Explanation for the Output of the Iasoberg Model
Instead of a Legend for the interpretation of the displays of the output of the Iasoberg Model, a detailed description of the elements of the model will provide the observer with a more comprehensive understanding of what the elements represent.
It would be very useful for the reader to take the time to view The Allias Effect – The Iasoberg Model – The Future presentation and read the paper on the Papua New Guinea and Western South American Terrestrial Gravitational Anomaly Plane to gain a reasonable understanding of the Allais Effect and the Iasoberg Model. The links to these two documents are below:
There are 4 Iasoberg Model spatial configurations that are generated by various algorithms (programs) and displayed on most graphs and charts. The iasobergs (3 band 3xred and 3xgreen bands) and the celestial subpoints (sun – red, blue – moon and green – center of the galaxy) are essentially fixed as the Earth rotates through them in a 24 hour period. The other 2 configurations, ie the PNGWSATGA Plane and the boundaries of the tectonic plates obviously rotate with the Earth.
So let’s start with the iasobergs. The term iasoberg, was a term coined as the generic descriptor of the regions where the Iasoberg Model output intersect the Earth’s surface to indicate the influence of the Allais Effect. Initially, an iasoberg was displayed as a line on the Earth’s surface to indicate its location. This early model consisted of 4 iasobergs (lines), two associated with the Sun and 2 with the two with center of the galaxy. The solar iasobergs were focused at the barycenter of the Earth Moon system and the anti-barycenter, which is a point on the Earth Moon axis opposite to the barycenter and at the same distance from the center of the Earth to the barycenter. The galactic iasobergs were configured similarly to the solar iasobergs.
Prior to a study of severe wind events in August 2008, 2 additional iasobergs had been developed to provide additional intersections on the Earth’s surface for investigating links between event(s) and the output of the model. These two additional iasobergs were styled the Solar and Galactic Earth Centric Iasobergs focused at the mass center of the Earth. The geometry of these Iasobergs was as per the initial 4. The lines were further developed into 3 bands for each iasoberg. The 3 band iasoberg was developed as an exploratory representation of the observations recorded in the Saxl and Allen experiment (1970) and the 3 clusters of severe events described in the severe wind study. All the work and results presented in Note 4, a study on severe wind events in August 2008 in continental USA, were based on the current versions of the model and its associated software, the Iasoberg Model algorithms. The current set of 6 iasobergs are configured with 3 bands (3 iasobergs are linked to the Sun and are displayed with red dots and lines, and 3 linked to the center of the galaxy – similarly displayed in green).
The 3 solar linked iasobergs are shown with red dots and vertical lines on various maps and charts. The 3 bands of dark red dots indicate the iasoberg focused at the Earth Moon System barycenter styled the Solar Fundamental Iasoberg. The 3 bands of vertical lines indicate the iasoberg focused at the center of the Earth styled the Earth Centric Solar Iasoberg. And the 3 bands of light red dots indicate the iasoberg focused at the anti barycenter styled the Solar Mirror Image Iasoberg. The galactic/green iasobergs are configured and styled similarly as the solar iasobergs, except they are linked to the center of the galaxy.
Next, we have 3 points which are included in all displays; they are the subpoints of the Sun (red), Moon (blue) and center of the galaxy (green). The subpoint is where the axis between the above celestial body and the center of the Earth intersects the surface of the Earth. We have found in some of our work that their location in conjunction with the iasobergs have correlated with observations/reports of various geophysical events.
Thirdly, we have the elements associated with PNGWSATGA Plane (great circle shown as a red line) and iasospots (Iasospot 1 – PNG Magenta polygon – Iasospot 2 – WSA cyan polygon) which are shown in all maps/charts. The polygons represent two regions of the earth where there are significant terrestrial gravitational anomalies. Two additional elements have been included to the PNGWSATGA Plane configuration as a result of severe weather event observations. They are planes that are orthogonal to the PNGWSATGA plane and intersect the PNGWSATGA plane at the centroids of the PNG and WSA polygons.
Finally, in some maps you will also see lines of yellow dots which represent the boundaries of Earth’s tectonic plates.
At this stage there is no rationale for the distortion of the solar and galactic gravitational fields focused at the barycenter and anti barycenter of the Earth Moon system and mass center of the Earth. However, if the above fields are distorted, as hypothesized , that is one way field theory can accommodate non homogeneous gravitational vectors on the Earth’s surface that emanate from the above points within the Earth. iasoberg.com have a series of algorithms (programs) developed by my brother and myself, which can generate the locations for these ‘hypothesized’ distortions very accurately for any instant of time between 2500BC to 2500AD.
All the features presented on maps reflecting the output of the Iasoberg Model are subject to the dynamics of gravity. The iasobergs (hypothetical distorted gravitational potentials), the subpoints and regions near them (m1 x m2/r2), the TGAs because of more mass in those regions of the Earth and the tectonic plates which indicate the boundaries of large masses near the Earth’s surface are dynamically linked. It is my contention that these elements contribute to the dynamics that influence our terrestrial environment. It is important to note that some of these elements are constantly moving relative to each other, in some instances in excess of 1600 km/hr!!!!
Explanation for the Output of the Iasoberg Model
Working in Australia – Part 3
Today we continue with our series on ‘Working in Australia’ with the personal story written by Kiran Burra. He talks about his dream to migrate to Australia and the process he went through.
Kiran Burra – My Journey and Settlement in Australia
After completing my post graduate studies in geosciences, with a Diploma in GIS & Remote Sensing, I started my career in GIS with Patni Computer Systems, a multinational company in India. I gained professional experience working on all GIS & CAD software in capturing, maintaining data and quality assurance on all outgoing data. I am currently working for SA Power Networks, a distribution network company in Adelaide, undertaking in house GIS projects.
I have extensive experience applying geographic analysis and technologies for improved information management and decision support worldwide. I am experienced in data creation and maintenance, GPS/GIS integration and GIS analysis working on industry standard GIS tools like ESRI ArcGIS (3D Analyst and Spatial Analyst extensions), GeoMedia, and CAD.
Migrating to Australia:
I grew up in India in a well educated family where my parents both served in public sector organisations. With a growing passion for technology and continuous backup from my parents, I spent my childhood discovering new things. After finishing high school, I was inspired to pursue further studies in sciences and technology. During this time, I discovered an interest in geography and then pursued a university undergraduate degree in science and followed by masters in the geosciences.
Whilst searching for an appropriate GIS role, I undertook additional training by completing certifications in GIS. Shortly after that I started my GIS journey working with a number of very good companies.
Migrating to Australia was my dream of mine since 2002 but the circumstances and financial conditions did not support my dream. Whilst I working in Libya, with a Swedish company, I my colleagues encouraged me to get the process started.
In 2008 I consulted a migration company in India and from there the process of migration started by submitting all my certificates, IELTS scores, medicals, Police clearance certificates, and showing my assets in India. I was approved for a visa in September 2011 after waiting for more than a year and receiving my sponsorship from Government of South Australia.
After coming to Australia:
I thought coming to Australia and settling down would be easy. It was difficult to find job especially in the GIS field. It took more than 3 months to get a job and enter into Australian market. I would say I am lucky to have good skills in GIS and of course God’s grace was upon me.
Living happy life with healthy work-life balance. I am primarily looking to settle into a new GIS role in Adelaide, but I am open to relocation if offered a suitable permanent role interstate in GIS.
I trust you find this information helpful
Founder and CEO Geospatial Connect
Application of Mobile LiDAR on Pothole detection
Mobile LiDAR technology is found to be the most effective solution for the maintenance of public transportation. Identifying and repairing the potholes is one of the important aspects of maintenance of highways.
The disruptions on the road surface are formed by the wheel load on the crocodile cracking which are formed due to the fatigue of the road surface. Once a pothole is formed, it expands continuously due to chunks of broken tar/cement. Once the pothole gets full of rain water, its size increases rapidly. A quick repair helps avoid further damage which, in turn, helps avoid road accidents.
(Picture shows a series of potholes formed on the road and are filled by rain water.)
Currently the interesting subject in the LiDAR industry is mobile mapping: dynamic terrestrial lidar, often combined with simultaneous oblique, stereo image capture. Collection of very high resolution, high accuracy street-level views of urban infrastructure is facilitated by GPS/IMU on a moving vehicle, capturing vast quantities of GIS-compatible lidar point cloud data in a relatively short amount of time. A mobile lidar system is able to see between buildings and under tree canopy in ways that airborne lidar, regardless of point density, will never be able to. Mobile mapping systems generally collect a full 360-degree field of view at a speed of 15-20 miles per hour. This highly precise data can be used to create realistic streetscapes and highly accurate road maps for vehicle navigation.
(The picture shows terrestrial LiDAR equipment mounted on a vehicle which is scanning along the road corridor)
GIS Compatible LiDAR Point Cloud Data:
The popular LiDAR point cloud data file is .las (LASer) file format. Other than .las, .bin, .ascii, .pt,s etc are commonly known file format. The above mentioned files can be converted to a specific file (say .las) using different licensed and free software. Some of the open source modules of “Lastools” are the most impressive to play with the LiDAR files.
Automatic Classification of Ground:
The different LiDAR software have the capability to classify the bare earth automatically. Depending on the parameters such as; Grid Size, Terrain Shape\angle, Terrain height (Max\Min), Object height (Min\Max) and Building height (Max\Min), the software filters the terrain points and classifies them to a separate class.
The bare earth which is automatically classified is not perfect and still needs manual classification. In the process of manual classification, high and low points are removed. The patches of unclassified ground are classified. The miscellaneous objects on road are checked.
Detection of Potholes and Crocodile Cracks:
- A crocodile crack leads to a pothole and it differs from a pothole in shape. They are usually elongated in shape as compared to the potholes. As compared to the cracks, the potholes are deeper and circular in shape and often contain water.
(The upper image shows crocodile cracks and this leads to pothole which can be seen in the lower image)
- A surface model generated on the road pavement that clearly shows an anomaly. An anomaly containing water has lesser point density generate longer TINs.
- Traditional process of manual inspection of potholes and cracks is to take a cross section and view it as a side view where the concave shape is detected. A depression containing water may reflect minimum points and a pocket can be formed. The usual process is to classify “Bellow Line”.
(Upper image shows the aerial 2D view of the point cloud where the depression is not easy to identify. In the lower image, the cross section in the side view can be well realized)
- Shape of Contours:
For the rain water to be drained to the gutter, the central portion of every paved road is slightly raised. This way the contours acquire a specific shape. The contours are usually crowned at the road center line. With the availability of the potholes and crocodile cracks, the crowning shape is distorted. These deformations alert the user to a possibility of anomalies.
(Left image shows how perfectly the shape of the contours are generated on an aerial photo. The right photo shows the distortion of the contours generated on the model-keypoints. The possible anomalies are marked which need manual inspection.)
Advanced classification in 3D:
- The recent invention of LiDAgrammetry aids the facility of stereo vision where a user can see the data in 3D. The identification of the actual anomaly is possible with NO guess work. With the additional CAD tools available, the anomalies are not just classified but their outer edges can also be compiled. The process is not just accurate but also faster and easier. The deliverable is not just the classified anomalies but also the polygons that express the area of damage.
(A LiDAR\Photogrammetry technician classifying the anomalies on highway pavement)
- The aid of 360° rotation and roaming in stereo environment provides a wonderful facility to the user where the data can be viewed from all angles including from the bottom.
(The 3D viewing facility does not require any cross section. The tile can be rotated in 360 degree)
- Any high or low point that is classified into ground class is to be removed. The advanced 3D facility provides a unique way of cutting the road in to a slice with the facility of roam forward; the high and low points can be well identified. Using either a cube or a customized structure these points are removed without disturbing the actual ground points.
(In the above picture it shows a terrestrial slice(Front view slice). It is just a specified distance which is displayed as a slice around the location of the floating mark. The remaining near and far view remains invisible. With this facility, it is easy to identify the high\low points and classify them.)
- Temporary miscellaneous features on road such as vehicles, pet animals, human etc. are carefully inspected if any of the points are wrong and in ground class. The facility of 360° rotation helps the user confirm the accurate classification or correction.
(A close inspection of the vehicles and other temporary miscellaneous objects)
Any pothole with a concave shape is immediately realized in stereo vision. Upon seeing the pothole from the bottom by rotating view, the basin shape is further confirmed. The edge of the depression is carefully digitized and that is customized to a 3D structure to clip the data inside to an assigned class.
(It is very easy to detect the eroded pavement in stereo vision. Using the 3D cad tools, the edge can be plotted)
(Once the data is clipped, it is automatically classified to an assigned class. The anomaly can finally be confirmed by viewing the basin shape by rotating the aerial view 180 degree.)
(Above picture shows a classified anomaly)
As compared to the traditional deliverable, the advanced procedure helps in delivering 3 products and they are:
1) Classified Anomalies
These are just the points in a separate class from the default and ground points.
2) Line Work
The edges of the pothole or crack are drafted using the CAD line tool. In the form of polygons, they can provide information about the area of the anomaly.
(Polygons that define the edge of the anomalies)
3) Depth Information
With the help of a specific tool, the lowest point inside the polygon is detected there by calculating the maximum depth of the pothole.
(The area and depth of a pothole is calculated)
For more information or suggestions, please contact,
Manager(Photogrammetry & LiDAR)
Geo Resource Mapping
Flat # 2, ShreeShailya Apartments,
Prabhat Road, Lane 14 (Income tax Lane)
Cell: +91 9370740737
Just to add another feather in the cap, Connovate completed design and produced samples of connected and synchronised GPS Analog Wall Clock. This Wall Clock receives accurate time from a central master GPS receiver device which broad casts the Satellite time with split second accuracy. Most important is this analog clock is built with sensors to automatically set itself without any manual intervention.
Few important features of our Analog Clock are:
1. Auto-time-setting: All you need to do is to put in the battery and the time is set automatically in the clock.
2. Battery operated: Most GPS based sync clocks are AC powered which means you need to run your AC power to the wall clock. Our clock runs on battery and does not need AC line. It is power efficient and gives you one year battery life.
3. Sync multiple clocks with one master: You can sync multiple…
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