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Understanding Lidar for Resource Management
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.  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. ”
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