Simulating an Airborne Lidar Bathymetry (ALB) System

This study’s focus is on the horizontal and vertical uncertainties associated with ALB measurements due to scattering through the water column. A lidar simulator was constructed and we present its design and preliminary results

Lake Tahoe bottom characteristics extracted from SHOALS lidar waveform data and compared to backscatter data from a Multibeam echo sounder

The waveforms recorded by airborne lidar bathymetry (ALB) systems are currently processed only for depth information. In addition to bathymetry, multibeam echo sounder (MBES) systems provide backscatter data in which regions of different acoustic properties are distinguishable. These regions can often be correlated to different bottom types. Initial attempts to extract equivalent data from the ALB waveforms have confirmed the expectation that such information is encoded in those waveforms. Water clarity, bathymetry, and bottom type control the detailed shapes of ALB waveforms in different ways. Specific features of a bottom-reflected signal can be identified, for example its rise-time and amplitude, and used for clustering and classifying the individual data points. Two data sets from Lake Tahoe are available for comparison: ALB data from the SHOALS (scanning hydrographic operational airborne lidar survey) system of the US Army Corps of Engineers, and Simrad EM1000 MBES data from the USGS. Feature extraction, clustering, and classification of the SHOALS data reveals changes in the optical bottom reflectance characteristics that are echoed in the acoustic bottom backscatter properties

Airborne lidar observations of Arctic polar stratospheric clouds

Polar stratospheric clouds (PSC's) have been detected repeatedly during Arctic and Antarctic winters since 1978/1979 by the SAM II (Stratospheric Aerosol Measurement II) instrument aboard the NIMBUS-7 satellite. PSC's are believed to form when supercooled sulfuric acid droplets freeze, and subsequently grow by deposition of ambient water vapor as the local stratospheric temperature falls below the frost point. In order to study the characteristics of PSC's at higher spatial and temporal resolution than that possible from the satellite observations, aircraft missions were conducted within the Arctic polar night vortex in Jan. 1984 and Jan. 1986 using the NASA Langley Research Center airborne dual polarization ruby lidar system. A synopsis of the 1984 and 1986 PSC observations is presented illustrating short range spatial changes in cloud structure, the variation of backscatter ratio with temperature, and the depolarization characterics of cloud layers. Implications are noted with regard to PSC particle characteristics and the physical process by which the clouds are thougth to form

Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented

ICESat/GLAS Data as a Measurement Tool for Peatland Topography and Peat Swamp Forest Biomass in Kalimantan, Indonesia

Indonesian peatlands are one of the largest near-surface pools of terrestrial organic carbon. Persistent logging, drainage and recurrent fires lead to huge emission of carbon each year. Since tropical peatlands are highly inaccessible, few measurements on peat depth and forest biomass are available. We assessed the applicability of quality filtered ICESat/GLAS (a spaceborne LiDAR system) data to measure peatland topography as a proxy for peat volume and to estimate peat swamp forest Above Ground Biomass (AGB) in a thoroughly investigated study site in Central Kalimantan, Indonesia. Mean Shuttle Radar Topography Mission (SRTM) elevation was correlated to the corresponding ICESat/GLAS elevation. The best results were obtained from the waveform centroid (R2 = 0.92; n = 4,186). ICESat/GLAS terrain elevation was correlated to three 3D peatland elevation models derived from SRTM data (R2 = 0.90; overall difference = −1.0 m, ±3.2 m; n = 4,045). Based on the correlation of in situ peat swamp forest AGB and airborne LiDAR data (R2 = 0.75, n = 36) an ICESat/GLAS AGB prediction model was developed (R2 = 0.61, n = 35). These results demonstrate that ICESat/GLAS data can be used to measure peat topography and to collect large numbers of forest biomass samples in remote and highly inaccessible peatland forests

Airborne lidar stratospheric ozone and aerosol investigations

The objectives are to study the distribution of ozone (O3) and aerosols across the polar regions during the winter and spring periods and to relate these observations to chemical and dynamical processes that can contribute to the chemical perturbation of the polar stratosphere and the possible destruction of O3. The distribution and characteristics of stratospheric aerosols and polar stratospheric clouds (PSCs) are required to understand heterogeneous chemical processes that can lead to O3 depletion, and observation of O3 variations are important in the direct detection of O3 depletion and in tracing atmospheric dynamics. An airborne Differential Absorption Lidar (DIAL) system is operated in a zenith mode from the NASA DC-8 aircraft to obtain data on the large scale spatial variability of O3, and aerosol/PSC's in the lower stratosphere from about 11 to 23 km for O3, and 11 to 28 km for aerosols. The variability of O3 and aerosols/PSCs is studied in relation to chemical processes that can produce O3 depletion and to dynamics in the lower stratosphere that transport gases and aerosols inside the vortex and in some cases, across the edge of the vortex

Airborne LiDAR For Urban Planning

The United Nations press release (2019) states that 68% of the future world population will live in urban areas by 2050. Consequently, the cities will need more advanced technology to help them plan and manage the city. Airborne LiDAR is a cutting-edge technology for mapping objects on the Earth’s surface which is very beneficial for urban mapping. Airborne LiDAR can produce a 3D City Model which produces useful data for several applications in urban planning

GNSS Accuracy Analysis for Efficiency of Ground Control Point (GCP) Measurement

Nowadays, the Global Navigation Satellite System (GNSS) has a significant role in the field of surveying and mapping, especially in determining the coordinates of ground control points for rectifying aerial photography, satellite imagery and airborne lidar. Each of these rectification processes requires a different coordinate accuracy from 5 to 20 cm. This research will conduct GNSS measurement with radial method and observation length to see how far the required accuracy will be fulfilled. This research examined ten Ground Control Points (GCPs) using the GNSS receiver in Surabaya. Each GCP was observed for 2 hours with 15” epoch and then they were processed with an interval of 15 minutes such as 15’, 30’, 45’, 60’, 75’, 90’, 105’ and 120’ with the radial method. In general, the results showed that the longer the GNSS observation the more accurate coordinates from 0.923 m (15 minutes) to 0.011 m (120 minutes) will be achieved. Measurement of GCPs for aerial photogrammetry, High-Resolution Satellite Image (HRSI), and airborne LIDAR needs 15’ observation both of radial and network method for less than or equal 10 km of baseline. For 10 – 20 km, the radial method needs 90’ observation for photogrammetry, 75’ observation for HRSI, 45’ GCPs observation of airborne LIDAR, but for network methods need 45’ observation for photo and HRSI and 30’ observation for Airborne LIDAR.