WorldWideScience

Sample records for multispectral airborne lidar

  1. Water Mapping Using Multispectral Airborne LIDAR Data

    Science.gov (United States)

    Yan, W. Y.; Shaker, A.; LaRocque, P. E.

    2018-04-01

    This study investigates the use of the world's first multispectral airborne LiDAR sensor, Optech Titan, manufactured by Teledyne Optech to serve the purpose of automatic land-water classification with a particular focus on near shore region and river environment. Although there exist recent studies utilizing airborne LiDAR data for shoreline detection and water surface mapping, the majority of them only perform experimental testing on clipped data subset or rely on data fusion with aerial/satellite image. In addition, most of the existing approaches require manual intervention or existing tidal/datum data for sample collection of training data. To tackle the drawbacks of previous approaches, we propose and develop an automatic data processing workflow for land-water classification using multispectral airborne LiDAR data. Depending on the nature of the study scene, two methods are proposed for automatic training data selection. The first method utilizes the elevation/intensity histogram fitted with Gaussian mixture model (GMM) to preliminarily split the land and water bodies. The second method mainly relies on the use of a newly developed scan line elevation intensity ratio (SLIER) to estimate the water surface data points. Regardless of the training methods being used, feature spaces can be constructed using the multispectral LiDAR intensity, elevation and other features derived from these parameters. The comprehensive workflow was tested with two datasets collected for different near shore region and river environment, where the overall accuracy yielded better than 96 %.

  2. 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.

  3. 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.

  4. 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.

  5. 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%).

  6. 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 %).

  7. 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.

  8. Modelling forest canopy height by integrating airborne LiDAR samples with satellite Radar and multispectral imagery

    Science.gov (United States)

    García, Mariano; Saatchi, Sassan; Ustin, Susan; Balzter, Heiko

    2018-04-01

    Spatially-explicit information on forest structure is paramount to estimating aboveground carbon stocks for designing sustainable forest management strategies and mitigating greenhouse gas emissions from deforestation and forest degradation. LiDAR measurements provide samples of forest structure that must be integrated with satellite imagery to predict and to map landscape scale variations of forest structure. Here we evaluate the capability of existing satellite synthetic aperture radar (SAR) with multispectral data to estimate forest canopy height over five study sites across two biomes in North America, namely temperate broadleaf and mixed forests and temperate coniferous forests. Pixel size affected the modelling results, with an improvement in model performance as pixel resolution coarsened from 25 m to 100 m. Likewise, the sample size was an important factor in the uncertainty of height prediction using the Support Vector Machine modelling approach. Larger sample size yielded better results but the improvement stabilised when the sample size reached approximately 10% of the study area. We also evaluated the impact of surface moisture (soil and vegetation moisture) on the modelling approach. Whereas the impact of surface moisture had a moderate effect on the proportion of the variance explained by the model (up to 14%), its impact was more evident in the bias of the models with bias reaching values up to 4 m. Averaging the incidence angle corrected radar backscatter coefficient (γ°) reduced the impact of surface moisture on the models and improved their performance at all study sites, with R2 ranging between 0.61 and 0.82, RMSE between 2.02 and 5.64 and bias between 0.02 and -0.06, respectively, at 100 m spatial resolution. An evaluation of the relative importance of the variables in the model performance showed that for the study sites located within the temperate broadleaf and mixed forests biome ALOS-PALSAR HV polarised backscatter was the most important

  9. Airborne Multi-Spectral Minefield Survey

    Science.gov (United States)

    2005-05-01

    Swedish Defence Research Agency), GEOSPACE (Austria), GTD ( Ingenieria de Sistemas y Software Industrial, Spain), IMEC (Ineruniversity MicroElectronic...RTO-MP-SET-092 18 - 1 UNCLASSIFIED/UNLIMITED UNCLASSIFIED/UNLIMITED Airborne Multi-Spectral Minefield Survey Dirk-Jan de Lange, Eric den...actions is the severe lack of baseline information. To respond to this in a rapid way, cost-efficient data acquisition methods are a key issue. de

  10. Highly Protable Airborne Multispectral Imaging System

    Science.gov (United States)

    Lehnemann, Robert; Mcnamee, Todd

    2001-01-01

    A portable instrumentation system is described that includes and airborne and a ground-based subsytem. It can acquire multispectral image data over swaths of terrain ranging in width from about 1.5 to 1 km. The system was developed especially for use in coastal environments and is well suited for performing remote sensing and general environmental monitoring. It includes a small,munpilotaed, remotely controlled airplance that carries a forward-looking camera for navigation, three downward-looking monochrome video cameras for imaging terrain in three spectral bands, a video transmitter, and a Global Positioning System (GPS) reciever.

  11. Airborne Lidar Surface Topography (LIST) Simulator

    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; Winkert, Tom; Plants, Michael; hide

    2011-01-01

    In this paper we will discuss our development effort of an airborne instrument as a pathfinder for the Lidar Surface Technology (LIST) mission. This paper will discuss the system approach, enabling technologies, instrument concept and performance of the Airborne LIST Simulator (A-LISTS).

  12. An integrated compact airborne multispectral imaging system using embedded computer

    Science.gov (United States)

    Zhang, Yuedong; Wang, Li; Zhang, Xuguo

    2015-08-01

    An integrated compact airborne multispectral imaging system using embedded computer based control system was developed for small aircraft multispectral imaging application. The multispectral imaging system integrates CMOS camera, filter wheel with eight filters, two-axis stabilized platform, miniature POS (position and orientation system) and embedded computer. The embedded computer has excellent universality and expansibility, and has advantages in volume and weight for airborne platform, so it can meet the requirements of control system of the integrated airborne multispectral imaging system. The embedded computer controls the camera parameters setting, filter wheel and stabilized platform working, image and POS data acquisition, and stores the image and data. The airborne multispectral imaging system can connect peripheral device use the ports of the embedded computer, so the system operation and the stored image data management are easy. This airborne multispectral imaging system has advantages of small volume, multi-function, and good expansibility. The imaging experiment results show that this system has potential for multispectral remote sensing in applications such as resource investigation and environmental monitoring.

  13. 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.

  14. Multispectral LiDAR Data for Land Cover Classification of Urban Areas

    Directory of Open Access Journals (Sweden)

    Salem Morsy

    2017-04-01

    Full Text Available Airborne Light Detection And Ranging (LiDAR systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

  15. Multispectral LiDAR Data for Land Cover Classification of Urban Areas.

    Science.gov (United States)

    Morsy, Salem; Shaker, Ahmed; El-Rabbany, Ahmed

    2017-04-26

    Airborne Light Detection And Ranging (LiDAR) systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity) from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs) computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

  16. 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

  17. Study on analysis from sources of error for Airborne LIDAR

    Science.gov (United States)

    Ren, H. C.; Yan, Q.; Liu, Z. J.; Zuo, Z. Q.; Xu, Q. Q.; Li, F. F.; Song, C.

    2016-11-01

    With the advancement of Aerial Photogrammetry, it appears that to obtain geo-spatial information of high spatial and temporal resolution provides a new technical means for Airborne LIDAR measurement techniques, with unique advantages and broad application prospects. Airborne LIDAR is increasingly becoming a new kind of space for earth observation technology, which is mounted by launching platform for aviation, accepting laser pulses to get high-precision, high-density three-dimensional coordinate point cloud data and intensity information. In this paper, we briefly demonstrates Airborne laser radar systems, and that some errors about Airborne LIDAR data sources are analyzed in detail, so the corresponding methods is put forwarded to avoid or eliminate it. Taking into account the practical application of engineering, some recommendations were developed for these designs, which has crucial theoretical and practical significance in Airborne LIDAR data processing fields.

  18. Methods from Information Extraction from LIDAR Intensity Data and Multispectral LIDAR Technology

    Science.gov (United States)

    Scaioni, M.; Höfle, B.; Baungarten Kersting, A. P.; Barazzetti, L.; Previtali, M.; Wujanz, D.

    2018-04-01

    LiDAR is a consolidated technology for topographic mapping and 3D reconstruction, which is implemented in several platforms On the other hand, the exploitation of the geometric information has been coupled by the use of laser intensity, which may provide additional data for multiple purposes. This option has been emphasized by the availability of sensors working on different wavelength, thus able to provide additional information for classification of surfaces and objects. Several applications ofmonochromatic and multi-spectral LiDAR data have been already developed in different fields: geosciences, agriculture, forestry, building and cultural heritage. The use of intensity data to extract measures of point cloud quality has been also developed. The paper would like to give an overview on the state-of-the-art of these techniques, and to present the modern technologies for the acquisition of multispectral LiDAR data. In addition, the ISPRS WG III/5 on `Information Extraction from LiDAR Intensity Data' has collected and made available a few open data sets to support scholars to do research on this field. This service is presented and data sets delivered so far as are described.

  19. METHODS FROM INFORMATION EXTRACTION FROM LIDAR INTENSITY DATA AND MULTISPECTRAL LIDAR TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    M. Scaioni

    2018-04-01

    Full Text Available LiDAR is a consolidated technology for topographic mapping and 3D reconstruction, which is implemented in several platforms On the other hand, the exploitation of the geometric information has been coupled by the use of laser intensity, which may provide additional data for multiple purposes. This option has been emphasized by the availability of sensors working on different wavelength, thus able to provide additional information for classification of surfaces and objects. Several applications ofmonochromatic and multi-spectral LiDAR data have been already developed in different fields: geosciences, agriculture, forestry, building and cultural heritage. The use of intensity data to extract measures of point cloud quality has been also developed. The paper would like to give an overview on the state-of-the-art of these techniques, and to present the modern technologies for the acquisition of multispectral LiDAR data. In addition, the ISPRS WG III/5 on ‘Information Extraction from LiDAR Intensity Data’ has collected and made available a few open data sets to support scholars to do research on this field. This service is presented and data sets delivered so far as are described.

  20. Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

    Science.gov (United States)

    Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

    2016-06-01

    Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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

  6. Design and development of an airborne multispectral imaging system

    Science.gov (United States)

    Kulkarni, Rahul R.; Bachnak, Rafic; Lyle, Stacey; Steidley, Carl W.

    2002-08-01

    Advances in imaging technology and sensors have made airborne remote sensing systems viable for many applications that require reasonably good resolution at low cost. Digital cameras are making their mark on the market by providing high resolution at very high rates. This paper describes an aircraft-mounted imaging system (AMIS) that is being designed and developed at Texas A&M University-Corpus Christi (A&M-CC) with the support of a grant from NASA. The approach is to first develop and test a one-camera system that will be upgraded into a five-camera system that offers multi-spectral capabilities. AMIS will be low cost, rugged, portable and has its own battery power source. Its immediate use will be to acquire images of the Coastal area in the Gulf of Mexico for a variety of studies covering vast spectra from near ultraviolet region to near infrared region. This paper describes AMIS and its characteristics, discusses the process for selecting the major components, and presents the progress.

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis

    Science.gov (United States)

    Gilani, S. A. N.; Awrangjeb, M.; Lu, G.

    2015-03-01

    Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building's occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets

  15. EXTRACTION OF BUILDING BOUNDARY LINES FROM AIRBORNE LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    Y.-H. Tseng

    2016-10-01

    Full Text Available Building boundary lines are important spatial features that characterize the topographic maps and three-dimensional (3D city models. Airborne LiDAR Point clouds provide adequate 3D spatial information for building boundary mapping. However, information of boundary features contained in point clouds is implicit. This study focuses on developing an automatic algorithm of building boundary line extraction from airborne LiDAR data. In an airborne LiDAR dataset, top surfaces of buildings, such as roofs, tend to have densely distributed points, but vertical surfaces, such as walls, usually have sparsely distributed points or even no points. The intersection lines of roof and wall planes are, therefore, not clearly defined in point clouds. This paper proposes a novel method to extract those boundary lines of building edges. The extracted line features can be used as fundamental data to generate topographic maps of 3D city model for an urban area. The proposed method includes two major process steps. The first step is to extract building boundary points from point clouds. Then the second step is followed to form building boundary line features based on the extracted boundary points. In this step, a line fitting algorithm is developed to improve the edge extraction from LiDAR data. Eight test objects, including 4 simple low buildings and 4 complicated tall buildings, were selected from the buildings in NCKU campus. The test results demonstrate the feasibility of the proposed method in extracting complicate building boundary lines. Some results which are not as good as expected suggest the need of further improvement of the method.

  16. Feasibility study for airborne fluorescence/reflectivity lidar bathymetry

    Science.gov (United States)

    Steinvall, Ove; Kautsky, Hans; Tulldahl, Michael; Wollner, Erika

    2012-06-01

    There is a demand from the authorities to have good maps of the coastal environment for their exploitation and preservation of the coastal areas. The goal for environmental mapping and monitoring is to differentiate between vegetation and non-vegetated bottoms and, if possible, to differentiate between species. Airborne lidar bathymetry is an interesting method for mapping shallow underwater habitats. In general, the maximum depth range for airborne laser exceeds the possible depth range for passive sensors. Today, operational lidar systems are able to capture the bottom (or vegetation) topography as well as estimations of the bottom reflectivity using e.g. reflected bottom pulse power. In this paper we study the possibilities and advantages for environmental mapping, if laser sensing would be further developed from single wavelength depth sounding systems to include multiple emission wavelengths and fluorescence receiver channels. Our results show that an airborne fluorescence lidar has several interesting features which might be useful in mapping underwater habitats. An example is the laser induced fluorescence giving rise to the emission spectrum which could be used for classification together with the elastic lidar signal. In the first part of our study, vegetation and substrate samples were collected and their spectral reflectance and fluorescence were subsequently measured in laboratory. A laser wavelength of 532 nm was used for excitation of the samples. The choice of 532 nm as excitation wavelength is motivated by the fact that this wavelength is commonly used in bathymetric laser scanners and that the excitation wavelengths are limited to the visual region as e.g. ultraviolet radiation is highly attenuated in water. The second part of our work consisted of theoretical performance calculations for a potential real system, and comparison of separability between species and substrate signatures using selected wavelength regions for fluorescence sensing.

  17. 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.

  18. Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

    Science.gov (United States)

    Xiao, P.; Kelly, M.; Guo, Q.

    2014-12-01

    This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree

  19. Employing airborne multispectral digital imagery to map Brazilian pepper infestation in south Texas.

    Science.gov (United States)

    A study was conducted in south Texas to determine the feasibility of using airborne multispectral digital imagery for differentiating the invasive plant Brazilian pepper (Schinus terebinthifolius) from other cover types. Imagery obtained in the visible, near infrared, and mid infrared regions of th...

  20. 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

  1. 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.

  2. 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...

  3. 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...

  4. Impacts of airborne lidar pulse density on estimating biomass stocks and changes in a selectively logged tropical forest

    Science.gov (United States)

    Carlos Alberto Silva; Andrew Thomas Hudak; Lee Alexander Vierling; Carine Klauberg; Mariano Garcia; Antonio Ferraz; Michael Keller; Jan Eitel; Sassan Saatchi

    2017-01-01

    Airborne lidar has become a well-suited technology for predicting and mapping many tropical forest attributes, including aboveground biomass (AGB). However, trade-offs exist between lidar pulse density and acquisition cost. The aim of this study was to evaluate the influence of lidar pulse density on AGB change predictions using airborne lidar and field plot data in a...

  5. Forest Delineation Based on Airborne LIDAR Data

    Directory of Open Access Journals (Sweden)

    Norbert Pfeifer

    2012-03-01

    Full Text Available The delineation of forested areas is a critical task, because the resulting maps are a fundamental input for a broad field of applications and users. Different national and international forest definitions are available for manual or automatic delineation, but unfortunately most definitions lack precise geometrical descriptions for the different criteria. A mandatory criterion in forest definitions is the criterion of crown coverage (CC, which defines the proportion of the forest floor covered by the vertical projection of the tree crowns. For loosely stocked areas, this criterion is especially critical, because the size and shape of the reference area for calculating CC is not clearly defined in most definitions. Thus current forest delineations differ and tend to be non-comparable because of different settings for checking the criterion of CC in the delineation process. This paper evaluates a new approach for the automatic delineation of forested areas, based on airborne laser scanning (ALS data with a clearly defined method for calculating CC. The new approach, the ‘tree triples’ method, is based on defining CC as a relation between the sum of the crown areas of three neighboring trees and the area of their convex hull. The approach is applied and analyzed for two study areas in Tyrol, Austria. The selected areas show a loosely stocked forest at the upper timberline and a fragmented forest on the hillside. The fully automatic method presented for delineating forested areas from ALS data shows promising results with an overall accuracy of 96%, and provides a beneficial tool for operational applications.

  6. 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.

  7. Airborne laser altimetry and multispectral imagery for modeling Golden-cheeked Warbler (Setophaga chrysoparia) density

    Science.gov (United States)

    Steven E. Sesnie; James M. Mueller; Sarah E. Lehnen; Scott M. Rowin; Jennifer L. Reidy; Frank R. Thompson

    2016-01-01

    Robust models of wildlife population size, spatial distribution, and habitat relationships are needed to more effectively monitor endangered species and prioritize habitat conservation efforts. Remotely sensed data such as airborne laser altimetry (LiDAR) and digital color infrared (CIR) aerial photography combined with well-designed field studies can help fill these...

  8. 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.

  9. 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.

  10. Wide area methane emissions mapping with airborne IPDA lidar

    Science.gov (United States)

    Bartholomew, Jarett; Lyman, Philip; Weimer, Carl; Tandy, William

    2017-08-01

    Methane emissions from natural gas production, storage, and transportation are potential sources of greenhouse gas emissions. Methane leaks also constitute revenue loss potential from operations. Since 2013, Ball Aerospace has been developing advanced airborne sensors using integrated path differential absorption (IPDA) LIDAR instrumentation to identify methane, propane, and longer-chain alkanes in the lowest region of the atmosphere. Additional funding has come from the U.S. Department of Transportation, Pipeline and Hazardous Materials Administration (PHMSA) to upgrade instrumentation to a broader swath coverage of up to 400 meters while maintaining high spatial sampling resolution and geolocation accuracy. Wide area coverage allows efficient mapping of emissions from gathering and distribution networks, processing facilities, landfills, natural seeps, and other distributed methane sources. This paper summarizes the benefits of advanced instrumentation for aerial methane emission mapping, describes the operating characteristics and design of this upgraded IPDA instrumentation, and reviews technical challenges encountered during development and deployment.

  11. 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.

  12. Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data

    Directory of Open Access Journals (Sweden)

    Andrew Wallace

    2012-02-01

    Full Text Available We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC and reversible jump MCMC (RJMCMC methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI, which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion.

  13. 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

  14. 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...

  15. Airborne LiDAR reflective linear feature extraction for strip adjustment and horizontal accuracy determination.

    Science.gov (United States)

    2009-02-01

    ODOT's Office of Aerial Engineering (OAE) has been using an Opetch 30/70 ALTM airborne LiDAR system for about four years. The introduction of LiDAR technology was a major development towards improving the mapping operations. The overall experiences a...

  16. Regression modeling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral data

    Science.gov (United States)

    Andrew T. Hudak; Nicholas L. Crookston; Jeffrey S. Evans; Michael K. Falkowski; Alistair M. S. Smith; Paul E. Gessler; Penelope Morgan

    2006-01-01

    We compared the utility of discrete-return light detection and ranging (lidar) data and multispectral satellite imagery, and their integration, for modeling and mapping basal area and tree density across two diverse coniferous forest landscapes in north-central Idaho. We applied multiple linear regression models subset from a suite of 26 predictor variables derived...

  17. LSNR Airborne LIDAR Mapping System Design and Early Results (Invited)

    Science.gov (United States)

    Shrestha, K.; Carter, W. E.; Slatton, K. C.

    2009-12-01

    Low signal-to-noise ratio (LSNR) detection techniques allow for implementation of airborne light detection and range (LIDAR) instrumentation aboard platforms with prohibitive power, size, and weight restrictions. The University of Florida has developed the Coastal Area Tactical-mapping System (CATS), a prototype LSNR LIDAR system capable of single photon laser ranging. CATS is designed to operate in a fixed-wing aircraft flying 600 m above ground level, producing 532 nm, 480 ps, 3 μJ output pulses at 8 kHz. To achieve continuous coverage of the terrain with 20 cm spatial resolution in a single pass, a 10x10 array of laser beamlets is scanned. A Risley prism scanner (two rotating V-coated optical wedges) allows the array of laser beamlets to be deflected in a variety of patterns, including conical, spiral, and lines at selected angles to the direction of flight. Backscattered laser photons are imaged onto a 100 channel (10x10 segmented-anode) photomultiplier tube (PMT) with a micro-channel plate (MCP) amplifier. Each channel of the PMT is connected to a multi-stop 2 GHz event timer. Here we report on tests in which ranges for known targets were accumulated for repeated laser shots and statistical analyses were applied to evaluate range accuracy, minimum separation distance, bathymetric mapping depth, and atmospheric scattering. Ground-based field test results have yielded 10 cm range accuracy and sub-meter feature identification at variable scan settings. These experiments also show that a secondary surface can be detected at a distance of 15 cm from the first. Range errors in secondary surface identification for six separate trials were within 7.5 cm, or within the timing resolution limit of the system. Operating at multi-photon sensitivity may have value for situations in which high ambient noise precludes single-photon sensitivity. Low reflectivity targets submerged in highly turbid waters can cause detection issues. CATS offers the capability to adjust the

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  3. Airborne Lidar: Advances in Discrete Return Technology for 3D Vegetation Mapping

    Directory of Open Access Journals (Sweden)

    Valerie Ussyshkin

    2011-02-01

    Full Text Available Conventional discrete return airborne lidar systems, used in the commercial sector for efficient generation of high quality spatial data, have been considered for the past decade to be an ideal choice for various mapping applications. Unlike two-dimensional aerial imagery, the elevation component of airborne lidar data provides the ability to represent vertical structure details with very high precision, which is an advantage for many lidar applications focusing on the analysis of elevated features such as 3D vegetation mapping. However, the use of conventional airborne discrete return lidar systems for some of these applications has often been limited, mostly due to relatively coarse vertical resolution and insufficient number of multiple measurements in vertical domain. For this reason, full waveform airborne sensors providing more detailed representation of target vertical structure have often been considered as a preferable choice in some areas of 3D vegetation mapping application, such as forestry research. This paper presents an overview of the specific features of airborne lidar technology concerning 3D mapping applications, particularly vegetation mapping. Certain key performance characteristics of lidar sensors important for the quality of vegetation mapping are discussed and illustrated by the advanced capabilities of the ALTM-Orion, a new discrete return sensor manufactured by Optech Incorporated. It is demonstrated that advanced discrete return sensors with enhanced 3D mapping capabilities can produce data of enhanced quality, which can represent complex structures of vegetation targets at the level of details equivalent in some aspects to the content of full waveform data. It is also shown that recent advances in conventional airborne lidar technology bear the potential to create a new application niche, where high quality dense point clouds, enhanced by fully recorded intensity for multiple returns, may provide sufficient

  4. TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

    Directory of Open Access Journals (Sweden)

    K. Bakuła

    2016-06-01

    Full Text Available Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images, spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and

  5. Mapping Above- and Below-Ground Carbon Pools in Boreal Forests: The Case for Airborne Lidar.

    Science.gov (United States)

    Kristensen, Terje; Næsset, Erik; Ohlson, Mikael; Bolstad, Paul V; Kolka, Randall

    2015-01-01

    A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

  6. 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.

  7. 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.

  8. Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification

    Directory of Open Access Journals (Sweden)

    Wei Gong

    2015-09-01

    Full Text Available The abilities of multispectral LiDAR (MSL as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.

  9. 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.

  10. Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

    Science.gov (United States)

    Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

    2017-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

  11. Characterizing Forest Succession Stages for Wildlife Habitat Assessment Using Multispectral Airborne Imagery

    Directory of Open Access Journals (Sweden)

    Wen Zhang

    2017-06-01

    Full Text Available In this study, we demonstrate the potential of using high spatial resolution airborne imagery to characterize the structural development stages of forest canopies. Four forest succession stages were adopted: stand initiation, young multistory, understory reinitiation, and old growth. Remote sensing metrics describing the spatial patterns of forest structures were derived and a Random Forest learning algorithm was used to classify forest succession stages. These metrics included texture variables from Gray Level Co-occurrence Measures (GLCM, range and sill from the semi-variogram, and the fraction of shadow and its spatial distribution. Among all the derived variables, shadow fractions and the GLCM variables of contrast, mean, and dissimilarity were the most important for characterizing the forest succession stages (classification accuracy of 89%. In addition, a LiDAR (Light Detection and Ranging derived forest structural index (predicted Lorey’s height was employed to validate the classification result. The classification using imagery spatial variables was shown to be consistent with the LiDAR derived variable (R2 = 0.68 and Root Mean Square Error (RMSE = 2.39. This study demonstrates that high spatial resolution imagery was able to characterize forest succession stages with promising accuracy and may be considered an alternative to LiDAR data for this kind of application. Also, the results of stand development stages build a framework for future wildlife habitat mapping.

  12. 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...

  13. 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...

  14. Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data

    Science.gov (United States)

    Qi Chen; Dengsheng Lu; Michael Keller; Maiza dos-Santos; Edson Bolfe; Yunyun Feng; Changwei Wang

    2015-01-01

    Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems...

  15. 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...

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. An Airborne Multispectral Imaging System Based on Two Consumer-Grade Cameras for Agricultural Remote Sensing

    Directory of Open Access Journals (Sweden)

    Chenghai Yang

    2014-06-01

    Full Text Available This paper describes the design and evaluation of an airborne multispectral imaging system based on two identical consumer-grade cameras for agricultural remote sensing. The cameras are equipped with a full-frame complementary metal oxide semiconductor (CMOS sensor with 5616 × 3744 pixels. One camera captures normal color images, while the other is modified to obtain near-infrared (NIR images. The color camera is also equipped with a GPS receiver to allow geotagged images. A remote control is used to trigger both cameras simultaneously. Images are stored in 14-bit RAW and 8-bit JPEG files in CompactFlash cards. The second-order transformation was used to align the color and NIR images to achieve subpixel alignment in four-band images. The imaging system was tested under various flight and land cover conditions and optimal camera settings were determined for airborne image acquisition. Images were captured at altitudes of 305–3050 m (1000–10,000 ft and pixel sizes of 0.1–1.0 m were achieved. Four practical application examples are presented to illustrate how the imaging system was used to estimate cotton canopy cover, detect cotton root rot, and map henbit and giant reed infestations. Preliminary analysis of example images has shown that this system has potential for crop condition assessment, pest detection, and other agricultural applications.

  1. 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.

  2. 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; hide

    2010-01-01

    A high-performance Raman lidar operating in the UV portion of the spectrum has been used to acquire, for the first time using a single lidar, simultaneous airborne profiles of the water vapor mixing ratio, aerosol backscatter, aerosol extinction, aerosol depolarization and research mode measurements of cloud liquid water, cloud droplet radius, and number density. The Raman Airborne Spectroscopic Lidar (RASL) system was installed in a Beechcraft King Air B200 aircraft and was flown over the mid-Atlantic United States during July August 2007 at altitudes ranging between 5 and 8 km. During these flights, despite suboptimal laser performance and subaperture use of the telescope, all RASL measurement expectations were met, except that of aerosol extinction. Following the Water Vapor Validation Experiment Satellite/Sondes (WAVES_2007) field campaign in the summer of 2007, RASL was installed in a mobile trailer for groundbased use during the Measurements of Humidity and Validation Experiment (MOHAVE-II) field campaign held during October 2007 at the Jet Propulsion Laboratory s Table Mountain Facility in southern California. This ground-based configuration of the lidar hardware is called Atmospheric Lidar for Validation, Interagency Collaboration and Education (ALVICE). During theMOHAVE-II field campaign, during which only nighttime measurements were made, ALVICE demonstrated significant sensitivity to lower-stratospheric water vapor. Numerical simulation and comparisons with a cryogenic frost-point hygrometer are used to demonstrate that a system with the performance characteristics of RASL ALVICE should indeed be able to quantify water vapor well into the lower stratosphere with extended averaging from an elevated location like Table Mountain. The same design considerations that optimize Raman lidar for airborne use on a small research aircraft are, therefore, shown to yield significant dividends in the quantification of lower-stratospheric water vapor. The MOHAVE

  3. 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.

  4. 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.

  5. 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.

  6. High Spatial Resolution Airborne Multispectral Thermal Infrared Remote Sensing Data for Analysis of Urban Landscape Characteristics

    Science.gov (United States)

    Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.; Arnold, James E. (Technical Monitor)

    2000-01-01

    We have used airborne multispectral thermal infrared (TIR) remote sensing data collected at a high spatial resolution (i.e., 10m) over several cities in the United States to study thermal energy characteristics of the urban landscape. These TIR data provide a unique opportunity to quantify thermal responses from discrete surfaces typical of the urban landscape and to identify both the spatial arrangement and patterns of thermal processes across the city. The information obtained from these data is critical to understanding how urban surfaces drive or force development of the Urban Heat Island (UHI) effect, which exists as a dome of elevated air temperatures that presides over cities in contrast to surrounding non-urbanized areas. The UHI is most pronounced in the summertime where urban surfaces, such as rooftops and pavement, store solar radiation throughout the day, and release this stored energy slowly after sunset creating air temperatures over the city that are in excess of 2-4'C warmer in contrast with non-urban or rural air temperatures. The UHI can also exist as a daytime phenomenon with surface temperatures in downtown areas of cities exceeding 38'C. The implications of the UHI are significant, particularly as an additive source of thermal energy input that exacerbates the overall production of ground level ozone over cities. We have used the Airborne Thermal and Land Applications Sensor (ATLAS), flown onboard a Lear 23 jet aircraft from the NASA Stennis Space Center, to acquire high spatial resolution multispectral TIR data (i.e., 6 bandwidths between 8.2-12.2 (um) over Huntsville, Alabama, Atlanta, Georgia, Baton Rouge, Louisiana, Salt Lake City, Utah, and Sacramento, California. These TIR data have been used to produce maps and other products, showing the spatial distribution of heating and cooling patterns over these cities to better understand how the morphology of the urban landscape affects development of the UHI. In turn, these data have been used

  7. 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.; hide

    2012-01-01

    Knowledge of aerosol composition and vertical distribution is crucial for assessing the impact of aerosols on climate. In addition, aerosol classification is a key input to CALIOP aerosol retrievals, since CALIOP requires an inference of the lidar ratio in order to estimate the effects of aerosol extinction and backscattering. In contrast, the NASA airborne HSRL-1 directly measures both aerosol extinction and backscatter, and therefore the lidar ratio (extinction-to-backscatter ratio). Four aerosol intensive properties from HSRL-1 are combined to infer aerosol type. Aerosol classification results from HSRL-1 are used here to validate the CALIOP aerosol type inferences.

  8. 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.

  9. 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...

  10. Airborne LiDAR reflective linear feature extraction for strip adjustment and horizontal accuracy determination : executive summary.

    Science.gov (United States)

    2009-02-01

    The Office of Aerial Engineering (OAE) has been : using an Optech 30/70 ALTM airborne LiDAR system : for about four years. The introduction of LiDAR : technology was a major development towards : improving the mapping operations, and the overall : ex...

  11. 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.

  12. 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.

  13. Airborne Thermal Infrared Multispectral Scanner (TIMS) images over disseminated gold deposits, Osgood Mountains, Humboldt County, Nevada

    Science.gov (United States)

    Krohn, M. Dennis

    1986-01-01

    The U.S. Geological Survey (USGS) acquired airborne Thermal Infrared Multispectral Scanner (TIMS) images over several disseminated gold deposits in northern Nevada in 1983. The aerial surveys were flown to determine whether TIMS data could depict jasperoids (siliceous replacement bodies) associated with the gold deposits. The TIMS data were collected over the Pinson and Getchell Mines in the Osgood Mountains, the Carlin, Maggie Creek, Bootstrap, and other mines in the Tuscarora Mountains, and the Jerritt Canyon Mine in the Independence Mountains. The TIMS data seem to be a useful supplement to conventional geochemical exploration for disseminated gold deposits in the western United States. Siliceous outcrops are readily separable in the TIMS image from other types of host rocks. Different forms of silicification are not readily separable, yet, due to limitations of spatial resolution and spectral dynamic range. Features associated with the disseminated gold deposits, such as the large intrusive bodies and fault structures, are also resolvable on TIMS data. Inclusion of high-resolution thermal inertia data would be a useful supplement to the TIMS data.

  14. Airborne LIDAR borsight error calibration based on surface coincide

    International Nuclear Information System (INIS)

    Yuan, Fangyan; Li, Guoqing; Zuo, Zhengli; Li, Dong; Qi, Zengying; Qiu, Wen; Tan, Junxiang

    2014-01-01

    Light Detection and Ranging (LIDAR) is a system which can directly collect three-dimensional coordinate information of ground point and laser reflection strength information. With the wide application of LIDAR system, users hope to get more accurate results. Boresight error has an important effect on data accuracy and thus, it is thought that eliminating the error is very important. In recent years, many methods have been proposed to eliminate the error. Generally, they can be categorized into tie point method and surface matching method. In this paper, we propose another method called try value method based on surface coincide that is used in actual production by many companies. The method is simple and operable. Further, the efficacy of the method was demonstrated by analyzing the data from Zhangye city

  15. Airborne ocean water lidar (OWL) real time processor (RTP)

    Science.gov (United States)

    Hryszko, M.

    1995-03-01

    The Hyperflo Real Time Processor (RTP) was developed by Pacific-Sierra Research Corporation as a part of the Naval Air Warfare Center's Ocean Water Lidar (OWL) system. The RTP was used for real time support of open ocean field tests at Barbers Point, Hawaii, in March 1993 (EMERALD I field test), and Jacksonville, Florida, in July 1994 (EMERALD I field test). This report describes the system configuration, and accomplishments associated with the preparation and execution of these exercises. This document is intended to supplement the overall test reports and provide insight into the development and use of the PTP. A secondary objective is to provide basic information on the capabilities, versatility and expandability of the Hyperflo RTP for possible future projects. It is assumed herein that the reader has knowledge of the OWL system, field test operations, general lidar processing methods, and basic computer architecture.

  16. 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.

  17. Multispectral thermal airborne TASI-600 data to study the Pompeii (IT) archaeological area

    Science.gov (United States)

    Palombo, Angelo; Pascucci, Simone; Pergola, Nicola; Pignatti, Stefano; Santini, Federico; Soldovieri, Francesco

    2016-04-01

    The management of archaeological areas refers to the conservation of the ruins/buildings and the eventual prospection of new areas having an archaeological potential. In this framework, airborne remote sensing is a well-developed geophysical tool for supporting the archaeological surveys of wide areas. The spectral regions applied in archaeological remote sensing spans from the VNIR to the TIR. In particular, the archaeological thermal imaging considers that materials absorb, emit, transmit, and reflect the thermal infrared radiation at different rate according to their composition, density and moisture content. Despite its potential, thermal imaging in archaeological applications are scarce. Among them, noteworthy are the ones related to the use of Landsat and ASTER [1] and airborne remote sensing [2, 3, 4 and 5]. In view of these potential in Cultural Heritage applications, the present study aims at analysing the usefulness of the high spatial resolution thermal imaging on the Pompeii archaeological park. To this purpose TASI-600 [6] airborne multispectral thermal imagery (32 channels from 8 to 11.5 nm with a spectral resolution of 100nm and a spatial resolution of 1m/pixel) was acquired on December the 7th, 2015. Airborne survey has been acquired to get useful information on the building materials (both ancient and of consolidation) characteristics and, whenever possible, to retrieve quick indicators on their conservation status. Thermal images will be, moreover, processed to have an insight of the critical environmental issues impacting the structures (e.g. moisture). The proposed study shows the preliminary results of the airborne deployments, the pre-processing of the multispectral thermal imagery and the retrieving of accurate land surface temperatures (LST). LST map will be analysed to describe the thermal pattern of the city of Pompeii and detect any thermal anomalies. As far as the ongoing TASI-600 sensors pre-processing, it will include: (a) radiometric

  18. 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.

  19. MERGING AIRBORNE LIDAR DATA AND SATELLITE SAR DATA FOR BUILDING CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    T. Yamamoto

    2015-05-01

    Full Text Available A frequent map revision is required in GIS applications, such as disaster prevention and urban planning. In general, airborne photogrammetry and LIDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, attribute data acquisition and classification depend on manual editing works including ground surveys. In general, airborne photogrammetry and LiDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, these approaches classify geometrical attributes. Moreover, ground survey and manual editing works are finally required in attribute data classification. On the other hand, although geometrical data extraction is difficult, SAR data have a possibility to automate the attribute data acquisition and classification. The SAR data represent microwave reflections on various surfaces of ground and buildings. There are many researches related to monitoring activities of disaster, vegetation, and urban. Moreover, we have an opportunity to acquire higher resolution data in urban areas with new sensors, such as ALOS2 PALSAR2. Therefore, in this study, we focus on an integration of airborne LIDAR data and satellite SAR data for building extraction and classification.

  20. 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.

  1. 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.

  2. Airborne differential absorption lidar system for water vapor investigations

    Science.gov (United States)

    Browell, E. V.; Carter, A. F.; Wilkerson, T. D.

    1981-01-01

    Range-resolved water vapor measurements using the differential-absorption lidar (DIAL) technique is described in detail. The system uses two independently tunable optically pumped lasers operating in the near infrared with laser pulses of less than 100 microseconds separation, to minimize concentration errors caused by atmospheric scattering. Water vapor concentration profiles are calculated for each measurement by a minicomputer, in real time. The work is needed in the study of atmospheric motion and thermodynamics as well as in forestry and agriculture problems.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. Use of airborne multispectral scanner data to map alteration related to roll-front uranium migration

    International Nuclear Information System (INIS)

    Peters, D.C.

    1983-01-01

    Computer-enhanced airborne multispectral scanner (MSS) images have been used to detect and map red oxidized alteration related to roll-front uranium migration in the southern Powder River basin, Wyoming. Information in the 0.4- to 1.1-μm spectral region was used to produce a color ratio composite image, upon which the red-altered areas can be differentiated. The red-altered and incipiently altered sandstones result from the migration of a roll-front (or geochemical cell) through the sandstone in the direction of the hydrologic gradient. Most uranium deposits in the Powder River basin occur at the boundary between this oxidized sandstone and reduced sandstone. Therefore, the ability to detect and map this alteration reliably can provide important information about the potential for uranium mineralization down gradient from the altered areas, at the surface in an area of interest. Spectral reflectance studies indicate that a shift in the absorption band edge from 0.52 μm (for goethitic sandstone) to 0.58 μm (for hematitic sandstone) and an intensification of an absorption band at 0.85 μm (for hematitic sandstone) are the bases for identifying the red-altered sandstone as green anomalous areas on the color ratio composite image. Some of the incipiently altered sandstone also appears green, whereas unaltered material and white-altered sandstone appear as blue to cyan colors. Therefore, the composite image is useful in discriminating hematitic sandstone from goethitic sandstone. At high densities (>65%), vegetation masks the sandstones on the color ratio composite image. Artemisia tridentata (sage) and Stipa comata (grass) are the species that have the greatest individual effect on the image

  8. 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.

  9. 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.

  10. Quantifying spatial variability of depth of peat burn in wetlands in relation to antecedent characteristics using field data, multi-temporal and multi-spectral LiDAR

    Science.gov (United States)

    Chasmer, L.; Flade, L.; Virk, R.; Montgomery, J. S.; Hopkinson, C.; Thompson, D. K.; Petrone, R. M.; Devito, K.

    2017-12-01

    Landscape changes in the hydrological characteristics of wetlands in some parts of the Boreal region of Canada are occurring as a result of climate-induced feedbacks and anthropogenic disturbance. Wetlands are largely resilient to wildfire, however, natural, climatic and anthropogenic disturbances can change surface water regimes and predispose wetlands to greater depth of peat burn. Over broad areas, peat loss contributes to significant pollution emissions, which can affect community health. In this study, we a) quantify depth of peat burn and relationships to antecedent conditions (species type, topography, surficial geology) within three classified wetlands found in the Boreal Plains ecoregion of western Canada; and b) examine the impacts of wildfire on post-fire ground surface energy balance to determine how peat loss might affect local hydro-climatology and surface water feedbacks. High-resolution optical imagery, pre- and post-burn multi-spectral Light Detection And Ranging (LiDAR), airborne thermal infrared imagery, and field validation data products are integrated to identify multiple complex interactions within the study wetlands. LiDAR-derived depth of peat burn is within 1 cm (average) compared with measured (RMSE = 9 cm over the control surface), demonstrating the utility of LiDAR with high point return density. Depth of burn also correlates strongly with variations in Normalised Burn Ratio (NBR) determined for ground surfaces only. Antecedent conditions including topographic position, soil moisture, soil type and wetland species also have complex interactions with depth of peat loss within wetlands observed in other studies. However, while field measurements are important for validation and understanding eco-hydrological processes, results from remote sensing are spatially continuous. Temporal LiDAR data illustrate the full range of variability in depth of burn and wetland characteristics following fire. Finally, measurements of instantaneous surface

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. Effectiveness of airborne multispectral thermal data for karst groundwater resources recognition in coastal areas

    Science.gov (United States)

    Pignatti, Stefano; Fusilli, Lorenzo; Palombo, Angelo; Santini, Federico; Pascucci, Simone

    2013-04-01

    Currently the detection, use and management of groundwater in karst regions can be considered one of the most significant procedures for solving water scarcity problems during periods of low rainfall this because groundwater resources from karst aquifers play a key role in the water supply in karst areas worldwide [1]. In many countries of the Mediterranean area, where karst is widespread, groundwater resources are still underexploited, while surface waters are generally preferred [2]. Furthermore, carbonate aquifers constitute a crucial thermal water resource outside of volcanic areas, even if there is no detailed and reliable global assessment of thermal water resources. The composite hydrogeological characteristics of karst, particularly directions and zones of groundwater distribution, are not up till now adequately explained [3]. In view of the abovementioned reasons the present study aims at analyzing the detection capability of high spatial resolution thermal remote sensing of karst water resources in coastal areas in order to get useful information on the karst springs flow and on different characteristics of these environments. To this purpose MIVIS [4, 5] and TASI-600 [6] airborne multispectral thermal imagery (see sensors' characteristics in Table 1) acquired on two coastal areas of the Mediterranean area interested by karst activity, one located in Montenegro and one in Italy, were used. One study area is located in the Kotor Bay, a winding bay on the Adriatic Sea surrounded by high mountains in south-western Montenegro and characterized by many subaerial and submarine coastal springs related to deep karstic channels. The other study area is located in Santa Cesarea (Italy), encompassing coastal cold springs, the main local source of high quality water, and also a noticeable thermal groundwater outflow. The proposed study shows the preliminary results of the two airborne deployments on these areas. The preprocessing of the multispectral thermal imagery

  16. 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.

  17. 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.

  18. 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.

  19. Light Detection and Ranging (LiDAR and Multispectral Scanner (MSS Studies Examine Coastal Environments Influenced by Mining

    Directory of Open Access Journals (Sweden)

    W. Charles Kerfoot

    2014-01-01

    Full Text Available There are numerous examples of past and present mine disposal into freshwater and marine coastal bays and riverine environments. Due to its high spatial resolution and extended water penetration, coastal light detection and ranging (LiDAR, coupled with multispectral scanning (MSS, has great promise for resolving disturbed shoreline features in low turbidity environments. Migrating mine tailings present serious issues for Lake Superior and coastal marine environments. Previous investigations in Lake Superior uncovered a metal-rich “halo” around the Keweenaw Peninsula, related to past copper mining practices. For over a century, waste rock migrating from shoreline tailing piles has moved along extensive stretches of coastline, compromising critical fish breeding grounds, damming stream outlets, transgressing into wetlands and along recreational beaches and suppressing benthic invertebrate communities. In Grand (Big Traverse Bay, Buffalo Reef is an important spawning area for lake trout and whitefish threatened by drifting tailings. The movement of tailings into Buffalo Reef cobble fields may interfere with the hatching of fish eggs and fry survival, either by filling in crevices where eggs are deposited or by toxic effects on eggs, newly hatched larvae or benthic communities. Here, we show that the coastal tailing migration is not “out of sight, out of mind”, but clearly revealed by using a combination of LiDAR and MSS techniques.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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; hide

    2014-01-01

    An airborne 2 micron triple-pulse integrated path differential absorption (IPDA) lidar is currently under development at NASA Langley Research Center (LaRC). This lidar targets both atmospheric carbon dioxide (CO2) and water vapor (H2O) column measurements, simultaneously. Advancements in the development of this IPDA lidar are presented in this paper. Updates on advanced two-micron triple-pulse high-energy laser transmitter will be given including packaging and lidar integration status. In addition, receiver development updates will also be presented. This includes a state-of-the-art detection system integrated at NASA Goddard Space Flight Center. This detection system is based on a newly developed HgCdTe (MCT) electron-initiated avalanche photodiode (e-APD) array. Future plan for IPDA lidar system for ground integration, testing and flight validation will be discussed.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Airborne multispectral identification of individual cotton plants using consumer-grade cameras

    Science.gov (United States)

    Although multispectral remote sensing using consumer-grade cameras has successfully identified fields of small cotton plants, improvements to detection sensitivity are needed to identify individual or small clusters of plants. The imaging sensor of consumer-grade cameras are based on a Bayer patter...

  20. 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

  1. 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

  2. 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

  3. 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%.

  4. 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.

  5. 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.

  6. 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)

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

    Science.gov (United States)

    Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

    2014-11-01

    This work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary *.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM

  4. 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.

  5. 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.

  6. [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.

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

    Science.gov (United States)

    Alonzo, Michael; Morton, Douglas C.; Cook, Bruce D.; Andersen, Hans-Erik; Babcock, Chad; Pattison, Robert

    2017-01-01

    Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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.

  18. Synoptic channel morphodynamics with topo-bathymetric airborne lidar: promises, pitfalls and research needs

    Science.gov (United States)

    Lague, D.; Launeau, P.; Gouraud, E.

    2017-12-01

    Topo-bathymetric airborne lidar sensors using a green laser penetrating water and suitable for hydrography are now sold by major manufacturers. In the context of channel morphodynamics, repeat surveys could offer synoptic high resolution measurement of topo-bathymetric change, a key data that is currently missing. Yet, beyond the technological promise, what can we really achieve with these sensors in terms of depth penetration and bathymetric accuracy ? Can all rivers be surveyed ? How easy it is to process this new type of data to get the data needed by geomorphologists ? Here we report on the use of the Optech Titan dual wavelength (1064 nm & 532 nm) operated by the universities of Rennes and Nantes (France) and deployed over several rivers and lakes in France, including repeat surveys. We will illustrate cases where the topo-bathymetric survey is complete, reaching up to 6 m in rivers and offers unprecedented data for channel morphology analysis over tens of kilometres. We will also present challenging cases for which the technology will never work, or for which new algorithms to process full waveform are required. We will illustrate new developments for automated processing of large datasets, including the critical step of water surface detection and refraction correction. In suitable rivers, airborne topo-bathymetric surveys offer unprecedented synoptic 3D data at very high resolution (> 15 pts/m² in bathy) and precision (better than 10 cm for the bathy) down to 5-6 meters depth, with a perfectly continuous topography to bathymetry transition. This presentation will illustrate how this new type of data, when combined with 2D hydraulics modelling offers news insights into the spatial variations of friction in relation to channel bedforms, and the connectivity between rivers and floodplains.

  19. Airborne differential absorption lidar system for measurements of atmospheric water vapor and aerosols

    Science.gov (United States)

    Carter, Arlen F.; Allen, Robert J.; Mayo, M. Neale; Butler, Carolyn F.; Grossman, Benoist E.; Ismail, Syed; Grant, William B.; Browell, Edward V.; Higdon, Noah S.; Mayor, Shane D.; hide

    1994-01-01

    An airborne differential absorption lidar (DIAL) system has been developed at the NASA Langley Research Center for remote measurements of atmospheric water vapor (H2O) and aerosols. A solid-state alexandrite laser with a 1-pm linewidth and greater than 99.85% spectral purity was used as the on-line transmitter. Solid-state avalanche photodiode detector technology has replaced photomultiplier tubes in the receiver system, providing an average increase by a factor of 1.5-2.5 in the signal-to-noise ratio of the H2O measurement. By incorporating advanced diagnostic and data-acquisition instrumentation into other subsystems, we achieved additional improvements in system operational reliability and measurement accuracy. Laboratory spectroscopic measurements of H2O absorption-line parameters were performed to reduce the uncertainties in our knowledge of the absorption cross sections. Line-center H2O absorption cross sections were determined, with errors of 3-6%, for more than 120 lines in the 720-nm region. Flight tests of the system were conducted during 1989-1991 on the NASA Wallops Flight Facility Electra aircraft, and extensive intercomparison measurements were performed with dew-point hygrometers and H2O radiosondes. The H2O distributions measured with the DIAL system differed by less than 10% from the profiles determined with the in situ probes in a variety of atmospheric conditions.

  20. 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.

  1. 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.

  2. a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

    Science.gov (United States)

    Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

    2018-04-01

    Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

  3. Improved Model for Depth Bias Correction in Airborne LiDAR Bathymetry Systems

    Directory of Open Access Journals (Sweden)

    Jianhu Zhao

    2017-07-01

    Full Text Available Airborne LiDAR bathymetry (ALB is efficient and cost effective in obtaining shallow water topography, but often produces a low-accuracy sounding solution due to the effects of ALB measurements and ocean hydrological parameters. In bathymetry estimates, peak shifting of the green bottom return caused by pulse stretching induces depth bias, which is the largest error source in ALB depth measurements. The traditional depth bias model is often applied to reduce the depth bias, but it is insufficient when used with various ALB system parameters and ocean environments. Therefore, an accurate model that considers all of the influencing factors must be established. In this study, an improved depth bias model is developed through stepwise regression in consideration of the water depth, laser beam scanning angle, sensor height, and suspended sediment concentration. The proposed improved model and a traditional one are used in an experiment. The results show that the systematic deviation of depth bias corrected by the traditional and improved models is reduced significantly. Standard deviations of 0.086 and 0.055 m are obtained with the traditional and improved models, respectively. The accuracy of the ALB-derived depth corrected by the improved model is better than that corrected by the traditional model.

  4. 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.

  5. 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

  6. A Stochastic Geometry Method for Pylon Reconstruction from Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Bo Guo

    2016-03-01

    Full Text Available Object detection and reconstruction from remotely sensed data are active research topic in photogrammetric and remote sensing communities. Power engineering device monitoring by detecting key objects is important for power safety. In this paper, we introduce a novel method for the reconstruction of self-supporting pylons widely used in high voltage power-line systems from airborne LiDAR data. Our work constructs pylons from a library of 3D parametric models, which are represented using polyhedrons based on stochastic geometry. Firstly, laser points of pylons are extracted from the dataset using an automatic classification method. An energy function made up of two terms is then defined: the first term measures the adequacy of the objects with respect to the data, and the second term has the ability to favor or penalize certain configurations based on prior knowledge. Finally, estimation is undertaken by minimizing the energy using simulated annealing. We use a Markov Chain Monte Carlo sampler, leading to an optimal configuration of objects. Two main contributions of this paper are: (1 building a framework for automatic pylon reconstruction; and (2 efficient global optimization. The pylons can be precisely reconstructed through energy optimization. Experiments producing convincing results validated the proposed method using a dataset of complex structure.

  7. 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

  8. Capturing the Green River -- Multispectral airborne videography to evaluate the environmental impacts of hydropower operations

    International Nuclear Information System (INIS)

    Snider, M.A.; Hayse, J.W.; Hlohowskyj, I.; LaGory, K.E.

    1996-01-01

    The 500-mile long Green River is the largest tributary of the Colorado River. From its origin in the Wind River Range mountains of western Wyoming to its confluence with the Colorado River in southeastern Utah, the Green River is vital to the arid region through which it flows. Large portions of the area remain near-wilderness with the river providing a source of recreation in the form of fishing and rafting, irrigation for farming and ranching, and hydroelectric power. In the late 1950's and early 1960's hydroelectric facilities were built on the river. One of these, Flaming Gorge Dam, is located just south of the Utah-Wyoming border near the town of Dutch John, Utah. Hydropower operations result in hourly and daily fluctuations in the releases of water from the dam that alter the natural stream flow below the dam and affect natural resources in and along the river corridor. In the present study, the authors were interested in evaluating the potential impacts of hydropower operations at Flaming Gorge Dam on the downstream natural resources. Considering the size of the area affected by the daily pattern of water release at the dam as well as the difficult terrain and limited accessibility of many reaches of the river, evaluating these impacts using standard field study methods was virtually impossible. Instead an approach was developed that used multispectral aerial videography to determine changes in the affected parameters at different flows, hydrologic modeling to predict flow conditions for various hydropower operating scenarios, and ecological information on the biological resources of concern to assign impacts

  9. 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.

  10. 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.

  11. 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

  12. Multispectral Terrain Background Simulation Techniques For Use In Airborne Sensor Evaluation

    Science.gov (United States)

    Weinberg, Michael; Wohlers, Ronald; Conant, John; Powers, Edward

    1988-08-01

    A background simulation code developed at Aerodyne Research, Inc., called AERIE is designed to reflect the major sources of clutter that are of concern to staring and scanning sensors of the type being considered for various airborne threat warning (both aircraft and missiles) sensors. The code is a first principles model that could be used to produce a consistent image of the terrain for various spectral bands, i.e., provide the proper scene correlation both spectrally and spatially. The code utilizes both topographic and cultural features to model terrain, typically from DMA data, with a statistical overlay of the critical underlying surface properties (reflectance, emittance, and thermal factors) to simulate the resulting texture in the scene. Strong solar scattering from water surfaces is included with allowance for wind driven surface roughness. Clouds can be superimposed on the scene using physical cloud models and an analytical representation of the reflectivity obtained from scattering off spherical particles. The scene generator is augmented by collateral codes that allow for the generation of images at finer resolution. These codes provide interpolation of the basic DMA databases using fractal procedures that preserve the high frequency power spectral density behavior of the original scene. Scenes are presented illustrating variations in altitude, radiance, resolution, material, thermal factors, and emissivities. The basic models utilized for simulation of the various scene components and various "engineering level" approximations are incorporated to reduce the computational complexity of the simulation.

  13. A GUI visualization system for airborne lidar image data to reconstruct 3D city model

    Science.gov (United States)

    Kawata, Yoshiyuki; Koizumi, Kohei

    2015-10-01

    A visualization toolbox system with graphical user interfaces (GUIs) was developed for the analysis of LiDAR point cloud data, as a compound object oriented widget application in IDL (Interractive Data Language). The main features in our system include file input and output abilities, data conversion capability from ascii formatted LiDAR point cloud data to LiDAR image data whose pixel value corresponds the altitude measured by LiDAR, visualization of 2D/3D images in various processing steps and automatic reconstruction ability of 3D city model. The performance and advantages of our graphical user interface (GUI) visualization system for LiDAR data are demonstrated.

  14. TREE SPECIES CLASSIFICATION OF BROADLEAVED FORESTS IN NAGANO, CENTRAL JAPAN, USING AIRBORNE LASER DATA AND MULTISPECTRAL IMAGES

    Directory of Open Access Journals (Sweden)

    S. Deng

    2017-10-01

    Full Text Available This study attempted to classify three coniferous and ten broadleaved tree species by combining airborne laser scanning (ALS data and multispectral images. The study area, located in Nagano, central Japan, is within the broadleaved forests of the Afan Woodland area. A total of 235 trees were surveyed in 2016, and we recorded the species, DBH, and tree height. The geographical position of each tree was collected using a Global Navigation Satellite System (GNSS device. Tree crowns were manually detected using GNSS position data, field photographs, true-color orthoimages with three bands (red-green-blue, RGB, 3D point clouds, and a canopy height model derived from ALS data. Then a total of 69 features, including 27 image-based and 42 point-based features, were extracted from the RGB images and the ALS data to classify tree species. Finally, the detected tree crowns were classified into two classes for the first level (coniferous and broadleaved trees, four classes for the second level (Pinus densiflora, Larix kaempferi, Cryptomeria japonica, and broadleaved trees, and 13 classes for the third level (three coniferous and ten broadleaved species, using the 27 image-based features, 42 point-based features, all 69 features, and the best combination of features identified using a neighborhood component analysis algorithm, respectively. The overall classification accuracies reached 90 % at the first and second levels but less than 60 % at the third level. The classifications using the best combinations of features had higher accuracies than those using the image-based and point-based features and the combination of all of the 69 features.

  15. 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

  16. 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.

  17. 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.

  18. Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

    Science.gov (United States)

    Sun, Shaohui

    Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a "divide-and-conquer" scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected

  19. 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

  20. 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.

  1. 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; hide

    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 approx. 5% for the CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 micro-s 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.

  2. 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.

  3. 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.

  4. Using satellite and airborne LiDAR to model woodpecker habitat occupancy at the landscape scale

    Science.gov (United States)

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

    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...

  5. 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.

  6. 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.

  7. Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

    Directory of Open Access Journals (Sweden)

    Jake E. Simpson

    2016-12-01

    Full Text Available We provide the first assessment of tropical peatland depth of burn (DoB using structure from motion (SfM photogrammetry, applied to imagery collected using a low-cost, low-altitude unmanned aerial vehicle (UAV system operated over a 5.2 ha tropical peatland in Jambi Province on Sumatra, Indonesia. Tropical peat soils are the result of thousands of years of dead biomass accumulation, and when burned are globally significant net sources of carbon emissions. The El Niño year of 2015 saw huge areas of Indonesia affected by tropical peatland fires, more so than any year since 1997. However, the Depth of Burn (DoB of these 2015 fires has not been assessed, and indeed has only previously been assessed in few tropical peatland burns in Kalimantan. Therefore, DoB remains arguably the largest uncertainty when undertaking fire emissions calculations in these tropical peatland environments. We apply a SfM photogrammetric methodology to map this DoB metric, and also investigate combustion heterogeneity using orthomosaic photography collected using the UAV system. We supplement this information with pre-burn airborne light detection and ranging (LiDAR data, reducing uncertainty by estimating pre-burn soil height more accurately than from interpolation of adjacent unburned areas alone. Our pre-and post-fire Digital Terrain Models (DTMs show accuracies of 0.04 and 0.05 m (root-mean-square error, RMSE respectively, compared to ground-based global navigation satellite system (GNSS surveys. Our final DoB map of a 5.2 ha degraded peat swamp forest area neighboring Berbak National Park (Sumatra, Indonesia shows burn depths extending from close to zero to over 1 m, with a mean (±1σ DoB of 0.23 ± 0.19 m. This lies well within the range found by the few other studies available (on Kalimantan; none are available on Sumatra. Our combustion heterogeneity analysis suggests the deepest burns, which extend to ~1.3 m, occur around tree roots. We use these DoB data within

  8. 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.

  9. 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.

  10. 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...

  11. 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.

  12. 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.

  13. Derivation of Burn Scar Depths with Airborne Light Detection and Ranging (LIDAR) in Indonesian Peatlands

    Science.gov (United States)

    Ballhorn, U.; Siegert, F.

    2009-04-01

    more CO2 per year than the fourth-largest industrial nation, Germany, saved to achieve its Kyoto target. Since 1990, emissions from peat burning and peat decomposition have exceeded that of above ground biomass deforestation. These numbers show how important it is to have more accurate estimations for peat burn depth in the future. Until now few field measurements were made, which would require to know the fire affected area in advance or ignite peatland on purpose. Furthermore fire scars are quickly covered by regenerating vegetation. Another problem is the lack of a method without actually having to go into the field (e.g. through remote sensing techniques), due to the fact that many of the fire locations are remote and very difficult to access. We investigated if airborne light detection and ranging (LIDAR), an active laser pulse technology by which the height of objects can be precisely measured, can be used to determine the amount of peat burned during a fire event. From a LIDAR data set acquired in Central Kalimantan, Borneo, in 2007, one year after severe fires resulting from the 2006 El Niño drought, we calculated that the average depth of a burn scar was 0.30 ± 0.15 m .This was achieved through the construction of digital terrain models (DTMs) by interpolating the LIDAR ground return signals in burnt and adjacent unburned peatland. These calculated depths were compared to in situ measurements, which came to similar results. We believe that the method presented here to estimate burnt peat depth has the potential to considerably improve the accuracy of regional and global carbon emission models but would also be helpful for monitoring projects under the Kyoto Protocol like the Clean Development Mechanism (CDM) or the proposed Reducing Emissions from Deforestation and Degradation (REDD) mechanism.

  14. Estimating mangrove aboveground biomass from airborne LiDAR data: a case study from the Zambezi River delta

    Science.gov (United States)

    Fatoyinbo, Temilola; Feliciano, Emanuelle A.; Lagomasino, David; Kuk Lee, Seung; Trettin, Carl

    2018-02-01

    Mangroves are ecologically and economically important forested wetlands with the highest carbon (C) density of all terrestrial ecosystems. Because of their exceptionally large C stocks and importance as a coastal buffer, their protection and restoration has been proposed as an effective mitigation strategy for climate change. The inclusion of mangroves in mitigation strategies requires the quantification of C stocks (both above and belowground) and changes to accurately calculate emissions and sequestration. A growing number of countries are becoming interested in using mitigation initiatives, such as REDD+ (reducing emissions from deforestation and forest degradation), in these unique coastal forests. However, it is not yet clear how methods to measure C traditionally used for other ecosystems can be modified to estimate biomass in mangroves with the precision and accuracy needed for these initiatives. Airborne Lidar (ALS) data has often been proposed as the most accurate way for larger scale assessments but the application of ALS for coastal wetlands is scarce, primarily due to a lack of contemporaneous ALS and field measurements. Here, we evaluated the variability in field and Lidar-based estimates of aboveground biomass (AGB) through the combination of different local and regional allometric models and standardized height metrics that are comparable across spatial resolutions and sensor types, the end result being a simplified approach for accurately estimating mangrove AGB at large scales and determining the uncertainty by combining multiple allometric models. We then quantified wall-to-wall AGB stocks of a tall mangrove forest in the Zambezi Delta, Mozambique. Our results indicate that the Lidar H100 height metric correlates well with AGB estimates, with R 2 between 0.80 and 0.88 and RMSE of 33% or less. When comparing Lidar H100 AGB derived from three allometric models, mean AGB values range from 192 Mg ha-1 up to 252 Mg ha-1. We suggest the best model

  15. 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

  16. 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

  17. High-Speed Fiber Optic Micromultiplexer for Space and Airborne Lidar, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — To address the NASA Earth Science Division need for high-speed fiber optic multiplexers for next generation lidar systems, Luminit proposes to develop a new Fiber...

  18. 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

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Quantifying edge effect extent and its impacts on carbon stocks across a degraded landscape in the Amazon using airborne lidar.

    Science.gov (United States)

    dos-Santos, M. N.; Keller, M.; Morton, D. C.; Longo, M.; Scaranello, M. A., Sr.; Pinagé, E. R.; Correa Pabon, R.

    2017-12-01

    Ongoing tropical forest degradation and forest fragmentation increases forest edge area. Forest edges experience hotter, drier, and windier conditions and greater exposure to fires compared to interior areas, which elevate rates of tree mortality. Previous studies have suggested that forests within 100 m from the edge may lose 36% of biomass during the first two decades following fragmentation, although such estimates are based on a limited number of experimental plots. Degraded forests behave differently from intact forests and quantifying edge effect extension in a degraded forest landscape is more challenging compared to experimental studies. To overcome these limitations, we used airborne lidar data to quantify changes in forest structure near 91 edges in a heavily degraded tropical forest in Paragominas Municipality, eastern Brazilian Amazon. Paragominas was a center of timber production in the 1990s. Today, the landscape is a mosaic of different agricultural uses, degraded, secondary and unmanaged forests. A total of 3000 ha of high density (mean density of 17.9 points/m2) lidar data were acquired in August/September 2013 and June/July 2014 over 30 transects (200 x 5000m), systematically distributed over the study area, using the Optech Orion M-200 laser scanning system. We adopted lidar-measured forest heights as the edge effect criteria and found that mean extent of edge effect was highly variable across degraded forests (150 ± 354m) and secondary forest fragments (265 ± 365m). We related the extent of forest edges to the historical disturbances identified in Landsat imagery since 1984. Contrary to previous studies, we found that carbon stocks along forest edges were not significantly lower than forest core biomass when edges were defined by previously estimated range of 100 and 300m. In frontier forests, ecological edge effect may be masked by the cumulative impact of historic forest degradation - an anthropogenic edge effect that extends beyond the

  7. Lidar Ice nuclei estimates and how they relate with airborne in-situ measurements

    Directory of Open Access Journals (Sweden)

    Marinou Eleni

    2018-01-01

    Full Text Available By means of available ice nucleating particle (INP parameterization schemes we compute profiles of dust INP number concentration utilizing Polly-XT and CALIPSO lidar observations during the INUIT-BACCHUS-ACTRIS 2016 campaign. The polarization-lidar photometer networking (POLIPHON method is used to separate dust and non-dust aerosol backscatter, extinction, mass concentration, particle number concentration (for particles with radius > 250 nm and surface area concentration. The INP final products are compared with aerosol samples collected from unmanned aircraft systems (UAS and analyzed using the ice nucleus counter FRIDGE.

  8. Lidar Ice nuclei estimates and how they relate with airborne in-situ measurements

    Science.gov (United States)

    Marinou, Eleni; Amiridis, Vassilis; Ansmann, Albert; Nenes, Athanasios; Balis, Dimitris; Schrod, Jann; Binietoglou, Ioannis; Solomos, Stavros; Mamali, Dimitra; Engelmann, Ronny; Baars, Holger; Kottas, Michael; Tsekeri, Alexandra; Proestakis, Emmanouil; Kokkalis, Panagiotis; Goloub, Philippe; Cvetkovic, Bojan; Nichovic, Slobodan; Mamouri, Rodanthi; Pikridas, Michael; Stavroulas, Iasonas; Keleshis, Christos; Sciare, Jean

    2018-04-01

    By means of available ice nucleating particle (INP) parameterization schemes we compute profiles of dust INP number concentration utilizing Polly-XT and CALIPSO lidar observations during the INUIT-BACCHUS-ACTRIS 2016 campaign. The polarization-lidar photometer networking (POLIPHON) method is used to separate dust and non-dust aerosol backscatter, extinction, mass concentration, particle number concentration (for particles with radius > 250 nm) and surface area concentration. The INP final products are compared with aerosol samples collected from unmanned aircraft systems (UAS) and analyzed using the ice nucleus counter FRIDGE.

  9. Prediction of topographic and bathymetric measurement performance of airborne low-SNR lidar systems

    Science.gov (United States)

    Cossio, Tristan

    Low signal-to-noise ratio (LSNR) lidar (light detection and ranging) is an alternative paradigm to traditional lidar based on the detection of return signals at the single photoelectron level. The objective of this work was to predict low altitude (600 m) LSNR lidar system performance with regards to elevation measurement and target detection capability in topographic (dry land) and bathymetric (shallow water) scenarios. A modular numerical sensor model has been developed to provide data for further analysis due to the dearth of operational low altitude LSNR lidar systems. This simulator tool is described in detail, with consideration given to atmospheric effects, surface conditions, and the effects of laser phenomenology. Measurement performance analysis of the simulated topographic data showed results comparable to commercially available lidar systems, with a standard deviation of less than 12 cm for calculated elevation values. Bathymetric results, although dependent largely on water turbidity, were indicative of meter-scale horizontal data spacing for sea depths less than 5 m. The high prevalence of noise in LSNR lidar data introduces significant difficulties in data analysis. Novel algorithms to reduce noise are described, with particular focus on their integration into an end-to-end target detection classifier for both dry and submerged targets (cube blocks, 0.5 m to 1.0 m on a side). The key characteristic exploited to discriminate signal and noise is the temporal coherence of signal events versus the random distribution of noise events. Target detection performance over dry earth was observed to be robust, reliably detecting over 90% of targets with a minimal false alarm rate. Comparable results were observed in waters of high clarity, where the investigated system was generally able to detect more than 70% of targets to a depth of 5 m. The results of the study show that CATS, the University of Florida's LSNR lidar prototype, is capable of high fidelity

  10. High Density Airborne LIDAR Estimation of Disrupted Trees Induced by landslides

    NARCIS (Netherlands)

    Razak, K.A.; Bucksch, A.; Straatsma, M.W.; Abu Bakar, R.; Jong, S.M. de; Westen, C.J. van

    2013-01-01

    Airborne laser scanning (ALS) data has revolutionized the landslide assessment in a rugged vegetated terrain. It enables the parameterization of morphology and vegetation of the instability slopes. Vegetation characteristics are by far less investigated because of the currently available accuracy

  11. 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.

  12. Discrete Anisotropic Radiative Transfer (DART 5 for Modeling Airborne and Satellite Spectroradiometer and LIDAR Acquisitions of Natural and Urban Landscapes

    Directory of Open Access Journals (Sweden)

    Jean-Philippe Gastellu-Etchegorry

    2015-02-01

    Full Text Available Satellite and airborne optical sensors are increasingly used by scientists, and policy makers, and managers for studying and managing forests, agriculture crops, and urban areas. Their data acquired with given instrumental specifications (spectral resolution, viewing direction, sensor field-of-view, etc. and for a specific experimental configuration (surface and atmosphere conditions, sun direction, etc. are commonly translated into qualitative and quantitative Earth surface parameters. However, atmosphere properties and Earth surface 3D architecture often confound their interpretation. Radiative transfer models capable of simulating the Earth and atmosphere complexity are, therefore, ideal tools for linking remotely sensed data to the surface parameters. Still, many existing models are oversimplifying the Earth-atmosphere system interactions and their parameterization of sensor specifications is often neglected or poorly considered. The Discrete Anisotropic Radiative Transfer (DART model is one of the most comprehensive physically based 3D models simulating the Earth-atmosphere radiation interaction from visible to thermal infrared wavelengths. It has been developed since 1992. It models optical signals at the entrance of imaging radiometers and laser scanners on board of satellites and airplanes, as well as the 3D radiative budget, of urban and natural landscapes for any experimental configuration and instrumental specification. It is freely distributed for research and teaching activities. This paper presents DART physical bases and its latest functionality for simulating imaging spectroscopy of natural and urban landscapes with atmosphere, including the perspective projection of airborne acquisitions and LIght Detection And Ranging (LIDAR waveform and photon counting signals.

  13. Automated Reconstruction of Building LoDs from Airborne LiDAR Point Clouds Using an Improved Morphological Scale Space

    Directory of Open Access Journals (Sweden)

    Bisheng Yang

    2016-12-01

    Full Text Available Reconstructing building models at different levels of detail (LoDs from airborne laser scanning point clouds is urgently needed for wide application as this method can balance between the user’s requirements and economic costs. The previous methods reconstruct building LoDs from the finest 3D building models rather than from point clouds, resulting in heavy costs and inflexible adaptivity. The scale space is a sound theory for multi-scale representation of an object from a coarser level to a finer level. Therefore, this paper proposes a novel method to reconstruct buildings at different LoDs from airborne Light Detection and Ranging (LiDAR point clouds based on an improved morphological scale space. The proposed method first extracts building candidate regions following the separation of ground and non-ground points. For each building candidate region, the proposed method generates a scale space by iteratively using the improved morphological reconstruction with the increase of scale, and constructs the corresponding topological relationship graphs (TRGs across scales. Secondly, the proposed method robustly extracts building points by using features based on the TRG. Finally, the proposed method reconstructs each building at different LoDs according to the TRG. The experiments demonstrate that the proposed method robustly extracts the buildings with details (e.g., door eaves and roof furniture and illustrate good performance in distinguishing buildings from vegetation or other objects, while automatically reconstructing building LoDs from the finest building points.

  14. MSFC Doppler Lidar Science experiments and operations plans for 1981 airborne test flight

    Science.gov (United States)

    Fichtl, G. H.; Bilbro, J. W.; Kaufman, J. W.

    1981-01-01

    The flight experiment and operations plans for the Doppler Lidar System (DLS) are provided. Application of DLS to the study of severe storms and local weather penomena is addressed. Test plans involve 66 hours of flight time. Plans also include ground based severe storm and local weather data acquisition.

  15. 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

  16. 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

  17. 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

  18. Pulsed Lidar Measurements of Atmospheric CO2 Column Absorption and Range During the ASCENDS 2009-2011 Airborne Campaigns

    Science.gov (United States)

    Abshire, J. B.; Weaver, C. J.; Riris, H.; Mao, J.; Sun, X.; Allan, G. R.; Hasselbrack, W. E.; Browell, E. V.

    2012-01-01

    We have developed a pulsed lidar technique for measuring the tropospheric CO2 concentrations as a candidate for NASA's ASCENDS mission and have demonstrated the CO2 and O2 measurements from aircraft. Our technique uses two pulsed lasers allowing simultaneous measurement of a single CO2 absorption line near 1572 nm, O2 extinction in the Oxygen A-band, surface height and backscatter profile. The lasers are stepped in wavelength across the CO2 line and an O2 line doublet during the measurement. The column densities for the CO2 and O2 are estimated from the differential optical depths (DOD) of the scanned absorption lines via the IPDA technique. For the 2009 ASCENDS campaign we flew the CO2 lidar only on a Lear-25 aircraft, and measured the absorption line shapes of the CO2 line using 20 wavelength samples per scan. Measurements were made at stepped altitudes from 3 to 12.6 km over the Lamont OK, central Illinois, North Carolina, and over the Virginia Eastern Shore. Although the received signal energies were weaker than expected for ASCENDS, clear C02 line shapes were observed at all altitudes. Most flights had 5-6 altitude steps with 200-300 seconds of recorded measurements per step. We averaged every 10 seconds of measurements and used a cross-correlation approach to estimate the range to the scattering surface and the echo pulse energy at each wavelength. We then solved for the best-fit CO2 absorption line shape, and calculated the DOD of the fitted CO2 line, and computed its statistics at the various altitude steps. We compared them to CO2 optical depths calculated from spectroscopy based on HITRAN 2008 and the column number densities calculated from the airborne in-situ readings. The 2009 measurements have been analyzed in detail and they were similar on all flights. The results show clear CO2 line shape and absorption signals, which follow the expected changes with aircraft altitude from 3 to 13 km. They showed the expected nearly the linear dependence of DOD vs

  19. Ecosystem services - from assessements of estimations to quantitative, validated, high-resolution, continental-scale mapping via airborne LIDAR

    Science.gov (United States)

    Zlinszky, András; Pfeifer, Norbert

    2016-04-01

    "Ecosystem services" defined vaguely as "nature's benefits to people" are a trending concept in ecology and conservation. Quantifying and mapping these services is a longtime demand of both ecosystems science and environmental policy. The current state of the art is to use existing maps of land cover, and assign certain average ecosystem service values to their unit areas. This approach has some major weaknesses: the concept of "ecosystem services", the input land cover maps and the value indicators. Such assessments often aim at valueing services in terms of human currency as a basis for decision-making, although this approach remains contested. Land cover maps used for ecosystem service assessments (typically the CORINE land cover product) are generated from continental-scale satellite imagery, with resolution in the range of hundreds of meters. In some rare cases, airborne sensors are used, with higher resolution but less covered area. Typically, general land cover classes are used instead of categories defined specifically for the purpose of ecosystem service assessment. The value indicators are developed for and tested on small study sites, but widely applied and adapted to other sites far away (a process called benefit transfer) where local information may not be available. Upscaling is always problematic since such measurements investigate areas much smaller than the output map unit. Nevertheless, remote sensing is still expected to play a major role in conceptualization and assessment of ecosystem services. We propose that an improvement of several orders of magnitude in resolution and accuracy is possible through the application of airborne LIDAR, a measurement technique now routinely used for collection of countrywide three-dimensional datasets with typically sub-meter resolution. However, this requires a clear definition of the concept of ecosystem services and the variables in focus: remote sensing can measure variables closely related to "ecosystem

  20. 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.

  1. Quantitative study of tectonic geomorphology along Haiyuan fault based on airborne LiDAR

    Science.gov (United States)

    Chen, Tao; Zhang, Pei Zhen; Liu, Jing; Li, Chuan You; Ren, Zhi Kun; Hudnut, Kenneth W.

    2014-01-01

    High-precision and high-resolution topography are the fundamental data for active fault research. Light detection and ranging (LiDAR) presents a new approach to build detailed digital elevation models effectively. We take the Haiyuan fault in Gansu Province as an example of how LiDAR data may be used to improve the study of active faults and the risk assessment of related hazards. In the eastern segment of the Haiyuan fault, the Shaomayin site has been comprehensively investigated in previous research because of its exemplary tectonic topographic features. Based on unprecedented LiDAR data, the horizontal and vertical coseismic offsets at the Shaomayin site are described. The measured horizontal value is about 8.6 m, and the vertical value is about 0.8 m. Using prior dating ages sampled from the same location, we estimate the horizontal slip rate as 4.0 ± 1.0 mm/a with high confidence and define that the lower bound of the vertical slip rate is 0.4 ± 0.1 mm/a since the Holocene. LiDAR data can repeat the measurements of field work on quantifying offsets of tectonic landform features quite well. The offset landforms are visualized on an office computer workstation easily, and specialized software may be used to obtain displacement quantitatively. By combining precious chronological results, the fundamental link between fault activity and large earthquakes is better recognized, as well as the potential risk for future earthquake hazards.

  2. Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Almasi S. Maguya

    2014-07-01

    Full Text Available Extracting digital elevationmodels (DTMs from LiDAR data under forest canopy is a challenging task. This is because the forest canopy tends to block a portion of the LiDAR pulses from reaching the ground, hence introducing gaps in the data. This paper presents an algorithm for DTM extraction from LiDAR data under forest canopy. The algorithm copes with the challenge of low data density by generating a series of coarse DTMs by using the few ground points available and using trend surfaces to interpolate missing elevation values in the vicinity of the available points. This process generates a cloud of ground points from which the final DTM is generated. The algorithm has been compared to two other algorithms proposed in the literature in three different test sites with varying degrees of difficulty. Results show that the algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms. The results further show that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5m to over 10m.

  3. A GLOBAL SOLUTION TO TOPOLOGICAL RECONSTRUCTION OF BUILDING ROOF MODELS FROM AIRBORNE LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    J. Yan

    2016-06-01

    Full Text Available This paper presents a global solution to building roof topological reconstruction from LiDAR point clouds. Starting with segmented roof planes from building LiDAR points, a BSP (binary space partitioning algorithm is used to partition the bounding box of the building into volumetric cells, whose geometric features and their topology are simultaneously determined. To resolve the inside/outside labelling problem of cells, a global energy function considering surface visibility and spatial regularization between adjacent cells is constructed and minimized via graph cuts. As a result, the cells are labelled as either inside or outside, where the planar surfaces between the inside and outside form the reconstructed building model. Two LiDAR data sets of Yangjiang (China and Wuhan University (China are used in the study. Experimental results show that the completeness of reconstructed roof planes is 87.5%. Comparing with existing data-driven approaches, the proposed approach is global. Roof faces and edges as well as their topology can be determined at one time via minimization of an energy function. Besides, this approach is robust to partial absence of roof planes and tends to reconstruct roof models with visibility-consistent surfaces.

  4. 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.

  5. 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

    Scientists at NASA's Goddard Space Flight Center have developed an ultra-portable, low-cost, multi-sensor remote sensing system for studying the form and function of terrestrial ecosystems. G-LiHT integrates two LIDARs, a 905 nanometer single beam profiler and 1550 nm scanner, with a narrowband (1.5 nanometers) VNIR imaging spectrometer and a broadband (8-14 micrometers) thermal imager. The small footprint (approximately 12 centimeters) LIDAR data and approximately 1 meter ground resolution imagery are advantageous for high resolution applications such as the delineation of canopy crowns, characterization of canopy gaps, and the identification of sparse, low-stature vegetation, which is difficult to detect from space-based instruments and large-footprint LiDAR. The hyperspectral and thermal imagery can be used to characterize species composition, variations in biophysical variables (e.g., photosynthetic pigments), surface temperature, and responses to environmental stressors (e.g., heat, moisture loss). Additionally, the combination of LIDAR optical, and thermal data from G-LiHT is being used to assess forest health by sensing differences in foliage density, photosynthetic pigments, and transpiration. Low operating costs (approximately $1 ha) have allowed us to evaluate seasonal differences in LiDAR, passive optical and thermal data, which provides insight into year-round observations from space. Canopy characteristics and tree allometry (e.g., crown height:width, canopy:ground reflectance) derived from G-LiHT data are being used to generate realistic scenes for radiative transfer models, which in turn are being used to improve instrument design and ensure continuity between LiDAR instruments. G-LiHT has been installed and tested in aircraft with fuselage viewports and in a custom wing-mounted pod that allows G-LiHT to be flown on any Cessna 206, a common aircraft in use throughout the world. G-LiHT is currently being used for forest biomass and growth estimation

  6. A Model-Driven Approach for 3D Modeling of Pylon from Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Qingquan Li

    2015-09-01

    Full Text Available Reconstructing three-dimensional model of the pylon from LiDAR (Light Detection And Ranging point clouds automatically is one of the key techniques for facilities management GIS system of high-voltage nationwide transmission smart grid. This paper presents a model-driven three-dimensional pylon modeling (MD3DM method using airborne LiDAR data. We start with constructing a parametric model of pylon, based on its actual structure and the characteristics of point clouds data. In this model, a pylon is divided into three parts: pylon legs, pylon body and pylon head. The modeling approach mainly consists of four steps. Firstly, point clouds of individual pylon are detected and segmented from massive high-voltage transmission corridor point clouds automatically. Secondly, an individual pylon is divided into three relatively simple parts in order to reconstruct different parts with different strategies. Its position and direction are extracted by contour analysis of the pylon body in this stage. Thirdly, the geometric features of the pylon head are extracted, from which the head type is derived with a SVM (Support Vector Machine classifier. After that, the head is constructed by seeking corresponding model from pre-build model library. Finally, the body is modeled by fitting the point cloud to planes. Experiment results on several point clouds data sets from China Southern high-voltage nationwide transmission grid from Yunnan Province to Guangdong Province show that the proposed approach can achieve the goal of automatic three-dimensional modeling of the pylon effectively.

  7. Assessment of changes in formations of non-forest woody vegetation in southern Denmark based on airborne LiDAR.

    Science.gov (United States)

    Angelidis, Ioannis; Levin, Gregor; Díaz-Varela, Ramón Alberto; Malinowski, Radek

    2017-09-01

    LiDAR (Light Detection and Ranging) is a remote sensing technology that uses light in the form of pulses to measure the range between a sensor and the Earth's surface. Recent increase in availability of airborne LiDAR scanning (ALS) data providing national coverage with high point densities has opened a wide range of possibilities for monitoring landscape elements and their changes at broad geographical extent. We assessed the dynamics of the spatial extent of non-forest woody vegetation (NFW) in a study area of approx. 2500 km 2 in southern Jutland, Denmark, based on two acquisitions of ALS data for 2006 and 2014 in combination with other spatial data. Our results show a net-increase (4.8%) in the total area of NFW. Furthermore, this net change comprises of both areas with a decrease and areas with an increase of NFW. An accuracy assessment based on visual interpretation of aerial photos indicates high accuracy (>95%) in the delineation of NFW without changes during the study period. For NFW that changed between 2006 and 2014, accuracies were lower (90 and 82% in removed and new features, respectively), which is probably due to lower point densities of the 2006 ALS data (0.5 pts./m 2 ) compared to the 2014 data (4-5 pts./m 2 ). We conclude that ALS data, if combined with other spatial data, in principle are highly suitable for detailed assessment of changes in landscape features, such as formations of NFW at broad geographical extent. However, in change assessment based on multi-temporal ALS data with different point densities errors occur, particularly when examining small or narrow NFW objects.

  8. Three-Dimensional Wind Profiling of Offshore Wind Energy Areas With Airborne Doppler Lidar

    Science.gov (United States)

    Koch, Grady J.; Beyon, Jeffrey Y.; Cowen, Larry J.; Kavaya, Michael J.; Grant, Michael S.

    2014-01-01

    A technique has been developed for imaging the wind field over offshore areas being considered for wind farming. This is accomplished with an eye-safe 2-micrometer wavelength coherent Doppler lidar installed in an aircraft. By raster scanning the aircraft over the wind energy area (WEA), a three-dimensional map of the wind vector can be made. This technique was evaluated in 11 flights over the Virginia and Maryland offshore WEAs. Heights above the ocean surface planned for wind turbines are shown to be within the marine boundary layer, and the wind vector is seen to show variation across the geographical area of interest at turbine heights.

  9. Quantifying wind blown landscapes using time-series airborne LiDAR at White Sands Dune Field, New Mexico

    Science.gov (United States)

    Ewing, R. C.

    2011-12-01

    Wind blown landscapes are a default geomorphic and sedimentary environment in our solar system. Wind sand dunes are ubiquitous features on the surfaces of Earth, Mars and Titan and prevalent within the aeolian rock records of Earth and Mars. Dunes are sensitive to environmental and climatic changes and a complete understanding of this system promises a unique, robust and quantitative record of paleoclimate extending to the early histories of these worlds. However, our understanding of how aeolian dune landscapes evolve and how the details of the wind are recorded in cross-strata is limited by our lack of understanding of three-dimensional dune morphodynamics related to changing boundary conditions such as wind direction and magnitude and sediment source area. We use airborne LiDAR datasets over 40 km2 of White Sands Dune Field collected from June 2007, June 2008, January 2009, September 2009 and June 2010 to quantify 1) three-dimensional dune geometries, 2) annual and seasonal patterns of erosion and deposition across dune topography, 3) spatial changes in sediment flux related to position within the field, 4) spatial changes in sediment flux across sinuous crestlines and 5) morphologic changes through dune-dune interactions. In addition to measurements, we use the LiDAR data along with wind data from two near-by weather stations to develop a simple model that predicts depositional and stratigraphic patterns on dune lee slopes. Several challenges emerged using time series LiDAR data sets at White Sands Dune Field. The topography upon which the dunes sit is variable and rises by 16 meters over the length of the dune field. In order to compare individual dune geometries across the field and between data sets a base surface was interpolated from local minima and subtracted from the dune topography. Co-registration and error calculation between datasets was done manually using permanent vegetated features within the active dune field and structures built by the

  10. 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

  11. 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.

  12. Combined Atmospheric and Ocean Profiling from an Airborne High Spectral Resolution Lidar

    Directory of Open Access Journals (Sweden)

    Hair Johnathan

    2016-01-01

    Full Text Available First of its kind combined atmospheric and ocean profile data were collected by the recently upgraded NASA Langley Research Center’s (LaRC High Spectral Resolution Lidar (HSRL-1 during the 17 July – 7 August 2014 Ship-Aircraft Bio-Optical Research Experiment (SABOR. This mission sampled over a region that covered the Gulf of Maine, open-ocean near Bermuda, and coastal waters from Virginia to Rhode Island. The HSRL-1 and the Research Scanning Polarimeter from NASA Goddard Institute for Space Studies collected data onboard the NASA LaRC King Air aircraft and flight operations were closely coordinated with the Research Vessel Endeavor that made in situ ocean optical measurements. The lidar measurements provided profiles of atmospheric backscatter and particulate depolarization at 532nm, 1064nm, and extinction (532nm from approximately 9km altitude. In addition, for the first time HSRL seawater backscatter, depolarization, and diffuse attenuation data at 532nm were collected and compared to both the ship measurements and the Moderate Resolution Imaging Spectrometer (NASA MODIS-Aqua satellite ocean retrievals.

  13. 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.

  14. 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

  15. Semi-Global Filtering of Airborne LiDAR Data for Fast Extraction of Digital Terrain Models

    Directory of Open Access Journals (Sweden)

    Xiangyun Hu

    2015-08-01

    Full Text Available Automatic extraction of ground points, called filtering, is an essential step in producing Digital Terrain Models from airborne LiDAR data. Scene complexity and computational performance are two major problems that should be addressed in filtering, especially when processing large point cloud data with diverse scenes. This paper proposes a fast and intelligent algorithm called Semi-Global Filtering (SGF. The SGF models the filtering as a labeling problem in which the labels correspond to possible height levels. A novel energy function balanced by adaptive ground saliency is employed to adapt to steep slopes, discontinuous terrains, and complex objects. Semi-global optimization is used to determine labels that minimize the energy. These labels form an optimal classification surface based on which the points are classified as either ground or non-ground. The experimental results show that the SGF algorithm is very efficient and able to produce high classification accuracy. Given that the major procedure of semi-global optimization using dynamic programming is conducted independently along eight directions, SGF can also be paralleled and sped up via Graphic Processing Unit computing, which runs at a speed of approximately 3 million points per second.

  16. 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.

  17. Spatio-temporal monitoring of cotton cultivation using ground-based and airborne multispectral sensors in GIS environment.

    Science.gov (United States)

    Papadopoulos, Antonis; Kalivas, Dionissios; Theocharopoulos, Sid

    2017-07-01

    Multispectral sensor capability of capturing reflectance data at several spectral channels, together with the inherent reflectance responses of various soils and especially plant surfaces, has gained major interest in crop production. In present study, two multispectral sensing systems, a ground-based and an aerial-based, were applied for the multispatial and temporal monitoring of two cotton fields in central Greece. The ground-based system was Crop Circle ACS-430, while the aerial consisted of a consumer-level quadcopter (Phantom 2) and a modified Hero3+ Black digital camera. The purpose of the research was to monitor crop growth with the two systems and investigate possible interrelations between the derived well-known normalized difference vegetation index (NDVI). Five data collection campaigns were conducted during the cultivation period and concerned scanning soil and plants with the ground-based sensor and taking aerial photographs of the fields with the unmanned aerial system. According to the results, both systems successfully monitored cotton growth stages in terms of space and time. The mean values of NDVI changes through time as retrieved by the ground-based system were satisfactorily modelled by a second-order polynomial equation (R 2 0.96 in Field 1 and 0.99 in Field 2). Further, they were highly correlated (r 0.90 in Field 1 and 0.74 in Field 2) with the according values calculated via the aerial-based system. The unmanned aerial system (UAS) can potentially substitute crop scouting as it concerns a time-effective, non-destructive and reliable way of soil and plant monitoring.

  18. Wall-to-wall tree type classification using airborne lidar data and CIR images

    DEFF Research Database (Denmark)

    Schumacher, Johannes; Nord-Larsen, Thomas

    2014-01-01

    analysed at the individual tree level (object-based). However, due to computational challenges, most object-based studies cover only smaller areas and experience of larger areas is lacking. We present an approach for an object-based, unsupervised classification of trees into broadleaf or conifer using......-based classification of the TST plots showed an overall accuracy of 84% and a kappa coefficient () of 0.61 when using all plots, and 92% and 0.79, respectively, when leaving out plots with larch. NFI plots were assigned to conifer- or broadleaf-dominated or mixed depending on the area covered by the segments...... of the two tree types. In areas where lidar data were collected specifically during leaf-off conditions, 71% of the NFI plots were assigned correctly into the three categories with = 0.53. Using only NFI plots dominated by one type (broadleaf or conifer), 78% were categorized correctly with = 0...

  19. A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data

    Science.gov (United States)

    Chen, Chuanfa; Li, Yanyan; Li, Wei; Dai, Honglei

    2013-08-01

    We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were used to compare the performance of MHC with those of the 17 other publicized filtering methods. Results indicated that MHC with the average total error and average Cohen’s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods.

  20. 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.

  1. 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

  2. Virtual Surveyor based Object Extraction from Airborne LiDAR data

    Science.gov (United States)

    Habib, Md. Ahsan

    Topographic feature detection of land cover from LiDAR data is important in various fields - city planning, disaster response and prevention, soil conservation, infrastructure or forestry. In recent years, feature classification, compliant with Object-Based Image Analysis (OBIA) methodology has been gaining traction in remote sensing and geographic information science (GIS). In OBIA, the LiDAR image is first divided into meaningful segments called object candidates. This results, in addition to spectral values, in a plethora of new information such as aggregated spectral pixel values, morphology, texture, context as well as topology. Traditional nonparametric segmentation methods rely on segmentations at different scales to produce a hierarchy of semantically significant objects. Properly tuned scale parameters are, therefore, imperative in these methods for successful subsequent classification. Recently, some progress has been made in the development of methods for tuning the parameters for automatic segmentation. However, researchers found that it is very difficult to automatically refine the tuning with respect to each object class present in the scene. Moreover, due to the relative complexity of real-world objects, the intra-class heterogeneity is very high, which leads to over-segmentation. Therefore, the method fails to deliver correctly many of the new segment features. In this dissertation, a new hierarchical 3D object segmentation algorithm called Automatic Virtual Surveyor based Object Extracted (AVSOE) is presented. AVSOE segments objects based on their distinct geometric concavity/convexity. This is achieved by strategically mapping the sloping surface, which connects the object to its background. Further analysis produces hierarchical decomposition of objects to its sub-objects at a single scale level. Extensive qualitative and qualitative results are presented to demonstrate the efficacy of this hierarchical segmentation approach.

  3. Airborne laser scanner (LiDAR) proxies for understory light conditions

    DEFF Research Database (Denmark)

    Alexander, Cici; Moeslund, Jesper Erenskjold; Bøcher, Peder Klith

    2013-01-01

    to community structure. Angular canopy closure is more closely related to the direct and indirect light experienced by a plant or an animal than vertical canopy cover, but more challenging to estimate. We used airborne laser scanner (ALS) data to estimate canopy cover for 210 5-m radius vegetation plots......Canopy cover and canopy closure are two closely related measures of vegetation structure. They are used for estimating understory light conditions and their influence on a broad range of biological components in forest ecosystems, from the demography and population dynamics of individual species...... of azimuth and zenith angle intervals which contained points. We compared these estimates with field-based estimates using densiometer for 60 vegetation plots in forest. Finally, we compared ALS-based estimates of canopy cover and canopy closure to field-based estimates of understory light, based...

  4. Airborne lidar measurements to investigate the impact of long-range transported dust on shallow marine trade wind convection

    Science.gov (United States)

    Gross, S.; Gutleben, M.; Wirth, M.; Ewald, F.

    2017-12-01

    Aerosols and clouds are still main contributors to uncertainties in estimates and interpretation of the Earth's changing energy budget. Their interaction with the Earth's radiation budged has a direct component by scattering and absorbing solar and terrestrial radiation, and an indirect component, e.g. as aerosols modify the properties and thus the life-time of clouds or by changing the atmosphere's stability. Up to know now sufficient understanding in aerosol-cloud interaction and climate feedback is achieved. Thus studies with respect to clouds, aerosols, their interaction and influence on the radiation budged are highly demanded. In August 2016 the NARVAL-II (Next-generation airborne remote sensing for validation studies) mission took place. Measurements with a combined active (high spectral resolution and water vapor differential absorption lidar and cloud radar) and passive remote sensing (microwave radiometer, hyper spectral imager, radiation measurements) payload were performed with the German high altitude and long-range research aircraft HALO over the subtropical North-Atlantic Ocean to study shallow marine convection during the wet and dusty season. With this, NARVAL-II is follow-up of the NARVAL-I mission which took place during the dry and dust free season in December 2013. During NARVAL-II the measurement flights were designed the way to sample dust influenced areas as well as dust free areas in the trades. One main objective was to investigate the optical and macro physical properties of the dust layer, differences in cloud occurrence in dusty and non-dusty areas, and to study the influence of aerosols on the cloud properties and formation. This allows comparisons of cloud and aerosol distribution as well as their environment between the dry and the wet season, and of cloud properties and distribution with and without the influence of long-range transported dust across the Atlantic Ocean. In our presentation we will give an overview of the NARVAL

  5. 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.

  6. A comparison of mixing depths observed by ground-based wind profilers and an airborne lidar

    Energy Technology Data Exchange (ETDEWEB)

    White, A.B.; Senff, C. [Univ. of Colorado/NOAA Environmental Technology Lab., Cooperative Inst. for Research in Environmental Sciences, Boulder, CO (United States); Banta, R.M. [NOAA Environmental Technology Lab., Boulder, CO (United States)

    1997-10-01

    The mixing depth is one of the most important parameters in air pollution studies because it determines the vertical extent of the `box` in which pollutants are mixed and dispersed. During the 1995 Southern Oxidants Study (SOS95), scientists from the National Oceanic and Atmospheric Administration Environmental Technology Laboratory (NOAA/ETL) deployed four 915-MHz boundary-layer radar/wind profilers (hereafter radars) in and around the Nashville, Tennessee metropolitan area. Scientists from NOAA/ETL also operated an ultraviolet differential absorption lidar (DIAL) onboard a CASA-212 aircraft. Profiles from radar and DIAL can be used to derive estimates of the mixing depth. The methods used for both instruments are similar in that they depend on information derived from the backscattered power. However, different scattering mechanisms for the radar and DIAL mean that different tracers of mixing depth are measured. In this paper we compare the mixing depth estimates obtained from the radar and DIAL and discuss the similarities and differences that occur. (au)

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

    Directory of Open Access Journals (Sweden)

    CARLOS ALBERTO SILVA

    Full Text Available ABSTRACT 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.

  8. 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.

  9. Using Airborne Lidar Data from IcePod to Measure Annual and Seasonal Ice Changes Over Greenland

    Science.gov (United States)

    Frearson, N.; Bertinato, C.; Das, I.

    2014-12-01

    The IcePod is a multi-sensor airborne science platform that supports a wide suite of instruments, including a Riegl VQ-580 infrared scanning laser, GPS-inertial positioning system, shallow and deep-ice radars, visible-wave and infrared cameras, and upward-looking pyrometer. These instruments allow us to image the ice from top to bottom, including the surface of melt-water plumes that originate at the ice-ocean boundary. In collaboration with the New York Air National Guard 109th Airlift Wing, the IcePod is flown on LC-130 aircraft, which presents the unique opportunity to routinely image the Greenland ice sheet several times within a season. This is particularly important for mass balance studies, as we can measure elevation changes during the melt season. During the 2014 summer, laser data was collected via IcePod over the Greenland ice sheet, including Russell Glacier, Jakobshavn Glacier, Eqip Glacier, and Summit Camp. The Icepod will also be routinely operated in Antarctica. We present the initial testing, calibration, and error estimates from the first set of laser data that were collected on IcePod. At a survey altitude of 1000 m, the laser swath covers ~ 1000 m. A Northrop-Grumman LN-200 tactical grade IMU is rigidly attached to the laser scanner to provide attitude data at a rate of 200 Hz. Several methods were used to determine the lever arm between the IMU center of navigation and GPS antenna phase center, terrestrial scanning laser, total station survey, and optimal estimation. Additionally, initial bore sight calibration flights yielded misalignment angles within an accuracy of ±4 cm. We also performed routine passes over the airport ramp in Kangerlussuaq, Greenland, comparing the airborne GPS and Lidar data to a reference GPS-based ground survey across the ramp, spot GPS points on the ramp and a nearby GPS base station. Positioning errors can severely impact the accuracy of a laser altimeter when flying over remote regions such as across the ice sheets

  10. Estimation of Evapotraspiration of Tamarisk using Energy Balance Models with High Resolution Airborne Imagery and LIDAR Data

    Science.gov (United States)

    Geli, H. M.; Taghvaeian, S.; Neale, C. M.; Pack, R.; Watts, D. R.; Osterberg, J.

    2010-12-01

    The wide uncontrolled spread of the invasive species of Tamarisk (Salt Cedar) in the riparian areas of the southwest of the United States has become a source of concern to the water resource management community. This tree which was imported for ornamental purposes and to control bank erosion during the 1800’s later became problematic and unwanted due to its biophysical properties: Its vigorous growth out-competes native species for moisture, lowering water tables, increasing the soil salinity and hence becomes the dominant riparian vegetation especially over arid to semi-arid floodplain environments. Most importantly they consume large amounts of water leading to reduction of river flows and lowering the groundwater table. We implemented this study in an effort to provide reliable estimates of the amount of water consumed or “lost” by such species through evapotranspiration (ET) as well as to a better understand of the related land surface and near atmosphere interactions. The recent advances in remote sensing techniques and the related data quality made it possible to provide spatio-temporal estimates of ET at a considerably higher resolution and reliable accuracy over a wide range of surface heterogeneity. We tested two different soil-vegetation atmosphere transfer models (SVAT) that are based on thermal remote sensing namely: the two source model (TSM) of Norman et al. (1995) with its recent modifications and the Surface Energy balance algorithm (SEBAL) of Bastiaanssen et al. (1998) to estimate the different surface energy balance components and the evapotranspiration (ET) spatially. We used high resolution (1.0 meter pixel size) shortwave reflectance and longwave thermal airborne imagery acquired by the research aircraft at the Remote Sensing Services Lab at Utah State University (USU) and land use map classified from these images as well as a detailed vegetation height image acquired by the LASSI Lidar also developed at USU. We also compared estimates

  11. 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..

  12. Spectral control of an alexandrite laser for an airborne water-vapor differential absorption lidar system

    Science.gov (United States)

    Ponsardin, Patrick; Grossmann, Benoist E.; Browell, Edward V.

    1994-01-01

    A narrow-linewidth pulsed alexandrite laser has been greatly modified for improved spectral stability in an aircraft environment, and its operation has been evaluated in the laboratory for making water-vapor differential absorption lidar measurements. An alignment technique is described to achieve the optimum free spectral range ratio for the two etalons inserted in the alexandrite laser cavity, and the sensitivity of this ratio is analyzed. This technique drastically decreases the occurrence of mode hopping, which is commonly observed in a tunable, two-intracavity-etalon laser system. High spectral purity (greater than 99.85%) at 730 nm is demonstrated by the use of a water-vapor absorption line as a notch filter. The effective cross sections of 760-nm oxygen and 730-nm water-vapor absorption lines are measured at different pressures by using this laser, which has a finite linewidth of 0.02 cm(exp -1) (FWHM). It is found that for water-vapor absorption linewidths greater than 0.04 cm(exp -1) (HWHM), or for altitudes below 10 km, the laser line can be considered monochromatic because the measured effective absorption cross section is within 1% of the calculated monochromatic cross section. An analysis of the environmental sensitivity of the two intracavity etalons is presented, and a closed-loop computer control for active stabilization of the two intracavity etalons in the alexandrite laser is described. Using a water-vapor absorption line as a wavelength reference, we measure a long-term frequency drift (approximately 1.5 h) of less than 0.7 pm in the laboratory.

  13. The carbon debt from Amazon forest degradation: integrating airborne lidar, field measurements, and an ecosystem demography model.

    Science.gov (United States)

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

    2016-12-01

    Amazon deforestation has declined over the last decade, yet forest degradation from logging, fire, and fragmentation continue to impact forest carbon stocks and fluxes. The magnitude of this impact remains uncertain, and observation-based studies are often limited by short time intervals or small study areas. To better understand the long-term impact of forest degradation and recovery, we have been developing a framework that integrates field plot measurements and airborne lidar surveys into an individual- and process-based model (Ecosystem Demography model, ED). We modeled forest dynamics for three forest landscapes in the Amazon with diverse degradation histories: conventional and reduced-impact logging, logging and burning, and multiple burns. Based on the initialization with contemporary forest structure and composition, model results suggest that degraded forests rapidly recover (30 years) water and energy fluxes compared with old-growth, even at sites that were affected by multiple fires. However, degraded forests maintained different carbon stocks and fluxes even after 100 years without further disturbances, because of persistent differences in forest structure and composition. Recurrent disturbances may hinder the recovery of degraded forests. Simulations using a simple fire model entirely dependent on environmental controls indicate that the most degraded forests would take much longer to reach biomass typical of old-growth forests, because drier conditions near the ground make subsequent fires more intense and more recurrent. Fires in tropical forests are also closely related to nearby human activities; while results suggest an important feedback between fires and the microenvironment, additional work is needed to improve how the model represents the human impact on current and future fire regimes. Our study highlights that recovery of degraded forests may act as an important carbon sink, but efficient recovery depends on controlling future disturbances.

  14. Taking Stock of Circumboreal Forest Carbon With Ground Measurements, Airborne and Spaceborne LiDAR

    Science.gov (United States)

    Neigh, Christopher S. R.; Nelson, Ross F.; Ranson, K. Jon; Margolis, Hank A.; Montesano, Paul M.; Sun, Guoqing; Kharuk, Viacheslav; Naesset, Erik; Wulder, Michael A.; Andersen, Hans-Erik

    2013-01-01

    The boreal forest accounts for one-third of global forests, but remains largely inaccessible to ground-based measurements and monitoring. It contains large quantities of carbon in its vegetation and soils, and research suggests that it will be subject to increasingly severe climate-driven disturbance. We employ a suite of ground-, airborne- and space-based measurement techniques to derive the first satellite LiDAR-based estimates of aboveground carbon for the entire circumboreal forest biome. Incorporating these inventory techniques with uncertainty analysis, we estimate total aboveground carbon of 38 +/- 3.1 Pg. This boreal forest carbon is mostly concentrated from 50 to 55degN in eastern Canada and from 55 to 60degN in eastern Eurasia. Both of these regions are expected to warm >3 C by 2100, and monitoring the effects of warming on these stocks is important to understanding its future carbon balance. Our maps establish a baseline for future quantification of circumboreal carbon and the described technique should provide a robust method for future monitoring of the spatial and temporal changes of the aboveground carbon content.

  15. 2010-2011 US Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) Topobathy Lidar: Oregon and Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These files contain topographic and bathymetric lidar data collected with the Leica ALS60 (topo) and SHOALS-1000T (bathy) systems along the coasts of Oregon and...

  16. CoMet: an airborne mission to simultaneously measure CO2 and CH4 using lidar, passive remote sensing, and in-situ techniques

    Science.gov (United States)

    Fix, Andreas; Amediek, Axel; Bovensmann, Heinrich; Ehret, Gerhard; Gerbig, Christoph; Gerilowski, Konstantin; Pfeilsticker, Klaus; Roiger, Anke; Zöger, Martin

    2018-04-01

    TIn order to improve our current knowledge on the budgets of the two most important anthropogenic greenhouse gases, CO2 and CH4, an airborne mission on board the German research aircraft HALO in coordination with two smaller Cessna aircraft is going to be conducted in April/May 2017. The goal of CoMet is to combine a suite of the best currently available active (lidar) and passive remote sensors as well as in-situ instruments to provide regional-scale data of greenhouse gases which are urgently required.

  17. Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Jaewook Jung

    2017-03-01

    Full Text Available With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL combined with Hypothesize and Test (HAT. The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International

  18. Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data.

    Science.gov (United States)

    Jung, Jaewook; Jwa, Yoonseok; Sohn, Gunho

    2017-03-19

    With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS) data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP) technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL) combined with Hypothesize and Test (HAT). The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International Society for

  19. Mapping Canopy Height and Growing Stock Volume Using Airborne Lidar, ALOS PALSAR and Landsat ETM+

    Directory of Open Access Journals (Sweden)

    Wayne Walker

    2012-10-01

    Full Text Available We have investigated for forest plantations in Chile the stand-level retrieval of canopy height (CH and growing stock volume (GSV using Airborne Laser Scanner (ALS, ALOS PALSAR and Landsat. In a two-stage up-scaling approach, ensemble regression tree models (randomForest were used to relate a suite of ALS canopy structure indices to stand-level in situ measurements of CH and GSV for 319 stands. The retrieval of CH and GSV with ALS yielded high accuracies with R2s of 0.93 and 0.81, respectively. A second set of randomForest models was developed using multi-temporal ALOS PALSAR intensities and repeat-pass coherences in two polarizations as well as Landsat data as predictor and stand-level ALS based estimates of CH and GSV as response variables. At three test sites, the retrieval of CH and GSV with PALSAR/Landsat reached promising accuracies with R2s in the range of 0.7 to 0.85. We show that the combined use of multi-temporal PALSAR intensity, coherence and Landsat yields higher retrieval accuracies than the retrieval with any of the datasets alone. Potential limitations for the large-area application of the fusion approach included (1 the low sensitivity of ALS first/last return data to forest horizontal structure, affecting the retrieval of GSV in less managed types of forest, and (2 the dense ALS sampling required to achieve high retrieval accuracies at larger scale.

  20. 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.

  1. Retrieval of Cloud Properties from the Multi-spectral, Multi-viewing and Polarized Measurements of the Airborne Polarimeter OSIRIS

    Science.gov (United States)

    Matar, C.; Cornet, C.; Parol, F.; C-Labonnote, L.; Auriol, F.; Nicolas, J. M.

    2017-12-01

    Clouds are recognized as a major source of uncertainty in forecasting the evolution of climate change. One way to improve our knowledge is to obtain accurate cloud properties and variabilities at high spatial resolution. Airborne remote sensing measurements are very suitable to achieve these targets with a tens of meters resolution. In this context, we exploit multi-viewing measurements of the new airborne radiometer OSIRIS (Observing System Including Polarization in the Solar Infrared Spectrum), developed in the Laboratoire d'Optique Atmosphérique (LOA). It is based on POLDER concept as a prototype of the future spacecraft 3MI (Multi-Viewing Multi-Channel Multi-Polarisation Imaging Mission) that will be part of the EPS-SG Eumetsat-ESA mission. Currently, most operational remote sensing algorithms used to retrieve cloud properties from passive measurements, are based on the construction of pre-calculated Look-Up Tables (LUT) under the hypothesis of a single plane-parallel cloud layer. This assumption leads to certain limitations and possible large errors.We developed an optimal estimation method to retrieve cloud optical thickness and effective radius of cloud droplets. This inversion method is more flexible than the LUT method and allows to take into account uncertainties on both observations and the physical model leading to a direct estimation of the retrievals uncertainties in a well-established formalism. For example, we include uncertainties on retrieved cloud parameters due to an incorrect estimation of the ocean surface winds speed, the cloud vertical profiles and the 3D radiative transfer effects.OSIRIS has two separate optical sensors, one for the visible and near infrared range and the other one for the shortwave infrared (SWIR). Consequently, the developed algorithms are based on two different types of information: (1) the total and polarized multi-viewing reflectances from the visible range and (2) the multi-viewing total reflectances from two SWIR

  2. Comparison of Stem Map Developed from Crown Geometry Allometry Linked Census Data to Airborne and Terrestrial Lidar at Harvard Forest, MA

    Science.gov (United States)

    Sullivan, F.; Palace, M. W.; Ducey, M. J.; David, O.; Cook, B. D.; Lepine, L. C.

    2014-12-01

    Harvard Forest in Petersham, MA, USA is the location of one of the temperate forest plots established by the Center for Tropical Forest Science (CTFS) as a joint effort with Harvard Forest and the Smithsonian Institute's Forest Global Earth Observatory (ForestGEO) to characterize ecosystem processes and forest dynamics. Census of a 35 ha plot on Prospect Hill was completed during the winter of 2014 by researchers at Harvard Forest. Census data were collected according to CTFS protocol; measured variables included species, stem diameter, and relative X-Y locations. Airborne lidar data were collected over the censused plot using the high spatial resolution Goddard LiDAR, Hyperspectral, and Thermal sensor package (G-LiHT) during June 2012. As part of a separate study, 39 variable radius plots (VRPs) were randomly located and sampled within and throughout the Prospect Hill CTFS/ForestGEO plot during September and October 2013. On VRPs, biometric properties of trees were sampled, including species, stem diameter, total height, crown base height, crown radii, and relative location to plot centers using a 20 Basal Area Factor prism. In addition, a terrestrial-based lidar scanner was used to collect one lidar scan at plot center for 38 of the 39 VRPs. Leveraging allometric equations of crown geometry and tree height developed from 374 trees and 16 different species sampled on 39 VRPs, a 3-dimensional stem map will be created using the Harvard Forest ForestGEO Prospect Hill census. Vertical and horizontal structure of 3d field-based stem maps will be compared to terrestrial and airborne lidar scan data. Furthermore, to assess the quality of allometric equations, a 2d canopy height raster of the field-based stem map will be compared to a G-LiHT derived canopy height model for the 35 ha census plot. Our automated crown delineation methods will be applied to the 2d representation of the census stem map and the G-LiHT canopy height model. For future work related to this study

  3. New Generation Lidar Technology and Applications

    Science.gov (United States)

    Spinhirne, James D.

    1999-01-01

    Lidar has been a tool for atmospheric research for several decades. Until recently routine operational use of lidar was not known. Problems have involved a lack of appropriate technology rather than a lack of applications. Within the last few years, lidar based on a new generation of solid state lasers and detectors have changed the situation. Operational applications for cloud and aerosol research applications are now well established. In these research applications, the direct height profiling capability of lidar is typically an adjunct to other types of sensing, both passive and active. Compact eye safe lidar with the sensitivity for ground based monitoring of all significant cloud and aerosol structure and the reliability to operate full time for several years is now in routine use. The approach is known as micro pulse lidar (MPL). For MPL the laser pulse repetition rate is in the kilohertz range and the pulse energies are in the micro-Joule range. The low pulse energy permits the systems to be eye safe and reliable with solid state lasers. A number of MPL systems have been deployed since 1992 at atmospheric research sites at a variety of global locations. Accurate monitoring of cloud and aerosol vertical distribution is a critical measurement for atmospheric radiation. An airborne application of lidar cloud and aerosol profiling is retrievals of parameters from combined lidar and passive sensing involving visible, infrared and microwave frequencies. A lidar based on a large pulse, solid state diode pumped ND:YAG laser has been deployed on the NASA ER-2 high altitude research aircraft along with multi-spectral visible/IR and microwave imaging radiometers since 1993. The system has shown high reliability in an extensive series of experimental projects for cloud remote sensing. The retrieval of cirrus radiation parameters is an effective application for combined lidar and passive sensing. An approved NASA mission will soon begin long term lidar observation of

  4. 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...

  5. 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.

  6. Wind field measurement in the nonprecipitous regions surrounding storms by an airborne pulsed Doppler lidar system, appendix A

    Science.gov (United States)

    Bilbro, J. W.; Vaughan, W. W.

    1980-01-01

    Coherent Doppler lidar appears to hold great promise in contributing to the basic store of knowledge concerning flow field characteristics in the nonprecipitous regions surrounding severe storms. The Doppler lidar, through its ability to measure clear air returns, augments the conventional Doppler radar system, which is most useful in the precipitous regions of the storm. A brief description of the Doppler lidar severe storm measurement system is provided along with the technique to be used in performing the flow field measurements. The application of the lidar is addressed, and the planned measurement program is outlined.

  7. 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.

  8. Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey

    Science.gov (United States)

    Lei Wang; Andrew G. Birt; Charles W. Lafon; David M. Cairns; Robert N. Coulson; Maria D. Tchakerian; Weimin Xi; Sorin C. Popescu; James M. Guldin

    2013-01-01

    Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical...

  9. Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (lidar) in Densely Vegetated Areas of Tropics

    Science.gov (United States)

    Bibi, T.; Azahari Razak, K.; Rahman, A. Abdul; Latif, A.

    2017-10-01

    Landslides are an inescapable natural disaster, resulting in massive social, environmental and economic impacts all over the world. The tropical, mountainous landscape in generally all over Malaysia especially in eastern peninsula (Borneo) is highly susceptible to landslides because of heavy rainfall and tectonic disturbances. The purpose of the Landslide hazard mapping is to identify the hazardous regions for the execution of mitigation plans which can reduce the loss of life and property from future landslide incidences. Currently, the Malaysian research bodies e.g. academic institutions and government agencies are trying to develop a landslide hazard and risk database for susceptible areas to backing the prevention, mitigation, and evacuation plan. However, there is a lack of devotion towards landslide inventory mapping as an elementary input of landslide susceptibility, hazard and risk mapping. The developing techniques based on remote sensing technologies (satellite, terrestrial and airborne) are promising techniques to accelerate the production of landslide maps, shrinking the time and resources essential for their compilation and orderly updates. The aim of the study is to provide a better perception regarding the use of virtual mapping of landslides with the help of LiDAR technology. The focus of the study is spatio temporal detection and virtual mapping of landslide inventory via visualization and interpretation of very high-resolution data (VHR) in forested terrain of Mesilau river, Kundasang. However, to cope with the challenges of virtual inventory mapping on in forested terrain high resolution LiDAR derivatives are used. This study specifies that the airborne LiDAR technology can be an effective tool for mapping landslide inventories in a complex climatic and geological conditions, and a quick way of mapping regional hazards in the tropics.

  10. 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.

  11. APPLIED GEOSPATIAL EDUCATION: ACQUISITION AND PROCESSING OF HIGH RESOLUTION AIRBORNE LIDAR AND ORTHOIMAGES FOR THE GREAT SMOKY MOUNTAINS NATIONAL PARK, SOUTHEASTERN UNITED STATES

    Directory of Open Access Journals (Sweden)

    T. R. Jordan

    2012-07-01

    Full Text Available In an innovative collaboration between government, university and private industry, researchers at the University of Georgia and Gainesville State College are collaborating with Photo Science, Inc. to acquire, process and quality control check lidar and or-thoimages of forest areas in the Southern Appalachian Mountains of the United States. Funded by the U.S. Geological Survey, this project meets the objectives of the ARRA initiative by creating jobs, preserving jobs and training students for high skill positions in geospatial technology. Leaf-off lidar data were acquired at 1-m resolution of the Tennessee portion of the Great Smoky Mountain National Park (GRSM and adjacent Foothills Parkway. This 1400-sq. km. area is of high priority for national/global interests due to biodiversity, rare and endangered species and protection of some of the last remaining virgin forest in the U.S. High spatial resolution (30 cm leaf-off 4-band multispectral orthoimages also were acquired for both the Chattahoochee National Forest in north Georgia and the entire GRSM. The data are intended to augment the National Elevation Dataset and orthoimage database of The National Map with information that can be used by many researchers in applications of LiDAR point clouds, high resolution DEMs and or-thoimage mosaics. Graduate and undergraduate students were involved at every stage of the workflow in order to provide then with high level technical educational and professional experience in preparation for entering the geospatial workforce. This paper will present geospatial workflow strategies, multi-team coordination, distance-learning training and industry-academia partnership.

  12. 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.

  13. 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.

  14. 2003 U.S. Geological Survey (USGS) Experimental Advanced Airborne Research Lidar (EAARL): US Virgin Islands (St. John, St. Croix)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains topographic and bathymetric lidar data that were collected on April 21, 23, 30, May 2, and June 14, 17 of 2003, cooperatively by the U.S....

  15. 2009 USGS/NPS Experimental Advanced Airborne Research Lidar (EAARL): Cape Hatteras National Seashore - Post-Nor'easter Ida

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This is a bare-earth data lidar data set that was collected on November 27, 29 and December 1, 2009 along the shoreline of the Cape Hatteras National Seashore in...

  16. 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...

  17. Lidar measurements of boundary layer depolarization and CCSEM-EDX compositional analysis of airborne particles on collocated passive samplers throughout the forest canopy during the 2016 airborne pollen season at UMBS, Pellston, MI

    Science.gov (United States)

    Wozniak, M. C.; Steiner, A.; Ault, A. P.; Kort, E. A.; Lersch, T.; Casuccio, G.

    2017-12-01

    Observations of airborne pollen are typically made with volumetric samplers that obtain a time-averaged pollen concentration at a single point. While spatial variations in surface pollen concentrations may be known with these samplers given multiple sampling sites, real-time boundary layer transport of pollen grains cannot be determined except by particle dispersion or tracer transport models. Recently, light detection and ranging (lidar) techniques, such as depolarization, have been used to measure pollen transport and optical properties throughout the boundary layer over time. Here, we use a ground-based micro-pulse lidar (MPL) to observe boundary layer vertical profiles before, during and after the peak anemophilous (wind-driven) pollen season. The lidar depolarization ratio is measured in tandem with the normalized R-squared backscatter (NRB) intensity to determine the contribution of aspherical particles to the scatterers present throughout the boundary layer. Measurements are taken from April 15 - July 12, 2016 at the University of Michigan Biological Station (UMBS) PROPHET outdoor research lab and tower within a largely forested region. UMBS is dominated by Acer rubrum, Betula papyrifera, Pinus resinosa, Quercus rubra and Pinus strobus, all of which began flowering on 4/19, 5/3, 5/25, 5/25 and 6/14, respectively. Temperature, relative humidity and wind speed measured on site determine daytime conditions conducive to pollen dispersion from flowers. Lidar depolarization ratios between 0.08-0.14 and higher are observed in the daytime boundary layer on days shortly after the flowering dates of the aforementioned species, elevated above the background level of 0.06 or less. Lidar observations are supplemented with aerosol compositional analysis determined by computer-controlled scanning electron microscopy and energy-dispersive X-ray spectroscopy (CCSEM-EDX) on passive sampler data from below, within and above the forest canopy at PROPHET tower. Particles are

  18. CLASSIFICATION BY USING MULTISPECTRAL POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    C. T. Liao

    2012-07-01

    Full Text Available Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

  19. Classification by Using Multispectral Point Cloud Data

    Science.gov (United States)

    Liao, C. T.; Huang, H. H.

    2012-07-01

    Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Estimation of Aboveground Biomass in Alpine Forests: A Semi-Empirical Approach Considering Canopy Transparency Derived from Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Martin Rutzinger

    2010-12-01

    Full Text Available In this study, a semi-empirical model that was originally developed for stem volume estimation is used for aboveground biomass (AGB estimation of a spruce dominated alpine forest. The reference AGB of the available sample plots is calculated from forest inventory data by means of biomass expansion factors. Furthermore, the semi-empirical model is extended by three different canopy transparency parameters derived from airborne LiDAR data. These parameters have not been considered for stem volume estimation until now and are introduced in order to investigate the behavior of the model concerning AGB estimation. The developed additional input parameters are based on the assumption that transparency of vegetation can be measured by determining the penetration of the laser beams through the canopy. These parameters are calculated for every single point within the 3D point cloud in order to consider the varying properties of the vegetation in an appropriate way. Exploratory Data Analysis (EDA is performed to evaluate the influence of the additional LiDAR derived canopy transparency parameters for AGB estimation. The study is carried out in a 560 km2 alpine area in Austria, where reference forest inventory data and LiDAR data are available. The investigations show that the introduction of the canopy transparency parameters does not change the results significantly according to R2 (R2 = 0.70 to R2 = 0.71 in comparison to the results derived from, the semi-empirical model, which was originally developed for stem volume estimation.

  7. Sub-Compartment Variation in Tree Height, Stem Diameter and Stocking in a Pinus radiata D. Don Plantation Examined Using Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Hanieh Saremi

    2014-08-01

    Full Text Available Better information regarding the spatial variability of height, Diameter at Breast Height (DBH and stocking could improve inventory estimates at the operational Planning Unit since these parameters are used extensively in allometric equations, including stem volume, biomass and carbon calculations. In this study, the influence of stand stocking on height and DBH of two even aged radiata pine (Pinus radiata D. Don stands were investigated using airborne Light Detection and Ranging (LiDAR data at a study site in New South Wales, Australia. Both stands were characterized by irregular stocking due to patchy establishment and self-thinning in the absence of any silvicultural thinning events. For the purpose of this study, a total of 34 plots from a 34 year old site and 43 plots from a nine year old site were established, from which a total of 447 trees were sampled. Within these plots, DBH and height measurements were measured and their relationships with stocking were evaluated. LiDAR was used for height estimation as well as stem counts in fixed plots (stocking. The results showed a significant relationship between stem DBH and stocking. At both locations, trees with larger diameters were found on lower stocking sites. Height values were also significantly correlated with stocking, with taller trees associated with high stocking. These results were further verified of additional tree samples, with independent field surveys for DBH and LiDAR-derived metrics for height analysis. This study confirmed the relationship between P. radiata tree heights and stem diameter with stocking and demonstrated the capacity of LiDAR to capture sub-compartment variation in these tree-level attributes.

  8. Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

    Science.gov (United States)

    Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

    2015-01-01

    Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

  9. 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.

  10. A COMPARITIVE STUDY USING GEOMETRIC AND VERTICAL PROFILE FEATURES DERIVED FROM AIRBORNE LIDAR FOR CLASSIFYING TREE GENERA

    Directory of Open Access Journals (Sweden)

    C. Ko

    2012-07-01

    Full Text Available We present a comparative study between two different approaches for tree genera classification using descriptors derived from tree geometry and those derived from the vertical profile analysis of LiDAR point data. The different methods provide two perspectives for processing LiDAR point clouds for tree genera identification. The geometric perspective analyzes individual tree crowns in relation to valuable information related to characteristics of clusters and line segments derived within crowns and overall tree shapes to highlight the spatial distribution of LiDAR points within the crown. Conversely, analyzing vertical profiles retrieves information about the point distributions with respect to height percentiles; this perspective emphasizes of the importance that point distributions at specific heights express, accommodating for the decreased point density with respect to depth of canopy penetration by LiDAR pulses. The targeted species include white birch, maple, oak, poplar, white pine and jack pine at a study site northeast of Sault Ste. Marie, Ontario, Canada.

  11. Application of lidar and optical data for oil palm plantation management in Malaysia

    Science.gov (United States)

    Shafri, Helmi Z. M.; Ismail, Mohd Hasmadi; Razi, Mohd Khairil M.; Anuar, Mohd Izzuddin; Ahmad, Abdul Rahman

    2012-11-01

    Proper oil palm plantation management is crucial for Malaysia as the country depends heavily on palm oil as a major source of national income. Precision agriculture is considered as one of the approaches that can be adopted to improve plantation practices for plantation managers such as the government-owned FELDA. However, currently the implementation of precision agriculture based on remote sensing and GIS is still lacking. This study explores the potential of the use of LiDAR and optical remote sensing data for plantation road and terrain planning for planting purposes. Traditional approaches use land surveying techniques that are time consuming and costly for vast plantation areas. The first ever airborne LiDAR and multispectral survey for oil palm plantation was carried out in early 2012 to test its feasibility. Preliminary results show the efficiency of such technology in demanding engineering and agricultural requirements of oil palm plantation. The most significant advantage of the approach is that it allows plantation managers to accurately plan the plantation road and determine the planting positions of new oil palm seedlings. Furthermore, this creates for the first time, digital database of oil palm estate and the airborne imagery can also be used for related activities such as oil palm tree inventory and detection of palm diseases. This work serves as the pioneer towards a more frequent application of LiDAR and multispectral data for oil palm plantation in Malaysia.

  12. 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...

  13. 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...

  14. Airborne Measurements of CO2 Column Concentration and Range Using a Pulsed Direct-Detection IPDA Lidar

    Science.gov (United States)

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

    2013-01-01

    We have previously demonstrated a pulsed direct detection IPDA lidar to measure range and the column concentration of atmospheric CO2. The lidar measures the atmospheric backscatter profiles and samples the shape of the 1,572.33 nm CO2 absorption line. We participated in the ASCENDS science flights on the NASA DC-8 aircraft during August 2011 and report here lidar measurements made on four flights over a variety of surface and cloud conditions near the US. These included over a stratus cloud deck over the Pacific Ocean, to a dry lake bed surrounded by mountains in Nevada, to a desert area with a coal-fired power plant, and from the Rocky Mountains to Iowa, with segments with both cumulus and cirrus clouds. Most flights were to altitudes >12 km and had 5-6 altitude steps. Analyses show the retrievals of lidar range, CO2 column absorption, and CO2 mixing ratio worked well when measuring over topography with rapidly changing height and reflectivity, through thin clouds, between cumulus clouds, and to stratus cloud tops. The retrievals shows the decrease in column CO2 due to growing vegetation when flying over Iowa cropland as well as a sudden increase in CO2 concentration near a coal-fired power plant. For regions where the CO2 concentration was relatively constant, the measured CO2 absorption lineshape (averaged for 50 s) matched the predicted shapes to better than 1% RMS error. For 10 s averaging, the scatter in the retrievals was typically 2-3 ppm and was limited by the received signal photon count. Retrievals were made using atmospheric parameters from both an atmospheric model and from in situ temperature and pressure from the aircraft. The retrievals had no free parameters and did not use empirical adjustments, and >70% of the measurements passed screening and were used in analysis. The differences between the lidar-measured retrievals and in situ measured average CO2 column concentrations were 6 km.

  15. Quantifying the Spatio-temporal Impacts of Sea Level Rise on Carbon Storage Using Repeat Lidar Surveys and Multispectral Satellite Imagery

    Science.gov (United States)

    Smart, L.; Taillie, P. J.; Smith, J. W.; Meentemeyer, R. K.

    2017-12-01

    Sound coastal land-use policy and management decisions to mitigate or adapt to sea level rise impacts depend on understanding vegetation responses to sea level rise over large extents. Accurate methodologies to quantify these changes are necessary to understand the continued production of the ecosystem services upon which human health and well-being depend. This research quantifies spatio-temporal changes in aboveground biomass altered by sea level rise across North Carolina's coastal plain using a combination of repeat-acquisition lidar data and multi-temporal satellite imagery. Using field data from across the study area, we evaluated the reliability of multi-temporal lidar data with disparate densities and accuracies to detect changes along a coastal vegetation gradient from marsh to forested wetland. Despite an 18 fold increase in lidar point density between survey years (2001, 2014), the relationships between lidar-derived heights and field-measured heights were similar (adjusted r2; 0.6 -0.7). Random Forest, a machine learning algorithm, was used to separately predict above-ground biomass pools at the landscape-scale for the two time periods using the 98 field plots as reference data. Models performed well for both years (adjusted r2; 0.67-0.85). The 2001 model required the addition of Landsat spectral indices to meet the same adjusted r2 values as the 2014 model, which utilized lidar-derived metrics alone. Of the many potential lidar-derived predictor metrics, median and mean vegetation height were the best predictors in both time periods. To measure the spatial patterns of biomass change across the landscape, we subtracted the 2001 biomass model from the 2014 model and found significant spatial heterogeneity in biomass change across both the vegetation gradient and across the peninsula over the 12-year time period. In forested areas, we found a mean increase in aboveground biomass whereas in transition zones, marshes and freshwater emergent wetlands we

  16. Application of Airborne LiDAR to the Determination of the Height of Large Structures. Case Study: Dams

    Directory of Open Access Journals (Sweden)

    Rubén Martínez Marín

    2014-01-01

    Full Text Available La mejor forma de calcular la altura de una presa es realizar una nivelación geométrica de precisión. No obstante, este método es demandante y costoso. La precisión de los datos obtenidos ha mejorado sustancialmente, esta tecnología puede proveer precisiones de 2 a 3 centímetros, más que suficiente para determinar la altura de presa y utilizar ésta como dato de partida para cualquier actividad posterior que así lo requiera. La densidad de adquisición de los datos LiDAR (Light Detection and Ranging es importante para establecer la bondad de los resultados. Finalmente, como los sistemas LiDAR aerotransportados están basados en alturas elipsoidales, es necesario transformarlas a ortométricas. Este trabajo muestra los resultados obtenidos usando un LiDAR de baja densidad (0.5 pts/m2 y su validación con observaciones GPS (Global Positioning System en postproceso. Los resultados demuestran que se puede obtener una precisión del orden de 10-25 cm, suficiente para la mayoría de las actividades relacionadas con la ingeniería civil.

  17. A principal component approach for predicting the stem volume in Eucalyptus plantations in Brazil using airborne LiDAR data

    Science.gov (United States)

    Carlos Alberto Silva; Carine Klauberg; Andrew T. Hudak; Lee A. Vierling; Veraldo Liesenberg; Samuel P. C. e Carvalho; Luiz C. E. Rodriguez

    2016-01-01

    Improving management practices in industrial forest plantations may increase production efficiencies, thereby reducing pressures on native tropical forests for meeting global pulp needs. This study aims to predict stem volume (V) in plantations of fast-growing Eucalyptus hybrid clones located in southeast Brazil using field plot and airborne Light Detection...

  18. Integration of TerraSAR-X, RapidEye and airborne lidar for remote sensing of intertidal bedforms on the upper flats of Norderney (German Wadden Sea)

    Science.gov (United States)

    Adolph, Winny; Jung, Richard; Schmidt, Alena; Ehlers, Manfred; Heipke, Christian; Bartholomä, Alexander; Farke, Hubert

    2017-04-01

    The Wadden Sea is a large coastal transition area adjoining the southern North Sea uniting ecological key functions with an important role in coastal protection. The region is strictly protected by EU directives and national law and is a UNESCO World Heritage Site, requiring frequent quality assessments and regular monitoring. In 2014 an intertidal bedform area characterised by alternating crests and water-covered troughs on the tidal flats of the island of Norderney (German Wadden Sea sector) was chosen to test different remote sensing methods for habitat mapping: airborne lidar, satellite-based radar (TerraSAR-X) and electro-optical sensors (RapidEye). The results revealed that, although sensitive to different surface qualities, all sensors were able to image the bedforms. A digital terrain model generated from the lidar data shows crests and slopes of the bedforms with high geometric accuracy in the centimetre range, but high costs limit the operation area. TerraSAR-X data enabled identifying the positions of the bedforms reflecting the residual water in the troughs also with a high resolution of up to 1.1 m, but with larger footprints and much higher temporal availability. RapidEye data are sensitive to differences in sediment moisture employed to identify crest areas, slopes and troughs, with high spatial coverage but the lowest resolution (6.5 m). Monitoring concepts may differ in their remote sensing requirements regarding areal coverage, spatial and temporal resolution, sensitivity and geometric accuracy. Also financial budgets limit the selection of sensors. Thus, combining differing assets into an integrated concept of remote sensing contributes to solving these issues.

  19. Three-Dimensional Reconstruction of Building Roofs from Airborne LiDAR Data Based on a Layer Connection and Smoothness Strategy

    Directory of Open Access Journals (Sweden)

    Yongjun Wang

    2016-05-01

    Full Text Available A new approach for three-dimensional (3-D reconstruction of building roofs from airborne light detection and ranging (LiDAR data is proposed, and it includes four steps. Building roof points are first extracted from LiDAR data by using the reversed iterative mathematic morphological (RIMM algorithm and the density-based method. The corresponding relations between points and rooftop patches are then established through a smoothness strategy involving “seed point selection, patch growth, and patch smoothing.” Layer-connection points are then generated to represent a layer in the horizontal direction and to connect different layers in the vertical direction. Finally, by connecting neighboring layer-connection points, building models are constructed with the second level of detailed data. The key contributions of this approach are the use of layer-connection points and the smoothness strategy for building model reconstruction. Experimental results are analyzed from several aspects, namely, the correctness and completeness, deviation analysis of the reconstructed building roofs, and the influence of elevation to 3-D roof reconstruction. In the two experimental regions used in this paper, the completeness and correctness of the reconstructed rooftop patches were about 90% and 95%, respectively. For the deviation accuracy, the average deviation distance and standard deviation in the best case were 0.05 m and 0.18 m, respectively; and those in the worst case were 0.12 m and 0.25 m. The experimental results demonstrated promising correctness, completeness, and deviation accuracy with satisfactory 3-D building roof models.

  20. 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...

  1. 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...

  2. Archaeological application of airborne LiDAR to examine social changes in the Ceibal region of the Maya lowlands

    Science.gov (United States)

    Triadan, Daniela; Pinzón, Flory; Burham, Melissa; Ranchos, José Luis; Aoyama, Kazuo; Haraguchi, Tsuyoshi

    2018-01-01

    Although the application of LiDAR has made significant contributions to archaeology, LiDAR only provides a synchronic view of the current topography. An important challenge for researchers is to extract diachronic information over typically extensive LiDAR-surveyed areas in an efficient manner. By applying an architectural chronology obtained from intensive excavations at the site center and by complementing it with surface collection and test excavations in peripheral zones, we analyze LiDAR data over an area of 470 km2 to trace social changes through time in the Ceibal region, Guatemala, of the Maya lowlands. We refine estimates of structure counts and populations by applying commission and omission error rates calculated from the results of ground-truthing. Although the results of our study need to be tested and refined with additional research in the future, they provide an initial understanding of social processes over a wide area. Ceibal appears to have served as the only ceremonial complex in the region during the transition to sedentism at the beginning of the Middle Preclassic period (c. 1000 BC). As a more sedentary way of life was accepted during the late part of the Middle Preclassic period and the initial Late Preclassic period (600–300 BC), more ceremonial assemblages were constructed outside the Ceibal center, possibly symbolizing the local groups’ claim to surrounding agricultural lands. From the middle Late Preclassic to the initial Early Classic period (300 BC-AD 300), a significant number of pyramidal complexes were probably built. Their high concentration in the Ceibal center probably reflects increasing political centralization. After a demographic decline during the rest of the Early Classic period, the population in the Ceibal region reached the highest level during the Late and Terminal Classic periods, when dynastic rule was well established (AD 600–950). PMID:29466384

  3. Archaeological application of airborne LiDAR to examine social changes in the Ceibal region of the Maya lowlands.

    Directory of Open Access Journals (Sweden)

    Takeshi Inomata

    Full Text Available Although the application of LiDAR has made significant contributions to archaeology, LiDAR only provides a synchronic view of the current topography. An important challenge for researchers is to extract diachronic information over typically extensive LiDAR-surveyed areas in an efficient manner. By applying an architectural chronology obtained from intensive excavations at the site center and by complementing it with surface collection and test excavations in peripheral zones, we analyze LiDAR data over an area of 470 km2 to trace social changes through time in the Ceibal region, Guatemala, of the Maya lowlands. We refine estimates of structure counts and populations by applying commission and omission error rates calculated from the results of ground-truthing. Although the results of our study need to be tested and refined with additional research in the future, they provide an initial understanding of social processes over a wide area. Ceibal appears to have served as the only ceremonial complex in the region during the transition to sedentism at the beginning of the Middle Preclassic period (c. 1000 BC. As a more sedentary way of life was accepted during the late part of the Middle Preclassic period and the initial Late Preclassic period (600-300 BC, more ceremonial assemblages were constructed outside the Ceibal center, possibly symbolizing the local groups' claim to surrounding agricultural lands. From the middle Late Preclassic to the initial Early Classic period (300 BC-AD 300, a significant number of pyramidal complexes were probably built. Their high concentration in the Ceibal center probably reflects increasing political centralization. After a demographic decline during the rest of the Early Classic period, the population in the Ceibal region reached the highest level during the Late and Terminal Classic periods, when dynastic rule was well established (AD 600-950.

  4. Archaeological application of airborne LiDAR to examine social changes in the Ceibal region of the Maya lowlands.

    Science.gov (United States)

    Inomata, Takeshi; Triadan, Daniela; Pinzón, Flory; Burham, Melissa; Ranchos, José Luis; Aoyama, Kazuo; Haraguchi, Tsuyoshi

    2018-01-01

    Although the application of LiDAR has made significant contributions to archaeology, LiDAR only provides a synchronic view of the current topography. An important challenge for researchers is to extract diachronic information over typically extensive LiDAR-surveyed areas in an efficient manner. By applying an architectural chronology obtained from intensive excavations at the site center and by complementing it with surface collection and test excavations in peripheral zones, we analyze LiDAR data over an area of 470 km2 to trace social changes through time in the Ceibal region, Guatemala, of the Maya lowlands. We refine estimates of structure counts and populations by applying commission and omission error rates calculated from the results of ground-truthing. Although the results of our study need to be tested and refined with additional research in the future, they provide an initial understanding of social processes over a wide area. Ceibal appears to have served as the only ceremonial complex in the region during the transition to sedentism at the beginning of the Middle Preclassic period (c. 1000 BC). As a more sedentary way of life was accepted during the late part of the Middle Preclassic period and the initial Late Preclassic period (600-300 BC), more ceremonial assemblages were constructed outside the Ceibal center, possibly symbolizing the local groups' claim to surrounding agricultural lands. From the middle Late Preclassic to the initial Early Classic period (300 BC-AD 300), a significant number of pyramidal complexes were probably built. Their high concentration in the Ceibal center probably reflects increasing political centralization. After a demographic decline during the rest of the Early Classic period, the population in the Ceibal region reached the highest level during the Late and Terminal Classic periods, when dynastic rule was well established (AD 600-950).

  5. Estimation of Above Ground Biomass in a Tropical Mountain Forest in Southern Ecuador Using Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Víctor González-Jaramillo

    2018-04-01

    Full Text Available A reliable estimation of Above Ground Biomass (AGB in Tropical Mountain Forest (TMF is still complicated, due to fast-changing climate and topographic conditions, which modifies the forest structure within fine scales. The variations in vertical and horizontal forest structure are hardly detectable by small field plots, especially in natural TMF due to the high tree diversity and the inaccessibility of remote areas. Therefore, the present approach used remotely sensed data from a Light Detection and Ranging (LiDAR sensor in combination with field measurements to estimate AGB accurately for a catchment in the Andes of south-eastern Ecuador. From the LiDAR data, information about horizontal and vertical structure of the TMF could be derived and the vegetation at tree level classified, differentiated between the prevailing forest types (ravine forest, ridge forest and Elfin Forest. Furthermore, topographical variables (Topographic Position Index, TPI; Morphometric Protection Index, MPI were calculated by means of the high-resolution LiDAR data to analyse the AGB distribution within the catchment. The field measurements included different tree parameters of the species present in the plots, which were used to determine the local mean Wood Density (WD as well as the specific height-diameter relationship to calculate AGB, applying regional scale modelling at tree level. The results confirmed that field plot measurements alone cannot capture completely the forest structure in TMF but in combination with high resolution LiDAR data, applying a classification at tree level, the AGB amount (Mg ha−1 and its distribution in the entire catchment could be estimated adequately (model accuracy at tree level: R2 > 0.91. It was found that the AGB distribution is strongly related to ridges and depressions (TPI and to the protection of the site (MPI, because high AGB was also detected at higher elevations (up to 196.6 Mg ha−1, above 2700 m, if the site is

  6. Registration of airborne LiDAR data and aerial images based on straight lines and POS data

    Science.gov (United States)

    Du, Quanye; Xu, Biao; Cao, Hui

    2009-10-01

    This paper presents a registration method which based on straight lines primitive. Firstly, 2D straight lines are extracted from aerial images using Canny operator and straight line fitting. In the similar way, 3D straight lines are extracted from LiDAR range images which derive from laser scanning point cloud. Secondly, 3D straight lines are projected to aerial images using collinearity equations and Position and Orientation System (POS) data. Then the corresponding lines are determined by straight line error. At last, each image's new exterior orientation elements are calculated by generalized point (straight line) photogrammetry.

  7. Airborne Lidar Measurements of Below-canopy Surface Water Height , Slope and Optical Properties in the Florida Everglades Shark River Slough

    Science.gov (United States)

    Dabney, P.; Harding, D. J.; Valett, S. R.; Yu, A. W.; Feliciano, E. A.; Neuenschwander, A. L.; Pitts, K.

    2015-12-01

    Determining the presence, persistence, optical properties and variation in height and slope of surface water beneath the dense canopies of flooded forests and mangrove stands could contribute to studies of the acquisition of water and nutrients by plant roots. NASA's airborne Slope Imaging Multi-polarization Photon-counting Lidar (SIMPL) provides unique capabilities that can identify below-canopy surface water, measure its height with respect to vegetation constituents with sub-decimeter precision and quantify its slope. It also provides information on canopy structure and closure, the water column extinction profile as a proxy for turbidity and water depth, with the penetration depth constrained by turbidity. It achieves this by using four laser beams operating at two wavelengths with measurements of water surface elevation at 1064 nm (near infrared) and water column properties at 532 nm (green), analogous to a bathymetric lidar. Importantly the instrument adds a polarimetry function, like some atmospheric lidars, which measures the amount of depolarization determined by the degree to which the plane-parallel transmitted laser pulse energy is converted to the perpendicular state. The degree of depolarization is sensitive to the number of photon multiple-scattering events. For the water surface, which is specular consisting only of single-scattering events, the near-infrared received signal retains the parallel polarization state. Absence of the perpendicular signal uniquely identifies surface water. Penetration of green light and the depth profile of photons converted to the perpendicular state compared to those in the parallel state is a measure of water-column multiple scattering, providing a relative measure of turbidity. The amount of photons reflected from the canopy versus the water provides a wavelength-dependent measure of canopy closure. By rapidly firing laser pulses (11,400 pulses per second) with a narrow width (1 nsec) and detecting single photons

  8. High-resolution digital elevation model of Mount St. Helens crater and upper North Fork Toutle River basin, Washington, based on an airborne lidar survey of September 2009

    Science.gov (United States)

    Mosbrucker, Adam

    2014-01-01

    The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the North Fork Toutle River basin, which drains the northern flank of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, built a sediment retention structure on the North Fork Toutle River in 1989 to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From September 16–20, 2009, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 214 square kilometers (83 square miles) of Mount St. Helens and the upper North Fork Toutle River basin from the sediment retention structure to the volcano's crater. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at Castle, Coldwater, and Spirit Lakes. Final results averaged about five laser last

  9. High-resolution digital elevation model of lower Cowlitz and Toutle Rivers, adjacent to Mount St. Helens, Washington, based on an airborne lidar survey of October 2007

    Science.gov (United States)

    Mosbrucker, Adam

    2015-01-01

    The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the Toutle River basin, which drains the northern and western flanks of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and lower Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, continues to monitor and mitigate excess sediment in North and South Fork Toutle River basins to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From October 22–27, 2007, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 273 square kilometers (105 square miles) of lower Cowlitz and Toutle River tributaries from the Columbia River at Kelso, Washington, to upper North Fork Toutle River (below the volcano's edifice), including lower South Fork Toutle River. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at

  10. Mapping forest aboveground biomass using airborne hyperspectral and LiDAR data in the mountainous conditions of Central Europe

    Czech Academy of Sciences Publication Activity Database

    Brovkina, Olga; Novotný, Jan; Cienciala, E.; Zemek, František; Russ, R.

    2017-01-01

    Roč. 100, Mar (2017), s. 219-230 ISSN 0925-8574 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk OC09001 Institutional support: RVO:67179843 Keywords : biomass estimation * spruce * beech * airborne remote sensing * tree level * plot level Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7) Impact factor: 2.914, year: 2016

  11. Airborne differential absorption lidar for water vapour measurements in the upper troposphere and lower stratosphere in the spectral region around 940 nm

    Energy Technology Data Exchange (ETDEWEB)

    Poberaj, G.

    2000-07-01

    Two all-solid-state laser systems were developed and studied in detail to optimise their performance for an airborne water vapour differential absorption lidar (DIAL). Their special features are high average output powers and excellent spectral properties in the 940-nm spectral region relevant for monitoring very low water vapour contents in the upper troposphere and lower stratosphere. One system is an injection-seeded pulsed Ti:sapphire ring laser with a spectral bandwidth of 105 MHz and an average power of 1.1 W. The other system is an injection-seeded optical parametric oscillator (OPO) in a ring configuration. Using KTP as nonlinear crystal, a signal output with a spectral bandwidth of 140 MHz and an average power of 1.2 W was achieved. Both systems, the Ti:sapphire ring laser and the KTP OPO, possess spectral purity values higher than 99%. The pump source for these systems is a frequency doubled diode-pumped Nd:YAG laser operating at a repetition rate of 100 Hz. The KTP OPO system has been used as a transmitter in a new airborne water vapour DIAL instrument. For the first time, measurements of two-dimensional water vapour distributions with a high vertical (500 m) and horizontal (20 km) resolution across several potential vorticity streamers were performed. Very low water vapour mixing ratios (10-50 ppmv) and strong gradients were observed in the tropopause region. The sensitivity of the DIAL instrument in the centre of a stratospheric intrusion ranges from 3% in the near field to 12% in the far field (4 km). The first comparison experiments with in situ measuring instruments show a good agreement. Considerable differences are found between DIAL measurements and data obtained from the ECMWF operational analyses and a mesoscale numerical model. (orig.)

  12. Lidar to lidar calibration

    DEFF Research Database (Denmark)

    Fernandez Garcia, Sergio; Villanueva, Héctor

    This report presents the result of the lidar to lidar calibration performed for ground-based lidar. Calibration is here understood as the establishment of a relation between the reference lidar wind speed measurements with measurement uncertainties provided by measurement standard and corresponding...... lidar wind speed indications with associated measurement uncertainties. The lidar calibration concerns the 10 minute mean wind speed measurements. The comparison of the lidar measurements of the wind direction with that from the reference lidar measurements are given for information only....

  13. Application of Airborne LiDAR Data and Geographic Information Systems (GIS to Develop a Distributed Generation System for the Town of Normal, IL

    Directory of Open Access Journals (Sweden)

    Jin H. Jo

    2015-03-01

    Full Text Available Distributed generation allows a variety of small, modular power-generating technologies to be combined with load management and energy storage systems to improve the quality and reliability of our electricity supply. As part of the US Environmental Protection Agency's effort to reduce CO2 emissions from existing power plants by 30% by 2030, distributed generation through solar photovoltaic systems provides a viable option for mitigating the negative impacts of centralized fossil fuel plants. This study conducted a detailed analysis to identify the rooftops in a town in Central Illinois that are suitable for distributed generation solar photovoltaic systems with airborn LiDAR data and to quantify their energy generation potential with an energy performance model. By utilizing the available roof space of the 9,718 buildings in the case study area, a total of 39.27 MW solar photovoltaic systems can provide electrical generation of 53,061 MWh annually. The unique methodology utilized for this assessment of a town's solar potential provides an effective way to invest in a more sustainable energy future and ensure economic stability.

  14. Aerosol backscatter measurements at 10.6 microns with airborne and ground-based CO2 Doppler lidars over the Colorado High Plains. II - Backscatter structure

    Science.gov (United States)

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

    1991-01-01

    Measurements of tropospheric aerosol volume backscatter coefficients at 10.6-microns wavelength were obtained with airborne continuous wave and ground-based pulsed CO2 Doppler lidars over the Colorado High Plains during a 20-day period in summer 1982. A persistent 'background' layer was found between 6- and 10-km altitude, with a generally uniform backscatter mixing ratio of about 10 to the -10th sq m/kg per sr. The upper boundary of this background layer varied with the tropopause height; the lower boundary varied with the strength and diurnal cycle of convective mixing in the planetary boundary layer (PBL). For quiescent meteorological conditions, the transition from the PBL to the background layer was usually very sharp, with backscatter decreases sometimes as large as 3 decades in about 70 m. Sharp gradients were also found at the boundaries of shallow (tens of meters) subvisible cirrus clouds. For less stable conditions, associated with vertical aerosol transport by deep cumuliform clouds, backscatter tended to decrease exponentially with altitude.

  15. Physical and optical properties of 2010 Eyjafjallajökull volcanic eruption aerosol: ground-based, Lidar and airborne measurements in France

    Directory of Open Access Journals (Sweden)

    M. Hervo

    2012-02-01

    Full Text Available During the Eyjafjallajökull eruption (14 April to 24 May 2010, the volcanic aerosol cloud was observed across Europe by several airborne in situ and ground-based remote-sensing instruments. On 18 and 19 May, layers of depolarizing particles (i.e. non-spherical particles were detected in the free troposphere above the Puy de Dôme station, (PdD, France with a Rayleigh-Mie LIDAR emitting at a wavelength of 355 nm, with parallel and crossed polarization channels. These layers in the free troposphere (FT were also well captured by simulations with the Lagrangian particle dispersion model FLEXPART, which furthermore showed that the ash was eventually entrained into the planetary boundary layer (PBL. Indeed, the ash cloud was then detected and characterized with a comprehensive set of in situ instruments at the Puy de Dôme station (PdD. In agreement with the FLEXPART simulation, up to 65 μg m−3 of particle mass and 2.2 ppb of SO2 were measured at PdD, corresponding to concentrations higher than the 95 percentile of 2 yr of measurements at PdD. Moreover, the number concentration of particles increased to 24 000 cm−3, mainly in the submicronic mode, but a supermicronic mode was also detected with a modal diameter of 2 μm. The resulting optical properties of the ash aerosol were characterized by a low scattering Ångström exponent (0.98, showing the presence of supermicronic particles. For the first time to our knowledge, the combination of in situ optical and physical characterization of the volcanic ash allowed the calculation of the mass-to-extinction ratio (η with no assumptions on the aerosol density. The mass-to-extinction ratio was found to be significantly different from the background boundary layer aerosol (max: 1.57 g m−2 as opposed to 0.33 ± 0.03 g m−2. Using this ratio, ash mass concentration in the volcanic plume derived from LIDAR measurements was found to be 655 ± 23

  16. Detection of tropical landslides using airborne lidar data and multi imagery: A case study in genting highland, pahang

    International Nuclear Information System (INIS)

    Khamsin, I; Zulkarnain, M; Razak, K A; Rizal, S

    2014-01-01

    The landslide geomorphological system in a tropical region is complex, and its understanding often depends on the completeness and correctness of landslide inventorization. In mountainous regions, landslides pose a significant impact and are known as an important geomorphic process in shaping major landscape in the tropics. A modern remote sensing based approach has revolutionized the landslide investigation in a forested terrain. Optical satellite imagery, aerial photographs and synthetic aperture radar images are less effective to create reliable tropical DTMs for landslide recognition, and even so in the forested equatorial regions. Airborne laser scanning (ALS) data have been used to construct the digital terrain model (DTM) under dense vegetation, but its reliability for landslide recognition in the tropics remains surprisingly unknown. The present study aims at providing better insight into the use of airborne laser scanning (ALS) data. For the bare-earth extraction, several prominent filtering algorithms and surface interpolation methods, i.e. progressive TIN densitification, morphological, and command prompt from Lastool are evaluated in a qualitative analysis, aiming at removing non-ground points while preserving important landslide features. As a result, a large landslide can be detected using OOA. Small landslides remain unrecognized. Three out of five landslides can be detected, with a 60 percent overall accuracy

  17. CO-REGISTRATION AIRBORNE LIDAR POINT CLOUD DATA AND SYNCHRONOUS DIGITAL IMAGE REGISTRATION BASED ON COMBINED ADJUSTMENT

    Directory of Open Access Journals (Sweden)

    Z. H. Yang

    2016-06-01

    Full Text Available Aim at the problem of co-registration airborne laser point cloud data with the synchronous digital image, this paper proposed a registration method based on combined adjustment. By integrating tie point, point cloud data with elevation constraint pseudo observations, using the principle of least-squares adjustment to solve the corrections of exterior orientation elements of each image, high-precision registration results can be obtained. In order to ensure the reliability of the tie point, and the effectiveness of pseudo observations, this paper proposed a point cloud data constrain SIFT matching and optimizing method, can ensure that the tie points are located on flat terrain area. Experiments with the airborne laser point cloud data and its synchronous digital image, there are about 43 pixels error in image space using the original POS data. If only considering the bore-sight of POS system, there are still 1.3 pixels error in image space. The proposed method regards the corrections of the exterior orientation elements of each image as unknowns and the errors are reduced to 0.15 pixels.

  18. 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

  19. 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.

  20. 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...

  1. 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...

  2. A Two-Stage Optimization Strategy for Fuzzy Object-Based Analysis Using Airborne LiDAR and High-Resolution Orthophotos for Urban Road Extraction

    Directory of Open Access Journals (Sweden)

    Maher Ibrahim Sameen

    2017-01-01

    Full Text Available In the last decade, object-based image analysis (OBIA has been extensively recognized as an effective classification method for very high spatial resolution images or integrated data from different sources. In this study, a two-stage optimization strategy for fuzzy object-based analysis using airborne LiDAR was proposed for urban road extraction. The method optimizes the two basic steps of OBIA, namely, segmentation and classification, to realize accurate land cover mapping and urban road extraction. This objective was achieved by selecting the optimum scale parameter to maximize class separability and the optimum shape and compactness parameters to optimize the final image segments. Class separability was maximized using the Bhattacharyya distance algorithm, whereas image segmentation was optimized using the Taguchi method. The proposed fuzzy rules were created based on integrated data and expert knowledge. Spectral, spatial, and texture features were used under fuzzy rules by implementing the particle swarm optimization technique. The proposed fuzzy rules were easy to implement and were transferable to other areas. An overall accuracy of 82% and a kappa index of agreement (KIA of 0.79 were achieved on the studied area when results were compared with reference objects created via manual digitization in a geographic information system. The accuracy of road extraction using the developed fuzzy rules was 0.76 (producer, 0.85 (user, and 0.72 (KIA. Meanwhile, overall accuracy was decreased by approximately 6% when the rules were applied on a test site. A KIA of 0.70 was achieved on the test site using the same rules without any changes. The accuracy of the extracted urban roads from the test site was 0.72 (KIA, which decreased to approximately 0.16. Spatial information (i.e., elongation and intensity from LiDAR were the most interesting properties for urban road extraction. The proposed method can be applied to a wide range of real applications

  3. Assessing fire effects on forest spatial structure using a fusion of Landsat and airborne LiDAR data in Yosemite National Park

    Science.gov (United States)

    Kane, Van R.; North, Malcolm P.; Lutz, James A.; Churchill, Derek J.; Roberts, Susan L.; Smith, Douglas F.; McGaughey, Robert J.; Kane, Jonathan T.; Brooks, Matthew L.

    2014-01-01

    Mosaics of tree clumps and openings are characteristic of forests dominated by frequent, low- and moderate-severity fires. When restoring these fire-suppressed forests, managers often try to reproduce these structures to increase ecosystem resilience. We examined unburned and burned forest structures for 1937 0.81 ha sample areas in Yosemite National Park, USA. We estimated severity for fires from 1984 to 2010 using the Landsat-derived Relativized differenced Normalized Burn Ratio (RdNBR) and measured openings and canopy clumps in five height strata using airborne LiDAR data. Because our study area lacked concurrent field data, we identified methods to allow structural analysis using LiDAR data alone. We found three spatial structures, canopy-gap, clump-open, and open, that differed in spatial arrangement and proportion of canopy and openings. As fire severity increased, the total area in canopy decreased while the number of clumps increased, creating a patchwork of openings and multistory tree clumps. The presence of openings > 0.3 ha, an approximate minimum gap size needed to favor shade-intolerant pine regeneration, increased rapidly with loss of canopy area. The range and variation of structures for a given fire severity were specific to each forest type. Low- to moderate-severity fires best replicated the historic clump-opening patterns that were common in forests with frequent fire regimes. Our results suggest that managers consider the following goals for their forest restoration: 1) reduce total canopy cover by breaking up large contiguous areas into variable-sized tree clumps and scattered large individual trees; 2) create a range of opening sizes and shapes, including ~ 50% of the open area in gaps > 0.3 ha; 3) create multistory clumps in addition to single story clumps; 4) retain historic densities of large trees; and 5) vary treatments to include canopy-gap, clump-open, and open mosaics across project areas to mimic the range of patterns found for each

  4. Airborne lidar measurements of aerosol spatial distribution and optical properties over the Atlantic Ocean during a European pollution outbreak of ACE-2[Special issue with manuscripts related to the second Aerosol Characterization Experiment (ACE-2), 16 June-25 July 1997

    Energy Technology Data Exchange (ETDEWEB)

    Flamant, Cyrille; Pelon, Jaques; Trouillet, Vincent; Bruneau, Didier [CNRS-UPMC-UVSQ, Paris (France). Service d' Aeronomie; Chazette, Patrick; Leon, J.F. [CEA-CNRS, Gif-sur-Yvette (France). Lab. des Sciences du Climat et de l' Environment; Quinn, P.K.; Bates, T.S.; Johnson, James [National Oceanic and Atmospheric Administration, Seattle, WA (United States). Pacific Marine Environmental Lab.; Frouin, Robert [Scripps Inst. of Oceanography, La Jolla, CA (United States); Livingston, John [SRI International, Menlo Park, CA (United States)

    2000-04-01

    Airborne lidar measurements of the aerosol spatial distribution and optical properties associated with an European pollution outbreak which occurred during the Second Aerosol Characterization Experiment (ACE-2) are presented. Size distribution spectra measured over the ocean near Sagres (Portugal), on-board the Research Vessel Vodyanitsky and on-board the Avion de Recherche Atmospherique et Teledetection (ARAT) have been used to parameterize the aerosol vertical distribution. This parameterization, which is essential to the analysis of airborne lidar measurements, has been validated via closure experiments on extinction coefficient profiles and aerosol optical depth (AOD). During the studied event, AOD's retrieved from lidar measurements at 0.73 {mu}m range between 0.055 and 0.10. The parameterized aerosol vertical distribution has been used to shift AOD retrievals from 0.73 to 0.55 {mu}m to enable comparison with other remote sensing instruments. At the latter wavelength, AOD's retrieved from lidar measurements range between 0.08 and 0.14. An agreement better than 20% is obtained between AOD's derived from lidar and sunphotometer measurements made at the same time and place over the ocean near the coast. However, large differences are observed with the AOD estimated from Meteosat imagery in the same area. These differences are thought to be caused by large uncertainties associated with the Meteosat sensitivity for small AOD's or by the presence of thin scattered clouds. Lidar-derived particulate extinction profiles and scattering coefficient profiles measured by a nephelometer mounted on the ARAT, in a different part of the plume, were found in good agreement, which could be an indication that absorption by pollution aerosols is small and/or that soot is present in small amounts in the European pollution plume. Lidar measurements have also been used to differentiate the contribution of different aerosol layers to the total AOD. It is shown that

  5. Estimating Roof Solar Energy Potential in the Downtown Area Using a GPU-Accelerated Solar Radiation Model and Airborne LiDAR Data

    Directory of Open Access Journals (Sweden)

    Yan Huang

    2015-12-01

    Full Text Available Solar energy, as a clean and renewable resource is becoming increasingly important in the global context of climate change and energy crisis. Utilization of solar energy in urban areas is of great importance in urban energy planning, environmental conservation, and sustainable development. However, available spaces for solar panel installation in cities are quite limited except for building roofs. Furthermore, complex urban 3D morphology greatly affects sunlit patterns on building roofs, especially in downtown areas, which makes the determination of roof solar energy potential a challenging task. The object of this study is to estimate the solar radiation on building roofs in an urban area in Shanghai, China, and select suitable spaces for installing solar panels that can effectively utilize solar energy. A Graphic Processing Unit (GPU-based solar radiation model named SHORTWAVE-C simulating direct and non-direct solar radiation intensity was developed by adding the capability of considering cloud influence into the previous SHORTWAVE model. Airborne Light Detection and Ranging (LiDAR data was used as the input of the SHORTWAVE-C model and to investigate the morphological characteristics of the study area. The results show that the SHORTWAVE-C model can accurately estimate the solar radiation intensity in a complex urban environment under cloudy conditions, and the GPU acceleration method can reduce the computation time by up to 46%. Two sites with different building densities and rooftop structures were selected to illustrate the influence of urban morphology on the solar radiation and solar illumination duration. Based on the findings, an object-based method was implemented to identify suitable places for rooftop solar panel installation that can fully utilize the solar energy potential. Our study provides useful strategic guidelines for the selection and assessment of roof solar energy potential for urban energy planning.

  6. Accuracy assessment of TanDEM-X IDEM using airborne LiDAR on the area of Poland

    Directory of Open Access Journals (Sweden)

    Woroszkiewicz Małgorzata

    2017-06-01

    Full Text Available The TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM provided by the German Aerospace Center (DLR under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE, was 0.77 m.

  7. Comparison of Aerosol Classification Results from Airborne High Spectral Resolution Lidar (HSRL) Measurements and the Calipso Vertical Feature Mask

    Science.gov (United States)

    Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Rogers, R. R.; Obland, M. D.; Butler, C. F.; Cook, A. L.; Harper, D. B.; Froyd, K. D.; hide

    2012-01-01

    Knowledge of the vertical profile, composition, concentration, and size of aerosols is required for assessing the direct impact of aerosols on radiation, the indirect effects of aerosols on clouds and precipitation, and attributing these effects to natural and anthropogenic aerosols. Because anthropogenic aerosols are predominantly submicrometer, fine mode fraction (FMF) retrievals from satellite have been used as a tool for deriving anthropogenic aerosols. Although column and profile satellite retrievals of FMF have been performed over the ocean, such retrievals have not yet been been done over land. Consequently, uncertainty in satellite estimates of the anthropogenic component of the aerosol direct radiative forcing is greatest over land, due in large part to uncertainties in the FMF. Satellite measurements have been used to detect and evaluate aerosol impacts on clouds; however, such efforts have been hampered by the difficulty in retrieving vertically-resolved cloud condensation nuclei (CCN) concentration, which is the most direct parameter linking aerosol and clouds. Recent studies have shown correlations between average satellite derived column aerosol optical thickness (AOT) and in situ measured CCN. However, these same studies, as well as others that use detailed airborne in situ measurements have noted that vertical variability of the aerosol distribution, impacts of relative humidity, and the presence of coarse mode aerosols such as dust introduce large uncertainties in such relations.

  8. 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...

  9. 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...

  10. 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...

  11. Estimation of diameter and height of individual trees for Pinus sylvestris L. based on the individualising of crowns using airborne LiDAR and the National Forestry Inventory data

    Energy Technology Data Exchange (ETDEWEB)

    Valbuena-Rabadán, M.A.; Santamaría-Peña, J.; Sanz-Adán, F.

    2016-07-01

    Aim of the study: The objective of this study is to test the validity of the DBH and total height allometric models fitted to the crown polygon data obtained by the application of a crown delineation and individualisation algorithm which uses the geometrical relationships between the points in the original LiDAR point clouds in the Pinus sylvestris L. stands. Area of study: The study area is located in the province of Álava in the Autonomous Community of the Basque Country. Material and Methods: The crowns are delineated using data from airborne LiDAR point clouds obtained in the 2008 overflight of the Basque Autonomous Community. The DBH and total height data for field trees are obtained from the plots in the 4th National forest inventory. Main Results: For the adjusted total height and DBH models coefficients of determination of 0.87 and 0.74 respectively were obtained. The root mean squared errors were 10.67% and 18.97% respectively. The distributions of obtained DBH and total height fitted values and the distributions of the DBH and total height of the field trees are very similar except for the DBH below 15 cm. Research highlights: For stands of Pinus sylvestris L. in Álava, the geometrical relationships between the points that correspond to laser signal echoes obtained with airborne LiDAR sensors can be used directly to delineate approximations of the horizontal projections of the crowns of the trees. Although the procedure set out here was developed for stands of P. sylvestris L. in Álava, it can be applied to other conifers in regular stands by adjusting the working parameters of the function which delineates the crowns on the basis of the point cloud. (Author)

  12. 3D Spatial and Spectral Fusion of Terrestrial Hyperspectral Imagery and Lidar for Hyperspectral Image Shadow Restoration Applied to a Geologic Outcrop

    Science.gov (United States)

    Hartzell, P. J.; Glennie, C. L.; Hauser, D. L.; Okyay, U.; Khan, S.; Finnegan, D. C.

    2016-12-01

    Recent advances in remote sensing technology have expanded the acquisition and fusion of active lidar and passive hyperspectral imagery (HSI) from an exclusively airborne technique to terrestrial modalities. This enables high resolution 3D spatial and spectral quantification of vertical geologic structures for applications such as virtual 3D rock outcrop models for hydrocarbon reservoir analog analysis and mineral quantification in open pit mining environments. In contrast to airborne observation geometry, the vertical surfaces observed by horizontal-viewing terrestrial HSI sensors are prone to extensive topography-induced solar shadowing, which leads to reduced pixel classification accuracy or outright removal of shadowed pixels from analysis tasks. Using a precisely calibrated and registered offset cylindrical linear array camera model, we demonstrate the use of 3D lidar data for sub-pixel HSI shadow detection and the restoration of the shadowed pixel spectra via empirical methods that utilize illuminated and shadowed pixels of similar material composition. We further introduce a new HSI shadow restoration technique that leverages collocated backscattered lidar intensity, which is resistant to solar conditions, obtained by projecting the 3D lidar points through the HSI camera model into HSI pixel space. Using ratios derived from the overlapping lidar laser and HSI wavelengths, restored shadow pixel spectra are approximated using a simple scale factor. Simulations of multiple lidar wavelengths, i.e., multi-spectral lidar, indicate the potential for robust HSI spectral restoration that is independent of the complexity and costs associated with rigorous radiometric transfer models, which have yet to be developed for horizontal-viewing terrestrial HSI sensors. The spectral restoration performance is quantified through HSI pixel classification consistency between full sun and partial sun exposures of a single geologic outcrop.

  13. 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

  14. Forest Canopy LAI and Vertical FAVD Profile Inversion from Airborne Full-Waveform LiDAR Data Based on a Radiative Transfer Model

    Directory of Open Access Journals (Sweden)

    Han Ma

    2015-02-01

    Full Text Available Forest canopy leaf area index (LAI is a critical variable for the modeling of climates and ecosystems over both regional and global scales. This paper proposes a physically based method to retrieve LAI and foliage area volume density (FAVD profile directly from full-waveform Light Detection And Ranging (LiDAR data using a radiative transfer (RT model. First, a physical interaction model between LiDAR and a forest scene was built on the basis of radiative transfer theories. Next, FAVD profile of each laser shot of full-waveform LiDAR was inverted using the physical model. In addition, the missing LiDAR data, caused by high-density forest and LiDAR system limitations, were filled in based on the inverted FAVD and the ancillary CHM data. Finally, LAI of the study area was retrieved from the inverted FAVD at a 10-m resolution. CHM derived LAI based on the Beer-Lambert law was compared with the LAI derived from full-waveform data. Also, we compared the results with the field measured LAI. The values of correlation coefficient r and RMSE of the estimated LAI were 0.73 and 0.67, respectively. The results indicate that full-waveform LiDAR data is a reliable data source and represent a useful tool for retrieving forest LAI.

  15. SAFARI 2000 MODIS Airborne Simulator Data, Southern Africa, Dry Season 2000

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset contains the Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) multispectral data collected during the SAFARI 2000 project....

  16. AIRBORNE LIGHT DETECTION AND RANGING (LIDAR DERIVED DEFORMATION FROM THE MW 6.0 24 AUGUST, 2014 SOUTH NAPA EARTHQUAKE ESTIMATED BY TWO AND THREE DIMENSIONAL POINT CLOUD CHANGE DETECTION TECHNIQUES

    Directory of Open Access Journals (Sweden)

    A. W. Lyda

    2016-06-01

    Full Text Available Remote sensing via LiDAR (Light Detection And Ranging has proven extremely useful in both Earth science and hazard related studies. Surveys taken before and after an earthquake for example, can provide decimeter-level, 3D near-field estimates of land deformation that offer better spatial coverage of the near field rupture zone than other geodetic methods (e.g., InSAR, GNSS, or alignment array. In this study, we compare and contrast estimates of deformation obtained from different pre and post-event airborne laser scanning (ALS data sets of the 2014 South Napa Earthquake using two change detection algorithms, Iterative Control Point (ICP and Particle Image Velocimetry (PIV. The ICP algorithm is a closest point based registration algorithm that can iteratively acquire three dimensional deformations from airborne LiDAR data sets. By employing a newly proposed partition scheme, “moving window,” to handle the large spatial scale point cloud over the earthquake rupture area, the ICP process applies a rigid registration of data sets within an overlapped window to enhance the change detection results of the local, spatially varying surface deformation near-fault. The other algorithm, PIV, is a well-established, two dimensional image co-registration and correlation technique developed in fluid mechanics research and later applied to geotechnical studies. Adapted here for an earthquake with little vertical movement, the 3D point cloud is interpolated into a 2D DTM image and horizontal deformation is determined by assessing the cross-correlation of interrogation areas within the images to find the most likely deformation between two areas. Both the PIV process and the ICP algorithm are further benefited by a presented, novel use of urban geodetic markers. Analogous to the persistent scatterer technique employed with differential radar observations, this new LiDAR application exploits a classified point cloud dataset to assist the change detection

  17. Bridging gaps: On the performance of airborne LiDAR to model wood mouse-habitat structure relationships in pine forests.

    Science.gov (United States)

    Jaime-González, Carlos; Acebes, Pablo; Mateos, Ana; Mezquida, Eduardo T

    2017-01-01

    LiDAR technology has firmly contributed to strengthen the knowledge of habitat structure-wildlife relationships, though there is an evident bias towards flying vertebrates. To bridge this gap, we investigated and compared the performance of LiDAR and field data to model habitat preferences of wood mouse (Apodemus sylvaticus) in a Mediterranean high mountain pine forest (Pinus sylvestris). We recorded nine field and 13 LiDAR variables that were summarized by means of Principal Component Analyses (PCA). We then analyzed wood mouse's habitat preferences using three different models based on: (i) field PCs predictors, (ii) LiDAR PCs predictors; and (iii) both set of predictors in a combined model, including a variance partitioning analysis. Elevation was also included as a predictor in the three models. Our results indicate that LiDAR derived variables were better predictors than field-based variables. The model combining both data sets slightly improved the predictive power of the model. Field derived variables indicated that wood mouse was positively influenced by the gradient of increasing shrub cover and negatively affected by elevation. Regarding LiDAR data, two LiDAR PCs, i.e. gradients in canopy openness and complexity in forest vertical structure positively influenced wood mouse, although elevation interacted negatively with the complexity in vertical structure, indicating wood mouse's preferences for plots with lower elevations but with complex forest vertical structure. The combined model was similar to the LiDAR-based model and included the gradient of shrub cover measured in the field. Variance partitioning showed that LiDAR-based variables, together with elevation, were the most important predictors and that part of the variation explained by shrub cover was shared. LiDAR derived variables were good surrogates of environmental characteristics explaining habitat preferences by the wood mouse. Our LiDAR metrics represented structural features of the forest

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. Airborne LiDAR analysis and geochronology of faulted glacial moraines in the Tahoe-Sierra frontal fault zone reveal substantial seismic hazards in the Lake Tahoe region, California-Nevada USA

    Science.gov (United States)

    Howle, James F.; Bawden, Gerald W.; Schweickert, Richard A.; Finkel, Robert C.; Hunter, Lewis E.; Rose, Ronn S.; von Twistern, Brent

    2012-01-01

    We integrated high-resolution bare-earth airborne light detection and ranging (LiDAR) imagery with field observations and modern geochronology to characterize the Tahoe-Sierra frontal fault zone, which forms the neotectonic boundary between the Sierra Nevada and the Basin and Range Province west of Lake Tahoe. The LiDAR imagery clearly delineates active normal faults that have displaced late Pleistocene glacial moraines and Holocene alluvium along 30 km of linear, right-stepping range front of the Tahoe-Sierra frontal fault zone. Herein, we illustrate and describe the tectonic geomorphology of faulted lateral moraines. We have developed new, three-dimensional modeling techniques that utilize the high-resolution LiDAR data to determine tectonic displacements of moraine crests and alluvium. The statistically robust displacement models combined with new ages of the displaced Tioga (20.8 ± 1.4 ka) and Tahoe (69.2 ± 4.8 ka; 73.2 ± 8.7 ka) moraines are used to estimate the minimum vertical separation rate at 17 sites along the Tahoe-Sierra frontal fault zone. Near the northern end of the study area, the minimum vertical separation rate is 1.5 ± 0.4 mm/yr, which represents a two- to threefold increase in estimates of seismic moment for the Lake Tahoe basin. From this study, we conclude that potential earthquake moment magnitudes (Mw) range from 6.3 ± 0.25 to 6.9 ± 0.25. A close spatial association of landslides and active faults suggests that landslides have been seismically triggered. Our study underscores that the Tahoe-Sierra frontal fault zone poses substantial seismic and landslide hazards.

  4. Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Jitendra [ORNL; HargroveJr., William Walter [United States Department of Agriculture (USDA), United States Forest Service (USFS); Norman, Steven P [United States Department of Agriculture (USDA), United States Forest Service (USFS); Hoffman, Forrest M [ORNL; Newcomb, Doug [U.S. Fish and Wildlife Service

    2015-01-01

    Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.

  5. 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

  6. 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.

  7. 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...

  8. 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...

  9. Airborne multispectral detection of regrowth cotton fields

    Science.gov (United States)

    Regrowth of cotton, Gossypium hirsutum L., can provide boll weevils, Anthonomus grandis Boheman, with an extended opportunity to feed and reproduce beyond the production season. Effective methods for timely areawide detection of these potential host plants are critically needed to achieve eradicati...

  10. Assessing the Transferability of Statistical Predictive Models for Leaf Area Index Between Two Airborne Discrete Return LiDAR Sensor Designs Within Multiple Intensely Managed Loblolly Pine Forest Locations in the South-Eastern USA

    Science.gov (United States)

    Sumnall, Matthew; Peduzzi, Alicia; Fox, Thomas R.; Wynne, Randolph H.; Thomas, Valerie A.; Cook, Bruce

    2016-01-01

    Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were

  11. 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.

  12. 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...

  13. 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.

  14. 2012 NOAA American Samoa Lidar: Islands of Tutuila, Aunu'u, Ofu, Olosega, Ta'u and Rose Atoll

    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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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....

  20. 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....

  1. 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....

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 2007 FEMA New Jersey Flood Mitigation Lidar: Gloucester County

    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...

  1. 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...

  2. 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...

  3. High Power, Thermally Optimized Blue Laser for Lidar, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — To enable widespread and rapid airborne bathymetric lidar to adequate depths in many ocean regions a low-cost, rugged, and high energy pulsed laser source must be...

  4. High Power, Thermally Optimized Blue Laser for Lidar, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — To enable widespread and rapid airborne bathymetric lidar to adequate depths in many ocean regions a low-cost, rugged, and high energy pulsed laser source must be...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 2006 FEMA New Jersey Flood Mitigation Lidar: Middlesex County

    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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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....

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. Predictive Modeling of Black Spruce (Picea mariana (Mill. B.S.P. Wood Density Using Stand Structure Variables Derived from Airborne LiDAR Data in Boreal Forests of Ontario

    Directory of Open Access Journals (Sweden)

    Bharat Pokharel

    2016-12-01

    Full Text Available Our objective was to model the average wood density in black spruce trees in representative stands across a boreal forest landscape based on relationships with predictor variables extracted from airborne light detection and ranging (LiDAR point cloud data. Increment core samples were collected from dominant or co-dominant black spruce trees in a network of 400 m2 plots distributed among forest stands representing the full range of species composition and stand development across a 1,231,707 ha forest management unit in northeastern Ontario, Canada. Wood quality data were generated from optical microscopy, image analysis, X-ray densitometry and diffractometry as employed in SilviScan™. Each increment core was associated with a set of field measurements at the plot level as well as a suite of LiDAR-derived variables calculated on a 20 × 20 m raster from a wall-to-wall coverage at a resolution of ~1 point m−2. We used a multiple linear regression approach to identify important predictor variables and describe relationships between stand structure and wood density for average black spruce trees in the stands we observed. A hierarchical classification model was then fitted using random forests to make spatial predictions of mean wood density for average trees in black spruce stands. The model explained 39 percent of the variance in the response variable, with an estimated root mean square error of 38.8 (kg·m−3. Among the predictor variables, P20 (second decile LiDAR height in m and quadratic mean diameter were most important. Other predictors describing canopy depth and cover were of secondary importance and differed according to the modeling approach. LiDAR-derived variables appear to capture differences in stand structure that reflect different constraints on growth rates, determining the proportion of thin-walled earlywood cells in black spruce stems, and ultimately influencing the pattern of variation in important wood quality attributes

  17. 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...

  18. Lidar Remote Sensing for Industry and Environment Monitoring

    Science.gov (United States)

    Singh, Upendra N. (Editor); Itabe, Toshikazu (Editor); Sugimoto, Nobuo (Editor)

    2000-01-01

    Contents include the following: 1. Keynote paper: Overview of lidar technology for industrial and environmental monitoring in Japan. 2. lidar technology I: NASA's future active remote sensing mission for earth science. Geometrical detector consideration s in laser sensing application (invited paper). 3. Lidar technology II: High-power femtosecond light strings as novel atmospheric probes (invited paper). Design of a compact high-sensitivity aerosol profiling lidar. 4. Lasers for lidars: High-energy 2 microns laser for multiple lidar applications. New submount requirement of conductively cooled laser diodes for lidar applications. 5. Tropospheric aerosols and clouds I: Lidar monitoring of clouds and aerosols at the facility for atmospheric remote sensing (invited paper). Measurement of asian dust by using multiwavelength lidar. Global monitoring of clouds and aerosols using a network of micropulse lidar systems. 6. Troposphere aerosols and clouds II: Scanning lidar measurements of marine aerosol fields at a coastal site in Hawaii. 7. Tropospheric aerosols and clouds III: Formation of ice cloud from asian dust particles in the upper troposphere. Atmospheric boundary layer observation by ground-based lidar at KMITL, Thailand (13 deg N, 100 deg. E). 8. Boundary layer, urban pollution: Studies of the spatial correlation between urban aerosols and local traffic congestion using a slant angle scanning on the research vessel Mirai. 9. Middle atmosphere: Lidar-observed arctic PSC's over Svalbard (invited paper). Sodium temperature lidar measurements of the mesopause region over Syowa Station. 10. Differential absorption lidar (dIAL) and DOAS: Airborne UV DIAL measurements of ozone and aerosols (invited paper). Measurement of water vapor, surface ozone, and ethylene using differential absorption lidar. 12. Space lidar I: Lightweight lidar telescopes for space applications (invited paper). Coherent lidar development for Doppler wind measurement from the International Space

  19. 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

  20. Helios: a Multi-Purpose LIDAR Simulation Framework for Research, Planning and Training of Laser Scanning Operations with Airborne, Ground-Based Mobile and Stationary Platforms

    Science.gov (United States)

    Bechtold, S.; Höfle, B.

    2016-06-01

    In many technical domains of modern society, there is a growing demand for fast, precise and automatic acquisition of digital 3D models of a wide variety of physical objects and environments. Laser scanning is a popular and widely used technology to cover this demand, but it is also expensive and complex to use to its full potential. However, there might exist scenarios where the operation of a real laser scanner could be replaced by a computer simulation, in order to save time and costs. This includes scenarios like teaching and training of laser scanning, development of new scanner hardware and scanning methods, or generation of artificial scan data sets to support the development of point cloud processing and analysis algorithms. To test the feasibility of this idea, we have developed a highly flexible laser scanning simulation framework named Heidelberg LiDAR Operations Simulator (HELIOS). HELIOS is implemented as a Java library and split up into a core component and multiple extension modules. Extensible Markup Language (XML) is used to define scanner, platform and scene models and to configure the behaviour of modules. Modules were developed and implemented for (1) loading of simulation assets and configuration (i.e. 3D scene models, scanner definitions, survey descriptions etc.), (2) playback of XML survey descriptions, (3) TLS survey planning (i.e. automatic computation of recommended scanning positions) and (4) interactive real-time 3D visualization of simulated surveys. As a proof of concept, we show the results of two experiments: First, a survey planning test in a scene that was specifically created to evaluate the quality of the survey planning algorithm. Second, a simulated TLS scan of a crop field in a precision farming scenario. The results show that HELIOS fulfills its design goals.

  1. Atmospheric CO2 Column Measurements with an Airborne Intensity-Modulated Continuous-Wave 1.57-micron Fiber Laser Lidar

    Science.gov (United States)

    Dobler, Jeremy T.; Harrison, F. Wallace; Browell, Edward V.; Lin, Bing; McGregor, Doug; Kooi, Susan; Choi, Yonghoon; Ismail, Syed

    2013-01-01

    The 2007 National Research Council (NRC) Decadal Survey on Earth Science and Applications from Space recommended Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) as a mid-term, Tier II, NASA space mission. ITT Exelis, formerly ITT Corp., and NASA Langley Research Center have been working together since 2004 to develop and demonstrate a prototype Laser Absorption Spectrometer for making high-precision, column CO2 mixing ratio measurements needed for the ASCENDS mission. This instrument, called the Multifunctional Fiber Laser Lidar (MFLL), operates in an intensity-modulated, continuous-wave mode in the 1.57- micron CO2 absorption band. Flight experiments have been conducted with the MFLL on a Lear-25, UC-12, and DC-8 aircraft over a variety of different surfaces and under a wide range of atmospheric conditions. Very high-precision CO2 column measurements resulting from high signal-to-noise (great than 1300) column optical depth measurements for a 10-s (approximately 1 km) averaging interval have been achieved. In situ measurements of atmospheric CO2 profiles were used to derive the expected CO2 column values, and when compared to the MFLL measurements over desert and vegetated surfaces, the MFLL measurements were found to agree with the in situ-derived CO2 columns to within an average of 0.17% or approximately 0.65 ppmv with a standard deviation of 0.44% or approximately 1.7 ppmv. Initial results demonstrating ranging capability using a swept modulation technique are also presented.

  2. First airborne water vapor lidar measurements in the tropical upper troposphere and mid-latitudes lower stratosphere: accuracy evaluation and intercomparisons with other instruments

    Directory of Open Access Journals (Sweden)

    C. Schiller

    2008-09-01

    Full Text Available In the tropics, deep convection is the major source of uncertainty in water vapor transport to the upper troposphere and into the stratosphere. Although accurate measurements in this region would be of first order importance to better understand the processes that govern stratospheric water vapor concentrations and trends in the context of a changing climate, they are sparse because of instrumental shortcomings and observational challenges. Therefore, the Falcon research aircraft of the Deutsches Zentrum für Luft- und Raumfahrt (DLR flew a zenith-viewing water vapor differential absorption lidar (DIAL during the Tropical Convection, Cirrus and Nitrogen Oxides Experiment (TROCCINOX in 2004 and 2005 in Brazil. The measurements were performed alternatively on three water vapor absorption lines of different strength around 940 nm. These are the first aircraft DIAL measurements in the tropical upper troposphere and in the mid-latitudes lower stratosphere. Sensitivity analyses reveal an accuracy of 5% between altitudes of 8 and 16 km. This is confirmed by intercomparisons with the Fast In-situ Stratospheric Hygrometer (FISH and the Fluorescent Advanced Stratospheric Hygrometer (FLASH onboard the Russian M-55 Geophysica research aircraft during five coordinated flights. The average relative differences between FISH and DIAL amount to −3%±8% and between FLASH and DIAL to −8%±14%, negative meaning DIAL is more humid. The average distance between the probed air masses was 129 km. The DIAL is found to have no altitude- or latitude-dependent bias. A comparison with the balloon ascent of a laser absorption spectrometer gives an average difference of 0%±19% at a distance of 75 km. Six tropical DIAL under-flights of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS on board ENVISAT reveal a mean difference of −8%±49% at an average distance of 315 km. While the comparison with MIPAS is somewhat less significant due to poorer

  3. Responses of Tree Growths to Tree Size, Competition, and Topographic Conditions in Sierra Nevada Forests Using Bi-temporal Airborne LiDAR Data

    Science.gov (United States)

    Ma, Q.; Su, Y.; Tao, S.; Guo, Q.

    2016-12-01

    Trees in the Sierra Nevada (SN) forests are experiencing rapid changes due to human disturbances and climatic changes. An improved monitoring of tree growth and understanding of how tree growth responses to different impact factors, such as tree competition, forest density, topographic and hydrologic conditions, are urgently needed in tree growth modeling. Traditional tree growth modeling mainly relied on field survey, which was highly time-consuming and labor-intensive. Airborne Light detection and ranging System (ALS) is increasingly used in forest survey, due to its high efficiency and accuracy in three-dimensional tree structure delineation and terrain characterization. This study successfully detected individual tree growth in height (ΔH), crown area (ΔA), and crown volume (ΔV) over a five-year period (2007-2012) using bi-temporal ALS data in two conifer forest areas in SN. We further analyzed their responses to original tree size, competition indices, forest structure indices, and topographic environmental parameters at individual tree and forest stand scales. Our results indicated ΔH was strongly sensitive to topographic wetness index; whereas ΔA and ΔV were highly responsive to forest density and original tree sizes. These ALS based findings in ΔH were consistent with field measurements. Our study demonstrated the promising potential of using bi-temporal ALS data in forest growth measurements and analysis. A more comprehensive study over a longer temporal period and a wider range of forest stands would give better insights into tree growth in the SN, and provide useful guides for forest growth monitoring, modeling, and management.

  4. 2011 - 2012 New York State Department of Environmental Conservation (NYSDEC) Lidar: Coastal New York (Long Island and along the Hudson River)

    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...

  5. Multispectral imaging for biometrics

    Science.gov (United States)

    Rowe, Robert K.; Corcoran, Stephen P.; Nixon, Kristin A.; Ostrom, Robert E.

    2005-03-01

    Automated identification systems based on fingerprint images are subject to two significant types of error: an incorrect decision about the identity of a person due to a poor quality fingerprint image and incorrectly accepting a fingerprint image generated from an artificial sample or altered finger. This paper discusses the use of multispectral sensing as a means to collect additional information about a finger that significantly augments the information collected using a conventional fingerprint imager based on total internal reflectance. In the context of this paper, "multispectral sensing" is used broadly to denote a collection of images taken under different polarization conditions and illumination configurations, as well as using multiple wavelengths. Background information is provided on conventional fingerprint imaging. A multispectral imager for fingerprint imaging is then described and a means to combine the two imaging systems into a single unit is discussed. Results from an early-stage prototype of such a system are shown.

  6. Lidar to lidar calibration of Ground-based Lidar

    DEFF Research Database (Denmark)

    Fernandez Garcia, Sergio; Courtney, Michael

    This report presents the result of the lidar to lidar calibration performed for ground-based lidar. Calibration is here understood as the establishment of a relation between the reference lidar wind speed measurements with measurement uncertainties provided by measurement standard and corresponding...... lidar wind speed indications with associated measurement uncertainties. The lidar calibration concerns the 10 minute mean wind speed measurements. The comparison of the lidar measurements of the wind direction with that from the reference lidar measurements are given for information only....

  7. Lidar-based mapping of flood control levees in south Louisiana

    Science.gov (United States)

    Thatcher, Cindy A.; Lim, Samsung; Palaseanu-Lovejoy, Monica; Danielson, Jeffrey J.; Kimbrow, Dustin R.

    2016-01-01

    Flood protection in south Louisiana is largely dependent on earthen levees, and in the aftermath of Hurricane Katrina the state’s levee system has received intense scrutiny. Accurate elevation data along the levees are critical to local levee district managers responsible for monitoring and maintaining the extensive system of non-federal levees in coastal Louisiana. In 2012, high resolution airborne lidar data were acquired over levees in Lafourche Parish, Louisiana, and a mobile terrestrial lidar survey was conducted for selected levee segments using a terrestrial lidar scanner mounted on a truck. The mobile terrestrial lidar data were collected to test the feasibility of using this relatively new technology to map flood control levees and to compare the accuracy of the terrestrial and airborne lidar. Metrics assessing levee geometry derived from the two lidar surveys are also presented as an efficient, comprehensive method to quantify levee height and stability. The vertical root mean square error values of the terrestrial lidar and airborne lidar digital-derived digital terrain models were 0.038 m and 0.055 m, respectively. The comparison of levee metrics derived from the airborne and terrestrial lidar-based digital terrain models showed that both types of lidar yielded similar results, indicating that either or both surveying techniques could be used to monitor geomorphic change over time. Because airborne lidar is costly, many parts of the USA and other countries have never been mapped with airborne lidar, and repeat surveys are often not available for change detection studies. Terrestrial lidar provides a practical option for conducting repeat surveys of levees and other terrain features that cover a relatively small area, such as eroding cliffs or stream banks, and dunes.

  8. Final Technical Report for Interagency Agreement No. DE-SC0005453 “Characterizing Aerosol Distributions, Types, and Optical and Microphysical Properties using the NASA Airborne High Spectral Resolution Lidar (HSRL) and the Research Scanning Polarimeter (RSP)”

    Energy Technology Data Exchange (ETDEWEB)

    Hostetler, Chris [NASA Langley Research Center, Hampton, VA (United States); Ferrare, Richard [NASA Langley Research Center, Hampton, VA (United States)

    2015-01-13

    Measurements of the vertical profile of atmospheric aerosols and aerosol optical and microphysical characteristics are required to: 1) determine aerosol direct and indirect radiative forcing, 2) compute radiative flux and heating rate profiles, 3) assess model simulations of aerosol distributions and types, and 4) establish the ability of surface and space-based remote sensors to measure the indirect effect. Consequently the ASR program calls for a combination of remote sensing and in situ measurements to determine aerosol properties and aerosol influences on clouds and radiation. As part of our previous DOE ASP project, we deployed the NASA Langley airborne High Spectral Resolution Lidar (HSRL) on the NASA B200 King Air aircraft during major field experiments in 2006 (MILAGRO and MaxTEX), 2007 (CHAPS), 2009 (RACORO), and 2010 (CalNex and CARES). The HSRL provided measurements of aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm). These measurements were typically made in close temporal and spatial coincidence with measurements made from DOE-funded and other participating aircraft and ground sites. On the RACORO, CARES, and CalNEX missions, we also deployed the NASA Goddard Institute for Space Studies (GISS) Research Scanning Polarimeter (RSP). RSP provided intensity and degree of linear polarization over a broad spectral and angular range enabling column-average retrievals of aerosol optical and microphysical properties. Under this project, we analyzed observations and model results from RACORO, CARES, and CalNex and accomplished the following objectives. 1. Identified aerosol types, characterize the vertical distribution of the aerosol types, and partition aerosol optical depth by type, for CARES and CalNex using HSRL data as we have done for previous missions. 2. Investigated aerosol microphysical and macrophysical properties using the RSP. 3. Used the aerosol backscatter and extinction profiles measured by the HSRL

  9. 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.

  10. Statistical properties of mean stand biomass estimators in a LIDAR-based double sampling forest survey design.

    Science.gov (United States)

    H.E. Anderson; J. Breidenbach

    2007-01-01

    Airborne laser scanning (LIDAR) can be a valuable tool in double-sampling forest survey designs. LIDAR-derived forest structure metrics are often highly correlated with important forest inventory variables, such as mean stand biomass, and LIDAR-based synthetic regression estimators have the potential to be highly efficient compared to single-stage estimators, which...

  11. Lidar to lidar calibration phase 2

    DEFF Research Database (Denmark)

    Yordanova, Ginka; Courtney, Michael

    This report presents the results from phase 2 of a lidar to lidar (L2L) calibration procedure. Phase two of the project included two measurement campaigns conducted at given sites. The purpose was to find out if the lidar-to-lidar calibration procedure can be conducted with similar results...

  12. Multispectral Image Feature Points

    Directory of Open Access Journals (Sweden)

    Cristhian Aguilera

    2012-09-01

    Full Text Available This paper presents a novel feature point descriptor for the multispectral image case: Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  13. Multispectral analytical image fusion

    International Nuclear Information System (INIS)

    Stubbings, T.C.

    2000-04-01

    With new and advanced analytical imaging methods emerging, the limits of physical analysis capabilities and furthermore of data acquisition quantities are constantly pushed, claiming high demands to the field of scientific data processing and visualisation. Physical analysis methods like Secondary Ion Mass Spectrometry (SIMS) or Auger Electron Spectroscopy (AES) and others are capable of delivering high-resolution multispectral two-dimensional and three-dimensional image data; usually this multispectral data is available in form of n separate image files with each showing one element or other singular aspect of the sample. There is high need for digital image processing methods enabling the analytical scientist, confronted with such amounts of data routinely, to get rapid insight into the composition of the sample examined, to filter the relevant data and to integrate the information of numerous separate multispectral images to get the complete picture. Sophisticated image processing methods like classification and fusion provide possible solution approaches to this challenge. Classification is a treatment by multivariate statistical means in order to extract analytical information. Image fusion on the other hand denotes a process where images obtained from various sensors or at different moments of time are combined together to provide a more complete picture of a scene or object under investigation. Both techniques are important for the task of information extraction and integration and often one technique depends on the other. Therefore overall aim of this thesis is to evaluate the possibilities of both techniques regarding the task of analytical image processing and to find solutions for the integration and condensation of multispectral analytical image data in order to facilitate the interpretation of the enormous amounts of data routinely acquired by modern physical analysis instruments. (author)

  14. 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.

  15. 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.

  16. Quantifying TOLNet Ozone Lidar Accuracy During the 2014 DISCOVER-AQ and FRAPPE Campaigns

    Science.gov (United States)

    Wang, Lihua; Newchurch, Michael J.; Alvarez, Raul J., II; Berkoff, Timothy A.; Brown, Steven S.; Carrion, William; De Young, Russell J.; Johnson, Bryan J.; Ganoe, Rene; Gronoff, Guillaume; hide

    2017-01-01

    The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry Experiment (FRAPPA) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than +/-15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than +/-5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts.

  17. Lidar to lidar calibration phase 1

    DEFF Research Database (Denmark)

    Yordanova, Ginka; Courtney, Michael

    This report presents a feasibility study of a lidar to lidar (L2L) calibration procedure. Phase one of the project was conducted at Høvsøre, Denmark. Two windcubes were placed next to the 116m met mast and different methods were applied to obtain the sensing height error of the lidars. The purpose...... is to find the most consistent method and use it in a potential lidar to lidar calibration procedure....

  18. Airborne Lidar Bathymetry: The SHOALS System

    Science.gov (United States)

    2016-05-09

    with the depths. The application of this kind of data includes engineering evaluation of coastal structures, shoreline surveys, beach and dune surveys...similar manner, SHOALS data is a monitoring tool for beach fill projects. SHOALS data can extend from the dune , through the surf zone, and out to depth...requirements, above and below-water jetty conditions, toe scour at the jetties, and nearshore conditions. Table 3.2 Profile Spacing Volume

  19. Automated oil spill detection with multispectral imagery

    Science.gov (United States)

    Bradford, Brian N.; Sanchez-Reyes, Pedro J.

    2011-06-01

    In this publication we present an automated detection method for ocean surface oil, like that which existed in the Gulf of Mexico as a result of the April 20, 2010 Deepwater Horizon drilling rig explosion. Regions of surface oil in airborne imagery are isolated using red, green, and blue bands from multispectral data sets. The oil shape isolation procedure involves a series of image processing functions to draw out the visual phenomenological features of the surface oil. These functions include selective color band combinations, contrast enhancement and histogram warping. An image segmentation process then separates out contiguous regions of oil to provide a raster mask to an analyst. We automate the detection algorithm to allow large volumes of data to be processed in a short time period, which can provide timely oil coverage statistics to response crews. Geo-referenced and mosaicked data sets enable the largest identified oil regions to be mapped to exact geographic coordinates. In our simulation, multispectral imagery came from multiple sources including first-hand data collected from the Gulf. Results of the simulation show the oil spill coverage area as a raster mask, along with histogram statistics of the oil pixels. A rough square footage estimate of the coverage is reported if the image ground sample distance is available.

  20. 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.

  1. A multispectral scanner survey of the Idaho National Engineering Laboratory and the Hanford Reservation

    International Nuclear Information System (INIS)

    Brewster, S.B. Jr.; Howard, M.E.; Shines, J.E.

    1994-09-01

    An airborne multispectral scanner survey of selected sites on the Idaho National Engineering Laboratory and the Hanford Reservation was performed in mid-November 1993. Aerial multispectral scanner and photography data were acquired coincidentally with the Big O experiment at both locations. To illustrate two potential applications, the multispectral scanner data were digitally enhanced to facilitate the detection of soil disturbance and evidence of surface water transport. The main conclusion of this study was that multispectral data acquired under these conditions can be useful for soil disturbance detection. The imagery did not prove as useful, however, for direct indications of surface water transport. It was possible to infer some water transport patterns from dry water beds, but only if surface indications were present

  2. 2007 Northwest Florida Water Management District (NWFWMD) Lidar: North Jefferson County

    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 range finding, GPS...

  3. 2006 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Connecticut Coastline Survey

    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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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....

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...