtering of the geometric edges. In fact the algorithm has shown some problems because of the presence of shadows close to the geometric breaklines; a more dense point cloud could overcome this problem. Furthermore, rounded edges are difficult to model as it is difficult to identify the position of the breakline in the image: in this situation, the algorithm does not allow good results to be obtained. It is expected that the geometric precision in the edge matching will be increased by implementing a Least Square Matching (LSM). A first step will be to perform a Multi-Photo LSM of dominants points; then it is planned to carry out an LS B-Snake matching (Zhang, 2005) which could slightly improve the quality of extracted edges. A great advantage in the traditional point cloud segmentation will be obtained from the extracted edges. The segmentation will be guided by edges that define the boundaries of each façade portion and fix a constraint in the region growing algorithm. In this way it is expected to make the modelling procedures easier."

Normalization of LIDAR intensity

There are a lot of research today about laser intensity, because we find a huge potential at Lidar intensity datasets. These information could help by different processes, like segmentation, classification or visualization. All of lidar applicatnions based on x,y,z parameters, and I think, in the future, we will use this extra information (i=intensity), which could mean 4th dimension of lidar.

Normalization of intensity is a very useful direction, here is a new paper:

NORMALIZATION OF LIDAR INTENSITY DATA BASED ON
RANGE AND SURFACE INCIDENCE ANGLE
B. Jutzi, H. Gross

" ABSTRACT:
The analysis of airborne laser scanner data to extract surface features is of great interest in photogrammetric research. Especially for applications based on airborne measurements, where the intensity is crucial (e.g. for segmentation, classification or visualization purposes), a normalization considering the beam divergence, the incidence angle and the atmospheric attenuation is required. Our investigations show that the same material of a surface (e.g. gabled roof) yields to different measured values for the intensity. These values are strongly correlated to the incidence angle of the laser beam on the surface. Therefore the intensity value is improved with the incidence angle derived by the sensor and object position as well as its surface orientation. The surface orientation is estimated by the eigenvectors of the covariance matrix including all object points inside a close environment. Further the atmospheric attenuation is estimated. The adaptation of vegetation areas is disregarded in this study. After these improvements the intensity does no longer depend on the incidence angle but may be influenced by the material of the object surface only. For surface modelling the Phong model is introduced, considering diffuse and specular backscattering characteristics of the surface. A measurement campaign was carried out to investigate the influences of the incidence angle on the measured intensity. By considering the incidence angle and the distance between sensor and object the laser data captured from different flight paths (data stripes) can be successfully fused. In our experiments it could be shown that the radiometric normalization of the intensity for the investigated areas are improved.


DISCUSSION AND CONCLUSION
For assessing the normalized intensity values nearly
homogenous regions have been selected interactively. The
variation parameter is selected as measure for the comparison of
the values before and after normalization. Mean and standard
deviation of this measure over all regions decreases by the
normalization, especially if all flights are included. For pulsed
laser systems a strong intensity variation could be observed. The
intensity inside a region shows a high variance even for a
constant incidence angle. This may caused by material features
or local surface effects. For nearly all regions the results for the intensity have been improved, even with region disturbances on the roofs like chimneys. The Lambertian model fits the investigated surfaces well. For specular reflectance based on the Phong model no significant improvements could be derived. This might depend on the diffuse backscattering characteristic of the material. Further investigations for this study were not possible because only one data set with surfaces of a single material with different orientations was available. For terrestrial laser data enhanced results can be expected, with a lower variance of the intensity, due to a better signal-to-noise ratio for the measured data. This paper proposes a general approach for intensity normalization considering diffuse and specular scattering characteristics of the surface. This assumption should be proved in future by investigating reference targets where the
backscattering characteristic is known or could be measured by reference measurements."

NETWORK SNAKES and LiDAR

I think, there is a lot of potential in laser intensity information. Now we use at the most applications the X,Y,Z parameters. We must collect more experiences about LiDAR intensity, because this extra information is very dependent from different properties (material, topography, laser footprint, flight direction....more about these later).

Very unique paper about the feature detection with help of intensity information:


ADAPTATION OF ROADS TO ALS DATA BY MEANS OF NETWORK SNAKES
J. Goepfert, F. Rottensteiner

"ABSTRACT:

In the Authoritative Topographic Cartographic Information System (ATKIS®), which is the main public topographic data base inGermany, the heights and the 2D positions of objects such as roads are stored separately in the digital terrain model (DTM) anddigital landscape model (DLM). However, for many applications a combined visualization and processing of these two data sets is useful, leading to the demand for a 3D representation of the objects. For this purpose an integration of the height and position is essential. However, discrepancies exist between the DLM and the DTM due to different kinds of acquisition, processing, and modeling. This inconsistency has to be solved within the integration algorithm. Airborne Laserscanning (ALS) is used to acquire the height information for the DTM. Therefore, intensity values of the ALS echoes, which contain the reflectance properties of the lluminated objects, as well as object heights can be exploited in addition to the terrain height. However, the ALS data contain the information related to the DLM-objects only implicitly. Usually, features, for example edges or distinctive points, have to be extracted which can be connected to DLM-objects to realize the integration process. In this paper the matching of the data sets is realized by network snakes which are able to use the implicit ALS information about the position of the DLM-objects without the feature extraction step. The initialization of the contour with the vector data enables the use of ALS data as image energy for an iterative optimization process. Examples are given which apply the concept of network-snakes for the adaptation of a road network to ALS data taking advantage of the prior known topology.

CONCLUSION:

In this paper an active contour approach is applied to the
adaptation of a road network to ALS data. Even with a simple
definition of the image energy by combining ALS height and
intensity information promising results could be achieved.
Based on the exploitation of the topology of given initialisation
the snake converges to the desired position in comparison to the
ground truth. Contour parts connected by nodal points support
each other during the optimisation process.
The introduced algorithm offers many possibilities regarding
the integration of object knowledge for future research. For
example, constraints about the shape of the objects (parallelism
of road edges, slope constraints) or relations to other ATKIS
objects can be incorporated in the initialisation as well as in
additional energy terms. Furthermore, a more sophisticated
formulation of suitable image energies concerning different
vector objects can improve the applicability of the method.
Additionally, the algorithm can be extended to other DLM
objects having a relation to features in ALS data such as rivers.
Subsequently, all the adapted objects provide a dense network
of shift vectors which can be used in addition to prior accuracy
knowledge in order to improve the consistency of the DLM and
ALS data."

Image energy from a combination of intensity and height values (green: ground truth; blue: initialisation; red: final position)