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Understanding Lidar for Resource Management

Mudit Mathur


Mudit Mathur
1341 S-2 RK Purum
New Delhi-30
Email: [email protected]

Jasbir Sandhu


Jasbir Sandhu
J3/79 Malviyanagar
New Delhi-17
Email: [email protected]

1. INTRODUCTION

The biggest challenge in the modern remote sensing is to device an assured means to achieve a high degree of accuracy in ground sampling, without undertaking physical survey. This has been an enigma for the civil as well as military remote sensing scientists. LiDAR(Light Detection and Ranging; or Laser Imaging Detection and Ranging), is a technology that determines distance to an object or surface using laser pulses, the range to an object is determined by measuring the time delay between transmission of a pulse and detection of the reflected signals. The acronym LADAR (Laser Detection and Ranging) for elastic backscatter is mainly used in military context. The term laser radar is also in use but somewhat misleading as laser light and not radio waves are used. LiDAR, an airborne technique is becoming more and more important in terrain applications programmes and for acquiring remotely sensed topographical data.

LiDAR term as defined in the dictionary say all about its physical property and its capability

Main Entry: li•dar
Pronunciation: ‘Li -“där
Function: noun
Etymology: light + radar

Definition-1: A device that is similar in operation to radar but emits pulsed laser light instead of microwaves

Definition-2: A method of detecting distant objects and determining their position, velocity, or other characteristics by analysis of pulsed laser light reflected from their surfaces. The equipment are used in such detection.

This article provides a window for understanding the few of many capabilities of the LiDAR that can be used in infinite application of resource management so that optimized canalization and exploitation of the resources can be attempted. In all we should not lose the sight of the fact that LiDAR is one of the sources of highly accurate data and not the solution by itself.

Technology in a glance

The LiDAR system basically consists of integration of three technologies, namely, Inertial Navigation System (INS), LASER, and GPS.

A pulsed laser ranging system is mounted in an aircraft equipped with a precise kinematic GPS receiver and an Inertial Navigation System (INS). Solid-state lasers are now available that can produce thousands of pulses per second, each pulse having a duration of a few nanoseconds (109 seconds). The laser basically consists of an emitting diode that produces a light source at a very specific frequency. The signal is sent towards the earth where it is reflected off a feature back towards the aircraft. A receiver then captures the return pulse. Using accurate timing, the distance to the feature can be measured. By knowing a speed of the light and the time the signal takes to travel from the aircraft to the object and back to the aircraft, the distances can be computed. Using a rotating mirror inside the laser transmitter, the laser pulses can be made to sweep through an angle, tracing out a line on the ground. By reversing the direction of rotation at a selected angular interval, the laser pulses can be made to scan back and forth along a line. When such a laser ranging system is mounted in an aircraft with the scan line perpendicular to the direction of flight, it produces a saw tooth pattern along the flight path.

Employment

There are multitudinous usages of LiDAR technologies. Presently worldwide network of observatories use LiDAR to measure the distance of earth-moon with millimeter precision and enabling tests of general relativity. The Mars Orbiting Laser Altimeter [MOLA], used a LiDAR instrument in a Mars-orbiting satellite to produce a stunningly accurate topographic survey of the red planet. In atmospherics, LiDAR is used as a remote detection instrument to measure densities of certain constituents of the middle and upper atmosphere, such as potassium, sodium, or molecular nitrogen and oxygen. These measurements can be used to calculate temperatures. LiDAR can also be used to measure wind speed. One situation where LiDAR has notable non-scientific application is for vehicle speed measurement. The technology for this application is small enough to be mounted in a hand held camera “gun” and permits a particular vehicle’s speed to be determined from a stream of traffic. Military applications are not yet in place, but a considerable amount of research is underway in their use for imaging. Their higher resolution makes them particularly good for collecting enough detail to identify targets, such as tanks. Here the name LADAR is more common. At the JET nuclear fusion research facility in Oxfordshire. LIDAR Thomson Scattering is used to determine Electron Density and Temperature profiles of the plasma. There are ongoing military research programmes in Sweden, Denmark, USA and UK with 3-D gated viewing imaging at several kilometers range with a range resolution and accuracy less than ten centimeters 2. RESOURCES

2.1. LIDAR IN LARGE SCALE MAPPING
LiDAR is extensively used for the large scale mapping projects, which in turn takes its employment from the national level planning maps and maps for the military applications, with the integrated use of space borne IFSAR technology, along with the cartography. With the advent of the LiDAR in the development of maps the new generation map development cycle is reduced i.e. much precise, user-friendly maps in a very short development and design periods are made available. The absolute accuracy of the elevation data achieved is 15 cm however a relative accuracy of less than 5 cm or below can be achieved which is dependent on operating parameters such as flight altitude etc.

The elevation data is generated at 1000s of points per second, which is far greater than traditional ground survey methods. With these high sampling rates, it is possible to rapidly complete a large topographic survey and generate DTMs with a grid spacing of 1 m or less.

LiDAR data using fixed-wing aircraft flying at higher altitudes which is very essential to meet accuracies required for large-scale contour mapping

LiDAR data filtered to a bare-Earth DTM can be used for aerial triangulation. The orthophoto is very useful for 3-D modeling of bridges, highway ramps, etc. Because LiDAR points are collected randomly and at an angle, points may appear atop and below bridges. This causes a feature such as a bridge to appear distorted on a digital orthophoto. With proper break-line placement, obstructions are rectified and appears geographically correct and aesthetically pleasing.

2.2. FOREST MANAGEMENT

LiDAR remote sensing is a breakthrough technology for forestry applications. New LiDAR data sets provide precise measurements of various forest parameters like canopy height, sub canopy topography, and the vertical distribution of intercepted surfaces between the canopy top and the ground. Other forest structural characteristics, such as aboveground biomass, are modeled or inferred from these direct measurements Ecologists and wildlife managers are using the data to assist in applying information to better characterize, model and manage habitats and associated natural resources.

2.3. TELECOMMUNICATIONS

Application of LiDAR in telecommunication is going to boom in the near future. Telecommunication companies rely on accurate and detailed data sets this industry needs a spatially accurate of least one meter x, y and z to ensure proper planning. Because of its flexibility, accuracy and timeliness, these industries have started acquiring LiDAR-generated building contour renderings for the accurate geo-referenced dataset. These data are being used to evaluate radio frequency, wave interference and traffic capability.

2.3. SEISMIC MANAGEMENT

A relatively new technology, airborne LiDAR, is gaining widespread use in seismic acquisition.

Applications of LiDAR products to land seismic acquisition operations include the following:

  1. Slope determination -preplanning of source locations, source type identification, locating staging areas, positioning crews to work in downhill directions and illustrating regulation compliance
  2. Survey efficiency – using LiDAR derived elevation (Z) value for seismic points, instead of acquiring Z with Global Positioning System (GPS) units, can increase the efficiency of survey crews, especially in conditions of heavy vegetative canopy
  3. Identification of operational hazards – steep terrain, thick vegetation and oilfield infrastructure such as pipelines, well pads and roads
  4. Map creation – LiDAR DEM’s serve as a backdrop and provide the capability to create various themes
  5. Radio communication -radio transmission and reception models help locate ideal signal repeater locations
  6. Logistical and safety planning – fly-through simulations on DTM’s provide a visualization of ground conditions and hazards that occur on any travel route

3.5. URBAN PLANNING

A LiDAR generated DTM associated with orthophotos is a wonderful tool for the localisation and classification of urban areas, man made infrastructure and to generate land use classes. It is possible to produce volumetric data for quarry and landfill sites, cyclic census of forested expanses, location of wildcat buildings and land use classification.

River Basins
The availability of a DTM of a floodplain and a river basin is a paramount for the control and monitoring of riverbanks and coastlines. The deployment of an airborne LiDAR enables the timely survey of large areas of the floodplain efficiently and accurately, during or immediately after a flooding event by analysis and comparison of altitude data and orthophotos It is also possible to obtain accurate and up to date estimates of sediment/erosion volumes along the river course and pinpoint potential landslide prone areas.

The use of a DTM greatly enhances the planning capability of the basin and helps in managing emergency scenarios. This also helps in studying, evaluation, modeling and analysis of the hydrological parameters within the river basin. An accurate DTM can measure the distance, steepness and river cross-sections.

3. LiDAR IN GIS

LiDAR is well suited for GIS applications due to the fact the data is processed rapidly, is geo-referenced and can be readily imported into a GIS environment. Imported data is in vector format consisting of spatially distributed points. From this topology many GIS functions may be performed including aggregation, neighborhood/proximity analysis, spatial statistics and contour modeling etc. Most LiDAR information is used for the study and building of digital elevation models. In the case of atmospheric applications, multi-spectral LiDAR allows for quick monitoring of aerosols, where varying light pulses of different wavelength result in thematic layers being created for individual type of airborne particles.

GIS image analysis software is being increasingly used to differentiate between light points of differing time returns and or differing spectral color. The data captured with LiDAR can be readily integrated with other thematic content if all information is geo-referenced. Issues related to scale and resolution require consideration, since LiDAR information tends to be quite accurate with sub-meter resolutions while other data sets may be of a coarser resolution. Future applications are likely to be coupled to artificial intelligence and real-time coupling to other instrumentation. One of the primary benefits of LiDAR is the quick construction of 3-D and 4-D models.

4. FUTURE DEVELOPMENT OF LIDAR

As the GIS community advances toward 3-D technology and virtual-reality environments for modeling and analysis, the demand for highly detailed and accurate DTMs will increase significantly. Digital ortho-photography will demand DTM models for “true orthophoto” production, which rectifies buildings and other tall structures. DTMs can be used to simulate “fly through” of areas to view tall buildings, freeway ramps and other obstructions. True 3-D ortho-photography provides engineers and planners with a powerful tool to design and visualize our cities and utility infrastructures.

Moreover, points currently filtered out of datasets to create a bare-Earth DTM will be classified through feature-recognition techniques to differentiate buildings, trees, cars, etc., alleviating the monotony of collecting the features manually. Using this methodology, a land-base project executed over a city of the size of New Delhi could automatically classify 1 million buildings. LiDAR can be used to efficiently locate areas of change, which is invaluable information for subsequent mapping update. Original LiDAR DTMs taken during the first mapping phase are compared to later datasets, and areas of change can be located by superposition.

LiDAR is an appropriate complement to existing photogrammetric technologies, and it offers substantial benefits in terms of increased data collection efficiencies and accuracy levels. As LiDAR becomes more sophisticated and refined, uses for the technology will expand.

5. CONCLUSION

The increased resolution and accuracy of elevation data from modern LiDAR systems are proving useful in a variety of earth resource applications. From a military perspective, traditional sources of elevation models such as 30 meter DEMs are often inadequate for assured mobility in tactical settings. This problem must be solved in order to meet the requirement for mobile units to defeat micro-terrain gaps by crossing or avoidance. Advance knowledge of the type, location, and characteristics of gaps available in a geographic information system can be a useful tool for cross-country planning purposes. Fine-grained terrain information will be even more critical for the smaller wheelbases of future unmanned ground vehicles.

If slope breaklines can be considered useful indicators of the spatial limits of gap features, the refinement of numerical algorithms for finding breaklines from high-resolution terrain models will increase the speed and accuracy of gap identification. Slope breakline information may then be processed and organized into individual linear gap features as geo-located objects in a GIS, whose extent would be constrained by input geometric parameters. In spite of the difficulty of discovering breaklines using a discrete sampling scheme, current and future LiDAR sensors may provide adequate resolution for characterizing micro-terrain anomalies from an elevation model.

Future work may include development and testing of effective breakline-finding algorithms, based on the algorithm development strategy described above. Such work would include the determination of algorithm constraints and thresholds under field conditions. We also intend to experiment with “bare-earth” LIDAR elevation models to reduce the capture of spurious breaklines resulting from neighboring pulse returns from tree canopies and adjacent terrain. Additional work is possible in the investigation of elevation models derived from Interferometric Synthetic Aperture Radar (IFSAR) over the same site for comparative analysis with the LIDAR data in modeling micro-terrain discontinuities. In addition to modeling mobility barriers, such efforts would complement studies of the geomorphic distribution of fault scarps. To date, the results from this preliminary study indicate that high-resolution elevation models show strong potential for the extraction of specialized slope/terrain products, with the promise of more efficient capture of these features by semi-automated and automated means. Complex solutions for the interoperable issues has been tried out along with application like artificial intelligence GIS data mining engines along with LiDAR data so that futuristic solutions can be generated at a higher degree of accuracy. Presently the system utilization is infinitesimal vis-à-vis the power enriched in the system.

“ This work is a collection of works done in the field if LiDAR by various individuals and institutes, author takes no claim in either designing the LiDAR or its methodologies, however only the integration of isolated works in the field of LiDAR has been done in this article, keeping in view Resource management for instituting awareness towards developing LiDAR concepts. Various proceedings of IEEE & ezines on Remote sensing & GIS , data from various conferences, Journals and references from open source have contributed towards the development of this article. ”