Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

Science.gov (United States)

Beyon, Jeffrey Y. (Inventor); Koch, Grady J. (Inventor); Kavaya, Michael J. (Inventor)

2015-01-01

Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

All-Fiber Airborne Coherent Doppler Lidar to Measure Wind Profiles

Directory of Open Access Journals (Sweden)

Liu Jiqiao

2016-01-01

Full Text Available An all-fiber airborne pulsed coherent Doppler lidar (CDL prototype at 1.54μm is developed to measure wind profiles in the lower troposphere layer. The all-fiber single frequency pulsed laser is operated with pulse energy of 300μJ, pulse width of 400ns and pulse repetition rate of 10kHz. To the best of our knowledge, it is the highest pulse energy of all-fiber eye-safe single frequency laser that is used in airborne coherent wind lidar. The telescope optical diameter of monostatic lidar is 100 mm. Velocity-Azimuth-Display (VAD scanning is implemented with 20 degrees elevation angle in 8 different azimuths. Real-time signal processing board is developed to acquire and process the heterodyne mixing signal with 10000 pulses spectra accumulated every second. Wind profiles are obtained every 20 seconds. Several experiments are implemented to evaluate the performance of the lidar. We have carried out airborne wind lidar experiments successfully, and the wind profiles are compared with aerological theodolite and ground based wind lidar. Wind speed standard error of less than 0.4m/s is shown between airborne wind lidar and balloon aerological theodolite.

Derivation of Strike and Dip in Sedimentary Terrain Using 3D Image Interpretation Based on Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Chih-Hsiang Yeh

2014-01-01

Full Text Available Traditional geological mapping may be hindered by rough terrain and dense vegetation resulting in obscured geological details. The advent of airborne Light Detection and Ranging (LiDAR provides a very precise three-dimensional (3D digital terrain model (DTM. However, its full potential in complementing traditional geological mapping remains to be explored using 3D rendering techniques. This study uses two types of 3D images which differ in imaging principles to further explore the finer details of sedimentary terrain. Our purposes are to demonstrate detailed geological mapping with 3D rendering techniques, to generate LiDAR-derived 3D strata boundaries that are advantageous in generating 2D geological maps and cross sections, and to develop a new practice in deriving the strike and dip of bedding with LiDAR data using an example from the north bank of the Keelung River in northern Taiwan. We propose a geological mapping practice that improves efficiency and meets a high-precision mapping standard with up to 2 m resolution using airborne LiDAR data. Through field verification and assessment, LiDAR data manipulation with relevant 3D visualization is shown to be an effective approach in improving the details of existing geological maps, specifically in sedimentary terrain.

Automatic 3d Building Model Generations with Airborne LiDAR Data

Science.gov (United States)

Yastikli, N.; Cetin, Z.

2017-11-01

LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D

AUTOMATIC 3D BUILDING MODEL GENERATIONS WITH AIRBORNE LiDAR DATA

Directory of Open Access Journals (Sweden)

N. Yastikli

2017-11-01

Full Text Available LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified

Lidar technologies for airborne and space-based applications

International Nuclear Information System (INIS)

Henson, T.D.; Schmitt, R.L.; Sobering, T.J.; Raymond, T.D.; Stephenson, D.A.

1994-10-01

This study identifies technologies required to extend the capabilities of airborne light detection and ranging (lidar) systems and establish the feasibility of autonomous space-based lidars. Work focused on technologies that enable the development of a lightweight, low power, rugged and autonomous Differential Absorption Lidar (DIAL) instruments. Applications for airborne or space-based DIAL include the measurement of water vapor profiles in support of climate research and processing-plant emissions signatures for environmental and nonproliferation monitoring. A computer-based lidar performance model was developed to allow trade studies to be performed on various technologies and system configurations. It combines input from the physics (absorption line strengths and locations) of the problem, the system requirements (weight, power, volume, accuracy), and the critical technologies available (detectors, lasers, filters) to produce the best conceptual design. Conceptual designs for an airborne and space-based water vapor DIAL, and a detailed design of a ground-based water vapor DIAL demonstration system were completed. Future work planned includes the final testing, integration, and operation of the demonstration system to prove the capability of the critical enabling technologies identified

Comparisons of Simultaneously Acquired Airborne Sfm Photogrammetry and Lidar

Science.gov (United States)

Larsen, C. F.

2014-12-01

Digital elevation models (DEMs) created using images from a consumer DSLR camera are compared against simultaneously acquired LiDAR on a number of airborne mapping projects across Alaska, California and Utah. The aircraft used is a Cessna 180, and is equipped with the University of Alaska Geophysical Institute (UAF-GI) scanning airborne LiDAR system. This LiDAR is the same as described in Johnson et al, 2013, and is the principal instrument used for NASA's Operation IceBridge flights in Alaska. The system has been in extensive use since 2009, and is particularly well characterized with dozens of calibration flights and a careful program of boresight angle determination and monitoring. The UAF-GI LiDAR has a precision of +/- 8 cm and accuracy of +/- 15 cm. The photogrammetry DEM simultaneously acquired with the LiDAR relies on precise shutter timing using an event marker input to the IMU associated with the LiDAR system. The photo positions are derived from the fully coupled GPS/IMU processing, which samples at 100 Hz and is able to directly calculate the antenna to image plane offset displacements from the full orientation data. This use of the GPS/IMU solution means that both the LiDAR and Cessna 180 photogrammetry DEM share trajectory input data, however no orientation data nor ground control is used for the photorammetry processing. The photogrammetry DEMs are overlaid on the LiDAR point cloud and analyzed for horizontal shifts or warps relative to the LiDAR. No warping or horizontal shifts have been detectable for a number of photogrammetry DEMs. Vertical offsets range from +/- 30 cm, with a typical standard deviation about that mean of 10 cm or better. LiDAR and photogrammetry function inherently differently over trees and brush, and direct comparisons between the two methods show much larger differences over vegetated areas. Finally, the differences in flight patterns associated with the two methods will be discussed, highlighting the photogrammetry

Probabilistic change mapping from airborne LiDAR for post-disaster damage assessment

Science.gov (United States)

Jalobeanu, A.; Runyon, S. C.; Kruse, F. A.

2013-12-01

When both pre- and post-event LiDAR point clouds are available, change detection can be performed to identify areas that were most affected by a disaster event, and to obtain a map of quantitative changes in terms of height differences. In the case of earthquakes in built-up areas for instance, first responders can use a LiDAR change map to help prioritize search and recovery efforts. The main challenge consists of producing reliable change maps, robust to collection conditions, free of processing artifacts (due for instance to triangulation or gridding), and taking into account the various sources of uncertainty. Indeed, datasets acquired within a few years interval are often of different point density (sometimes an order of magnitude higher for recent data), different acquisition geometries, and very likely suffer from georeferencing errors and geometric discrepancies. All these differences might not be important for producing maps from each dataset separately, but they are crucial when performing change detection. We have developed a novel technique for the estimation of uncertainty maps from the LiDAR point clouds, using Bayesian inference, treating all variables as random. The main principle is to grid all points on a common grid before attempting any comparison, as working directly with point clouds is cumbersome and time consuming. A non-parametric approach based on local linear regression was implemented, assuming a locally linear model for the surface. This enabled us to derive error bars on gridded elevations, and then elevation differences. In this way, a map of statistically significant changes could be computed - whereas a deterministic approach would not allow testing of the significance of differences between the two datasets. This approach allowed us to take into account not only the observation noise (due to ranging, position and attitude errors) but also the intrinsic roughness of the observed surfaces occurring when scanning vegetation. As only

Typical Applications of Airborne LIDAR Technolagy in Geological Investigation

Science.gov (United States)

Zheng, X.; Xiao, C.

2018-05-01

The technology of airborne light detection and ranging (LiDAR), also referred to as Airborne Laser Scanning, is widely used for high-resolution topographic data acquisition (even under forest cover) with sub-meter planimetric and vertical accuracy. This contribution constructs the real digital terrain model to provide the direct observation data for the landscape analysis in geological domains. Based on the advantage of LiDAR, the authors mainly deal with the applications of LiDAR data to such fields as surface land collapse, landslide and fault structure extraction. The review conclusion shows that airborne LiDAR technology is becoming an indispensable tool for above mentioned issues, especially in the local and large scale investigations of micro-topography. The technology not only can identify the surface collapse, landslide boundary and subtle faulted landform, but also be able to extract the filling parameters of collapsed surface, the geomorphic parameters of landslide stability evaluation and cracks. This technology has extensive prospect of applications in geological investigation.

TYPICAL APPLICATIONS OF AIRBORNE LIDAR TECHNOLAGY IN GEOLOGICAL INVESTIGATION

Directory of Open Access Journals (Sweden)

X. Zheng

2018-05-01

Full Text Available The technology of airborne light detection and ranging (LiDAR, also referred to as Airborne Laser Scanning, is widely used for high-resolution topographic data acquisition (even under forest cover with sub-meter planimetric and vertical accuracy. This contribution constructs the real digital terrain model to provide the direct observation data for the landscape analysis in geological domains. Based on the advantage of LiDAR, the authors mainly deal with the applications of LiDAR data to such fields as surface land collapse, landslide and fault structure extraction. The review conclusion shows that airborne LiDAR technology is becoming an indispensable tool for above mentioned issues, especially in the local and large scale investigations of micro-topography. The technology not only can identify the surface collapse, landslide boundary and subtle faulted landform, but also be able to extract the filling parameters of collapsed surface, the geomorphic parameters of landslide stability evaluation and cracks. This technology has extensive prospect of applications in geological investigation.

Contribution to understanding the post-mining landscape - Application of airborn LiDAR and historical maps at the example from Silesian Upland (Poland)

Science.gov (United States)

Gawior, D.; Rutkiewicz, P.; Malik, I.; Wistuba, M.

2017-11-01

LiDAR data provide new insights into the historical development of mining industry recorded in the topography and landscape. In the study on the lead ore mining in the 13th-17th century we identified remnants of mining activity in relief that are normally obscured by dense vegetation. The industry in Tarnowice Plateau was based on exploitation of galena from the bedrock. New technologies, including DEM from airborne LiDAR provide show that present landscape and relief of post-mining area under study developed during several, subsequent phases of exploitation when different techniques of exploitation were used and probably different types of ores were exploited. Study conducted on the Tarnowice Plateau proved that combining GIS visualization techniques with historical maps, among all geological maps, is a promising approach in reconstructing development of anthropogenic relief and landscape..

Airborne Lidar Measurements of Aerosol Optical Properties During SAFARI-2000

Science.gov (United States)

McGill, M. J.; Hlavka, D. L.; Hart, W. D.; Welton, E. J.; Campbell, J. R.; Starr, David OC. (Technical Monitor)

2002-01-01

The Cloud Physics Lidar (CPL) operated onboard the NASA ER-2 high altitude aircraft during the SAFARI-2000 field campaign. The CPL provided high spatial resolution measurements of aerosol optical properties at both 1064 nm and 532 nm. We present here results of planetary boundary layer (PBL) aerosol optical depth analysis and profiles of aerosol extinction. Variation of optical depth and extinction are examined as a function of regional location. The wide-scale aerosol mapping obtained by the CPL is a unique data set that will aid in future studies of aerosol transport. Comparisons between the airborne CPL and ground-based MicroPulse Lidar Network (MPL-Net) sites are shown to have good agreement.

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

Science.gov (United States)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

Advances and perspectives in bathymetry by airborne lidar

Science.gov (United States)

Zhou, Guoqing; Wang, Chenxi; Li, Mingyan; Wang, Yuefeng; Ye, Siqi; Han, Caiyun

2015-12-01

In this paper, the history of the airborne lidar and the development stages of the technology are reviewed. The basic principle of airborne lidar and the method of processing point-cloud data were discussed. At present, single point laser scanning method is widely used in bathymetric survey. Although the method has high ranging accuracy, the data processing and hardware system is too much complicated and expensive. For this reason, this paper present a kind of improved dual-frequency method for bathymetric and sea surface survey, in this method 176 units of 1064nm wavelength laser has been used by push-broom scanning and due to the airborne power limits still use 532nm wavelength single point for bathymetric survey by zigzag scanning. We establish a spatial coordinates for obtaining the WGS-84 of point cloud by using airborne POS system.

NASA Goddards LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager

Science.gov (United States)

Cook, Bruce D.; Corp, Lawrence A.; Nelson, Ross F.; Middleton, Elizabeth M.; Morton, Douglas C.; McCorkel, Joel T.; Masek, Jeffrey G.; Ranson, Kenneth J.; Ly, Vuong; Montesano, Paul M.

2013-01-01

The combination of LiDAR and optical remotely sensed data provides unique information about ecosystem structure and function. Here, we describe the development, validation and application of a new airborne system that integrates commercial off the shelf LiDAR hyperspectral and thermal components in a compact, lightweight and portable system. Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) airborne imager is a unique system that permits simultaneous measurements of vegetation structure, foliar spectra and surface temperatures at very high spatial resolution (approximately 1 m) on a wide range of airborne platforms. The complementary nature of LiDAR, optical and thermal data provide an analytical framework for the development of new algorithms to map plant species composition, plant functional types, biodiversity, biomass and carbon stocks, and plant growth. In addition, G-LiHT data enhance our ability to validate data from existing satellite missions and support NASA Earth Science research. G-LiHT's data processing and distribution system is designed to give scientists open access to both low- and high-level data products (http://gliht.gsfc.nasa.gov), which will stimulate the community development of synergistic data fusion algorithms. G-LiHT has been used to collect more than 6,500 km2 of data for NASA-sponsored studies across a broad range of ecoregions in the USA and Mexico. In this paper, we document G-LiHT design considerations, physical specifications, instrument performance and calibration and acquisition parameters. In addition, we describe the data processing system and higher-level data products that are freely distributed under NASA's Data and Information policy.

Optical Backscattering Measured by Airborne Lidar and Underwater Glider

Directory of Open Access Journals (Sweden)

James H. Churnside

2017-04-01

Full Text Available The optical backscattering from particles in the ocean is an important quantity that has been measured by remote sensing techniques and in situ instruments. In this paper, we compare estimates of this quantity from airborne lidar with those from an in situ instrument on an underwater glider. Both of these technologies allow much denser sampling of backscatter profiles than traditional ship surveys. We found a moderate correlation (R = 0.28, p < 10−5, with differences that are partially explained by spatial and temporal sampling mismatches, variability in particle composition, and lidar retrieval errors. The data suggest that there are two different regimes with different scattering properties. For backscattering coefficients below about 0.001 m−1, the lidar values were generally greater than the glider values. For larger values, the lidar was generally lower than the glider. Overall, the results are promising and suggest that airborne lidar and gliders provide comparable and complementary information on optical particulate backscattering.

Airborne and Ground-Based Measurements Using a High-Performance Raman Lidar

Science.gov (United States)

Whiteman, David N.; Rush, Kurt; Rabenhorst, Scott; Welch, Wayne; Cadirola, Martin; McIntire, Gerry; Russo, Felicita; Adam, Mariana; Venable, Demetrius; Connell, Rasheen;

Estimating forest structural characteristics using the airborne LiDAR scanning system and a near-real time profiling laser system

Science.gov (United States)

Zhao, Kaiguang

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of

CLASSIFICATION OF WATER SURFACES USING AIRBORNE TOPOGRAPHIC LIDAR DATA

Directory of Open Access Journals (Sweden)

J. Smeeckaert

2013-05-01

Full Text Available Accurate Digital Terrain Models (DTM are inevitable inputs for mapping areas subject to natural hazards. Topographic airborne laser scanning has become an established technique to characterize the Earth surface: lidar provides 3D point clouds allowing a fine reconstruction of the topography. For flood hazard modeling, the key step before terrain modeling is the discrimination of land and water surfaces within the delivered point clouds. Therefore, instantaneous shoreline, river borders, inland waters can be extracted as a basis for more reliable DTM generation. This paper presents an automatic, efficient, and versatile workflow for land/water classification of airborne topographic lidar data. For that purpose, a classification framework based on Support Vector Machines (SVM is designed. First, a restricted set of features, based only 3D lidar point coordinates and flightline information, is defined. Then, the SVM learning step is performed on small but well-targeted areas thanks to an automatic region growing strategy. Finally, label probabilities given by the SVM are merged during a probabilistic relaxation step in order to remove pixel-wise misclassification. Results show that survey of millions of points are labelled with high accuracy (>95% in most cases for coastal areas, and >89% for rivers and that small natural and anthropic features of interest are still well classified though we work at low point densities (0.5–4 pts/m2. Our approach is valid for coasts and rivers, and provides a strong basis for further discrimination of land-cover classes and coastal habitats.

Assessing Structure and Condition of Temperate And Tropical Forests: Fusion of Terrestrial Lidar and Airborne Multi-Angle and Lidar Remote Sensing

Science.gov (United States)

Saenz, Edward J.

Forests provide vital ecosystem functions and services that maintain the integrity of our natural and human environment. Understanding the structural components of forests (extent, tree density, heights of multi-story canopies, biomass, etc.) provides necessary information to preserve ecosystem services. Increasingly, remote sensing resources have been used to map and monitor forests globally. However, traditional satellite and airborne multi-angle imagery only provide information about the top of the canopy and little about the forest structure and understory. In this research, we investigative the use of rapidly evolving lidar technology, and how the fusion of aerial and terrestrial lidar data can be utilized to better characterize forest stand information. We further apply a novel terrestrial lidar methodology to characterize a Hemlock Woolly Adelgid infestation in Harvard Forest, Massachusetts, and adapt a dynamic terrestrial lidar sampling scheme to identify key structural vegetation profiles of tropical rainforests in La Selva, Costa Rica.

Mapping Savanna Tree Species at Ecosystem Scales Using Support Vector Machine Classification and BRDF Correction on Airborne Hyperspectral and LiDAR Data

Directory of Open Access Journals (Sweden)

Gregory P. Asner

2012-11-01

Full Text Available Mapping the spatial distribution of plant species in savannas provides insight into the roles of competition, fire, herbivory, soils and climate in maintaining the biodiversity of these ecosystems. This study focuses on the challenges facing large-scale species mapping using a fusion of Light Detection and Ranging (LiDAR and hyperspectral imagery. Here we build upon previous work on airborne species detection by using a two-stage support vector machine (SVM classifier to first predict species from hyperspectral data at the pixel scale. Tree crowns are segmented from the lidar imagery such that crown-level information, such as maximum tree height, can then be combined with the pixel-level species probabilities to predict the species of each tree. An overall prediction accuracy of 76% was achieved for 15 species. We also show that bidirectional reflectance distribution (BRDF effects caused by anisotropic scattering properties of savanna vegetation can result in flight line artifacts evident in species probability maps, yet these can be largely mitigated by applying a semi-empirical BRDF model to the hyperspectral data. We find that confronting these three challenges—reflectance anisotropy, integration of pixel- and crown-level data, and crown delineation over large areas—enables species mapping at ecosystem scales for monitoring biodiversity and ecosystem function.

APPLICATION OF MOBILE LIDAR MAPPING FOR DAMAGE SURVEY AFTER GREAT EAST JAPAN EARTHQUAKE

Directory of Open Access Journals (Sweden)

E. Ariyasu

2012-07-01

Full Text Available A massive earthquake of magnitude 9.0 hit off Tohoku region, the east coast of the Japanese main land, on 11 March, 2011. It was one of the historically powerful earthquakes in the world. The earthquake triggered powerful tsunami and broad-scale subsidence, so that, residential areas and infrastructures were catastrophically damaged. After that, it is necessary to renew a new map for reconstruction, such as cadastral map. In the critical situation, Mobile LiDAR Mapping system is efficient to rapidly collect fine data at once and capture more details of terrain features than data from airborne. In this paper, we would like to introduce procured instruments in our company and implemented survey several areas after the event, and suggest how to survey for cadastral map by Mobile LiDAR Mapping System.

Monitoring the Distribution and Dynamics of an Invasive Grass in Tropical Savanna Using Airborne LiDAR

Directory of Open Access Journals (Sweden)

Shaun R. Levick

2015-04-01

Full Text Available The spread of an alien invasive grass (gamba grass—Andropogon gayanus in the tropical savannas of Northern Australia is a major threat to habitat quality and biodiversity in the region, primarily through its influence on fire intensity. Effective control and eradication of this invader requires better insight into its spatial distribution and rate of spread to inform management actions. We used full-waveform airborne LiDAR to map areas of known A. gayanus invasion in the Batchelor region of the Northern Territory, Australia. Our stratified sampling campaign included wooded savanna areas with differing degrees of A. gayanus invasion and adjacent areas of native grass and woody tree mixtures. We used height and spatial contiguity based metrics to classify returns from A. gayanus and developed spatial representations of A. gayanus occurrence (1 m resolution and canopy cover (10 m resolution. The cover classification proved robust against two independent field-based investigations at 500 m2 (R2 = 0.87, RMSE = 12.53 and 100 m2 (R2 = 0.79, RMSE = 14.13 scale. Our mapping results provide a solid benchmark for evaluating the rate and pattern of A. gayanus spread from future LiDAR campaigns. In addition, this high-resolution mapping can be used to inform satellite image analysis for the evaluation of A. gayanus invasion over broader regional scales. Our research highlights the huge potential that airborne LiDAR holds for facilitating the monitoring and management of savanna habitat condition.

The impact of lidar elevation uncertainty on mapping intertidal habitats on barrier islands

Science.gov (United States)

Enwright, Nicholas M.; Wang, Lei; Borchert, Sinéad M.; Day, Richard H.; Feher, Laura C.; Osland, Michael J.

2018-01-01

While airborne lidar data have revolutionized the spatial resolution that elevations can be realized, data limitations are often magnified in coastal settings. Researchers have found that airborne lidar can have a vertical error as high as 60 cm in densely vegetated intertidal areas. The uncertainty of digital elevation models is often left unaddressed; however, in low-relief environments, such as barrier islands, centimeter differences in elevation can affect exposure to physically demanding abiotic conditions, which greatly influence ecosystem structure and function. In this study, we used airborne lidar elevation data, in situ elevation observations, lidar metadata, and tide gauge information to delineate low-lying lands and the intertidal wetlands on Dauphin Island, a barrier island along the coast of Alabama, USA. We compared three different elevation error treatments, which included leaving error untreated and treatments that used Monte Carlo simulations to incorporate elevation vertical uncertainty using general information from lidar metadata and site-specific Real-Time Kinematic Global Position System data, respectively. To aid researchers in instances where limited information is available for error propagation, we conducted a sensitivity test to assess the effect of minor changes to error and bias. Treatment of error with site-specific observations produced the fewest omission errors, although the treatment using the lidar metadata had the most well-balanced results. The percent coverage of intertidal wetlands was increased by up to 80% when treating the vertical error of the digital elevation models. Based on the results from the sensitivity analysis, it could be reasonable to use error and positive bias values from literature for similar environments, conditions, and lidar acquisition characteristics in the event that collection of site-specific data is not feasible and information in the lidar metadata is insufficient. The methodology presented in

Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data.

Science.gov (United States)

Silva, Carlos Alberto; Hudak, Andrew Thomas; Klauberg, Carine; Vierling, Lee Alexandre; Gonzalez-Benecke, Carlos; de Padua Chaves Carvalho, Samuel; Rodriguez, Luiz Carlos Estraviz; Cardil, Adrián

2017-12-01

LiDAR remote sensing is a rapidly evolving technology for quantifying a variety of forest attributes, including aboveground carbon (AGC). Pulse density influences the acquisition cost of LiDAR, and grid cell size influences AGC prediction using plot-based methods; however, little work has evaluated the effects of LiDAR pulse density and cell size for predicting and mapping AGC in fast-growing Eucalyptus forest plantations. The aim of this study was to evaluate the effect of LiDAR pulse density and grid cell size on AGC prediction accuracy at plot and stand-levels using airborne LiDAR and field data. We used the Random Forest (RF) machine learning algorithm to model AGC using LiDAR-derived metrics from LiDAR collections of 5 and 10 pulses m -2 (RF5 and RF10) and grid cell sizes of 5, 10, 15 and 20 m. The results show that LiDAR pulse density of 5 pulses m -2 provides metrics with similar prediction accuracy for AGC as when using a dataset with 10 pulses m -2 in these fast-growing plantations. Relative root mean square errors (RMSEs) for the RF5 and RF10 were 6.14 and 6.01%, respectively. Equivalence tests showed that the predicted AGC from the training and validation models were equivalent to the observed AGC measurements. The grid cell sizes for mapping ranging from 5 to 20 also did not significantly affect the prediction accuracy of AGC at stand level in this system. LiDAR measurements can be used to predict and map AGC across variable-age Eucalyptus plantations with adequate levels of precision and accuracy using 5 pulses m -2 and a grid cell size of 5 m. The promising results for AGC modeling in this study will allow for greater confidence in comparing AGC estimates with varying LiDAR sampling densities for Eucalyptus plantations and assist in decision making towards more cost effective and efficient forest inventory.

Tropical Airborne LiDAR for Landslide Assessment in Malaysia: a technical perspective

Science.gov (United States)

Abd Manap, Mohamad; Azhari Razak, Khamarrul; Mohamad, Zakaria; Ahmad, Azhari; Ahmad, Ferdaus; Mohamad Zin, Mazlan; A'zad Rosle, Qalam

2015-04-01

Malaysia has faced a substantial number of landslide events every year. Cameron Highlands, Pahang is one of the badly areas affected by slope failures characterized by extreme climate, rugged topographic and weathered geological structures in a tropical environment. A high frequency of landslide occurrence in the hilly areas is predominantly due to the geological materials, tropical monsoon seasons and uncontrolled agricultural activities. Therefore the Government of Malaysia through the Prime Minister Department has allocated a special budget to conduct national level hazard and risk mapping project through Minerals and Geoscience Department Malaysia, the Ministry of Natural Resources and Environment. The primary aim of this project is to provide slope hazard risk information for a better slope management in Malaysia. In addition this project will establish national infrastructure for geospatial information on the geological terrain and slope by emphasizing the disaster risk throughout the country. The areas of interest are located in the three different selected areas i.e. Cameron Highlands (275 square kilometers), Ipoh (200 square kilometers) and Cheras Kajang -- Batang kali (650 square kilometers). These areas are selected based on National Slope Master Plan (2009 -- 2023) that endorsed by Malaysia Government Cabinet. The national hazard and risk mapping project includes six parts of major tasks: (1) desk study and mobilization, (2) airborne LiDAR data acquisition and analysis, (3) field data acquisition and verification, (4) hazard and risk for natural terrain, (5) hazard and risk analysis for man-made slope and (6) Man-made slope mitigation/preventive measures. The project was authorized in September, 2014 and will be ended in March, 2016. In this paper, the main focus is to evaluate the suitability of integrated capability of airborne- and terrestrial LiDAR data acquisition and analysis, and also digital photography for regional landslide assessment. The

Tropical forest carbon assessment: integrating satellite and airborne mapping approaches

International Nuclear Information System (INIS)

Asner, Gregory P

2009-01-01

Large-scale carbon mapping is needed to support the UNFCCC program to reduce deforestation and forest degradation (REDD). Managers of forested land can potentially increase their carbon credits via detailed monitoring of forest cover, loss and gain (hectares), and periodic estimates of changes in forest carbon density (tons ha -1 ). Satellites provide an opportunity to monitor changes in forest carbon caused by deforestation and degradation, but only after initial carbon densities have been assessed. New airborne approaches, especially light detection and ranging (LiDAR), provide a means to estimate forest carbon density over large areas, which greatly assists in the development of practical baselines. Here I present an integrated satellite-airborne mapping approach that supports high-resolution carbon stock assessment and monitoring in tropical forest regions. The approach yields a spatially resolved, regional state-of-the-forest carbon baseline, followed by high-resolution monitoring of forest cover and disturbance to estimate carbon emissions. Rapid advances and decreasing costs in the satellite and airborne mapping sectors are already making high-resolution carbon stock and emissions assessments viable anywhere in the world.

A Study on Factors Affecting Airborne LiDAR Penetration

Directory of Open Access Journals (Sweden)

Wei-Chen Hsu

2015-01-01

Full Text Available This study uses data from different periods, areas and parameters of airborne LiDAR (light detection and ranging surveys to understand the factors that influence airborne LiDAR penetration rate. A discussion is presented on the relationships between these factors and LiDAR penetration rate. The results show that the flight height above ground level (AGL does not have any relationship with the penetration rate. There are some factors that should have larger influence. For example, the laser is affected by a wet ground surface by reducing the number of return echoes. The field of view (FOV has a slightly negative correlation with the penetration rate, which indicates that the laser incidence angle close to zero should achieve the best penetration. The vegetation cover rate also shows a negative correlation with the penetration rate, thus bare ground and reduced vegetation in the aftermath of a typhoon also cause high penetration rate. More return echoes could be extracted from the full-waveform system, thereby effectively improving the penetration rate. This study shows that full-waveform LiDAR is an effective method for increasing the number of surface reflected echoes. This study suggests avoiding LiDAR survey employment directly following precipitation to prevent laser echo reduction.

Capability Assessment and Performance Metrics for the Titan Multispectral Mapping Lidar

Directory of Open Access Journals (Sweden)

Juan Carlos Fernandez-Diaz

2016-11-01

Full Text Available In this paper we present a description of a new multispectral airborne mapping light detection and ranging (lidar along with performance results obtained from two years of data collection and test campaigns. The Titan multiwave lidar is manufactured by Teledyne Optech Inc. (Toronto, ON, Canada and emits laser pulses in the 1550, 1064 and 532 nm wavelengths simultaneously through a single oscillating mirror scanner at pulse repetition frequencies (PRF that range from 50 to 300 kHz per wavelength (max combined PRF of 900 kHz. The Titan system can perform simultaneous mapping in terrestrial and very shallow water environments and its multispectral capability enables new applications, such as the production of false color active imagery derived from the lidar return intensities and the automated classification of target and land covers. Field tests and mapping projects performed over the past two years demonstrate capabilities to classify five land covers in urban environments with an accuracy of 90%, map bathymetry under more than 15 m of water, and map thick vegetation canopies at sub-meter vertical resolutions. In addition to its multispectral and performance characteristics, the Titan system is designed with several redundancies and diversity schemes that have proven to be beneficial for both operations and the improvement of data quality.

Individual tree detection based on densities of high points of high resolution airborne lidar

NARCIS (Netherlands)

Abd Rahman, M.Z.; Gorte, B.G.H.

2008-01-01

The retrieval of individual tree location from Airborne LiDAR has focused largely on utilizing canopy height. However, high resolution Airborne LiDAR offers another source of information for tree detection. This paper presents a new method for tree detection based on high points’ densities from a

Buildings classification from airborne LiDAR point clouds through OBIA and ontology driven approach

Science.gov (United States)

Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.

2013-04-01

In the last years, airborne Light Detection and Ranging (LiDAR) data proved to be a valuable information resource for a vast number of applications ranging from land cover mapping to individual surface feature extraction from complex urban environments. To extract information from LiDAR data, users apply prior knowledge. Unfortunately, there is no consistent initiative for structuring this knowledge into data models that can be shared and reused across different applications and domains. The absence of such models poses great challenges to data interpretation, data fusion and integration as well as information transferability. The intention of this work is to describe the design, development and deployment of an ontology-based system to classify buildings from airborne LiDAR data. The novelty of this approach consists of the development of a domain ontology that specifies explicitly the knowledge used to extract features from airborne LiDAR data. The overall goal of this approach is to investigate the possibility for classification of features of interest from LiDAR data by means of domain ontology. The proposed workflow is applied to the building extraction process for the region of "Biberach an der Riss" in South Germany. Strip-adjusted and georeferenced airborne LiDAR data is processed based on geometrical and radiometric signatures stored within the point cloud. Region-growing segmentation algorithms are applied and segmented regions are exported to the GeoJSON format. Subsequently, the data is imported into the ontology-based reasoning process used to automatically classify exported features of interest. Based on the ontology it becomes possible to define domain concepts, associated properties and relations. As a consequence, the resulting specific body of knowledge restricts possible interpretation variants. Moreover, ontologies are machinable and thus it is possible to run reasoning on top of them. Available reasoners (FACT++, JESS, Pellet) are used to check

Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR.

Science.gov (United States)

Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M

2017-07-01

There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate

Turbulence and Mountain Wave Conditions Observed with an Airborne 2-Micron Lidar

Science.gov (United States)

Teets, Edward H., Jr.; Ehernberger, Jack; Bogue, Rodney; Ashburn, Chris

2007-01-01

Joint efforts by the National Aeronautics and Space Administration (NASA), the Department of Defense, and industry partners are enhancing the capability of airborne wind and turbulence detection. The Airborne Coherent Lidar for Advanced In-Flight Measurements (ACLAIM) was flown on three series of flights to assess its capability over a range of altitudes, air mass conditions, and gust phenomena. This paper describes the observation of mountain waves and turbulence induced by mountain waves over the Tehachapi and Sierra Nevada mountain ranges in southern California by lidar onboard the NASA Airborne Science DC-8 airplane. The examples in this paper compare lidar-predicted mountain waves and wave-induced turbulence to subsequent aircraft-measured true airspeed. Airplane acceleration data is presented describing the effects of the wave-induced turbulence on the DC-8 airplane. Highlights of the lidar-predicted airspeed from the two flights show increases of 12 m/s at the mountain wave interface and peak-to-peak airspeed changes of 10 m/s and 15 m/s in a span of 12 s in moderate turbulence.

Now You See It… Now You Don’t: Understanding Airborne Mapping LiDAR Collection and Data Product Generation for Archaeological Research in Mesoamerica

Directory of Open Access Journals (Sweden)

Juan Carlos Fernandez-Diaz

2014-10-01

Full Text Available In this paper we provide a description of airborne mapping LiDAR, also known as airborne laser scanning (ALS, technology and its workflow from mission planning to final data product generation, with a specific emphasis on archaeological research. ALS observations are highly customizable, and can be tailored to meet specific research needs. Thus it is important for an archaeologist to fully understand the options available during planning, collection and data product generation before commissioning an ALS survey, to ensure the intended research questions can be answered with the resultant data products. Also this knowledge is of great use for the researcher trying to understand the quality and limitations of existing datasets collected for other purposes. Throughout the paper we use examples from archeological ALS projects to illustrate the key concepts of importance for the archaeology researcher.

Monitoring individual tree-based change with airborne lidar.

Science.gov (United States)

Duncanson, Laura; Dubayah, Ralph

2018-05-01

Understanding the carbon flux of forests is critical for constraining the global carbon cycle and managing forests to mitigate climate change. Monitoring forest growth and mortality rates is critical to this effort, but has been limited in the past, with estimates relying primarily on field surveys. Advances in remote sensing enable the potential to monitor tree growth and mortality across landscapes. This work presents an approach to measure tree growth and loss using multidate lidar campaigns in a high-biomass forest in California, USA. Individual tree crowns were delineated in 2008 and again in 2013 using a 3D crown segmentation algorithm, with derived heights and crown radii extracted and used to estimate individual tree aboveground biomass. Tree growth, loss, and aboveground biomass were analyzed with respect to tree height and crown radius. Both tree growth and loss rates decrease with increasing tree height, following the expectation that trees slow in growth rate as they age. Additionally, our aboveground biomass analysis suggests that, while the system is a net source of aboveground carbon, these carbon dynamics are governed by size class with the largest sources coming from the loss of a relatively small number of large individuals. This study demonstrates that monitoring individual tree-based growth and loss can be conducted with multidate airborne lidar, but these methods remain relatively immature. Disparities between lidar acquisitions were particularly difficult to overcome and decreased the sample of trees analyzed for growth rate in this study to 21% of the full number of delineated crowns. However, this study illuminates the potential of airborne remote sensing for ecologically meaningful forest monitoring at an individual tree level. As methods continue to improve, airborne multidate lidar will enable a richer understanding of the drivers of tree growth, loss, and aboveground carbon flux.

Airborne lidar measurements of the Soufriere eruption of 17 April 1979

Science.gov (United States)

Fuller, W. H., Jr.; Sokol, S.; Hunt, W. H.

1982-01-01

At the time of the Soufriere, St. Vincent, volcanic eruption of April 17, 1979, a NASA P-3 aircraft with an uplooking lidar (light detection and ranging) system onboard was airborne 130 kilometers east of the island. Lidar measurements of the fresh volcanic ash were made approximately 2 hours after the eruption, 120 kilometers to the northeast and east. On the evening of April 18, the airborne lidar, on a southerly flight track, detected significant amounts of stratospheric material in layers at 16, 17, 18, and 19.5 kilometers. These data, and measurements to the north on April 19, indicate that the volcanic plume penetrated the stratosphere to an altitude of about 20 kilometers and moved south during the first 48 hours after the eruption.

COMPREHENSIVE COMPARISON OF TWO IMAGE-BASED POINT CLOUDS FROM AERIAL PHOTOS WITH AIRBORNE LIDAR FOR LARGE-SCALE MAPPING

Directory of Open Access Journals (Sweden)

E. Widyaningrum

2017-09-01

Full Text Available The integration of computer vision and photogrammetry to generate three-dimensional (3D information from images has contributed to a wider use of point clouds, for mapping purposes. Large-scale topographic map production requires 3D data with high precision and accuracy to represent the real conditions of the earth surface. Apart from LiDAR point clouds, the image-based matching is also believed to have the ability to generate reliable and detailed point clouds from multiple-view images. In order to examine and analyze possible fusion of LiDAR and image-based matching for large-scale detailed mapping purposes, point clouds are generated by Semi Global Matching (SGM and by Structure from Motion (SfM. In order to conduct comprehensive and fair comparison, this study uses aerial photos and LiDAR data that were acquired at the same time. Qualitative and quantitative assessments have been applied to evaluate LiDAR and image-matching point clouds data in terms of visualization, geometric accuracy, and classification result. The comparison results conclude that LiDAR is the best data for large-scale mapping.

Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations

Science.gov (United States)

Ross Nelson; Hank Margolis; Paul Montesano; Guoqing Sun; Bruce Cook; Larry Corp; Hans-Erik Andersen; Ben deJong; Fernando Paz Pellat; Thaddeus Fickel; Jobriath Kauffman; Stephen Prisley

2017-01-01

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar...

Object Classification Using Airborne Multispectral LiDAR Data

Directory of Open Access Journals (Sweden)

PAN Suoyan

2018-02-01

Full Text Available Airborne multispectral LiDAR system,which obtains surface geometry and spectral data of objects,simultaneously,has become a fast effective,large-scale spatial data acquisition method.Multispectral LiDAR data are characteristics of completeness and consistency of spectrum and spatial geometric information.Support vector machine (SVM,a machine learning method,is capable of classifying objects based on small samples.Therefore,by means of SVM,this paper performs land cover classification using multispectral LiDAR data. First,all independent point cloud with different wavelengths are merged into a single point cloud,where each pixel contains the three-wavelength spectral information.Next,the merged point cloud is converted into range and intensity images.Finally,land-cover classification is performed by means of SVM.All experiments were conducted on the Optech Titan multispectral LiDAR data,containing three individual point cloud collected by 532 nm,1024 nm,and 1550 nm laser beams.Experimental results demonstrate that ①compared to traditional single-wavelength LiDAR data,multispectral LiDAR data provide a promising solution to land use and land cover applications;②SVM is a feasible method for land cover classification of multispectral LiDAR data.

Forest Stand Segmentation Using Airborne LIDAR Data and Very High Resolution Multispectral Imagery

Science.gov (United States)

Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet, Valérie; Hervieu, Alexandre

2016-06-01

Forest stands are the basic units for forest inventory and mapping. Stands are large forested areas (e.g., ≥ 2 ha) of homogeneous tree species composition. The accurate delineation of forest stands is usually performed by visual analysis of human operators on very high resolution (VHR) optical images. This work is highly time consuming and should be automated for scalability purposes. In this paper, a method based on the fusion of airborne laser scanning data (or lidar) and very high resolution multispectral imagery for automatic forest stand delineation and forest land-cover database update is proposed. The multispectral images give access to the tree species whereas 3D lidar point clouds provide geometric information on the trees. Therefore, multi-modal features are computed, both at pixel and object levels. The objects are individual trees extracted from lidar data. A supervised classification is performed at the object level on the computed features in order to coarsely discriminate the existing tree species in the area of interest. The analysis at tree level is particularly relevant since it significantly improves the tree species classification. A probability map is generated through the tree species classification and inserted with the pixel-based features map in an energetical framework. The proposed energy is then minimized using a standard graph-cut method (namely QPBO with α-expansion) in order to produce a segmentation map with a controlled level of details. Comparison with an existing forest land cover database shows that our method provides satisfactory results both in terms of stand labelling and delineation (matching ranges between 94% and 99%).

Mapping of past stand-level forest disturbances and estimation of time since disturbance using simulated spaceborne LiDAR data

Science.gov (United States)

Sanchez Lopez, N.; Hudak, A. T.; Boschetti, L.

2017-12-01

, and Elk Creek watersheds ( 54,000 ha) within the Nez Perce-Clearwater National Forest in Idaho, where airborne LiDAR and reference maps on TSD were available. Simulated GEDI footprints and waveforms were obtained from airborne LiDAR point clouds and the results were compared to similar analysis performed with airborne LiDAR.

2005 Oahu/Maui Lidar Mapping Project

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser rangefinding, GPS positioning...

Pulsed Airborne Lidar Measurements of C02 Column Absorption

Science.gov (United States)

Abshire, James B.; Riris, Haris; Allan, Graham R.; Weaver, Clark J.; Mao, Jianping; Sun, Xiaoli; Hasselbrack, William E.; Rodriquez, Michael; Browell, Edward V.

2011-01-01

We report on airborne lidar measurements of atmospheric CO2 column density for an approach being developed as a candidate for NASA's ASCENDS mission. It uses a pulsed dual-wavelength lidar measurement based on the integrated path differential absorption (IPDA) technique. We demonstrated the approach using the CO2 measurement from aircraft in July and August 2009 over four locations. The results show clear CO2 line shape and absorption signals, which follow the expected changes with aircraft altitude from 3 to 13 km. The 2009 measurements have been analyzed in detail and the results show approx.1 ppm random errors for 8-10 km altitudes and approx.30 sec averaging times. Airborne measurements were also made in 2010 with stronger signals and initial analysis shows approx. 0.3 ppm random errors for 80 sec averaging times for measurements at altitudes> 6 km.

Voxel-Based Spatial Filtering Method for Canopy Height Retrieval from Airborne Single-Photon Lidar

Directory of Open Access Journals (Sweden)

Hao Tang

2016-09-01

Full Text Available Airborne single-photon lidar (SPL is a new technology that holds considerable potential for forest structure and carbon monitoring at large spatial scales because it acquires 3D measurements of vegetation faster and more efficiently than conventional lidar instruments. However, SPL instruments use green wavelength (532 nm lasers, which are sensitive to background solar noise, and therefore SPL point clouds require more elaborate noise filtering than other lidar instruments to determine canopy heights, particularly in daytime acquisitions. Histogram-based aggregation is a commonly used approach for removing noise from photon counting lidar data, but it reduces the resolution of the dataset. Here we present an alternate voxel-based spatial filtering method that filters noise points efficiently while largely preserving the spatial integrity of SPL data. We develop and test our algorithms on an experimental SPL dataset acquired over Garrett County in Maryland, USA. We then compare canopy attributes retrieved using our new algorithm with those obtained from the conventional histogram binning approach. Our results show that canopy heights derived using the new algorithm have a strong agreement with field-measured heights (r2 = 0.69, bias = 0.42 m, RMSE = 4.85 m and discrete return lidar heights (r2 = 0.94, bias = 1.07 m, RMSE = 2.42 m. Results are consistently better than height accuracies from the histogram method (field data: r2 = 0.59, bias = 0.00 m, RMSE = 6.25 m; DRL: r2 = 0.78, bias = −0.06 m and RMSE = 4.88 m. Furthermore, we find that the spatial-filtering method retains fine-scale canopy structure detail and has lower errors over steep slopes. We therefore believe that automated spatial filtering algorithms such as the one presented here can support large-scale, canopy structure mapping from airborne SPL data.

USACE National Coastal Mapping Program Update

Science.gov (United States)

Sylvester, C.

2017-12-01

The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) formed in 1998 to support the coastal mapping and charting requirements of the USACE, NAVO, NOAA and USGS. This partnership fielded three generations of airborne lidar bathymeters, executed operational data collection programs within the U.S. and overseas, and advanced research and development in airborne lidar bathymetry and complementary technologies. JALBTCX executes a USACE Headquarters-funded National Coastal Mapping Program (NCMP). Initiated in 2004, the NCMP provides high-resolution, high-accuracy elevation and imagery data along the sandy shorelines of the U.S. on a recurring basis. NCMP mapping activities are coordinated with Federal mapping partners through the Interagency Working Group on Ocean and Coastal Mapping and the 3D Elevation Program. The NCMP, currently in it's third cycle, is performing operations along the East Coast in 2017, after having completed surveys along the Gulf Coast in 2016 and conducting emergency response operations in support of Hurricane Matthew. This presentation will provide an overview of JALBTCX, its history in furthering airborne lidar bathymetry technology to meet emerging mapping requirements, current NCMP operations and data products, and Federal mapping coordination activities.

Tree filtering for high density airborne LiDAR data

NARCIS (Netherlands)

Abd Rahman, M.Z.; Gorte, B.G.H.

2008-01-01

A high resolution Airborne LiDAR data creates better opportunity for an individual tree measurement and provides valuable results for more precise forest inventory. This paper presents tree filtering approach that able to separate dominant tree and undergrowth vegetation. The results can be used for

INTEGRATING SMARTPHONE IMAGES AND AIRBORNE LIDAR DATA FOR COMPLETE URBAN BUILDING MODELLING

Directory of Open Access Journals (Sweden)

S. Zhang

2016-06-01

Full Text Available A complete building model reconstruction needs data collected from both air and ground. The former often has sparse coverage on building façades, while the latter usually is unable to observe the building rooftops. Attempting to solve the missing data issues in building reconstruction from single data source, we describe an approach for complete building reconstruction that integrates airborne LiDAR data and ground smartphone imagery. First, by taking advantages of GPS and digital compass information embedded in the image metadata of smartphones, we are able to find airborne LiDAR point clouds for the corresponding buildings in the images. In the next step, Structure-from-Motion and dense multi-view stereo algorithms are applied to generate building point cloud from multiple ground images. The third step extracts building outlines respectively from the LiDAR point cloud and the ground image point cloud. An automated correspondence between these two sets of building outlines allows us to achieve a precise registration and combination of the two point clouds, which ultimately results in a complete and full resolution building model. The developed approach overcomes the problem of sparse points on building façades in airborne LiDAR and the deficiency of rooftops in ground images such that the merits of both datasets are utilized.

Low-pass parabolic FFT filter for airborne and satellite lidar signal processing.

Science.gov (United States)

Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian

2015-10-14

In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing.

Unveiling topographical changes using LiDAR mapping capability: case study of Belaga in Sarawak, East-Malaysia

Science.gov (United States)

Ganendra, T. R.; Khan, N. M.; Razak, W. J.; Kouame, Y.; Mobarakeh, E. T.

2016-06-01

The use of Light Detection and Ranging (LiDAR) remote sensing technology to scan and map landscapes has proven to be one of the most popular techniques to accurately map topography. Thus, LiDAR technology is the ultimate method of unveiling the surface feature under dense vegetation, and, this paper intends to emphasize the diverse techniques that can be utilized to elucidate topographical changes over the study area, using multi-temporal airborne full waveform LiDAR datasets collected in 2012 and 2014. Full waveform LiDAR data offers access to an almost unlimited number of returns per shot, which enables the user to explore in detail topographical changes, such as vegetation growth measurement. The study also found out topography changes at the study area due to earthwork activities contributing to soil consolidation, soil erosion and runoff, requiring cautious monitoring. The implications of this study not only concurs with numerous investigations undertaken by prominent researchers to improve decision making, but also corroborates once again that investigations employing multi-temporal LiDAR data to unveil topography changes in vegetated terrains, produce more detailed and accurate results than most other remote sensing data.

Mapping and quantifying geodiversity in land-water transition zones using MBES and topobathymetric LiDAR

Science.gov (United States)

Brandbyge Ernstsen, Verner; Skovgaard Andersen, Mikkel; Gergely, Aron; Schulze Tenberge, Yvonne; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Winter, Christian; Bartholomä, Alexander

2016-04-01

Land-water transition zones, like e.g. coastal and fluvial environments, are valuable ecosystems which are often characterised by high biodiversity and geodiversity. However, often these land-water transition zones are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point clouds, which both have point densities in the order of 20 points/m2. Morphometric analyses of the DEMs enabled the identification and mapping of the different landforms within the coastal and fluvial environments. Hereby, we demonstrate that vessel borne MBES and airborne topobathymetric LiDAR, here in combination, are promising tools for seamless mapping across land-water transition zones as well as for the quantification of a range of landforms at landscape scale in different land-water transition zone environments. Hence, we demonstrate the potential for mapping and quantifying geomorphological diversity, which is one of the main components of geodiversity and a prerequisite for assessing geoheritage. Acknowledgements This work was funded by the Danish Council for

THE RAILMAPPER – A DEDICATED MOBILE LIDAR MAPPING SYSTEM FOR RAILWAY NETWORKS

Directory of Open Access Journals (Sweden)

J. Kremer

2012-07-01

Full Text Available The Mobile LiDAR Mapping System StreetMapper from IGI and 3D Laser Mapping (Bingham Nottingham, UK is mounted on a large variety of road vehicles to cover different mission specifications. In addition to the operation on the road, the system finds its applications on other kinds of vehicles, like boats or trains. The modular and flexible system concept even allows utilizing the same LiDAR Mapping system for Mobile Mapping on the ground and for airborne missions on helicopters, respectively. Besides this general flexibility, each application has its own special requirements. Special hardware and software components are needed to complete the core components, like the laser scanner and the GNSS/IMU systems, to build a dedicated system for the chosen task. Compared to the typical dynamics of a road vehicle mounted Mobile Mapping system, a dedicated rail mapping system operates under conditions that are much more challenging for a high accuracy GNSS/IMU trajectory determination. Furthermore, the typical rail mapping tasks, like the exact measurement of the rail track geometry, require the operation of the most accurate laser scanners and of specialized post-processing software. In this paper, the RailMapper, a specialized Mobile Mapping system for railway surveys is presented. The system is described with focus on the railway specific requirements and results of practical surveys are given.

BUILDING EDGE DETECTION USING SMALL-FOOTPRINT AIRBORNE FULL-WAVEFORM LIDAR DATA

Directory of Open Access Journals (Sweden)

J.-C. Michelin

2012-07-01

Full Text Available The full-waveform lidar technology allows a complete access to the information related to the emitted and backscattered laser signals. Although most of the common applications of full-waveform lidar are currently dedicated to the study of forested areas, some recent studies have shown that airborne full-waveform data is relevant for urban area analysis. We extend the field to pattern recognition with a focus on retrieval. Our proposed approach combines two steps. In a first time, building edges are coarsely extracted. Then, a physical model based on the lidar equation is used to retrieve a more accurate position of the estimated edge than the size of the lidar footprint. Another consequence is the estimation of more accurate planimetric positions of the extracted echoes.

Reducing Uncertainty in Mapping of Mangrove Aboveground Biomass Using Airborne Discrete Return Lidar Data

Directory of Open Access Journals (Sweden)

Francisca Rocha de Souza Pereira

2018-04-01

Full Text Available Remote sensing techniques offer useful tools for estimating forest biomass to large extent, thereby contributing to the monitoring of land use and landcover dynamics and the effectiveness of environmental policies. The main goal of this study was to investigate the potential use of discrete return light detection and ranging (lidar data to produce accurate aboveground biomass (AGB maps of mangrove forests. AGB was estimated in 34 small plots scatted over a 50 km2 mangrove forest in Rio de Janeiro, Brazil. Plot AGB was computed using either species-specific or non-species-specific allometric models. A total of 26 descriptive lidar metrics were extracted from the normalized height of the lidar point cloud data, and various model forms (random forest and partial least squares regression with backward selection of predictors (Auto-PLS were tested to predict the recorded AGB. The models developed using species-specific allometric models were distinctly more accurate (R2(calibration = 0.89, R2(validation = 0.80, root-mean-square error (RMSE, calibration = 11.20 t·ha−1, and RMSE(validation = 14.80 t·ha−1. The use of non-species-specific allometric models yielded large errors on a landscape scale (+14% or −18% bias depending on the allometry considered, indicating that using poor quality training data not only results in low precision but inaccuracy at all scales. It was concluded that under suitable sampling pattern and provided that accurate field data are used, discrete return lidar can accurately estimate and map the AGB in mangrove forests. Conversely this study underlines the potential bias affecting the estimates of AGB in other forested landscapes where only non-species-specific allometric equations are available.

Lidar and airborne investigation of smoke plume characteristics: Kootenai Creek Fire case study

Science.gov (United States)

S. Urbanski; V. Kovalev; W. M. Hao; C. Wold; A. Petkov

2010-01-01

A ground-based scanning lidar was utilized with a set of airborne instruments to acquire measurements of smoke plume dynamics, smoke aerosol distribution and chemical composition in the vicinity of active wildfires in the western U.S. A new retrieval technique was used for processing lidar multiangle measurements. The technique determines the location of...

Crown-Level Tree Species Classification Using Integrated Airborne Hyperspectral and LIDAR Remote Sensing Data

Science.gov (United States)

Wang, Z.; Wu, J.; Wang, Y.; Kong, X.; Bao, H.; Ni, Y.; Ma, L.; Jin, J.

2018-05-01

Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR) and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1) A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM) derived from LiDAR data; 2) The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3) Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4) The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90) performed better than LiDAR-metrics method (OA = 79

Remote Sensing of Vegetation Species Diversity: The Utility of Integrated Airborne Hyperspectral and Lidar Data

Science.gov (United States)

Krause, Keith Stuart

The change, reduction, or extinction of species is a major issue currently facing the Earth. Efforts are underway to measure, monitor, and protect habitats that contain high species diversity. Remote sensing technology shows extreme value for monitoring species diversity by mapping ecosystems and using those land cover maps or other derived data as proxies to species number and distribution. The National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) consists of remote sensing instruments such as an imaging spectrometer, a full-waveform lidar, and a high-resolution color camera. AOP collected data over the Ordway-Swisher Biological Station (OSBS) in May 2014. A majority of the OSBS site is covered by the Sandhill ecosystem, which contains a very high diversity of vegetation species and is a native habitat for several threatened fauna species. The research presented here investigates ways to analyze the AOP data to map ecosystems at the OSBS site. The research attempts to leverage the high spatial resolution data and study the variability of the data within a ground plot scale along with integrating data from the different sensors. Mathematical features are derived from the data and brought into a decision tree classification algorithm (rpart), in order to create an ecosystem map for the site. The hyperspectral and lidar features serve as proxies for chemical, functional, and structural differences in the vegetation types for each of the ecosystems. K-folds cross validation shows a training accuracy of 91%, a validation accuracy of 78%, and a 66% accuracy using independent ground validation. The results presented here represent an important contribution to utilizing integrated hyperspectral and lidar remote sensing data for ecosystem mapping, by relating the spatial variability of the data within a ground plot scale to a collection of vegetation types that make up a given ecosystem.

Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network

Directory of Open Access Journals (Sweden)

Hasan Asy’ari Arief

2018-06-01

Full Text Available Inspired by the success of deep learning techniques in dense-label prediction and the increasing availability of high precision airborne light detection and ranging (LiDAR data, we present a research process that compares a collection of well-proven semantic segmentation architectures based on the deep learning approach. Our investigation concludes with the proposition of some novel deep learning architectures for generating detailed land resource maps by employing a semantic segmentation approach. The contribution of our work is threefold. (1 First, we implement the multiclass version of the intersection-over-union (IoU loss function that contributes to handling highly imbalanced datasets and preventing overfitting. (2 Thereafter, we propose a novel deep learning architecture integrating the deep atrous network architecture with the stochastic depth approach for speeding up the learning process, and impose a regularization effect. (3 Finally, we introduce an early fusion deep layer that combines image-based and LiDAR-derived features. In a benchmark study carried out using the Follo 2014 LiDAR data and the NIBIO AR5 land resources dataset, we compare our proposals to other deep learning architectures. A quantitative comparison shows that our best proposal provides more than 5% relative improvement in terms of mean intersection-over-union over the atrous network, providing a basis for a more frequent and improved use of LiDAR data for automatic land cover segmentation.

Portable and Airborne Small Footprint LiDAR: Forest Canopy Structure Estimation of Fire Managed Plots

Directory of Open Access Journals (Sweden)

Claudia M.C.S. Listopad

2011-06-01

Full Text Available This study used an affordable ground-based portable LiDAR system to provide an understanding of the structural differences between old-growth and secondary-growth Southeastern pine. It provided insight into the strengths and weaknesses in the structural determination of portable systems in contrast to airborne LiDAR systems. Portable LiDAR height profiles and derived metrics and indices (e.g., canopy cover, canopy height were compared among plots with different fire frequency and fire season treatments within secondary forest and old growth plots. The treatments consisted of transitional season fire with four different return intervals: 1-yr, 2-yr, 3-yr fire return intervals, and fire suppressed plots. The remaining secondary plots were treated using a 2-yr late dormant season fire cycle. The old growth plots were treated using a 2-yr growing season fire cycle. Airborne and portable LiDAR derived canopy cover were consistent throughout the plots, with significantly higher canopy cover values found in 3-yr and fire suppressed plots. Portable LiDAR height profile and metrics presented a higher sensitivity in capturing subcanopy elements than the airborne system, particularly in dense canopy plots. The 3-dimensional structures of the secondary plots with varying fire return intervals were dramatically different to old-growth plots, where a symmetrical distribution with clear recruitment was visible. Portable LiDAR, even though limited to finer spatial scales and specific biases, is a low-cost investment with clear value for the management of forest canopy structure.

Forest Biomass Mapping From Lidar and Radar Synergies

Science.gov (United States)

Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.

2011-01-01

The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the

Column CO2 Measurement From an Airborne Solid-State Double-Pulsed 2-Micron Integrated Path Differential Absorption Lidar

Science.gov (United States)

Singh, U. N.; Yu, J.; Petros, M.; Refaat, T. F.; Remus, R.; Fay, J.; Reithmaier, K.

2014-01-01

NASA LaRC is developing and integrating a double-Pulsed 2-micron direct detection IPDA lidar for CO2 column measurement from an airborne platform. The presentation will describe the development of the 2-micrometers IPDA lidar system and present the airborne measurement of column CO2 and will compare to in-situ measurement for various ground target of different reflectivity.

Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar

Science.gov (United States)

Fedrigo, Melissa; Newnham, Glenn J.; Coops, Nicholas C.; Culvenor, Darius S.; Bolton, Douglas K.; Nitschke, Craig R.

2018-02-01

Light detection and ranging (lidar) data have been increasingly used for forest classification due to its ability to penetrate the forest canopy and provide detail about the structure of the lower strata. In this study we demonstrate forest classification approaches using airborne lidar data as inputs to random forest and linear unmixing classification algorithms. Our results demonstrated that both random forest and linear unmixing models identified a distribution of rainforest and eucalypt stands that was comparable to existing ecological vegetation class (EVC) maps based primarily on manual interpretation of high resolution aerial imagery. Rainforest stands were also identified in the region that have not previously been identified in the EVC maps. The transition between stand types was better characterised by the random forest modelling approach. In contrast, the linear unmixing model placed greater emphasis on field plots selected as endmembers which may not have captured the variability in stand structure within a single stand type. The random forest model had the highest overall accuracy (84%) and Cohen's kappa coefficient (0.62). However, the classification accuracy was only marginally better than linear unmixing. The random forest model was applied to a region in the Central Highlands of south-eastern Australia to produce maps of stand type probability, including areas of transition (the 'ecotone') between rainforest and eucalypt forest. The resulting map provided a detailed delineation of forest classes, which specifically recognised the coalescing of stand types at the landscape scale. This represents a key step towards mapping the structural and spatial complexity of these ecosystems, which is important for both their management and conservation.

Airborne direct-detection and coherent wind lidar measurements over the North Atlantic in 2015 supporting ESA's aeolus mission

Science.gov (United States)

Marksteiner, Uwe; Reitebuch, Oliver; Lemmerz, Christian; Lux, Oliver; Rahm, Stephan; Witschas, Benjamin; Schäfler, Andreas; Emmitt, Dave; Greco, Steve; Kavaya, Michael J.; Gentry, Bruce; Neely, Ryan R.; Kendall, Emma; Schüttemeyer, Dirk

2018-04-01

The launch of the Aeolus mission by the European Space Agency (ESA) is planned for 2018. The satellite will carry the first wind lidar in space, ALADIN (Atmospheric Laser Doppler INstrument). Its prototype instrument, the ALADIN Airborne Demonstrator (A2D), was deployed during several airborne campaigns aiming at the validation of the measurement principle and optimization of algorithms. In 2015, flights of two aircraft from DLR & NASA provided the chance to compare parallel wind measurements from four airborne wind lidars for the first time.

Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data

Directory of Open Access Journals (Sweden)

Xiaolong Liu

2015-01-01

Full Text Available Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR data in an object-based image analysis (OBIA paradigm. The aims of this work were the following: (i to understand the performances of different spectral dimension-reduced features from hyperspectral data and their combination with LiDAR derived height information in image segmentation; (ii to understand what classification accuracies of crop species can be achieved by combining hyperspectral and LiDAR data in an OBIA paradigm, especially in regions that have fragmented agricultural landscape and complicated crop planting structure; and (iii to understand the contributions of the crop height that is derived from LiDAR data, as well as the geometric and textural features of image objects, to the crop species’ separabilities. The study region was an irrigated agricultural area in the central Heihe river basin, which is characterized by many crop species, complicated crop planting structures, and fragmented landscape. The airborne hyperspectral data acquired by the Compact Airborne Spectrographic Imager (CASI with a 1 m spatial resolution and the Canopy Height Model (CHM data derived from the LiDAR data acquired by the airborne Leica ALS70 LiDAR system were used for this study. The image segmentation accuracies of different feature combination schemes (very high-resolution imagery (VHR, VHR/CHM, and minimum noise fractional transformed data (MNF/CHM were evaluated and analyzed. The results showed that VHR/CHM outperformed the other two combination schemes with a segmentation accuracy of 84.8%. The object-based crop species classification results of different feature integrations indicated that

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

Science.gov (United States)

Leitold, Veronika; Keller, Michael; Morton, Douglas C; Cook, Bruce D; Shimabukuro, Yosio E

2015-12-01

Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (~20 returns m -2 ) data was highly accurate (mean signed error of 0.19 ± 0.97 m), while those derived from reduced-density datasets (8 m -2 , 4 m -2 , 2 m -2 and 1 m -2 ) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4 m -2 , the bias in height estimates translated into errors of 80-125 Mg ha -1 in predicted aboveground biomass. Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Landslides Mapped from LIDAR Imagery, Kitsap County, Washington

Science.gov (United States)

McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.

2008-01-01

Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser

2008 City of Baltimore Lidar

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — In the spring of 2008, the City of Baltimore expressed an interest to upgrade the City GIS Database with mapping quality airborne LiDAR data. The City of Baltimore...

Estimating Aboveground Forest Carbon Stock of Major Tropical Forest Land Uses Using Airborne Lidar and Field Measurement Data in Central Sumatra

Science.gov (United States)

Thapa, R. B.; Watanabe, M.; Motohka, T.; Shiraishi, T.; shimada, M.

2013-12-01

Tropical forests are providing environmental goods and services including carbon sequestration, energy regulation, water fluxes, wildlife habitats, fuel, and building materials. Despite the policy attention, the tropical forest reserve in Southeast Asian region is releasing vast amount of carbon to the atmosphere due to deforestation. Establishing quality forest statistics and documenting aboveground forest carbon stocks (AFCS) are emerging in the region. Airborne and satellite based large area monitoring methods are developed to compliment conventional plot based field measurement methods as they are costly, time consuming, and difficult to implement for large regions. But these methods still require adequate ground measurements for calibrating accurate AFCS model. Furthermore, tropical region comprised of varieties of natural and plantation forests capping higher variability of forest structures and biomass volumes. To address this issue and the needs for ground data, we propose the systematic collection of ground data integrated with airborne light detection and ranging (LiDAR) data. Airborne LiDAR enables accurate measures of vertical forest structure, including canopy height and volume demanding less ground measurement plots. Using an appropriate forest type based LiDAR sampling framework, structural properties of forest can be quantified and treated similar to ground measurement plots, producing locally relevant information to use independently with satellite data sources including synthetic aperture radar (SAR). In this study, we examined LiDAR derived forest parameters with field measured data and developed general and specific AFCS models for tropical forests in central Sumatra. The general model is fitted for all types of natural and plantation forests while the specific model is fitted to the specific forest type. The study region consists of natural forests including peat swamp and dry moist forests, regrowth, and mangrove and plantation forests

Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

Directory of Open Access Journals (Sweden)

Carlos Alberto Silva

2017-10-01

Full Text Available Airborne lidar is a technology well-suited for mapping many forest attributes, including aboveground biomass (AGB stocks and changes in selective logging in tropical forests. However, trade-offs still exist between lidar pulse density and accuracy of AGB estimates. We assessed the impacts of lidar pulse density on the estimation of AGB stocks and changes using airborne lidar and field plot data in a selectively logged tropical forest located near Paragominas, Pará, Brazil. Field-derived AGB was computed at 85 square 50 × 50 m plots in 2014. Lidar data were acquired in 2012 and 2014, and for each dataset the pulse density was subsampled from its original density of 13.8 and 37.5 pulses·m−2 to lower densities of 12, 10, 8, 6, 4, 2, 0.8, 0.6, 0.4 and 0.2 pulses·m−2. For each pulse density dataset, a power-law model was developed to estimate AGB stocks from lidar-derived mean height and corresponding changes between the years 2012 and 2014. We found that AGB change estimates at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg·ha−1 when pulse density decreased from 12 to 0.2 pulses·m−2. The effects of pulse density were more pronounced in areas of steep slope, especially when the digital terrain models (DTMs used in the lidar derived forest height were created from reduced pulse density data. In particular, when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and the estimated AGB stock and changes did not exceed 20 Mg·ha−1. The results suggest that AGB change can be monitored in selective logging in tropical forests with reasonable accuracy and low cost with low pulse density lidar surveys if a baseline high-quality DTM is available from at least one lidar survey. We recommend the results of this study to be considered in developing projects and national

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

Science.gov (United States)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

2008 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) Topobathy Lidar: North Carolina

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These files contain topographic lidar data collected by the Compact Hydrographic Airborne Rapid Total Survey (CHARTS) system along the coast of North Carolina near...

Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

Science.gov (United States)

Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John Y.

2016-01-01

Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

Assessing biomass accumulation in second growth forests of Puerto Rico using airborne lidar

Science.gov (United States)

Martinuzzi, S.; Cook, B.; Corp, L. A.; Morton, D. C.; Helmer, E.; Keller, M.

2017-12-01

Degraded and second growth tropical forests provide important ecosystem services, such as carbon sequestration and soil stabilization. Lidar data measure the three-dimensional structure of forest canopies and are commonly used to quantify aboveground biomass in temperate forest landscapes. However, the ability of lidar data to quantify second growth forest biomass in complex, tropical landscapes is less understood. Our goal was to evaluate the use of airborne lidar data to quantify aboveground biomass in a complex tropical landscape, the Caribbean island of Puerto Rico. Puerto Rico provides an ideal place for studying biomass accumulation because of the abundance of second growth forests in different stages of recovery, and the high ecological heterogeneity. Puerto Rico was almost entirely deforested for agriculture until the 1930s. Thereafter, agricultural abandonment resulted in a mosaic of second growth forests that have recovered naturally under different types of climate, land use, topography, and soil fertility. We integrated forest plot data from the US Forest Service, Forest Inventory and Analysis (FIA) Program with recent lidar data from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) airborne imager to quantify forest biomass across the island's landscape. The G-LiHT data consisted on targeted acquisitions over the FIA plots and other forested areas representing the environmental heterogeneity of the island. To fully assess the potential of the lidar data, we compared the ability of lidar-derived canopy metrics to quantify biomass alone, and in combination with intensity and topographic metrics. The results presented here are a key step for improving our understanding of the patterns and drivers of biomass accumulation in tropical forests.

Individual tree crown modeling and change detection from airborne lidar data

NARCIS (Netherlands)

Xiao, W.; Xu, Sudan; Oude Elberink, S.J.; Vosselman, G.

2016-01-01

Light detection and ranging (lidar) provides a promising way of detecting changes of trees in three-dimensional (3-D) because laser beams can penetrate through the foliage and therefore provide full coverage of trees. The aim is to detect changes in trees in urban areas using multitemporal airborne

Performance analysis and technical assessment of coherent lidar systems for airborne wind shear detection

Science.gov (United States)

Huffaker, R. Milton; Targ, Russell

1988-01-01

Detailed computer simulations of the lidar wind-measuring process have been conducted to evaluate the use of pulsed coherent lidar for airborne windshear monitoring. NASA data fields for an actual microburst event were used in the simulation. Both CO2 and Ho:YAG laser lidar systems performed well in the microburst test case, and were able to measure wind shear in the severe weather of this wet microburst to ranges in excess of 1.4 km. The consequent warning time gained was about 15 sec.

CROWN-LEVEL TREE SPECIES CLASSIFICATION USING INTEGRATED AIRBORNE HYPERSPECTRAL AND LIDAR REMOTE SENSING DATA

Directory of Open Access Journals (Sweden)

Z. Wang

2018-05-01

Full Text Available Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1 A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM derived from LiDAR data; 2 The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3 Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4 The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90 performed better than Li

Mapping and quantifying geodiversity in land-water transition zones using MBES and topobathymetric LiDAR

DEFF Research Database (Denmark)

Ernstsen, Verner Brandbyge; Andersen, Mikkel Skovgaard; Gergely, Aron

due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal...... coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part...... of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point...

Atmospheric CO2 Concentration Measurements with Clouds from an Airborne Lidar

Science.gov (United States)

Mao, J.; Abshire, J. B.; Kawa, S. R.; Riris, H.; Allan, G. R.; Hasselbrack, W. E.; Numata, K.; Chen, J. R.; Sun, X.; DiGangi, J. P.; Choi, Y.

2017-12-01

Globally distributed atmospheric CO2 concentration measurements with high precision, low bias and full seasonal sampling are crucial to advance carbon cycle sciences. However, two thirds of the Earth's surface is typically covered by clouds, and passive remote sensing approaches from space are limited to cloud-free scenes. NASA Goddard is developing a pulsed, integrated-path differential absorption (IPDA) lidar approach to measure atmospheric column CO2 concentrations, XCO2, from space as a candidate for NASA's ASCENDS mission. Measurements of time-resolved laser backscatter profiles from the atmosphere also allow this technique to estimate XCO2 and range to cloud tops in addition to those to the ground with precise knowledge of the photon path-length. We demonstrate this measurement capability using airborne lidar measurements from summer 2017 ASCENDS airborne science campaign in Alaska. We show retrievals of XCO2 to ground and to a variety of cloud tops. We will also demonstrate how the partial column XCO2 to cloud tops and cloud slicing approach help resolving vertical and horizontal gradient of CO2 in cloudy conditions. The XCO2 retrievals from the lidar are validated against in situ measurements and compared to the Goddard Parameterized Chemistry Transport Model (PCTM) simulations. Adding this measurement capability to the future lidar mission for XCO2 will provide full global and seasonal data coverage and some information about vertical structure of CO2. This unique facility is expected to benefit atmospheric transport process studies, carbon data assimilation in models, and global and regional carbon flux estimation.

2003 NCFMP Lidar: NC Statewide Phase 2

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Airborne LIDAR terrain mapping data acquired January through March 2003. Point data (XYZ) in ASCII format. Horizontal datum NAD83(1995) North Carolina State Plane...

Airborne Lidar Simulator for the Lidar Surface Topography (LIST) Mission

Science.gov (United States)

Yu, Anthony W.; Krainak, Michael A.; Abshire, James B.; Cavanaugh, John; Valett, Susan; Ramos-Izquierdo, Luis

2010-01-01

In 2007, the National Research Council (NRC) completed its first decadal survey for Earth science at the request of NASA, NOAA, and USGS. The Lidar Surface Topography (LIST) mission is one of fifteen missions recommended by NRC, whose primary objectives are to map global topography and vegetation structure at 5 m spatial resolution, and to acquire global surface height mapping within a few years. NASA Goddard conducted an initial mission concept study for the LIST mission in 2007, and developed the initial measurement requirements for the mission.

2005 NCFMP Lidar: NC Statewide Phase 3

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Airborne LIDAR terrain mapping data acquired March through April 2005. These data sets may represent a single geographic tile of a larger, county/sub-county data...

Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

Science.gov (United States)

Vierling, Lee A.; Vierling, Kerri T.; Adam, Patrick; Hudak, Andrew T.

2013-01-01

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2

Airborne Measurements of Atmospheric Pressure made Using an IPDA Lidar Operating in the Oxygen A-Band

Science.gov (United States)

Riris, Haris; Abshire, James B.; Stephen, Mark; Rodriquez, Michael; Allan, Graham; Hasselbrack, William; Mao, Jianping

2012-01-01

We report airborne measurements of atmospheric pressure made using an integrated path differential absorption (IPDA) lidar that operates in the oxygen A-band near 765 nm. Remote measurements of atmospheric temperature and pressure are needed for NASA s Active Sensing of CO2 Emissions Over Nights, Days, and Seasons (ASCENDS) mission to measure atmospheric CO2. Accurate measurements of tropospheric CO2 on a global scale are very important in order to better understand its sources and sinks and to improve our predictions of climate change. The goal of ASCENDS is to determine the CO2 dry mixing ratio with lidar measurements from space at a level of 1 ppm. Analysis to date shows that with current weather models, measurements of both the CO2 column density and the column density of dry air are needed. Since O2 is a stable molecule that uniformly mixed in the atmosphere, measuring O2 absorption in the atmosphere can be used to infer the dry air density. We have developed an airborne (IPDA) lidar for Oxygen, with support from the NASA ESTO IIP program. Our lidar uses DFB-based seed laser diodes, a pulsed modulator, a fiber laser amplifier, and a non-linear crystal to generate wavelength tunable 765 nm laser pulses with a few uJ/pulse energy. The laser pulse rate is 10 KHz, and average transmitted laser power is 20 mW. Our lidar steps laser pulses across a selected line O2 doublet near 764.7 nm in the Oxygen A-band. The direct detection lidar receiver uses a 20 cm diameter telescope, a Si APD detector in Geiger mode, and a multi-channel scalar to detect and record the time resolved laser backscatter in 40 separate wavelength channels. Subsequent analysis is used to estimate the transmission line shape of the doublet for the laser pulses reflected from the ground. Ground based data analysis allows averaging from 1 to 60 seconds to increase SNR in the transmission line shape of the doublet. Our retrieval algorithm fits the expected O2 lineshapes against the measurements and

Demystifying LiDAR technologies for temperate rainforest in the Pacific Northwest

Science.gov (United States)

Rhonda Mazza; Demetrios Gatziolis

2013-01-01

Light detection and ranging (LiDAR), also known as airborne laser scanning, is a rapidly emerging technology for remote sensing. Used to help map, monitor, and assess natural resources, LiDAR data were first embraced by forestry professionals in Scandinavia as a tool for conducting forest inventories in the mid to late 1990s. Thus early LiDAR theory and applications...

Development of an Airborne Triple-Pulse 2-Micron Integrated Path Differential Absorption Lidar (IPDA) for Simultaneous Airborne Column Measurements of Carbon Dioxide and Water Vapor in the Atmosphere

Science.gov (United States)

Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Yu, Jirong; Antill, Charles W.; Remus, Ruben

2016-01-01

This presentation will provide status and details of an airborne 2-micron triple-pulse integrated path differential absorption (IPDA) lidar being developed at NASA Langley Research Center with support from NASA ESTO Instrument Incubator Program. The development of this active optical remote sensing IPDA instrument is targeted for measuring both atmospheric carbon dioxide and water vapor in the atmosphere from an airborne platform. This presentation will focus on the advancement of the 2-micron triple-pulse IPDA lidar development. Updates on the state-of-the-art triple-pulse laser transmitter will be presented including the status of seed laser locking, wavelength control, receiver and detector upgrades, laser packaging and lidar integration. Future plan for IPDA lidar system for ground integration, testing and flight validation will also be presented.

Michigan 2008 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the MI coasts of Lake Superior, Lake Michigan and...

Indiana 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Michigan coastline in the summer of 2006....

California 2009 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Pacific coast in 2009. The data types collected...

Connecticut 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic Coastline, in the summer of 2007. The...

Nevada 2008 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along Truckee River in NV in 2008. The data types...

California 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Pacific coast in 2010. The data types collected...

Georgia 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic Coast in 2010. The data types collected...

Scaling wood volume estimates from inventory plots to landscapes with airborne LiDAR in temperate deciduous forest

Directory of Open Access Journals (Sweden)

Shaun R. Levick

2016-05-01

Full Text Available Abstract Background Monitoring and managing carbon stocks in forested ecosystems requires accurate and repeatable quantification of the spatial distribution of wood volume at landscape to regional scales. Grid-based forest inventory networks have provided valuable records of forest structure and dynamics at individual plot scales, but in isolation they may not represent the carbon dynamics of heterogeneous landscapes encompassing diverse land-management strategies and site conditions. Airborne LiDAR has greatly enhanced forest structural characterisation and, in conjunction with field-based inventories, it provides avenues for monitoring carbon over broader spatial scales. Here we aim to enhance the integration of airborne LiDAR surveying with field-based inventories by exploring the effect of inventory plot size and number on the relationship between field-estimated and LiDAR-predicted wood volume in deciduous broad-leafed forest in central Germany. Results Estimation of wood volume from airborne LiDAR was most robust (R2 = 0.92, RMSE = 50.57 m3 ha−1 ~14.13 Mg C ha−1 when trained and tested with 1 ha experimental plot data (n = 50. Predictions based on a more extensive (n = 1100 plot network with considerably smaller (0.05 ha plots were inferior (R2 = 0.68, RMSE = 101.01 ~28.09 Mg C ha−1. Differences between the 1 and 0.05 ha volume models from LiDAR were negligible however at the scale of individual land-management units. Sample size permutation tests showed that increasing the number of inventory plots above 350 for the 0.05 ha plots returned no improvement in R2 and RMSE variability of the LiDAR-predicted wood volume model. Conclusions Our results from this study confirm the utility of LiDAR for estimating wood volume in deciduous broad-leafed forest, but highlight the challenges associated with field plot size and number in establishing robust relationships between airborne LiDAR and field derived wood volume. We

Scaling wood volume estimates from inventory plots to landscapes with airborne LiDAR in temperate deciduous forest.

Science.gov (United States)

Levick, Shaun R; Hessenmöller, Dominik; Schulze, E-Detlef

2016-12-01

Monitoring and managing carbon stocks in forested ecosystems requires accurate and repeatable quantification of the spatial distribution of wood volume at landscape to regional scales. Grid-based forest inventory networks have provided valuable records of forest structure and dynamics at individual plot scales, but in isolation they may not represent the carbon dynamics of heterogeneous landscapes encompassing diverse land-management strategies and site conditions. Airborne LiDAR has greatly enhanced forest structural characterisation and, in conjunction with field-based inventories, it provides avenues for monitoring carbon over broader spatial scales. Here we aim to enhance the integration of airborne LiDAR surveying with field-based inventories by exploring the effect of inventory plot size and number on the relationship between field-estimated and LiDAR-predicted wood volume in deciduous broad-leafed forest in central Germany. Estimation of wood volume from airborne LiDAR was most robust (R 2  = 0.92, RMSE = 50.57 m 3 ha -1  ~14.13 Mg C ha -1 ) when trained and tested with 1 ha experimental plot data (n = 50). Predictions based on a more extensive (n = 1100) plot network with considerably smaller (0.05 ha) plots were inferior (R 2  = 0.68, RMSE = 101.01 ~28.09 Mg C ha -1 ). Differences between the 1 and 0.05 ha volume models from LiDAR were negligible however at the scale of individual land-management units. Sample size permutation tests showed that increasing the number of inventory plots above 350 for the 0.05 ha plots returned no improvement in R 2 and RMSE variability of the LiDAR-predicted wood volume model. Our results from this study confirm the utility of LiDAR for estimating wood volume in deciduous broad-leafed forest, but highlight the challenges associated with field plot size and number in establishing robust relationships between airborne LiDAR and field derived wood volume. We are moving into a forest management era where

Maine 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic Coast of ME in 2010. The data types...

Florida 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic Coast and Gulf of Mexico in 2010. The...

Wisconsin 2008 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Michigan coast of WI in 2008. The data...

Delaware 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2005. The data...

Florida 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic, Gulf of Mexico in the summer of 2006....

Maryland 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2010. The data...

Georgia 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2006. The data...

Virginia 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of VA in 2005. The data types...

Louisiana 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2011. The data types collected...

Virginia 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of VA in 2010. The data types...

Illinois 2008 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along Lake Michigan in the summer of 2008. The data types...

Maryland 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2005. The data...

Maine 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2005. The data...

Oregon 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Pacific coast of OR in 2011. The data types...

Hawaii 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Pacific Coast, in the summer of 2007. The data...

Virginia 2009 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of VA in 2009. The data types...

Michigan 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the MI coast of Lake Superior in 2011. The data...

Minnesota 2009 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Superior coast of MN in 2009. The data...

Texas 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf coast of TX in 2010. The data types...

Oregon 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Pacific coast of OR in 2010. The data types...

Indiana 2008 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along Lake Michigan in the summer of 2008. The data types...

Massachusetts 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of MA in 2011. The data types...

Michigan 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the MI coasts of Lake Superior, Lake St. Clair and...

Florida 2009 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2009. The data types collected...

Louisiana 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2010. The data types collected...

Washington 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Pacific coast of WA in 2010. The data types...

Wisconsin 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Superior coast of WI in 2007. The data...

Washington 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Pacific coast of WA in 2011. The data types...

Michigan 2009 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the MI coast of Lake Superior in 2009. The data...

Delaware 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2010. The data...

Alabama 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2011. The data types collected...

Massachusetts 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic Coast of MA in 2010. The data types...

Massachusetts 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2005. The data...

Alabama 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2010. The data types collected...

Wisconsin 2009 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Superior coast of WI in 2009. The data...

Large Scale Landform Mapping Using Lidar DEM

Directory of Open Access Journals (Sweden)

Türkay Gökgöz

2015-08-01

Full Text Available In this study, LIDAR DEM data was used to obtain a primary landform map in accordance with a well-known methodology. This primary landform map was generalized using the Focal Statistics tool (Majority, considering the minimum area condition in cartographic generalization in order to obtain landform maps at 1:1000 and 1:5000 scales. Both the primary and the generalized landform maps were verified visually with hillshaded DEM and an orthophoto. As a result, these maps provide satisfactory visuals of the landforms. In order to show the effect of generalization, the area of each landform in both the primary and the generalized maps was computed. Consequently, landform maps at large scales could be obtained with the proposed methodology, including generalization using LIDAR DEM.

High resolution, topobathymetric LiDAR coastal zone characterization in Denmark

DEFF Research Database (Denmark)

Steinbacher, Frank; Baran, Ramona; Andersen, Mikkel S.

2016-01-01

Coastal and tidal environments are valuable ecosystems, which, however, are under pressure in many areas around the world due to globalization and/or climate change. Detailed mapping of these environments is required in order to manage the coastal zone in a sustainable way. However, historically...... locations with different environmental settings. We demonstrate the potential of using airborne topobathymetric LiDAR for seamless mapping of land-water transition zones in challenging coastal environments, e.g. in an environment with high water column turbidity and continuously varying water levels due...... these transition zones between land and water are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. The new generation of airborne topobathymetric light detection and ranging (LiDAR) potentially enables full-coverage and high...

Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

Science.gov (United States)

Montesano, P. M.; Cook, B. D.; Sun, G.; Simard, M.; Zhang, Z.; Nelson, R. F.; Ranson, K. J.; Lutchke, S.; Blair, J. B.

2012-01-01

The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized

Mississippi 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2004. The data...

Michigan 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the MI coasts of Lake Huron, Lake Erie and the St....

Florida 2003 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2003. The data...

Alabama 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2004. The data...

Pennsylvania 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Erie coast of PA in 2006. The data types...

Ohio 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Erie coast of OH in 2006. The data types...

Florida 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2004. The data...

Louisiana 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2006. The data...

Massachusetts 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of MA in the summer of 2007. The...

Louisiana 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico, in the summer of 2007. The data...

Alabama 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico, in the summer of 2007. The data...

Pennsylvania 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Lake Erie coast of PA in 2007. The data types...

Mississippi 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2007. The data...

Mississippi 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2011. The data...

Mississippi 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2010. The data...

2004 Alaska Lidar Mapping

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The data sets are generated using the OPTECH ALTM 70 kHz LIDAR system mounted onboard AeroMap's twin-engine Cessna 320 aircraft. Classified data sets such as this...

Derivation of Sky-View Factors from LIDAR Data

Science.gov (United States)

Kidd, Christopher; Chapman, Lee

2013-01-01

The use of Lidar (Light Detection and Ranging), an active light-emitting instrument, is becoming increasingly common for a range of potential applications. Its ability to provide fine resolution spatial and vertical resolution elevation data makes it ideal for a wide range of studies. This paper demonstrates the capability of Lidar data to measure sky view factors (SVF). The Lidar data is used to generate a spatial map of SVFs which are then compared against photographically-derived SVF at selected point locations. At each location three near-surface elevations measurements were taken and compared with collocated Lidar-derived estimated. It was found that there was generally good agreement between the two methodologies, although with decreasing SVF the Lidar-derived technique tended to overestimate the SVF: this can be attributed in part to the spatial resolution of the Lidar sampling. Nevertheless, airborne Lidar systems can map sky view factors over a large area easily, improving the utility of such data in atmospheric and meteorological models.

Aerosol backscatter measurements at 10.6 microns with airborne and ground-based CO2 Doppler lidars over the Colorado High Plains. I - Lidar intercomparison

Science.gov (United States)

Bowdle, David A.; Rothermel, Jeffry; Vaughan, J. Michael; Brown, Derek W.; Post, Madison J.

1991-01-01

An airborne continuous-wave (CW) focused CO2 Doppler lidar and a ground-based pulsed CO2 Doppler lidar were to obtain seven pairs of comparative measurements of tropospheric aerosol backscatter profiles at 10.6-micron wavelength, near Denver, Colorado, during a 20-day period in July 1982. In regions of uniform backscatter, the two lidars show good agreement, with differences usually less than about 50 percent near 8-km altitude and less than a factor of 2 or 3 elsewhere but with the pulsed lidar often lower than the CW lidar. Near sharp backscatter gradients, the two lidars show poorer agreement, with the pulsed lidar usually higher than the CW lidar. Most discrepancies arise from a combination of atmospheric factors and instrument factors, particularly small-scale areal and temporal backscatter heterogeneity above the planetary boundary layer, unusual large-scale vertical backscatter structure in the upper troposphere and lower stratosphere, and differences in the spatial resolution, detection threshold, and noise estimation for the two lidars.

Forest biomass mapping from fusion of GEDI Lidar data and TanDEM-X InSAR data

Science.gov (United States)

Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.

2017-12-01

Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

Science.gov (United States)

Veronika Leitold; Michael Keller; Douglas C Morton; Bruce D Cook; Yosio E Shimabukuro

2015-01-01

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas...

Advances in High Energy Solid-State Pulsed 2-Micron Lidar Development for Ground and Airborne Wind, Water Vapor and CO2 Measurements

Science.gov (United States)

Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Refaat, Tamer; Kavaya, Michael J.; Remus, Ruben

2015-01-01

NASA Langley Research Center has a long history of developing 2-micron lasers. From fundamental spectroscopy research, theoretical prediction of new materials, laser demonstration and engineering of lidar systems, it has been a very successful program spanning around two decades. Successful development of 2-micron lasers has led to development of a state-of-the-art compact lidar transceiver for a pulsed coherent Doppler lidar system for wind measurement with an unprecedented laser pulse energy of 250 millijoules in a rugged package. This high pulse energy is produced by a Ho:Tm:LuLiF laser with an optical amplifier. While the lidar is meant for use as an airborne instrument, ground-based tests were carried out to characterize performance of the lidar. Atmospheric measurements will be presented, showing the lidar's capability for wind measurement in the atmospheric boundary layer and free troposphere. Lidar wind measurements are compared to a balloon sonde, showing good agreement between the two sensors. Similar architecture has been used to develop a high energy, Ho:Tm:YLF double-pulsed 2-micron Integrated Differential Absorption Lidar (IPDA) instrument based on direct detection technique that provides atmospheric column CO2 measurements. This instrument has been successfully used to measure atmospheric CO2 column density initially from a ground mobile lidar trailer, and then it was integrated on B-200 plane and 20 hours of flight measurement were made from an altitude ranging 1500 meters to 8000 meters. These measurements were compared to in-situ measurements and National Oceanic and Atmospheric Administration (NOAA) airborne flask measurement to derive the dry mixing ratio of the column CO2 by reflecting the signal by various reflecting surfaces such as land, vegetation, ocean surface, snow and sand. The lidar measurements when compared showed a very agreement with in-situ and airborne flask measurement. NASA Langley Research Center is currently developing a

2001 NCFMP Lidar: Phase 1B (Cape Fear and Lumber River Basins)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This airborne LiDAR terrain mapping data was acquired in the spring of 2001. The data were collected for the floodplain mapping program for the state of North...

New York 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Niagara River and Lake Erie and Lake Ontario...

Assessment of the CALIPSO Lidar 532 nm attenuated backscatter calibration using the NASA LaRC airborne High Spectral Resolution Lidar

Directory of Open Access Journals (Sweden)

R. R. Rogers

2011-02-01

Full Text Available The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO spacecraft has provided global, high-resolution vertical profiles of aerosols and clouds since it became operational on 13 June 2006. On 14 June 2006, the NASA Langley Research Center (LaRC High Spectral Resolution Lidar (HSRL was deployed aboard the NASA Langley B-200 aircraft for the first of a series of 86 underflights of the CALIPSO satellite to provide validation measurements for the CALIOP data products. To better assess the range of conditions under which CALIOP data products are produced, these validation flights were conducted under both daytime and nighttime lighting conditions, in multiple seasons, and over a large range of latitudes and aerosol and cloud conditions. This paper presents a quantitative assessment of the CALIOP 532 nm calibration (through the 532 nm total attenuated backscatter using internally calibrated airborne HSRL underflight data and is the most extensive study of CALIOP 532 nm calibration. Results show that HSRL and CALIOP 532 nm total attenuated backscatter agree on average within 2.7% ± 2.1% (CALIOP lower at night and within 2.9% ± 3.9% (CALIOP lower during the day, demonstrating the accuracy of the CALIOP 532 nm calibration algorithms. Additionally, comparisons with HSRL show consistency of the CALIOP calibration before and after the laser switch in 2009 as well as improvements in the daytime version 3.01 calibration scheme compared with the version 2 calibration scheme. Potential biases and uncertainties in the methodology relevant to validating satellite lidar measurements with an airborne lidar system are discussed and found to be less than 4.5% ± 3.2% for this validation effort with HSRL. Results from this study are also compared with prior assessments of the CALIOP 532 nm attenuated backscatter calibration.

Airborne 2-Micron Double-Pulsed Integrated Path Differential Absorption Lidar for Column CO2 Measurement

Science.gov (United States)

Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Refaat, Tamer F.; Remus, Ruben G.; Fay, James J.; Reithmaier, Karl

2014-01-01

Double-pulse 2-micron lasers have been demonstrated with energy as high as 600 millijouls and up to 10 Hz repetition rate. The two laser pulses are separated by 200 microseconds and can be tuned and locked separately. Applying double-pulse laser in DIAL system enhances the CO2 measurement capability by increasing the overlap of the sampled volume between the on-line and off-line. To avoid detection complicity, integrated path differential absorption (IPDA) lidar provides higher signal-to-noise ratio measurement compared to conventional range-resolved DIAL. Rather than weak atmospheric scattering returns, IPDA rely on the much stronger hard target returns that is best suited for airborne platforms. In addition, the IPDA technique measures the total integrated column content from the instrument to the hard target but with weighting that can be tuned by the transmitter. Therefore, the transmitter could be tuned to weight the column measurement to the surface for optimum CO2 interaction studies or up to the free troposphere for optimum transport studies. Currently, NASA LaRC is developing and integrating a double-Pulsed 2-micron direct detection IPDA lidar for CO2 column measurement from an airborne platform. The presentation will describe the development of the 2-micron IPDA lidar system and present the airborne measurement of column CO2 and will compare to in-situ measurement for various ground target of different reflectivity.

Geological Mapping of Sabah, Malaysia, Using Airborne Gravity Survey

DEFF Research Database (Denmark)

Fauzi Nordin, Ahmad; Jamil, Hassan; Noor Isa, Mohd

2016-01-01

Airborne gravimetry is an effective tool for mapping local gravity fields using a combination of airborne sensors, aircraft and positioning systems. It is suitable for gravity surveys over difficult terrains and areas mixed with land and ocean. This paper describes the geological mapping of Sabah...... using airborne gravity surveys. Airborne gravity data over land areas of Sabah has been combined with the marine airborne gravity data to provide a seamless land-to-sea gravity field coverage in order to produce the geological mapping. Free-air and Bouguer anomaly maps (density 2.67 g/cm3) have been...... derived from the airborne data both as simple ad-hoc plots (at aircraft altitude), and as final plots from the downward continued airborne data, processed as part of the geoids determination. Data are gridded at 0.025 degree spacing which is about 2.7 km and the data resolution of the filtered airborne...

North Carolina 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NC in 2010. The data types...

North Carolina 2008 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NC in 2008. The data types...

North Carolina 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NC in 2004. The data types...

North Carolina 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NC in 2005. The data types...

New York 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NY in 2010. The data types...

New York 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NY in 2005. The data types...

New Jersey 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NJ in 2005. The data types...

South Carolina 2006 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of SC in 2006. The data types...

New Hampshire 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NH in 2005. The data types...

New Hampshire 2011 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NH in 2011. The data types...

Rhode Island 2005 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of RI in 2005. The data types...

South Carolina 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of SC in 2010. The data types...

New Hampshire 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NH in 2010. The data types...

Rhode Island 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of RI in 2007. The data types...

North Carolina 2009 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NC in 2009. The data types...

Rhode Island 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of RI in 2010. The data types...

New Jersey 2010 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast of NJ in 2010. The data types...

2006 Federal Emergency Management Agency (FEMA) Lidar: Nueces County, Texas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Spectrum Mapping, LLC was tasked by MAPVI - URS Corporation, Albuquergue, to provide airborne Light Detection and Ranging (Lidar) of approximately 620 square miles...

Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

Science.gov (United States)

Gu, Huan

Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our

Airborne Lidar for Simultaneous Measurement of Column CO2 and Water Vapor in the Atmosphere

Science.gov (United States)

Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Antill, Charles W.; Remus, Ruben; Yu, Jirong

2016-01-01

The 2-micron wavelength region is suitable for atmospheric carbon dioxide (CO2) measurements due to the existence of distinct absorption feathers for the gas at this particular wavelength. For more than 20 years, researchers at NASA Langley Research Center (LaRC) have developed several high-energy and high repetition rate 2-micron pulsed lasers. This paper will provide status and details of an airborne 2-micron triple-pulse integrated path differential absorption (IPDA) lidar. The development of this active optical remote sensing IPDA instrument is targeted for measuring both CO2 and water vapor (H2O) in the atmosphere from an airborne platform. This presentation will focus on the advancement of the 2-micron triple-pulse IPDA lidar development. Updates on the state-of-the-art triple-pulse laser transmitter will be presented including the status of seed laser locking, wavelength control, receiver telescope, detection system and data acquisition. Future plans for the IPDA lidar system for ground integration, testing and flight validation will also be presented.

Irish Ice Sheet dynamics during deglaciation of the central Irish Midlands: Evidence of ice streaming and surging from airborne LiDAR

Science.gov (United States)

Delaney, Catherine A.; McCarron, Stephen; Davis, Stephen

2018-04-01

High resolution digital terrain models (DTMs) generated from airborne LiDAR data and supplemented by field evidence are used to map glacial landform assemblages dating from the last glaciation (Midlandian glaciation; OI stages 2-3) in the central Irish Midlands. The DTMs reveal previously unrecognised low-amplitude landforms, including crevasse-squeeze ridges and mega-scale glacial lineations overprinted by conduit fills leading to ice-marginal subaqueous deposits. We interpret this landform assemblage as evidence for surging behaviour during ice recession. The data indicate that two separate phases of accelerated ice flow were followed by ice sheet stagnation during overall deglaciation. The second surge event was followed by a subglacial outburst flood, forming an intricate esker and crevasse-fill network. The data provide the first clear evidence that ice flow direction was eastward along the eastern watershed of the Shannon River basin, at odds with previous models, and raise the possibility that an ice stream existed in this area. Our work demonstrates the potential for airborne LiDAR surveys to produce detailed paleoglaciological reconstructions and to enhance our understanding of complex palaeo-ice sheet dynamics.

Mapping Ross Ice Shelf with ROSETTA-Ice airborne laser altimetry

Science.gov (United States)

Becker, M. K.; Fricker, H. A.; Padman, L.; Bell, R. E.; Siegfried, M. R.; Dieck, C. C. M.

2017-12-01

The Ross Ocean and ice Shelf Environment and Tectonic setting Through Aerogeophysical surveys and modeling (ROSETTA-Ice) project combines airborne glaciological, geological, and oceanographic observations to enhance our understanding of the history and dynamics of the large ( 500,000 square km) Ross Ice Shelf (RIS). Here, we focus on the Light Detection And Ranging (LiDAR) data collected in 2015 and 2016. This data set represents a significant advance in resolution: Whereas the last attempt to systematically map RIS (the surface-based RIGGS program in the 1970s) was at 55 km grid spacing, the ROSETTA-Ice grid has 10-20 km line spacing and much higher along-track resolution. We discuss two different strategies for processing the raw LiDAR data: one that requires proprietary software (Riegl's RiPROCESS package), and one that employs open-source programs and libraries. With the processed elevation data, we are able to resolve fine-scale ice-shelf features such as the "rampart-moat" ice-front morphology, which has previously been observed on and modeled for icebergs. This feature is also visible in the ROSETTA-Ice shallow-ice radar data; comparing the laser data with radargrams provides insight into the processes leading to their formation. Near-surface firn state and total firn air content can also be investigated through combined analysis of laser altimetry and radar data. By performing similar analyses with data from the radar altimeter aboard CryoSat-2, we demonstrate the utility of the ROSETTA-Ice LiDAR data set in satellite validation efforts. The incorporation of the LiDAR data from the third and final field season (December 2017) will allow us to construct a DEM and an ice thickness map of RIS for the austral summers of 2015-2017. These products will be used to validate and extend observations of height changes from satellite radar and laser altimetry, as well as to update regional models of ocean circulation and ice dynamics.

New York 2011 Lidar Coverage, USACE National Coastal Mapping Proram

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the NY coasts of Lake Erie and Lake Ontario in 2011....

Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles

Science.gov (United States)

Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Kittaka, C.; Vaughn, M. A.; Remer, L. A.

2010-01-01

We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lidar ratio. The backscatter data were acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The HSRL also simultaneously measures aerosol extinction coefficients independently using the high spectral resolution lidar technique, thereby providing an ideal data set for evaluating the retrieval. We retrieve aerosol extinction profiles from both HSRL and CALIOP attenuated backscatter data constrained with HSRL, Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer column AOT. The resulting profiles are compared with the aerosol extinction measured by HSRL. Retrievals are limited to cases where the column aerosol thickness is greater than 0.2 over land and 0.15 over water. In the case of large AOT, the results using the Aqua MODIS constraint over water are poorer than Aqua MODIS over land or Terra MODIS. The poorer results relate to an apparent bias in Aqua MODIS AOT over water observed in August 2007. This apparent bias is still under investigation. Finally, aerosol extinction coefficients are derived from CALIPSO backscatter data using AOT from Aqua MODIS for 28 profiles over land and 9 over water. They agree with coincident measurements by the airborne HSRL to within +/-0.016/km +/- 20% for at least two-thirds of land points and within +/-0.028/km +/- 20% for at least two-thirds of ocean points.

AUTOMATED RECONSTRUCTION OF WALLS FROM AIRBORNE LIDAR DATA FOR COMPLETE 3D BUILDING MODELLING

Directory of Open Access Journals (Sweden)

Y. He

2012-07-01

Full Text Available Automated 3D building model generation continues to attract research interests in photogrammetry and computer vision. Airborne Light Detection and Ranging (LIDAR data with increasing point density and accuracy has been recognized as a valuable source for automated 3D building reconstruction. While considerable achievements have been made in roof extraction, limited research has been carried out in modelling and reconstruction of walls, which constitute important components of a full building model. Low point density and irregular point distribution of LIDAR observations on vertical walls render this task complex. This paper develops a novel approach for wall reconstruction from airborne LIDAR data. The developed method commences with point cloud segmentation using a region growing approach. Seed points for planar segments are selected through principle component analysis, and points in the neighbourhood are collected and examined to form planar segments. Afterwards, segment-based classification is performed to identify roofs, walls and planar ground surfaces. For walls with sparse LIDAR observations, a search is conducted in the neighbourhood of each individual roof segment to collect wall points, and the walls are then reconstructed using geometrical and topological constraints. Finally, walls which were not illuminated by the LIDAR sensor are determined via both reconstructed roof data and neighbouring walls. This leads to the generation of topologically consistent and geometrically accurate and complete 3D building models. Experiments have been conducted in two test sites in the Netherlands and Australia to evaluate the performance of the proposed method. Results show that planar segments can be reliably extracted in the two reported test sites, which have different point density, and the building walls can be correctly reconstructed if the walls are illuminated by the LIDAR sensor.

Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry

Directory of Open Access Journals (Sweden)

Zhigang Pan

2015-04-01

Full Text Available We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.

Airborne geophysical radon hazard mapping

International Nuclear Information System (INIS)

Walker, P.

1993-01-01

Shales containing uranium pose a radon health hazard even when covered by several meters of overburden. Such an alum shale in southern Norway has been mapped with a joint helicopter borne electromagnetic (HEM) and radiometric survey. Results are compared with ground spectrometer, radon emanometer and radon gas measurements in dwellings, and a model to predict radon gas concentrations from the airborne data is developed. Since the shale is conductive, combining the HEM data with the radiometric channel allows the shale to be mapped with greater reliability than if the radiometric channel were used alone. Radiometrically more active areas which do not pose a radon gas hazard can thus be separated from the shales which do. The ground follow-up work consisted of spectrometer and radon emanometer measurements over a uranium anomaly coinciding with a conductor. The correlation between the airborne uranium channel, the ground uranium channel and emanometry is extremely good, indicating that airborne geophysics can, in this case, be used to predict areas having a high radon potential. Contingency tables comparing both radon exhalation and concentration in dwellings with the airborne uranium data show a strong relationship exists between exhalation and the airborne data and while a relationship between concentration and the airborne data is present, but weaker

MULTISPECTRAL AIRBORNE LASER SCANNING - A NEW TREND IN THE DEVELOPMENT OF LIDAR TECHNOLOGY

Directory of Open Access Journals (Sweden)

Bakuła Krzysztof

2015-12-01

Full Text Available Airborne laser scanning (ALS is the one of the most accurate remote sensing techniques for data acquisition where the terrain and its coverage is concerned. Modern scanners have been able to scan in two or more channels (frequencies of the laser recently. This gives the rise to the possibility of obtaining diverse information about an area with the different spectral properties of objects. The paper presents an example of a multispectral ALS system - Titan by Optech - with the possibility of data including the analysis of digital elevation models accuracy and data density. As a result of the study, the high relative accuracy of LiDAR acquisition in three spectral bands was proven. The mean differences between digital terrain models (DTMs were less than 0.03 m. The data density analysis showed the influence of the laser wavelength. The points clouds that were tested had average densities of 25, 23 and 20 points per square metre respectively for green (G, near-infrared (NIR and shortwave-infrared (SWIR lasers. In this paper, the possibility of the generation of colour composites using orthoimages of laser intensity reflectance and its classification capabilities using data from airborne multispectral laser scanning for land cover mapping are also discussed and compared with conventional photogrammetric techniques.

2001 NCFMP Lidar: Phase 1A (Neuse, Pasquotank, Tar-Pamlico, White Oak River Basins)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This airborne LiDAR terrain mapping data was acquired January through March 2001. The data were collected for the floodplain mapping program for the state of North...

Automated method for measuring the extent of selective logging damage with airborne LiDAR data

Science.gov (United States)

Melendy, L.; Hagen, S. C.; Sullivan, F. B.; Pearson, T. R. H.; Walker, S. M.; Ellis, P.; Kustiyo; Sambodo, Ari Katmoko; Roswintiarti, O.; Hanson, M. A.; Klassen, A. W.; Palace, M. W.; Braswell, B. H.; Delgado, G. M.

2018-05-01

Selective logging has an impact on the global carbon cycle, as well as on the forest micro-climate, and longer-term changes in erosion, soil and nutrient cycling, and fire susceptibility. Our ability to quantify these impacts is dependent on methods and tools that accurately identify the extent and features of logging activity. LiDAR-based measurements of these features offers significant promise. Here, we present a set of algorithms for automated detection and mapping of critical features associated with logging - roads/decks, skid trails, and gaps - using commercial airborne LiDAR data as input. The automated algorithm was applied to commercial LiDAR data collected over two logging concessions in Kalimantan, Indonesia in 2014. The algorithm results were compared to measurements of the logging features collected in the field soon after logging was complete. The automated algorithm-mapped road/deck and skid trail features match closely with features measured in the field, with agreement levels ranging from 69% to 99% when adjusting for GPS location error. The algorithm performed most poorly with gaps, which, by their nature, are variable due to the unpredictable impact of tree fall versus the linear and regular features directly created by mechanical means. Overall, the automated algorithm performs well and offers significant promise as a generalizable tool useful to efficiently and accurately capture the effects of selective logging, including the potential to distinguish reduced impact logging from conventional logging.

Column carbon dioxide and water vapor measurements by an airborne triple-pulse integrated path differential absorption lidar: novel lidar technologies and techniques with path to space

Science.gov (United States)

Singh, U. N.; Petros, M.; Refaat, T. F.; Yu, J.; Ismail, S.

2017-09-01

The 2-micron wavelength region is suitable for atmospheric carbon dioxide (CO2) measurements due to the existence of distinct absorption features for the gas at this wavelength region [1]. For more than 20 years, researchers at NASA Langley Research Center (LaRC) have developed several high-energy and high repetition rate 2-micron pulsed lasers [2]. Currently, LaRC team is engaged in designing, developing and demonstrating a triple-pulsed 2-micron direct detection Integrated Path Differential Absorption (IPDA) lidar to measure the weighted-average column dry-air mixing ratios of carbon dioxide (XCO2) and water vapor (XH2O) from an airborne platform [1, 3-5]. This novel technique allows measurement of the two most dominant greenhouse gases, simultaneously and independently, using a single instrument. This paper will provide status and details of the development of this airborne 2-micron triple-pulse IPDA lidar. The presented work will focus on the advancement of critical IPDA lidar components. Updates on the state-of-the-art triple-pulse laser transmitter will be presented including the status of seed laser locking, wavelength control, receiver and detector upgrades, laser packaging and lidar integration. Future plans for IPDA lidar ground integration, testing and flight validation will also be discussed. This work enables new Earth observation measurements, while reducing risk, cost, size, volume, mass and development time of required instruments.

Florida 2006 Post Wilma Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic in the summer of 2006. The data types...

Massachusetts 2005 and 2007 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Atlantic coast in the summer of 2005 and 2007....

Alabama 2009 Post Gustav Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2009. The data types collected...

Louisiana 2009 Post Ike Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2009. The data types collected...

Louisiana 2009 Post Gustav Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in 2009. The data types collected...

Bayou Portage, Mississippi 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2004. The data...

Gaillard Island, AL 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2004. The data...

Florida 2004 Post Ivan Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2004. The data...

Bayou Cadet, Mississippi 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2004. The data...

Florida 2005 Post Dennis Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2005. The data...

Deer Island, Mississippi 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2004. The data...

Alabama 2005 Post Dennis Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2005. The data...

Alabama 2005 Post Katrina Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2005. The data...

Florida 2005 Post Katrina Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2005. The data...

Looe Key, Florida 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2004. The data...

Mississippi 2009 Post Gustav Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2009. The data...

Utilizing The Synergy of Airborne Backscatter Lidar and In-Situ Measurements for Evaluating CALIPSO

Directory of Open Access Journals (Sweden)

Tsekeri Alexandra

2016-01-01

Full Text Available Airborne campaigns dedicated to satellite validation are crucial for the effective global aerosol monitoring. CALIPSO is currently the only active remote sensing satellite mission, acquiring the vertical profiles of the aerosol backscatter and extinction coefficients. Here we present a method for CALIPSO evaluation from combining lidar and in-situ airborne measurements. The limitations of the method have to do mainly with the in-situ instrumentation capabilities and the hydration modelling. We also discuss the future implementation of our method in the ICE-D campaign (Cape Verde, August 2015.

Fusion of NASA Airborne Snow Observatory (ASO Lidar Time Series over Mountain Forest Landscapes

Directory of Open Access Journals (Sweden)

António Ferraz

2018-01-01

Full Text Available Mountain ecosystems are among the most fragile environments on Earth. The availability of timely updated information on forest 3D structure would improve our understanding of the dynamic and impact of recent disturbance and regeneration events including fire, insect damage, and drought. Airborne lidar is a critical tool for monitoring forest change at high resolution but it has been little used for this purpose due to the scarcity of long-term time-series of measurements over a common region. Here, we investigate the reliability of on-going, multi-year lidar observations from the NASA-JPL Airborne Snow Observatory (ASO to characterize forest 3D structure at a fine spatial scale. In this study, weekly ASO measurements collected at ~1 pt/m2, primarily acquired to quantify snow volume and dynamics, are coherently merged to produce high-resolution point clouds ( ~ 12 pt/m2 that better describe forest structure. The merging methodology addresses the spatial bias in multi-temporal data due to uncertainties in platform trajectory and motion by collecting tie objects from isolated tree crown apexes in the lidar data. The tie objects locations are assigned to the centroid of multi-temporal lidar points to fuse and optimize the location of multiple measurements without the need for ancillary data or GPS control points. We apply the methodology to ASO lidar acquisitions over the Tuolumne River Basin in the Sierra Nevada, California, during the 2014 snow monitoring campaign and provide assessment of the fidelity of the fused point clouds for forest mountain ecosystem studies. The availability of ASO measurements that currently span 2013–2017 enable annual forest monitoring of important vegetated ecosystems that currently face ecological threads of great significance such as the Sierra Nevada (California and Olympic National Forest (Washington.

Assessing stream bank condition using airborne LiDAR and high spatial resolution image data in temperate semirural areas in Victoria, Australia

Science.gov (United States)

Johansen, Kasper; Grove, James; Denham, Robert; Phinn, Stuart

2013-01-01

Stream bank condition is an important physical form indicator for streams related to the environmental condition of riparian corridors. This research developed and applied an approach for mapping bank condition from airborne light detection and ranging (LiDAR) and high-spatial resolution optical image data in a temperate forest/woodland/urban environment. Field observations of bank condition were related to LiDAR and optical image-derived variables, including bank slope, plant projective cover, bank-full width, valley confinement, bank height, bank top crenulation, and ground vegetation cover. Image-based variables, showing correlation with the field measurements of stream bank condition, were used as input to a cumulative logistic regression model to estimate and map bank condition. The highest correlation was achieved between field-assessed bank condition and image-derived average bank slope (R2=0.60, n=41), ground vegetation cover (R=0.43, n=41), bank width/height ratio (R=0.41, n=41), and valley confinement (producer's accuracy=100%, n=9). Cross-validation showed an average misclassification error of 0.95 from an ordinal scale from 0 to 4 using the developed model. This approach was developed to support the remotely sensed mapping of stream bank condition for 26,000 km of streams in Victoria, Australia, from 2010 to 2012.

LiDAR Mapping of Earthquake Uplifted Paleo-shorelines, Southern Wairarapa Coast, North Island, New Zealand

Science.gov (United States)

Valenciano, J.; Angenent, J.; Marshall, J. S.; Clark, K.; Litchfield, N. J.

2017-12-01

The Hikurangi subduction margin along the east coast of the North Island, New Zealand accommodates oblique convergence of the Pacific Plate westward beneath the Australian plate at 45 mm/yr. Pronounced forearc uplift occurs at the southern end of the margin along the Wairarapa coast, onshore of the subducting Hikurangi plateau. Along a narrow coastal lowland, a series of uplifted Holocene marine terraces and beach ridges preserve a geologic record of prehistoric coseismic uplift events. In January 2017, we participated in the Research Experience for Undergraduates (REU) program of the NSF SHIRE Project (Subduction at Hikurangi Integrated Research Experiment). We visited multiple coastal sites for reconnaissance fieldwork to select locations for future in-depth study. For the coastline between Flat Point and Te Kaukau Point, we used airborne LiDAR data provided by Land Information New Zealand (LINZ) to create ArcGIS digital terrain models for mapping and correlating uplifted paleo-shorelines. Terrace elevations derived from the LiDAR data were calibrated through the use of Real Time Kinematic (RTK) GPS surveying at one field site (Glenburn Station). Prior field mapping and radiocarbon dating results (Berryman et al., 2001; Litchfield and Clark, 2015) were used to guide our LiDAR mapping efforts. The resultant maps show between four and seven uplifted terraces and associated beach ridges along this coastal segment. At some sites, terrace mapping and lateral correlation are impeded by discontinuous exposures and the presence of landslide debris, alluvial fan deposits, and sand dunes. Tectonic uplift along the southern Hikurangi margin is generated by a complex interaction between deep megathrust slip and shallow upper-plate faulting. Each uplifted Holocene paleo-shoreline is interpreted to represent a single coseismic uplift event. Continued mapping, surveying, and age dating may help differentiate between very large margin-wide megathrust earthquakes (M8.0-9.0+) and

2004 Harrison County, Mississippi Lidar Mapping

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This metadata record describes the topographic mapping of Harrison County, Mississippi in March of 2004. Products generated include lidar point clouds in .LAS format...

Linking rainforest ecophysiology and microclimate through fusion of airborne LiDAR and hyperspectral imagery

Science.gov (United States)

Eben N. Broadbent; Angélica M. Almeyda Zambrano; Gregory P. Asner; Christopher B. Field; Brad E. Rosenheim; Ty Kennedy-Bowdoin; David E. Knapp; David Burke; Christian Giardina; Susan Cordell

2014-01-01

We develop and validate a high-resolution three-dimensional model of light and air temperature for a tropical forest interior in Hawaii along an elevation gradient varying greatly in structure but maintaining a consistent species composition. Our microclimate models integrate high-resolution airborne waveform light detection and ranging data (LiDAR) and hyperspectral...

Detecting Multi-layered Forest Stands Using High Density Airborne LiDAR Data. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

OpenAIRE

Schultz, Alfred; Mund, Jan-Peter; Körner, Michael; Wilke, Robert

2016-01-01

Since two decades, the use of terrestrial laser scanning (TLS) and Airborne Light Detection and Ranging (LIDAR) has become very prominent in analysing 3D forest structures (AKAY et al. 2009). The potential of full waveform analysis of high density Airborne LiDAR data (ALS) for the detection and structural analysis of multi-layered forest stands is not yet well investigated (JASKIERNIAK et al. 2011), although ALS data provide exact information on tree heights of multi-layered forest stands usi...

A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

Directory of Open Access Journals (Sweden)

Bin Wu

2017-01-01

Full Text Available 3D building model reconstruction is of great importance for environmental and urban applications. Airborne light detection and ranging (LiDAR is a very useful data source for acquiring detailed geometric and topological information of building objects. In this study, we employed a graph-based method based on hierarchical structure analysis of building contours derived from LiDAR data to reconstruct urban building models. The proposed approach first uses a graph theory-based localized contour tree method to represent the topological structure of buildings, then separates the buildings into different parts by analyzing their topological relationships, and finally reconstructs the building model by integrating all the individual models established through the bipartite graph matching process. Our approach provides a more complete topological and geometrical description of building contours than existing approaches. We evaluated the proposed method by applying it to the Lujiazui region in Shanghai, China, a complex and large urban scene with various types of buildings. The results revealed that complex buildings could be reconstructed successfully with a mean modeling error of 0.32 m. Our proposed method offers a promising solution for 3D building model reconstruction from airborne LiDAR point clouds.

Ground-Truthing of Airborne LiDAR Using RTK-GPS Surveyed Data in Coastal Louisiana's Wetlands

Science.gov (United States)

Lauve, R. M.; Alizad, K.; Hagen, S. C.

2017-12-01

Airborne LiDAR (Light Detection and Ranging) data are used by engineers and scientists to create bare earth digital elevation models (DEM), which are essential to modeling complex coastal, ecological, and hydrological systems. However, acquiring accurate bare earth elevations in coastal wetlands is difficult due to the density of marsh grasses that prevent the sensors reflection off the true ground surface. Previous work by Medeiros et al. [2015] developed a technique to assess LiDAR error and adjust elevations according to marsh vegetation density and index. The aim of this study is the collection of ground truth points and the investigation on the range of potential errors found in existing LiDAR datasets within coastal Louisiana's wetlands. Survey grids were mapped out in an area dominated by Spartina alterniflora and a survey-grade Trimble Real Time Kinematic (RTK) GPS device was employed to measure bare earth ground elevations in the marsh system adjacent to Terrebonne Bay, LA. Elevations were obtained for 20 meter-spaced surveyed grid points and were used to generate a DEM. The comparison between LiDAR derived and surveyed data DEMs yield an average difference of 23 cm with a maximum difference of 68 cm. Considering the local tidal range of 45 cm, these differences can introduce substantial error when the DEM is used for ecological modeling [Alizad et al., 2016]. Results from this study will be further analyzed and implemented in order to adjust LiDAR-derived DEMs closer to their true elevation across Louisiana's coastal wetlands. ReferencesAlizad, K., S. C. Hagen, J. T. Morris, S. C. Medeiros, M. V. Bilskie, and J. F. Weishampel (2016), Coastal wetland response to sea-level rise in a fluvial estuarine system, Earth's Future, 4(11), 483-497, 10.1002/2016EF000385. Medeiros, S., S. Hagen, J. Weishampel, and J. Angelo (2015), Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated Aboveground Biomass Density, Remote Sensing, 7

Mississippi 2005 Post Hurricane Katrina Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2005 after...

Texas 2009 Post Hurricane Ike Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf coast of TX in 2009. The data types...

Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico.

Science.gov (United States)

Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane

2018-02-21

Information on the spatial distribution of aboveground biomass (AGB) over large areas is needed for understanding and managing processes involved in the carbon cycle and supporting international policies for climate change mitigation and adaption. Furthermore, these products provide important baseline data for the development of sustainable management strategies to local stakeholders. The use of remote sensing data can provide spatially explicit information of AGB from local to global scales. In this study, we mapped national Mexican forest AGB using satellite remote sensing data and a machine learning approach. We modelled AGB using two scenarios: (1) extensive national forest inventory (NFI), and (2) airborne Light Detection and Ranging (LiDAR) as reference data. Finally, we propagated uncertainties from field measurements to LiDAR-derived AGB and to the national wall-to-wall forest AGB map. The estimated AGB maps (NFI- and LiDAR-calibrated) showed similar goodness-of-fit statistics (R 2 , Root Mean Square Error (RMSE)) at three different scales compared to the independent validation data set. We observed different spatial patterns of AGB in tropical dense forests, where no or limited number of NFI data were available, with higher AGB values in the LiDAR-calibrated map. We estimated much higher uncertainties in the AGB maps based on two-stage up-scaling method (i.e., from field measurements to LiDAR and from LiDAR-based estimates to satellite imagery) compared to the traditional field to satellite up-scaling. By removing LiDAR-based AGB pixels with high uncertainties, it was possible to estimate national forest AGB with similar uncertainties as calibrated with NFI data only. Since LiDAR data can be acquired much faster and for much larger areas compared to field inventory data, LiDAR is attractive for repetitive large scale AGB mapping. In this study, we showed that two-stage up-scaling methods for AGB estimation over large areas need to be analyzed and validated

HgCdTe Avalanche Photodiode Detectors for Airborne and Spaceborne Lidar at Infrared Wavelengths

Science.gov (United States)

Sun, Xiaoli; Abshire, James B.; Beck, Jeffrey D.; Mitra, Pradip; Reiff, Kirk; Yang, Guangning

2017-01-01

We report results from characterizing the HgCdTe avalanche photodiode (APD) sensorchip assemblies (SCA) developed for lidar at infrared wavelength using the high density vertically integrated photodiodes (HDVIP) technique. These devices demonstrated high quantum efficiency, typically greater than 90 between 0.8 micrometers and the cut-off wavelength, greater than 600 APD gain, near unity excess noise factor, 6-10 MHz electrical bandwidth and less than 0.5 fW/Hz(exp.1/2) noise equivalent power (NEP). The detectors provide linear analog output with a dynamic range of 2-3 orders of magnitude at a fixed APD gain without averaging, and over 5 orders of magnitude by adjusting the APD and preamplifier gain settings. They have been successfully used in airborne CO2 and CH4 integrated path differential absorption (IPDA) lidar as a precursor for space lidar applications.

Drought-induced changes in Amazon forest structure from repeat airborne lidar

Science.gov (United States)

Morton, D. C.; Leitold, V.; Longo, M.; Keller, M.; dos-Santos, M. N.; Scaranello, M. A., Sr.

2017-12-01

Drought events in tropical forests, including the 2015-2016 El Niño, may reduce net primary productivity and increase canopy tree mortality, thereby altering the short and long-term net carbon balance of tropical forests. Given the broad extent of drought impacts, forest inventory plots or eddy flux towers may not capture regional variability in forest response to drought. Here, we analyzed repeat airborne lidar data to evaluate canopy turnover from branch and tree fall before (2013-2014) and during (2014-2016) the recent El Niño drought in the eastern and central Brazilian Amazon. Coincident field surveys for a 16-ha subset of the lidar coverage provided complementary information to classify turnover areas by mechanism (branch, multiple branch, tree fall, multiple tree fall) and estimate the total coarse woody debris volume from canopy and understory tree mortality. Annualized rates of canopy turnover increased by 50%, on average, during the drought period in both intact and fragmented forests near Santarém, Pará. Turnover increased uniformly across all size classes, and there was limited evidence that taller trees contributed a greater proportion of turnover events in any size class in 2014-2016 compared to 2013-2014. This short-term increase in canopy turnover differs from findings in multi-year rainfall exclusion experiments that large trees were more sensitive to drought impacts. Field measurements confirmed the separability of the smallest (single branch) and largest damage classes (multiple tree falls), but single tree and multiple branch fall events generated similar coarse woody debris production and lidar-derived changes in canopy volume. Large-scale sampling possible with repeat airborne lidar data also captured strong local and regional gradients in canopy turnover. Differences in slope partially explained the north-south gradient in canopy turnover dynamics near Santarém, with larger increases in turnover on flatter terrain. Regional variability

Little Dauphin Island, AL 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2004. The data...

Louisiana 2005 Post Hurricane Katrina Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2005. The data...

Assessing Accuracy in Varying LIDAR Data Point Densities in Digital Elevation Maps

National Research Council Canada - National Science Library

Anderson, Brian C

2008-01-01

... analysis when comparing the different DEMs built by randomly selecting 90%, 66%, 50%, 30%, 10%, 5%, 3%, 1%, 0.5%, 0.3%, 0.05%, 0.03% and 0.01% of the data from an airborne Lidar collection from Honduras in 2008...

Progress on Development of an Airborne Two-Micron IPDA Lidar for Water Vapor and Carbon Dioxide Column Measurements

Science.gov (United States)

Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Yu, Jirong; Antill, Charles W.; Taylor, Bryant D.; Bowen, Stephen C.; Welters, Angela M.; Remus, Ruben G.; Wong, Teh-Hwa;

Analysis of airborne LiDAR surveys to quantify the characteristic morphologies of northern forested wetlands

Science.gov (United States)

Murray C. Richardson; Carl P. J. Mitchell; Brian A. Branfireun; Randall K. Kolka

2010-01-01

A new technique for quantifying the geomorphic form of northern forested wetlands from airborne LiDAR surveys is introduced, demonstrating the unprecedented ability to characterize the geomorphic form of northern forested wetlands using high-resolution digital topography. Two quantitative indices are presented, including the lagg width index (LWI) which objectively...

Registration of Aerial Image with Airborne LiDAR Data Based on Plücker Line

Directory of Open Access Journals (Sweden)

SHENG Qinghong

2015-07-01

Full Text Available Registration of aerial image with airborne LiDAR data is a key to feature extraction. A registration model based on Plücker line is proposed. The relative position and attitude relationship between the conjugate lines in LiDAR and image is determined based on Plücker linear equation, which describes line transformation in space, then coplanarity condition equation is established. Finally, coordinate transformation between image point and corresponding LiDAR point is achieved by the spiral movement of Plücker lines in the image. The registration model of Plücker linear coplanarity condition equation is simple, and jointly describes the rotation and translation to avoid coupling error between them, so the accuracy is approved. This research provides technical support for high-quality earth spatial information acquisition.

IMPROVED TOPOGRAPHIC MODELS VIA CONCURRENT AIRBORNE LIDAR AND DENSE IMAGE MATCHING

Directory of Open Access Journals (Sweden)

G. Mandlburger

2017-09-01

Full Text Available Modern airborne sensors integrate laser scanners and digital cameras for capturing topographic data at high spatial resolution. The capability of penetrating vegetation through small openings in the foliage and the high ranging precision in the cm range have made airborne LiDAR the prime terrain acquisition technique. In the recent years dense image matching evolved rapidly and outperforms laser scanning meanwhile in terms of the achievable spatial resolution of the derived surface models. In our contribution we analyze the inherent properties and review the typical processing chains of both acquisition techniques. In addition, we present potential synergies of jointly processing image and laser data with emphasis on sensor orientation and point cloud fusion for digital surface model derivation. Test data were concurrently acquired with the RIEGL LMS-Q1560 sensor over the city of Melk, Austria, in January 2016 and served as basis for testing innovative processing strategies. We demonstrate that (i systematic effects in the resulting scanned and matched 3D point clouds can be minimized based on a hybrid orientation procedure, (ii systematic differences of the individual point clouds are observable at penetrable, vegetated surfaces due to the different measurement principles, and (iii improved digital surface models can be derived combining the higher density of the matching point cloud and the higher reliability of LiDAR point clouds, especially in the narrow alleys and courtyards of the study site, a medieval city.

A rigorous assessment of tree height measurements obtained using airborne LIDAR and conventional field methods.

Science.gov (United States)

Hans-Erik Andersen; Stephen E. Reutebuch; Robert J. McGaughey

2006-01-01

Tree height is an important variable in forest inventory programs but is typically time-consuming and costly to measure in the field using conventional techniques. Airborne light detection and ranging (LIDAR) provides individual tree height measurements that are highly correlated with field-derived measurements, but the imprecision of conventional field techniques does...

An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation

Directory of Open Access Journals (Sweden)

Wuming Zhang

2016-06-01

Full Text Available Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models (DTMs from airborne LiDAR (light detection and ranging data. However, most filtering algorithms need to carefully set up a number of complicated parameters to achieve high accuracy. In this paper, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. Within the proposed approach, a LiDAR point cloud is inverted, and then a rigid cloth is used to cover the inverted surface. By analyzing the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface. Finally, the ground points can be extracted from the LiDAR point cloud by comparing the original LiDAR points and the generated surface. Benchmark datasets provided by ISPRS (International Society for Photogrammetry and Remote Sensing working Group III/3 are used to validate the proposed filtering method, and the experimental results yield an average total error of 4.58%, which is comparable with most of the state-of-the-art filtering algorithms. The proposed easy-to-use filtering method may help the users without much experience to use LiDAR data and related technology in their own applications more easily.

A Decade Remote Sensing River Bathymetry with the Experimental Advanced Airborne Research LiDAR

Science.gov (United States)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.; Skinner, K.

2012-12-01

Since 2002, the first generation of the Experimental Advanced Airborne Research LiDAR (EAARL-A) sensor has been deployed for mapping rivers and streams. We present and summarize the results of comparisons between ground truth surveys and bathymetry collected by the EAARL-A sensor in a suite of rivers across the United States. These comparisons include reaches on the Platte River (NE), Boise and Deadwood Rivers (ID), Blue and Colorado Rivers (CO), Klamath and Trinity Rivers (CA), and the Shenandoah River (VA). In addition to diverse channel morphologies (braided, single thread, and meandering) these rivers possess a variety of substrates (sand, gravel, and bedrock) and a wide range of optical characteristics which influence the attenuation and scattering of laser energy through the water column. Root mean square errors between ground truth elevations and those measured by the EAARL-A ranged from 0.15-m in rivers with relatively low turbidity and highly reflective sandy bottoms to over 0.5-m in turbid rivers with less reflective substrates. Mapping accuracy with the EAARL-A has proved challenging in pools where bottom returns are either absent in waveforms or are of such low intensity that they are treated as noise by waveform processing algorithms. Resolving bathymetry in shallow depths where near surface and bottom returns are typically convolved also presents difficulties for waveform processing routines. The results of these evaluations provide an empirical framework to discuss the capabilities and limitations of the EAARL-A sensor as well as previous generations of post-processing software for extracting bathymetry from complex waveforms. These experiences and field studies not only provide benchmarks for the evaluation of the next generation of bathymetric LiDARs for use in river mapping, but also highlight the importance of developing and standardizing more rigorous methods to characterize substrate reflectance and in-situ optical properties at study sites

[Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

Science.gov (United States)

Liu, Feng; Tan, Chang; Lei, Pi-Feng

2014-11-01

Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.

Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations

Science.gov (United States)

Babcock, Chad; Finley, Andrew O.; Andersen, Hans-Erik; Pattison, Robert; Cook, Bruce D.; Morton, Douglas C.; Alonzo, Michael; Nelson, Ross; Gregoire, Timothy; Ene, Liviu; Gobakken, Terje; Næsset, Erik

2018-06-01

The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip samples of airborne lidar and Landsat-based remote sensing data products to predict aboveground biomass (AGB) in interior Alaska's Tanana Valley. The proposed modeling strategy facilitates pixel-level mapping of AGB density predictions across the entire spatial domain. Additionally, the coregionalization framework allows for statistically sound estimation of total AGB for arbitrary areal units within the study area---a key advance to support diverse management objectives in interior Alaska. This research focuses on appropriate characterization of prediction uncertainty in the form of posterior predictive coverage intervals and standard deviations. Using the framework detailed here, it is possible to quantify estimation uncertainty for any spatial extent, ranging from pixel-level predictions of AGB density to estimates of AGB stocks for the full domain. The lidar-informed coregionalization models consistently outperformed their counterpart lidar-free models in terms of point-level predictive performance and total AGB precision. Additionally, the inclusion of Landsat-derived forest cover as a covariate further improved estimation precision in regions with lower lidar sampling intensity. Our findings also demonstrate that model-based approaches that do not explicitly account for residual spatial dependence can grossly underestimate uncertainty, resulting in falsely precise estimates of AGB. On the other hand, in a geostatistical setting, residual spatial structure can be modeled within a Bayesian hierarchical framework to obtain statistically defensible assessments of uncertainty for AGB estimates.

Comparison of Aerosol Classification From Airborne High Spectral Resolution Lidar and the CALIPSO Vertical Feature Mask

Science.gov (United States)

Burton, Sharon P.; Ferrare, Rich A.; Omar, Ali H.; Vaughan, Mark A.; Rogers, Raymond R.; Hostetler, Chris a.; Hair, Johnathan W.; Obland, Michael D.; Butler, Carolyn F.; Cook, Anthony L.;

PERFORMANCE EVALUATION OF A LIGHT-WEIGHT MULTI-ECHO LIDAR FOR UNMANNED ROTORCRAFT APPLICATIONS

Directory of Open Access Journals (Sweden)

G. Conte

2013-08-01

Full Text Available The paper presents a light-weight and low-cost airborne terrain mapping system. The developed Airborne LiDAR Scanner (ALS system consists of a high-precision GNSS receiver, an inertial measurement unit and a magnetic compass which are used to complement a LiDAR sensor in order to compute a digital surface model. Evaluation of the accuracy of the generated surface model is presented. Additionally, a comparison is provided between the surface model generated from the developed ALS system and a model generated using a commercial photogrammetric software. Finally, the multi-echo capability of the used LiDAR sensor is evaluated in areas covered with dense vegetation. The ALS system and camera systems were mounted on-board an industrial unmanned helicopter of around 100 kilograms maximum take-off weight. Presented results are based on real flight-test data.

Remote Sensing of Aerosol Backscatter and Earth Surface Targets By Use of An Airborne Focused Continuous Wave CO2 Doppler Lidar Over Western North America

Science.gov (United States)

Jarzembski, Maurice A.; Srivastava, Vandana; Goodman, H. Michael (Technical Monitor)

2000-01-01

Airborne lidar systems are used to determine wind velocity and to measure aerosol or cloud backscatter variability. Atmospheric aerosols, being affected by local and regional sources, show tremendous variability. Continuous wave (cw) lidar can obtain detailed aerosol loading with unprecedented high resolution (3 sec) and sensitivity (1 mg/cubic meter) as was done during the 1995 NASA Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission over western North America and the Pacific Ocean. Backscatter variability was measured at a 9.1 micron wavelength cw focused CO2 Doppler lidar for approximately 52 flight hours, covering an equivalent horizontal distance of approximately 30,000 km in the troposphere. Some quasi-vertical backscatter profiles were also obtained during various ascents and descents at altitudes that ranged from approximately 0.1 to 12 km. Similarities and differences for aerosol loading over land and ocean were observed. Mid-tropospheric aerosol backscatter background mode was approximately 6 x 10(exp -11)/ms/r, consistent with previous lidar datasets. While these atmospheric measurements were made, the lidar also retrieved a distinct backscatter signal from the Earth's surface from the unfocused part of the focused cw lidar beam during aircraft rolls. Atmospheric backscatter can be highly variable both spatially and temporally, whereas, Earth-surface backscatter is relatively much less variant and can be quite predictable. Therefore, routine atmospheric backscatter measurements by an airborne lidar also give Earth surface backscatter which can allow for investigating the Earth terrain. In the case where the Earth's surface backscatter is coming from a well-known and fairly uniform region, then it can potentially offer lidar calibration opportunities during flight. These Earth surface measurements over varying Californian terrain during the mission were compared with laboratory backscatter measurements using the same lidar of various

Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies.

Science.gov (United States)

Ferraz, A.; Painter, T. H.; Saatchi, S.; Bormann, K. J.

2016-12-01

Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies The NASA Jet Propulsion Laboratory developed the Airborne Snow Observatory (ASO), a coupled scanning lidar system and imaging spectrometer, to quantify the spatial distribution of snow volume and dynamics over mountains watersheds (Painter et al., 2015). To do this, ASO weekly over-flights mountainous areas during snowfall and snowmelt seasons. In addition, there are additional flights in snow-off conditions to calculate Digital Terrain Models (DTM). In this study, we focus on the reliability of ASO lidar data to characterize the 3D forest vegetation structure. The density of a single point cloud acquisition is of nearly 1 pt/m2, which is not optimal to properly characterize vegetation. However, ASO covers a given study site up to 14 times a year that enables computing a high-resolution point cloud by merging single acquisitions. In this study, we present a method to automatically register ASO multi-temporal lidar 3D point clouds. Although flight specifications do not change between acquisition dates, lidar datasets might have significant planimetric shifts due to inaccuracies in platform trajectory estimation introduced by the GPS system and drifts of the IMU. There are a large number of methodologies that address the problem of 3D data registration (Gressin et al., 2013). Briefly, they look for common primitive features in both datasets such as buildings corners, structures like electric poles, DTM breaklines or deformations. However, they are not suited for our experiment. First, single acquisition point clouds have low density that makes the extraction of primitive features difficult. Second, the landscape significantly changes between flights due to snowfall and snowmelt. Therefore, we developed a method to automatically register point clouds using tree apexes as keypoints because they are features that are supposed to experience little change

Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery

Science.gov (United States)

Dechesne, Clément; Mallet, Clément; Le Bris, Arnaud; Gouet-Brunet, Valérie

2017-04-01

Forest stands are the basic units for forest inventory and mapping. Stands are defined as large forested areas (e.g., ⩾ 2 ha) of homogeneous tree species composition and age. Their accurate delineation is usually performed by human operators through visual analysis of very high resolution (VHR) infra-red images. This task is tedious, highly time consuming, and should be automated for scalability and efficient updating purposes. In this paper, a method based on the fusion of airborne lidar data and VHR multispectral images is proposed for the automatic delineation of forest stands containing one dominant species (purity superior to 75%). This is the key preliminary task for forest land-cover database update. The multispectral images give information about the tree species whereas 3D lidar point clouds provide geometric information on the trees and allow their individual extraction. Multi-modal features are computed, both at pixel and object levels: the objects are individual trees extracted from lidar data. A supervised classification is then performed at the object level in order to coarsely discriminate the existing tree species in each area of interest. The classification results are further processed to obtain homogeneous areas with smooth borders by employing an energy minimum framework, where additional constraints are joined to form the energy function. The experimental results show that the proposed method provides very satisfactory results both in terms of stand labeling and delineation (overall accuracy ranges between 84 % and 99 %).

System analysis and simulation of airborne scannerless 3D imaging lidar

Science.gov (United States)

Guo, Pan; Hao, Qiwei; Chen, Siying

2009-11-01

Airborne non-scanned 3D imaging lidar is a recently developed method for remote sensing. The design method and flow of the system parameters round with the spatial resolution are established and explained in detail with examples. An evaluation indicator of data coverage is proposed to optimize the imaging control method. Pixel aliasing in all directions are analyzed, the possible factors cause the aliasing are stated, including the time control error, atmospheric disturbance and platform shake. At last, a parallel data output format is proposed to eliminate the timing mismatch of image data and POS parameters.

Building extraction for 3D city modelling using airborne laser ...

African Journals Online (AJOL)

Light detection and ranging (LiDAR) technology has become a standard tool for three-dimensional mapping because it offers fast rate of data acquisition with unprecedented level of accuracy. This study presents an approach to accurately extract and model building in three-dimensional space from airborne laser scanning ...

Improving stream studies with a small-footprint green lidar

Science.gov (United States)

Jim McKean; Dan Isaak; Wayne Wright

2009-01-01

Technology is changing how scientists and natural resource managers describe and study streams and rivers. A new generation of airborne aquatic-terrestrial lidars is being developed that can penetrate water and map the submerged topography inside a stream as well as the adjacent subaerial terrain and vegetation in one integrated mission. A leading example of these new...

First Airborne IPDA Lidar Measurements of Methane and Carbon Dioxide Applying the DLR Greenhouse Gas Sounder CHARM-F

Science.gov (United States)

Amediek, A.; Ehret, G.; Fix, A.; Wirth, M.; Quatrevalet, M.; Büdenbender, C.; Kiemle, C.; Loehring, J.; Gerbig, C.

2015-12-01

First airborne measurement using CHARM-F, the four-wavelengths lidar for simultaneous soundings of atmospheric CO2 and CH4, were performed in Spring 2015 onboard the German research aircraft HALO. The lidar is designed in the IPDA (integrated path differential absorption) configuration using short double pulses, which gives column averaged gas mixing ratios between aircraft and ground. HALO's maximum flight altitude of 15 km and special features of the lidar, such as a relatively large laser ground spot, enable the CHARM-F system to be an airborne demonstrator for future spaceborne greenhouse gas lidars. Due to a high technological conformity this applies in particular to the French-German satellite mission MERLIN, the spaceborne methane IPDA lidar. The successfully completed flight measurements provide a valuable dataset, which supports the retrieval algorithm development for MERLIN notably. The flights covered different ground cover types, different orography types as well as the sea. Additionally, we captured different cloud conditions, at which the broken cloud case is a matter of particular interest. This dataset allows detailed analyses of measurement sensitivities, general studies on the IPDA principle and on technical details of the system. These activities are supported by another instrument onboard: a cavity ring down spectrometer, providing in-situ data of carbon dioxide, methane and water vapor with high accuracy and precision, which is ideal for validation purposes of the lidar. Additionally the onboard instrumentation of HALO gives information about pressure and temperature for cross-checking the ECMWF data, which are intended to be used for calculating the weighting function, the key quantity for the retrieval of gas column mixing ratios from the measured gas optical depths. In combination with dedicated descents into the boundary layer and subsequent ascents, a self-contained dataset for characterizations of CHARM-F is available.

Important LiDAR metrics for discriminating forest tree species in Central Europe

Science.gov (United States)

Shi, Yifang; Wang, Tiejun; Skidmore, Andrew K.; Heurich, Marco

2018-03-01

Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe.

2012 MEGIS Topographic Lidar: Statewide Lidar Project Area 1 (Aroostook), Maine

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

Measurement of atmospheric CO2 column concentrations to cloud tops with a pulsed multi-wavelength airborne lidar

Science.gov (United States)

Mao, Jianping; Ramanathan, Anand; Abshire, James B.; Kawa, Stephan R.; Riris, Haris; Allan, Graham R.; Rodriguez, Michael; Hasselbrack, William E.; Sun, Xiaoli; Numata, Kenji; Chen, Jeff; Choi, Yonghoon; Yang, Mei Ying Melissa

2018-01-01

We have measured the column-averaged atmospheric CO2 mixing ratio to a variety of cloud tops by using an airborne pulsed multi-wavelength integrated-path differential absorption (IPDA) lidar. Airborne measurements were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) science campaigns flown in the United States West and Midwest and were compared to those from an in situ sensor. Analysis of the lidar backscatter profiles shows the average cloud top reflectance was ˜ 5 % for the CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 µs wide laser pulses reflected from cloud tops were sufficient to allow clear identification of CO2 absorption line shape and then to allow retrievals of atmospheric column CO2 from the aircraft to cloud tops more than 90 % of the time. Retrievals from the CO2 measurements to cloud tops had minimal bias but larger standard deviations when compared to those made to the ground, depending on cloud top roughness and reflectance. The measurements show this new capability helps resolve CO2 horizontal and vertical gradients in the atmosphere. When used with nearby full-column measurements to ground, the CO2 measurements to cloud tops can be used to estimate the partial-column CO2 concentration below clouds, which should lead to better estimates of surface carbon sources and sinks. This additional capability of the range-resolved CO2 IPDA lidar technique provides a new benefit for studying the carbon cycle in future airborne and space-based CO2 missions.

Measurement of Atmospheric CO2 Column Concentrations to Cloud Tops With a Pulsed Multi-Wavelength Airborne Lidar

Science.gov (United States)

Mao, Jianping; Ramanathan, Anand; Abshire, James B.; Kawa, Stephan R.; Riris, Haris; Allan, Graham R.; Rodriguez, Michael R.; Hasselbrack, William E.; Sun, Xiaoli; Numata, Kenji;

Airborne measurements of CO2 column concentrations made with a pulsed IPDA lidar using a multiple-wavelength-locked laser and HgCdTe APD detector

Science.gov (United States)

Abshire, James B.; Ramanathan, Anand K.; Riris, Haris; Allan, Graham R.; Sun, Xiaoli; Hasselbrack, William E.; Mao, Jianping; Wu, Stewart; Chen, Jeffrey; Numata, Kenji; Kawa, Stephan R.; Yang, Mei Ying Melissa; DiGangi, Joshua

2018-04-01

Here we report on measurements made with an improved CO2 Sounder lidar during the ASCENDS 2014 and 2016 airborne campaigns. The changes made to the 2011 version of the lidar included incorporating a rapidly wavelength-tunable, step-locked seed laser in the transmitter, using a much more sensitive HgCdTe APD detector and using an analog digitizer with faster readout time in the receiver. We also improved the lidar's calibration approach and the XCO2 retrieval algorithm. The 2014 and 2016 flights were made over several types of topographic surfaces from 3 to 12 km aircraft altitudes in the continental US. The results are compared to the XCO2 values computed from an airborne in situ sensor during spiral-down maneuvers. The 2014 results show significantly better performance and include measurement of horizontal gradients in XCO2 made over the Midwestern US that agree with chemistry transport models. The results from the 2016 airborne lidar retrievals show precisions of ˜ 0.7 parts per million (ppm) with 1 s averaging over desert surfaces, which is an improvement of about 8 times compared to similar measurements made in 2011. Measurements in 2016 were also made over fresh snow surfaces that have lower surface reflectance at the laser wavelengths. The results from both campaigns showed that the mean values of XCO2 retrieved from the lidar consistently agreed with those based on the in situ sensor to within 1 ppm. The improved precision and accuracy demonstrated in the 2014 and 2016 flights should benefit future airborne science campaigns and advance the technique's readiness for a space-based instrument.

Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

Science.gov (United States)

Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

2017-12-01

The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

Using Airborne LIDAR Data for Assessment of Forest Fire Fuel Load Potential

Science.gov (United States)

İnan, M.; Bilici, E.; Akay, A. E.

2017-11-01

Forest fire incidences are one of the most detrimental disasters that may cause long terms effects on forest ecosystems in many parts of the world. In order to minimize environmental damages of fires on forest ecosystems, the forested areas with high fire risk should be determined so that necessary precaution measurements can be implemented in those areas. Assessment of forest fire fuel load can be used to estimate forest fire risk. In order to estimate fuel load capacity, forestry parameters such as number of trees, tree height, tree diameter, crown diameter, and tree volume should be accurately measured. In recent years, with the advancements in remote sensing technology, it is possible to use airborne LIDAR for data estimation of forestry parameters. In this study, the capabilities of using LIDAR based point cloud data for assessment of the forest fuel load potential was investigated. The research area was chosen in the Istanbul Bentler series of Bahceköy Forest Enterprise Directorate that composed of mixed deciduous forest structure.

Observation of wind field over heterogeneous terrain by the French-German airborne Doppler lidar WIND

Science.gov (United States)

Dabas, A.; Werner, C.; Delville, P.; Reitebuch, O.; Drobinski, P.; Cousin, F.

2003-04-01

In summer 2001, the French-German airborne Doppler lidar WIND participated to field campaign ESCOMPTE. ESCOMPTE was carried out in the region of Marseille along the Mediterranean coast of France. It was dedicated to the observation of heavy pollution events in this industrialized, densely populated region of nearly 4 million inhabitants. The aim was to gather a data base as comprehensive as possible on several pollution events and use them to check the ability of several regional forecast models to predict such events. The specific mission devoted to WIND was the characterization at mesoscale of the wind field and the topography of the planetary boundary layer. Both are complex around Marseille due the heterogeneity of the surface with a transition sea/land to the south, the fore-Alps to the North, the Rhône valley to the North-West etc... Seven, 3-hr flights were carried out and gave excellent results. In 2002, first comparisons were made with mesoscale models. They will be shown during the presentation. They are good examples of the usefulness of airborne Doppler lidar for validating and improving atmospheric model simulations.

Challenges and opportunities : One stop processing of automatic large-scale base map production using airborne lidar data within gis environment case study: Makassar City, Indonesia

NARCIS (Netherlands)

Widyaningrum, E.; Gorte, B.G.H.

2017-01-01

LiDAR data acquisition is recognized as one of the fastest solutions to provide basis data for large-scale topographical base maps worldwide. Automatic LiDAR processing is believed one possible scheme to accelerate the large-scale topographic base map provision by the Geospatial Information

Fusion of Airborne Discrete-Return LiDAR and Hyperspectral Data for Land Cover Classification

Directory of Open Access Journals (Sweden)

Shezhou Luo

2015-12-01

Full Text Available Accurate land cover classification information is a critical variable for many applications. This study presents a method to classify land cover using the fusion data of airborne discrete return LiDAR (Light Detection and Ranging and CASI (Compact Airborne Spectrographic Imager hyperspectral data. Four LiDAR-derived images (DTM, DSM, nDSM, and intensity and CASI data (48 bands with 1 m spatial resolution were spatially resampled to 2, 4, 8, 10, 20 and 30 m resolutions using the nearest neighbor resampling method. These data were thereafter fused using the layer stacking and principal components analysis (PCA methods. Land cover was classified by commonly used supervised classifications in remote sensing images, i.e., the support vector machine (SVM and maximum likelihood (MLC classifiers. Each classifier was applied to four types of datasets (at seven different spatial resolutions: (1 the layer stacking fusion data; (2 the PCA fusion data; (3 the LiDAR data alone; and (4 the CASI data alone. In this study, the land cover category was classified into seven classes, i.e., buildings, road, water bodies, forests, grassland, cropland and barren land. A total of 56 classification results were produced, and the classification accuracies were assessed and compared. The results show that the classification accuracies produced from two fused datasets were higher than that of the single LiDAR and CASI data at all seven spatial resolutions. Moreover, we find that the layer stacking method produced higher overall classification accuracies than the PCA fusion method using both the SVM and MLC classifiers. The highest classification accuracy obtained (OA = 97.8%, kappa = 0.964 using the SVM classifier on the layer stacking fusion data at 1 m spatial resolution. Compared with the best classification results of the CASI and LiDAR data alone, the overall classification accuracies improved by 9.1% and 19.6%, respectively. Our findings also demonstrated that the

Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests

Science.gov (United States)

Liu, Jing; Skidmore, Andrew K.; Heurich, Marco; Wang, Tiejun

2017-10-01

As an important metric for describing vertical forest structure, the plant area index (PAI) profile is used for many applications including biomass estimation and wildlife habitat assessment. PAI profiles can be estimated with the vertically resolved gap fraction from airborne LiDAR data. Most research utilizes a height normalization algorithm to retrieve local or relative height by assuming the terrain to be flat. However, for many forests this assumption is not valid. In this research, the effect of topographic normalization of airborne LiDAR data on the retrieval of PAI profile was studied in a mountainous forest area in Germany. Results show that, although individual tree height may be retained after topographic normalization, the spatial arrangement of trees is changed. Specifically, topographic normalization vertically condenses and distorts the PAI profile, which consequently alters the distribution pattern of plant area density in space. This effect becomes more evident as the slope increases. Furthermore, topographic normalization may also undermine the complexity (i.e., canopy layer number and entropy) of the PAI profile. The decrease in PAI profile complexity is not solely determined by local topography, but is determined by the interaction between local topography and the spatial distribution of each tree. This research demonstrates that when calculating the PAI profile from airborne LiDAR data, local topography needs to be taken into account. We therefore suggest that for ecological applications, such as vertical forest structure analysis and modeling of biodiversity, topographic normalization should not be applied in non-flat areas when using LiDAR data.

Fractal properties and denoising of lidar signals from cirrus clouds

NARCIS (Netherlands)

Heuvel, J.C. van den; Driesenaar, M.L.; Lerou, R.J.L.

2000-01-01

Airborne lidar signals of cirrus clouds are analyzed to determine the cloud structure. Climate modeling and numerical weather prediction benefit from accurate modeling of cirrus clouds. Airborne lidar measurements of the European Lidar in Space Technology Experiment (ELITE) campaign were analyzed by

Airborne 3D Imaging Lidar for Contiguous Decimeter Resolution Terrain Mapping and Shallow Water Bathymetry

Science.gov (United States)

Degnan, J. J.; Wells, D. N.; Huet, H.; Chauvet, N.; Lawrence, D. W.; Mitchell, S. E.; Eklund, W. D.

2005-12-01

A 3D imaging lidar system, developed for the University of Florida at Gainesville and operating at the water transmissive wavelength of 532 nm, is designed to contiguously map underlying terrain and/or perform shallow water bathymetry on a single overflight from an altitude of 600 m with a swath width of 225 m and a horizontal spatial resolution of 20 cm. Each 600 psec pulse from a frequency-doubled, low power (~3 microjoules @ 8 kHz = 24 mW), passively Q-switched Nd:YAG microchip laser is passed through a holographic element which projects a 10x10 array of spots onto a 2m x 2m target area. The individual ground spots are then imaged onto individual anodes within a 10x10 segmented anode photomultiplier. The latter is followed by a 100 channel multistop ranging receiver with a range resolution of about 4 cm. The multistop feature permits single photon detection in daylight with wide range gates as well as multiple single photon returns per pixel per laser fire from volumetric scatterers such as tree canopies or turbid water columns. The individual single pulse 3D images are contiguously mosaiced together through the combined action of the platform velocity and a counter-rotating dual wedge optical scanner whose rotations are synchronized to the laser pulse train. The paper provides an overview of the lidar opto-mechanical design, the synchronized dual wedge scanner and servo controller, and the experimental results obtained to date.

Delineation of peatland lagg boundaries from airborne LiDAR

Science.gov (United States)

Langlois, Melanie N.; Richardson, Murray C.; Price, Jonathan S.

2017-09-01

In Canada, peatlands are the most common type of wetland, but boundary delineation in peatland complexes has received little attention in the scientific literature. Typically, peatland boundaries are mapped as crisp, absolute features, and the transitional lagg zone—the ecotone found between a raised bog and the surrounding mineral land—is often overlooked. In this study, we aim (1) to advance existing approaches for detecting and locating laggs and lagg boundaries using airborne LiDAR surveys and (2) to describe the spatial distribution of laggs around raised bog peatlands. Two contrasting spatial analytical approaches for lagg detection were tested using five LiDAR-derived topographic and vegetation indices: topography, vegetation height, topographic wetness index, the standard deviation of the vegetation's height (as a proxy for the complexity of the vegetation's structure), and local indices of elevation variance. Using a dissimilarity approach (edge-detection, split-moving window analysis), no one variable accurately depicted both the lagg-mineral land and bog-lagg boundaries. Some indicators were better at predicting the bog-lagg boundary (i.e., vegetation height) and others at finding the lagg-mineral land boundary (i.e., topography). Dissimilarity analysis reinforces the usefulness of derived variables (e.g., wetness indices) in locating laggs, especially for those with weak topographic and vegetation gradients. When the lagg was confined between the bog and the adjacent upland, it took a linear form, parallel to the peatland's edge and was easier to predict. When the adjacent mineral land was flat or sloping away from the peatland, the lagg was discontinuous and intermittent and more difficult to predict.

Prediction of Canopy Heights over a Large Region Using Heterogeneous Lidar Datasets: Efficacy and Challenges

Directory of Open Access Journals (Sweden)

Ranjith Gopalakrishnan

2015-08-01

Full Text Available Generating accurate and unbiased wall-to-wall canopy height maps from airborne lidar data for large regions is useful to forest scientists and natural resource managers. However, mapping large areas often involves using lidar data from different projects, with varying acquisition parameters. In this work, we address the important question of whether one can accurately model canopy heights over large areas of the Southeastern US using a very heterogeneous dataset of small-footprint, discrete-return airborne lidar data (with 76 separate lidar projects. A unique aspect of this effort is the use of nationally uniform and extensive field data (~1800 forested plots from the Forest Inventory and Analysis (FIA program of the US Forest Service. Preliminary results are quite promising: Over all lidar projects, we observe a good correlation between the 85th percentile of lidar heights and field-measured height (r = 0.85. We construct a linear regression model to predict subplot-level dominant tree heights from distributional lidar metrics (R2 = 0.74, RMSE = 3.0 m, n = 1755. We also identify and quantify the importance of several factors (like heterogeneity of vegetation, point density, the predominance of hardwoods or softwoods, the average height of the forest stand, slope of the plot, and average scan angle of lidar acquisition that influence the efficacy of predicting canopy heights from lidar data. For example, a subset of plots (coefficient of variation of vegetation heights <0.2 significantly reduces the RMSE of our model from 3.0–2.4 m (~20% reduction. We conclude that when all these elements are factored into consideration, combining data from disparate lidar projects does not preclude robust estimation of canopy heights.

A mini backscatter lidar for airborne measurements in the framework of DACCIWA

Science.gov (United States)

Chazette, Patrick; Totems, Julien; Flamant, Cyrille; Shang, Xiaoxia; Denjean, Cyrielle; Meynadier, Rémi; Perrin, Thierry; Laurens, Marc

2017-04-01

During the international campaign of the European program Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA), investigating the relationship between weather, climate and air pollution in southern West Africa, a mini backscatter lidar was embedded on the French research aircraft (ATR42) of the Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE). This implementation was made possible thanks to the support of the Centre National d'Etude Spatial (CNES), with the aim of assessing the relative relevance of airborne or spaceborne (e.g. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, CALIPSO) remote sensing instruments. The lidar complemented the various in-situ observations carried out on the plane, by identifying the aerosol layers in the atmospheric column below the aircraft, and bringing strong constraints for the validation of other measurements. The field campaign took place from 27 to 16 July 2016 from Lomé, Togo. The aircraft conducted flights between 1 km and 5 km above the mean sea level (amsl), allowing the coupling of in situ and remote sensing data to assess the properties of the aerosol layers. Aerosol plumes of different origins were identified using the coupling between the lidar cross-polarized channels, satellite observations and a set of back trajectories analyses. During several flights, depolarizing aerosol layers from the northeast were observed between 2.5 and 4 km amsl, which highlight the significant contribution of dust-like particles to the aerosol load in the coastal region. Conversely, air masses originating from the east-southeast were loaded with a mixing of biomass burning and pollution aerosols. The former originated from Central Africa and the latter from human activities in and around large cities (Lomé). The flight sampling strategy and related lidar investigations will be presented and discussed.

Coastal Seabed Mapping with Hyperspectral and Lidar data

Science.gov (United States)

Taramelli, A.; Valentini, E.; Filipponi, F.; Cappucci, S.

2017-12-01

A synoptic view of the coastal seascape and its dynamics needs a quantitative ability to dissect different components over the complexity of the seafloor where a mixture of geo - biological facies determines geomorphological features and their coverage. The present study uses an analytical approach that takes advantage of a multidimensional model to integrate different data sources from airborne Hyperspectral and LiDAR remote sensing and in situ measurements to detect antropogenic features and ecological `tipping points' in coastal seafloors. The proposed approach has the ability to generate coastal seabed maps using: 1) a multidimensional dataset to account for radiometric and morphological properties of waters and the seafloor; 2) a field spectral library to assimilate the high environmental variability into the multidimensional model; 3) a final classification scheme to represent the spatial gradients in the seafloor. The spatial pattern of the response to anthropogenic forcing may be indistinguishable from patterns of natural variability. It is argued that this novel approach to define tipping points following anthropogenic impacts could be most valuable in the management of natural resources and the economic development of coastal areas worldwide. Examples are reported from different sites of the Mediterranean Sea, both from Marine Protected and un-Protected Areas.

Remote Sensing of Sub-Surface Suspended Sediment Concentration by Using the Range Bias of Green Surface Point of Airborne LiDAR Bathymetry

Directory of Open Access Journals (Sweden)

Xinglei Zhao

2018-04-01

Full Text Available Suspended sediment concentrations (SSCs have been retrieved accurately and effectively through waveform methods by using green-pulse waveforms of airborne LiDAR bathymetry (ALB. However, the waveform data are commonly difficult to analyze. Thus, this paper proposes a 3D point-cloud method for remote sensing of SSCs in calm waters by using the range biases of green surface points of ALB. The near water surface penetrations (NWSPs of green lasers are calculated on the basis of the green and reference surface points. The range biases (ΔS are calculated by using the corresponding NWSPs and beam-scanning angles. In situ measured SSCs (C and range biases (ΔS are used to establish an empirical C-ΔS model at SSC sampling stations. The SSCs in calm waters are retrieved by using the established C-ΔS model. The proposed method is applied to a practical ALB measurement performed by Optech Coastal Zone Mapping and Imaging LiDAR. The standard deviations of the SSCs retrieved by the 3D point-cloud method are less than 20 mg/L.

Measurement of atmospheric CO2 column concentrations to cloud tops with a pulsed multi-wavelength airborne lidar

Directory of Open Access Journals (Sweden)

J. Mao

2018-01-01

Full Text Available We have measured the column-averaged atmospheric CO2 mixing ratio to a variety of cloud tops by using an airborne pulsed multi-wavelength integrated-path differential absorption (IPDA lidar. Airborne measurements were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS science campaigns flown in the United States West and Midwest and were compared to those from an in situ sensor. Analysis of the lidar backscatter profiles shows the average cloud top reflectance was ∼ 5 % for the CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 µs wide laser pulses reflected from cloud tops were sufficient to allow clear identification of CO2 absorption line shape and then to allow retrievals of atmospheric column CO2 from the aircraft to cloud tops more than 90 % of the time. Retrievals from the CO2 measurements to cloud tops had minimal bias but larger standard deviations when compared to those made to the ground, depending on cloud top roughness and reflectance. The measurements show this new capability helps resolve CO2 horizontal and vertical gradients in the atmosphere. When used with nearby full-column measurements to ground, the CO2 measurements to cloud tops can be used to estimate the partial-column CO2 concentration below clouds, which should lead to better estimates of surface carbon sources and sinks. This additional capability of the range-resolved CO2 IPDA lidar technique provides a new benefit for studying the carbon cycle in future airborne and space-based CO2 missions.

Lidar-revised geologic map of the Des Moines 7.5' quadrangle, King County, Washington

Science.gov (United States)

Tabor, Rowland W.; Booth, Derek B.

2017-11-06

This map is an interpretation of a modern lidar digital elevation model combined with the geology depicted on the Geologic Map of the Des Moines 7.5' Quadrangle, King County, Washington (Booth and Waldron, 2004). Booth and Waldron described, interpreted, and located the geology on the 1:24,000-scale topographic map of the Des Moines 7.5' quadrangle. The base map that they used was originally compiled in 1943 and revised using 1990 aerial photographs; it has 25-ft contours, nominal horizontal resolution of about 40 ft (12 m), and nominal mean vertical accuracy of about 10 ft (3 m). Similar to many geologic maps, much of the geology in the Booth and Waldron (2004) map was interpreted from landforms portrayed on the topographic map. In 2001, the Puget Sound Lidar Consortium obtained a lidar-derived digital elevation model (DEM) for much of the Puget Sound area, including the entire Des Moines 7.5' quadrangle. This new DEM has a horizontal resolution of about 6 ft (2 m) and a mean vertical accuracy of about 1 ft (0.3 m). The greater resolution and accuracy of the lidar DEM compared to topography constructed from air-photo stereo models have much improved the interpretation of geology, even in this heavily developed area, especially the distribution and relative age of some surficial deposits. For a brief description of the light detection and ranging (lidar) remote sensing method and this data acquisition program, see Haugerud and others (2003). 

Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR

Science.gov (United States)

Jones, Benjamin M.; Stoker, Jason M.; Gibbs, Ann E.; Grosse, Guido; Romanovsky, Vladimir E.; Douglas, Thomas A.; Kinsman, Nichole E.M.; Richmond, Bruce M.

2013-01-01

Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100 km2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m2) that had changed in height by at least 0.55 m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods.

Tenneco and Greenwood Islands Disposal Sites (Mississippi) 2004 Lidar Coverage, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2004. The data...

Airborne LiDAR for the Detection of Archaeological Vegetation Marks Using Biomass as a Proxy

Directory of Open Access Journals (Sweden)

David Stott

2015-02-01

Full Text Available In arable landscapes, the airborne detection of archaeological features is often reliant on using the properties of the vegetation cover as a proxy for sub-surface features in the soil. Under the right conditions, the formation of vegetation marks allows archaeologists to identify and interpret archaeological features. Using airborne Laser Scanning, based on the principles of Light Detection and Ranging (LiDAR to detect these marks is challenging, particularly given the difficulties of resolving subtle changes in a low and homogeneous crop with these sensors. In this paper, an experimental approach is adopted to explore how these marks could be detected as variations in canopy biomass using both range and full waveform LiDAR data. Although some detection was achieved using metrics of the full waveform data, it is the novel multi-temporal method of using discrete return data to detect and characterise archaeological vegetation marks that is offered for further consideration. This method was demonstrated to be applicable over a range of capture conditions, including soils deemed as difficult (i.e., clays and other heavy soils, and should increase the certainty of detection when employed in the increasingly multi-sensor approaches to heritage prospection and management.

Quantifying biomass consumption and carbon release from the California Rim fire by integrating airborne LiDAR and Landsat OLI data.

Science.gov (United States)

Garcia, Mariano; Saatchi, Sassan; Casas, Angeles; Koltunov, Alexander; Ustin, Susan; Ramirez, Carlos; Garcia-Gutierrez, Jorge; Balzter, Heiko

2017-02-01

Quantifying biomass consumption and carbon release is critical to understanding the role of fires in the carbon cycle and air quality. We present a methodology to estimate the biomass consumed and the carbon released by the California Rim fire by integrating postfire airborne LiDAR and multitemporal Landsat Operational Land Imager (OLI) imagery. First, a support vector regression (SVR) model was trained to estimate the aboveground biomass (AGB) from LiDAR-derived metrics over the unburned area. The selected model estimated AGB with an R 2 of 0.82 and RMSE of 59.98 Mg/ha. Second, LiDAR-based biomass estimates were extrapolated to the entire area before and after the fire, using Landsat OLI reflectance bands, Normalized Difference Infrared Index, and the elevation derived from LiDAR data. The extrapolation was performed using SVR models that resulted in R 2 of 0.73 and 0.79 and RMSE of 87.18 (Mg/ha) and 75.43 (Mg/ha) for the postfire and prefire images, respectively. After removing bias from the AGB extrapolations using a linear relationship between estimated and observed values, we estimated the biomass consumption from postfire LiDAR and prefire Landsat maps to be 6.58 ± 0.03 Tg (10 12  g), which translate into 12.06 ± 0.06 Tg CO2 e released to the atmosphere, equivalent to the annual emissions of 2.57 million cars.

Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

Directory of Open Access Journals (Sweden)

J. Jubanski

2013-06-01

Full Text Available Quantification of tropical forest above-ground biomass (AGB over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+ projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia through correlating airborne light detection and ranging (LiDAR to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52. Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

Filtering Airborne LIDAR Data by AN Improved Morphological Method Based on Multi-Gradient Analysis

Science.gov (United States)

Li, Y.

2013-05-01

The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data. Although many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging task, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR point clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms of the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient of each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to carry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working Group III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to filtering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes including urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively small interval. This algorithm can efficiently remove object points while preserves ground points to a great degree.

Airborne LIDAR Power Line Classification Based on Spatial Topological Structure Characteristics

Science.gov (United States)

Wang, Y.; Chen, Q.; Li, K.; Zheng, D.; Fang, J.

2017-09-01

Automatic extraction of power lines has become a topic of great importance in airborne LiDAR data processing for transmission line management. In this paper, we present a new, fully automated and versatile framework that consists of four steps: (i) power line candidate point filtering, (ii) neighbourhood selection, (iii) feature extraction based on spatial topology, and (iv) SVM classification. In a detailed evaluation involving seven neighbourhood definitions, 26 geometric features and two datasets, we demonstrated that the use of multi-scale neighbourhoods for individual 3D points significantly improved the power line classification. Additionally, we showed that the spatial topological features may even further improve the results while reducing data processing time.

A fast approach to generate large-scale topographic maps based on new Chinese vehicle-borne Lidar system

International Nuclear Information System (INIS)

Youmei, Han; Bogang, Yang

2014-01-01

Large -scale topographic maps are important basic information for city and regional planning and management. Traditional large- scale mapping methods are mostly based on artificial mapping and photogrammetry. The traditional mapping method is inefficient and limited by the environments. While the photogrammetry methods(such as low-altitude aerial mapping) is an economical and effective way to map wide and regulate range of large scale topographic map but doesn't work well in the small area due to the high cost of manpower and resources. Recent years, the vehicle-borne LIDAR technology has a rapid development, and its application in surveying and mapping is becoming a new topic. The main objective of this investigation is to explore the potential of vehicle-borne LIDAR technology to be used to fast mapping large scale topographic maps based on new Chinese vehicle-borne LIDAR system. It studied how to use the new Chinese vehicle-borne LIDAR system measurement technology to map large scale topographic maps. After the field data capture, it can be mapped in the office based on the LIDAR data (point cloud) by software which programmed by ourselves. In addition, the detailed process and accuracy analysis were proposed by an actual case. The result show that this new technology provides a new fast method to generate large scale topographic maps, which is high efficient and accuracy compared to traditional methods

MIN-CUT BASED SEGMENTATION OF AIRBORNE LIDAR POINT CLOUDS

Directory of Open Access Journals (Sweden)

S. Ural

2012-07-01

Full Text Available Introducing an organization to the unstructured point cloud before extracting information from airborne lidar data is common in many applications. Aggregating the points with similar features into segments in 3-D which comply with the nature of actual objects is affected by the neighborhood, scale, features and noise among other aspects. In this study, we present a min-cut based method for segmenting the point cloud. We first assess the neighborhood of each point in 3-D by investigating the local geometric and statistical properties of the candidates. Neighborhood selection is essential since point features are calculated within their local neighborhood. Following neighborhood determination, we calculate point features and determine the clusters in the feature space. We adapt a graph representation from image processing which is especially used in pixel labeling problems and establish it for the unstructured 3-D point clouds. The edges of the graph that are connecting the points with each other and nodes representing feature clusters hold the smoothness costs in the spatial domain and data costs in the feature domain. Smoothness costs ensure spatial coherence, while data costs control the consistency with the representative feature clusters. This graph representation formalizes the segmentation task as an energy minimization problem. It allows the implementation of an approximate solution by min-cuts for a global minimum of this NP hard minimization problem in low order polynomial time. We test our method with airborne lidar point cloud acquired with maximum planned post spacing of 1.4 m and a vertical accuracy 10.5 cm as RMSE. We present the effects of neighborhood and feature determination in the segmentation results and assess the accuracy and efficiency of the implemented min-cut algorithm as well as its sensitivity to the parameters of the smoothness and data cost functions. We find that smoothness cost that only considers simple distance

Study of ocean red tide multi-parameter monitoring technology based on double-wavelength airborne lidar system

Science.gov (United States)

Lin, Hong; Wang, Xinming; Liang, Kun

2010-10-01

For monitoring and forecasting of the ocean red tide in real time, a marine environment monitoring technology based on the double-wavelength airborne lidar system is proposed. An airborne lidar is father more efficient than the traditional measure technology by the boat. At the same time, this technology can detect multi-parameter about the ocean red tide by using the double-wavelength lidar.It not only can use the infrared laser to detect the scattering signal under the water and gain the information about the red tise's density and size, but also can use the blue-green laser to detect the Brillouin scattering signal and deduce the temperature and salinity of the seawater.The red tide's density detecting model is firstly established by introducing the concept about the red tide scattering coefficient based on the Mie scattering theory. From the Brillouin scattering theory, the relationship about the blue-green laser's Brillouin scattering frequency shift value and power value with the seawater temperature and salinity is found. Then, the detecting mode1 of the saewater temperature and salinity can be established. The value of the red tide infrared scattering signal is evaluated by the simulation, and therefore the red tide particles' density can be known. At the same time, the blue-green laser's Brillouin scattering frequency shift value and power value are evaluated by simulating, and the temperature and salinity of the seawater can be known. Baed on the multi-parameters, the ocean red tide's growth can be monitored and forecasted.

2011 FEMA Risk Mapping, Assessment, and Planning (Risk MAP) Lidar: Nashua River Watershed (Massachusetts, New Hampshire)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These data are the lidar points collected for FEMA Risk Mapping, Assessment, and Planning (Risk MAP) for the Nashua River Watershed. This area falls in portions of...

Extraction of Urban Trees from Integrated Airborne Based Digital Image and LIDAR Point Cloud Datasets - Initial Results

Science.gov (United States)

Dogon-yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

2016-10-01

Timely and accurate acquisition of information on the condition and structural changes of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting tree features include; ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraint, such as labour intensive field work, a lot of financial requirement, influences by weather condition and topographical covers which can be overcome by means of integrated airborne based LiDAR and very high resolution digital image datasets. This study presented a semi-automated approach for extracting urban trees from integrated airborne based LIDAR and multispectral digital image datasets over Istanbul city of Turkey. The above scheme includes detection and extraction of shadow free vegetation features based on spectral properties of digital images using shadow index and NDVI techniques and automated extraction of 3D information about vegetation features from the integrated processing of shadow free vegetation image and LiDAR point cloud datasets. The ability of the developed algorithms shows a promising result as an automated and cost effective approach to estimating and delineated 3D information of urban trees. The research also proved that integrated datasets is a suitable technology and a viable source of information for city managers to be used in urban trees management.

2012 FEMA Risk Map Lidar: Merrimack River Watershed (Massachusetts, New Hampshire)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These data are the lidar points collected for FEMA Risk Mapping, Assessment, and Planning (Risk MAP) for the Merrimack River Watershed. This area falls in portions...

Lidar mapping of atmospheric atomic mercury in the Wanshan area, China.

Science.gov (United States)

Lian, Ming; Shang, Lihai; Duan, Zheng; Li, Yiyun; Zhao, Guangyu; Zhu, Shiming; Qiu, Guangle; Meng, Bo; Sommar, Jonas; Feng, Xinbin; Svanberg, Sune

2018-05-08

A novel mobile laser radar system was used for mapping gaseous atomic mercury (Hg 0 ) atmospheric pollution in the Wanshan district, south of Tongren City, Guizhou Province, China. This area is heavily impacted by legacy mercury from now abandoned mining activities. Differential absorption lidar measurements were supplemented by localized point monitoring using a Lumex RA-915M Zeeman modulation mercury analyzer. Range-resolved concentration measurements in different directions were performed. Concentrations in the lower atmospheric layers often exceeded levels of 100 ng/m 3 for March conditions with temperature ranging from 5 °C to 20 °C. A flux measurement of Hg 0 over a vertical cross section of 0.12 km 2 resulted in about 29 g/h. Vertical lidar sounding at night revealed quickly falling Hg 0 concentrations with height. This is the first lidar mapping demonstration in a heavily mercury-polluted area in China, illustrating the lidar potential in complementing point monitors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Airborne Two-Micron Double-Pulse IPDA Lidar Validation for Carbon Dioxide Measurements Over Land

Science.gov (United States)

Refaat, Tamer F.; Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Remus, Ruben; Ismail, Syed

2018-04-01

An airborne double-pulse 2-μm Integrated Path Differential Absorption (IPDA) lidar has been developed at NASA LaRC for measuring atmospheric CO2. IPDA was validated using NASA B-200 aircraft over land and ocean under different conditions. IPDA evaluation for land vegetation returns, during full day background conditions, are presented. IPDA CO2 measurements compare well with model results driven from on-board insitu sensor data. These results also indicate that CO2 measurement bias is consistent with that from ocean surface returns.

QUALITY ASSESSMENT AND CONTROL OF OUTPUTS OF A NATIONWIDE AGRICULTURAL LAND COVER MAPPING PROGRAM USING LIDAR: PHIL-LIDAR 2 PARMAP EXPERIENCE

Directory of Open Access Journals (Sweden)

H. M. Pagkalinawan

2017-11-01

Full Text Available The Agricultural Resources Extraction from LiDAR Surveys (PARMAP project component of the Nationwide Detailed Resources Assessment using LiDAR (Phil-LiDAR 2 Program aims to produce detailed agricultural maps using LiDAR. Agricultural land cover at crop level was classified through object based image analysis using Support Vector Machine as classifier and LiDAR derivatives from point cloud (2 points per sq.m. and orthophoto (0.5-meter resolution as inputs. An accuracy of at least 90 %, assessed using validation points from the field and through image interpretation, was required before proceeding to post-processing and map lay-out. Knowledge sharing and capacity development facilitated by the University of the Philippines Diliman (UPD enabled partner universities across the Philippines to produce outputs for their assigned region. Considering output layers were generated by multiple teams working on different landscape complexities with some degree of data quality variability, quality checking is crucial to ensure accuracy standards were met. UPD PARMap devised a centralized and end-to-end scheme divided into four steps – land classification, GIS post-processing, schema application, and map lay-out. At each step, a block is reviewed and, subsequently, either approved or returned with documentation on required revisions. Turnaround time of review is at least one block (area ranging from 10 to 580 sq. km. per day. For coastal municipalities, an additional integration process to incorporate mapped coastal features was applied. Common problems observed during quality checking include misclassifications, gaps between features, incomplete attributes and missing map elements. Some issues are particular to specific blocks such as problematic LiDAR derivatives. UPD addressed these problems through discussion and mentoring visits to partner universities. As of March 2017, a total of 336 municipal agricultural maps have been turned-over to various

Gluing for Raman lidar systems using the lamp mapping technique.

Science.gov (United States)

Walker, Monique; Venable, Demetrius; Whiteman, David N

2014-12-20

In the context of combined analog and photon counting (PC) data acquisition in a Lidar system, glue coefficients are defined as constants used for converting an analog signal into a virtual PC signal. The coefficients are typically calculated using Lidar profile data taken under clear, nighttime conditions since, in the presence of clouds or high solar background, it is difficult to obtain accurate glue coefficients from Lidar backscattered data. Here we introduce a new method in which we use the lamp mapping technique (LMT) to determine glue coefficients in a manner that does not require atmospheric profiles to be acquired and permits accurate glue coefficients to be calculated when adequate Lidar profile data are not available. The LMT involves scanning a halogen lamp over the aperture of a Lidar receiver telescope such that the optical efficiency of the entire detection system is characterized. The studies shown here involve two Raman lidar systems; the first from Howard University and the second from NASA/Goddard Space Flight Center. The glue coefficients determined using the LMT and the Lidar backscattered method agreed within 1.2% for the water vapor channel and within 2.5% for the nitrogen channel for both Lidar systems. We believe this to be the first instance of the use of laboratory techniques for determining the glue coefficients for Lidar data analysis.

Quantifying landscape change in an arctic coastal lowland using repeat airborne LiDAR

International Nuclear Information System (INIS)

Jones, Benjamin M; Stoker, Jason M; Gibbs, Ann E; Richmond, Bruce M; Grosse, Guido; Romanovsky, Vladimir E; Douglas, Thomas A; Kinsman, Nicole E M

2013-01-01

Increases in air, permafrost, and sea surface temperature, loss of sea ice, the potential for increased wave energy, and higher river discharge may all be interacting to escalate erosion of arctic coastal lowland landscapes. Here we use airborne light detection and ranging (LiDAR) data acquired in 2006 and 2010 to detect landscape change in a 100 km 2 study area on the Beaufort Sea coastal plain of northern Alaska. We detected statistically significant change (99% confidence interval), defined as contiguous areas (>10 m 2 ) that had changed in height by at least 0.55 m, in 0.3% of the study region. Erosional features indicative of ice-rich permafrost degradation were associated with ice-bonded coastal, river, and lake bluffs, frost mounds, ice wedges, and thermo-erosional gullies. These features accounted for about half of the area where vertical change was detected. Inferred thermo-denudation and thermo-abrasion of coastal and river bluffs likely accounted for the dominant permafrost-related degradational processes with respect to area (42%) and volume (51%). More than 300 thermokarst pits significantly subsided during the study period, likely as a result of storm surge flooding of low-lying tundra (<1.4 m asl) as well as the lasting impact of warm summers in the late-1980s and mid-1990s. Our results indicate that repeat airborne LiDAR can be used to detect landscape change in arctic coastal lowland regions at large spatial scales over sub-decadal time periods. (letter)

Airborne dust distributions over the Tibetan Plateau and surrounding areas derived from the first year of CALIPSO lidar observations

Directory of Open Access Journals (Sweden)

Z. Liu

2008-08-01

Full Text Available Using an analysis of the first full year of CALIPSO lidar measurements, this paper derives unprecedented, altitude-resolved seasonal distributions of desert dust transported over the Tibetan Plateau (TP and the surrounding areas. The CALIPSO lidar observations include numerous large dust plumes over the northern slope and eastern part of the TP, with the largest number of dust events occurring in the spring of 2007, and some layers being lofted to altitudes of 11–12 km. Generation of the Tibetan airborne dusts appears to be largely associated with source regions to the north and on the eastern part of the plateau. Examination of the CALIPSO time history reveals an "airborne dust corridor" due to the eastward transport of dusts originating primarily in these source areas. This corridor extends from west to east and shows a seasonality largely modulated by the TP through its dynamical and thermal forcing on the atmospheric flows. On the southern side, desert dust particles originate predominately in Northwest India and Pakistan. The dust transport occurs primarily in dry seasons around the TP western and southern slopes and dust particles become mixed with local polluted aerosols. No significant amount of dust appears to be transported over the Himalayas. Extensive forward trajectory simulations are also conducted to confirm the dust transport pattern from the nearby sources observed by the CALIPSO lidar. Comparisons with the OMI and MODIS measurements show the unique capability of the CALIPSO lidar to provide unambiguous, altitude-resolved dust measurements.

Data products of NASA Goddard's LiDAR, hyperspectral, and thermal airborne imager (G-LiHT)

Science.gov (United States)

Corp, Lawrence A.; Cook, Bruce D.; McCorkel, Joel; Middleton, Elizabeth M.

2015-06-01

Scientists in the Biospheric Sciences Laboratory at NASA's Goddard Space Flight Center have undertaken a unique instrument fusion effort for an airborne package that integrates commercial off the shelf LiDAR, Hyperspectral, and Thermal components. G-LiHT is a compact, lightweight and portable system that can be used on a wide range of airborne platforms to support a number of NASA Earth Science research projects and space-based missions. G-LiHT permits simultaneous and complementary measurements of surface reflectance, vegetation structure, and temperature, which provide an analytical framework for the development of new algorithms for mapping plant species composition, plant functional types, biodiversity, biomass, carbon stocks, and plant growth. G-LiHT and its supporting database are designed to give scientists open access to the data that are needed to understand the relationship between ecosystem form and function and to stimulate the advancement of synergistic algorithms. This system will enhance our ability to design new missions and produce data products related to biodiversity and climate change. G-LiHT has been operational since 2011 and has been used to collect data for a number of NASA and USFS sponsored studies, including NASA's Carbon Monitoring System (CMS) and the American ICESat/GLAS Assessment of Carbon (AMIGA-Carb). These acquisitions target a broad diversity of forest communities and ecoregions across the United States and Mexico. Here, we will discuss the components of G-LiHT, their calibration and performance characteristics, operational implementation, and data processing workflows. We will also provide examples of higher level data products that are currently available.

Estimation of Airborne Lidar-Derived Tropical Forest Canopy Height Using Landsat Time Series in Cambodia

Directory of Open Access Journals (Sweden)

Tetsuji Ota

2014-11-01

Full Text Available In this study, we test and demonstrate the utility of disturbance and recovery information derived from annual Landsat time series to predict current forest vertical structure (as compared to the more common approaches, that consider a sample of airborne Lidar and single-date Landsat derived variables. Mean Canopy Height (MCH was estimated separately using single date, time series, and the combination of single date and time series variables in multiple regression and random forest (RF models. The combination of single date and time series variables, which integrate disturbance history over the entire time series, overall provided better MCH prediction than using either of the two sets of variables separately. In general, the RF models resulted in improved performance in all estimates over those using multiple regression. The lowest validation error was obtained using Landsat time series variables in a RF model (R2 = 0.75 and RMSE = 2.81 m. Combining single date and time series data was more effective when the RF model was used (opposed to multiple regression. The RMSE for RF mean canopy height prediction was reduced by 13.5% when combining the two sets of variables as compared to the 3.6% RMSE decline presented by multiple regression. This study demonstrates the value of airborne Lidar and long term Landsat observations to generate estimates of forest canopy height using the random forest algorithm.

2012 MEGIS Topographic Lidar: Statewide Lidar Project Areas 2 and 3 (Mid-Coastal Cleanup), Maine

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data.

Science.gov (United States)

Luo, Laiping; Zhai, Qiuping; Su, Yanjun; Ma, Qin; Kelly, Maggi; Guo, Qinghua

2018-05-14

Crown base height (CBH) is an essential tree biophysical parameter for many applications in forest management, forest fuel treatment, wildfire modeling, ecosystem modeling and global climate change studies. Accurate and automatic estimation of CBH for individual trees is still a challenging task. Airborne light detection and ranging (LiDAR) provides reliable and promising data for estimating CBH. Various methods have been developed to calculate CBH indirectly using regression-based means from airborne LiDAR data and field measurements. However, little attention has been paid to directly calculate CBH at the individual tree scale in mixed-species forests without field measurements. In this study, we propose a new method for directly estimating individual-tree CBH from airborne LiDAR data. Our method involves two main strategies: 1) removing noise and understory vegetation for each tree; and 2) estimating CBH by generating percentile ranking profile for each tree and using a spline curve to identify its inflection points. These two strategies lend our method the advantages of no requirement of field measurements and being efficient and effective in mixed-species forests. The proposed method was applied to a mixed conifer forest in the Sierra Nevada, California and was validated by field measurements. The results showed that our method can directly estimate CBH at individual tree level with a root-mean-squared error of 1.62 m, a coefficient of determination of 0.88 and a relative bias of 3.36%. Furthermore, we systematically analyzed the accuracies among different height groups and tree species by comparing with field measurements. Our results implied that taller trees had relatively higher uncertainties than shorter trees. Our findings also show that the accuracy for CBH estimation was the highest for black oak trees, with an RMSE of 0.52 m. The conifer species results were also good with uniformly high R 2 ranging from 0.82 to 0.93. In general, our method has

Retrieving aboveground biomass of wetland Phragmites australis (common reed) using a combination of airborne discrete-return LiDAR and hyperspectral data

Science.gov (United States)

Luo, Shezhou; Wang, Cheng; Xi, Xiaohuan; Pan, Feifei; Qian, Mingjie; Peng, Dailiang; Nie, Sheng; Qin, Haiming; Lin, Yi

2017-06-01

Wetland biomass is essential for monitoring the stability and productivity of wetland ecosystems. Conventional field methods to measure or estimate wetland biomass are accurate and reliable, but expensive, time consuming and labor intensive. This research explored the potential for estimating wetland reed biomass using a combination of airborne discrete-return Light Detection and Ranging (LiDAR) and hyperspectral data. To derive the optimal predictor variables of reed biomass, a range of LiDAR and hyperspectral metrics at different spatial scales were regressed against the field-observed biomasses. The results showed that the LiDAR-derived H_p99 (99th percentile of the LiDAR height) and hyperspectral-calculated modified soil-adjusted vegetation index (MSAVI) were the best metrics for estimating reed biomass using the single regression model. Although the LiDAR data yielded a higher estimation accuracy compared to the hyperspectral data, the combination of LiDAR and hyperspectral data produced a more accurate prediction model for reed biomass (R2 = 0.648, RMSE = 167.546 g/m2, RMSEr = 20.71%) than LiDAR data alone. Thus, combining LiDAR data with hyperspectral data has a great potential for improving the accuracy of aboveground biomass estimation.

Application of a Terrestrial LIDAR System for Elevation Mapping in Terra Nova Bay, Antarctica

Directory of Open Access Journals (Sweden)

Hyoungsig Cho

2015-09-01

Full Text Available A terrestrial Light Detection and Ranging (LIDAR system has high productivity and accuracy for topographic mapping, but the harsh conditions of Antarctica make LIDAR operation difficult. Low temperatures cause malfunctioning of the LIDAR system, and unpredictable strong winds can deteriorate data quality by irregularly shaking co-registration targets. For stable and efficient LIDAR operation in Antarctica, this study proposes and demonstrates the following practical solutions: (1 a lagging cover with a heating pack to maintain the temperature of the terrestrial LIDAR system; (2 co-registration using square planar targets and two-step point-merging methods based on extracted feature points and the Iterative Closest Point (ICP algorithm; and (3 a georeferencing module consisting of an artificial target and a Global Navigation Satellite System (GNSS receiver. The solutions were used to produce a topographic map for construction of the Jang Bogo Research Station in Terra Nova Bay, Antarctica. Co-registration and georeferencing precision reached 5 and 45 mm, respectively, and the accuracy of the Digital Elevation Model (DEM generated from the LIDAR scanning data was ±27.7 cm.

Application of a Terrestrial LIDAR System for Elevation Mapping in Terra Nova Bay, Antarctica.

Science.gov (United States)

Cho, Hyoungsig; Hong, Seunghwan; Kim, Sangmin; Park, Hyokeun; Park, Ilsuk; Sohn, Hong-Gyoo

2015-09-16

A terrestrial Light Detection and Ranging (LIDAR) system has high productivity and accuracy for topographic mapping, but the harsh conditions of Antarctica make LIDAR operation difficult. Low temperatures cause malfunctioning of the LIDAR system, and unpredictable strong winds can deteriorate data quality by irregularly shaking co-registration targets. For stable and efficient LIDAR operation in Antarctica, this study proposes and demonstrates the following practical solutions: (1) a lagging cover with a heating pack to maintain the temperature of the terrestrial LIDAR system; (2) co-registration using square planar targets and two-step point-merging methods based on extracted feature points and the Iterative Closest Point (ICP) algorithm; and (3) a georeferencing module consisting of an artificial target and a Global Navigation Satellite System (GNSS) receiver. The solutions were used to produce a topographic map for construction of the Jang Bogo Research Station in Terra Nova Bay, Antarctica. Co-registration and georeferencing precision reached 5 and 45 mm, respectively, and the accuracy of the Digital Elevation Model (DEM) generated from the LIDAR scanning data was ±27.7 cm.

Calibration and Validation of a Detailed Architectural Canopy Model Reconstruction for the Simulation of Synthetic Hemispherical Images and Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Magnus Bremer

2017-02-01

Full Text Available Canopy density measures such as the Leaf Area Index (LAI have become standardized mapping products derived from airborne and terrestrial Light Detection And Ranging (aLiDAR and tLiDAR, respectively data. A specific application of LiDAR point clouds is their integration into radiative transfer models (RTM of varying complexity. Using, e.g., ray tracing, this allows flexible simulations of sub-canopy light condition and the simulation of various sensors such as virtual hemispherical images or waveform LiDAR on a virtual forest plot. However, the direct use of LiDAR data in RTMs shows some limitations in the handling of noise, the derivation of surface areas per LiDAR point and the discrimination of solid and porous canopy elements. In order to address these issues, a strategy upgrading tLiDAR and Digital Hemispherical Photographs (DHP into plausible 3D architectural canopy models is suggested. The presented reconstruction workflow creates an almost unbiased virtual 3D representation of branch and leaf surface distributions, minimizing systematic errors due to the object–sensor relationship. The models are calibrated and validated using DHPs. Using the 3D models for simulations, their capabilities for the description of leaf density distributions and the simulation of aLiDAR and DHP signatures are shown. At an experimental test site, the suitability of the models, in order to systematically simulate and evaluate aLiDAR based LAI predictions under various scan settings is proven. This strategy makes it possible to show the importance of laser point sampling density, but also the diversity of scan angles and their quantitative effect onto error margins.

Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests

Directory of Open Access Journals (Sweden)

Ross F. Nelson

2012-06-01

Full Text Available The objective of this study was to determine whether leaf area index (LAI in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar data or dual-band, single-pass interferometric synthetic aperture radar data (from GeoSAR alone, or both in combination. In situ measurements of LAI were made using the LiCor LAI-2000 Plant Canopy Analyzer on 61 plots (21 hardwood, 36 pine, 4 mixed pine hardwood; stand age ranging from 12-164 years; mean height ranging from 0.4 to 41.2 m in the Appomattox-Buckingham State Forest, Virginia, USA. Lidar distributional metrics were calculated for all returns and for ten one meter deep crown density slices (a new metric, five above and five below the mode of the vegetation returns for each plot. GeoSAR metrics were calculated from the X-band backscatter coefficients (four looks as well as both X- and P-band interferometric heights and magnitudes for each plot. Lidar metrics alone explained 69% of the variability in LAI, while GeoSAR metrics alone explained 52%. However, combining the lidar and GeoSAR metrics increased the R² to 0.77 with a CV-RMSE of 0.42. This study indicates the clear potential for X-band backscatter and interferometric height (both now available from spaceborne sensors, when combined with small-footprint lidar data, to improve LAI estimation in temperate mixed forests.

Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

Science.gov (United States)

Gastellu-Etchegorry, Jean-Philippe; Yin, Tiangang; Lauret, Nicolas; Grau, Eloi; Rubio, Jeremy; Cook, Bruce D.; Morton, Douglas C.; Sun, Guoqing

2016-01-01

Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

Effects of bathymetric lidar errors on flow properties predicted with a multi-dimensional hydraulic model

Science.gov (United States)

J. McKean; D. Tonina; C. Bohn; C. W. Wright

2014-01-01

New remote sensing technologies and improved computer performance now allow numerical flow modeling over large stream domains. However, there has been limited testing of whether channel topography can be remotely mapped with accuracy necessary for such modeling. We assessed the ability of the Experimental Advanced Airborne Research Lidar, to support a multi-dimensional...

The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

Science.gov (United States)

Ackers, Steven H.; Davis, Raymond J.; Olsen, K.; Dugger, Catherine

2015-01-01

Wildlife habitat mapping has evolved at a rapid pace over the last few decades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often essential for producing range wide maps. Habitat monitoring for northern spotted owls (Strix occidentalis caurina), whose geographic covers about 23 million ha, is based on SDMs that use Landsat Thematic Mapper imagery to create forest vegetation data layers using gradient nearest neighbor (GNN) methods. Vegetation data layers derived from GNN are modeled relationships between forest inventory plot data, climate and topographic data, and the spectral signatures acquired by the satellite. When used as predictor variables for SDMs, there is some transference of the GNN modeling error to the final habitat map.Recent increases in the use of light detection and ranging (lidar) data, coupled with the need to produce spatially accurate and detailed forest vegetation maps have spurred interest in its use for SDMs and habitat mapping. Instead of modeling predictor variables from remotely sensed spectral data, lidar provides direct measurements of vegetation height for use in SDMs. We expect a SDM habitat map produced from directly measured predictor variables to be more accurate than one produced from modeled predictors.We used maximum entropy (Maxent) SDM modeling software to compare predictive performance and estimates of habitat area between Landsat-based and lidar-based northern spotted owl SDMs and habitat maps. We explored the differences and similarities between these maps, and to a pre-existing aerial photo-interpreted habitat map produced by local wildlife biologists. The lidar-based map had the highest predictive performance based on 10 bootstrapped replicate models (AUC = 0.809 ± 0.011), but the

Lidar measurements of ozone and aerosol distributions during the 1992 airborne Arctic stratospheric expedition

Science.gov (United States)

Browell, Edward V.; Butler, Carolyn F.; Fenn, Marta A.; Grant, William B.; Ismail, Syed; Carter, Arlen F.

1994-01-01

The NASA Langley airborne differential absorption lidar system was operated from the NASA Ames DC-8 aircraft during the 1992 Airborne Arctic Stratospheric Expedition to investigate the distribution of stratospheric aerosols and ozone (O3) across the Arctic vortex from January to March 1992. Aerosols from the Mt. Pinatubo eruption were found outside and inside the Arctic vortex with distinctly different scattering characteristics and spatial distributions in the two regions. The aerosol and O3 distributions clearly identified the edge of the vortex and provided additional information on vortex dynamics and transport processes. Few polar stratospheric clouds were observed during the AASE-2; however, those that were found had enhanced scattering and depolarization over the background Pinatubo aerosols. The distribution of aerosols inside the vortex exhibited relatively minor changes during the AASE-2. Ozone depletion inside the vortex as limited to less than or equal to 20 percent in the altitude region from 15-20 km.

Evaluating lidar point densities for effective estimation of aboveground biomass

Science.gov (United States)

Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason M.; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.

2016-01-01

The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

Pointing Verification Method for Spaceborne Lidars

Directory of Open Access Journals (Sweden)

Axel Amediek

2017-01-01

Full Text Available High precision acquisition of atmospheric parameters from the air or space by means of lidar requires accurate knowledge of laser pointing. Discrepancies between the assumed and actual pointing can introduce large errors due to the Doppler effect or a wrongly assumed air pressure at ground level. In this paper, a method for precisely quantifying these discrepancies for airborne and spaceborne lidar systems is presented. The method is based on the comparison of ground elevations derived from the lidar ranging data with high-resolution topography data obtained from a digital elevation model and allows for the derivation of the lateral and longitudinal deviation of the laser beam propagation direction. The applicability of the technique is demonstrated by using experimental data from an airborne lidar system, confirming that geo-referencing of the lidar ground spot trace with an uncertainty of less than 10 m with respect to the used digital elevation model (DEM can be obtained.

Airborne High Spectral Resolution Lidar Aerosol Measurements during MILAGRO and TEXAQS/GOMACCS

Science.gov (United States)

Ferrare, Richard; Hostetler, Chris; Hair, John; Cook Anthony; Harper, David; Burton, Sharon; Clayton, Marian; Clarke, Antony; Russell, Phil; Redemann, Jens

2007-01-01

Two1 field experiments conducted during 2006 provided opportunities to investigate the variability of aerosol properties near cities and the impacts of these aerosols on air quality and radiative transfer. The Megacity Initiative: Local and Global Research Observations (MILAGRO) /Megacity Aerosol Experiment in Mexico City (MAX-MEX)/Intercontinental Chemical Transport Experiment-B (INTEX-B) joint experiment conducted during March 2006 investigated the evolution and transport of pollution from Mexico City. The Texas Air Quality Study (TEXAQS)/Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS) (http://www.al.noaa.gov/2006/) conducted during August and September 2006 investigated climate and air quality in the Houston/Gulf of Mexico region. During both missions, the new NASA Langley airborne High Spectral Resolution Lidar (HSRL) was deployed on the NASA Langley B200 King Air aircraft and measured profiles of aerosol extinction, backscattering, and depolarization to: 1) characterize the spatial and vertical distributions of aerosols, 2) quantify aerosol extinction and optical thickness contributed by various aerosol types, 3) investigate aerosol variability near clouds, 4) evaluate model simulations of aerosol transport, and 5) assess aerosol optical properties derived from a combination of surface, airborne, and satellite measurements.

An airborne interferometric SAR system for high-performance 3D mapping

Science.gov (United States)

Lange, Martin; Gill, Paul

2009-05-01

With a vertical accuracy better than 1 m and collection rates up to 7000 km2/h, airborne interferometric synthetic aperture radars (InSAR) bridge the gap between space borne radar sensors and airborne optical LIDARs. This paper presents the latest generation of X-band InSAR sensors, developed by Intermap TechnologiesTM, which are operated on our four aircrafts. The sensors collect data for the NEXTMap(R) program - a digital elevation model (DEM) with 1 m vertical accuracy for the contiguous U.S., Hawaii, and most of Western Europe. For a successful operation, challenges like reduction of multipath reflections, very high interferometric phase stability, and a precise system calibration had to be mastered. Recent advances in sensor design, comprehensive system automation and diagnostics have increased the sensor reliability to a level where no radar operator is required onboard. Advanced flight planning significantly improved aircraft utilization and acquisition throughput, while reducing operational costs. Highly efficient data acquisition with straight flight lines up to 1200 km is daily routine meanwhile. The collected data pass though our automated processing cluster and finally are edited to our terrain model products. Extensive and rigorous quality control at every step of the workflow are key to maintain stable vertical accuracies of 1 m and horizontal accuracies of 2 m for our 3D maps. The combination of technical and operational advances presented in this paper enabled Intermap to survey two continents, producing 11 million km2 of uniform and accurate 3D terrain data.

Improving estimation of tree carbon stocks by harvesting aboveground woody biomass within airborne LiDAR flight areas

Science.gov (United States)

Colgan, M.; Asner, G. P.; Swemmer, A. M.

2011-12-01

The accurate estimation of carbon stored in a tree is essential to accounting for the carbon emissions due to deforestation and degradation. Airborne LiDAR (Light Detection and Ranging) has been successful in estimating aboveground carbon density (ACD) by correlating airborne metrics, such as canopy height, to field-estimated biomass. This latter step is reliant on field allometry which is applied to forest inventory quantities, such as stem diameter and height, to predict the biomass of a given tree stem. Constructing such allometry is expensive, time consuming, and requires destructive sampling. Consequently, the sample sizes used to construct such allometry are often small, and the largest tree sampled is often much smaller than the largest in the forest population. The uncertainty resulting from these sampling errors can lead to severe biases when the allometry is applied to stems larger than those harvested to construct the allometry, which is then subsequently propagated to airborne ACD estimates. The Kruger National Park (KNP) mission of maintaining biodiversity coincides with preserving ecosystem carbon stocks. However, one hurdle to accurately quantifying carbon density in savannas is that small stems are typically harvested to construct woody biomass allometry, yet they are not representative of Kruger's distribution of biomass. Consequently, these equations inadequately capture large tree variation in sapwood/hardwood composition, root/shoot/leaf allocation, branch fall, and stem rot. This study eliminates the "middleman" of field allometry by directly measuring, or harvesting, tree biomass within the extent of airborne LiDAR. This enables comparisons of field and airborne ACD estimates, and also enables creation of new airborne algorithms to estimate biomass at the scale of individual trees. A field campaign was conducted at Pompey Silica Mine 5km outside Kruger National Park, South Africa, in Mar-Aug 2010 to harvest and weigh tree mass. Since

MONITORING CONCEPTS FOR COASTAL AREAS USING LIDAR DATA

Directory of Open Access Journals (Sweden)

A. Schmidt

2013-05-01

Full Text Available Coastal areas are characterized by high spatial and temporal variability. In order to detect undesired changes at early stages, enabling rapid countermeasures to mitigate or minimize potential harm or hazard, a recurrent monitoring becomes necessary. In this paper, we focus on two monitoring task: the analysis of morphological changes and the classification and mapping of habitats. Our concepts are solely based on airborne lidar data which provide substantial information in coastal areas. For the first task, we generate a digital terrain model (DTM from the lidar point cloud and analyse the dynamic of an island by comparing the DTMs of different epochs with a time difference of six years. For the deeper understanding of the habitat composition in coastal areas, we classify the lidar point cloud by a supervised approach based on Conditional Random Fields. From the classified point cloud, water-land-boundaries as well as mussel bed objects are derived afterwards. We evaluate our approaches on two datasets of the German Wadden Sea.

Handling Low-Density LiDAR Data: Calculating the Heights of Civil Constructions and the Accuracy Expected

Directory of Open Access Journals (Sweden)

Rubén Martínez Marín

2013-01-01

Full Text Available During the last years, in many developed countries, administrations and private companies have devoted considerable amounts of money to obtain mapping data using airborne LiDAR. For many civil activities, we can take advantage of it, since those data are available with no cost. Some important questions arise: Are those data good enough to be used for determining the heights of the civil constructions with the accuracy we need in some civil work? What accuracy can we expect when using low-density LiDAR data (0.5 pts/m2? In order to answer those questions, we have developed a specific methodology based on establishing a set of control points on the top of several constructions and calculating the elevation of each one using postprocessing GPS. Those results have been taken as correct values and the comparison between those values and the elevations obtained, assigning values to the control points by the interpolation of the LiDAR dataset, has been carried out. This paper shows the results obtained using low-density airborne LiDAR data and the accuracy obtained. Results have shown that LiDAR can be accurate enough (10–25 cm to determine the height of civil constructions and apply those data in many civil engineering activities.

Comparison of small-footprint discrete return and full waveform airborne lidar data for estimating multiple forest variables

OpenAIRE

Sumnall, Matthew J.; Hill, Ross A.; Hinsley, Shelley A.

2016-01-01

The quantification of forest ecosystems is important for a variety of purposes, including the assessment of wildlife habitat, nutrient cycles, timber yield and fire propagation. This research assesses the estimation of forest structure, composition and deadwood variables from small-footprint airborne lidar data, both discrete return (DR) and full waveform (FW), acquired under leaf-on and leaf-off conditions. The field site, in the New Forest, UK, includes managed plantation and ancient, se...

2-Micron Triple-Pulse Integrated Path Differential Absorption Lidar Development for Simultaneous Airborne Column Measurements of Carbon Dioxide and Water Vapor in the Atmosphere

Science.gov (United States)

Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Yu, Jirong

2016-01-01

For more than 15 years, NASA Langley Research Center (LaRC) has contributed in developing several 2-micron carbon dioxide active remote sensors using the DIAL technique. Currently, an airborne 2-micron triple-pulse integrated path differential absorption (IPDA) lidar is under development at NASA LaRC. This paper focuses on the advancement of the 2-micron triple-pulse IPDA lidar development. Updates on the state-of-the-art triple-pulse laser transmitter will be presented including the status of wavelength control, packaging and lidar integration. In addition, receiver development updates will also be presented, including telescope integration, detection systems and data acquisition electronics. Future plan for IPDA lidar system for ground integration, testing and flight validation will be presented.

Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study

Directory of Open Access Journals (Sweden)

Rubini Mahalingam

2016-11-01

Full Text Available Landslides are a significant geohazard, which frequently result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping using GIS and remote sensing can help communities prepare for these damaging events. Current mapping efforts utilize a wide variety of techniques and consider multiple factors. Unfortunately, each study is relatively independent of others in the applied technique and factors considered, resulting in inconsistencies. Further, input data quality often varies in terms of source, data collection, and generation, leading to uncertainty. This paper investigates if lidar-derived data-sets (slope, slope roughness, terrain roughness, stream power index, and compound topographic index can be used for predictive mapping without other landslide conditioning factors. This paper also assesses the differences in landslide susceptibility mapping using several, widely used statistical techniques. Landslide susceptibility maps were produced from the aforementioned lidar-derived data-sets for a small study area in Oregon using six representative statistical techniques. Most notably, results show that only a few factors were necessary to produce satisfactory maps with high predictive capability (area under the curve >0.7. The sole use of lidar digital elevation models and their derivatives can be used for landslide mapping using most statistical techniques without requiring additional detailed data-sets that are often difficult to obtain or of lower quality.

GRIP LIDAR ATMOSPHERIC SENSING EXPERIMENT (LASE) V1

Data.gov (United States)

National Aeronautics and Space Administration — The GRIP Lidar Atmospheric Sensing Experiment (LASE) dataset was collected by NASA's Lidar Atmospheric Sensing Experiment (LASE) system, which is an airborne...

Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud

Science.gov (United States)

Yao, C.; Zhang, X.; Liu, H.

2017-09-01

The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

FOREST STEM VOLUME CALCULATION USING AIRBORNE LIDAR DATA

Directory of Open Access Journals (Sweden)

I. Büyüksalih

2017-05-01

Full Text Available Airborne LiDAR data have been collected for the city of Istanbul using Riegl laser scanner Q680i with 400 kHz and an average flight height of 600 m. The flight campaign was performed by a helicopter and covers an area of 5400 km2. According to a flight speed of 80 knot a point density of more than 16 points/m2 and a laser footprint size of 30 cm could be achieved. As a result of bundle adjustment, in total, approximately 17,000 LAS files with the file size of 500 m by 700 m have been generated for the whole city. The main object classes Ground, Building, Vegetation (medium, high were derived from these LAS files using the macros in Terrasolid software. The forest area under investigation is located northwest of the city of Istanbul, main tree species occurring in the test site are pine (pinus pinaster, oak (quercus and beech (fagus. In total, 120 LAS tiles covering the investigation area have been analysed using the software IMPACT of Joanneum Research Forschungsgesellschaft, Graz, Austria. First of all, the digital terrain model (DTM and the digital surface models (DSM were imported and converted into a raster file from the original laser point clouds with a spatial resolution of 50 cm. Then, a normalized digital surface model (nDSM was derived as the difference between DSM and the DTM. Tree top detection was performed by multi – resolution filter operations and tree crowns were segmented by a region growing algorithms develop specifically for this purpose. Breast Height Diameter (BHD was calculated on the base of tree height and crown areas derived from image segmentation applying allometric functions found in literature. The assessment of stem volume was then calculated as a function of tree height and BHD. A comparison of timber volume estimated from the LiDAR data and field plots measured by the Forest Department of Istanbul showed R2 of 0.46. The low correlation might arise either from the low quality of the field plots or

CALIOPE airborne CO{sub 2} DIAL (CACDI) system design

Energy Technology Data Exchange (ETDEWEB)

Mietz, D.; Archuleta, B.; Archuleta, J. [and others

1997-09-01

Los Alamos National Laboratory is currently developing an airborne CO{sub 2} Differential Absorption Lidar (DIAL) system based on second generation technology demonstrated last summer at NTS. The CALIOPE Airborne CO{sub 2} DIAL (CACDI) system requirements have been compiled based on the mission objectives and SONDIAL model trade studies. Subsystem designs have been developed based on flow down from these system requirements, as well as experience gained from second generation ground tests and N-ABLE (Non-proliferation AirBorne Lidar Experiments) airborne experiments. This paper presents the CACDI mission objectives, system requirements, the current subsystem design, and provides an overview of the airborne experimental plan.

2008 St. Johns County, FL Countywide Lidar

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Airborne terrestrial LiDAR was collected for St. Johns County, FL. System Parameters/Flight Plan. The LiDAR system acquisition parameters were developed based on a...

Evaluation of airborne lidar data to predict vegetation Presence/Absence

Science.gov (United States)

Palaseanu-Lovejoy, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, C.W.

2009-01-01

This study evaluates the capabilities of the Experimental Advanced Airborne Research Lidar (EAARL) in delineating vegetation assemblages in Jean Lafitte National Park, Louisiana. Five-meter-resolution grids of bare earth, canopy height, canopy-reflection ratio, and height of median energy were derived from EAARL data acquired in September 2006. Ground-truth data were collected along transects to assess species composition, canopy cover, and ground cover. To decide which model is more accurate, comparisons of general linear models and generalized additive models were conducted using conventional evaluation methods (i.e., sensitivity, specificity, Kappa statistics, and area under the curve) and two new indexes, net reclassification improvement and integrated discrimination improvement. Generalized additive models were superior to general linear models in modeling presence/absence in training vegetation categories, but no statistically significant differences between the two models were achieved in determining the classification accuracy at validation locations using conventional evaluation methods, although statistically significant improvements in net reclassifications were observed. ?? 2009 Coastal Education and Research Foundation.

Airborne Instrument Simulator for the Lidar Surface Topography (LIST) Mission

Science.gov (United States)

Yu, Anthony W.; Krainak, Michael A.; Harding, David J.; Abshire, James B.; Sun, Xiaoli; Cavanaugh, John; Valett, Susan; Ramos-Izquierdo, Luis

2010-01-01

In 2007, the National Research Council (NRC) completed its first decadal survey for Earth science at the request of NASA, NOAA, and USGS. The Lidar Surface Topography (LIST) mission is one of fifteen missions recommended by NRC, whose primary objectives are to map global topography and vegetation structure at 5 m spatial resolution, and to acquire global coverage with a few years. NASA Goddard conducted an initial mission concept study for the LIST mission 2007, and developed the initial measurement requirements for the mission.

2007 South Carolina DNR Lidar: Anderson County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The LiDAR data acquisition was executed in 5 sessions, from March 7 to March 9, 2007. The airborne GPS (ABGPS) base stations supporting the LiDAR acquisition...

2012 NRCS-USGS Tupelo, MS Lidar Survey

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

Automatic reconstruction of 3D urban landscape by computing connected regions and assigning them an average altitude from LiDAR point cloud image

Science.gov (United States)

Kawata, Yoshiyuki; Koizumi, Kohei

2014-10-01

The demand of 3D city modeling has been increasing in many applications such as urban planing, computer gaming with realistic city environment, car navigation system with showing 3D city map, virtual city tourism inviting future visitors to a virtual city walkthrough and others. We proposed a simple method for reconstructing a 3D urban landscape from airborne LiDAR point cloud data. The automatic reconstruction method of a 3D urban landscape was implemented by the integration of all connected regions, which were extracted and extruded from the altitude mask images. These mask images were generated from the gray scale LiDAR image by the altitude threshold ranges. In this study we demonstrated successfully in the case of Kanazawa city center scene by applying the proposed method to the airborne LiDAR point cloud data.

Automated Tree Crown Delineation and Biomass Estimation from Airborne LiDAR data: A Comparison of Statistical and Machine Learning Methods

Science.gov (United States)

Gleason, C. J.; Im, J.

2011-12-01

Airborne LiDAR remote sensing has been used effectively in assessing forest biomass because of its canopy penetrating effects and its ability to accurately describe the canopy surface. Current research in assessing biomass using airborne LiDAR focuses on either the individual tree as a base unit of study or statistical representations of a small aggregation of trees (i.e., plot level), and both methods usually rely on regression against field data to model the relationship between the LiDAR-derived data (e.g., volume) and biomass. This study estimates biomass for mixed forests and coniferous plantations (Picea Abies) within Heiberg Memorial Forest, Tully, NY, at both the plot and individual tree level. Plots are regularly spaced with a radius of 13m, and field data include diameter at breast height (dbh), tree height, and tree species. Field data collection and LiDAR data acquisition were seasonally coincident and both obtained in August of 2010. Resulting point cloud density was >5pts/m2. LiDAR data were processed to provide a canopy height surface, and a combination of watershed segmentation, active contouring, and genetic algorithm optimization was applied to delineate individual trees from the surface. This updated delineation method was shown to be more accurate than traditional watershed segmentation. Once trees had been delineated, four biomass estimation models were applied and compared: support vector regression (SVR), linear mixed effects regression (LME), random forest (RF), and Cubist regression. Candidate variables to be used in modeling were derived from the LiDAR surface, and include metrics of height, width, and volume per delineated tree footprint. Previously published allometric equations provided field estimates of biomass to inform the regressions and calculate their accuracy via leave-one-out cross validation. This study found that for forests such as found in the study area, aggregation of individual trees to form a plot-based estimate of

2016 USACE National Coastal Mapping Program (NCMP) Gulf Coast Lidar and Imagery Acquisition - Texas, Louisiana, Mississippi, Alabama and Florida

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) plans to perform a coastal survey along the Gulf Coast in 2016 with funding provided by...

Enhanced canopy fuel mapping by integrating lidar data

Science.gov (United States)

Peterson, Birgit E.; Nelson, Kurtis J.

2016-10-03

BackgroundThe Wildfire Sciences Team at the U.S. Geological Survey’s Earth Resources Observation and Science Center produces vegetation type, vegetation structure, and fuel products for the United States, primarily through the Landscape Fire and Resource Management Planning Tools (LANDFIRE) program. LANDFIRE products are used across disciplines for a variety of applications. The LANDFIRE data retain their currency and relevancy through periodic updating or remapping. These updating and remapping efforts provide opportunities to improve the LANDFIRE product suite by incorporating data from other sources. Light detection and ranging (lidar) is uniquely suitable for gathering information on vegetation structure and spatial arrangement because it can collect data in three dimensions. The Wildfire Sciences Team has several completed and ongoing studies focused on integrating lidar into vegetation and fuels mapping.

Flood Modeling Using a Synthesis of Multi-Platform LiDAR Data

Directory of Open Access Journals (Sweden)

Ryan M. Csontos

2013-09-01

Full Text Available This study examined the utility of a high resolution ground-based (mobile and terrestrial Light Detection and Ranging (LiDAR dataset (0.2 m point-spacing supplemented with a coarser resolution airborne LiDAR dataset (5 m point-spacing for use in a flood inundation analysis. The techniques for combining multi-platform LiDAR data into a composite dataset in the form of a triangulated irregular network (TIN are described, and quantitative comparisons were made to a TIN generated solely from the airborne LiDAR dataset. For example, a maximum land surface elevation difference of 1.677 m and a mean difference of 0.178 m were calculated between the datasets based on sample points. Utilizing the composite and airborne LiDAR-derived TINs, a flood inundation comparison was completed using a one-dimensional steady flow hydraulic modeling analysis. Quantitative comparisons of the water surface profiles and depth grids indicated an underestimation of flooding extent, volume, and maximum flood height using the airborne LiDAR data alone. A 35% increase in maximum flood height was observed using the composite LiDAR dataset. In addition, the extents of the water surface profiles generated from the two datasets were found to be statistically significantly different. The urban and mountainous characteristics of the study area as well as the density (file size of the high resolution ground based LiDAR data presented both opportunities and challenges for flood modeling analyses.

Airborne system for mapping and tracking extended gamma ray sources

International Nuclear Information System (INIS)

Stuart, T.P.; Hendricks, T.J.; Wallace, G.G.; Cleland, J.R.

1976-01-01

An airborne system was developed for mapping and tracking extended sources of airborne or terrestrially distributed γ-ray emitters. The system records 300 channel γ-ray spectral data every three seconds on magnetic tape. Computer programs have been written to isolate the contribution from the particular radionuclide of interest. Aircraft position as sensed by a microwave ranging system is recorded every second on magnetic tape. Measurements of airborne stack releases of 41 A concentrations versus time or aircraft position agree well with computer code predictions

Deciphering the Precision of Stereo IKONOS Canopy Height Models for US Forests with G-LiHT Airborne LiDAR

Directory of Open Access Journals (Sweden)

Christopher S. R. Neigh

2014-02-01

Full Text Available Few studies have evaluated the precision of IKONOS stereo data for measuring forest canopy height. The high cost of airborne light detection and ranging (LiDAR data collection for large area studies and the present lack of a spaceborne instrument lead to the need to explore other low cost options. The US Government currently has access to a large archive of commercial high-resolution imagery, which could be quite valuable to forest structure studies. At 1 m resolution, we here compared canopy height models (CHMs and height data derived from Goddard’s airborne LiDAR Hyper-spectral and Thermal Imager (G-LiHT with three types of IKONOS stereo derived digital surface models (DSMs that estimate CHMs by subtracting National Elevation Data (NED digital terrain models (DTMs. We found the following in three different forested regions of the US after excluding heterogeneous and disturbed forest samples: (1 G-LiHT DTMs were highly correlated with NED DTMs with R2 > 0.98 and root mean square errors (RMSEs < 2.96 m; (2 when using one visually identifiable ground control point (GCP from NED, G-LiHT DSMs and IKONOS DSMs had R2 > 0.84 and RMSEs of 2.7 to 4.1 m; and (3 one GCP CHMs for two study sites had R2 > 0.7 and RMSEs of 2.6 to 3 m where data were collected less than four years apart. Our results suggest that IKONOS stereo data are a useful LiDAR alternative where high-quality DTMs are available.

Coherent Lidar Turbulence Measurement for Gust Load Alleviation

Science.gov (United States)

Bogue, Rodney K.; Ehernberger, L. J.; Soreide, David; Bagley, Hal

1996-01-01

Atmospheric turbulence adversely affects operation of commercial and military aircraft and is a design constraint. The airplane structure must be designed to survive the loads imposed by turbulence. Reducing these loads allows the airplane structure to be lighter, a substantial advantage for a commercial airplane. Gust alleviation systems based on accelerometers mounted in the airplane can reduce the maximum gust loads by a small fraction. These systems still represent an economic advantage. The ability to reduce the gust load increases tremendously if the turbulent gust can be measured before the airplane encounters it. A lidar system can make measurements of turbulent gusts ahead of the airplane, and the NASA Airborne Coherent Lidar for Advanced In-Flight Measurements (ACLAIM) program is developing such a lidar. The ACLAIM program is intended to develop a prototype lidar system for use in feasibility testing of gust load alleviation systems and other airborne lidar applications, to define applications of lidar with the potential for improving airplane performance, and to determine the feasibility and benefits of these applications. This paper gives an overview of the ACLAIM program, describes the lidar architecture for a gust alleviation system, and describes the prototype ACLAIM lidar system.

Airborne lidar observations of long-range transport in the free troposphere

Science.gov (United States)

Shipley, S. T.; Browell, E. V.; Mcdougal, D. S.; Orndorff, B. L.; Haagenson, P.

1984-01-01

Airborne lidar measurements of ozone and aerosols in the lower troposphere show the presence of pollutant layers above the mixed layer. Two case studies are analyzed to identify probable source regions and mechanisms for material injection into the free troposphere above local mixed layers. An elevated haze/oxidant layer observed over South Carolina on Aug. 2, 1980, was found to originate in cumulus convection over Georgia on Aug. 1, 1980. An extensive haze/oxidant layer observed over southeastern Virginia on July 31, 1981, is shown to have been in contact with the New England mixed layer on July 30, 1981. This transported air mass is estimated to contribute approximately 30 percent of the ozone maximum measured at the surface in the Norfolk, VA, area on July 31, 1981. Such elevated 'reservoir' layers are transported over long ranges and are not detected by sensors which are confined to the surface.

Raster Vs. Point Cloud LiDAR Data Classification

Science.gov (United States)

El-Ashmawy, N.; Shaker, A.

2014-09-01

Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the

2009 - 2011 CA Coastal Conservancy Coastal Lidar Project

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

Urban forest topographical mapping using UAV LIDAR

Science.gov (United States)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

A geomorphologist's dream come true: synoptic high resolution river bathymetry with the latest generation of airborne dual wavelength lidar

Science.gov (United States)

Lague, Dimitri; Launeau, Patrick; Michon, Cyril; Gouraud, Emmanuel; Juge, Cyril; Gentile, William; Hubert-Moy, Laurence; Crave, Alain

2016-04-01

Airborne, terrestrial lidar and Structure From Motion have dramatically changed our approach of geomorphology, from low density/precision data, to a wealth of data with a precision adequate to actually measure topographic change across multiple scales, and its relation to vegetation. Yet, an important limitation in the context of fluvial geomorphology has been the inability of these techniques to penetrate water due to the use of NIR laser wavelengths or to the complexity of accounting for water refraction in SFM. Coastal bathymetric systems using a green lidar can penetrate clear water up to 50 m but have a resolution too coarse and deployment costs that are prohibitive for fluvial research and management. After early prototypes of narrow aperture green lidar (e.g., EEARL NASA), major lidar manufacturer are now releasing dual wavelength laser system that offer water penetration consistent with shallow fluvial bathymetry at very high resolution (> 10 pts/m²) and deployment costs that makes the technology, finally accessible. This offers unique opportunities to obtain synoptic high resolution, high precision data for academic research as well as for fluvial environment management (flood risk mapping, navigability,…). In this presentation, we report on the deployment of the latest generation Teledyne-Optech Titan dual-wavelength lidar (1064 nm + 532 nm) owned by the University of Nantes and Rennes. The instrument has been deployed over several fluvial and lacustrine environments in France. We present results and recommendation on how to optimize the bathymetric cover as a function of aerial and aquatic vegetation cover and the hydrology regime of the river. In the surveyed rivers, the penetration depth varies from 0.5 to 4 m with discrete echoes (i.e., onboard detection), heavily impacted by water clarity and bottom reflectance. Simple post-processing of the full waveform record allows to recover an additional 20 % depth. As for other lidar techniques, the main

Classification of LIDAR Data for Generating a High-Precision Roadway Map

Science.gov (United States)

Jeong, J.; Lee, I.

2016-06-01

Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.

CLASSIFICATION OF LIDAR DATA FOR GENERATING A HIGH-PRECISION ROADWAY MAP

Directory of Open Access Journals (Sweden)

J. Jeong

2016-06-01

Full Text Available Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.

Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

Science.gov (United States)

Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

2018-03-01

Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

Mapping of landslides under dense vegetation cover using object - oriented analysis and LiDAR derivatives

NARCIS (Netherlands)

Van Den Eeckhout, Miet; Kerle, N.; Hervas, Javier; Supper, Robert; Margottini, C.; Canuti, P.; Sassa, K.

2013-01-01

Light Detection and Ranging (LiDAR) and its wide range of derivative products have become a powerful tool in landslide research, particularly for landslide identification and landslide inventory mapping. In contrast to the many studies that use expert-based analysis of LiDAR derivatives to identify

Aboveground Biomass Estimation Using Reconstructed Feature of Airborne Discrete-Return LIDAR by Auto-Encoder Neural Network

Science.gov (United States)

Li, T.; Wang, Z.; Peng, J.

2018-04-01

Aboveground biomass (AGB) estimation is critical for quantifying carbon stocks and essential for evaluating carbon cycle. In recent years, airborne LiDAR shows its great ability for highly-precision AGB estimation. Most of the researches estimate AGB by the feature metrics extracted from the canopy height distribution of the point cloud which calculated based on precise digital terrain model (DTM). However, if forest canopy density is high, the probability of the LiDAR signal penetrating the canopy is lower, resulting in ground points is not enough to establish DTM. Then the distribution of forest canopy height is imprecise and some critical feature metrics which have a strong correlation with biomass such as percentiles, maximums, means and standard deviations of canopy point cloud can hardly be extracted correctly. In order to address this issue, we propose a strategy of first reconstructing LiDAR feature metrics through Auto-Encoder neural network and then using the reconstructed feature metrics to estimate AGB. To assess the prediction ability of the reconstructed feature metrics, both original and reconstructed feature metrics were regressed against field-observed AGB using the multiple stepwise regression (MS) and the partial least squares regression (PLS) respectively. The results showed that the estimation model using reconstructed feature metrics improved R2 by 5.44 %, 18.09 %, decreased RMSE value by 10.06 %, 22.13 % and reduced RMSEcv by 10.00 %, 21.70 % for AGB, respectively. Therefore, reconstructing LiDAR point feature metrics has potential for addressing AGB estimation challenge in dense canopy area.

State-of-the-Art: DTM Generation Using Airborne LIDAR Data

Directory of Open Access Journals (Sweden)

Ziyue Chen

2017-01-01

Full Text Available Digital terrain model (DTM generation is the fundamental application of airborne Lidar data. In past decades, a large body of studies has been conducted to present and experiment a variety of DTM generation methods. Although great progress has been made, DTM generation, especially DTM generation in specific terrain situations, remains challenging. This research introduces the general principles of DTM generation and reviews diverse mainstream DTM generation methods. In accordance with the filtering strategy, these methods are classified into six categories: surface-based adjustment; morphology-based filtering, triangulated irregular network (TIN-based refinement, segmentation and classification, statistical analysis and multi-scale comparison. Typical methods for each category are briefly introduced and the merits and limitations of each category are discussed accordingly. Despite different categories of filtering strategies, these DTM generation methods present similar difficulties when implemented in sharply changing terrain, areas with dense non-ground features and complicated landscapes. This paper suggests that the fusion of multi-sources and integration of different methods can be effective ways for improving the performance of DTM generation.

State-of-the-Art: DTM Generation Using Airborne LIDAR Data

Science.gov (United States)

Chen, Ziyue; Gao, Bingbo; Devereux, Bernard

2017-01-01

Digital terrain model (DTM) generation is the fundamental application of airborne Lidar data. In past decades, a large body of studies has been conducted to present and experiment a variety of DTM generation methods. Although great progress has been made, DTM generation, especially DTM generation in specific terrain situations, remains challenging. This research introduces the general principles of DTM generation and reviews diverse mainstream DTM generation methods. In accordance with the filtering strategy, these methods are classified into six categories: surface-based adjustment; morphology-based filtering, triangulated irregular network (TIN)-based refinement, segmentation and classification, statistical analysis and multi-scale comparison. Typical methods for each category are briefly introduced and the merits and limitations of each category are discussed accordingly. Despite different categories of filtering strategies, these DTM generation methods present similar difficulties when implemented in sharply changing terrain, areas with dense non-ground features and complicated landscapes. This paper suggests that the fusion of multi-sources and integration of different methods can be effective ways for improving the performance of DTM generation. PMID:28098810

Geomorphological mapping of shallow landslides using UAVs

Science.gov (United States)

Fiorucci, Federica; Giordan, Daniele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto

2015-04-01

The mapping of event shallow landslides is a critical activity, due to the large number of phenomena, mostly with small dimension, affecting extensive areas. This is commonly done through aerial photo-interpretation or through field surveys. Nowadays, landslide maps can be realized exploiting other methods/technologies: (i) airborne LiDARs, (ii) stereoscopic satellite images, and (iii) unmanned aerial vehicles (UAVs). In addition to the landslide maps, these methods/technologies allow the generation of updated Digital Terrain Models (DTM). In December 2013, in the Collazzone area (Umbria, Central Italy), an intense rainfall event triggered a large number of shallow landslides. To map the landslides occurred in the area, we exploited data and images obtained through (A) an airborne LiDAR survey, (B) a remote controlled optocopter (equipped with a Canon EOS M) survey, and (C) a stereoscopic satellite WorldView II MS. To evaluate the mapping accuracy of these methods, we select two landslides and we mapped them using a GPS RTK instrumentation. We consider the GPS survey as the benchmark being the most accurate system. The results of the comparison allow to highlight pros and cons of the methods/technologies used. LiDAR can be considered the most accurate system and in addition it allows the extraction and the classification of the digital surface models from the surveyed point cloud. Conversely, LiDAR requires additional time for the flight planning, and specific data analysis user capabilities. The analysis of the satellite WorldView II MS images facilitates the landslide mapping over large areas, but at the expenses of a minor resolution to detect the smaller landslides and their boundaries. UAVs can be considered the cheapest and fastest solution for the acquisition of high resolution ortho-photographs on limited areas, and the best solution for a multi-temporal analysis of specific landslide phenomena. Limitations are due to (i) the needs of optimal climatic

Airborne lidar detection of an underwater thermal vent

Science.gov (United States)

Roddewig, Michael R.; Churnside, James H.; Shaw, Joseph A.

2017-07-01

We report the lidar detection of an underwater feature that appears to be a thermal vent in Yellowstone Lake, Yellowstone National Park, USA, with the Montana State University Fish Lidar. The location of the detected vent was 30 m from the closest vent identified in a United States Geological Survey of Yellowstone Lake in 2008. A second possible vent is also presented, and the appearance of both vents in the lidar data is compared to descriptions of underwater thermal vents in Yellowstone Lake from the geological literature.

2003 Oahu Coastline Lidar

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser rangefinding, GPS positioning...

G-LiHT: Goddard's LiDAR, Hyperspectral and Thermal Airborne Imager

Science.gov (United States)

Cook, Bruce; Corp, Lawrence; Nelson, Ross; Morton, Douglas; Ranson, Kenneth J.; Masek, Jeffrey; Middleton, Elizabeth

2012-01-01

in the CONUS and Mexico in support of NASA's Carbon Monitoring System (CMS) and AMIGA-Carb (AMerican Icesat Glas Assessment of Carbon). For NASA's CMS, wall-to-wall G-LiHT data have been acquired over intensive study sites with historic LiDAR datasets, dense inventory data, stem maps and flux tower observations. For AMIGA-Carb, G-LiHT transects have been acquired over ICESat tracks and USDA-FS inventory plots throughout the CONUS, and similar data will be acquired in Mexico during 2013. This talk will highlight recent science results from continental-scale transects landscape-scale deployments of G-LiHT, as well as seasonal forest dynamics from repeat pass G-LiHT acquisitions.

2006 FEMA New Jersey Flood Mitigation Lidar: Highlands Area

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. LiDAR was flown for...

Impact of pitch angle fluctuations on airborne lidar forward sensing along the flight direction

Science.gov (United States)

Sergeevich Gurvich, Alexander; Alexeevich Kulikov, Victor

2017-10-01

Airborne lidar forward sensing along the flight direction can serve for notification of clear air turbulence (CAT) and help to prevent injuries or fatal air accidents. The validation of this concept was presented in the framework of the DELICAT (DEmonstration of LIdar-based CAT detection) project. However, the strong variations in signal level, which were observed during the DELICAT measurements but not explained, sometimes indicated the need of a better understanding the observational errors due to geometrical factors. In this paper, we discuss possible error sources pertinent to this technique, related to fluctuations of the flight parameters, which may lead to strong signal variations caused by the random deviations of the sensing beam from the forward flight trajectory. We analyze the variations in backscattered lidar signal caused by fluctuations of the most important forward-sensing flight parameter, the pitch angle. The fluctuation values considered in the paper correspond to the error limits of the compensational gyro platform used in civil aviation. The part of the pitch angle fluctuations not compensated for by the beam-steering device in the presence of aerosol concentration variations can lead to noticeable signal variations that can be mistakenly attributed to wind shear, turbulence, or fast evolution of the aerosol layer. We formulate the criteria that allow the recognition of signal variations caused by pitch angle fluctuations. Influence of these fluctuations is shown to be stronger for aerosol variations on smaller vertical scales. An example of DELICAT observations indicating a noticeable pitch angle fluctuation impact is presented.

Impact of pitch angle fluctuations on airborne lidar forward sensing along the flight direction

Directory of Open Access Journals (Sweden)

A. S. Gurvich

2017-10-01

Full Text Available Airborne lidar forward sensing along the flight direction can serve for notification of clear air turbulence (CAT and help to prevent injuries or fatal air accidents. The validation of this concept was presented in the framework of the DELICAT (DEmonstration of LIdar-based CAT detection project. However, the strong variations in signal level, which were observed during the DELICAT measurements but not explained, sometimes indicated the need of a better understanding the observational errors due to geometrical factors. In this paper, we discuss possible error sources pertinent to this technique, related to fluctuations of the flight parameters, which may lead to strong signal variations caused by the random deviations of the sensing beam from the forward flight trajectory. We analyze the variations in backscattered lidar signal caused by fluctuations of the most important forward-sensing flight parameter, the pitch angle. The fluctuation values considered in the paper correspond to the error limits of the compensational gyro platform used in civil aviation. The part of the pitch angle fluctuations not compensated for by the beam-steering device in the presence of aerosol concentration variations can lead to noticeable signal variations that can be mistakenly attributed to wind shear, turbulence, or fast evolution of the aerosol layer. We formulate the criteria that allow the recognition of signal variations caused by pitch angle fluctuations. Influence of these fluctuations is shown to be stronger for aerosol variations on smaller vertical scales. An example of DELICAT observations indicating a noticeable pitch angle fluctuation impact is presented.

A Multi-temporal Analysis of Logging Impacts on Tropical Forest Structure Using Airborne Lidar Data

Science.gov (United States)

Keller, M. M.; Pinagé, E. R.; Duffy, P.; Longo, M.; dos-Santos, M. N.; Leitold, V.; Morton, D. C.

2017-12-01

The long-term impacts of selective logging on carbon cycling and ecosystem function in tropical-forests are still uncertain. Despite improvements in selective logging detection using satellite data, quantifying changes in forest structure from logging and recovery following logging is difficult using orbital data. We analyzed the dynamics of forest structure comparing logged and unlogged forests in the Eastern Brazilian Amazon (Paragominas Municipality, Pará State) using small footprint discrete return airborne lidar data acquired in 2012 and 2014. Logging operations were conducted at the 1200 ha study site from 2006 through 2013 using reduced impact logging techniques—management practices that minimize canopy and ground damage compared to more common conventional logging. Nevertheless, logging still reduced aboveground biomass by 10% to 20% in logged areas compared to intact forests. We aggregated lidar point-cloud data at spatial scales ranging from 50 m to 250 m and developed a binomial classification model based on the height distribution of lidar returns in 2012 and validated the model against the 2014 lidar acquisition. We accurately classified intact and logged forest classes compared with field data. Classification performance improved as spatial resolution increased (AUC = 0.974 at 250 m). We analyzed the differences in canopy gaps, understory damage (based on a relative density model), and biomass (estimated from total canopy height) of intact and logged classes. As expected, logging greatly increased both canopy gap formation and understory damage. However, while the area identified as canopy gap persisted for at least 8 years (from the oldest logging treatments in 2006 to the most recent lidar acquisition in 2014), the effects of ground damage were mostly erased by vigorous understory regrowth after about 5 years. The rate of new gap formation was 6 to 7 times greater in recently logged forests compared to undisturbed forests. New gaps opened at a

Coastal and tidal landform detection from high resolution topobathymetric LiDAR data

Science.gov (United States)

Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

2016-04-01

Coastal and tidal environments are valuable ecosystems, which, however, are under pressure in many areas around the world due to globalisation and/or climate change. Detailed mapping of these environments is required in order to manage the coastal zone in a sustainable way. However, historically these transition zones between land and water are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. The new generation of airborne topobathymetric light detection and ranging (LiDAR) potentially enables full-coverage and high-resolution mapping of these land-water transition zones. We have carried out topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the LiDAR point cloud with a mean point density in the order of 20 points/m2. The DEM was analysed morphometrically using a modification of the tool Benthic Terrain Modeler (BTM) developed by Wright et al. (2005). Initially, stage (the elevation in relation to tidal range) was used to divide the area of investigation into the different tidal zones, i.e. subtidal, intertidal and supratidal. Subsequently, morphometric units were identified and characterised by a combination of statistical neighbourhood analysis with varying window sizes (using the Bathymetric Positioning Index (BPI) from the BTM, moving average and standard deviation), slope parameters and area/perimeter ratios. Finally, these morphometric units were classified into six different types of landforms based on their stage and morphometric characteristics, i.e. either subtidal channel, intertidal flat, intertidal creek, linear bar, swash bar or beach dune. We hereby demonstrate the potential of using airborne topobathymetric LiDAR for seamless mapping of land

Identifying Methane Sources with an Airborne Pulsed IPDA Lidar System Operating near 1.65 µm

Science.gov (United States)

Yerasi, A.; Bartholomew, J.; Tandy, W., Jr.; Emery, W. J.

2016-12-01

Methane is a powerful greenhouse gas that is predicted to play an important role in future global climate trends. It would therefore be beneficial to locate areas that produce methane in significant amounts so that these trends can be better understood. In this investigation, some initial performance test results of a lidar system called the Advanced Leak Detector Lidar - Natural Gas (ALDL-NG) are discussed. The feasibility of applying its fundamental principle of operation to methane source identification is also explored. The ALDL-NG was originally created by the Ball Aerospace & Technologies Corp. to reveal leaks emanating from pipelines that transport natural gas, which is primarily composed of methane. It operates in a pulsed integrated path differential absorption (IPDA) configuration and it is carried by a piloted, single-engine aircraft. In order to detect the presence of natural gas leaks, the laser wavelengths of its online and offline channels operate in the 1.65 µm region. The functionality of the ALDL-NG was tested during a recent field campaign in Colorado. It was determined that the ambient concentration of methane in the troposphere ( 1.8 ppm) could indeed be retrieved from ALDL-NG data with a lower-than-expected uncertainty ( 0.2 ppm). Furthermore, when the ALDL-NG scanned over areas that were presumed to be methane sources (feedlots, landfills, etc.), significantly higher concentrations of methane were retrieved. These results are intriguing because the ALDL-NG was not specifically designed to observe anything beyond natural gas pipelines. Nevertheless, they strongly indicate that utilizing an airborne pulsed IPDA lidar system operating near 1.65 µm may very well be a viable technique for identifying methane sources. Perhaps future lidar systems could build upon the heritage of the ALDL-NG and measure methane concentration with even better precision for a variety of scientific applications.

Processing and evaluation of riverine waveforms acquired by an experimental bathymetric LiDAR

Science.gov (United States)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.

2010-12-01

Accurate mapping of fluvial environments with airborne bathymetric LiDAR is challenged not only by environmental characteristics but also the development and application of software routines to post-process the recorded laser waveforms. During a bathymetric LiDAR survey, the transmission of the green-wavelength laser pulses through the water column is influenced by a number of factors including turbidity, the presence of organic material, and the reflectivity of the streambed. For backscattered laser pulses returned from the river bottom and digitized by the LiDAR detector, post-processing software is needed to interpret and identify distinct inflections in the reflected waveform. Relevant features of this energy signal include the air-water interface, volume reflection from the water column itself, and, ideally, a strong return from the bottom. We discuss our efforts to acquire, analyze, and interpret riverine surveys using the USGS Experimental Advanced Airborne Research LiDAR (EAARL) in a variety of fluvial environments. Initial processing of data collected in the Trinity River, California, using the EAARL Airborne Lidar Processing Software (ALPS) highlighted the difficulty of retrieving a distinct bottom signal in deep pools. Examination of laser waveforms from these pools indicated that weak bottom reflections were often neglected by a trailing edge algorithm used by ALPS to process shallow riverine waveforms. For the Trinity waveforms, this algorithm had a tendency to identify earlier inflections as the bottom, resulting in a shallow bias. Similarly, an EAARL survey along the upper Colorado River, Colorado, also revealed the inadequacy of the trailing edge algorithm for detecting weak bottom reflections. We developed an alternative waveform processing routine by exporting digitized laser waveforms from ALPS, computing the local extrema, and fitting Gaussian curves to the convolved backscatter. Our field data indicate that these techniques improved the

Increasing the Impact of High-Resolution Lidar Topography Through Online Data Access and Processing

Science.gov (United States)

Crosby, C. J.; Nandigam, V.; Baru, C.; Arrowsmith, R.

2013-12-01

Topography data acquired with lidar (light detection and ranging) technology are revolutionizing the way we study the Earth's surface and overlying vegetation. These data, collected from satellite, airborne, tripod, or mobile-mounted scanners have emerged as a fundamental tool for research on topics including earthquake hazards, hillslope processes, and cyrosphere change. The U.S. National Science Foundation-funded OpenTopography (OT) Facility (http://www.opentopography.org) is a web-based system designed to democratize access to earth science-oriented lidar topography data. OT provides free, online access to lidar data in a number of forms, including the point cloud and associated geospatial-processing tools for customized analysis. The point cloud data are co-located with on-demand processing tools to generate digital elevation models, and derived products and visualizations which allow users to quickly access data in a format appropriate for their scientific application. The OT system is built using a service-oriented architecture (SOA) that leverages cyberinfrastructure resources at the San Diego Supercomputer Center at the University of California San Diego to allow users, regardless of expertise, to access these massive lidar datasets and derived raster data products for use in research and teaching. OT hosts over 600 billion lidar returns covering more than 120,000 km2. These data are provided by a variety of partners under joint agreements and memoranda of understanding with OT. Partners include national facilities such as the NSF-funded National Center for Airborne Lidar Mapping (NCALM), as well as non-governmental organizations and local, state, and federal agencies. OT has become a hub for high-resolution topography resources. Datasets hosted by other organizations, as well as lidar-specific software, can be registered into the OT catalog, providing users a 'one-stop shop' for such information. OT is also a partner on the NASA Lidar Access System (NLAS

Big data; sensor networks and remotely-sensed data for mapping; feature extraction from lidar

Science.gov (United States)

Tlhabano, Lorato

2018-05-01

Unmanned aerial vehicles (UAVs) can be used for mapping in the close range domain, combining aerial and terrestrial photogrammetry and now the emergence of affordable platforms to carry these technologies has opened up new opportunities for mapping and modeling cadastral boundaries. At the current state mainly low cost UAVs fitted with sensors are used in mapping projects with low budgets, the amount of data produced by the UAVs can be enormous hence the need for big data techniques' and concepts. The past couple of years have witnessed the dramatic rise of low-cost UAVs fitted with high tech Lidar sensors and as such the UAVS have now reached a level of practical reliability and professionalism which allow the use of these systems as mapping platforms. UAV based mapping provides not only the required accuracy with respect to cadastral laws and policies as well as requirements for feature extraction from the data sets and maps produced, UAVs are also competitive to other measurement technologies in terms of economic aspects. In the following an overview on how the various technologies of UAVs, big data concepts and lidar sensor technologies can work together to revolutionize cadastral mapping particularly in Africa and as a test case Botswana in particular will be used to investigate these technologies. These technologies can be combined to efficiently provide cadastral mapping in difficult to reach areas and over large areas of land similar to the Land Administration Procedures, Capacity and Systems (LAPCAS) exercise which was recently undertaken by the Botswana government, we will show how the uses of UAVS fitted with lidar sensor and utilizing big data concepts could have reduced not only costs and time for our government but also how UAVS could have provided more detailed cadastral maps.

High-Rate Data-Capture for an Airborne Lidar System

Science.gov (United States)

Valett, Susan; Hicks, Edward; Dabney, Philip; Harding, David

2012-01-01

A high-rate data system was required to capture the data for an airborne lidar system. A data system was developed that achieved up to 22 million (64-bit) events per second sustained data rate (1408 million bits per second), as well as short bursts (less than 4 s) at higher rates. All hardware used for the system was off the shelf, but carefully selected to achieve these rates. The system was used to capture laser fire, single-photon detection, and GPS data for the Slope Imaging Multi-polarization Photo-counting Lidar (SIMPL). However, the system has applications for other laser altimeter systems (waveform-recording), mass spectroscopy, xray radiometry imaging, high-background- rate ranging lidar, and other similar areas where very high-speed data capture is needed. The data capture software was used for the SIMPL instrument that employs a micropulse, single-photon ranging measurement approach and has 16 data channels. The detected single photons are from two sources those reflected from the target and solar background photons. The instrument is non-gated, so background photons are acquired for a range window of 13 km and can comprise many times the number of target photons. The highest background rate occurs when the atmosphere is clear, the Sun is high, and the target is a highly reflective surface such as snow. Under these conditions, the total data rate for the 16 channels combined is expected to be approximately 22 million events per second. For each photon detection event, the data capture software reads the relative time of receipt, with respect to a one-per-second absolute time pulse from a GPS receiver, from an event timer card with 0.1-ns precision, and records that information to a RAID (Redundant Array of Independent Disks) storage device. The relative time of laser pulse firings must also be read and recorded with the same precision. Each of the four event timer cards handles the throughput from four of the channels. For each detection event, a flag is

Estimating forest biomass and identifying low-intensity logging areas using airborne scanning lidar in Antimary State Forest, Acre State, Western Brazilian Amazon

Science.gov (United States)

Marcus V.N. d' Oliveira; Stephen E. Reutebuch; Robert J. McGaughey; Hans-Erik. Andersen

2012-01-01

The objectives of this study were to estimate above ground forest biomass and identify areas disturbed by selective logging in a 1000 ha Brazilian tropical forest in the Antimary State Forest using airborne lidar data. The study area consisted of three management units, two of which were unlogged, while the third unit was selectively logged at a low intensity. A...

Evaluating UAV and LiDAR Retrieval of Snow Depth in a Coniferous Forest in Arizona

Science.gov (United States)

Van Leeuwen, W. J. D.; Broxton, P.; Biederman, J. A.

2017-12-01

Remote sensing of snow depth and cover in forested environments is challenging. Trees interfere with the remote sensing of snowpack below the canopy and cause large variations in the spatial distribution of the snowpack itself (e.g. between below canopy environments to shaded gaps to open clearings). The distribution of trees and topographic variation make it challenging to monitor the snowpack with in-situ observations. Airborne LiDAR has improved our ability to monitor snowpack over large areas in montane and forested environments because of its high sampling rate and ability to penetrate the canopy. However, these LiDAR flights can be too expensive and time-consuming to process, making it hard to use them for real-time snow monitoring. In this research, we evaluate Structure from Motion (SfM) as an alternative to Airborne LiDAR to generate high-resolution snow depth data in forested environments. This past winter, we conducted a snow field campaign over Arizona's Mogollon Rim where we acquired aerial LiDAR, multi-angle aerial photography from a UAV, and extensive field observations of snow depth at two sites. LiDAR and SFM derived snow depth maps were generated by comparing "snow-on" and "snow-off" LiDAR and SfM data. The SfM- and LiDAR-generated snow depth maps were similar at a site with fewer trees, though there were more discrepancies at a site with more trees. Both compared reasonably well with the field observations at the sparser forested site, with poorer agreement at the denser forested site. Finally, although the SfM produced point clouds with much higher point densities than the aerial LiDAR, the SfM was not able to produce meaningful snow depth estimates directly underneath trees and had trouble in areas with deep shadows. Based on these findings, we are optimizing our UAV data acquisition strategies for this upcoming field season. We are using these data, along with high-resolution hydrological modeling, to gain a better understanding of how

Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar

Science.gov (United States)

Chen, Qi

2015-08-01

Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.

Remote identification of potential polar bear maternal denning habitat in northern Alaska using airborne LiDAR

Science.gov (United States)

Jones, B. M.; Durner, G. M.; Stoker, J.; Shideler, R.; Perham, C.; Liston, G. E.

2013-12-01

Polar bear (Ursus maritimus) populations throughout the Arctic are being threatened by reductions in critical sea ice habitat. Throughout much of their range, polar bears give birth to their young in winter dens that are excavated in snowdrifts. New-born cubs, which are unable to survive exposure to Arctic winter weather, require 2-3 months of the relatively warm, stable, and undisturbed environment of the den for their growth. In the southern Beaufort Sea (BS), polar bears may den on the Alaskan Arctic Coastal Plain (ACP).The proportion of dens occurring on land has increased because of reductions in stable multi-year ice, increases in unconsolidated ice, and lengthening of the fall open-water period. Large portions of the ACP are currently being used for oil and gas activities and proposed projects will likely expand this footprint in the near future. Since petroleum exploration and development activities increase during winter there is the potential for human activities to disturb polar bears in maternal dens. Thus, maps showing the potential distribution of terrestrial denning habitat can help to mitigate negative interactions. Prior remote sensing efforts have consisted of manual interpretation of vertical aerial photography and automated classification of Interferometric Synthetic Aperture (IfSAR) derived digital terrain models (DTM) (5-m spatial resolution) focused on the identification of snowdrift forming landscape features. In this study, we assess the feasibility of airborne Light Detection and Ranging (LiDAR) data (2-m spatial resolution) for the automated classification of potential polar bear maternal denning habitat in a 1,400 km2 area on the central portion of the ACP. The study region spans the BS coast from the Prudhoe Bay oilfield in the west to near Point Thompson in the east and extends inland from 10 to 30 km. Approximately 800 km2 of the study area contains 19 known den locations, 51 field survey sites with information on bank height and

The application of LiDAR to investigate foredune morphology and vegetation

Science.gov (United States)

Doyle, Thomas B.; Woodroffe, Colin D.

2018-02-01

LiDAR (Light Detection and Ranging) has been used to investigate coastal landform morphology, evolution, and change for almost a decade. Repeated airborne LiDAR surveys can provide the scientific community with significant observations of how shorelines have evolved, which may then enable forecasts of future patterns of change. However, there have been few studies that have considered the application of this new technology to the specific study of foredune morphology and vegetation. The accuracy and appropriateness of airborne LiDAR needs to be assessed, particularly where the density of vegetation may obscure the underlying topography, prior to interpreting derived geomorphic features. This study: i) tests the vertical accuracy of airborne LiDAR in 37 foredune systems along the coast of south-eastern Australia, and ii) demonstrates that it can be used to describe foredune morphology and vegetation in considerable detail. There was a strong correlation between the remotely-sensed LiDAR-derived elevation and field topographic and vegetation surveys (R2 = 0.96). A protocol for obtaining foredune geomorphic and botanical parameters is described. It enables widespread biogeomorphic characterisation along coasts for which LiDAR data is available, which can benefit both coastal managers and researchers alike.

Iowa LiDAR Mapping Project

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — This is collection level metadata for LAS and ASCII data files from the statewide Iowa Lidar Project. The Iowa Light Detection and Ranging (LiDAR) Project collects...

Towards Automation in Landcover Mapping from LiDAR Data in Alpine Environment

Science.gov (United States)

Dorninger, Peter; Briese, Christian; Nothegger, Clemens; Klauser, Armin

2010-05-01

Digital terrain models derived from airborne LiDAR (often referred to as airborne laser scanning) are commonly used for various applications in geomorphology. The ongoing development in sensor technology makes flight campaigns with some 10 points per square meter economically feasible for large areas. Simultaneously, the achievable accuracy of the originally acquired points as well as those of the derived products increases due to improved measurement techniques. Additionally, full-waveform (FWF) laser scanning systems record the time-dependent strength of the backscattered signal. This allows for the determination of numerous points (i.e. echoes) for one emitted laser beam hitting multiple targets within its footprint. Practically, about five echoes may be determined from the digitized signal form. Furthermore, additional attributes can be determined for each echo. These are, for example, a reflectivity measure (amplitude), the widening of the echo (echo width), or the sequence of the echoes of a single shot. By considering the polar measurement range and atmospheric conditions, a physical calibration of such measurements is possible. The application of FWF information to increase the accuracy and the reliability of digital terrain models especially in areas with dense vegetation was shown by Doneus & Briese (2006). However, these additional attributes are rarely used for object or landcover classification. This is still the domain of automated image interpretation (e.g. Zebedin et al., 2006). Nevertheless, image interpretation has well known deficiencies in areas with vegetation or if shadows occur. Therefore, we tested a hybrid approach which uses conventional first echo / last echo (FE/LE) airborne laser scanning data (first and last pulse) and an RGB-orthophoto. The testing site is located in an alpine area in Tyrol, Austria. For the classification, topographic models, a slope map, a local roughness measure and a penetration ratio were determined from the

Parameter identification of JONSWAP spectrum acquired by airborne LIDAR

Science.gov (United States)

Yu, Yang; Pei, Hailong; Xu, Chengzhong

2017-12-01

In this study, we developed the first linear Joint North Sea Wave Project (JONSWAP) spectrum (JS), which involves a transformation from the JS solution to the natural logarithmic scale. This transformation is convenient for defining the least squares function in terms of the scale and shape parameters. We identified these two wind-dependent parameters to better understand the wind effect on surface waves. Due to its efficiency and high-resolution, we employed the airborne Light Detection and Ranging (LIDAR) system for our measurements. Due to the lack of actual data, we simulated ocean waves in the MATLAB environment, which can be easily translated into industrial programming language. We utilized the Longuet-Higgin (LH) random-phase method to generate the time series of wave records and used the fast Fourier transform (FFT) technique to compute the power spectra density. After validating these procedures, we identified the JS parameters by minimizing the mean-square error of the target spectrum to that of the estimated spectrum obtained by FFT. We determined that the estimation error is relative to the amount of available wave record data. Finally, we found the inverse computation of wind factors (wind speed and wind fetch length) to be robust and sufficiently precise for wave forecasting.

Lidar-enhanced geologic mapping, examples from the Medford and Hood River areas, Oregon

Science.gov (United States)

Wiley, T. J.; McClaughry, J. D.

2012-12-01

Lidar-based 3-foot digital elevation models (DEMs) and derivatives (slopeshade, hillshade, contours) were used to help map geology across 1700 km2 (650 mi2) near Hood River and Medford, Oregon. Techniques classically applied to interpret coarse DEMs and small-scale topographic maps were adapted to take advantage of lidar's high resolution. Penetration and discrimination of plant cover by the laser system allowed recognition of fine patterns and textures related to underlying geologic units and associated soils. Surficial geologic maps were improved by the ability to examine tiny variations in elevation and slope. Recognition of low-relief features of all sizes was enhanced where pixel elevation ranges of centimeters to meters, established by knowledge of the site or by trial, were displayed using thousands of sequential colors. Features can also be depicted relative to stream level by preparing a DEM that compensates for gradient. Near Medford, lidar-derived contour maps with 1- to 3-foot intervals revealed incised bajada with young, distal lobes defined by concentric contour lines. Bedrock geologic maps were improved by recognizing geologic features associated with surface textures and patterns or topographic anomalies. In sedimentary and volcanic terrain, structure was revealed by outcrops or horizons lying at one stratigraphic level. Creating a triangulated irregular network (TIN) facet from positions of three or more such points gives strike and dip. Each map area benefited from hundreds of these measurements. A more extensive DEM in the plane of the TIN facet can be subtracted from surface elevation (lidar DEM) to make a DEM with elevation zero where the stratigraphic horizon lies at the surface. The distribution of higher and lower stratigraphic horizons can be shown by highlighting areas similarly higher or lower on the same DEM. Poor fit of contacts or faults projected between field traverses suggest the nature and amount of intervening geologic structure

Improved progressive morphological filter for digital terrain model generation from airborne lidar data.

Science.gov (United States)

Hui, Zhenyang; Wu, Beiping; Hu, Youjian; Ziggah, Yao Yevenyo

2017-12-01

Obtaining high-precision filtering results from airborne lidar point clouds in complex environments has always been a hot topic. Mathematical morphology was widely used for filtering, owing to its simplicity and high efficiency. However, the morphology-based algorithms are deficient in preserving terrain details. In order to obtain a better filtering effect, this paper proposed an improved progressive morphological filter based on hierarchical radial basis function interpolation (PMHR) to refine the classical progressive morphological filter. PMHR involved two main improvements, namely, automatic setting of self-adaptive thresholds and terrain details preservation, respectively. The performance of PMHR was evaluated using datasets provided by the International Society for Photogrammetry and Remote Sensing. Experimental results show that PMHR achieved good performance under variant terrain features with an average total error of 4.27% and average Kappa coefficient of 84.57%.

APPLICABILITY ANALYSIS OF CLOTH SIMULATION FILTERING ALGORITHM FOR MOBILE LIDAR POINT CLOUD

Directory of Open Access Journals (Sweden)

S. Cai

2018-04-01

Full Text Available Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging data post-processing. Cloth simulation filtering (CSF algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM, 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

Quantification of Greenhouse Gas Emission Rates from strong Point Sources by Airborne IPDA-Lidar Measurements: Methodology and Experimental Results

Science.gov (United States)

Ehret, G.; Amediek, A.; Wirth, M.; Fix, A.; Kiemle, C.; Quatrevalet, M.

2016-12-01

We report on a new method and on the first demonstration to quantify emission rates from strong greenhouse gas (GHG) point sources using airborne Integrated Path Differential Absorption (IPDA) Lidar measurements. In order to build trust in the self-reported emission rates by countries, verification against independent monitoring systems is a prerequisite to check the reported budget. A significant fraction of the total anthropogenic emission of CO2 and CH4 originates from localized strong point sources of large energy production sites or landfills. Both are not monitored with sufficiently accuracy by the current observation system. There is a debate whether airborne remote sensing could fill in the gap to infer those emission rates from budgeting or from Gaussian plume inversion approaches, whereby measurements of the GHG column abundance beneath the aircraft can be used to constrain inverse models. In contrast to passive sensors, the use of an active instrument like CHARM-F for such emission verification measurements is new. CHARM-F is a new airborne IPDA-Lidar devised for the German research aircraft HALO for the simultaneous measurement of the column-integrated dry-air mixing ratio of CO2 and CH4 commonly denoted as XCO2 und XCH4, respectively. It has successfully been tested in a serious of flights over Central Europe to assess its performance under various reflectivity conditions and in a strongly varying topography like the Alps. The analysis of a methane plume measured in crosswind direction of a coal mine ventilation shaft revealed an instantaneous emission rate of 9.9 ± 1.7 kt CH4 yr-1. We discuss the methodology of our point source estimation approach and give an outlook on the CoMet field experiment scheduled in 2017 for the measurement of anthropogenic and natural GHG emissions by a combination of active and passive remote sensing instruments on research aircraft.

Experimental Advanced Airborne Research Lidar (EAARL) Data Processing Manual

Science.gov (United States)

Bonisteel, Jamie M.; Nayegandhi, Amar; Wright, C. Wayne; Brock, John C.; Nagle, David

2009-01-01

The Experimental Advanced Airborne Research Lidar (EAARL) is an example of a Light Detection and Ranging (Lidar) system that utilizes a blue-green wavelength (532 nanometers) to determine the distance to an object. The distance is determined by recording the travel time of a transmitted pulse at the speed of light (fig. 1). This system uses raster laser scanning with full-waveform (multi-peak) resolving capabilities to measure submerged topography and adjacent coastal land elevations simultaneously (Nayegandhi and others, 2009). This document reviews procedures for the post-processing of EAARL data using the custom-built Airborne Lidar Processing System (ALPS). ALPS software was developed in an open-source programming environment operated on a Linux platform. It has the ability to combine the laser return backscatter digitized at 1-nanosecond intervals with aircraft positioning information. This solution enables the exploration and processing of the EAARL data in an interactive or batch mode. ALPS also includes modules for the creation of bare earth, canopy-top, and submerged topography Digital Elevation Models (DEMs). The EAARL system uses an Earth-centered coordinate and reference system that removes the necessity to reference submerged topography data relative to water level or tide gages (Nayegandhi and others, 2006). The EAARL system can be mounted in an array of small twin-engine aircraft that operate at 300 meters above ground level (AGL) at a speed of 60 meters per second (117 knots). While other systems strive to maximize operational depth limits, EAARL has a narrow transmit beam and receiver field of view (1.5 to 2 milliradians), which improves the depth-measurement accuracy in shallow, clear water but limits the maximum depth to about 1.5 Secchi disk depth (~20 meters) in clear water. The laser transmitter [Continuum EPO-5000 yttrium aluminum garnet (YAG)] produces up to 5,000 short-duration (1.2 nanosecond), low-power (70 microjoules) pulses each second

Comparison of the filtering models for airborne LiDAR data by three classifiers with exploration on model transfer

Science.gov (United States)

Ma, Hongchao; Cai, Zhan; Zhang, Liang

2018-01-01

This paper discusses airborne light detection and ranging (LiDAR) point cloud filtering (a binary classification problem) from the machine learning point of view. We compared three supervised classifiers for point cloud filtering, namely, Adaptive Boosting, support vector machine, and random forest (RF). Nineteen features were generated from raw LiDAR point cloud based on height and other geometric information within a given neighborhood. The test datasets issued by the International Society for Photogrammetry and Remote Sensing (ISPRS) were used to evaluate the performance of the three filtering algorithms; RF showed the best results with an average total error of 5.50%. The paper also makes tentative exploration in the application of transfer learning theory to point cloud filtering, which has not been introduced into the LiDAR field to the authors' knowledge. We performed filtering of three datasets from real projects carried out in China with RF models constructed by learning from the 15 ISPRS datasets and then transferred with little to no change of the parameters. Reliable results were achieved, especially in rural area (overall accuracy achieved 95.64%), indicating the feasibility of model transfer in the context of point cloud filtering for both easy automation and acceptable accuracy.

Neural networks for the generation of sea bed models using airborne lidar bathymetry data

Science.gov (United States)

Kogut, Tomasz; Niemeyer, Joachim; Bujakiewicz, Aleksandra

2016-06-01

Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project `Investigation on the use of airborne laser bathymetry in hydrographic surveying'. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW), Delaunay Triangulation (TIN), and supervised Artificial Neural Networks (ANN), for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

Neural networks for the generation of sea bed models using airborne lidar bathymetry data

Directory of Open Access Journals (Sweden)

Kogut Tomasz

2016-06-01

Full Text Available Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project ‘Investigation on the use of airborne laser bathymetry in hydrographic surveying’. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW, Delaunay Triangulation (TIN, and supervised Artificial Neural Networks (ANN, for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

Systematic variations in multi-spectral lidar representations of canopy height profiles and gap probability

Science.gov (United States)

Chasmer, L.; Hopkinson, C.; Gynan, C.; Mahoney, C.; Sitar, M.

2015-12-01

Airborne and terrestrial lidar are increasingly used in forest attribute modeling for carbon, ecosystem and resource monitoring. The near infra-red wavelength at 1064nm has been utilised most in airborne applications due to, for example, diode manufacture costs, surface reflectance and eye safety. Foliage reflects well at 1064nm and most of the literature on airborne lidar forest structure is based on data from this wavelength. However, lidar systems also operate at wavelengths further from the visible spectrum (e.g. 1550nm) for eye safety reasons. This corresponds to a water absorption band and can be sensitive to attenuation if surfaces contain moisture. Alternatively, some systems operate in the visible range (e.g. 532nm) for specialised applications requiring simultaneous mapping of terrestrial and bathymetric surfaces. All these wavelengths provide analogous 3D canopy structure reconstructions and thus offer the potential to be combined for spatial comparisons or temporal monitoring. However, a systematic comparison of wavelength-dependent foliage profile and gap probability (index of transmittance) is needed. Here we report on two multispectral lidar missions carried out in 2013 and 2015 over conifer, deciduous and mixed stands in Ontario, Canada. The first used separate lidar sensors acquiring comparable data at three wavelengths, while the second used a single sensor with 3 integrated laser systems. In both cases, wavelenegths sampled were 532nm, 1064nm and 1550nm. The experiment revealed significant differences in proportions of returns at ground level, the vertical foliage distribution and gap probability across wavelengths. Canopy attenuation was greatest at 532nm due to photosynthetic plant tissue absorption. Relative to 1064nm, foliage was systematically undersampled at the 10% to 60% height percentiles at both 1550nm and 532nm (this was confirmed with coincident terrestrial lidar data). When using all returns to calculate gap probability, all

Parallel Landscape Driven Data Reduction & Spatial Interpolation Algorithm for Big LiDAR Data

Directory of Open Access Journals (Sweden)

Rahil Sharma

2016-06-01

Full Text Available Airborne Light Detection and Ranging (LiDAR topographic data provide highly accurate digital terrain information, which is used widely in applications like creating flood insurance rate maps, forest and tree studies, coastal change mapping, soil and landscape classification, 3D urban modeling, river bank management, agricultural crop studies, etc. In this paper, we focus mainly on the use of LiDAR data in terrain modeling/Digital Elevation Model (DEM generation. Technological advancements in building LiDAR sensors have enabled highly accurate and highly dense LiDAR point clouds, which have made possible high resolution modeling of terrain surfaces. However, high density data result in massive data volumes, which pose computing issues. Computational time required for dissemination, processing and storage of these data is directly proportional to the volume of the data. We describe a novel technique based on the slope map of the terrain, which addresses the challenging problem in the area of spatial data analysis, of reducing this dense LiDAR data without sacrificing its accuracy. To the best of our knowledge, this is the first ever landscape-driven data reduction algorithm. We also perform an empirical study, which shows that there is no significant loss in accuracy for the DEM generated from a 52% reduced LiDAR dataset generated by our algorithm, compared to the DEM generated from an original, complete LiDAR dataset. For the accuracy of our statistical analysis, we perform Root Mean Square Error (RMSE comparing all of the grid points of the original DEM to the DEM generated by reduced data, instead of comparing a few random control points. Besides, our multi-core data reduction algorithm is highly scalable. We also describe a modified parallel Inverse Distance Weighted (IDW spatial interpolation method and show that the DEMs it generates are time-efficient and have better accuracy than the one’s generated by the traditional IDW method.

Automatically Generated Vegetation Density Maps with LiDAR Survey for Orienteering Purpose

Science.gov (United States)

Petrovič, Dušan

2018-05-01

The focus of our research was to automatically generate the most adequate vegetation density maps for orienteering purpose. Application Karttapullatuin was used for automated generation of vegetation density maps, which requires LiDAR data to process an automatically generated map. A part of the orienteering map in the area of Kazlje-Tomaj was used to compare the graphical display of vegetation density. With different settings of parameters in the Karttapullautin application we changed the way how vegetation density of automatically generated map was presented, and tried to match it as much as possible with the orienteering map of Kazlje-Tomaj. Comparing more created maps of vegetation density the most suitable parameter settings to automatically generate maps on other areas were proposed, too.

Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of Sao Paulo, Brazil

Science.gov (United States)

Carlos Alberto Silva; Carine Klauberg; Samuel de Padua Chaves e Carvalho; Andrew T. Hudak; e Luiz Carlos Estraviz. Rodriguez

2014-01-01

Fast growing plantation forests provide a low-cost means to sequester carbon for greenhouse gas abatement. The aim of this study was to evaluate airborne LiDAR (Light Detection And Ranging) to predict aboveground carbon (AGC) stocks in Eucalyptus spp. plantations. Biometric parameters (tree height (Ht) and diameter at breast height (DBH)) were collected from...

Habitat Mapping and Change Assessment of Coastal Environments: An Examination of WorldView-2, QuickBird, and IKONOS Satellite Imagery and Airborne LiDAR for Mapping Barrier Island Habitats

Directory of Open Access Journals (Sweden)

Matthew J. McCarthy

2014-03-01

Full Text Available Habitat mapping can be accomplished using many techniques and types of data. There are pros and cons for each technique and dataset, therefore, the goal of this project was to investigate the capabilities of new satellite sensor technology and to assess map accuracy for a variety of image classification techniques based on hundreds of field-work sites. The study area was Masonboro Island, an undeveloped area in coastal North Carolina, USA. Using the best map results, a habitat change assessment was conducted between 2002 and 2010. WorldView-2, QuickBird, and IKONOS satellite sensors were tested using unsupervised and supervised methods using a variety of spectral band combinations. Light Detection and Ranging (LiDAR elevation and texture data pan-sharpening, and spatial filtering were also tested. In total, 200 maps were generated and results indicated that WorldView-2 was consistently more accurate than QuickBird and IKONOS. Supervised maps were more accurate than unsupervised in 80% of the maps. Pan-sharpening the images did not consistently improve map accuracy but using a majority filter generally increased map accuracy. During the relatively short eight-year period, 20% of the coastal study area changed with intertidal marsh experiencing the most change. Smaller habitat classes changed substantially as well. For example, 84% of upland scrub-shrub experienced change. These results document the dynamic nature of coastal habitats, validate the use of the relatively new Worldview-2 sensor, and may be used to guide future coastal habitat mapping.

Multi-Beam Surface Lidar for Lunar and Planetary Mapping

Science.gov (United States)

Bufton, Jack L.; Garvin, James B.

1998-01-01

Surface lidar techniques are now being demonstrated in low Earth orbit with a single beam of pulsed laser radiation at 1064 nm that profiles the vertical structure of Earth surface landforms along the nadir track of a spacecraft. In addition, a profiling laser altimeter, called MOLA, is operating in elliptical Martian orbit and returning surface topography data. These instruments form the basis for suggesting an improved lidar instrument that employs multiple beams for extension of sensor capabilities toward the goal of true, 3-dimensional mapping of the Moon or other similar planetary surfaces. In general the lidar waveform acquired with digitization of a laser echo can be used for laser distance measurement (i.e. range-to-the-surface) by time-of-flight measurement and for surface slope and shape measurements by examining the detailed lidar waveform. This is particularly effective when the intended target is the lunar surface or another planetary body free of any atmosphere. The width of the distorted return pulse is a first order measure of the surface incidence angle, a combination of surface slope and laser beam pointing. Assuming an independent and absolute (with respect to inertial space) measurement of laser beam pointing on the spacecraft, it is possible to derive a surface slope with-respect-to the mean planetary surface or its equipotential gravity surface. Higher-order laser pulse distortions can be interpreted in terms of the vertical relief of the surface or reflectivity variations within the area of the laser beam footprint on the surface.

Modelling canopy fuel and forest stand variables and characterizing the influence of thinning in the stand structure using airborne LiDAR

Directory of Open Access Journals (Sweden)

A. Hevia

2016-02-01

Full Text Available Forest fires are a major threat in NW Spain. The importance and frequency of these events in the area suggests the need for fuel management programs to reduce the spread and severity of forest fires. Thinning treatments can contribute for fire risk reduction, because they cut off the horizontal continuity of forest fuels. Besides, it is necessary to conduct a fire risk management based on the knowledge of fuel allocation, since fire behaviour and fire spread study is dependent on the spatial factor. Therefore, mapping fuel for different silvicultural scenarios is essential. Modelling forest variables and forest structure parameters from LiDAR technology is the starting point for developing spatially explicit maps. This is essential in the generation of fuel maps since field measurements of canopy fuel variables is not feasible. In the present study, we evaluated the potential of LiDAR technology to estimate canopy fuel variables and other stand variables, as well as to identify structural differences between silvicultural managed and unmanaged P. pinaster Ait. stands. Independent variables (LiDAR metrics of greater explanatory significance were identified and regression analyses indicated strong relationships between those and field-derived variables (R2 varied between 0.86 and 0.97. Significant differences were found in some LiDAR metrics when compared thinned and unthinned stands. Results showed that LiDAR technology allows to model canopy fuel and stand variables with high precision in this species, and provides useful information for identifying areas with and without silvicultural management.

Estimation of Biomass Dynamics in Alpine Treeline Ecotone using Airborne Lidar and Repeat Photography

Science.gov (United States)

McCaffrey, D. R.; Hopkinson, C.

2016-12-01

Historic photographs provide visual records of landscapes which pre-date aerial and satellite observations, but analysis of these photographs has largely been qualitative due to varying spatial scale within an oblique image. Recent technological advances, such as the WSL monoplotting tool, provide the ability to georeference single oblique images, allowing for quantitative spatial analysis of land cover change between historic photographs and contemporary repeat photographs. The WSL monoplotting tool was used to compare alpine land cover change between 12 photographs from a 1914 survey of the West Castle valley (Alberta, Canada; 49.3° N, 114.4° W) and 12 repeat photographs, collected in 2006 by the Mountain Legacy Project. We tested for correlations between land cover shifts over the 92 year observation period and geomorphic controls (e.g. elevation, slope, aspect), with a focus on vegetative change in the alpine treeline ecotone (ATE). A model of above ground biomass was generated using an airborne lidar observation of the valley (2014) and ground validated measurements of tree height, diameter at breast height, and leaf area index from 25 plots (400 m2). By creating a high resolution map of ATE dynamics over a 92 year interval and incorporating a model of above ground biomass, the relative magnitude of anthropogenic, orographic, and climatic controls on ATE can be explored. This research provides a unique opportunity to understand the impact that continued atmospheric warming could have on vegetative boundaries in sensitive alpine systems, such as the eastern slopes of the Rocky Mountains.

Mapping and monitoring coal mine subsidence using LiDAR and InSAR

Energy Technology Data Exchange (ETDEWEB)

Froese, C.R.; Mei, S. [Alberta Geological Survey, Edmonton, AB (Canada). Energy Resources Conservation Board

2008-07-01

In the early 1900s, the abandonment of coal mines in Alberta was not regulated and closure documentation was poor. Although the general locations of mines are known, the locations of the specific adits and shafts are not. As such, there are many cases in southwestern Alberta where infrastructure was built on top of old coal mine workings without any detailed records of the abandoned mine or displacement monitoring. The crowns of these workings have been subject to ongoing strain that is reflected at the surface. The rate at which the strain is progressing prior to collapse is not well understood. Mitigation of collapse events is site specific and reactive. This paper demonstrated that airborne LiDAR and spaceborne InSAR technologies can provide valuable information on the distribution of abandoned underground coal mine workings. Both remote sensing techniques were used on Turtle Mountain in the Crowsnest Pass to obtain quantitative information on landslide mechanics, including the patterns and rate of ground movement and subsidence. These techniques can be used to map the location of surface collapse and delineate the location of the coal mine workings that were not previously documented. It was concluded that these technologies will likely become more readily available in the future and incorporated into geo-engineering practices for use in ground hazard detection, monitoring and management. 8 refs., 6 figs.

2006 FEMA Lidar: Hawaiian Islands

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The FEMA Task Order 26 LiDAR data set was collected by Airborne 1 Corporation of El Segundo, California in September - December of 2006 for URS Corp.

Hydrographic & Topographic LIDAR Acquisition, Northwest Coast, Washington State - Bathymetric Survey Data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These data were collected by the SHOALS-1000T(Scanning Hydrographic Operational Airborne Lidar Survey)system which consists of an airborne laser transmitter/receiver...

Mapping wetlands in Nova Scotia with multi-beam RADARSAT-2 Polarimetric SAR, optical satellite imagery, and Lidar data

Science.gov (United States)

Jahncke, Raymond; Leblon, Brigitte; Bush, Peter; LaRocque, Armand

2018-06-01

Wetland maps currently in use by the Province of Nova Scotia, namely the Department of Natural Resources (DNR) wetland inventory map and the swamp wetland classes of the DNR forest map, need to be updated. In this study, wetlands were mapped in an area southwest of Halifax, Nova Scotia by classifying a combination of multi-date and multi-beam RADARSAT-2 C-band polarimetric SAR (polSAR) images with spring Lidar, and fall QuickBird optical data using the Random Forests (RF) classifier. The resulting map has five wetland classes (open-water/marsh complex, open bog, open fen, shrub/treed fen/bog, swamp), plus lakes and various upland classes. Its accuracy was assessed using data from 156 GPS wetland sites collected in 2012 and compared to the one obtained with the current wetland map of Nova Scotia. The best overall classification was obtained using a combination of Lidar, RADARSAT-2 HH, HV, VH, VV intensity with polarimetric variables, and QuickBird multispectral (89.2%). The classified image was compared to GPS validation sites to assess the mapping accuracy of the wetlands. It was first done considering a group consisting of all wetland classes including lakes. This showed that only 69.9% of the wetland sites were correctly identified when only the QuickBird classified image was used in the classification. With the addition of variables derived from lidar, the number of correctly identified wetlands increased to 88.5%. The accuracy remained the same with the addition of RADARSAT-2 (88.5%). When we tested the accuracy for identifying wetland classes (e.g. marsh complex vs. open bog) instead of grouped wetlands, the resulting wetland map performed best with either QuickBird and Lidar, or QuickBird, Lidar, and RADARSAT-2 (66%). The Province of Nova Scotia's current wetland inventory and its associated wetland classes (aerial-photo interpreted) were also assessed against the GPS wetland sites. This provincial inventory correctly identified 62.2% of the grouped wetlands

Computational modeling of river flow using bathymetry collected with an experimental, water-penetrating, green LiDAR

Science.gov (United States)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.

2009-12-01

Airborne bathymetric Light Detection and Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly being deployed in fluvial environments. While the adaptation of this technology to rivers and streams would appear to be straightforward, currently technical challenges remain with regard to achieving high levels of vertical accuracy and precision when mapping bathymetry in shallow fluvial settings. Collectively these mapping errors have a direct bearing on hydraulic model predictions made using these data. We compared channel surveys conducted along the Platte River, Nebraska, and the Trinity River, California, using conventional ground-based methods with those made with the hybrid topographic/bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). In the turbid and braided Platte River, a bathymetric-waveform processing algorithm was shown to enhance the definition of thalweg channels over a more simplified, first-surface waveform processing algorithm. Consequently flow simulations using data processed with the shallow bathymetric algorithm resulted in improved prediction of wetted area relative to the first-surface algorithm, when compared to the wetted area in concurrent aerial imagery. However, when compared to using conventionally collected data for flow modeling, the inundation extent was over predicted with the EAARL topography due to higher bed elevations measured by the LiDAR. In the relatively clear, meandering Trinity River, bathymetric processing algorithms were capable of defining a 3 meter deep pool. However, a similar bias in depth measurement was observed, with the LiDAR measuring the elevation of the river bottom above its actual position, resulting in a predicted water surface higher than that measured by field data. This contribution addresses the challenge of making bathymetric measurements with the EAARL in different environmental conditions encountered in fluvial settings, explores technical issues related to

Airborne lidar reflectance measurements at 1.57 μm in support of the A-SCOPE mission for atmospheric CO2

Directory of Open Access Journals (Sweden)

J. Caron

2009-11-01

Full Text Available The characteristics of the lidar reflectance of the Earth's surface is an important issue for the IPDA lidar technique (integrated path differential absorption lidar which is the proposed method for the spaceborne measurement of atmospheric carbon dioxide within the framework of ESA's A-SCOPE project. Both, the absolute reflectance of the ground and its variations have an impact on the measurement sensitivity. The first aspect influences the instrument's signal to noise ratio, the second one can lead to retrieval errors, if the ground reflectance changes are strong on small scales. The investigation of the latter is the main purpose of this study. Airborne measurements of the lidar ground reflectance at 1.57 μm wavelength were performed in Central and Western Europe, including many typical land surface coverages as well as the open sea. The analyses of the data show, that the lidar ground reflectance is highly variable on a wide range of spatial scales. However, by means of the assumption of laser footprints in the order of several tens of meters, as planned for spaceborne systems, and by means of an averaging of the data it was shown, that this specific retrieval error is well below 1 ppm (CO2 column mixing ratio, and so compatible with the sensitivity requirements of spaceborne CO2 measurements. Several approaches for upscaling the data in terms of the consideration of larger laser footprints, compared to the one used here, are shown and discussed. Furthermore, the collected data are compared to MODIS ground reflectance data.

Airborne Lidar Measurements of Atmospheric Pressure Made Using the Oxygen A-Band

Science.gov (United States)

Riris, Haris; Rodriquez, Michael D.; Allan, Graham R.; Hasselbrack, William E.; Mao, Jianping; Stephen, Mark A.; Abshire, James B.

2012-01-01

Accurate measurements of greenhouse gas mixing ratios on a global scale are currently needed to gain a better understanding of climate change and its possible impact on our planet. In order to remotely measure greenhouse gas concentrations in the atmosphere with regard to dry air, the air number density in the atmosphere is also needed in deriving the greenhouse gas concentrations. Since oxygen is stable and uniformly mixed in the atmosphere at 20.95%, the measurement of an oxygen absorption in the atmosphere can be used to infer the dry air density and used to calculate the dry air mixing ratio of a greenhouse gas, such as carbon dioxide or methane. OUT technique of measuring Oxygen uses integrated path differential absorption (IPDA) with an Erbium Doped Fiber Amplifier (EDF A) laser system and single photon counting module (SPCM). It measures the absorbance of several on- and off-line wavelengths tuned to an O2 absorption line in the A-band at 764.7 nm. The choice of wavelengths allows us to maximize the pressure sensitivity using the trough between two absorptions in the Oxygen A-band. Our retrieval algorithm uses ancillary meteorological and aircraft altitude information to fit the experimentally obtained lidar O2 line shapes to a model atmosphere and derives the pressure from the profiles of the two lines. We have demonstrated O2 measurements from the ground and from an airborne platform. In this paper we will report on our airborne measurements during our 2011 campaign for the ASCENDS program.

Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes

Science.gov (United States)

Halligan, K. Q.; Roberts, D. A.

2006-12-01

Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation

Uncovering archaeological landscapes at Angkor using lidar.

Science.gov (United States)

Evans, Damian H; Fletcher, Roland J; Pottier, Christophe; Chevance, Jean-Baptiste; Soutif, Dominique; Tan, Boun Suy; Im, Sokrithy; Ea, Darith; Tin, Tina; Kim, Samnang; Cromarty, Christopher; De Greef, Stéphane; Hanus, Kasper; Bâty, Pierre; Kuszinger, Robert; Shimoda, Ichita; Boornazian, Glenn

2013-07-30

Previous archaeological mapping work on the successive medieval capitals of the Khmer Empire located at Angkor, in northwest Cambodia (∼9th to 15th centuries in the Common Era, C.E.), has identified it as the largest settlement complex of the preindustrial world, and yet crucial areas have remained unmapped, in particular the ceremonial centers and their surroundings, where dense forest obscures the traces of the civilization that typically remain in evidence in surface topography. Here we describe the use of airborne laser scanning (lidar) technology to create high-precision digital elevation models of the ground surface beneath the vegetation cover. We identify an entire, previously undocumented, formally planned urban landscape into which the major temples such as Angkor Wat were integrated. Beyond these newly identified urban landscapes, the lidar data reveal anthropogenic changes to the landscape on a vast scale and lend further weight to an emerging consensus that infrastructural complexity, unsustainable modes of subsistence, and climate variation were crucial factors in the decline of the classical Khmer civilization.

On the detectability of internal waves by an imaging lidar

NARCIS (Netherlands)

Magalhaes, J.M.; da Silva, J.C.B.; Batista, M.; Gostiaux, L.; Gerkema, T.; New, A.L.; Jeans, D.R.G.

2013-01-01

The first results of a multisensor airborne survey conducted off the western Iberian Coast are presented (including visible, lidar, and infrared imagery) and reveal the presence of internal solitary waves (ISWs) propagating into the nearshore region. For the first time, two-dimensional lidar imagery

Mapping snags and understory shrubs for LiDAR based assessment of wildlife habitat suitability

Science.gov (United States)

Sebastian Martinuzzi; Lee A. Vierling; William A. Gould; Michael J. Falkowski; Jeffrey S. Evans; Andrew T. Hudak; Kerri T. Vierling

2009-01-01

The lack of maps depicting forest three-dimensional structure, particularly as pertaining to snags and understory shrub species distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to remotely map snags and understory shrubs is therefore an important need. To address this, we first evaluated the use of LiDAR data for...

Alabama 2003 Lidar Coverage, USACE

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2003. The data...

TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION

Directory of Open Access Journals (Sweden)

N. Li

2016-06-01

Full Text Available Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the “raw” data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.

A 3D convolutional neural network approach to land cover classification using LiDAR and multi-temporal Landsat imagery

Science.gov (United States)

Xu, Z.; Guan, K.; Peng, B.; Casler, N. P.; Wang, S. W.

2017-12-01

Landscape has complex three-dimensional features. These 3D features are difficult to extract using conventional methods. Small-footprint LiDAR provides an ideal way for capturing these features. Existing approaches, however, have been relegated to raster or metric-based (two-dimensional) feature extraction from the upper or bottom layer, and thus are not suitable for resolving morphological and intensity features that could be important to fine-scale land cover mapping. Therefore, this research combines airborne LiDAR and multi-temporal Landsat imagery to classify land cover types of Williamson County, Illinois that has diverse and mixed landscape features. Specifically, we applied a 3D convolutional neural network (CNN) method to extract features from LiDAR point clouds by (1) creating occupancy grid, intensity grid at 1-meter resolution, and then (2) normalizing and incorporating data into a 3D CNN feature extractor for many epochs of learning. The learned features (e.g., morphological features, intensity features, etc) were combined with multi-temporal spectral data to enhance the performance of land cover classification based on a Support Vector Machine classifier. We used photo interpretation for training and testing data generation. The classification results show that our approach outperforms traditional methods using LiDAR derived feature maps, and promises to serve as an effective methodology for creating high-quality land cover maps through fusion of complementary types of remote sensing data.

2006 FEMA Lidar: Rhode Island Coastline

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

Science.gov (United States)

Huang, Rongyong; Zheng, Shunyi; Hu, Kun

2018-06-01

Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4⁻1/2 (0.17⁻0.27 m) and 1/8⁻1/4 (0.10⁻0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.

High-Density LiDAR Mapping of the Ancient City of Mayapán

Directory of Open Access Journals (Sweden)

Timothy Hare

2014-09-01

Full Text Available A 2013 survey of a 40 square kilometer area surrounding Mayapán, Yucatan, Mexico used high-density LiDAR data to map prehispanic architecture and related natural features. Most of the area is covered by low canopy dense forest vegetation over karstic hilly terrain that impedes full coverage archaeological survey. We used LiDAR at 40 laser points per square meter to generate a bare earth digital elevation model (DEM. Results were evaluated with comparisons to previously mapped areas and with traditional archaeological survey methods for 38 settlement clusters outside of the city wall. Ground checking employed full coverage survey of selected 500 m grid squares, as well as documentation of the chronology and detail of new public and domestic settlement features and cenotes. Results identify the full extent of continued, contemporary Postclassic settlement (A.D. 1150–1450 outside of the city wall to at least 500 meters to the east, north, and west. New data also reveal an extensive modified landscape of terraformed residential hills, rejolladas, and dense settlement dating from Preclassic through Classic Periods. The LiDAR data also allow for the identification of rooms, benches, and stone property walls and lanes within the city.

2015 NOAA Lidar: Pelekane Watershed (HI)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This metadata describes the Digital Elevation Model (DEM) 1 meter products derived from the airborne LiDAR data collected in August of 2015 for the Pelekane...

Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

Directory of Open Access Journals (Sweden)

Tingting Cui

2016-12-01

Full Text Available For multi-sensor integrated systems, such as the mobile mapping system (MMS, data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

Lidar-revised geologic map of the Poverty Bay 7.5' quadrangle, King and Pierce Counties, Washington

Science.gov (United States)

Tabor, Rowland W.; Booth, Derek B.; Troost, Kathy Goetz

2014-01-01

For this map, we interpreted a 6-ft-resolution lidar digital elevation model combined with the geology depicted on the Geologic Map of the Poverty Bay 7.5' Quadrangle, King and Pierce Counties, Washington (Booth and others, 2004b). The authors of the 2004 map described, interpreted, and located the geology on the 1:24,000-scale topographic map of the Poverty Bay 7.5' quadrangle.

Catchment-Scale Terrain Modelling with Structure-from-Motion Photogrammetry: a replacement for airborne lidar?

Science.gov (United States)

Brasington, James; James, Joe; Cook, Simon; Cox, Simon; Lotsari, Eliisa; McColl, Sam; Lehane, Niall; Williams, Richard; Vericat, Damia

2016-04-01

In recent years, 3D terrain reconstructions based on Structure-from-Motion photogrammetry have dramatically democratized the availability of high quality topographic data. This approach involves the use of a non-linear bundle adjustment to estimate simultaneously camera position, pose, distortion and 3D model coordinates. In contrast to traditional aerial photogrammetry, the bundle adjustment is typically solved without external constraints and instead ground control is used a posteriori to transform the modelled coordinates to an established datum using a similarity transformation. The limited data requirements, coupled with the ability to self-calibrate compact cameras, has led to a burgeoning of applications using low-cost imagery acquired terrestrially or from low-altitude platforms. To date, most applications have focused on relatively small spatial scales (0.1-5 Ha), where relaxed logistics permit the use of dense ground control networks and high resolution, close-range photography. It is less clear whether this low-cost approach can be successfully upscaled to tackle larger, watershed-scale projects extending over 102-3 km2 where it could offer a competitive alternative to established landscape modelling with airborne lidar. At such scales, compromises over the density of ground control, the speed and height of sensor platform and related image properties are inevitable. In this presentation we provide a systematic assessment of the quality of large-scale SfM terrain products derived for over 80 km2 of the braided Dart River and its catchment in the Southern Alps of NZ. Reference data in the form of airborne and terrestrial lidar are used to quantify the quality of 3D reconstructions derived from helicopter photography and used to establish baseline uncertainty models for geomorphic change detection. Results indicate that camera network design is a key determinant of model quality, and that standard aerial photogrammetric networks based on strips of nadir

Improving snow density estimation for mapping SWE with Lidar snow depth: assessment of uncertainty in modeled density and field sampling strategies in NASA SnowEx

Science.gov (United States)

Raleigh, M. S.; Smyth, E.; Small, E. E.

2017-12-01

The spatial distribution of snow water equivalent (SWE) is not sufficiently monitored with either remotely sensed or ground-based observations for water resources management. Recent applications of airborne Lidar have yielded basin-wide mapping of SWE when combined with a snow density model. However, in the absence of snow density observations, the uncertainty in these SWE maps is dominated by uncertainty in modeled snow density rather than in Lidar measurement of snow depth. Available observations tend to have a bias in physiographic regime (e.g., flat open areas) and are often insufficient in number to support testing of models across a range of conditions. Thus, there is a need for targeted sampling strategies and controlled model experiments to understand where and why different snow density models diverge. This will enable identification of robust model structures that represent dominant processes controlling snow densification, in support of basin-scale estimation of SWE with remotely-sensed snow depth datasets. The NASA SnowEx mission is a unique opportunity to evaluate sampling strategies of snow density and to quantify and reduce uncertainty in modeled snow density. In this presentation, we present initial field data analyses and modeling results over the Colorado SnowEx domain in the 2016-2017 winter campaign. We detail a framework for spatially mapping the uncertainty in snowpack density, as represented across multiple models. Leveraging the modular SUMMA model, we construct a series of physically-based models to assess systematically the importance of specific process representations to snow density estimates. We will show how models and snow pit observations characterize snow density variations with forest cover in the SnowEx domains. Finally, we will use the spatial maps of density uncertainty to evaluate the selected locations of snow pits, thereby assessing the adequacy of the sampling strategy for targeting uncertainty in modeled snow density.

Multiscale influence of woody riparian vegetation on fluvial topography quantified with ground-based and airborne lidar

Science.gov (United States)

Bywater-Reyes, Sharon; Wilcox, Andrew C.; Diehl, Rebecca M.

2017-06-01

Coupling between riparian vegetation and river processes can result in the coevolution of plant communities and channel morphology. Quantifying biotic-abiotic interactions remains difficult because of the challenges in making and analyzing appropriately scaled observations. We measure the influence of woody vegetation on channel topography at the patch and reach scales in a sand bed, dryland river system (Santa Maria River, Arizona) with native Populus and invasive Tamarix. At the patch scale, we use ground-based lidar to relate plant morphology to "tail bars" formed in the lee of vegetation. We find vegetation roughness density (λf) to most influence tail-bar shape and size, suggesting coherent flow structures associated with roughness density are responsible for sediment deposition at this scale. Using airborne lidar, we test whether relationships between topography and vegetation morphology observed at the patch scale are persistent at the reach scale. We find that elevation of the channel (relative to the local mean) covaries with a metric of vegetation density, indicating analogous influences of vegetation density on topography across spatial scales. While these results are expected, our approach provides insight regarding interactions between woody riparian vegetation and channel topography at multiple scales, and a means to quantify such interactions for use in other field settings.

2009 - 2011 CA Coastal Conservancy Coastal Lidar Project: Hydro-flattened Bare Earth DEM

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

2004 Federal Emergency Management Agency (FEMA) Bare Earth Topographic LiDAR: Connecticut River

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. The LiDAR files were converted from .PTS format to LAS...

Predicting forest height using the GOST, Landsat 7 ETM+, and airborne LiDAR for sloping terrains in the Greater Khingan Mountains of China

Science.gov (United States)

Gu, Chengyan; Clevers, Jan G. P. W.; Liu, Xiao; Tian, Xin; Li, Zhouyuan; Li, Zengyuan

2018-03-01

Sloping terrain of forests is an overlooked factor in many models simulating the canopy bidirectional reflectance distribution function, which limits the estimation accuracy of forest vertical structure parameters (e.g., forest height). The primary objective of this study was to predict forest height on sloping terrain over large areas with the Geometric-Optical Model for Sloping Terrains (GOST) using airborne Light Detection and Ranging (LiDAR) data and Landsat 7 imagery in the western Greater Khingan Mountains of China. The Sequential Maximum Angle Convex Cone (SMACC) algorithm was used to generate image endmembers and corresponding abundances in Landsat imagery. Then, LiDAR-derived forest metrics, topographical factors and SMACC abundances were used to calibrate and validate the GOST, which aimed to accurately decompose the SMACC mixed forest pixels into sunlit crown, sunlit background and shade components. Finally, the forest height of the study area was retrieved based on a back-propagation neural network and a look-up table. Results showed good performance for coniferous forests on all slopes and at all aspects, with significant coefficients of determination above 0.70 and root mean square errors (RMSEs) between 0.50 m and 1.00 m based on ground observed validation data. Higher RMSEs were found in areas with forest heights below 5 m and above 17 m. For 90% of the forested area, the average RMSE was 3.58 m. Our study demonstrates the tremendous potential of the GOST for quantitative mapping of forest height on sloping terrains with multispectral and LiDAR inputs.

Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis

Science.gov (United States)

Dupuy, Stéphane; Lainé, Gérard; Tassin, Jacques; Sarrailh, Jean-Michel

2013-12-01

This article's goal is to explore the benefits of using Digital Surface Model (DSM) and Digital Terrain Model (DTM) derived from LiDAR acquisitions for characterizing the horizontal structure of different facies in forested areas (primary forests vs. secondary forests) within the framework of an object-oriented classification. The area under study is the island of Mayotte in the western Indian Ocean. The LiDAR data were the data originally acquired by an airborne small-footprint discrete-return LiDAR for the "Litto3D" coastline mapping project. They were used to create a Digital Elevation Model (DEM) at a spatial resolution of 1 m and a Digital Canopy Model (DCM) using median filtering. The use of two successive segmentations at different scales allowed us to adjust the segmentation parameters to the local structure of the landscape and of the cover. Working in object-oriented mode with LiDAR allowed us to discriminate six vegetation classes based on canopy height and horizontal heterogeneity. This heterogeneity was assessed using a texture index calculated from the height-transition co-occurrence matrix. Overall accuracy exceeds 90%. The resulting product is the first vegetation map of Mayotte which emphasizes the structure over the composition.

Unsupervised classification of lidar-based vegetation structure metrics at Jean Lafitte National Historical Park and Preserve

Science.gov (United States)

Kranenburg, Christine J.; Palaseanu-Lovejoy, Monica; Nayegandhi, Amar; Brock, John; Woodman, Robert

2012-01-01

Traditional vegetation maps capture the horizontal distribution of various vegetation properties, for example, type, species and age/senescence, across a landscape. Ecologists have long known, however, that many important forest properties, for example, interior microclimate, carbon capacity, biomass and habitat suitability, are also dependent on the vertical arrangement of branches and leaves within tree canopies. The objective of this study was to use a digital elevation model (DEM) along with tree canopy-structure metrics derived from a lidar survey conducted using the Experimental Advanced Airborne Research Lidar (EAARL) to capture a three-dimensional view of vegetation communities in the Barataria Preserve unit of Jean Lafitte National Historical Park and Preserve, Louisiana. The EAARL instrument is a raster-scanning, full waveform-resolving, small-footprint, green-wavelength (532-nanometer) lidar system designed to map coastal bathymetry, topography and vegetation structure simultaneously. An unsupervised clustering procedure was then applied to the 3-dimensional-based metrics and DEM to produce a vegetation map based on the vertical structure of the park's vegetation, which includes a flotant marsh, scrub-shrub wetland, bottomland hardwood forest, and baldcypress-tupelo swamp forest. This study was completed in collaboration with the National Park Service Inventory and Monitoring Program's Gulf Coast Network. The methods presented herein are intended to be used as part of a cost-effective monitoring tool to capture change in park resources.

A Hierarchical Object-oriented Urban Land Cover Classification Using WorldView-2 Imagery and Airborne LiDAR data

Science.gov (United States)

Wu, M. F.; Sun, Z. C.; Yang, B.; Yu, S. S.

2016-11-01

In order to reduce the “salt and pepper” in pixel-based urban land cover classification and expand the application of fusion of multi-source data in the field of urban remote sensing, WorldView-2 imagery and airborne Light Detection and Ranging (LiDAR) data were used to improve the classification of urban land cover. An approach of object- oriented hierarchical classification was proposed in our study. The processing of proposed method consisted of two hierarchies. (1) In the first hierarchy, LiDAR Normalized Digital Surface Model (nDSM) image was segmented to objects. The NDVI, Costal Blue and nDSM thresholds were set for extracting building objects. (2) In the second hierarchy, after removing building objects, WorldView-2 fused imagery was obtained by Haze-ratio-based (HR) fusion, and was segmented. A SVM classifier was applied to generate road/parking lot, vegetation and bare soil objects. (3) Trees and grasslands were split based on an nDSM threshold (2.4 meter). The results showed that compared with pixel-based and non-hierarchical object-oriented approach, proposed method provided a better performance of urban land cover classification, the overall accuracy (OA) and overall kappa (OK) improved up to 92.75% and 0.90. Furthermore, proposed method reduced “salt and pepper” in pixel-based classification, improved the extraction accuracy of buildings based on LiDAR nDSM image segmentation, and reduced the confusion between trees and grasslands through setting nDSM threshold.

Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data

Science.gov (United States)

Pitkänen, T. P.; Käyhkö, N.

2017-08-01

Mapping structural changes in vegetation dynamics has, for a long time, been carried out using satellite images, orthophotos and, more recently, airborne lidar acquisitions. Lidar has established its position as providing accurate material for structure-based analyses but its limited availability, relatively short history, and lack of spectral information, however, are generally impeding the use of lidar data for change detection purposes. A potential solution in respect of detecting both contemporary vegetation structures and their previous trajectories is to combine lidar acquisitions with optical remote sensing data, which can substantially extend the coverage, span and spectral range needed for vegetation mapping. In this study, we tested the simultaneous use of a single low-density lidar data set, a series of Landsat satellite frames and two high-resolution orthophotos to detect vegetation succession related to grassland overgrowth, i.e. encroachment of woody plants into semi-natural grasslands. We built several alternative Random Forest models with different sets of variables and tested the applicability of respective data sources for change detection purposes, aiming at distinguishing unchanged grassland and woodland areas from overgrown grasslands. Our results show that while lidar alone provides a solid basis for indicating structural differences between grassland and woodland vegetation, and orthophoto-generated variables alone are better in detecting successional changes, their combination works considerably better than its respective parts. More specifically, a model combining all the used data sets reduces the total error from 17.0% to 11.0% and omission error of detecting overgrown grasslands from 56.9% to 31.2%, when compared to model constructed solely based on lidar data. This pinpoints the efficiency of the approach where lidar-generated structural metrics are combined with optical and multitemporal observations, providing a workable framework to

Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation.

Science.gov (United States)

Silva, Carlos Alberto; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Liesenberg, Veraldo; Bernett, Luiz G; Scheraiber, Clewerson F; Schoeninger, Emerson R

2018-01-01

Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more effective for retrieving height than tree density. The model coefficients of determination (adj.R2) and a root mean squared difference (RMSD) for HD, HM and TD were 0.90, 0.94, 0.38m and 6.99, 5.70, 12.92%, respectively. Our results show that LiDAR and k-NN imputation can be used to predict stand heights with high accuracy in Pinus taeda. However, furthers studies need to be realized to improve the accuracy prediction of TD and to evaluate and compare the cost of acquisition and processing of LiDAR data against the conventional inventory procedures.

Airborne Measurements of CO2 Column Absorption and Range Using a Pulsed Direct-Detection Integrated Path Differential Absorption Lidar

Science.gov (United States)

Abshire, James B.; Riris, Haris; Weaver, Clark J.; Mao, Jianping; Allan, Graham R.; Hasselbrack, William E.; Browell, Edward V.

2013-01-01

We report on airborne CO2 column absorption measurements made in 2009 with a pulsed direct-detection lidar operating at 1572.33 nm and utilizing the integrated path differential absorption technique. We demonstrated these at different altitudes from an aircraft in July and August in flights over four locations in the central and eastern United States. The results show clear CO2 line shape and absorption signals, which follow the expected changes with aircraft altitude from 3 to 13 km. The lidar measurement statistics were also calculated for each flight as a function of altitude. The optical depth varied nearly linearly with altitude, consistent with calculations based on atmospheric models. The scatter in the optical depth measurements varied with aircraft altitude as expected, and the median measurement precisions for the column varied from 0.9 to 1.2 ppm. The altitude range with the lowest scatter was 810 km, and the majority of measurements for the column within it had precisions between 0.2 and 0.9 ppm.

The Combined Use of Airborne Remote Sensing Techniques within a GIS Environment for the Seismic Vulnerability Assessment of Urban Areas: An Operational Application

Directory of Open Access Journals (Sweden)

Antonio Costanzo

2016-02-01

Full Text Available The knowledge of the topographic features, the building properties, and the road infrastructure settings are relevant operational tasks for managing post-crisis events, restoration activities, and for supporting search and rescue operations. Within such a framework, airborne remote sensing tools have demonstrated to be powerful instruments, whose joint use can provide meaningful analyses to support the risk assessment of urban environments. Based on this rationale, in this study, the operational benefits obtained by combining airborne LiDAR and hyperspectral measurements are shown. Terrain and surface digital models are gathered by using LiDAR data. Information about roads and roof materials are provided through the supervised classification of hyperspectral images. The objective is to combine such products within a geographic information system (GIS providing value-added maps to be used for the seismic vulnerability assessment of urban environments. Experimental results are gathered for the city of Cosenza, Italy.

Triple-Pulse Integrated Path Differential Absorption Lidar for Carbon Dioxide Measurement - Novel Lidar Technologies and Techniques with Path to Space

Science.gov (United States)

Singh, Upendra N.; Refaat, Tamer F.; Petros, Mulugeta

2017-01-01

The societal benefits of understanding climate change through identification of global carbon dioxide sources and sinks led to the desired NASA's active sensing of carbon dioxide emissions over nights, days, and seasons (ASCENDS) space-based missions of global carbon dioxide measurements. For more than 15 years, NASA Langley Research Center (LaRC) have developed several carbon dioxide active remote sensors using the differential absorption lidar (DIAL) technique operating at the two-micron wavelength. Currently, an airborne two-micron triple-pulse integrated path differential absorption (IPDA) lidar is under development. This IPDA lidar measures carbon dioxide as well as water vapor, the dominant interfering molecule on carbon dioxide remote sensing. Advancement of this triple-pulse IPDA lidar development is presented.

Rapid mapping of ultrafine fault zone topography with structure from motion

Science.gov (United States)

Johnson, Kendra; Nissen, Edwin; Saripalli, Srikanth; Arrowsmith, J. Ramón; McGarey, Patrick; Scharer, Katherine M.; Williams, Patrick; Blisniuk, Kimberly

2014-01-01

Structure from Motion (SfM) generates high-resolution topography and coregistered texture (color) from an unstructured set of overlapping photographs taken from varying viewpoints, overcoming many of the cost, time, and logistical limitations of Light Detection and Ranging (LiDAR) and other topographic surveying methods. This paper provides the first investigation of SfM as a tool for mapping fault zone topography in areas of sparse or low-lying vegetation. First, we present a simple, affordable SfM workflow, based on an unmanned helium balloon or motorized glider, an inexpensive camera, and semiautomated software. Second, we illustrate the system at two sites on southern California faults covered by existing airborne or terrestrial LiDAR, enabling a comparative assessment of SfM topography resolution and precision. At the first site, an ∼0.1 km2 alluvial fan on the San Andreas fault, a colored point cloud of density mostly >700 points/m2 and a 3 cm digital elevation model (DEM) and orthophoto were produced from 233 photos collected ∼50 m above ground level. When a few global positioning system ground control points are incorporated, closest point vertical distances to the much sparser (∼4 points/m2) airborne LiDAR point cloud are mostly 530 points/m2 and a 2 cm DEM and orthophoto were produced from 450 photos taken from ∼60 m above ground level. Closest point vertical distances to existing terrestrial LiDAR data of comparable density are mostly geomorphic offsets related to past earthquakes as well as rapid response mapping or long-term monitoring of faulted landscapes.

A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY

Directory of Open Access Journals (Sweden)

A. Roncat

2016-06-01

Full Text Available In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a “single-wavelength reflectometer” to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.

Coastal erosion and mass wasting along the Canadian Beaufort Sea based on annual airborne LiDAR elevation data

Science.gov (United States)

Obu, Jaroslav; Lantuit, Hugues; Grosse, Guido; Günther, Frank; Sachs, Torsten; Helm, Veit; Fritz, Michael

2017-09-01

Erosion of permafrost coasts has received increasing scientific attention since 1990s because of rapid land loss and the mobilisation potential of old organic carbon. The majority of permafrost coastal erosion studies are limited to time periods from a few years to decades. Most of these studies emphasize the spatial variability of coastal erosion, but the intensity of inter-annual variations, including intermediate coastal aggradation, remains poorly documented. We used repeat airborne Light Detection And Ranging (LiDAR) elevation data from 2012 and 2013 with 1 m horizontal resolution to study coastal erosion and accompanying mass-wasting processes in the hinterland. Study sites were selected to include different morphologies along the coast of the Yukon Coastal Plain and on Herschel Island. We studied elevation and volume changes and coastline movement and compared the results between geomorphic units. Results showed simple uniform coastal erosion from low coasts (up to 10 m height) and a highly diverse erosion pattern along coasts with higher backshore elevation. This variability was particularly pronounced in the case of active retrogressive thaw slumps, which can decrease coastal erosion or even cause temporary progradation by sediment release. Most of the extremes were recorded in study sites with active slumping (e.g. 22 m of coastline retreat and 42 m of coastline progradation). Coastline progradation also resulted from the accumulation of slope collapse material. These occasional events can significantly affect the coastline position on a specific date and can affect coastal retreat rates as estimated in long term by coastline digitalisation from air photos and satellite imagery. These deficiencies can be overcome by short-term airborne LiDAR measurements, which provide detailed and high-resolution information about quickly changing elevations in coastal areas.

Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

Science.gov (United States)

Hakkenberg, C R; Peet, R K; Urban, D L; Song, C

2018-01-01

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.

Assessment of the mapping of fractional woody cover in southern African savannas using multi-temporal and polarimetric ALOS PALSAR L-band images

CSIR Research Space (South Africa)

Urbazaev, M

2015-09-01

Full Text Available cover maps. The LiDAR survey was carried out in April 2008 with the Carnegie Airborne Observatory (CAO, http://cao.ciw.edu). The highest correlations to the reference data were obtained from SAR backscatters of the dry season, followed by the wet season...

Automated Detection of Selective Logging in Amazon Forests Using Airborne Lidar Data and Pattern Recognition Algorithms

Science.gov (United States)

Keller, M. M.; d'Oliveira, M. N.; Takemura, C. M.; Vitoria, D.; Araujo, L. S.; Morton, D. C.

2012-12-01

Selective logging, the removal of several valuable timber trees per hectare, is an important land use in the Brazilian Amazon and may degrade forests through long term changes in structure, loss of forest carbon and species diversity. Similar to deforestation, the annual area affected by selected logging has declined significantly in the past decade. Nonetheless, this land use affects several thousand km2 per year in Brazil. We studied a 1000 ha area of the Antimary State Forest (FEA) in the State of Acre, Brazil (9.304 ○S, 68.281 ○W) that has a basal area of 22.5 m2 ha-1 and an above-ground biomass of 231 Mg ha-1. Logging intensity was low, approximately 10 to 15 m3 ha-1. We collected small-footprint airborne lidar data using an Optech ALTM 3100EA over the study area once each in 2010 and 2011. The study area contained both recent and older logging that used both conventional and technologically advanced logging techniques. Lidar return density averaged over 20 m-2 for both collection periods with estimated horizontal and vertical precision of 0.30 and 0.15 m. A relative density model comparing returns from 0 to 1 m elevation to returns in 1-5 m elevation range revealed the pattern of roads and skid trails. These patterns were confirmed by ground-based GPS survey. A GIS model of the road and skid network was built using lidar and ground data. We tested and compared two pattern recognition approaches used to automate logging detection. Both segmentation using commercial eCognition segmentation and a Frangi filter algorithm identified the road and skid trail network compared to the GIS model. We report on the effectiveness of these two techniques.

Inland excess water mapping using hyperspectral imagery

Directory of Open Access Journals (Sweden)

Csendes Bálint

2016-01-01

Full Text Available Hyperspectral imaging combined with the potentials of airborne scanning is a powerful tool to monitor environmental processes. The aim of this research was to use high resolution remotely sensed data to map the spatial extent of inland excess water patches in a Hungarian study area that is known for its oil and gas production facilities. Periodic floodings show high spatial and temporal variability, nevertheless, former studies have proven that the affected soil surfaces can be accurately identified. Besides separability measurements, we performed spectral angle classification, which gave a result of 85% overall accuracy and we also compared the generated land cover map with LIDAR elevation data.

Application of LiDAR to hydrologic flux estimation in Australian eucalypt forests (Invited)

Science.gov (United States)

Lane, P. N.; Mitchell, P. J.; Jaskierniak, D.; Hawthorne, S. N.; Griebel, A.

2013-12-01

inventory methods.These models can be used to parameterize hydrologic models to explore disturbance and age-related ET changes, and develop spatial-temporal maps of ET based on accurate representation of sapwood areas in complex terrain. The third example involves analyses of stand growth and long term streamflow response to thinning treatments in eucalyptus regnans forests. These forests have a strong age-streamflow relationship that can lead to streamflow declines as disturbed stands regrow. A set of thinning treatments in small experimental catchments (uniform, strip and understorey removal) were implemented in 1978-1982. The streamflow analysis supported early findings that flows increase and then relaxed, but also detected a flow decline below expected undisturbed levels for most catchments. Airborne LiDAR was used to analyse the structural recovery of treated stands, estimate LAI and canopy coverage via gap-fraction analysis, and scale ET measurements. The LiDAR data revealed the association of treatment type and regrowth and demonstrated that despite a net reduction in overstorey stem density, stand LAI had recovered and may explain the flow response. Finally, new terrestrial LiDAR instruments are being used in conjunction with eddy-covariance flux tower and sapflow measurement to measure fine temporal scale carbon-water dynamics. These instruments can be combined with airborne derived data to produce 3 dimensional canopy profile for linkage with ET processes.

Spaceborne Lidar in the Study of Marine Systems.

Science.gov (United States)

Hostetler, Chris A; Behrenfeld, Michael J; Hu, Yongxiang; Hair, Johnathan W; Schulien, Jennifer A

2018-01-03

Satellite passive ocean color instruments have provided an unbroken ∼20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

Spaceborne Lidar in the Study of Marine Systems

Science.gov (United States)

Hostetler, Chris A.; Behrenfeld, Michael J.; Hu, Yongxiang; Hair, Johnathan W.; Schulien, Jennifer A.

2018-01-01

Satellite passive ocean color instruments have provided an unbroken ˜20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

Evaluation of Airborne Lidar Elevation Surfaces for Propagation of Coastal Inundation: The Importance of Hydrologic Connectivity

Directory of Open Access Journals (Sweden)

Sandra Poppenga

2015-09-01

Full Text Available Detailed information about coastal inundation is vital to understanding dynamic and populated areas that are impacted by storm surge and flooding. To understand these natural hazard risks, lidar elevation surfaces are frequently used to model inundation in coastal areas. A single-value surface method is sometimes used to inundate areas in lidar elevation surfaces that are below a specified elevation value. However, such an approach does not take into consideration hydrologic connectivity between elevation grids cells resulting in inland areas that should be hydrologically connected to the ocean, but are not. Because inland areas that should drain to the ocean are hydrologically disconnected by raised features in a lidar elevation surface, simply raising the water level to propagate coastal inundation will lead to inundation uncertainties. We took advantage of this problem to identify hydrologically disconnected inland areas to point out that they should be considered for coastal inundation, and that a lidar-based hydrologic surface should be developed with hydrologic connectivity prior to inundation analysis. The process of achieving hydrologic connectivity with hydrologic-enforcement is not new, however, the application of hydrologically-enforced lidar elevation surfaces for improved coastal inundation mapping as approached in this research is innovative. In this article, we propagated a high-resolution lidar elevation surface in coastal Staten Island, New York to demonstrate that inland areas lacking hydrologic connectivity to the ocean could potentially be included in inundation delineations. For inland areas that were hydrologically disconnected, we evaluated if drainage to the ocean was evident, and calculated an area exceeding 11 ha (~0.11 km2 that could be considered in inundation delineations. We also assessed land cover for each inland area to determine the type of physical surfaces that would be potentially impacted if the inland areas

Evaluation of airborne lidar elevation surfaces for propagation of coastal inundation: the importance of hydrologic connectivity

Science.gov (United States)

Poppenga, Sandra K.; Worstell, Bruce B.

2015-01-01

Detailed information about coastal inundation is vital to understanding dynamic and populated areas that are impacted by storm surge and flooding. To understand these natural hazard risks, lidar elevation surfaces are frequently used to model inundation in coastal areas. A single-value surface method is sometimes used to inundate areas in lidar elevation surfaces that are below a specified elevation value. However, such an approach does not take into consideration hydrologic connectivity between elevation grids cells resulting in inland areas that should be hydrologically connected to the ocean, but are not. Because inland areas that should drain to the ocean are hydrologically disconnected by raised features in a lidar elevation surface, simply raising the water level to propagate coastal inundation will lead to inundation uncertainties. We took advantage of this problem to identify hydrologically disconnected inland areas to point out that they should be considered for coastal inundation, and that a lidar-based hydrologic surface should be developed with hydrologic connectivity prior to inundation analysis. The process of achieving hydrologic connectivity with hydrologic-enforcement is not new, however, the application of hydrologically-enforced lidar elevation surfaces for improved coastal inundation mapping as approached in this research is innovative. In this article, we propagated a high-resolution lidar elevation surface in coastal Staten Island, New York to demonstrate that inland areas lacking hydrologic connectivity to the ocean could potentially be included in inundation delineations. For inland areas that were hydrologically disconnected, we evaluated if drainage to the ocean was evident, and calculated an area exceeding 11 ha (~0.11 km2) that could be considered in inundation delineations. We also assessed land cover for each inland area to determine the type of physical surfaces that would be potentially impacted if the inland areas were considered as

An Approach for Foliar Trait Retrieval from Airborne Imaging Spectroscopy of Tropical Forests

Directory of Open Access Journals (Sweden)

Roberta E. Martin

2018-01-01

Full Text Available Spatial information on forest functional composition is needed to inform management and conservation efforts, yet this information is lacking, particularly in tropical regions. Canopy foliar traits underpin the functional biodiversity of forests, and have been shown to be remotely measurable using airborne 350–2510 nm imaging spectrometers. We used newly acquired imaging spectroscopy data constrained with concurrent light detection and ranging (LiDAR measurements from the Carnegie Airborne Observatory (CAO, and field measurements, to test the performance of the Spectranomics approach for foliar trait retrieval. The method was previously developed in Neotropical forests, and was tested here in the humid tropical forests of Malaysian Borneo. Multiple foliar chemical traits, as well as leaf mass per area (LMA, were estimated with demonstrable precision and accuracy. The results were similar to those observed for Neotropical forests, suggesting a more general use of the Spectranomics approach for mapping canopy traits in tropical forests. Future mapping studies using this approach can advance scientific investigations and applications based on imaging spectroscopy.

LAN MAP: An Innovative Airborne Light at Night Mapping Project