Tag Archive: LiDAR mapping services

Disaster management through spatial modeling

The geographic information system (GIS) has a great role to play in disaster management activities at all stages of its operations. Disasters are emergency situations which cannot be managed locally. Disasters can be manmade or natural or combination of both. Geographic information system is used in all disaster management activities irrespective of its source as manmade or natural. GIS is stool which can be effectively used in disaster management activities in its all phases. It has a pre event phase, during phase and post disaster phase. Disaster preparedness required. Disaster management is altogether a cyclic operation composed of mitigation, preparedness, response and recovery. GIS can be effectively used in all these phases of operations and in most of the cases no other techniques can provide such solutions.

Mitigation is the advance prevention and identification of vulnerable zones so that emergencies cannot be turn into a disaster all together. Role of GIS in this phase is the map all vulnerable areas and safe areas in terms of all types of disasters. For this we need to identify all possible disasters in the area, classify them into zones of high risk, medium risk and low rick zones. Here lies the role of GIS. Through GIS technique available spatial domain can be classified. For example, in case of a floods from the major rivers, mapping and modeling using various themes and elevation data in the forms of digital terrain models will ease out in classification of high to low risk areas and provide in the form of map so that planners and decision makers can take better information based decision. SBL multidisciplinary geo spatial team can cater all such mapping and modeling services.

Preparedness phase of the disaster management also require geo spatial services. GIS will help in site selection of shelter areas, location for emergency resource storing facilities. Selection and modeling of evacuation routes is also can be done using GIS techniques. This include road capacity versus population size, direction of travel, where to place relief camps, identification of key tactical and strategic facilities, marking of nearest safe hospitals and public safely facilities. Identifying supply chain of relief materials and its pre routing, mass awareness and training to concerned officers and aiding agencies. The far most important part of GIS at this phase is that to identify the locations of impact, area it will influence, model to how it is spread etc. To achieve comprehensive preparedness, a great deal of information must be gathered and managed. When disasters strike, the right information must be available at the right place to support emergency decision requirements.

When an emergency strike an area, the already amazed spatial data can be effectively used to combat the disaster. Unfolding impact influence area, marking of areas in harm’s way and mass notification can be possible through GIS. Optimizing shelters, routings, estimating effected population and property, assessing quantity of relief materials, advance warnings to nearby possibly affected areas etc will be ease out with the help of GIS

GIS will act as a central data base repository during the recovery phase of a disaster. GIS couples with remote sensing act as an apt tool in assessment of damage and losses incurred. These kinds of spatial data assessment give information on degree of damage to individual properties and aerial extent of the damage. These will enable the planners and decision makers to estimate the reconstructions cost, prioritizing the areas for development.

Modelling of Road Assets using mobile point cloud data

Another feather in SBL’s cap. SBL was recently awarded a road asset mapping project from mobile point cloud data by a reputed firm of chartered land surveyors in the UK. The project area was mapping a stretch of the A937 highway passing through the town of Laurencekirk, Scotland, UK (see image below).

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Figure 1 – Project extents shown by highlighted blue and green lines

The length of road that was mapped was 2.3 kms and all road furniture (top and bottom of curbs, road edges, hedges and gates and walls etc.) markings (parking marks, bus stop marks etc) was captured to a high degree of accuracy. A major challenge in the project was that the input point cloud data was provided without RGB values since the mobile LiDAR survey was carried out at night.
SBL carried out the detailed mapping from the mobile point cloud data using “as is”, rule without generalizing or offsetting any feature. Cross section views at distances of less than 7m were used to capture the data to the highest possible accuracy. Check out the images below which depict graphically the level of expertise and care that was taken by the team at SBL to execute the project.

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Figure 2- Input point cloud data (Isometric View)

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Figure 3 – Profile view of the curb drawn with vertexes

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Figure 4 – Digitized top and bottom of curbs

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Figure 5 – Modelling of street markings

A significant achievement on this project was that SBL provided a “first time right” work with high levels of accuracy in a very short turnaround time of 4 working days. This was possible only because of the dedication and expertise of the LiDAR modelling team of SBL. We hope to come up with more such success stories in the coming days, so stay tuned.

Role of GIS in disaster management

Natural disasters and catastrophes bring to light major dares for federal controls and local authorities. Earthquakes, floods, cyclones, epidemics, tsunamis, and landslides have become of regular occurrence many parts of the world, continually taking a heavy toll of life and property. Under serious disaster conditions, the major task for establishments is the protection of life (both human and animal), property, and the dynamic life-supporting infrastructure necessary for disaster alleviation. To give an edge in preparing and management of disasters, GIS technology could provide a crucial inputs for preparing a decision support and management system for authorities at times of disaster-related crises.
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Over the past few eons, Space expertise and Geographic Information Systems (GIS) Applications have become obligatory part of the modern information civilization. As the frequency of disasters become more and more regular and penetrating, the demand for these technologies is swelling in order to save lives, to minimize economic losses and to build resilience of the disaster affected region. It is imperious that the policymakers and decision makers make determined efforts to widen and expand the use of space technology and GIS applications in catastrophe prone areas to diminish the effect of disasters.

ROLE OF GIS TECHNOLOGY
GIS technology is a crucial component of information, communication, and space technologies (ICST), enabled disaster controlling systems because it remains predominantly untouched during disasters unlike in the instance of both information and communication technologies which are based on ground arrangement are wide-open to natural disasters.

The scope of GIS in disaster administration is as follows:

  • A large volume of data can be collected.
  • Data collection can be focused across a widespread area.
  • Data accuracy can fit in to the purpose of application.
  • Transfer of data is more consistent and safe even during disasters.
  • Communication is faster in various locations.
  • Communication is reliable across a wide area and remote distances.

TECHNOLOGY OPTIONS
The wide continuum of ICSTs used in disaster alertness, alleviation, and supervision include:

  • Airborne Remote sensing;
  • Geographical Information System (GIS);
  • Global Positioning System (GPS);
  • Satellite navigation system;
  • Internet, e-mail; and
  • Special software packages, on-line management databases, disaster information networks.

Range of Applications
The following phases of Disaster management areas are the point of interest for professionals who hinge on ICSTs for critical solutions.

  • Database generation
  • Information assimilation and analysis
  • Disaster charting and consequence simulation
  • Hazard valuation and observing
  • Disaster tendency forecasting
  • Susceptibility assessment
  • Emergency response decision support
  • Logistics preparation for disaster relief
  • Needs calculation for disaster reclamation and reconstruction
  • Risk analysis and assessment

Data integration is one of the strongest points of GIS. In general the following types of data are required:

  • Data on the disastrous phenomena (e.g. landslides, floods, earthquakes), their location, frequency, magnitude etc.
  • Data on the environment in which the disastrous events might take place: topography, geology, geo-morphology, soils, hydrology, land use, vegetation etc.
  • Data on the elements that might be destroyed if the event takes place: infrastructure, settlements, population, socio-economic data etc.
  • Data on the emergency relief resources, such as hospitals, fire brigades, police stations, warehouses etc.

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When an emergency strike an area, the already amassed spatial data can be effectively used to combat the disaster. Unfolding impact influence area, marking of areas in harm’s way and mass notification can be possible through GIS. Optimizing shelters, routings, estimating effected population and property, assessing quantity of relief materials, advance warnings to nearby possibly affected areas etc will be ease out with the help of GIS
GIS will act as a central database repository during the recovery phase of a disaster. GIS coupled with remote sensing will act as an apt tool in assessment of damage and losses incurred. These kind of spatial data assessment give information on the extent of damage to individual properties and aerial coverage of the damage. This will enable the planners and decision makers to estimate the reconstructions cost, prioritizing the areas for development.

TREE COUNTING USING REMOTE SENSING TECHNIQUES

Operational administration of green assets such as forests and urban green cover ordinarily necessitates reliable, timely and well-run information about its developments and current status. Tree count management is important for sustaining conservational stability and ecological biodiversity. A systematic tree inventory of the forested areas and in the urban areas can help us involvedly view the causes of decline of forests in the area, decline in green cover in urban areas etc. and assist in decision making. Customary methods for counting trees are labor-intensive catalogue in the field or on an elucidation of large scale aerial photographs. Nevertheless these methods are pricey, time consuming and not pertinent to large, sequestered areas. Remote sensing technology know-how is the operational method for management and monitoring of green resources.
Polygon with tree point

There are different methods of getting the remotely sensed data, like the ones listed below.
1.LiDAR
2.Satellite Images
3.UAV/Drone Images
4.Terrestrial Photogrammetry

LiDAR
LiDAR methods of data collection is progressively used in forestry applications but also employed in urban environments for green cover calculations, tree canopy mapping and tree counting. Vast point clouds are usually converted software specific readable formats and are used to do the mapping for the tree counting and urban forestry mapping.
Tree Location and count

Satellite Images
One of the most important resources in the earth that needs constant monitoring and needs to be accurately measured for effective management is forest resources. Remotely sensed high-resolution or very high resolution satellite image data are crucial in this management, since it provides detailed information to administrators and planners for better decision making

UAV/Drone Images
Hyperspectral remote sensing, which uses the modern satellite sensors ability to capture the data in multiple-bands, in amalgamation with a properly updated land information system is understood to be a worthy technique to assist in making fast decisions. The practice of using Unmanned Aerial Vehicle (UAV) platform for many remote sensing applications is done to combine the advantages of traditional remote sensing techniques and the inexpensiveness of operating such techniques. UAV drones can fly at varying altitudes subject to the objective of the mission and end-result type. This tractability allows for optimization of the procedures according the meteorological conditions over a given area and the user requirements.

Terrestrial Photogrammetry
Tree counting is crucial for cultivated area and environmental management, biodiversity monitoring and many other applications. Regardless of the factor that satellite and aerial images have been widely used to distinguish, demarcate and count individual tree in urban areas and forested lands, till such techniques becomes widely accessible and knowledge of processing such data is increased, the traditional methods still hold the sway and might be detrimental for the green cover we all wish to have.

Use of Airborne LIDAR in Transmission Line Projects

The growing energy demand is an issue that power utility authorities incessantly face. The creation of new transmission lines is not always probable due to complications in acquiring rights-of-way and obtaining environmental approvals. Airborne LIDAR uses a precise laser scanning technology that offers decidedly accurate terrain and tower elevation data for the transmission line corridor. The advanced software tools allow the analysis of critical distances, obstacles identification, slackness calculation, catenary shape calculation, and location of structures besides allowing data to be exported to specialized engineering softwares.
GIS plays an important role regarding operation planning, data maintenance and design of transmission lines. A great amount of data is required for the operation and maintenance of data related to transmission lines, which includes property ownership data, corridor land use/land cover (LULC), transmission line situation and characteristics. The physical features of the lines and corridor LULC are determined during construction but has to be updated due to the constant change in surroundings during the lifetime. Automation of technological procedures involved in data collection, integration and processing will ensure increased efficiency in the management of the utilities. Dispensation of the data discusses to the production of complete topographic GIS products including their custom-made presentation and analysis.
LIDAR (Light Detection and Ranging) is a contemporary remote sensing technique for the collection of high density and accurate topographic data, which allows high-speed and economical data acquisition of power utility networks. LIDAR together with GIS technology offers efficient tools for database management and analysis.

Fig 1. LIDAR components

Fig 1. LIDAR components

Further to range measurements, some LiDAR systems are also adept in registering the intensity of the backscattered laser pulse. Intensity is defined as the ratio of strength of reflected laser to that of emitted laser, and is influenced mainly by the reflectance of the reflecting object (Song, 2002). Reflectance deviates with material characteristics so that different materials have different reflectance. Therefore intensity images may be supplementary information for a LULC classification. The merging of intensity images with Elevation information produces an image where features can be easily identified. Intrinsic to the collection process the above mentioned images are ortho-rectified images facilitating in the collection of required data for a GIS System. These ortho-images can be used as location image references to maintain or to update an existing GIS database.

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Figure 2 – (a) Intensity Image (b) Image obtained by fusing intensity information with elevation information.

Results of the managed LIDAR data consists of 3D information about cables, structures as well as all hindrances along the corridor in a form of a point cloud with X, Y, Z coordinates and intensity value. Post-processing actions are needed in order to classify features and to develop additional information. Ground and cable points are categorized using algorithms available in TerraScan software.

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Among the non-ground points power lines strings can be captured using top views and need to ensure that it connects all the towers. This classification is the result of analysis by an automated filter developed which detects all LIDAR hits returns from the power lines and can be categorized as wires. Towers were also can be detected in a similar way. Critical points can be detected along the transmission lines and exact height needs to be assigned to each object. 50m either side of the transmission lines can be considered for object search and exact height of the objects can be derived. The objects encountered will be houses and vegetation in general. A vegetation clearance report will help to details location of the critical points and its complete information.
LIDAR technology provides a well-organized collection of high density and accurate topographic data, being one of the most recognized cost-effective and high-speed method to such projects. Above and beyond the obstacles and vegetation along the corridor, the location and height of the prevailing towers can be derived precisely. The high density of the laser points enables accurate delineation of the cables as well as the derivation of the connection points. LIDAR in concurrence with GIS methodologies provides efficient database updating and analysis.

LiDAR DATA PROCESSING AND ASSET MANAGEMENT

LiDAR(Light Detection And Ranging):A form of representation of 3D surfaces, Point cloud data, are usually produced by aerial or terrestrial laser scanning, also known as Light Detection and Ranging (LiDAR). The data is produced as sets of very dense (x, y, z) points or in a more common, binary format called LAS that may include values of multiple returns and point intensities. Many leading GIS processing software’s now accommodate and supports basic and advanced LiDAR data processing and analysis. LiDAR is emerging as one of the cost-effective and accurate data capture system to manage large assets such as Railway stations and other public/private infrastructures.
SBL GIS Services division has been in the forefront of processing LiDAR services for some time now. Our LiDAR data processing services has been entrusted with prestigious and complex Infrastructure modelling projects across many geographies. One such example is demonstrated in the picture given below.

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Fig-1: All visible data captured as vector data with the help of Terrestrial LiDAR scanner point cloud data related to this project and attributed to their respective code. The above view is illustration of the output.

The Science behind LiDAR Working
LiDAR working is quite simple and it works on the principle of Light – speed and time taken to reflect the same from a surface. The distance is calculated from the difference between the time when a beam of light hits a surface and measure the time it takes to return to its source. Light travels very fast – about 300,000 kilometers per second, or 0.3 meters per nanosecond so we feel the instantaneous result when a light is turned on. The paraphernalia required to measure this needs to function extremely fast. Only with the advancements in modern computing technology has this has become possible.
Distance = (Speed of Light x Time of Flight) / 2

USES OF LiDAR MAPPING.
One of the main focus of LiDAR services in the Urban Infrastructure Mapping.

Urban Infrastructure Planning  
Urban Planning or City development is the science of land use planning which considers several aspects of the as-built data and social environments of the area of interest. LiDAR Mapping is a moderately new technology for obtaining Digital Surface Models (DSMs) and Digital Building Models. This data, when combined with orthorectified images, can create highly detailed Surface Models and eventually 3D City Models.
Wayside assets include tarmacs, streetlights, signs, advertisement boards, traffic signals and street furniture. A thorough understanding of all the assets, what they are and where each asset is located, is crucial to the development of an asset portfolio.
An accurate record of all assets along the transportation network is vital to asset management, to plan a maintenance schedule and budget costs. A bigger challenge than developing the asset database is keeping it up to date and this is where the cost-effective, accurate LiDAR Mapping will come into play.