Bartholomew, Jarett; Lyman, Philip; Weimer, Carl; Tandy, William
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.
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
Qi Chen; Dengsheng Lu; Michael Keller; Maiza dos-Santos; Edson Bolfe; Yunyun Feng; Changwei Wang
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...
Full Text Available The ability to better understand tropical peat ecosystems for restoration and climate change mitigation is often hampered by the lack of availability accurate and detailed data on vegetation cover and hydrologys, which is typically only derived from detailed and high-resolution imaging or field-based measurements. The aims of this study were to explore the potential advantage of airborne discrete-return lidar for mapping of forest cover in peat swamp forests. We used 2.8 pulse.m-1 lidar and the associated 1-m DTM derived from an airborne platform. The lidar dataset fully covered a 120 thousand hectare protection forest in Central Kalimantan. We extracted maximum vegetation heights in 5-m grid resolution to allow detailed mapping of the forest. We followed forest definition from FAO for forest and non-forest classification. We found that lidar was able to capture detail variation of canopy height in high-resolution, thus provide more accurate classification. A comparison with existing maps suggested that the lidar-derived vegetation map was more consistent in defining canopy structure of the vegetation, with small standard deviations of the mean height of each class.
Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.
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.
National Aeronautics and Space Administration — This data set was collected to test the concept of measuring snow depth using aerial lidar. The data set consists of color infrared orthophotography (TerrainVision®...
Nelson, Ross; Ratnaswamy, Mary; Keller, Cherry
Twenty five hundred thirty nine kilometers of airborne laser profiling and videography data were acquired over the state of Delaware during the summer of 2000. The laser ranging measurements and video from approximately one-half of that data set (1304 km) were analyzed to identify and locate forested sites that might potentially support populations of Delmarva fox squirrel (DFS, Sciurus niger cinereus). The DFS is an endangered species previously endemic to tall, dense, mature forests with open understories on the Eastern Shore of the Chesapeake Bay. The airborne LiDAR employed in this study can measure forest canopy height and canopy closure, but cannot measure or infer understory canopy conditions. Hence the LiDAR must be viewed as a tool to map potential, not actual, habitat. Fifty-three potentially suitable DFS sites were identified in the 1304 km of flight transect data. Each of the 53 sites met the following criteria according to the LiDAR and video record: (1 ) at least 120m of contiguous forest; (2) an average canopy height greater than 20m; (3) an average canopy closure of >80%; and (4) no roofs, impervious surface (e.g., asphalt, concrete), and/or open water anywhere along the 120m length of the laser segment. Thirty-two of the 53 sites were visited on the ground and measurements taken for a DFS habitat suitability model. Seventy eight percent of the sites (25 of 32) were judged by the model to be suited to supporting a DFS population. Twenty-eight of the 32 sites visited in the field were in forest cover types (hardwood, mixed wood, conifer, wetlands) according to a land cover GIS map. Of these, 23 (82%) were suited to support DFS. The remaining 4 sites were located in nonforest cover types - agricultural or residential areas. Two of the four, or 50% were suited to the DFS. All of the LiDAR flight data, 2539 km, were analyzed to
Rutzinger, Martin; Höfle, Bernhard; Vetter, Michael; Stötter, Johann; Pfeifer, Norbert
Airborne LiDAR surveys provide 3D high-resolution elevation information for area-wide applications. Due to the capability of LiDAR to penetrate vegetation cover highly accurate digital terrain models (DTMs) can be derived also for forested areas. Breaklines derived from LiDAR DTMs mark regions of slope discontinuities, describing the main characteristics of a terrain surface in an efficient manner. Breaklines are often used for DTM enhancement but also for the detection and interpretation of geomorphologically relevant landforms such as landslides, torrents, erosion scraps and tectonic faults. Because of human activities geomorphologic landforms are often disturbed and reshaped i.e. by construction of roads, skiing slopes, drainage channels and surface mining. Therefore, DTMs contain both, anthropogenic and geomorphologic discontinuities. This significantly disturbs morphometric analysis and causes problems for automatic landform mapping algorithms. In this research an automatic breakline detection method is applied in an alpine region with high relief variation containing surface discontinuities such as torrents, creeping slope failure, and landslides, which are reshaped by anthropogenic activities. Regions of high curvature are classified and vectorised in order to derive 3D breaklines. These are further filtered and classified based on object-based properties such as their size, shape and slope to separate natural i.e. geomorphologic relevant and anthropogenic structures. The classification result is compared to reference map data indicating a high reliability of the classification quality. After the removal of anthropogenic breaklines the remaining natural breaklines are used to compute line density maps using a moving window approach. These density maps point out areas of different relief energy and assist to delineate areas of geomorphologic relevance. These areas are also of most interest to identify geomorphological landforms. The methodology presented
This paper presents a new approach for mapping wetland inundation change using Landsat and LiDAR intensity data. In this approach, LiDAR data were used to derive highly accurate reference subpixel inundation percentage (SIP) maps at the 30-m resolution. The reference SIP maps were then used to est...
Kristensen, Terje; Næsset, Erik; Ohlson, Mikael; Bolstad, Paul V; Kolka, Randall
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.
Lidar remote sensing provides one of the best means for acquiring detailed information on forest structure. However, its application over large areas has been limited largely because of its expense. Nonetheless, extant data exist over many states in the U.S., funded largely by state and federal consortia and mainly for infrastructure, emergency response, flood plain and coastal mapping. These lidar data are almost always acquired in leaf-off seasons, and until recently, usually with low point count densities. Even with these limitations, they provide unprecedented wall-to-wall mappings that enable development of appropriate methodologies for large-scale deployment of lidar. In this talk we summarize our research and lessons learned in deriving forest structure over regional areas as part of NASA's Carbon Monitoring System (CMS). We focus on two areas: the entire state of Maryland and Sonoma County, California. The Maryland effort used low density, leaf-off data acquired by each county in varying epochs, while the on-going Sonoma work employs state-of-the-art, high density, wall-to-wall, leaf-on lidar data. In each area we combine these lidar coverages with high-resolution multispectral imagery from the National Agricultural Imagery Program (NAIP) and in situ plot data to produce maps of canopy height, tree cover and biomass, and compare our results against FIA plot data and national biomass maps. Our work demonstrates that large-scale mapping of forest structure at high spatial resolution is achievable but products may be complex to produce and validate over large areas. Furthermore, fundamental issues involving statistical approaches, plot types and sizes, geolocation, modeling scales, allometry, and even the definitions of "forest" and "non-forest" must be approached carefully. Ultimately, determining the "price of precision", that is, does the value of wall-to-wall forest structure data justify their expense, should consider not only carbon market applications
Hoge, F. E.; Swift, R. N.
Laser fluorosensing techniques used for the airborne measurement of chlorophyll a and other naturally occurring waterborne pigments are reviewed. Previous experiments demonstrating the utility of the airborne oceanographic lidar (AOL) for assessment of various marine parameters are briefly discussed. The configuration of the AOL during the NOAA/NASA Superflux experiments is described. The participation of the AOL in these experiments is presented and the preliminary results are discussed. The importance of multispectral receiving capability in a laser fluorosensing system for providing reproducible measurements over wide areas having spatial variations in water column transmittance properties is addressed. This capability minimizes the number of truthing points required and is usable even in shallow estuarine areas where resuspension of bottom sediment is common. Finally, problems encountered on the Superflux missions and the resulting limitations on the AOL data sets are addressed and feasible solutions to these problems are provided.
Silva, Carlos A; Klauberg, Carine; Hudak, Andrew T; Vierling, Lee A; Fennema, Scott J; Corte, Ana Paula D
Basal area (BA) is a good predictor of timber stand volume and forest growth. This study developed predictive models using field and airborne LiDAR (Light Detection and Ranging) data for estimation of basal area in Pinus taeda plantation in south Brazil. In the field, BA was collected from conventional forest inventory plots. Multiple linear regression models for predicting BA from LiDAR-derived metrics were developed and evaluated for predictive power and parsimony. The best model to predict BA from a family of six models was selected based on corrected Akaike Information Criterion (AICc) and assessed by the adjusted coefficient of determination (adj. R²) and root mean square error (RMSE). The best model revealed an adj. R²=0.93 and RMSE=7.74%. Leave one out cross-validation of the best regression model was also computed, and revealed an adj. R² and RMSE of 0.92 and 8.31%, respectively. This study showed that LiDAR-derived metrics can be used to predict BA in Pinus taeda plantations in south Brazil with high precision. We conclude that there is good potential to monitor growth in this type of plantations using airborne LiDAR. We hope that the promising results for BA modeling presented herein will stimulate to operate this technology in Brazil.
Francisca Rocha de Souza Pereira
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.
Stovall, A. E.
The storage and flux of terrestrial carbon (C) is one of the largest and most uncertain components of the global C budget, the vast majority of which is held within the biomass of the world's forests. However, the spatial distribution and quantification of forest C remains difficult to measure on a large scale. Remote sensing of forests with airborne LiDAR has proven to be an extremely effective method of bridging the gap between data from plot-level forestry mensuration and landscape-scale C storage estimates, but the standard method of assessing forest C is typically based on national or regional-scale allometric equations that are often not representative on the local-scale. Improvement of these measurements is necessary in order for collaborative multi-national carbon monitoring programs such as REDD implemented by the UNFCCC to be successful in areas, such as tropical forests, with tree species that have insufficiently documented allometric relationships. The primary goal of this study is to set forth a pipeline for precise non-destructive monitoring of C storage by: 1) determining C storage on 15 1/10th ha plots in a 25.6 ha Virginia temperate forest using the recently updated national allometric equations from Chojnacky et. al 2014, 2) comparing these estimates to non-destructively determined individual tree biomass using several semi-automated approaches of three-dimensionally analyzing the point cloud from a high-precision Terrestrial Laser Scanner (TLS), and 3) creating a predictive model of forest C storage by fusing airborne LiDAR data to the plot-level TLS measurements. Our findings align with several other studies, indicating a strong relationship between allometrically-derived C estimates and TLS-derived C measurements (R2=0.93, n=30) using relatively few individuals, suggesting the potential application of these methods to species that are understudied or are without allometric relationships. Voxel based C storage was estimated on the plot level and
Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M
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
Zlinszky, András; Pfeifer, Norbert
"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
Airborne LIDAR technology allows accurate and inexpensive measurements of topography, vegetation canopy heights, and buildings over large areas. In order to provide researchers high quality data, NSF has created the National Center for Airborne Laser Mapping (NCALM) to collect, archive, and distribute the LIDAR data. However, the LIDAR systems collect voluminous irregularly-spaced, three-dimensional point measurements of ground and non-ground objects scanned by the laser beneath the aircraft. To advance the use of the technology and data, NCALM is developing public domain algorithms for ground and non-ground measurement classification and tools for data retrieval and transformation. We present the main functions of the ALDPAT (Airborne LIDAR Data Processing and Analysis Tools) developed by NCALM. While Geographic Information Systems (GIS) provide a useful platform for storing, analyzing, and visualizing most spatial data, the shear volume of raw LIDAR data makes most commercial GIS packages impractical. Instead, we have developed a suite of applications in ALDPAT which combine self developed C++ programs with the APIs of commercial remote sensing and GIS software. Tasks performed by these applications include: 1) transforming data into specified horizontal coordinate systems and vertical datums; 2) merging and sorting data into manageable sized tiles, typically 4 square kilometers in dimension; 3) filtering point data to separate measurements for the ground from those for non-ground objects; 4) interpolating the irregularly spaced elevations onto a regularly spaced grid to allow raster based analysis; and 5) converting the gridded data into standard GIS import formats. The ALDPAT 1.0 is available through http://lidar.ihrc.fiu.edu/.
Ebe, V.; Sailer, R.; Bollmann, E.; Mitterer, S.; Klug, C.; Stötter, J.
In recent years the use of airborne laser scanning (ALS) data has gained increasingly in importance in geomorphology. Most research is based on the analysis of morphometric parameters derived from a single high-resolution digital elevation model (DEM). In contrast to the aforementioned mono-temporal analyses, in this study geomorphologic process areas are mapped, quantified and statistically evaluated by means of repeat ALS datasets. The study area is located in the Central Tyrolean Alps, Austria (Oetztal, Pitztal, Kaunertal and Nauderer Mountains) and covers an area of about 750 km^2. ALS point data of this area from 2006 and 2010 are used to calculate DEMs in various raster resolutions (1 m, 3 m, 5 m, 10 m). The mapping of the geomorphologic process areas is carried out on the basis of DEM differencing calculated from the 2006 and 2010 DEMs (dDEM). In these dDEMs, areas with a decrease in elevation (erosion) as well as areas with an increase in elevation (deposition) can be identified and mapped. The mapped process areas are thereafter classified into the gravitative process types rock fall, land slide and debris flow based on their morphometric characteristics. The analyses show that depending on the raster resolution a different number of processes can be identified. In the lowest resolution class (10 m) 62 distinct process areas could be mapped, whereas in the highest resolution class (1 m) 181 process areas could be identified. In the highest resolution a total of 78 process areas are mapped in the Oetztal area, of which 33 are classified as rock falls, 37 as land slides and 18 as debris flows. 23 areas were mapped in the Pitztal area (8 rock falls, 6 land slides and 18 debris flows), 55 in the Kaunertal area (11 rock falls, 9 land slides, 35 debris flows) and 16 in the Nauderer Mountains (4 rock falls, 2 land slides, 10 debris flows). All mapped process areas are within the elevation band from 2200 m to 3400 m. Almost all rock falls released above 3000 m in
Irish, Jennifer L
.... One such sensor is the US Army Corps of Engineers SHOALS system. SHOALS is unique in that it is the only lidar sensor, worldwide, that simultaneously collects bathymetry and adjacent topography...
Kane, V. R.; McGaughey, R. J.; Asner, G. P.; Kane, J. T.; Churchill, D.; Vaughn, N.
Most natural forests are structured as mosaics of tree clumps and openings. These mosaics reflect both the underlying patterns of the biophysical environment and the finer scale patterns of disturbance and regrowth. We have developed methods to quantify and map patterns of tree clumps and openings at scales from within stands to landscapes using airborne LiDAR. While many studies have used LiDAR data to identify individual trees, we also identify clumps as adjacent trees with similar heights within a stand that likely established at a similar time following a disturbance. We characterize openings by both size class and shape complexity. Spatial statistics are used to identify patterns of tree clumps and openings at the local (0.81 ha) scale, and these patterns are then mapped across entire landscapes. We use LiDAR data acquired over Sequoia National Park, California, USA, to show how forest structure varies with patterns of productivity driven by the biophysical environment. We then show how clump and opening patterns vary with different fire histories and how recent drought mortality correlates with different tree clump and opening structural mosaics. We also demonstrate that nesting sites for the California spotted owl, a species of concern, are associated with clumps of large (>32 and especially >48 m) trees but that the surrounding foraging areas consist of a heterogeneous pattern of forest structure. These methods are especially useful for studying clumps of large trees, which dominate above ground forest biomass, and the effects of disturbance on the abundance and pattern of large trees as key forest structures.
Bibi, T.; Azahari Razak, K.; Rahman, A. Abdul; Latif, A.
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.
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.
Widyaningrum, E.; Gorte, B. G. H.
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.
Gawior, D.; Rutkiewicz, P.; Malik, I.; Wistuba, M.
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..
National Aeronautics and Space Administration — The data set consists of color infrared orthophotography (TerrainVision® - High resolution Topographic Mapping & Aerial Photography, with 6-inch pixel...
Sullivan, F.; Palace, M. W.; Ducey, M. J.; David, O.; Cook, B. D.; Lepine, L. C.
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
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
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.
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.
Juan Carlos Fernandez-Diaz
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.
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).
This bimonthly contractor progress report covers the operation, maintenance and data management of the Airborne Oceanographic Lidar and the Airborne Topographic Mapper. Monthly activities included: mission planning, sensor operation and calibration, data processing, data analysis, network development and maintenance and instrument maintenance engineering and fabrication.
Gregory P. Asner
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.
National Oceanic and Atmospheric Administration, Department of Commerce — The data sets are generated using the OPTECH ALTM 70 kHz LIDAR system mounted onboard AeroMap's twin-engine Cessna 320 aircraft. Classified data sets such as this...
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...
Schwemmer, Geary K.
Scanning holographic lidar receivers are currently in use in two operational lidar systems, PHASERS (Prototype Holographic Atmospheric Scanner for Environmental Remote Sensing) and now HARLIE (Holographic Airborne Rotating Lidar Instrument Experiment). These systems are based on volume phase holograms made in dichromated gelatin (DCG) sandwiched between 2 layers of high quality float glass. They have demonstrated the practical application of this technology to compact scanning lidar systems at 532 and 1064 nm wavelengths, the ability to withstand moderately high laser power and energy loading, sufficient optical quality for most direct detection systems, overall efficiencies rivaling conventional receivers, and the stability to last several years under typical lidar system environments. Their size and weight are approximately half of similar performing scanning systems using reflective optics. The cost of holographic systems will eventually be lower than the reflective optical systems depending on their degree of commercialization. There are a number of applications that require or can greatly benefit from a scanning capability. Several of these are airborne systems, which either use focal plane scanning, as in the Laser Vegetation Imaging System or use primary aperture scanning, as in the Airborne Oceanographic Lidar or the Large Aperture Scanning Airborne Lidar. The latter class requires a large clear aperture opening or window in the aircraft. This type of system can greatly benefit from the use of scanning transmission holograms of the HARLIE type because the clear aperture required is only about 25% larger than the collecting aperture as opposed to 200-300% larger for scan angles of 45 degrees off nadir.
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...
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.
Larsen, C. F.
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
Carlos Alberto Silva; Andrew Thomas Hudak; Carine Klauberg; Lee Alexandre Vierling; Carlos Gonzalez‑Benecke; Samuel de Padua Chaves Carvalho; Luiz Carlos Estraviz Rodriguez; Adrian Cardil
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 mâ 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...
Widyaningrum, E.; Gorte, B.G.H.
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
Kim, Seongjoon; Min, Seonghong; Kim, Geunhan; Lee, Impyeong; Jun, Chulmin
An airborne LIDAR (LIght Detection And Ranging) system can rapidly generate 3D points by densely sampling the terrain surfaces using laser pulses. The LIDAR points can be efficiently utilized for automatic reconstruction of 3D models of the objects on the terrain and the terrain itself. The data simulation of such a LIDAR system is significantly useful not only to design an optimal sensor for a specific application but also to assess data processing algorithms with various kinds of test data. In this study, we thus attempted to develop data simulation software of an airborne LIDAR system generally consisting of a GPS, an IMU and a laser scanner. We focused particularly on the geometric modeling of the sensors and the object modeling of the targets and background. Hence the data simulation software has been developed using these models. For the geometric modeling, we derived the sensor equation by modeling not only the geometric relationships between the three modules, such as a GPS, an IMU and a laser scanner but also the systematic errors associated with them. Moreover, for rapid and effective simulation, we designed the data model for both targets and background. We constructed the model data by converting the VRML formatted data into the designed model and stored these data in a 3D spatial database that can offer more effective 3D spatial indexing and query processing. Finally, we developed a program that generates simulated data along with the system parameters of a sensor, a terrain model and its trajectories over the model given.
Brovkina, Olga; Novotný, Jan; Cienciala, E.; Zemek, František; Russ, R.
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
Yu, Anthony W.; Krainak, Michael A.; Abshire, James B.; Cavanaugh, John; Valett, Susan; Ramos-Izquierdo, Luis
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.
Maack, Joachim; Lingenfelder, Marcus; Eilers, Christina; Smaltschinski, Thomas; Weinacker, Holger; Jaeger, Dirk; Koch, Barbara
Trees Outside Forests (TOF) represent a source of lignocellulosic biomass that has received increasing attention in the recent years. While some studies have already investigated the potential of TOF in Germany, a spatial explicit analysis, specifically for Baden-Wuerttemberg, is still lacking. We used a unique wall-to-wall airborne Light Detection and Ranging (LiDAR) dataset combined with OpenStreetMap (OSM) data to map and classify TOF of the federal state of Baden-Wuerttemberg (∼35.000 km2) in south-western Germany. Furthermore, from annual biomass potentials of TOF areas collected from available literature, we calculated the mean annual biomass supply for all TOF areas in Baden-Wuerttemberg. This combination of remote sensing-based classification and available literature resulted in a mean annual biomass supply between ∼490,000-730,000 t from TOF in Baden-Wuerttemberg. The classification congruence on three reference sites was very high (∼99%) using a simple filter technique applied to the LiDAR data and masking man-made objects using OSM data. In contrast, the available literature revealed a high variability of biomass potentials, supporting the demand for an inventory system. Still, the results demonstrate the applicability of LiDAR based vegetation mapping and the value of OSM data in Baden-Wuerttemberg to detect man-made objects.
Fatoyinbo, T.; Lagomasino, D.; Simard, M.; Lee, S. K.; Feliciano, E. A.; Trettin, C.
Vegetated coastal ecosystems, also called Blue Carbon ecosystems are highly efficient carbon sinks and have been shown to play a role in ameliorating the effect of increasing global climate change by capturing significant amounts of carbon into sediments and plant biomass. Mangrove-lined estuaries and coastal ecosystems are significant to global biogeochemical processes and regulate the structure, productivity and function of adjacent coastal ecosystems disproportionately to their land cover. Here we present recent efforts by the CMS Total Blue Carbon Stocks in Africa Project to estimate total (above and belowground) carbon stocks in East and Central Africa using in situ, high resolution stereo, airborne lidar and spaceborne SAR data. We generated Mangrove extent and change maps and canopy height estimates for the 2000 and 2015 eras that were used as input to carry out stratified field plot samples of above, below and soil Carbon stocks in the Rufiji Delta, Tanzania, Zambezi Delta, Mozambique and Pongara National Park, Gabon. By combining the field measurements and remotely sensed data, we estimated countrywide mangrove total carbon stocks. Uncertainties of estimates associated with different remote sensing input data were also calculated and will be presented. In this talk, we will give an overview of recent efforts to quantify mangrove forest 3-D structure, composition and change at high resolution globally in the context of estimating forest biomass and blue carbon stocks. Our presentation covers field and remotely sensed investigations and describes unique remotely sensed datasets produced and collected at NASA, with an emphasis on recently collected airborne Lidar and Radar from the AfriSAR campaign. Specifically, we will present new results focusing on the validation and comparison of independent mangrove canopy height and biomass measurements from commercial airborne lidar, LVIS, TanDEM-X, UAVSAR and World View, from Gabon, Mozambique and Tanzania.
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...
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...
James H. Churnside
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.
Thatcher, Cindy A.; Lim, Samsung; Palaseanu-Lovejoy, Monica; Danielson, Jeffrey J.; Kimbrow, Dustin R.
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.
Full Text Available The ability to build three-dimensional models through technologies based on satellite navigation systems GNSS and the continuous development of new sensors, as Airborne Laser Scanning Hydrography (ALH, data acquisition methods and 3D multi-resolution representations, have contributed significantly to the digital 3D documentation, mapping, preservation and representation of landscapes and heritage as well as to the growth of research in this fields. However, GNSS systems led to the use of the ellipsoidal height; to transform this height in orthometric is necessary to know a geoid undulation model. The latest and most accurate global geoid undulation model, available worldwide, is EGM2008 which has been publicly released by the U.S. National Geospatial-Intelligence Agency (NGA EGM Development Team. Therefore, given the availability and accuracy of this geoid model, we can use it in geomatics applications that require the conversion of heights. Using this model, to correct the elevation of a point does not coincide with any node must interpolate elevation information of adjacent nodes. The purpose of this paper is produce a Matlab® geodetic software for processing airborne LIDAR bathymetry data. In particular we want to focus on the point clouds in ASPRS LAS format and convert the ellipsoidal height in orthometric. The algorithm, valid on the whole globe and operative for all UTM zones, allows the conversion of ellipsoidal heights using the EGM2008 model. Of this model we analyse the slopes which occur, in some critical areas, between the nodes of the undulations grid; we will focus our attention on the marine areas verifying the impact that the slopes have in the calculation of the orthometric height and, consequently, in the accuracy of the in the 3-D point clouds. This experiment will be carried out by analysing a LAS APRS file containing topographic and bathymetric data collected with LIDAR systems along the coasts of Oregon and Washington
Zhou, Guoqing; Wang, Chenxi; Li, Mingyan; Wang, Yuefeng; Ye, Siqi; Han, Caiyun
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.
Li, N.; Pfeifer, N.; Liu, C.
The common statistical methods for supervised classification usually require a large amount of training data to achieve reasonable results, which is time consuming and inefficient. This paper proposes a tensor sparse representation classification (SRC) method for airborne LiDAR points. The LiDAR points are represented as tensors to keep attributes in its spatial space. Then only a few of training data is used for dictionary learning, and the sparse tensor is calculated based on tensor OMP algorithm. The point label is determined by the minimal reconstruction residuals. Experiments are carried out on real LiDAR points whose result shows that objects can be distinguished by this algorithm successfully.
Harper, David B.; Cook, Anthony; Hostetler, Chris; Hair, John W.; Mack, Terry L.
NASA Langley Research Center (LaRC) recently developed the LaRC Airborne High Spectral Resolution Lidar (HSRL) to make measurements of aerosol and cloud distribution and optical properties. The Airborne HSRL has undergone as series of test flights and was successfully deployed on the Megacity Initiative: Local and Global Research Observations (MILAGRO) field mission in March 2006 (see Hair et al. in these proceedings). This paper provides an overview of the design of the Airborne HSRL and descriptions of some key subsystems unique to this instrument.
Ramanathan, Anand; Numata, Kenji; Wu, Stewart T.; Li, Steven X.; Dawsey, Martha W.; Mao, Jianping; Kawa, Stephan R.; Riris, Haris
We demonstrate the airborne measurement of atmospheric methane using a pulsed lidar at 1650 nm using an integrated path differential absorption scheme. Our seeded nanosecond-pulsed optical parametric amplifier (OPA)-based instrument works up to the highest altitudes flown (<10 km). The obtained absorption profile is in good agreement with theoretical predictions based on the HITRAN database.
Brian M. Wing; Martin W. Ritchie; Kevin Boston; Warren B. Cohen; Michael J. Olsen
The ability to estimate and monitor standing dead trees (snags) has been difficult due to their irregular and sparse distribution, often requiring intensive sampling methods to obtain statistically significant estimates. This study presents a new method for estimating and monitoring snags using neighborhood attribute filtered airborne discrete-return lidar data. The...
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.
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.
Blair, J. B.; Rabine, D.; Hofton, M. A.; Citrin, E.; Luthcke, S. B.; Misakonis, A.; Wake, S.
Full waveform laser altimetry has demonstrated its ability to capture highly-accurate surface topography and vertical structure (e.g. vegetation height and structure) even in the most challenging conditions. NASA's high-altitude airborne laser altimeter, LVIS (the Land Vegetation, and Ice Sensor) has produced high-accuracy surface maps over a wide variety of science targets for the last 2 decades. Recently NASA has funded the transition of LVIS into a full-time NASA airborne Facility instrument to increase the amount and quality of the data and to decrease the end-user costs, to expand the utilization and application of this unique sensor capability. Based heavily on the existing LVIS sensor design, the Facility LVIS instrument includes numerous improvements for reliability, resolution, real-time performance monitoring and science products, decreased operational costs, and improved data turnaround time and consistency. The development of this Facility instrument is proceeding well and it is scheduled to begin operations testing in mid-2016. A comprehensive description of the LVIS Facility capability will be presented along with several mission scenarios and science applications examples. The sensor improvements included increased spatial resolution (footprints as small as 5 m), increased range precision (sub-cm single shot range precision), expanded dynamic range, improved detector sensitivity, operational autonomy, real-time flight line tracking, and overall increased reliability and sensor calibration stability. The science customer mission planning and data product interface will be discussed. Science applications of the LVIS Facility include: cryosphere, territorial ecology carbon cycle, hydrology, solid earth and natural hazards, and biodiversity.
Tamás, János; Lehoczky, Éva; Fehér, János; Fórián, Tünde; Nagy, Attila; Bozsik, Éva; Gálya, Bernadett; Riczu, Péter
Agriculture uses 70% of global available fresh water. However, ca. 50-70% of water used by cultivated plants, the rest of water transpirated by the weeds. Thus, to define the distribution of weeds is very important in precision agriculture and horticulture as well. To survey weeds on larger fields by traditional methods is often time consuming. Remote sensing instruments are useful to detect weeds in larger area. In our investigation a 3D airborne laser scanner (RIEGL LMS-Q680i) was used in agricultural field near Sopron to scouting weeds. Beside the airborne LiDAR, hyperspectral imaging system (AISA DUAL) and air photos helped to investigate weed coverage. The LiDAR survey was carried out at early April, 2012, before sprouting of cultivated plants. Thus, there could be detected emerging of weeds and direction of cultivation. However airborne LiDAR system was ideal to detect weeds, identification of weeds at species level was infeasible. Higher point density LiDAR - Terrestrial laser scanning - systems are appropriate to distinguish weed species. Based on the results, laser scanner is an effective tool to scouting of weeds. Appropriate weed detection and mapping systems could contribute to elaborate water and herbicide saving management technique. This publication was supported by the OTKA project K 105789.
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.
Full Text Available The goal of this study was to map watercourses, watersheds, and small wetland features that are completely obscured by the forest canopy using airborne LiDAR (Light Detection and Ranging within the archaeological site from Porolissum. This technology was used to generate a bare-earth Digital Terrain Model (DTM with 0.5 m spatial resolution in order to map small depressions and concavities across 10 km2 of forested landscape. Although further research is needed to determine the ecological, geological, and archaeological significance of the mapped waterbodies, the general methodology represents important progress in the rapid and accurate detection of wetland habitats in forested landscapes.
Werner, C; Bachstein, F; Dietz, S; Herrmann, H; Köpp, F; Löffler, H
During May 1977 the Airborne Science Spacelab Experiments System Simulation (ASSESS II) took place, using the NASA CV 990 aircraft. A ND:glass lidar system, measuring the aerosol mass concentration over large areas, was proxy operated by trained ''Payload Specialists.'' The main part of this paper is concerned with the lidar experiment and its results. The participants in the mission viewed it as a tool for judging their spacelab science management and as the final stage of a guide for future planning of experiments. A general result that has emerged is that, for a real spacelab mission, the handling of remote sensing experiments should be fully automatic.
Kinzel, Paul J.; Legleiter, Carl; Nelson, Jonathan M.
Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated
Popescu, Sorin C. [Spatial Sciences Laboratory, Department of Ecosystem Science and Management, Texas A and M University, 1500 Research Parkway, Suite B 223, College Station, TX 77845 (United States)
Airborne lidar (Light Detection And Ranging) is a proven technology that can be used to accurately assess aboveground forest biomass and bio-energy feedstocks. The overall goal of this study was to develop a method for assessing aboveground biomass and component biomass for individual trees using airborne lidar data in forest settings typical for loblolly pine stands (Pinus taeda L.) in the southeastern United States. More specific objectives included: (1) assessing the accuracy of estimating diameter at breast height (dbh) for individual pine trees using lidar-derived individual tree measurements, such as tree height and crown diameter, and (2) investigating the use of lidar-derived individual tree measurements with linear and nonlinear regression to estimate per tree aboveground biomass. In addition, the study presents a method for estimating the biomass of individual tree components, such as foliage, coarse roots, stem bark, and stem wood, as derived quantities from the aboveground biomass prediction. A lidar software application, TreeVaW, was used to extract forest inventory parameters at individual tree level from a lidar-derived canopy height model. Lidar-measured parameters at individual tree level, such as height and crown diameter, were used with regression models to estimate dbh, aboveground tree biomass, and tree-component biomass. Field measurements were collected for 45 loblolly pine trees over 0.1- and 0.01-acre plots. Linear regression models were able to explain 93% of the variability associated with individual tree biomass, 90% for dbh, and 79-80% for components biomass. (author)
Yu, Jirong; Petros, Mulugeta; Refaat, Tamer; Singh, Upendra
We have developed an airborne 2-micron Integrated Path Differential Absorption (IPDA) lidar for atmospheric CO2 measurements. The double pulsed, high pulse energy lidar instrument can provide high-precision CO2 column density measurements.
Abshire, James B.; Riris, Haris; Allan, Graham R.; Weaver, Clark J.; Mao, Jianping; Sun, Xiaoli; Hasselbrack, William E.; Rodriquez, Michael; Browell, Edward V.
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.
James H. Churnside; Richard D. Marchbanks; Chad Lembke; Jordon Beckler
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 ex...
Full Text Available The common statistical methods for supervised classification usually require a large amount of training data to achieve reasonable results, which is time consuming and inefficient. This paper proposes a tensor sparse representation classification (SRC method for airborne LiDAR points. The LiDAR points are represented as tensors to keep attributes in its spatial space. Then only a few of training data is used for dictionary learning, and the sparse tensor is calculated based on tensor OMP algorithm. The point label is determined by the minimal reconstruction residuals. Experiments are carried out on real LiDAR points whose result shows that objects can be distinguished by this algorithm successfully.
Langlois, Melanie N.; Richardson, Murray C.; Price, Jonathan S.
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.
Brocher, T. M.; Prentice, C. S.; Phillips, D. A.; Bevis, M.; Shrestha, R. L.
We present a digital elevation model (DEM) constructed from newly acquired high-resolution LIght Detection and Ranging (LIDAR) data along the Hayward Fault in Northern California. The data were acquired by the National Center for Airborne Laser Mapping (NCALM) in the spring of 2007 in conjunction with a larger regional airborne LIDAR survey of the major crustal faults in northern California coordinated by UNAVCO and funded by the National Science Foundation as part of GeoEarthScope. A consortium composed of the U. S. Geological Survey, Pacific Gas & Electric Company, the San Francisco Public Utilities Commission, and the City of Berkeley separately funded the LIDAR acquisition along the Hayward Fault. Airborne LIDAR data were collected within a 106-km long by 1-km wide swath encompassing the Hayward Fault that extended from San Pablo Bay on the north to the southern end of its restraining stepover with the Calaveras Fault on the south. The Hayward Fault is among the most urbanized faults in the nation. With its most recent major rupture in 1868, it is well within the time window for its next large earthquake, making it an excellent candidate for a "before the earthquake" DEM image. After the next large Hayward Fault event, this DEM can be compared to a post-earthquake LIDAR DEM to provide a means for a detailed analysis of fault slip. In order to minimize location errors, temporary GPS ground control stations were deployed by Ohio State University, UNAVCO, and student volunteers from local universities to augment the available continuous GPS arrays operated in the study area by the Bay Area Regional Deformation (BARD) Network and the Plate Boundary Observatory (PBO). The vegetation cover varies along the fault zone: most of the vegetation is non-native species. Photographs from the 1860s show very little tall vegetation along the fault zone. A number of interesting geomorphic features are associated with the Hayward Fault, even in urbanized areas. Sag ponds and
Hoge, F. E.
From February 1986 to the present, the AOL participated in six interagency flight missions. (1) Shelf Edge Exchange Processes (SEEP II) (Department of Energy). The SEEP experiments are designed to assess the assimilative capacity of the Continental Shelf to absorb the energy by-products introduced into the near-shore ocean environment from coastal communities and marine activities such as energy production plants and offshore oil operations. (2) BIOWATT II (Office of Naval Research). The major objective of this study was to provide a better understanding of the relationships between ocean physics, biology, bioluminescence, and optics in oligotrophic portions of the Atlantic Ocean. (3) Fall Experiment (FLEX) (Department of Energy). The FLEX studies were designed to determine the fate of low salinity water in the coastal boundary zone that is advected south towards the Florida coast during autumn. (4) Greenland Sea and Icelandic Marine Biological Experiments (NASA). The investigations were designed to evaluate the distribution of surface layer chlorophyll in the Greeland Sea and in the coastal waters in the vicinity of Iceland. (5) Submerged Oceanic Scattering Layer Experiment (Naval Ocean Systems Center). This flight experiment demonstrated for the first time the feasibility of detecting and metrically measuring the depth to submerged layers of particulate matter in the shelf break region and in the inner coastal zone. (6) Microbial Exchanges and Coupling in Coastal Atlantic Systems (National Science Foundation). This investigation was designed to study the transportation and fate of particulates in coastal waters and in particular the Chesapeake Bay/coastal Atlantic Ocean. Shortly after the conduct of the flight experiments, airborne laser-induced chlorophyll a and phycoerythrin fluorescence data, as well as sea surface temperature and airborne expendable bathythermograph water column temperature profiles are supplied to cooperating institutions.
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.
Abd Rahman, M.Z.; Gorte, B.G.H.
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
Full Text Available In this study, LIDAR DEM data was used to obtain a primary landform map in accordance with a well-known methodology. This primary landform map was generalized using the Focal Statistics tool (Majority, considering the minimum area condition in cartographic generalization in order to obtain landform maps at 1:1000 and 1:5000 scales. Both the primary and the generalized landform maps were verified visually with hillshaded DEM and an orthophoto. As a result, these maps provide satisfactory visuals of the landforms. In order to show the effect of generalization, the area of each landform in both the primary and the generalized maps was computed. Consequently, landform maps at large scales could be obtained with the proposed methodology, including generalization using LIDAR DEM.
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...
Simonson, William D; Allen, Harriet D; Coomes, David A
Airborne lidar is a remote-sensing tool of increasing importance in ecological and conservation research due to its ability to characterize three-dimensional vegetation structure. If different aspects of plant species diversity and composition can be related to vegetation structure, landscape-level assessments of plant communities may be possible. We examined this possibility for Mediterranean oak forests in southern Portugal, which are rich in biological diversity but also threatened. We compared data from a discrete, first-and-last return lidar data set collected for 31 plots of cork oak (Quercus suber) and Algerian oak (Quercus canariensis) forest with field data to test whether lidar can be used to predict the vertical structure of vegetation, diversity of plant species, and community type. Lidar- and field-measured structural data were significantly correlated (up to r= 0.85). Diversity of forest species was significantly associated with lidar-measured vegetation height (R(2) = 0.50, p lidar data. Lidar can be applied widely for mapping of habitat and assessments of habitat condition (e.g., in support of the European Species and Habitats Directive [92/43/EEC]). However, particular attention needs to be paid to issues of survey design: density of lidar points and geospatial accuracy of ground-truthing and its timing relative to acquisition of lidar data. ©2012 Society for Conservation Biology.
Matthew J. McCarthy
Full Text Available Habitat mapping can be accomplished using many techniques and types of data. There are pros and cons for each technique and dataset, therefore, the goal of this project was to investigate the capabilities of new satellite sensor technology and to assess map accuracy for a variety of image classification techniques based on hundreds of field-work sites. The study area was Masonboro Island, an undeveloped area in coastal North Carolina, USA. Using the best map results, a habitat change assessment was conducted between 2002 and 2010. WorldView-2, QuickBird, and IKONOS satellite sensors were tested using unsupervised and supervised methods using a variety of spectral band combinations. Light Detection and Ranging (LiDAR elevation and texture data pan-sharpening, and spatial filtering were also tested. In total, 200 maps were generated and results indicated that WorldView-2 was consistently more accurate than QuickBird and IKONOS. Supervised maps were more accurate than unsupervised in 80% of the maps. Pan-sharpening the images did not consistently improve map accuracy but using a majority filter generally increased map accuracy. During the relatively short eight-year period, 20% of the coastal study area changed with intertidal marsh experiencing the most change. Smaller habitat classes changed substantially as well. For example, 84% of upland scrub-shrub experienced change. These results document the dynamic nature of coastal habitats, validate the use of the relatively new Worldview-2 sensor, and may be used to guide future coastal habitat mapping.
Nabucet, Jean; Hubert-Moy, Laurence; Corpetti, Thomas; Launeau, Patrick; Lague, Dimitri; Michon, Cyril; Quenol, Herve
Because of the large increase of urban population in the last decades, the question of sustainable development in urban areas is crucial. In this context, vegetation plays a significant role in urban planning, environmental protecting, and sustainable development policy making, heating and cooling requirements of buildings, displacement of animals dispersion, concentration of pollutants, and well-being. In numerous cities, vegetation is limited to public areas using GPS surveys or aerial remote sensing data. Recently, very high-resolution sensors as Light Detection and Ranging (LiDAR) data have permitted significant improvements in vegetation mapping in urban areas. This paper presents an evaluation of a new generation of airborne LIDAR bi-spectral discrete point (Optech titan) for mapping and characterizing urban vegetation. The methodology is based on a four-step approach: 1) the analysis of the quality of data in order to estimate noise between the green and near-infrared LIDAR point clouds; 2) this enables to remove the topographic effects and 3) a first classification, devoted to the elimination of the non-vegetation class, is performed based on the intensity value of the two channels; finally, in 4), the tree coverage is classified into seven categories of strata combination. To this end specific descriptors related to the organization of the point clouds are used. These first results show that compared to monospectral LiDAR data, bi-spectral LiDAR enables to improve significantly both the extraction and the characterization of urban objects. This reveals new perspectives for mapping and characterizing urban patterns and other complex structures.
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.
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.
Full Text Available 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 (~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.
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.
Widyaningrum, E.; Gorte, B.G.H.
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
Bluestein, H. B.; Doviak, R. J.; Eilts, M. D.; Mccaul, E. W.; Rabin, R.; Sundara-Rajan, A.; Zrnic, D. S.
The first experiment to combine airborne Doppler Lidar and ground-based dual Doppler Radar measurements of wind to detail the lower tropospheric flows in quiescent and stormy weather was conducted in central Oklahoma during four days in June-July 1981. Data from these unique remote sensing instruments, coupled with data from conventional in-situ facilities, i.e., 500-m meteorological tower, rawinsonde, and surface based sensors, were analyzed to enhance understanding of wind, waves and turbulence. The purposes of the study were to: (1) compare winds mapped by ground-based dual Doppler radars, airborne Doppler lidar, and anemometers on a tower; (2) compare measured atmospheric boundary layer flow with flows predicted by theoretical models; (3) investigate the kinematic structure of air mass boundaries that precede the development of severe storms; and (4) study the kinematic structure of thunderstorm phenomena (downdrafts, gust fronts, etc.) that produce wind shear and turbulence hazardous to aircraft operations. The report consists of three parts: Part 1, Intercomparison of Wind Data from Airborne Lidar, Ground-Based Radars and Instrumented 444 m Tower; Part 2, The Structure of the Convective Atmospheric Boundary Layer as Revealed by Lidar and Doppler Radars; and Part 3, Doppler Lidar Observations in Thunderstorm Environments.
Saatchi, S. S.; Xu, L.; Meyer, V.; Ferraz, A.; Yang, Y.; Shapiro, A.; Bastin, J. F.
Tropical countries are required to produce robust and verifiable estimates of forest carbon stocks for successful implementation of climate change mitigation. Lack of systematic national inventory data due to access, cost, and infrastructure, has impacted the capacity of most tropical countries to accurately report the GHG emissions to the international community. Here, we report on the development of the aboveground forest carbon (AGC) map of Democratic Republic of Congo (DRC) by using the VCS (Verified Carbon Standard) methodology developed by Sassan Saatchi (VT0005) using high-resolution airborne LiDAR samples. The methodology provides the distribution of the carbon stocks in aboveground live trees of more than 150 million ha of forests at 1-ha spatial resolution in DRC using more than 430, 000 ha of systematic random airborne Lidar inventory samples of forest structure. We developed a LIDAR aboveground biomass allometry using more than 100 1-ha plots across forest types and power-law model with LIDAR height metrics and average landscape scale wood density. The methodology provided estimates of forest biomass over the entire country using two approaches: 1) mean, variance, and total carbon estimates for each forest type present in DRC using inventory statistical techniques, and 2) a wall-to-wall map of the forest biomass extrapolated using satellite radar (ALOS PALSAR), surface topography from SRTM, and spectral information from Landsat (TM) and machine learning algorithms. We present the methodology, the estimates of carbon stocks and the spatial uncertainty over the entire country. AcknowledgementsThe theoretical research was carried out partially at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration, and the design and implementation in the Democratic Republic of Congo was carried out at the Institute of Environment and Sustainability at University of California Los
Minsley, B. J.; Ball, L. B.; Bloss, B. R.; Kass, A.; Pastick, N.; Smith, B. D.; Voss, C. I.; Walsh, D. O.; Walvoord, M. A.; Wylie, B. K.
Permafrost is a key characteristic of cold region landscapes, yet detailed assessments of how the subsurface distribution of permafrost impacts the environment, hydrologic systems, and infrastructure are lacking. Data acquired from several airborne electromagnetic (AEM) surveys in Alaska provide significant new insight into the spatial extent of permafrost over larger areas (hundreds to thousands of square kilometers) than can be mapped using ground-based geophysical methods or through drilling. We compare several AEM datasets from different areas of interior Alaska, and explore the capacity of these data to infer geologic structure, permafrost extent, and related hydrologic processes. We also assess the impact of fires on permafrost by comparing data from different burn years within similar geological environments. Ultimately, interpretations rely on understanding the relationship between electrical resistivity measured by AEM surveys and the physical properties of interest such as geology, permafrost, and unfrozen water content in the subsurface. These relationships are often ambiguous and non-unique, so additional information is useful for reducing uncertainty. Shallow (upper ~1m) permafrost and soil characteristics identified from remotely sensed imagery and field observations help to constrain and aerially extend near-surface AEM interpretations, where correlations between the AEM and remote sensing data are identified using empirical multivariate analyses. Surface nuclear magnetic resonance (sNMR) measurements quantify the contribution of unfrozen water at depth to the AEM-derived electrical resistivity models at several locations within one survey area. AEM surveys fill a critical data gap in the subsurface characterization of permafrost environments and will be valuable in future mapping and monitoring programs in cold regions.
Liu, Bo; Wang, Zhien; Cai, Yong; Wechsler, Perry; Kuestner, William; Burkhart, Matthew; Welch, Wayne
A compact airborne Raman lidar system, which can perform water vapor and aerosol measurements both during nighttime and daytime is described. The system design, setup and the data processing methods are described in the paper. The Raman lidar was tested on University of Wyoming King Air research aircraft (UWKA) during the Wyoming King Air PBL Exploratory Experiment (KAPEE) in 2010. An observation showing clouds, aerosols and a dry line is presented to illustrate the lidar detection capabilities. Comparisons of the water vapor and aerosol measurements using the Raman lidar and other in situ airborne instruments show good agreement.
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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....
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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....
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....
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
Yastikli, N.; Cetin, Z.
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
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
Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.
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
Elaksher, Ahmed F.; Bhandari, Subodh; Carreon-Limones, Christian A.; Lauf, Rachel
Recently, developments in airborne sensors and easy to fly, reliable, low-cost commercial Unmanned Aerial Vehicles, UAVs, have opened a new era for high quality and reliable mapping from UAVs using remote sensing techniques. The restricted payload capacity of low-cost UAVs imposes constraints on the quality of their navigation systems and the sensors they can carry. Therefore, LIDAR sensors with limited sample rate are utilized within the UAV system. This article introduces several applications that utilizes UAV-LIDAR systems, processing of a sample dataset downloaded from the internet and a new system that is being developed and flown. Our data was collected with DJI S900 Hexacopter and a VLP-16 LIDAR system from Velodyne. We then process the raw data to generate the 3D point cloud. The test site is a farming site so we classified the points into ground points and vegetation points. The results are very promising as an early research investigation. Currently, we are planning for other flights with more rigorous systems and quantitative evaluation.
An airborne 2-micron double-pulsed Integrated Path Differential Absorption (IPDA) lidar has been developed for atmospheric CO2 measurements. This new 2-miron pulsed IPDA lidar has been flown in spring of 2014 for total ten flights with 27 flight hours. It provides high precision measurement capability by unambiguously eliminating contamination from aerosols and clouds that can bias the IPDA measurement.
S. Urbanski; V. Kovalev; W. M. Hao; C. Wold; A. Petkov
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...
Yu, Anthony W.; Krainak, Michael A.; Harding, David J.; Abshire, James B.; Sun, Xiaoli; Cavanaugh, John; Valett, Susan; Ramos-Izquierdo, Luis
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.
Enwright, Nicholas M.; Wang, Lei; Borchert, Sinéad M.; Day, Richard H.; Feher, Laura C.; Osland, Michael J.
While airborne lidar data have revolutionized the spatial resolution that elevations can be realized, data limitations are often magnified in coastal settings. Researchers have found that airborne lidar can have a vertical error as high as 60 cm in densely vegetated intertidal areas. The uncertainty of digital elevation models is often left unaddressed; however, in low-relief environments, such as barrier islands, centimeter differences in elevation can affect exposure to physically demanding abiotic conditions, which greatly influence ecosystem structure and function. In this study, we used airborne lidar elevation data, in situ elevation observations, lidar metadata, and tide gauge information to delineate low-lying lands and the intertidal wetlands on Dauphin Island, a barrier island along the coast of Alabama, USA. We compared three different elevation error treatments, which included leaving error untreated and treatments that used Monte Carlo simulations to incorporate elevation vertical uncertainty using general information from lidar metadata and site-specific Real-Time Kinematic Global Position System data, respectively. To aid researchers in instances where limited information is available for error propagation, we conducted a sensitivity test to assess the effect of minor changes to error and bias. Treatment of error with site-specific observations produced the fewest omission errors, although the treatment using the lidar metadata had the most well-balanced results. The percent coverage of intertidal wetlands was increased by up to 80% when treating the vertical error of the digital elevation models. Based on the results from the sensitivity analysis, it could be reasonable to use error and positive bias values from literature for similar environments, conditions, and lidar acquisition characteristics in the event that collection of site-specific data is not feasible and information in the lidar metadata is insufficient. The methodology presented in
Gentry, Bruce; McGill, Matthew; Schwemmer, Geary; Hardesty, Michael; Brewer, Alan; Wilkerson, Thomas; Atlas, Robert; Sirota, Marcos; Lindemann, Scott
In the fall of 2005 we began developing an airborne scanning direct detection molecular Doppler lidar. The instrument is being built as part of the Tropospheric Wind Lidar Technology Experiment (TWiLiTE), a three year project selected by the NASA Earth Sun Technology Office under the Instrument Incubator Program. The TWiLiTE project is a collaboration involving scientists and engineers from NASA Goddard Space Flight Center, NOAA ESRL, Utah State University Space Dynamics Lab, Michigan Aerospace Corporation and Sigma Space Corporation. The TWiLiTE instrument will leverage significant research and development investments made by NASA Goddard and it's partners in the past several years in key lidar technologies and sub-systems (lasers, telescopes, scanning systems, detectors and receivers) required to enable spaceborne global wind lidar measurement. These sub-systems will be integrated into a complete molecular direct detection Doppler wind lidar system designed for autonomous operation on a high altitude aircraft, such as the NASA WB57. The WB57 flies at an altitude of 18 km and from this vantage point the nadir viewing Doppler lidar will be able to profile winds through the full troposphere. The TWiLiTE integrated airborne Doppler lidar instrument will be the first demonstration of a airborne scanning direct detection Doppler lidar and will serve as a critical milestone on the path to a future spaceborne tropospheric wind system. In addition to being a technology testbed for space based tropospheric wind lidar, when completed the TWiLiTE high altitude airborne lidar will be used for studying mesoscale dynamics and storm research (e.g. winter storms, hurricanes) and could be used for calibration and validation of satellite based wind systems such as ESA's Aeolus Atmospheric Dynamics Mission. The TWiLiTE Doppler lidar will have the capability to profile winds in clear air from the aircraft altitude of 18 km to the surface with 250 m vertical resolution and < 2mls
Full Text Available 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.
Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian
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.
Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian
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. PMID:26473881
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
Hopkinson, C.; Crasto, N.; Marsh, P.; Forbes, D.; Lesack, L.
Airborne light detection and ranging (LiDAR) data were used to map water level (WL) and hydraulic gradients (??H/??x) in the Mackenzie Delta. The LiDAR WL data were validated against eight independent hydrometric gauge measurements and demonstrated mean offsets from - 0??22 to + 0??04 m (??LiDAR-based WL gradients could be estimated with confidence over channel lengths exceeding 5-10 km where the WL change exceeded local noise levels in the LiDAR data. For the entire Delta, the LiDAR sample coverage indicated a rate of change in longitudinal gradient (??2H/??x) of 5??5 ?? 10-10 m m-2; therefore offering a potential means to estimate average flood stage hydraulic gradient for areas of the Delta not sampled or monitored. In the Outer Delta, within-channel and terrain gradient measurements all returned a consistent estimate of - 1 ?? 10-5 m m-1, suggesting that this is a typical hydraulic gradient for the downstream end of the Delta. For short reaches (short distances, however, was observed in the Peel Channel immediately upstream of Aklavik. A positive elevation anomaly (bulge) of > 0??1 m was observed at a channel constriction entering a meander bend, suggesting a localized modification of the channel hydraulics. Furthermore, water levels in the anabranch channels of the Peel River were almost 1 m higher than in Middle Channel of the Mackenzie River. This suggests: (i) the channels are elevated and have shallower bank heights in this part of the delta, leading to increased cross-delta and along-channel hydraulic gradients; and/or (ii) a proportion of the Peel River flow is lost to Middle Channel due to drainage across the delta through anastamosing channels. This study has demonstrated that airborne LiDAR data contain valuable information describing Arctic river delta water surface and hydraulic attributes that would be challenging to acquire by other means. ?? 2011 John Wiley & Sons, Ltd.
Shaun R. Levick
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.
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.
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.
Full Text Available Airborne Lidar Bathymetry (ALB provides a rapid means of data collection that provides seamless digital elevation maps across land and water. However, environmental factors such as water surface induce significant uncertainty in the ALB measurements. In this study, the effect of water surface on the ALB measurements is characterized both theoretically and empirically. Theoretical analysis includes Monte Carlo ray-tracing simulations that evaluate different environmental and hardware conditions such as wind speed, laser beam footprint diameter and off-nadir angle that are typically observed in ALB survey conditions. The empirical study includes development of an optical detector array to measure and analyze the refraction angle of the laser beam under a variety of environmental and hardware conditions. The results suggest that the refraction angle deviations ( 2 σ in the along-wind direction vary between 3–5° when variations in wind speed, laser beam footprint size and the laser beam incidence angle are taken into account.
Yu, Yang; Pei, Hailong; Xu, Chengzhong
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.
Poole, L. R.; Kent, G. S.
Polar stratospheric clouds (PSC's) have been detected repeatedly during Arctic and Antarctic winters since 1978/1979 by the SAM II (Stratospheric Aerosol Measurement II) instrument aboard the NIMBUS-7 satellite. PSC's are believed to form when supercooled sulfuric acid droplets freeze, and subsequently grow by deposition of ambient water vapor as the local stratospheric temperature falls below the frost point. In order to study the characteristics of PSC's at higher spatial and temporal resolution than that possible from the satellite observations, aircraft missions were conducted within the Arctic polar night vortex in Jan. 1984 and Jan. 1986 using the NASA Langley Research Center airborne dual polarization ruby lidar system. A synopsis of the 1984 and 1986 PSC observations is presented illustrating short range spatial changes in cloud structure, the variation of backscatter ratio with temperature, and the depolarization characterics of cloud layers. Implications are noted with regard to PSC particle characteristics and the physical process by which the clouds are thougth to form.
Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi
Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.
Bonisteel, Jamie M.; Nayegandhi, Amar; Wright, C. Wayne; Brock, John C.; Nagle, David
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
Full Text Available A massive earthquake of magnitude 9.0 hit off Tohoku region, the east coast of the Japanese main land, on 11 March, 2011. It was one of the historically powerful earthquakes in the world. The earthquake triggered powerful tsunami and broad-scale subsidence, so that, residential areas and infrastructures were catastrophically damaged. After that, it is necessary to renew a new map for reconstruction, such as cadastral map. In the critical situation, Mobile LiDAR Mapping system is efficient to rapidly collect fine data at once and capture more details of terrain features than data from airborne. In this paper, we would like to introduce procured instruments in our company and implemented survey several areas after the event, and suggest how to survey for cadastral map by Mobile LiDAR Mapping System.
Fedrigo, Melissa; Newnham, Glenn J.; Coops, Nicholas C.; Culvenor, Darius S.; Bolton, Douglas K.; Nitschke, Craig R.
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.
Gentry, Bruce; McGill, Matthew; Schwemmer, Geary; Hardesty, Michael; Brewer, Alan; Wilkerson, Thomas; Atlas, Robert; Sirota, Marcos; Lindemann, Scott
Global measurement of tropospheric winds is a key measurement for understanding atmospheric dynamics and improving numerical weather prediction. Global wind profiles remain a high priority for the operational weather community and also for a variety of research applications including studies of the global hydrologic cycle and transport studies of aerosols and trace species. In addition to space based winds, a high altitude airborne system flown on UAV or other advanced platforms would be of great interest for studying mesoscale dynamics and hurricanes. The Tropospheric Wind Lidar Technology Experiment (TWiLiTE) project was selected in 2005 by the NASA Earth Sun Technology Office as part of the Instrument Incubator Program. TWiLiTE will leverage significant research and development investments in key technologies made in the past several years. The primary focus will be on integrating these sub-systems into a complete molecular direct detection Doppler wind lidar system designed for autonomous operation on a high altitude aircraft, such as the NASA WB57, so that the nadir viewing lidar will be able to profile winds through the full troposphere. TWiLiTE is a collaboration involving scientists and technologists from NASA Goddard, NOAA ESRL, Utah State University Space Dynamics Lab and industry partners Michigan Aerospace Corporation and Sigma Space Corporation. NASA Goddard and it's partners have been at the forefront in the development of key lidar technologies (lasers, telescopes, scanning systems, detectors and receivers) required to enable spaceborne global wind lidar measurement. The TWiLiTE integrated airborne Doppler lidar instrument will be the first demonstration of a airborne scanning direct detection Doppler lidar and will serve as a critical milestone on the path to a fixture spaceborne tropospheric wind system. The completed system will have the capability to profile winds in clear air from the aircraft altitude of 18 h to the surface with 250 m vertical
Büyüksalih, I.; Bayburt, S.; Schardt, M.; Büyüksalih, G.
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 from the inadequacy of the
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
Simonson, W.; Ruiz-Benito, P.; Valladares, F.; Coomes, D.
Woodlands represent highly significant carbon sinks globally, though could lose this function under future climatic change. Effective large-scale monitoring of these woodlands has a critical role to play in mitigating for, and adapting to, climate change. Mediterranean woodlands have low carbon densities, but represent important global carbon stocks due to their extensiveness and are particularly vulnerable because the region is predicted to become much hotter and drier over the coming century. Airborne lidar is already recognized as an excellent approach for high-fidelity carbon mapping, but few studies have used multi-temporal lidar surveys to measure carbon fluxes in forests and none have worked with Mediterranean woodlands. We use a multi-temporal (5-year interval) airborne lidar data set for a region of central Spain to estimate above-ground biomass (AGB) and carbon dynamics in typical mixed broadleaved and/or coniferous Mediterranean woodlands. Field calibration of the lidar data enabled the generation of grid-based maps of AGB for 2006 and 2011, and the resulting AGB change was estimated. There was a close agreement between the lidar-based AGB growth estimate (1.22 Mg ha-1 yr-1) and those derived from two independent sources: the Spanish National Forest Inventory, and a tree-ring based analysis (1.19 and 1.13 Mg ha-1 yr-1, respectively). We parameterised a simple simulator of forest dynamics using the lidar carbon flux measurements, and used it to explore four scenarios of fire occurrence. Under undisturbed conditions (no fire) an accelerating accumulation of biomass and carbon is evident over the next 100 years with an average carbon sequestration rate of 1.95 Mg C ha-1 yr-1. This rate reduces by almost a third when fire probability is increased to 0.01 (fire return rate of 100 years), as has been predicted under climate change. Our work shows the power of multi-temporal lidar surveying to map woodland carbon fluxes and provide parameters for carbon
Singh, U. N.; Yu, J.; Petros, M.; Refaat, T. F.; Remus, R.; Fay, J.; Reithmaier, K.
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.
Nikandrova, A.; Väänänen, R.; Tabakova, K.; Kerminen, V. M.; O'Connor, E.
The aim of this work was to identify discrete aerosol layers and diagnose their origin, investigate the strength of mixing within the free-troposphere and with the boundary layer (BL), and understand the impact that mixing has on local and long-range transport of aerosol. For these purposes we combined airborne in-situ aerosol measurements with data obtained by a High Spectral Resolution Lidar (HSRL). The HSRL was deployed in Hyytiälä, Southern Finland, from January to September 2014 as a part of the US DoE ARM (Atmospheric Radiation Measurement) Mobile Facility during the BAECC (Biogenic Aerosols - Effects on Cloud and Climate) Campaign. Two airborne campaigns took place in April and August 2014 during the BAECC campaign. The vertical profile of backscatter coefficient from the HSRL was used to diagnose the location and depth of significant aerosol layers in the atmosphere. Frequently, in addition to the BL, one or two tropospheric layers were identified. In-situ measurements of the aerosol size distribution in these layers were obtained from a Scanning Mobility Particle Sizer (SMPS) and Optical Particle Sizer (OPS), that were installed on board the aircraft; these measurements were combined to cover sizes ranging from 10 nm to 10 µm. As expected, the highest number concentration of aerosol particles at all size ranges was found predominantly in the BL. Many upper layers had size distributions with a similar shape to that in the BL but with overall lower concentrations attributed to dilution of particles into a large volume of air. Hence, these layers were likely of very similar origin to the air in the BL and presumably were the result of lofted residual layers. Intervening layers however, could contain markedly different distribution shapes, which could be attributed to both different air mass origins, and different ambient relative humidity. Potential for mixing between two discreet elevated layers was often seen as a thin interface layer, which exhibited a
Marenco, Franco; Turnbull, Kate; Johnson, Ben; Haywood, Jim
The South AMerican Biomass Burning Analysis (SAMBBA) campaign took place in Brazil in September and October 2012, involving the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft. SAMBBA was aimed at investigating the properties of aerosols over South America during the dry season, when most of the deforestation and agricultural fires occur. Twenty research flights were carried out, and included the following aerosol measurements: physical, optical and chemical properties, as well as vertical distribution and mapping. Moreover, measurements of gas phase chemistry and fire radiative power were also carried out. This presentation focuses mainly on results obtained with the on-board lidar, putting them into context with data from other sources such as optical particle counters, dropsondes, and ground-based remote sensing. An optically thick haze layer was observed during most flights. This layer tended to be elevated, often at an altitude of 1-3 km, with multiple thinner layers all the way up to 7 km. This atmospheric structure is believed to be the result of the interaction between smoke injected in the boundary layer and deep convective clouds often formed in the afternoon hours, with the potential of lifting aerosols quite high into the free troposphere. Lidar observations also reveal smoke plumes originated from single fires, and allow to characterise them in terms of size and plume rise. Good cases of pyrocumulus are also revealed, rising some times from the ground up to altitudes of 6 km.
Carlos Alberto Silva
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
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.
Xu, Y.; Yue, D.; He, P.
The point cloud segmentation of gullies with high accuracy lays the groundwork for the gully parameter extraction and developing models. A point cloud segmentation method of gullies based on characteristic difference from airborne LIDAR is proposed. Firstly, point cloud characteristics of gullies are discussed, and then differences in surface features are obtained based on different scales after preprocessing of the point cloud. Initial gullies are segmented from point clouds combined with a curvature threshold. Finally, real gully point clouds are obtained based on the clustering analysis. The experimental results demonstrate that gullies can be detected accurately with airborne LIDAR point clouds, and this method provides a new idea for quantitative evaluation of gullies.
Coops, Nicholas C; Morsdorf, Felix; Schaepman, Michael E; Zimmermann, Niklaus E
Understanding what environmental drivers control the position of the alpine tree line is important for refining our understanding of plant stress and tree development, as well as for climate change studies. However, monitoring the location of the tree line position and potential movement is difficult due to cost and technical challenges, as well as a lack of a clear boundary. Advanced remote sensing technologies such as Light Detection and Ranging (LiDAR) offer significant potential to map short individual tree crowns within the transition zone despite the lack of predictive capacity. Process-based forest growth models offer a complementary approach by quantifying the environmental stresses trees experience at the tree line, allowing transition zones to be defined and ultimately mapped. In this study, we investigate the role remote sensing and physiological, ecosystem-based modeling can play in the delineation of the alpine tree line. To do so, we utilize airborne LiDAR data to map tree height and stand density across a series of altitudinal gradients from below to above the tree line within the Swiss National Park (SNP), Switzerland. We then utilize a simple process-based model to assess the importance of seasonal variations on four climatically related variables that impose non-linear constraints on photosynthesis. Our results indicate that all methods predict the tree line to within a 50 m altitudinal zone and indicate that aspect is not a driver of significant variations in tree line position in the region. Tree cover, rather than tree height is the main discriminator of the tree line at higher elevations. Temperatures in fall and spring are responsible for the major differences along altitudinal zones, however, changes in evaporative demand also control plant growth at lower altitudes. Our results indicate that the two methods provide complementary information on tree line location and, when combined, provide additional insights into potentially endangered
Huffaker, R. Milton; Targ, Russell
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.
Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John Y.
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.
Federal Emergency Management Agency, Department of Homeland Security — This is collection level metadata for LAS and ASCII data files from the statewide Iowa Lidar Project. The Iowa Light Detection and Ranging (LiDAR) Project collects...
Idris, R.; Latif, Z. A.; Hamid, J. R. A.; Jaafar, J.; Ahmad, M. Y.
A 3D building model of man-made objects is an important tool for various applications such as urban planning, flood mapping and telecommunication. The reconstruction of 3D building models remains difficult. No universal algorithms exist that can extract all objects in an image successfully. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) technology have changed the conventional method of topographic mapping and increased the interest of these valued datasets towards 3D building model construction. Airborne LiDAR has proven accordingly that it can provide three dimensional (3D) information of the Earth surface with high accuracy. In this study, with the availability of open source software such as Sketch Up, LiDAR datasets and photographic images could be integrated towards the construction of a 3D building model. In order to realize the work an area comprising residential areas situated at Putrajaya in the Klang Valley region, Malaysia, covering an area of two square kilometer was chosen. The accuracy of the derived 3D building model is assessed quantitatively. It is found that the difference between the vertical height (z) of the 3D building models derived from LiDAR dataset and ground survey is approximately ± 0.09 centimeter (cm). For the horizontal component (RMSExy), the accuracy estimates derived for the 3D building models were ± 0.31m. The result also shows that the qualitative assessment of the 3D building models constructed seems feasible for the depiction in the standard of LOD 3 (Level of details).
Idris, R; Latif, Z A; Hamid, J R A; Jaafar, J; Ahmad, M Y
A 3D building model of man-made objects is an important tool for various applications such as urban planning, flood mapping and telecommunication. The reconstruction of 3D building models remains difficult. No universal algorithms exist that can extract all objects in an image successfully. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) technology have changed the conventional method of topographic mapping and increased the interest of these valued datasets towards 3D building model construction. Airborne LiDAR has proven accordingly that it can provide three dimensional (3D) information of the Earth surface with high accuracy. In this study, with the availability of open source software such as Sketch Up, LiDAR datasets and photographic images could be integrated towards the construction of a 3D building model. In order to realize the work an area comprising residential areas situated at Putrajaya in the Klang Valley region, Malaysia, covering an area of two square kilometer was chosen. The accuracy of the derived 3D building model is assessed quantitatively. It is found that the difference between the vertical height (z) of the 3D building models derived from LiDAR dataset and ground survey is approximately ± 0.09 centimeter (cm). For the horizontal component (RMSExy), the accuracy estimates derived for the 3D building models were ± 0.31m. The result also shows that the qualitative assessment of the 3D building models constructed seems feasible for the depiction in the standard of LOD 3 (Level of details)
Brovkina, Olga; Zemek, František; Fabiánek, Tomáš
Roč. 8, č. 1 (2015), s. 35-46 ISSN 1803-2451 R&D Projects: GA MŠk(CZ) LO1415; GA MŠk OC09001 Institutional support: RVO:67179843 Keywords : forest aboveground biomass * hyperspectral data * airborne LiDAR * Beskydy Mountains Subject RIV: EH - Ecology, Behaviour
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
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...
Hans-Erik Andersen; Stephen E. Reutebuch; Robert J. McGaughey
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...
Murray C. Richardson; Carl P. J. Mitchell; Brian A. Branfireun; Randall K. Kolka
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...
Fauzi Nordin, Ahmad; Jamil, Hassan; Noor Isa, Mohd
Airborne gravimetry is an effective tool for mapping local gravity fields using a combination of airborne sensors, aircraft and positioning systems. It is suitable for gravity surveys over difficult terrains and areas mixed with land and ocean. This paper describes the geological mapping of Sabah...... using airborne gravity surveys. Airborne gravity data over land areas of Sabah has been combined with the marine airborne gravity data to provide a seamless land-to-sea gravity field coverage in order to produce the geological mapping. Free-air and Bouguer anomaly maps (density 2.67 g/cm3) have been...... gravity data were 5-6 km. The airborne gravity survey database for landand marine areas has been compiled using ArcGIS geodatabase format in order to produce the update geological map of Sabah....
S. C. Huang
Full Text Available Forest canopy structure is composed by the various species. Sun light is a main factor to affect the crown structures after tree competition. However, thinning operation is an appropriate way to control canopy density, which can adjust the competition conditions in the different crown structures. Recently, Airborne Light Detection and Ranging (LiDAR, has been established as a standard technology for high precision three dimensional forest data acquisition; it could get stand characteristics with three-dimensional information that had develop potential for the structure characteristics of forest canopy. The 65 years old, different planting density of Cryptomeria japonica experiment area was selected for this study in Nanytou, Taiwan. Use the LiDAR image to estimate LiDAR characteristic values by constructed CHM, voxel-based LiDAR, mu0ltiple echoes, and assess the accuracy of stand characteristics with intensity values and field data. The competition index was calculated with field data, and estimate competition index of LiDAR via multiple linear regression. The results showed that the highest accuracy with stand characteristics was stand high which estimate by LiDAR, its average accuracy of 91.03%. LiDAR raster grid size was 20 m × 20 m for the correlation was the best, however, the higher canopy density will reduce the accuracy of the LiDAR characteristic values to estimate the stand characteristics. The significantly affect canopy thickness and the degree of competition in different planting distances.
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.
Riris, Haris; Numata, Kenji; Wu, Stewart; Gonzalez, Brayler; Rodriguez, Michael; Scott, Stan; Kawa, Stephan; Mao, Jianping
We report on an airborne demonstration of atmospheric methane (CH4) measurements with an integrated path differential absorption lidar using an optical parametric amplifier and optical parametric oscillator laser transmitter and sensitive avalanche photodiode detector. The lidar measures the atmospheric CH4 absorption at multiple, discrete wavelengths near 1650.96 nm. The instrument was deployed in the fall of 2015, aboard NASA's DC-8 airborne laboratory along with an in situ spectrometer and measured CH4 over a wide range of surfaces and atmospheric conditions from altitudes of 2 to 13 km. We will show the results from our flights, compare the performance of the two laser transmitters, and identify areas of improvement for the lidar.
Riris, Haris; Numata, Kenji; Wu, Stewart; Gonzalez, Brayler; Rodriguez, Michael; Scott, Stan; Kawa, Stephan; Mao, Jianping
We report on an airborne demonstration of atmospheric methane (CH 4 ) measurements with an Integrated Path Differential Absorption (IPDA) lidar using an optical parametric amplifier (OPA) and optical parametric oscillator (OPO) laser transmitter and sensitive avalanche photodiode detector. The lidar measures the atmospheric CH 4 absorption at multiple, discrete wavelengths near 1650.96 nm. The instrument was deployed in the fall of 2015, aboard NASA's DC-8 airborne laboratory along with an in-situ spectrometer and measured CH 4 over a wide range of surfaces and atmospheric conditions from altitudes of 2 km to 13 km. In this paper, we will show the results from our flights, compare the performance of the two laser transmitters, and identify areas of improvement for the lidar.
Liu, Jing; Skidmore, Andrew K.; Jones, Simon; Wang, Tiejun; Heurich, Marco; Zhu, Xi; Shi, Yifang
Gap fraction (Pgap) and vertical gap fraction profile (vertical Pgap profile) are important forest structural metrics. Accurate estimation of Pgap and vertical Pgap profile is therefore critical for many ecological applications, including leaf area index (LAI) mapping, LAI profile estimation and wildlife habitat modelling. Although many studies estimated Pgap and vertical Pgap profile from airborne LiDAR data, the scan angle was often overlooked and a nadir view assumed. However, the scan angle can be off-nadir and highly variable in the same flight strip or across different flight strips. In this research, the impact of off-nadir scan angle on Pgap and vertical Pgap profile was evaluated, for several forest types. Airborne LiDAR data from nadir (0°∼7°), small off-nadir (7°∼23°), and large off-nadir (23°∼38°) directions were used to calculate both Pgap and vertical Pgap profile. Digital hemispherical photographs (DHP) acquired during fieldwork were used as references for validation. Our results show that angular Pgap from airborne LiDAR correlates well with angular Pgap from DHP (R2 = 0.74, 0.87, and 0.67 for nadir, small off-nadir and large off-nadir direction). But underestimation of Pgap from LiDAR amplifies at large off-nadir scan angle. By comparing Pgap and vertical Pgap profiles retrieved from different directions, it is shown that scan angle impact on Pgap and vertical Pgap profile differs amongst different forest types. The difference is likely to be caused by different leaf angle distribution and canopy architecture in these forest types. Statistical results demonstrate that the scan angle impact is more severe for plots with discontinuous or sparse canopies. These include coniferous plots, and deciduous or mixed plots with between-crown gaps. In these discontinuous plots, Pgap and vertical Pgap profiles are maximum when observed from nadir direction, and then rapidly decrease with increasing scan angle. The results of this research have many
During an international intercomparison exercise of airborne gamma spectrometry held in Switzerland 2007 teams from Germany, France and Switzerland were proving their capabilities. One of the tasks was the composite mapping of an area around Basel. Each team was mainly covering the part of its own country at its own flying procedures. They delivered the evaluated data in a data format agreed in advance. The quantities to be delivered were also defined in advance. Nevertheless, during the process to put the data together a few questions raised: Which dose rate was meant? Had the dose rate to be delivered with or without cosmic contribution? Activity per dry or wet mass? Which coordinate system was used? Finally, the data could be put together in one map. For working procedures in case of an emergency, quantities of interest and exchange data format have to be defined in advance. But the procedures have also to be proved regularly. (author)
Greaves, Heather E.
Climate change is disproportionately affecting high northern latitudes, and the extreme temperatures, remoteness, and sheer size of the Arctic tundra biome have always posed challenges that make application of remote sensing technology especially appropriate. Advances in high-resolution remote sensing continually improve our ability to measure characteristics of tundra vegetation communities, which have been difficult to characterize previously due to their low stature and their distribution in complex, heterogeneous patches across large landscapes. In this work, I apply terrestrial lidar, airborne lidar, and high-resolution airborne multispectral imagery to estimate tundra vegetation characteristics for a research area near Toolik Lake, Alaska. Initially, I explored methods for estimating shrub biomass from terrestrial lidar point clouds, finding that a canopy-volume based algorithm performed best. Although shrub biomass estimates derived from airborne lidar data were less accurate than those from terrestrial lidar data, algorithm parameters used to derive biomass estimates were similar for both datasets. Additionally, I found that airborne lidar-based shrub biomass estimates were just as accurate whether calibrated against terrestrial lidar data or harvested shrub biomass--suggesting that terrestrial lidar potentially could replace destructive biomass harvest. Along with smoothed Normalized Differenced Vegetation Index (NDVI) derived from airborne imagery, airborne lidar-derived canopy volume was an important predictor in a Random Forest model trained to estimate shrub biomass across the 12.5 km2 covered by our lidar and imagery data. The resulting 0.80 m resolution shrub biomass maps should provide important benchmarks for change detection in the Toolik area, especially as deciduous shrubs continue to expand in tundra regions. Finally, I applied 33 lidar- and imagery-derived predictor layers in a validated Random Forest modeling approach to map vegetation
Michelin, J.-C.; Mallet, C.; David, N.
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.
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.
Harding, David J.; Haugerud, Ralph A.; Johnson, Samuel Y.; Scott, Kevin M.; Weaver, Craig S.; Martinez, Diana M.; Zeigler, John C.; Latypov, Damir
Airborne laser swath mapping (ALSM) of the Puget Lowland conducted by TerraPoint LLC for the Purget Sound Lidar Concortium (PSLC), has been successful in revealing Holocene fault scarps and lendsliders hidden beneath the dense, temperate rain forest cover and in quantifying shoreline terrace uplift. Expanding the PSLC efforts, NASA-USGS collaboration is now focusing on topographic mapping of seismogenic zones adjacent to volcanois in the western Cascades range in order to assess the presence of active faulting and tectonic deformation, better define the extend of lahars and understand their flow processes, and characterize landslide occurrence. Mapping of the western Rainier zone (WRZ) was conducted by TerraPoint in late 2002, after leaf fall and before snow accumulation. The WRZ is a NNW-trending, approx. 30 km-long zone of seismicity west of Mount Rainier National Park. The Puget Lowland ALSM methods were modified to accommodate challenges posed by the steep, high relief terrian. The laser data, acquired with a density of approx. 2 pulses /sq m, was filtered to identify returns from the ground from which a bare Earth digital elevation model (DEM) was produced with a grid size of 1.8 m. The RMS elevation accuracy of the DEM in flat, unvegetated areas is approx. 10cm based on consistency between overlapping flight swaths and comparisons to ground control points. The resulting DEM substantially improves upon Shuttle Radar Topography Mission and USGS photogrammetric mapping. For example, the DEM defines the size and spatial distribution of flood erratics left by the Electron lahar and of megaclasts within the Round Pass lahar, important for characterizing the lahar hydraulics. A previously unknown lateral levee on the Round Pass lahar is also revealed. In addition, to illustrating geomorfic feature within the WRZ, future plans for laser mapping of the Saint Helens and Darrington seismic zones will be described.
Taramelli, A.; Valentini, E.; Filipponi, F.; Cappucci, S.
A synoptic view of the coastal seascape and its dynamics needs a quantitative ability to dissect different components over the complexity of the seafloor where a mixture of geo - biological facies determines geomorphological features and their coverage. The present study uses an analytical approach that takes advantage of a multidimensional model to integrate different data sources from airborne Hyperspectral and LiDAR remote sensing and in situ measurements to detect antropogenic features and ecological `tipping points' in coastal seafloors. The proposed approach has the ability to generate coastal seabed maps using: 1) a multidimensional dataset to account for radiometric and morphological properties of waters and the seafloor; 2) a field spectral library to assimilate the high environmental variability into the multidimensional model; 3) a final classification scheme to represent the spatial gradients in the seafloor. The spatial pattern of the response to anthropogenic forcing may be indistinguishable from patterns of natural variability. It is argued that this novel approach to define tipping points following anthropogenic impacts could be most valuable in the management of natural resources and the economic development of coastal areas worldwide. Examples are reported from different sites of the Mediterranean Sea, both from Marine Protected and un-Protected Areas.
Young, Michael; Andrews, John; Caldwell, Todd; Saylam, Kutalmis
The desert Southwestern United States serves as the host to the habitat for several threatened and endangered species, one of which is the desert tortoise (Gopherus agassizii). The goal in this study was to develop a fine-scale, remote sensing-based model that predicts potential habitat locations of G. agassizii in the Boulder City (Nevada) Conversation Easement area (35,500 hectares). This was done by analyzing airborne Lidar data (5-7 points/m2) and color imagery (4 bands, 0.15 m resolution) and determining percent vegetation cover, shrub height and area, NDVI, and several geomorphic characteristics including slope, azimuth, roughness, etc. Other field data used herein include estimates of canopy area and species richness using 1271 line transects, and shrub height and canopy area using plant-specific measurements of 200 plants. Larrea tridentada and Ambrosia dumosa shrubs were identified using an algorithm that obtained an optimum combination of NDVI and average reflectance of the four bands (IR, R, G, B) from pixels in each image. Results identified more than 65 million shrubs across the study area, and indicate that percent vegetation cover from the aerial imagery across the site (13.92%) compared favorably (14.52%) to the estimate obtained from the line transects, though the lidar method yielded shrub heights approximately 60% of measured shrub heights. Plants and landscape properties were combined with known locations of tortoise burrows (visually observed in 2014), yielding a predictive model of potential tortoise habitats. Masks were created using roughness coefficient, slope percent, azimuth of burrow openings, elevation and percent ground cover to isolate areas more likely to host habitats. Combined together, the masks isolated 55% of the total survey area, which would help target future field surveys. Overall, the vegetation map superimposed onto the background soil data could estimate the location of tortoise burrows.
Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.
The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the
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.
Juan Carlos Fernandez-Diaz
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.
Full Text Available In order to meet the requirements of the European Water Framework Directive (EU-WFD, authorities face the problem of repeatedly performing area-wide surveying of all kinds of inland waters. Especially for mid-sized or small rivers this is a considerable challenge imposing insurmountable logistical efforts and costs. It is therefore investigated if large-scale surveying of a river system on an operational basis is feasible by employing airborne hydrographic laser scanning. In cooperation with the Bavarian Water Authority (WWA Weilheim a pilot project was initiated by the Unit of Hydraulic Engineering at the University of Innsbruck and RIEGL Laser Measurement Systems exploiting the possibilities of a new LIDAR measurement system with high spatial resolution and high measurement rate to capture about 70 km of riverbed and foreland for the river Loisach in Bavaria/Germany and the estuary and parts of the shoreline (about 40km in length of lake Ammersee. The entire area surveyed was referenced to classic terrestrial cross-section surveys with the aim to derive products for the monitoring and managing needs of the inland water bodies forced by the EU-WFD. The survey was performed in July 2011 by helicopter and airplane and took 3 days in total. In addition, high resolution areal images were taken to provide an optical reference, offering a wide range of possibilities on further research, monitoring, and managing responsibilities. The operating altitude was about 500 m to maintain eye-safety, even for the aided eye, the airspeed was about 55 kts for the helicopter and 75 kts for the aircraft. The helicopter was used in the alpine regions while the fixed wing aircraft was used in the plains and the urban area, using appropriate scan rates to receive evenly distributed point clouds. The resulting point density ranged from 10 to 25 points per square meter. By carefully selecting days with optimum water quality, satisfactory penetration down to the river
Full Text Available This work presents a combined bottom-up and top-down approach to extraction and refinement of building footprints from airborne LIDAR data. Building footprints are interesting for many applications in urban planning. The cadastral maps, however, may be limited for certain areas or not be updated frequently. Airborne laser scanning data is therefore considered by many people in the last decade as an important alternative data for change detection and update of building footprints. Laser scanning data of city scenes, however, often shows noise and incompleteness because of, e.g., the clutter by vegetation and the reflection of windows/waterlogged depressions on the roof. Results of the bottom-up detection may thus be limited to incomplete or irregular polygons. We employ 3D Hough transform to detect the building points. An improved joint multiple-plane detection scheme is proposed to find and label the laser points on multiple roof facets synchronously. The bottom-up processing provides not only a rough point segmentation but also additional 3D information, e.g., roof heights and horizontal ridges. Using these as priors, a top-down reconstruction is conducted via generative models. We consider the building footprint as an assembly of regular primitives. A statistical search by means of Reversible Jump Markov Chain Monte Carlo and Maximum A Posteriori estimation is implemented to find the optimal configuration of the footprint. By these means a robust and plausible reconstruction is guaranteed. First results on point clouds with various resolutions show the potential of this approach.
McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.
Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser
Baldeck, C. A.; Colgan, M.; Féret, J.; Asner, G. P.
Airborne remote sensing data provide promising opportunities for species identification of individual tree and shrub crowns across large areas which cannot be mapped from the ground. Previous investigations of the potential for species identification of crowns from airborne data have focused on pixel-level information (0.5-1m2), and thus have been unable to take advantage of the structural information that exist at the crown level. Hyperspectral data consisting of 58 bands from 517 to 1054nm and LiDAR (light detection and ranging) data providing vegetation height information were acquired over several landscapes within Kruger National Park, South Africa, by the CAO in 2008 at 1.1m spatial resolution. Over 1,000 individual trees and shrubs were mapped and identified in the field to construct species spectral and structural libraries. We used stacked support vector machines (SVM) that incorporate pixel-level spectral information and crown-level structural information to predict species identity for individual tree crowns. The addition of a crown-level classification step that incorporates crown structural information significantly improved model accuracy by ~6% and our prediction accuracy of the final model was ~75% for 16 species classes. This model was then used to predict the species identity of individual crowns across multiple airborne-mapped landscapes, made possible by an automated crown segmentation algorithm. The resultant species maps will make it possible to examine the environmental controls over individual species distributions and tree community composition, and provide important landscape-scale species distribution information relevant to park management and conservation.
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.
Riris, Haris; Rodriquez, Michael; Allan, Graham R.; Hasselbrack, William E.; Stephen, Mark A.; Abshire, James B.
We report on airborne measurements of atmospheric pressure using a fiber-laser based lidar operating in the oxygen A-band near 765 nm and the integrated path differential absorption measurement technique. Our lidar uses fiber optic technology and non-linear optics to generate tunable laser radiation at 765 nm, which overlaps an absorption line pair in the Oxygen A-band. We use a pulsed time resolved technique, which rapidly steps the laser wavelength across the absorption line pair, a 20 cm telescope and photon counting detector to measure Oxygen concentrations.
Low-height vegetation, common in semiarid regions, is difficult to characterize with LiDAR (Light Detection and Ranging) due to similarities, in time and space, of the point returns of vegetation and ground. Other complications may occur due to the low-height vegetation structural characteristics a...
Martinuzzi, S.; Cook, B.; Corp, L. A.; Morton, D. C.; Helmer, E.; Keller, M.
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.
Full Text Available The Mobile LiDAR Mapping System StreetMapper from IGI and 3D Laser Mapping (Bingham Nottingham, UK is mounted on a large variety of road vehicles to cover different mission specifications. In addition to the operation on the road, the system finds its applications on other kinds of vehicles, like boats or trains. The modular and flexible system concept even allows utilizing the same LiDAR Mapping system for Mobile Mapping on the ground and for airborne missions on helicopters, respectively. Besides this general flexibility, each application has its own special requirements. Special hardware and software components are needed to complete the core components, like the laser scanner and the GNSS/IMU systems, to build a dedicated system for the chosen task. Compared to the typical dynamics of a road vehicle mounted Mobile Mapping system, a dedicated rail mapping system operates under conditions that are much more challenging for a high accuracy GNSS/IMU trajectory determination. Furthermore, the typical rail mapping tasks, like the exact measurement of the rail track geometry, require the operation of the most accurate laser scanners and of specialized post-processing software. In this paper, the RailMapper, a specialized Mobile Mapping system for railway surveys is presented. The system is described with focus on the railway specific requirements and results of practical surveys are given.
National Oceanic and Atmospheric Administration, Department of Commerce — These data are the lidar points collected for FEMA Risk Mapping, Assessment, and Planning (Risk MAP) for the Nashua River Watershed. This area falls in portions of...
Tulldahl, H. Michael; Larsson, Hâkan
Small UAV:s (Unmanned Aerial Vehicles) are currently in an explosive technical development phase. The performance of UAV-system components such as inertial navigation sensors, propulsion, control processors and algorithms are gradually improving. Simultaneously, lidar technologies are continuously developing in terms of reliability, accuracy, as well as speed of data collection, storage and processing. The lidar development towards miniature systems with high data rates has, together with recent UAV development, a great potential for new three dimensional (3D) mapping capabilities. Compared to lidar mapping from manned full-size aircraft a small unmanned aircraft can be cost efficient over small areas and more flexible for deployment. An advantage with high resolution lidar compared to 3D mapping from passive (multi angle) photogrammetry is the ability to penetrate through vegetation and detect partially obscured targets. Another advantage is the ability to obtain 3D data over the whole survey area, without the limited performance of passive photogrammetry in low contrast areas. The purpose of our work is to demonstrate 3D lidar mapping capability from a small multirotor UAV. We present the first experimental results and the mechanical and electrical integration of the Velodyne HDL-32E lidar on a six-rotor aircraft with a total weight of 7 kg. The rotating lidar is mounted at an angle of 20 degrees from the horizontal plane giving a vertical field-of-view of 10-50 degrees below the horizon in the aircraft forward directions. For absolute positioning of the 3D data, accurate positioning and orientation of the lidar sensor is of high importance. We evaluate the lidar data position accuracy both based on inertial navigation system (INS) data, and on INS data combined with lidar data. The INS sensors consist of accelerometers, gyroscopes, GPS, magnetometers, and a pressure sensor for altimetry. The lidar range resolution and accuracy is documented as well as the
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.
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.
Chust, Guillem; Galparsoro, Ibon; Borja, Ángel; Franco, Javier; Uriarte, Adolfo
The airborne laser scanning LIDAR (LIght Detection And Ranging) provides high-resolution Digital Terrain Models (DTM) that have been applied recently to the characterization, quantification and monitoring of coastal environments. This study assesses the contribution of LIDAR altimetry and intensity data, topographically-derived features (slope and aspect), and multi-spectral imagery (three visible and a near-infrared band), to map coastal habitats in the Bidasoa estuary and its adjacent coastal area (Basque Country, northern Spain). The performance of high-resolution data sources was individually and jointly tested, with the maximum likelihood algorithm classifier in a rocky shore and a wetland zone; thus, including some of the most extended Cantabrian Sea littoral habitats, within the Bay of Biscay. The results show that reliability of coastal habitat classification was more enhanced with LIDAR-based DTM, compared with the other data sources: slope, aspect, intensity or near-infrared band. The addition of the DTM, to the three visible bands, produced gains of between 10% and 27% in the agreement measures, between the mapped and validation data (i.e. mean producer's and user's accuracy) for the two test sites. Raw LIDAR intensity images are only of limited value here, since they appeared heterogeneous and speckled. However, the enhanced Lee smoothing filter, applied to the LIDAR intensity, improved the overall accuracy measurements of the habitat classification, especially in the wetland zone; here, there were gains up to 7.9% in mean producer's and 11.6% in mean user's accuracy. This suggests that LIDAR can be useful for habitat mapping, when few data sources are available. The synergy between the LIDAR data, with multi-spectral bands, produced high accurate classifications (mean producer's accuracy: 92% for the 16 rocky habitats and 88% for the 11 wetland habitats). Fusion of the data enabled discrimination of intertidal communities, such as Corallina elongata
Obland, Michael D.; Hostetler, Chris A.; Ferrare, Richard A.; Hair, John W.; Roers, Raymond R.; Burton, Sharon P.; Cook, Anthony L.; Harper, David B.
Since achieving first light in December of 2005, the NASA Langley Research Center (LaRC) Airborne High Spectral Resolution Lidar (HSRL) has been involved in seven field campaigns, accumulating over 450 hours of science data across more than 120 flights. Data from the instrument have been used in a variety of studies including validation and comparison with the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite mission, aerosol property retrievals combining passive and active instrument measurements, aerosol type identification, aerosol-cloud interactions, and cloud top and planetary boundary layer (PBL) height determinations. Measurements and lessons learned from the HSRL are leading towards next-generation HSRL instrument designs that will enable even further studies of aerosol intensive and extensive parameters and the effects of aerosols on the climate system. This paper will highlight several of the areas in which the NASA Airborne HSRL is making contributions to climate science.
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.
During an international intercomparison exercise of airborne gamma spectrometry held in Switzerland 2007 teams from Germany, France and Switzerland were proving their capabilities. One of the tasks was the composite mapping of an area around Basel. Each team was mainly covering the part of its own country at its own flying procedures. They delivered the evaluated data in a data format agreed in advance. The quantities to be delivered were also defined in advance. Nevertheless, during the process to put the data together a few questions raised: Which dose rate was meant? Had the dose rate to be delivered with or without cosmic contribution? Activity per dry or wet mass? Which coordinate system was used? Finally, the data could be put together in one map. For working procedures in case of an emergency, quantities of interest and exchange data format have to be defined in advance. But the procedures have also to be proved regularly. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: email@example.com.
Russell A. White
Full Text Available LiDAR-derived digital elevation models can reveal road networks located beneath dense forest canopy. This study tests the accuracy of forest road characteristics mapped using LiDAR in the Santa Cruz Mountains, CA. The position, gradient, and total length of a forest haul road were accurately extracted using a 1 m DEM. In comparison to a field-surveyed centerline, the LiDAR-derived road exhibited a positional accuracy of 1.5 m, road grade measurements within 0.53% mean absolute difference, and total road length within 0.2% of the field-surveyed length. Airborne LiDAR can provide thorough and accurate road inventory data to support forest management and watershed assessment activities.
Full Text Available The frequency of debris flow events caused by severe rainstorms has increased in Korea. LiDAR provides high-resolution topographical data that can represent the land surface more effectively than other methods. This study describes the analysis of geomorphologic changes using digital surface models derived from airborne LiDAR and aerial image data acquired before and after a debris flow event in the southern part of Seoul, South Korea in July 2011. During this event, 30 houses were buried, 116 houses were damaged, and 22 human casualties were reported. Longitudinal and cross-sectional profiles of the debris flow path reconstructed from digital surface models were used to analyze debris flow behaviors such as landslide initiation, transport, erosion, and deposition. LiDAR technology integrated with GIS is a very useful tool for understanding debris flow behavior.
Kim, G.; Yune, C. Y.; Paik, J.; Lee, S. W.
The frequency of debris flow events caused by severe rainstorms has increased in Korea. LiDAR provides high-resolution topographical data that can represent the land surface more effectively than other methods. This study describes the analysis of geomorphologic changes using digital surface models derived from airborne LiDAR and aerial image data acquired before and after a debris flow event in the southern part of Seoul, South Korea in July 2011. During this event, 30 houses were buried, 116 houses were damaged, and 22 human casualties were reported. Longitudinal and cross-sectional profiles of the debris flow path reconstructed from digital surface models were used to analyze debris flow behaviors such as landslide initiation, transport, erosion, and deposition. LiDAR technology integrated with GIS is a very useful tool for understanding debris flow behavior.
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...
Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Refaat, Tamer F.; Remus, Ruben G.; Fay, James J.; Reithmaier, Karl
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.
Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Refaat, Tamer F.; Remus, Ruben G.; Fay, James J.; Reithmaier, Karl
Double-pulse 2-micron lasers have been demonstrated with energy as high as 600 mJ and up to 10 Hz repetition rate. The two laser pulses are separated by 200 µs 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-µm direct detection IPDA lidar for CO2 column measurement from an airborne platform. The presentation will describe the development of the 2-μm 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.
Luo, Shezhou; Wang, Cheng; Xi, Xiaohuan; Pan, Feifei
The fraction of absorbed photosynthetically active radiation (FPAR) is a key parameter for ecosystem modeling, crop growth monitoring and yield prediction. Ground-based FPAR measurements are time consuming and labor intensive. Remote sensing provides an alternative method to obtain repeated, rapid and inexpensive estimates of FPAR over large areas. LiDAR is an active remote sensing technology and can be used to extract accurate canopy structure parameters. A method to estimating FPAR of maize from airborne discrete-return LiDAR data was developed and tested in this study. The raw LiDAR point clouds were processed to separate ground returns from vegetation returns using a filter method over a maize field in the Heihe River Basin, northwest China. The fractional cover (fCover) of maize canopy was computed using the ratio of canopy return counts or intensity sums to the total of returns or intensities. FPAR estimation models were established based on linear regression analysis between the LiDAR-derived fCover and the field-measured FPAR (R(2) = 0.90, RMSE = 0.032, p LiDAR-predicted FPARs and results show that the LiDAR-predicted FPAR has a high accuracy (R(2) = 0.89, RMSE = 0.034). In summary, this study suggests that the airborne discrete-return LiDAR data could be adopted to accurately estimate FPAR of maize.
He, Y.; Zhang, C.; Awrangjeb, M.; Fraser, C. S.
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.
Beyon, Jeffrey Y.; Koch, Grady J.; Kavaya, Michael J.; Ray, Taylor J.
Two versions of airborne wind profiling algorithms for the pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia are presented. Each algorithm utilizes different number of line-of-sight (LOS) lidar returns while compensating the adverse effects of different coordinate systems between the aircraft and the Earth. One of the two algorithms APOLO (Airborne Wind Profiling Algorithm for Doppler Wind Lidar) estimates wind products using two LOSs. The other algorithm utilizes five LOSs. The airborne lidar data were acquired during the NASA's Genesis and Rapid Intensification Processes (GRIP) campaign in 2010. The wind profile products from the two algorithms are compared with the dropsonde data to validate their results.
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
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.
Browell, E. V.; Carter, A. F.; Wilkerson, T. D.
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.
National Aeronautics and Space Administration — An advanced airborne imaging system for fire detection/mapping is proposed. The goal of the project is to improve control and management of wildfires in order to...
National Aeronautics and Space Administration — A high performance, inexpensive, airborne simulator that will serve as the prototype for a small satellite based imaging system capable of mapping thermal anomalies...
Amediek, Axel; Büdenbender, Christian; Ehret, Gerhard; Fix, Andreas; Gerbig, Christoph; Kiemle, Chritstoph; Quatrevalet, Mathieu; Wirth, Martin
CHARM-F is the new airborne four-wavelengths lidar for simultaneous soundings of atmospheric CO2 and CH4. Due to its high technological conformity it is also a demonstrator for MERLIN, the French-German satellite mission providing a methane lidar. MERLIN's Preliminary Design Review was successfully passed recently. The launch is planned for 2020. First CHARM-F measurements were performed in Spring 2015 onboard the German research aircraft HALO. The aircraft's maximum flight altitude of 15 km and special features of the lidar, such as a relatively large laser ground spot, result in data similar to those obtained by a spaceborne system. The CHARM-F and MERLIN lidars are designed in the IPDA (integrated path differential absorption) configuration using short double pulses, which gives column averaged gas mixing ratios between the system and ground. The successfully completed CHARM-F flight measurements provide a valuable dataset, which supports the retrieval algorithm development for MERLIN notably. Furthermore, the dataset allows detailed analyses of measurement sensitivities, general studies on the IPDA principle and on system design questions. These activities are supported by another instrument onboard the aircraft during the flight campaign: 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 aircraft lidar. For the near future, detailed characterizations of CHARM-F are planned, further support of the MERLIN design, as well as the scientific aircraft campaign CoMet.
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.
Hashemi Beni, L.; McArdle, S.; Khayer, Y.
As urbanization continues to increase and extreme climatic events become more prevalent, urban planners and engineers are actively implementing adaptive measures to protect urban assets and communities. To support the urban planning adaptation process, mapping of impervious and pervious areas is essential to understanding the hydrodynamic environment within urban areas for flood risk planning. The application of advance geospatial data and analytical techniques using remote sensing and GIS can improve land surface characterization to better quantify surface run-off and infiltration. This study presents a method to combine airborne hyperspectral and LiDAR data for classifying pervious (e.g. vegetation, gravel, and soil) and impervious (e.g. asphalt and concrete) areas within road allowance areas for the City of Surrey, British Columbia, Canada. Hyperspectral data was acquired using the Compact Airborne Spectrographic Imager (CASI) at 1 m ground spatial resolution, consisting of 72 spectral bands, and LiDAR data acquired from Leica Airborne LiDAR system at a density of 20 points/m2. A spectral library was established using 10 cm orthophotography and GIS data to identify surface features. In addition to spectral functions such as mean and standard deviation, several spectral indices were developed to discriminate between asphalt, concrete, gravel, vegetation, and shadows respectively. A spectral analysis of selected endmembers was conducted and an initial classification technique was applied using Spectral Angle Mapper (SAM). The classification results (i.e. shadows) were improved by integrating LIDAR data with the hyperspectral data.
Full Text Available Unmanned Aerial System (UAS technology is nowadays willingly used in small area topographic mapping due to low costs and good quality of derived products. Since cameras typically used with UAS have some limitations, e.g. cannot penetrate the vegetation, LiDAR sensors are increasingly getting attention in UAS mapping. Sensor developments reached the point when their costs and size suit the UAS platform, though, LiDAR UAS is still an emerging technology. One issue related to using LiDAR sensors on UAS is the limited performance of the navigation sensors used on UAS platforms. Therefore, various hardware and software solutions are investigated to increase the quality of UAS LiDAR point clouds. This work analyses several aspects of the UAS LiDAR point cloud generation performance based on UAS flights conducted with the Velodyne laser scanner and cameras. The attention was primarily paid to the trajectory reconstruction performance that is essential for accurate point cloud georeferencing. Since the navigation sensors, especially Inertial Measurement Units (IMUs, may not be of sufficient performance, the estimated camera poses could allow to increase the robustness of the estimated trajectory, and subsequently, the accuracy of the point cloud. The accuracy of the final UAS LiDAR point cloud was evaluated on the basis of the generated DSM, including comparison with point clouds obtained from dense image matching. The results showed the need for more investigation on MEMS IMU sensors used for UAS trajectory reconstruction. The accuracy of the UAS LiDAR point cloud, though lower than for point cloud obtained from images, may be still sufficient for certain mapping applications where the optical imagery is not useful.
Craine, Eric R.; Craine, B. L.; Craine, E. M.; Craine, P. R.
Widespread installation of inefficient and misdirected artificial light at night (LAN) has led to increasing concerns about light pollution and its impact, not only on astronomical facilities but larger communities as well. Light pollution impacts scientific research, environmental ecosystems, human health, and quality of life. In recent years, the public policy response to light pollution has included formulation of government codes to regulate lighting design and installation. Various environmental groups now include light pollution among their rallying themes to protest both specific and general developments. The latter efforts are often conducted in the absence of any quantitative data and are frequently charged by emotion rather than reason. To bring some scientific objectivity, and quantitative data, to these discussions, we have developed a suite of tools for simultaneous photometric measurements and temporal monitoring of both local communities and the sky overhead. We have also developed novel protocols for the use of these tools, including a triad of airborne, ground mobile, and ground static photometric surveys. We present a summary of these tools and protocols, with special emphasis on the airborne systems, and discuss baseline and follow-up measurements of LAN environments in the vicinity of numerous observatories in Arizona, the home of the initial LAN MAP surveys.
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.
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
Full Text Available Accurate and efficient species-based marine habitat assessment is in great demand for the marine environment. Remote sensing techniques including airborne light detection and ranging (LiDAR derived bathymetry can now be used, in concert with suitable ground truthing, to produce marine habitat maps over wide areas. Hydrodynamic conditions, e.g., current speeds and wave exposure influence habitat types through direct impact on marine organisms, as well as influence on sediment transport and, hence, substrate type. Habitat classification and mapping was carried out using both LiDAR derivatives and hydrodynamic parameters derived from numerical modelling at a location off the coast of Port Hedland in the Pilbara region of Western Australia, 1660 km north of Perth. Habitat classes included seagrass, algae, invertebrates, hard coral, and areas where there is no evident epibenthos. The inclusion of the hydrodynamic parameters significantly increased the accuracy of the classification by 7.7% when compared to using LiDAR derivatives alone.
Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Antill, Charles W.; Remus, Ruben; Yu, Jirong
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.
S. P. Burton
Full Text Available The NASA Langley Research Center (LaRC airborne High Spectral Resolution Lidar (HSRL on the NASA B200 aircraft has acquired extensive datasets of aerosol extinction (532 nm, aerosol optical depth (AOD (532 nm, backscatter (532 and 1064 nm, and depolarization (532 and 1064 nm profiles during 18 field missions that have been conducted over North America since 2006. The lidar measurements of aerosol intensive parameters (lidar ratio, depolarization, backscatter color ratio, and spectral depolarization ratio are shown to vary with location and aerosol type. A methodology based on observations of known aerosol types is used to qualitatively classify the extensive set of HSRL aerosol measurements into eight separate types. Several examples are presented showing how the aerosol intensive parameters vary with aerosol type and how these aerosols are classified according to this new methodology. The HSRL-based classification reveals vertical variability of aerosol types during the NASA ARCTAS field experiment conducted over Alaska and northwest Canada during 2008. In two examples derived from flights conducted during ARCTAS, the HSRL classification of biomass burning smoke is shown to be consistent with aerosol types derived from coincident airborne in situ measurements of particle size and composition. The HSRL retrievals of AOD and inferences of aerosol types are used to apportion AOD to aerosol type; results of this analysis are shown for several experiments.
Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Antill, Charles W.; Remus, Ruben; Yu, Jirong
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.
Thapa, R. B.; Watanabe, M.; Motohka, T.; Shiraishi, T.; shimada, M.
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
Full Text Available The common statistical methods for supervised classification usually require a large amount of training data to achieve reasonable results, which is time consuming and inefficient. In many methods, only the features of each point are used, regardless of their spatial distribution within a certain neighborhood. This paper proposes a tensor-based sparse representation classification (TSRC method for airborne LiDAR (Light Detection and Ranging points. To keep features arranged in their spatial arrangement, each LiDAR point is represented as a 4th-order tensor. Then, TSRC is performed for point classification based on the 4th-order tensors. Firstly, a structured and discriminative dictionary set is learned by using only a few training samples. Subsequently, for classifying a new point, the sparse tensor is calculated based on the tensor OMP (Orthogonal Matching Pursuit algorithm. The test tensor data is approximated by sub-dictionary set and its corresponding subset of sparse tensor for each class. The point label is determined by the minimal reconstruction residuals. Experiments are carried out on eight real LiDAR point clouds whose result shows that objects can be distinguished by TSRC successfully. The overall accuracy of all the datasets is beyond 80% by TSRC. TSRC also shows a good improvement on LiDAR points classification when compared with other common classifiers.
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...
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...
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...
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...
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...
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...
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...
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...
Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico coastline of MS in 2009. The data...
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...
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....
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...
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...
Full Text Available To improve the extraction accuracy for airborne LiDAR bathymetry,a signal extraction method based on deconvolution is introduced in waveform processing in this paper.The received waveform is preprocessed by deconvolution,and the accurate positions of the LiDAR signals are determined by the peak detection.For the deconvolution,the validity of four common algorithms,namely,Wiener filter deconvolution,nonnegative least squares,Richardson-Lucy deconvolution and blind deconvolution,are comparatively studied and the performance of the proposed method is assessed by the defined metrics.The experimental results show that the Richardson-Lucy deconvolution can effectively recover the signal resolution with wide adaptation and high success rate.The proposed method compared to the traditional peak detection methods offers a higher detection rate and accuracy and a wider range of bathymetry.
Full Text Available Detection of the damaged building is the obligatory step prior to evaluate earthquake casualty and economic losses. It's very difficult to detect damaged buildings accurately based on the assumption that intact roofs appear in laser data as large planar segments whereas collapsed roofs are characterized by many small segments. This paper presents a contour cluster shape similarity analysis algorithm for reliable building damage detection from the post-earthquake airborne LiDAR point cloud. First we evaluate the entropies of shape similarities between all the combinations of two contour lines within a building cluster, which quantitatively describe the shape diversity. Then the maximum entropy model is employed to divide all the clusters into intact and damaged classes. The tests on the LiDAR data at El Mayor-Cucapah earthquake rupture prove the accuracy and reliability of the proposed method.
Milenković, Milutin; Wagner, Wolfgang; Quast, Raphael; Hollaus, Markus; Ressl, Camillo; Pfeifer, Norbert
Canopy transmittance is a directional and wavelength-specific physical parameter that quantifies the amount of radiation attenuated when passing through a vegetation layer. The parameter has been estimated from LiDAR data in many different ways over the years. While early LiDAR methods treated each returned echo equally or weighted the echoes according to their return order, recent methods have focused more on the echo energy. In this study, we suggest a new method of estimating the total canopy transmittance considering only the energy of ground echoes. Therefore, this method does not require assumptions for the reflectance or absorption behavior of vegetation. As the oblique looking geometry of LiDAR is explicitly considered, canopy transmittance can be derived for individual laser beams and can be mapped spatially. The method was applied on a contemporary full-waveform LiDAR data set collected under leaf-off conditions and over a study site that contains two sub regions: one with a mixed (coniferous and deciduous) forest and another that is predominantly a deciduous forest in an alluvial plain. The resulting canopy transmittance map was analyzed for both sub regions and compared to aerial photos and the well-known fractional cover method. A visual comparison with aerial photos showed that even single trees and small canopy openings are visible in the canopy transmittance map. In comparison with the fractional cover method, the canopy transmittance map showed no saturation, i.e., there was better separability between patches with different vegetation structure.
McKean, J.; Wright, W.; Kinzel, P.; Isaak, D.
Stream environments are structured by complex biophysical processes that operate across multiple spatial and temporal scales. Disentangling these multiscalar and multicausal relationships is difficult, but fundamental to understanding, managing, and monitoring channel aquatic ecosystems. Standard field wading surveys of stream physical habitat are limited by cost and logistics to relatively small, isolated samples. Traditional remotely sensed surveys, including methods such as photogrammetry and near-infrared lidar, suffer from attenuation by water and do not directly map submerged channel topography. The Experimental Advanced Airborne Research Lidar (EAARL) is a full-waveform lidar with a unique ability to simultaneously map, with relatively high resolution, subaqueous and subaerial topography and the vegetation canopy. We have used the EAARL instrument to investigate two dissimilar stream ecosystems. We mapped 40km of low gradient, meandering, gravel-bed streams in central Idaho that are spawning habitat for threatened Chinook salmon. We are using the continuous three-dimensional channel maps to quantitatively explore how channel features affect the distribution of salmon spawning at multiple spatial scales and how modern stream and floodplain topography is related to post-glacial valley evolution. In contrast, the Platte River in central Nebraska is a wide and shallow, sand-bedded river that provides habitat for migratory water birds, including endangered species such as the whooping crane and least tern. Multi-temporal EAARL data are being used to map and monitor the physical response of the Platte River to habitat improvement projects that include in-channel and riparian vegetation removal and river flow augmentation to limit vegetation encroachment.
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.
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.
Riris, Haris; Numata, Kenji; Li, Steve; Wu, Stewart; Ramanathan, Anamd; Dawsey, Martha; Mao, Jianping; Kawa, Randolph; Abshire, James B.
We report airborne measurements of the column abundance of atmospheric methane made over an altitude range of 3-11 km using a direct detection IPDA lidar with a pulsed laser emitting at 1651 nm. The laser transmitter was a tunable, seeded optical parametric amplifier (OPA) pumped by a Nd:YAG laser and the receiver used a photomultiplier detector and photon counting electronics. The results follow the expected changes with aircraft altitude and the measured line shapes and optical depths show good agreement with theoretical calculations.
Guo, Pan; Hao, Qiwei; Chen, Siying
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.
Bulyshev, Alexander; Pierrottet, Diego; Amzajerdian, Farzin; Busch, George; Vanek, Michael; Reisse, Robert
Data from the first Flight Test of the NASA Langley Flash Lidar system have been processed. Results of the analyses are presented and discussed. A digital elevation map of the test site is derived from the data, and is compared with the actual topography. The set of algorithms employed, starting from the initial data sorting, and continuing through to the final digital map classification is described. The accuracy, precision, and the spatial and angular resolution of the method are discussed.
Davis, L. I., Jr.; James, J. V.; Morris, P. T.; Guo, C.; Postiff, R.
Under suitable laboratory conditions, it has been demonstrated that the laser-induced fluorescence (LIF) measurement technique is sensitive enough to detect single atoms and molecules. This potential sensitivity has provided motivation for the development of this technique for ambient OH measurements. The present paper is concerned with an airborne lidar instrument for measuring OH concentration as used for the NASA GTE/CITE (Global Tropospheric Experiment/Chemical Instrumentation Test and Evaluation) intercomparison experiments during the fall of 1983 and the spring of 1984. A description is given of a working airborne instrument for measurements of OH in ambient air. The detection sensitivity demonstrated in the experiments should be sufficient for routine measurements in areas in which the OH concentration is in the range of high 1,000,000 molecule per cu cm or higher.
Lauve, R. M.; Alizad, K.; Hagen, S. C.
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.  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
Kiemle, Christoph; Amediek, Axel; Fix, Andreas; Wirth, Martin; Quatrevalet, Mathieu; Büdenbender, Christian; Ehret, Gerhard
Installed onboard the German research aircraft HALO the integrated-path differential-absorption (IPDA) lidar CHARM-F measures weighted vertical columns of the greenhouse gases CO2 and CH4 below the aircraft and along its flight track aiming at high accuracy and precision. CHARM-F was designed and built as an airborne demonstrator for the space lidar MERLIN, the "Methane Remote Lidar Mission", conducted by the German and French space agencies DLR and CNES with launch foreseen in 2021. It provides excellent opportunities for targeted measurements of regional fluxes and hot spots. We present exemplary measurements from several flights performed in spring 2015 over Central Europe. Our analyses reveal a measurement precision of below 0.5% for 20-km averages. A methane plume from a coal mine ventilation shaft was overflown, as well as a carbon dioxide plume from a large coal-fired power plant. The method to estimate fluxes from the lidar signals will be explained. The results show good agreement with reported emission rates. The airborne measurements are expected to improve the retrieval of future space-borne IPDA lidar systems such as MERLIN. CHARM-F measurements over mountains, water and clouds help assess the strength and variability of backscatter from such challenging surfaces. The IPDA weighting function, or measurement sensitivity, is dependent on atmospheric pressure and temperature. We use ECMWF analyses interpolated in space and time to the aircraft track that provide these auxiliary data. The relatively coarse model representation of orography, with respect to the lidar, causes uncertainties that we assess. CHARM-F will be a key instrument in the upcoming CoMet field experiment, where active and passive remote sensing, as well as in-situ instruments will be installed onboard HALO. The flights are scheduled in April and May 2017 over Central Europe and will focus on point sources such as power plants, coal mines, and landfills, as well as on urban gradients and
Tim L. Webster
Full Text Available A significant portion of the Canadian Maritime coastline has been surveyed with airborne Light Detection and Ranging (LiDAR. The purpose of these surveys has been to map the risk of flooding from storm surges and projected long-term sea‑level rise from climate change and to include projects in all three Maritime Provinces: Prince Edward Island, New Brunswick, and Nova Scotia. LiDAR provides the required details in order to map the flood inundation from 1 to 2 m storm surge events, which cause coastal flooding in many locations in this region when they occur at high tide levels. The community of Annapolis Royal, Nova Scotia, adjacent to the Bay of Fundy, has been surveyed with LiDAR and a 1 m DEM (Digital Elevation Model was constructed for the flood inundation mapping. Validation of the LiDAR using survey grade GPS indicates a vertical accuracy better than 30 cm. A benchmark storm, known as the Groundhog Day storm (February 1–3, 1976, was used to assess the flood maps and to illustrate the effects of different sea-level rise projections based on climate change scenarios if it were to re-occur in 100 years time. Near shore bathymetry has been merged with the LiDAR and local wind observations used to model the impact of significant waves during this benchmark storm. Long-term (ca. greater than 30 years time series of water level observations from across the Bay of Fundy in Saint John, New Brunswick, have been used to estimate return periods of water levels under present and future sea-level rise conditions. Results indicate that under current sea-level rise conditions this storm has a 66 year return period. With a modest relative sea-level (RSL rise of 80 cm/century this decreases to 44 years and, with a possible upper limit rise of 220 cm/century, this decreases further to 22 years. Due to the uncertainty of climate change scenarios and sea-level rise, flood inundation maps have been constructed at 10 cm increments up to the 9 m contour
Chazette, Patrick; Totems, Julien; Flamant, Cyrille; Shang, Xiaoxia; Denjean, Cyrielle; Meynadier, Rémi; Perrin, Thierry; Laurens, Marc
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.
Vaglio Laurin, Gaia; Puletti, Nicola; Chen, Qi; Corona, Piermaria; Papale, Dario; Valentini, Riccardo
Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment.
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.
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; Reithmaier, Karl; Lee, Jane; Ismail, Syed
An airborne 2-μm 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.
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.
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.
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...
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...
Jake E. Simpson
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
Sergeevich Gurvich, Alexander; Alexeevich Kulikov, Victor
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.
Full Text Available The capability of acquiring accurate and dense three-dimensional geospatial information that covers large survey areas rapidly enables airborne light detection and ranging (LiDAR has become a powerful technology in numerous fields of geospatial applications and analysis. LiDAR data filtering is the first and essential step for digital elevation model generation, land cover classification, and object reconstruction. The morphological filtering approaches have the advantages of simple concepts and easy implementation, which are able to filter non-ground points effectively. However, the filtering quality of morphological approaches is sensitive to the structuring elements that are the key factors for the filtering success of mathematical operations. Aiming to deal with the dependence on the selection of structuring elements, this paper proposes a novel filter of LiDAR point clouds based on geodesic transformations of mathematical morphology. In comparison to traditional morphological transformations, the geodesic transformations only use the elementary structuring element and converge after a finite number of iterations. Therefore, this algorithm makes it unnecessary to select different window sizes or determine the maximum window size, which can enhance the robustness and automation for unknown environments. Experimental results indicate that the new filtering method has promising and competitive performance for diverse landscapes, which can effectively preserve terrain details and filter non-ground points in various complicated environments.
Baldeck, C A; Colgan, M S; Féret, J B; Levick, S R; Martin, R E; Asner, G P
Information on landscape-scale patterns in species distributions and community types is vital for ecological science and effective conservation assessment and planning. However, detailed maps of plant community structure at landscape scales seldom exist due to the inability of field-based inventories to map a sufficient number of individuals over large areas. The Carnegie Airborne Observatory (CAO) collected hyperspectral and lidar data over Kruger National Park, South Africa, and these data were used to remotely identify > 500 000 tree and shrub crowns over a 144-km2 landscape using stacked support vector machines. Maps of community compositional variation were produced by ordination and clustering, and the importance of hillslope-scale topo-edaphic variation in shaping community structure was evaluated with redundancy analysis. This remote species identification approach revealed spatially complex patterns in woody plant communities throughout the landscape that could not be directly observed using field-based methods alone. We estimated that topo-edaphic variables representing catenal sequences explained 21% of species compositional variation, while we also uncovered important community patterns that were unrelated to catenas, indicating a large role for other soil-related factors in shaping the savanna community. Our results demonstrate the ability of airborne species identification techniques to map biodiversity for the evaluation of ecological controls on community composition over large landscapes.
Mao, J.; Ramanathan, A. K.; Abshire, J. B.; Kawa, S. R.; Riris, H.; Allan, G. R.; Hasselbrack, W. E.
Globally distributed atmospheric CO2 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, e.g., OCO-2 and GOSAT, are limited to cloud-free scenes. They are unable to provide useful retrievals in cloudy areas where the photon path-length can't be well characterized. Thus, passive approaches have limited global coverage and poor sampling in cloudy regions, even though some cloudy regions have active carbon surface fluxes. NASA Goddard is developing a pulsed integrated-path, differential absorption (IPDA) lidar approach to measure atmospheric column CO2 concentrations 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 column CO2 and range to cloud tops in addition to those to the ground with precise knowledge of the photon path-length. This allows retrievals of column CO2 concentrations to cloud tops, providing much higher spatial coverage and some information about vertical structure of CO2. This is expected to benefit atmospheric transport process studies, carbon data assimilation in models, and global and regional carbon flux estimation. We show some preliminary results of the all-sky retrieval capability using airborne lidar measurements from the 2011, 2013 and 2014 ASCENDS airborne campaigns on the NASA DC-8. These show retrievals of atmospheric CO2 over low-level marine stratus clouds, cumulus clouds at the top of planetary boundary layer, some mid-level clouds and visually thin high-level cirrus clouds. The CO2 retrievals from the lidar are validated against in-situ measurements and compared to Goddard PCTM model simulations. Lidar cloud slicing to derive CO2 abundance in the planetary boundary layer and free troposphere also has been demonstrated. The
Leitold, Veronika; Keller, Michael; Morton, Douglas C; Cook, Bruce D; Shimabukuro, Yosio E
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.
Singh, U. N.; Petros, M.; Refaat, T. F.; Yu, J.; Ismail, S.
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 . 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 . 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.
Bayram, Eda; Vural, Elif; Alatan, Aydin
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.
Harikumar, A.; Bovolo, F.; Bruzzone, L.
Individual tree level inventory performed using high density multi-return airborne Light Detection and Ranging (LiDAR) systems provides both internal and external geometric details on individual tree crowns. Among them, the parameters such as, the stem location, and Diameter at Breast Height of the stem (DBH) are very relevant for accurate biomass, and forest growth estimation. However, methods that can accurately estimate these parameters along the vertical canopy are lacking in the state of the art. Thus, we propose a method to locate and model the stem by analyzing the empty volume that appears within the 3D high density LiDAR point cloud of a conifer, due to the stem. In a high LiDAR density data, the points most proximal to the stem location in the upper half of the crown are very likely due to laser reflections from the stem and/or the branch-stem junctions. By locating accurately these points, we can define the lattice of points representing branch-stem junctions and use it to model the empty volume associated to the stem location. We identify these points by using a state-of-the-art internal crown structure modelling technique that models individual conifer branches in a high density LiDAR data. Under the assumption that conifer stem can be closely modelled using a cone shape, we regression fit a geometric shape onto the lattice of branch-stem junction points. The parameters of the geometric shape are used to accurately estimate the diameter at breast height, and height of the tree. The experiments were performed on a set of hundred conifers consisting of trees from six dominant European conifer species, for which the height and the DBH were known. The results prove the method to be accurate.
Lague, Dimitri; Launeau, Patrick; Michon, Cyril; Gouraud, Emmanuel; Juge, Cyril; Gentile, William; Hubert-Moy, Laurence; Crave, Alain
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
Sanchez Lopez, N.; Hudak, A. T.; Boschetti, L.
, and Elk Creek watersheds ( 54,000 ha) within the Nez Perce-Clearwater National Forest in Idaho, where airborne LiDAR and reference maps on TSD were available. Simulated GEDI footprints and waveforms were obtained from airborne LiDAR point clouds and the results were compared to similar analysis performed with airborne LiDAR.
The overarching objective of this ongoing project is to assess the role of vegetation within climate change. Forests capture carbon, a green house gas, from the atmosphere. Thus, any change, whether, natural (e.g. growth, fire, death) or due to anthropogenic activity (e.g. logging, burning, urbanization) may have a significant impact on the Earth's carbon cycle. Through the use of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA's Laser Vegetation Imaging Sensor (LVIS), which are airborne Light Detection and Ranging (LIDAR) remote sensing technologies, we gather data to estimate the amount of carbon contained in forests and how the content changes over time. UAVSAR and LVIS sensors were sent all over the world with the objective of mapping out terrain to gather tree canopy height and biomass data; This data is in turn used to correlate vegetation with the global carbon cycle around the world.
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
L. I. Kleinman
Full Text Available The NASA Langley Research Center (LaRC airborne High Spectral Resolution Lidar (HSRL measures vertical profiles of aerosol extinction, backscatter, and depolarization at both 532 nm and 1064 nm. In March of 2006 the HSRL participated in the Megacity Initiative: Local and Global Research Observations (MILAGRO campaign along with several other suites of instruments deployed on both aircraft and ground based platforms. This paper presents high spatial and vertical resolution HSRL measurements of aerosol extinction and optical depth from MILAGRO and comparisons of those measurements with similar measurements from other sensors and model predictions. HSRL measurements coincident with airborne in situ aerosol scattering and absorption measurements from two different instrument suites on the C-130 and G-1 aircraft, airborne aerosol optical depth (AOD and extinction measurements from an airborne tracking sunphotometer on the J-31 aircraft, and AOD from a network of ground based Aerosol Robotic Network (AERONET sun photometers are presented as a validation of the HSRL aerosol extinction and optical depth products. Regarding the extinction validation, we find bias differences between HSRL and these instruments to be less than 3% (0.01 km−1 at 532 nm, the wavelength at which the HSRL technique is employed. The rms differences at 532 nm were less than 50% (0.015 km−1. To our knowledge this is the most comprehensive validation of the HSRL measurement of aerosol extinction and optical depth to date. The observed bias differences in ambient aerosol extinction between HSRL and other measurements is within 15–20% at visible wavelengths, found by previous studies to be the differences observed with current state-of-the-art instrumentation (Schmid et al., 2006.
Selkowitz, David J.; Green, Gordon; Peterson, Birgit E.; Wylie, Bruce
Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of
Full Text Available Airborne LiDAR bathymetry (ALB has been shown to have the ability to retrieve water turbidity using the waveform parameters (i.e., slopes and amplitudes of volume backscatter returns. However, directly and accurately extracting the parameters of volume backscatter returns from raw green-pulse waveforms in shallow waters is difficult because of the short waveform. This study proposes a new accurate and efficient method for the remote sensing of suspended sediment concentrations (SSCs in shallow waters based on the waveform decomposition of ALB. The proposed method approaches raw ALB green-pulse waveforms through a synthetic waveform model that comprises a Gaussian function (for fitting the air–water interface returns, triangle function (for fitting the volume backscatter returns, and Weibull function (for fitting the bottom returns. Moreover, the volume backscatter returns are separated from the raw green-pulse waveforms by the triangle function. The separated volume backscatter returns are used as bases to calculate the waveform parameters (i.e., slopes and amplitudes. These waveform parameters and the measured SSCs are used to build two power SSC models (i.e., SSC (C-Slope (K and SSC (C-Amplitude (A models at the measured SSC stations. Thereafter, the combined model is formed by the two established C-K and C-A models to retrieve SSCs. SSCs in the modeling water area are retrieved using the combined model. A complete process for retrieving SSCs using the proposed method is provided. The proposed method was applied to retrieve SSCs from an actual ALB measurement performed using the Optech Coastal Zone Mapping and Imaging LiDAR in a shallow and turbid water area. A mean bias of 0.05 mg/L and standard deviation of 3.8 mg/L were obtained in the experimental area using the combined model.
Urbazaev, Mikhail; Thiel, Christian; Cremer, Felix; Dubayah, Ralph; Migliavacca, Mirco; Reichstein, Markus; Schmullius, Christiane
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
Wang, Y.; Chen, Q.; Li, K.; Zheng, D.; Fang, J.
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.
Cliff, W. C.; Skarda, J. R.; Renne, D. S.; Sandusky, W. F.
The NASA/MSFC Airborne Doppler Lidar System was flown in July 1981 aboard the NASA/Ames Convair 990 on the east side of San Gorgonio Pass California, near Palm Springs, to measure and investigate the accelerated atmospheric wind field discharging from the pass. At this region, the maritime layer from the west coast accelerates through the pass and spreads out over the valley floor on the east side of the pass. The experiment was selected in order to study accelerated flow in and at the exit of the canyon. Ground truth wind data taken concurrently with the flight data were available from approximately 12 meteorological towers and 3 tala kites for limited comparison purposes. The experiment provided the first spatial data for ensemble averaging of spatial correlations to compute lateral and longitudinal length scales in the lateral and longitudinal directions for both components, and information on atmospheric flow in this region of interest from wind energy resource considerations.
Jones, Benjamin M; Stoker, Jason M; Gibbs, Ann E; Richmond, Bruce M; Grosse, Guido; Romanovsky, Vladimir E; Douglas, Thomas A; Kinsman, Nicole E M
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)
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
Full Text Available In this paper, an improved method based on a mixture of Gaussian and quadrilateral functions is presented to process airborne bathymetric LiDAR waveforms. In the presented method, the LiDAR waveform is fitted to a combination of three functions: one Gaussian function for the water surface contribution, another Gaussian function for the water bottom contribution, and a new quadrilateral function to fit the water column contribution. The proposed method was tested on a simulated dataset and a real dataset, with the focus being mainly on the performance of retrieving bottom response and water depths. We also investigated the influence of the parameter settings on the accuracy of the bathymetry estimates. The results demonstrate that the improved quadrilateral fitting algorithm shows a superior performance in terms of low RMSE and a high detection rate in the water depth and magnitude retrieval. What’s more, compared with the use of a triangular function or the existing quadrilateral function to fit the water column contribution, the presented method retrieved the least noise and the least number of unidentified waveforms, showed the best performance in fitting the return waveforms, and had consistent fitting goodness for all different water depths.
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.
Kong, Deming; Li, Xiaolu; Xu, Lijun
A new method based on the combination of two kinds of clustering algorithms for building roof segmentation from airborne LiDAR (light detection and ranging) point cloud data is proposed. The K-plane algorithm is introduced to classify the laser footprints that cannot be correctly classified by the traditional K-means algorithm. High-precision classification can be obtained by combining the two aforementioned clustering algorithms. Furthermore, to improve the performance of the new segmentation method, a new initialization method is proposed to acquire the number and coordinates of the initial cluster centers for the K-means algorithm. In the proposed initialization method, the geometrical planes of a building roof are estimated from the elevation image of the building roof by using the mathematical morphology and Hough transform techniques. By calculating the number and normal vectors of the estimated geometrical planes, the number and coordinates of the initial cluster centers for the K-means algorithm are obtained. With the aid of the proposed initialization and segmentation methods, the point cloud of the building roof can be rapidly and appropriately classified. The proposed methods are validated by using both simulated and real LiDAR data. (paper)
Full Text Available 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.
İnan, M.; Bilici, E.; Akay, A. E.
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.
Ding, Kai; Li, Qingquan; Zhu, Jiasong; Wang, Chisheng; Guan, Minglei; Chen, Zhipeng; Yang, Chao; Cui, Yang; Liao, Jianghai
In this paper, an improved method based on a mixture of Gaussian and quadrilateral functions is presented to process airborne bathymetric LiDAR waveforms. In the presented method, the LiDAR waveform is fitted to a combination of three functions: one Gaussian function for the water surface contribution, another Gaussian function for the water bottom contribution, and a new quadrilateral function to fit the water column contribution. The proposed method was tested on a simulated dataset and a real dataset, with the focus being mainly on the performance of retrieving bottom response and water depths. We also investigated the influence of the parameter settings on the accuracy of the bathymetry estimates. The results demonstrate that the improved quadrilateral fitting algorithm shows a superior performance in terms of low RMSE and a high detection rate in the water depth and magnitude retrieval. What's more, compared with the use of a triangular function or the existing quadrilateral function to fit the water column contribution, the presented method retrieved the least noise and the least number of unidentified waveforms, showed the best performance in fitting the return waveforms, and had consistent fitting goodness for all different water depths.
Full Text Available RANSAC algorithm is a robust method for model estimation. It is widely used in the extraction of geometry primitives and 3D model reconstruction. However, there has been relatively little comprehensive evaluation in RANSAC-based approach for plane extraction. In order to provide a reference for improving the quality on RANSAC-based approach for roof facets extraction or segmentation, this paper focuses on the quality analysis on classical RANSAC algorithm. Airborne LIDAR data from the test Area 1 and Area 2 in Vaihingen (German is used. 33 buildings (4 buildings with flat roofs and 29 buildings with slope roofs extracted from LIDAR data are taken as input for planes extraction. Based on the characteristics of detected planar surfaces, planes can fall into several categories: non-segmented planes, over-segmented planes, under-segmented planes and spurious planes. Then, several causes for these quality problems are discussed. Some experimental results and analyses show that, considering spatial-domain connectivity, most of the quality problems of classical RANSAC algorithm can be improved. However, there are still many issues requiring in-depth research. Finally, some methods are suggested to solve these problems.
Yan, J.; Jiang, W.; Shan, J.
RANSAC algorithm is a robust method for model estimation. It is widely used in the extraction of geometry primitives and 3D model reconstruction. However, there has been relatively little comprehensive evaluation in RANSAC-based approach for plane extraction. In order to provide a reference for improving the quality on RANSAC-based approach for roof facets extraction or segmentation, this paper focuses on the quality analysis on classical RANSAC algorithm. Airborne LIDAR data from the test Area 1 and Area 2 in Vaihingen (German) is used. 33 buildings (4 buildings with flat roofs and 29 buildings with slope roofs) extracted from LIDAR data are taken as input for planes extraction. Based on the characteristics of detected planar surfaces, planes can fall into several categories: non-segmented planes, over-segmented planes, under-segmented planes and spurious planes. Then, several causes for these quality problems are discussed. Some experimental results and analyses show that, considering spatial-domain connectivity, most of the quality problems of classical RANSAC algorithm can be improved. However, there are still many issues requiring in-depth research. Finally, some methods are suggested to solve these problems.
Ferraz, António; Mallet, Clément; Chehata, Nesrine
In forested mountainous areas, the road location and characterization are invaluable inputs for various purposes such as forest management, wood harvesting industry, wildfire protection and fighting. Airborne topographic lidar has become an established technique to characterize the Earth surface. Lidar provides 3D point clouds allowing for fine reconstruction of ground topography while preserving high frequencies of the relief: fine Digital Terrain Models (DTMs) is the key product. This paper addresses the problem of road detection and characterization in forested environments over large scales (>1000 km2). For that purpose, an efficient pipeline is proposed, which assumes that main forest roads can be modeled as planar elongated features in the road direction with relief variation in orthogonal direction. DTMs are the only input and no complex 3D point cloud processing methods are involved. First, a restricted but carefully designed set of morphological features is defined as input for a supervised Random Forest classification of potential road patches. Then, a graph is built over these candidate regions: vertices are selected using stochastic geometry tools and edges are created in order to fill gaps in the DTM created by vegetation occlusion. The graph is pruned using morphological criteria derived from the input road model. Finally, once the road is located in 2D, its width and slope are retrieved using an object-based image analysis. We demonstrate that our road model is valid for most forest roads and that roads are correctly retrieved (>80%) with few erroneously detected pathways (10-15%) using fully automatic methods. The full pipeline takes less than 2 min per km2 and higher planimetric accuracy than 2D existing topographic databases are achieved. Compared to these databases, additional roads can be detected with the ability of lidar sensors to penetrate the understory. In case of very dense vegetation and insufficient relief in the DTM, gaps may exist in
Corp, Lawrence A.; Cook, Bruce D.; McCorkel, Joel; Middleton, Elizabeth M.
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.
Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Kittaka, C.; Vaughn, M. A.; Remer, L. A.
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.
Full Text Available We describe the design, implementation and performance of a novel airborne system, which integrates commercial waveform LiDAR, CCD (Charge-Coupled Device camera and hyperspectral sensors into a common platform system. CAF’s (The Chinese Academy of Forestry LiCHy (LiDAR, CCD and Hyperspectral Airborne Observation System is a unique system that permits simultaneous measurements of vegetation vertical structure, horizontal pattern, and foliar spectra from different view angles at very high spatial resolution (~1 m on a wide range of airborne platforms. The horizontal geo-location accuracy of LiDAR and CCD is about 0.5 m, with LiDAR vertical resolution and accuracy 0.15 m and 0.3 m, respectively. The geo-location accuracy of hyperspectral image is within 2 pixels for nadir view observations and 5–7 pixels for large off-nadir observations of 55° with multi-angle modular when comparing to LiDAR product. The complementary nature of LiCHy’s sensors makes it an effective and comprehensive system for forest inventory, change detection, biodiversity monitoring, carbon accounting and ecosystem service evaluation. The LiCHy system has acquired more than 8000 km2 of data over typical forests across China. These data are being used to investigate potential LiDAR and optical remote sensing applications in forest management, forest carbon accounting, biodiversity evaluation, and to aid in the development of similar satellite configurations. This paper describes the integration of the LiCHy system, the instrument performance and data processing workflow. We also demonstrate LiCHy’s data characteristics, current coverage, and potential vegetation applications.
Shaun R. Levick
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
Riris, Haris; Abshire, James B.; Stephen, Mark; Rodriquez, Michael; Allan, Graham; Hasselbrack, William; Mao, Jianping
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
Beyon, Jeffrey Y.; Koch, Grady J.; Kavaya, Michael J.
A pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia flew on the NASA's DC-8 aircraft during the NASA Genesis and Rapid Intensification Processes (GRIP) during the summer of 2010. The participation was part of the project Doppler Aerosol Wind Lidar (DAWN) Air. Selected results of airborne wind profiling are presented and compared with the dropsonde data for verification purposes. Panoramic presentations of different wind parameters over a nominal observation time span are also presented for selected GRIP data sets. The realtime data acquisition and analysis software that was employed during the GRIP campaign is introduced with its unique features.
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.
Ferrare, Richard; Hostetler, Chris; Hair, John; Cook Anthony; Harper, David; Burton, Sharon; Clayton, Marian; Clarke, Antony; Russell, Phil; Redemann, Jens
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.
Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.
Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910
Delaney, Catherine A.; McCarron, Stephen; Davis, Stephen
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.
National Oceanic and Atmospheric Administration, Department of Commerce — These data are the lidar points collected for FEMA Risk Mapping, Assessment, and Planning (Risk MAP) for the Merrimack River Watershed. This area falls in portions...
in the EDMF Parameterization Scheme: An Airborne Doppler Wind Lidar Perspective 5a. CONTRACT NUMBER 5b. GRANT NUMBER N000141110450 5c. PROGRAM...Wind Lidar (TODWL) data near Monterey, CA and Dugway, UT to investigate the physical characteristics, TKE transports and contributions to EDMF...EDMF. 15. SUBJECT TERMS OLE, EDMF, Doppler Wind Lidar 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18. NUMBER a. REPORT b. ABSTRACT c. THIS
Full Text Available 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.
Yao, C.; Zhang, X.; Liu, H.
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.
R. R. Rogers
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.
Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph
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.
Koch, Grady J.; Beyon, Jeffrey Y.; Cowen, Larry J.; Kavaya, Michael J.; Grant, Michael S.
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.
Liu, Feng; Tan, Chang; Lei, Pi-Feng
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.
Johansen, Kasper; Grove, James; Denham, Robert; Phinn, Stuart
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.
Jones, B. M.; Durner, G. M.; Stoker, J.; Shideler, R.; Perham, C.; Liston, G. E.
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
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...
Full Text Available Foliage profile is a key biophysical parameter for forests. Airborne Light Detection and Ranging is an effective tool for vegetation parameter retrieval. Data acquisition conditions influence the estimation of biophysical parameters. To acquire accurate foliage profiles at the lowest cost, we used simulations to explore the effects of data acquisition conditions on forest foliage profile retrieval. First, a 3-D forest scene and the airborne small-footprint full-waveform LiDAR data were simulated by the DART model. Second, the foliage profile was estimated from LiDAR data based on a Geometric Optical and Radiative Transfer model. Lastly, the effects of the airborne LiDAR scanning angle, flying altitude, and pulse density on foliage profile retrieval were explored. The results indicated that the scanning angle was an important factor in the foliage profile retrieval, and the optimal scanning angle was 20°. The optimal scanning angle was independent of flying altitude and pulse density, and combinations of multiple scanning angles could improve the accuracy of the foliage profile estimation. The flying altitude and pulse density had little influence on foliage profile retrieval at plot level and could be ignored. In general, our study provides reliable information for selecting the optimal instrument operational parameters to acquire more accurate foliage profiles and minimize data acquisition costs.
Lai, Zulong; Shen, Shaohong; Chen, Xingyi; Liang, Xinmei; Zhang, Jie
In this paper, we propose an analysis on the combinative effect of high-resolution airborne image and light detection and ranging (LIDAR) data for the classification of complex urban areas. In greater detail, the proposed system is composed of three models briefly. Model one includes an advanced kernelized fuzzy c-means classification method for high-resolution airborne image. The characteristics of LIDAR point cloud are introduced in model two, membership degree function of buildings, vegetations and naked land have been built. In model three, high-resolution image and elevation data form LIDAR point cloud are jointed. Experiment carried out on a complex urban area provide interesting conclusions on the effectiveness and protentialities of the joint use of high-resolution image and LIDAR data. In particular, the elevation data was very effective for the separation of species with similar spectral signatures but different elevation information. Experimental results approve that elevation data can improve classification accuracy in building occupied area obviously.
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...
Nehrir, A. R.; Hair, J. W.; Ferrare, R. A.; Hostetler, C. A.; Notari, A.; Collins, J. E., Jr.; Hare, R. J.; Harper, D. B.; Antill, C.; Cook, A. L.; Young, J.; Chuang, T.; Welch, W.
Atmospheric methane (CH4) has the second largest radiative forcing of the long-lived greenhouse gasses (GHG) after carbon dioxide. However, methane's much shorter atmospheric lifetime and much stronger warming potential make its radiative forcing equivalent to that for CO2 over a 20-year time horizon which makes CH4 a particularly attractive target for mitigation strategies. Similar to CH4, water vapor (H2O) is the most dominant of the short-lived GHG in the atmosphere and plays a key role in many atmospheric processes. Atmospheric H2O concentrations span over four orders of magnitude from the planetary boundary layer where high impact weather initiates to lower levels in the upper troposphere and lower stratosphere where water vapor has significant and long term impacts on the Earth's radiation budget. Active remote sensing employing the differential absorption lidar (DIAL) technique enables scientific assessments of both natural and anthropogenic sources and sinks of CH4 with high accuracy and precision as well as and its impacts on the climate. The DIAL technique also allows for profiling of tropospheric water vapor for weather and climate applications with unprecedented spatial and temporal resolution. NASA Langley is developing the High Altitude Lidar Observatory (HALO) lidar system to address the observational needs of NASA's weather, climate, carbon cycle, and atmospheric composition focus areas. HALO is a multi-function airborne lidar being developed to measure atmospheric H2O and CH4 mixing ratios and aerosol and cloud optical properties using the DIAL and High Spectral Resolution Lidar (HSRL) techniques, respectively. HALO is designed as an airborne simulator for future space based DIAL missions and will serve as test bed for risk reduction of key technologies required of future space based GHG DIAL missions. A system level overview and up-to-date progress of the HALO lidar will be presented. Simulations on the expected accuracy and precision of HALO CH4
Amediek, A.; Ehret, G.; Fix, A.; Wirth, M.; Quatrevalet, M.; Büdenbender, C.; Kiemle, C.; Loehring, J.; Gerbig, C.
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.
Brandbyge Ernstsen, Verner; Skovgaard Andersen, Mikkel; Gergely, Aron; Schulze Tenberge, Yvonne; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Winter, Christian; Bartholomä, Alexander
Land-water transition zones, like e.g. coastal and fluvial environments, are valuable ecosystems which are often characterised by high biodiversity and geodiversity. However, often these land-water transition zones are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point clouds, which both have point densities in the order of 20 points/m2. Morphometric analyses of the DEMs enabled the identification and mapping of the different landforms within the coastal and fluvial environments. Hereby, we demonstrate that vessel borne MBES and airborne topobathymetric LiDAR, here in combination, are promising tools for seamless mapping across land-water transition zones as well as for the quantification of a range of landforms at landscape scale in different land-water transition zone environments. Hence, we demonstrate the potential for mapping and quantifying geomorphological diversity, which is one of the main components of geodiversity and a prerequisite for assessing geoheritage. Acknowledgements This work was funded by the Danish Council for
Palaseanu, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, W. C.
This study evaluates the capabilities of the NASA Experimental Advanced Airborne Research Lidar (EAARL) system in delineating vegetation assemblages in Jean Lafitte National Park, Louisiana. Five-meter-resolution grids of bare earth (BE), canopy height (CH), canopy-reflection ratio (CRR), and height of median energy (HOME) 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. Comparisons of the capabilities of general linear models (GLM) and generalized additive models (GAM) were conducted using conventional evaluation methods (sensitivity, specificity, kappa statistics, area under the curve) and two new indexes, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). GAMs were superior to GLMs in modeling the vegetation training data, but no statistically significant differences between the two models were achieved for predicting vegetation validation data using conventional evaluation methods, although statistically significant improvements in net reclassifications were observed. The goodness-of-fit and prediction accuracy for both models are influenced by data prevalence and occurrence, although GAM models perform much better in the case of training data for all vegetation communities. Vegetation communities with less than 60% prevalence (e.g., coarse woody debris, herbs, shrubs, floating aquatics, and palms) have less than 40% maximum deviance explained, with the exception of bare ground for which the deviance explained by the GAM model is 64%. Midstory and canopy trees that have over 80% prevalence and over 10% occurrence have 99% deviance explained by the GAM model. For the validation dataset with vegetation community prevalence above 35%, GAM models show improvements in NRI only for vegetation categories with occurrences above 10%, and improvements in IDI for vegetation categories with occurrences above 20
Browell, Edward V.; Butler, Carolyn F.; Kooi, Susan A.
Ozone (O3) and aerosol distributions were measured from an aircraft using a differential absorption lidar (DIAL) system as part of the 1988 NASA Global Tropospheric Experiment - Arctic Boundary Layer Experiment (ABLE-3A) to study the sources and sinks of gases and aerosols over the tundra regions of Alaska during the summer. The tropospheric O3 budget over the Arctic was found to be strongly influenced by stratospheric intrusions. Regions of low aerosol scattering and enhanced O3 mixing ratios were usually correlated with descending air from the upper troposphere or lower stratosphere. Several cases of continental polar air masses were examined during the experiment. The aerosol scattering associated with these air masses was very low, and the atmospheric distribution of aerosols was quite homogeneous for those air masses that had been transported over the ice for greater than or = 3 days. The transition in O3 and aerosol distributions from tundra to marine conditions was examined several times. The aerosol data clearly show an abrupt change in aerosol scattering properties within the mixed layer from lower values over the tundra to generally higher values over the water. The distinct differences in the heights of the mixed layers in the two regions was also readily apparent. Several cases of enhanced O3 were observed during ABLE-3 in conjunction with enhanced aerosol scattering in layers in the free atmosphere. Examples are presented of the large scale variations of O3 and aerosols observed with the airborne lidar system from near the surface to above the tropopause over the Arctic during ABLE-3.
Lange, Martin; Gill, Paul
With a vertical accuracy better than 1 m and collection rates up to 7000 km2/h, airborne interferometric synthetic aperture radars (InSAR) bridge the gap between space borne radar sensors and airborne optical LIDARs. This paper presents the latest generation of X-band InSAR sensors, developed by Intermap TechnologiesTM, which are operated on our four aircrafts. The sensors collect data for the NEXTMap(R) program - a digital elevation model (DEM) with 1 m vertical accuracy for the contiguous U.S., Hawaii, and most of Western Europe. For a successful operation, challenges like reduction of multipath reflections, very high interferometric phase stability, and a precise system calibration had to be mastered. Recent advances in sensor design, comprehensive system automation and diagnostics have increased the sensor reliability to a level where no radar operator is required onboard. Advanced flight planning significantly improved aircraft utilization and acquisition throughput, while reducing operational costs. Highly efficient data acquisition with straight flight lines up to 1200 km is daily routine meanwhile. The collected data pass though our automated processing cluster and finally are edited to our terrain model products. Extensive and rigorous quality control at every step of the workflow are key to maintain stable vertical accuracies of 1 m and horizontal accuracies of 2 m for our 3D maps. The combination of technical and operational advances presented in this paper enabled Intermap to survey two continents, producing 11 million km2 of uniform and accurate 3D terrain data.
Full Text Available This study considers recent airborne radiometric (gamma ray survey data, obtained at high-resolution, across various regions of the UK. The datasets all display a very evident attenuation of signal in association with peat, and intra-peat variations are observed. The geophysical response variations are examined in detail using example data sets across lowland areas (raised bogs, meres, fens and afforested peat and upland areas of blanket bog, together with associated wetland zones. The radiometric data do not map soils per se. The bedrock (the radiogenic parent provides a specific amplitude level. Attenuation of this signal level is then controlled by moisture content in conjunction with the density and porosity of the soil cover. Both soil and bedrock variations need to be jointly assessed. The attenuation theory, reviewed here, predicts that the behaviour of wet peat is distinct from most other soil types. Theory also predicts that the attenuation levels observed across wet peatlands cannot be generally used to map variations in peat thickness. Four survey areas at various scales, across England, Scotland, Wales and Ireland are used to demonstrate the ability of the airborne data to map peat zones. A 1:50 k national mapping of deep peat is used to provide control although variability in the definition of peat zones across existing databases is also demonstrated.
Valett, Susan; Hicks, Edward; Dabney, Philip; Harding, David
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
Carter, William E.; Shrestha, Ramesh L.
During October 1996, the University of Florida, the Florida Department of Environmental Protection, the Florida Department of Transportation and the United States Geological Survey-Center for Coastal Geology and Regional Marine Studies jointly conducted a demonstration/test project of airborne laser swath mapping. Project Laser Swath-mapping Evaluation and Resurvey, included mapping of more than three hundred kilometers of beaches, stretching from Mexico Beach, just east of Panama City, Florida, to the western tip of Perdido Key, Alabama. The observations collected along the beaches included returns from the water surface at a number of inlets and from near short portions of the Gulf. The typical flying altitude during the tests was 350 meters above the surface, with an airspeed of 75 meters per second. The laser swatch mapping system operated at 5000 pulses per second, and scanned in a saw tooth pattern with a scan angle of plus and minus 15 degrees and a scan rate of 25 Hz. More than 50 million data points were collected in about three hours of operations, spread over three days. Proprietary computer software was used by the vendor to combine aircraft orientation (roll, pitch and yaw) values from an inertial navigation unit in the laser scanning unit, the angular orientation of the scanner mirror, and the range data to compute vectors from the aircraft to the reflecting surface. These vectors were added to the location of the aircraft, determined by phase difference kinematic Global Positioning System observations to compute the coordinates of the reflecting surface at each measurement epoch, expressed in UTM Northings and Eastings and ellipsoid heights. Commercial software was then used to create a variety of products, including 3D shaded relief `snapshots,' contour maps, false colored maps, cross sections and profiles. Repeat coverage was used to estimate the short term repeatability of the measurements and comparisons with cross sections from classical
Lague, D.; Launeau, P.; Gouraud, E.
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.
Riris, Haris; Rodriquez, Michael D.; Allan, Graham R.; Hasselbrack, William E.; Mao, Jianping; Stephen, Mark A.; Abshire, James B.
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.
Anderson, Brian C
... analysis when comparing the different DEMs built by randomly selecting 90%, 66%, 50%, 30%, 10%, 5%, 3%, 1%, 0.5%, 0.3%, 0.05%, 0.03% and 0.01% of the data from an airborne Lidar collection from Honduras in 2008...
Cook, Bruce; Corp, Lawrence; Nelson, Ross; Morton, Douglas; Ranson, Kenneth J.; Masek, Jeffrey; Middleton, Elizabeth
in the CONUS and Mexico in support of NASA's Carbon Monitoring System (CMS) and AMIGA-Carb (AMerican Icesat Glas Assessment of Carbon). For NASA's CMS, wall-to-wall G-LiHT data have been acquired over intensive study sites with historic LiDAR datasets, dense inventory data, stem maps and flux tower observations. For AMIGA-Carb, G-LiHT transects have been acquired over ICESat tracks and USDA-FS inventory plots throughout the CONUS, and similar data will be acquired in Mexico during 2013. This talk will highlight recent science results from continental-scale transects landscape-scale deployments of G-LiHT, as well as seasonal forest dynamics from repeat pass G-LiHT acquisitions.
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.
Peduzzi, Alicia; Wynne, Randolph Hamilton; Thomas, Valerie A.; Nelson, Ross F.; Reis, James J.; Sanford, Mark
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.
Rhonda Mazza; Demetrios Gatziolis
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...
Becker, M. K.; Fricker, H. A.; Padman, L.; Bell, R. E.; Siegfried, M. R.; Dieck, C. C. M.
The Ross Ocean and ice Shelf Environment and Tectonic setting Through Aerogeophysical surveys and modeling (ROSETTA-Ice) project combines airborne glaciological, geological, and oceanographic observations to enhance our understanding of the history and dynamics of the large ( 500,000 square km) Ross Ice Shelf (RIS). Here, we focus on the Light Detection And Ranging (LiDAR) data collected in 2015 and 2016. This data set represents a significant advance in resolution: Whereas the last attempt to systematically map RIS (the surface-based RIGGS program in the 1970s) was at 55 km grid spacing, the ROSETTA-Ice grid has 10-20 km line spacing and much higher along-track resolution. We discuss two different strategies for processing the raw LiDAR data: one that requires proprietary software (Riegl's RiPROCESS package), and one that employs open-source programs and libraries. With the processed elevation data, we are able to resolve fine-scale ice-shelf features such as the "rampart-moat" ice-front morphology, which has previously been observed on and modeled for icebergs. This feature is also visible in the ROSETTA-Ice shallow-ice radar data; comparing the laser data with radargrams provides insight into the processes leading to their formation. Near-surface firn state and total firn air content can also be investigated through combined analysis of laser altimetry and radar data. By performing similar analyses with data from the radar altimeter aboard CryoSat-2, we demonstrate the utility of the ROSETTA-Ice LiDAR data set in satellite validation efforts. The incorporation of the LiDAR data from the third and final field season (December 2017) will allow us to construct a DEM and an ice thickness map of RIS for the austral summers of 2015-2017. These products will be used to validate and extend observations of height changes from satellite radar and laser altimetry, as well as to update regional models of ocean circulation and ice dynamics.
Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) plans to perform a coastal survey along the Gulf Coast in 2016 with funding provided by...
Van Den Eeckhout, Miet; Kerle, N.; Hervas, Javier; Supper, Robert; Margottini, C.; Canuti, P.; Sassa, K.
Light Detection and Ranging (LiDAR) and its wide range of derivative products have become a powerful tool in landslide research, particularly for landslide identification and landslide inventory mapping. In contrast to the many studies that use expert-based analysis of LiDAR derivatives to identify
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.
Palaseanu-Lovejoy, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, C.W.
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.
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.
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.
Full Text Available Most research on vegetation in mountain ranges focuses on elevation gradients as climate gradients, but elevation gradients are also the result of geological processes that build and deconstruct mountains. Recent findings from the Luquillo Mountains, Puerto Rico, have raised questions about whether erosion rates that vary due to past tectonic events and are spatially patterned in relation to elevation may drive vegetation patterns along elevation gradients. Here we use airborne light detection and ranging (LiDAR technology to observe forest height over the Luquillo Mountain Range. We show that models with different functional forms for the two prominent bedrock types best describe the forest height-elevation patterns. On one bedrock type there are abrupt decreases in forest height with elevation approximated by a sigmoidal function, with the inflection point near the elevation of where other studies have shown there to be a sharp change in erosion rates triggered by a tectonic uplift event that began approximately 4.2 My ago. Our findings are consistent with broad geologically mediated vegetation patterns along the elevation gradient, consistent with a role for mountain building and deconstructing processes.
Li, Qi; Zhou, Wei; Li, Chang
Small-Footprint Airborne LiDAR(light detection and ranging) remote sensing is a breakthrough technology for deriving forest canopy structural characteristics. Because the technique is relatively new as applied to canopy measurement in China, there is a tremendous need for experiments that integrate field work, LiDAR remote sensing and subsequent analyses for retrieving the full complement of structural measures critical for forestry applications. Data storage capacity and high processing speed available today have made it possible to digitally sample and store the entire reflected waveform, instead of only extracting the discrete coordinates which form the so-called point clouds. Return waveforms can give more detailed insights into the vertical structure of surface objects, surface slope, roughness and reflectivity than the conventional echoes. In this paper, an improved Expectation Maximum (EM) algorithm is adopted to decompose raw waveform data. Derived forest biophysical parameters, such as vegetation height, subcanopy topography, crown volume, ground reflectivity, vegetation reflectivity and canopy closure, are able to describe the horizontal and vertical forest canopy structure
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.
Sohn, G.; Jwa, Y.; Jung, J.; Kim, H.
This paper proposes a new algorithm to generalize noisy polylines comprising a rooftop model by maximizing a shape regularity (orthogonality, symmetricity and directional simplications). The nature of remotely sensed data including airborne LiDAR often produce errors in localizing salient features (corners, lines and planes) due to weak contrast, occlusions, shadows and object complexity. A generalization or regularization process is well known algorithm for eliminating erroneous vertices while preserving significant information on rooftop shapes. Most of existing regularization methods achieves this goal base on a local process such as if-then rules due to lacking global objective functions or mainly focusing on minimising residuals between boundary observations and models. In this study, we implicitly derive rules to generate local hypothetical models. Those hypothesized models produce possible drawings of regular patterns that given rooftop vectors can possibly generate by combining global and local analysis of line directions and their connections. A final optimal model is globally selected through a gradient descent optimization. A BSP (Binary Tree Partitioning)-tree was used to produce initial rooftop vectors using ISPRS WGIII/4's benchmarking test sites in Veihngen. The proposed regularization algorithm was applied to reduce modelling errors produced by BSP-tree. An evaluation demonstrates the proposed algorithm is promising for updating of building database.
Garcia-Alonso, M.; Casas Planes, Á.; Koltunov, A.; Ustin, S.; Falk, M.; Ramirez, C.
Accurate knowledge of the amount and distribution of fuels is critical for appropriate fire planning and management, but also to improve carbon emissions estimates resulting from both wildland and prescribed fires. Airborne LiDAR (ALS) data has shown great capability to determine the amount of biomass in different ecosystems. Nevertheless, for most incidents a pre-fire LiDAR dataset that would enable the characterization of fuels before the incident is not available. Addressing this problem, we investigated the potential of combining a post-fire ALS dataset and a pre-fire Landsat image to model the pre-fire biomass distribution for the third-largest wildfire in California history, the Rim fire. Very high density (≈ 20 points/m2) ALS data was acquired covering the burned area plus a 2 km buffer. 500+ ALS-plots were located throughout the buffer area using a stratified random sampling scheme, with the strata defined by species group (coniferous, hardwood, and mixed forests) and diametric classes (5-9.9"; 10-19.9"; 20-29.9" and >30"). In these plots, individual tree crowns were delineated by the Watershed algorithm. Crown delineation was visually refined to avoid over- and under-segmentation errors, and the tree biomass was determined based on species-specific allometric equations. The biomass estimates for correctly delineated trees were subsequently aggregated to the plot-level. The next step is to derive a model relating the plot-level biomass to plot-level ALS-derived height and intensity metrics as explanatory variables. This model will be used to map pre-fire biomass in the buffer area outside the burn. To determine pre-fire biomass inside the fire perimeter, where ALS data are not available, we will use a statistical approach based on spectral information provided by a pre-fire Landsat image and its relationships with the 2 km buffer LiDAR-derived biomass estimates. We will validate our results with field measurements collected independently, before the fire.
Moller, D.; Hensley, S.; Wu, X.; Muellerschoen, R.
In May 2009 a mm-wave single-pass interferometric synthetic aperture radar (InSAR) for the first time demonstrated ice surface topography swath-mapping in Greenland. This was achieved with the airborne Glacier and Ice Surface Topography Interferometer (GLISTIN-A). Ka-band (35.6GHz) was chosen for high-precision topographic mapping from a compact sensor with minimal surface penetration. In recent years, the system was comprehensively upgraded for improved performance, stability and calibration. In April 2013, after completing the upgrades, GLISTIN-A flew a brief campaign to Alaska. The primary purpose was to demonstrate the InSAR's ability to generate high-precision, high resolution maps of ice surface topography with swaths in excess of 10km. Comparison of GLISTIN-A's elevations over glacial ice with lidar verified the precision requirements and established elevation accuracies to within 2 m without tie points. Feature tracking of crevasses on Columbia Glacier using data acquired with a 3-day separation exhibit an impressive velocity mapping capability. Furthermore, GLISTIN-A flew over the Beaufort sea to determine if we could not only map sea ice, but also measure freeboard. Initial analysis has established we can measure sea-ice freeboard using height differences from the top of the sea-ice and the sea surface in open leads. In the future, a campaign with lidar is desired for a quantitative validation. Another proof-of-concept collection mapped snow-basins for hydrology. Snow depth measurements using summer and winter collections in the Sierras were compared with lidar measurements. Unsurprisingly when present, trees complicate the interpretation, but additional filtering and processing is in work. For each application, knowledge of the interferometric penetration is important for scientific interpretation. We present analytical predictions and experimental data to upper bound the elevation bias of the InSAR measurements over snow and snow-covered ice.
Geli, H. M.; Taghvaeian, S.; Neale, C. M.; Pack, R.; Watts, D. R.; Osterberg, J.
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
Dogon-yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.
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.
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.
Chen, Yi-Chen; Lin, Chao-Hung
With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority
Alonzo, Michael; Morton, Douglas C.; Cook, Bruce D.; Andersen, Hans-Erik; Babcock, Chad; Pattison, Robert
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 Alaska’s 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-30 m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broadleaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from aboveground 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
Full Text Available With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show
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.
Jubanski, J.; Ballhorn, U.; Kronseder, K.; Franke, J.; Siegert, F.
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.
Full Text Available From an unprecedented experiment using airborne measurements performed over the rich forests of Réunion Island, this paper aims to present a methodology for the classification of diverse tropical forest biomes as retrieved from vertical profiles measured using a full-waveform LiDAR. This objective is met through the retrieval of both the canopy height and the Leaf Area Index (LAI, obtained as an integral of the foliage profile. The campaign involved sites ranging from coastal to rain forest, including tropical montane cloud forest, as found on the Bélouve plateau. The mean values of estimated LAI retrieved from the apparent foliage profile are between ~5 and 8 m2/m2, and the mean canopy height values are ~15 m for both tropical montane cloud and rain forests. Good agreement is found between LiDAR- and MODIS-derived LAI for moderate LAI (~5 m2/m2, but the LAI retrieved from LiDAR is larger than MODIS on thick rain forest sites (~8 against ~6 m2/m2 from MODIS. Regarding the characterization of tropical forest biomes, we show that the rain and montane tropical forests can be well distinguished from planted forests by the use of the parameters directly retrieved from LiDAR measurements.
Full Text Available Automatic classification of light detection and ranging (LiDAR data in urban areas is of great importance for many applications such as generating three-dimensional (3D building models and monitoring power lines. Traditional supervised classification methods require training samples of all classes to construct a reliable classifier. However, complete training samples are normally hard and costly to collect, and a common circumstance is that only training samples for a class of interest are available, in which traditional supervised classification methods may be inappropriate. In this study, we investigated the possibility of using a novel one-class classification algorithm, i.e., the presence and background learning (PBL algorithm, to classify LiDAR data in an urban scenario. The results demonstrated that the PBL algorithm implemented by back propagation (BP neural network (PBL-BP could effectively classify a single class (e.g., building, tree, terrain, power line, and others from airborne LiDAR point cloud with very high accuracy. The mean F-score for all of the classes from the PBL-BP classification results was 0.94, which was higher than those from one-class support vector machine (SVM, biased SVM, and maximum entropy methods (0.68, 0.82 and 0.93, respectively. Moreover, the PBL-BP algorithm yielded a comparable overall accuracy to the multi-class SVM method. Therefore, this method is very promising in the classification of the LiDAR point cloud.
The surface geometry of air-water interface is considered as an important factor affecting the performance of Airborne Lidar Bathymetry (ALB), and laser optical communication through the water surface. ALB is a remote sensing technique that utilizes a pulsed green (532 nm) laser mounted to an airborne platform in order to measure water depth. The water surface (i.e., air-water interface) can distort the light beam's ray-path geometry and add uncertainty to range calculation measurements. Previous studies on light refracting through a complex water surface are heavily dependent on theoretical models and simulations. In addition, only very limited work has been conducted to validate these theoretical models using experiments under well-controlled laboratory conditions. The goal of the study is to establish a clear relationship between water-surface conditions and the uncertainty of ALB measurement. This relationship will be determined by conducting more extensive empirical measurements to characterize the changes in beam slant path associated with a variety of short wavelength wind ripples, typically seen in ALB survey conditions. This study will focus on the effects of capillary and gravity-capillary waves with surface wavelengths smaller than the diameter of the laser beam on the water surface. Simulations using Monte-Carlo techniques of the ALB beam footprints and the environmental conditions were used to analyze the ray-path geometries. Based on the simulation results, laboratory experiments were then designed to test key parameters that have the greatest contribution on beam path and direction through the water. The laser beam dispersion experiments were conducted in well-controlled laboratory setting at the University of New Hampshire's Wave and Tow tank. The spatial elevations of the water surface were independently measured using a high resolution wave staff. The refracted laser beam footprint was measured using an underwater optical detector consisting of a
Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Refaat, Tamer; Kavaya, Michael J.; Remus, Ruben
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
Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Yu, Jirong; Antill, Charles W.; Remus, Ruben
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.
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.
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
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.
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.
Alonzo, M.; Bookhagen, B.; McFadden, J. P.; Sun, A.; Roberts, D. A.
In urban areas leaf area index (LAI) is a key ecosystem structural attribute with implications for energy and water balance, gas exchange, and anthropogenic energy use. Typically, citywide LAI estimates are extrapolated from those made on forest inventory sample plots through intensive crown measurement and allometric scaling. This is a time- and labor-intensive process yielding coarse spatial resolution results. In this study we generate spatially explicit estimates of LAI using high-point density airborne lidar throughout our study area in downtown Santa Barbara, CA. We implement two theoretically distinct modeling approaches. First, based on hemispherical photography at our 71 field plots, we estimate effective LAI using scan-angle corrected lidar laser penetration metrics (LPM). For our second approach, we adapt existing allometric equations for use with a suite of crown structural metrics (e.g., tree height, crown base height) measured with lidar. This approach allows for estimates of LAI to be made at the individual tree crown scale (ITC). This is important for evaluating fine-scale interactions between canopy and urban surfaces. The LPM method resulted in good agreement with field estimates (r2 = 0.80) and a slope of near unity (β = 0.998) using a model that assumed a spherical leaf angle distribution. Within ITC segments that were automatically delineated using watershed segmentation, lidar estimates of crown structure closely paralleled field measurements (r2=0.87 for crown length). LAI estimates based on the lidar structural variables corresponded well with estimates from field measurements (r2 = 0.84). Agreement between the LPM and allometric lidar methods was also strong across the 71 validation plots (r2 = 0.88) and among 450 sample points (r2 = 0.72) randomly distributed throughout the citywide maps. This is notably higher than the agreement between the hemiphoto and allometric ground-based estimates (r2 = 0.56). The allometric approach generally
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.
Full Text Available During the SALTRACE field experiment, conducted during June/July 2013, the Saharan dust transport across the Atlantic was analyzed by a set of ground based, in-situ and airborne instruments, including a 2-μm coherent DWL (Doppler wind lidar mounted onboard the DLR Falcon 20 research aircraft. An overview of the measurements of aerosol backscatter and extinction, horizontal and vertical winds retrieved from the DWL are presented together with a brief description of the applied methods. The retrieved measurements provide direct observation of Saharan dust transport mechanisms across the Atlantic as well as island induced lee waves in the Barbados region.
da Costa, Renata F.; Steffens, Juliana; Landulfo, E.; Guardani, Roberto; Nakaema, W. M.; Moreira, Paulo F., Jr.; da Silva Lopes, Fabio J. S.; Ferrini, Patricia
Characterization of atmospheric emissions from industrial flare stacks represents a challenge in measurement techniques because it is extremely difficult to determine the real-time concentrations of combustion products by in situ sampling, due to stack height, sensor calibration difficulties, and the dynamics of oscillations in the emission patterns. A ground based laser remote sensing (LIDAR) system has been developed for continuous and real-time monitoring of atmospheric emissions from an oil refinery located approximately 400 m from the instrument. The system is able to perform 3D scanning and profiling around the emission point. Tests were carried out using a scanning system pointed to the refinery flare. The mapping was obtained from a sequence of measurements at different zenithal and azimuthal angles resulting in a 3D image of the flare shape plus the flame itself. The measurements can be used to estimate the aerosol size distribution based on the ratios of the backscattering signal at three distinct wavelengths: 1064/532 nm, 1064/355 nm, and 532/355 nm. The method can be used in real time monitoring of industrial aerosol emissions and in the control of industrial processes. Preliminary results indicate a calibration procedure to assess the refining process efficiency based on the particle size distribution within and around the flare.
Tabor, Rowland W.; Booth, Derek B.
This map is an interpretation of a modern lidar digital elevation model combined with the geology depicted on the Geologic Map of the Des Moines 7.5' Quadrangle, King County, Washington (Booth and Waldron, 2004). Booth and Waldron described, interpreted, and located the geology on the 1:24,000-scale topographic map of the Des Moines 7.5' quadrangle. The base map that they used was originally compiled in 1943 and revised using 1990 aerial photographs; it has 25-ft contours, nominal horizontal resolution of about 40 ft (12 m), and nominal mean vertical accuracy of about 10 ft (3 m). Similar to many geologic maps, much of the geology in the Booth and Waldron (2004) map was interpreted from landforms portrayed on the topographic map. In 2001, the Puget Sound Lidar Consortium obtained a lidar-derived digital elevation model (DEM) for much of the Puget Sound area, including the entire Des Moines 7.5' quadrangle. This new DEM has a horizontal resolution of about 6 ft (2 m) and a mean vertical accuracy of about 1 ft (0.3 m). The greater resolution and accuracy of the lidar DEM compared to topography constructed from air-photo stereo models have much improved the interpretation of geology, even in this heavily developed area, especially the distribution and relative age of some surficial deposits. For a brief description of the light detection and ranging (lidar) remote sensing method and this data acquisition program, see Haugerud and others (2003).
Full Text Available In the discovering, identifying and mapping work of heritage objects in forest or desert areas, LiDAR ensures work efficiency and can provide the most complete and accurate 3D data. In the field of heritage documentation in China, the integration of LiDAR and small UAV is highly desirable. However, due to issues on the vibration of flying platform, load capacity, safety and other factors, not all UAVs can be used as LiDAR carriers. Therefore, the selection and design of suitable UAVs are very important. Little research has been done in this area and related experiments, complete test data and clear conclusions are hard to find. After long-term selection, design, trial-manufacturing and testing, the authors compare the vibration, capacity, reliability, stability of many UAV types, and finally develop two UAV platforms which are most suitable for carrying LiDAR for heritage mapping projects.
Elaksher, Ahmed; Alharthy, Abdullatif; Ali, Tarig
Currently, most mapping tasks are carried out using remote sensing data such as satellite imageries and LIDAR point clouds. This paper presents the integration of a QuickBird imagery set (both pan and multispectral) and LIDAR DEM generated from a LIDAR point cloud for mapping the coastline. A number of image processing techniques were applied to pan image to generate a coastline. Then a supervised classification is performed on the multispectral image followed by a raster to vector conversion to extract another shoreline. A third line was created from the LIDAR data using a set of processing algorithms. The three lines are weighted and pixels belonging to all of them are grouped to fit a final coastline. In order to evaluate the results, we manually extracted the corresponding line from the pan image and compared points belonging to both lines. Differences averaged about 1.37 meters.
Lee A. Vierling; Kerri T. Vierling; Patrick Adam; Andrew T. Hudak
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...
Brogan, D. J.; Nelson, P. A.; MacDonald, L. H.
Quantifying and predicting geomorphic change over large spatial scales is increasingly feasible and of growing interest as repeat high resolution topography becomes available. We began detailed field studies of channel geomorphic change using RTK-GPS in two 15 km2 watersheds following the 2012 High Park Fire; the watersheds were then subjected to a several-hundred year flood in September 2013. During this time a series of airborne LiDAR datasets were collected, and the objectives of this study were to: 1) determine and compare the spatial variability in channel and valley erosion and deposition over time from the LiDAR; and 2) determine if the observed changes can be predicted from channel and valley bottom characteristics. Data quality issues in the initial LiDAR required us to rotate and translate flight lines in order to co-register ground-classified point clouds between successive datasets; uncertainty was then estimated using our RTK-GPS field measurements. Topographic changes were calculated using the Multiscale Model to Model Cloud Comparison (M3C2) algorithm. Results indicate that the 2013 flood mobilized much more sediment than was mobilized due to the fire alone; unfortunately the uncertainty in differencing is still frequently greater than the observed changes, especially within transfer reaches. Valley expansion and constriction are major controls on spatial patterns of erosion and deposition, suggesting that topographic metrics such as longitudinal distributions of channel slope and valley confinement may provide quasi-physically based estimates of sediment deposition and delivery potential.
Geli, H. M.; Neale, C. M.; Pack, R. T.; Watts, D. R.; Osterberg, J.
Estimates of evapotranspiration (ET) over heterogeneous areas is challenging especially in water-limited sparsely vegetated environments. New techniques such as airborne full-waveform LiDAR (Light Detection and Ranging) and high resolution multispectral and thermal imagery can provide enough detail of sparse canopies to improve energy balance model estimations as well as footprint analysis of scintillometer data. The objectives of this study were to estimate ET over such areas and develop methodologies for the use of these airborne data technologies. Because of the associated heterogeneity, this study was conducted over the Cibola National wildlife refuge, southern California on an area dominated with tamarisk (salt cedar) forest (90%) interspersed with arrowweed and bare soil (10%). A set of two large aperture scintillometers (LASs) were deployed over the area to provide estimates of sensible heat flux (HLAS). The LASs were distributed over the area in a way that allowed capturing different surface spatial heterogeneity. Bowen ratio systems were used to provide hydrometeorological variables and surface energy balance fluxes (SEBF) (i.e. Rn, G, H, and LE) measurements. Scintillometer-based estimates of HLAS were improved by considering the effect of the corresponding 3D footprint and the associated displacement height (d) and the roughness length (z0) following Geli et al. (2011). The LiDAR data were acquired using the LASSI Lidar developed at Utah State University (USU). The data was used to obtain 1-m spatial resolution DEM's and vegetation canopy height to improve the HLAS estimates. The BR measurements of Rn and G were combined with LAS estimates, HLAS, to provide estimates of LELASas a residual of the energy balance equation. A thermal remote sensing model namely the two source energy balance (TSEB) of Norman et al. (1995) was applied to provide spatial estimates of SEBF. Four airborne images at 1-4 meter spatial resolution acquired using the USU airborne
Székely, Balázs; Kania, Adam; Standovár, Tibor; Heilmeier, Hermann
Forest ecosystems have characteristic structure of features defined by various structural elements of different scales and vertical positions: shrub layers, understory vegetation, tree trunks, and branches. Furthermore in most of the cases there are superimposed structures in distributions (mosaic or island patterns) due to topography, soil variability, or even anthropogenic factors like past/present forest management activity. This multifaceted spatial context of the forests is relevant for many ecological issues, especially for maintaining forest biodiversity. Our aim in this study is twofold: (1) to quantify this structural variability laterally and vertically using lacunarity, and (2) to relate these results to relevant ecological features, i.e quantitatively described forest properties. Airborne LiDAR data of various quality and point density have been used for our study including a number of forested sites in Central and East Europe (partly Natura 2000 sites). The point clouds have been converted to voxel format and then converted to horizontal layers as images. These images were processed further for the lacunarity calculation. Areas of interest (AOIs) have been selected based on evaluation of the forested areas and auxiliary field information. The calculation has been performed for the AOIs for all available vertical data slices. The lacunarity function referring to a certain point and given vicinity varies horizontally and vertically, depending on the vegetation structure. Furthermore, the topography may also influence this property as the growth of plants, especially spacing and size of trees are influenced by the local topography and relief (e.g., slope, aspect). The comparisons of the flatland and hilly settings show interesting differences and the spatial patterns also vary differently. Because of the large amount of data resulting from these calculations, sophisticated methods are required to analyse the results. The large data amount then has been
Vahtmäe, Ele; Kutser, Tiit; Kotta, Jonne; Pärnoja, Merli; Möller, Tiia; Lennuk, Lennart
It is known that the structure of benthic macrophyte and invertebrate habitats indicate the quality of coastal water. Thus, a large-scale analysis of the spatial patterns of coastal marine habitats makes it possible to adequately estimate the status of valuable coastal marine habitats, provide better evidence for environmental changes, and describe the processes behind the changes. Knowing the spatial distribution of benthic habitats is also important from the coastal management point of view. Our previous results clearly demonstrated that remote sensing methods can be used to map water depth and distribution of taxonomic groups of benthic algae (e.g., red, green, and brown algae) in the optically complex coastal waters of the Baltic Sea. We have as well shown that benthic habitat mapping should be done at high spatial resolution owing to the small-scale heterogeneity of such habitats in Estonian coastal waters. Here we tested the capability of high spatial resolution hyperspectral airborne image in its application for mapping benthic habitats. A big challenge is to define appropriate mapping classes that are also meaningful from the ecological point of view. In this study two benthic habitat classification schemes—broader level and finer level—were defined for the study area. The broader level classes were relatively well classified, but discrimination among the units of the finer classification scheme posed a considerable challenge and required a careful approach. Benthic habitat classification provided the highest accuracy in the case of the Spectral Angle Mapper classification method applied to a radiometrically corrected image. Further processing levels, such as spatial filtering and glint correction, decreased the classification accuracy.
Abshire, James B.; Weaver, Clark J.; Riris, Haris; Mao, Jianping; Sun, Xiaoli; Allan, Graham R.; Hasselbrack, William; Browell, Edward V.
We have developed a pulsed lidar technique for measuring the tropospheric CO2 concentrations as a candidate for NASA's ASCENDS space mission . It uses two pulsed laser transmitters allowing simultaneous measurement of a CO2 absorption line in the 1575 nm band, O2 extinction in the Oxygen A-band, surface height and backscatter profile. The lasers are precisely stepped in wavelength across the CO2 line and an O2 line region during the measurement. The direct detection receiver measures the energies of the laser echoes from the surface along with the range profile of scattering in the path. The column densities for the CO2 and O2 gases are estimated from the ratio of the on- and off-line signals via the integrated path differential absorption (IPDA) technique. The time of flight of the laser pulses is used to estimate the height of the scattering surface and to reject laser photons scattered in the atmosphere. We developed an airborne lidar to demonstrate an early version of the CO2 measurement from the NASA Glenn Lear-25 aircraft. The airborne lidar stepped the pulsed laser's wavelength across the selected CO2 line with 20 wavelength steps per scan. The line scan rate is 450 Hz, the laser pulse widths are 1 usec, and laser pulse energy is 24 uJ. The time resolved laser backscatter is collected by a 20 cm telescope, detected by a NIR photomultiplier and is recorded on every other reading by a photon counting system . During August 2009 we made a series of 2.5 hour long flights and measured the atmospheric CO2 absorption and line shapes using the 1572.33 nm CO2 line. Measurements were made at stepped altitudes from 3-13 km over locations in the US, including the SGP ARM site in Oklahoma, central Illinois, north-eastern North Carolina, and over the Chesapeake Bay and the eastern shore of Virginia. Although the received signal energies were weaker than expected for ASCENDS, clear CO2 line shapes were observed at all altitudes, and some measurements were made
Sebastian Martinuzzi; Lee A. Vierling; William A. Gould; Michael J. Falkowski; Jeffrey S. Evans; Andrew T. Hudak; Kerri T. Vierling
The lack of maps depicting forest three-dimensional structure, particularly as pertaining to snags and understory shrub species distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to remotely map snags and understory shrubs is therefore an important need. To address this, we first evaluated the use of LiDAR data for...
Marcus V.N. d' Oliveira; Stephen E. Reutebuch; Robert J. McGaughey; Hans-Erik. Andersen
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...
Abshire, J. B.; Riris, H.; Allan, G. R.; Mao, J.; Hasselbrack, W. E.; Numata, K.; Chen, J. R.; Kawa, S. R.; DiGangi, J. P.; Choi, Y.
The CO2 Sounder lidar is a pulsed, multiple-wavelength integrated path differential absorption lidar for measuring CO2 column concentrations. The lidar measures the range resolved shape of the 1572.33 nm CO2 absorption line to scattering surfaces, including to the ground and to the tops of clouds. Airborne measurements are currently using 30 fixed-wavelength samples distributed across the line. Analysis estimates the lidar range and pulse energies at each wavelength 10 times per second. For each second the retrievals solve for the CO2 absorption line shape and the column average CO2 concentrations by using radiative transfer calculations, the aircraft altitude and range to the scattering surface, and the atmospheric conditions. The lidar was flown on the NASA DC-8 aircraft in late July and early August as part of the 2017 ASCENDS airborne campaign. The campaign objectives were to assess the accuracy of airborne IPDA lidar measurements of CO2 column concentrations (XCO2), and to extend these lidar measurements to the Arctic. To date three science flights have been conducted with simultaneous XCO2 measurements from the lidar and in-situ CO2 measurements made at aircraft altitude with the AVOCET and Picarro in-situ sensors. Over 20 spiral-down maneuvers have been conducted in the campaign so far in the campaign over locations in California, the US Midwest and in Northwest Territories (NWT) Canada. Since each spiral maneuver allows comparing the retrievals of XCO2 from the lidar against those computed from in-situ measured CO2, this campaign allows an unprecedented opportunity to assess the lidar's performance over a diverse set of conditions, including those in the Arctic. The presentation will describe the flight paths, and will present the results from analyzing the retrieved XCO2 from the lidar in the campaign over the different regions. It will also present the results of comparing the lidar-retrieved XCO2 to those computed from the in-situ sensors at the numerous
Ballhorn, U.; Siegert, F.
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.
Valenciano, J.; Angenent, J.; Marshall, J. S.; Clark, K.; Litchfield, N. J.
The Hikurangi subduction margin along the east coast of the North Island, New Zealand accommodates oblique convergence of the Pacific Plate westward beneath the Australian plate at 45 mm/yr. Pronounced forearc uplift occurs at the southern end of the margin along the Wairarapa coast, onshore of the subducting Hikurangi plateau. Along a narrow coastal lowland, a series of uplifted Holocene marine terraces and beach ridges preserve a geologic record of prehistoric coseismic uplift events. In January 2017, we participated in the Research Experience for Undergraduates (REU) program of the NSF SHIRE Project (Subduction at Hikurangi Integrated Research Experiment). We visited multiple coastal sites for reconnaissance fieldwork to select locations for future in-depth study. For the coastline between Flat Point and Te Kaukau Point, we used airborne LiDAR data provided by Land Information New Zealand (LINZ) to create ArcGIS digital terrain models for mapping and correlating uplifted paleo-shorelines. Terrace elevations derived from the LiDAR data were calibrated through the use of Real Time Kinematic (RTK) GPS surveying at one field site (Glenburn Station). Prior field mapping and radiocarbon dating results (Berryman et al., 2001; Litchfield and Clark, 2015) were used to guide our LiDAR mapping efforts. The resultant maps show between four and seven uplifted terraces and associated beach ridges along this coastal segment. At some sites, terrace mapping and lateral correlation are impeded by discontinuous exposures and the presence of landslide debris, alluvial fan deposits, and sand dunes. Tectonic uplift along the southern Hikurangi margin is generated by a complex interaction between deep megathrust slip and shallow upper-plate faulting. Each uplifted Holocene paleo-shoreline is interpreted to represent a single coseismic uplift event. Continued mapping, surveying, and age dating may help differentiate between very large margin-wide megathrust earthquakes (M8.0-9.0+) and
Fatoyinbo, Temilola; Feliciano, Emanuelle A.; Lagomasino, David; Kuk Lee, Seung; Trettin, Carl
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
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
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.
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...
National Aeronautics and Space Administration — The capacity of coherent LIDAR systems to produce a continuous, real-time, 3D scan of wind velocities via detection of backscatter of atmospheric aerosols in...
Full Text Available A terrestrial Light Detection and Ranging (LIDAR system has high productivity and accuracy for topographic mapping, but the harsh conditions of Antarctica make LIDAR operation difficult. Low temperatures cause malfunctioning of the LIDAR system, and unpredictable strong winds can deteriorate data quality by irregularly shaking co-registration targets. For stable and efficient LIDAR operation in Antarctica, this study proposes and demonstrates the following practical solutions: (1 a lagging cover with a heating pack to maintain the temperature of the terrestrial LIDAR system; (2 co-registration using square planar targets and two-step point-merging methods based on extracted feature points and the Iterative Closest Point (ICP algorithm; and (3 a georeferencing module consisting of an artificial target and a Global Navigation Satellite System (GNSS receiver. The solutions were used to produce a topographic map for construction of the Jang Bogo Research Station in Terra Nova Bay, Antarctica. Co-registration and georeferencing precision reached 5 and 45 mm, respectively, and the accuracy of the Digital Elevation Model (DEM generated from the LIDAR scanning data was ±27.7 cm.
Full Text Available Identifying historical forest disturbances is difficult, especially in selectively logged areas. LiDAR is able to measure fine-scale variations in forest structure over multiple kilometers. We use LiDAR data from ca. 16 km2 of forest in Sierra Leone, West Africa, to discriminate areas of old-growth from areas recovering from selective logging for 23 years. We examined canopy height variation and gap size distributions. We found that though recovering blocks of forest differed little in height from old-growth forest (up to 3 m, they had a greater area of canopy gaps (average 10.2% gap fraction in logged areas, compared to 5.6% in unlogged area; and greater numbers of gaps penetrating to the forest floor (162 gaps at 2 m height in logged blocks, and 101 in an unlogged block. Comparison of LiDAR measurements with field data demonstrated that LiDAR delivered accurate results. We found that gap size distributions deviated from power-laws reported previously, with substantially fewer large gaps than predicted by power-law functions. Our analyses demonstrate that LiDAR is a useful tool for distinguishing structural differences between old-growth and old-secondary forests. That makes LiDAR a powerful tool for REDD+ (Reduction of Emissions from Deforestation and Forest Degradation programs implementation and conservation planning.
Profe, Jörn; Höfle, Bernhard
Tufas are secondary carbonate precipitations which occur ubiquitously in karstic environments. Thus, freshwater tufas are increasingly noticed as a high-resolution terrestrial paleoclimate archive. However, complex interactions between climate, hydrology and geomorphology drive tufa landscapes as a self-organizing system that creates a patchy transition zone between land and water at the decimeter scale. These feedbacks challenge the modern analogue technique to understand paleo-tufa evolution and require a detailed 3D characterization of tufa geomorphometry to better understand their shaping processes in relation to channel bed morphology. Due to the complex geometric nature of tufa landscapes and predominant land-water transition zones, new remote sensing techniques such as airborne sub-meter footprint LiDAR topo-bathymetry (ALTB) are necessary to enable a detailed 3D description. Using the Riegl VQ-820-G at the Kaisinger Brunnenbach, Germany, we successfully detected submerged and subaerial tufas with maximum total dam heights from 0.3 m up to 1.6 m (cf. Profe et al. 2016). In addition, slope and openness derived from a high-resolution digital terrain model (DTM) with 0.2 m spatial resolution provide insights into barrage morphology and orientation. We found that longitudinal slope analysis along the river course relates tufa morphology to channel bed morphology. Raster-based data quality control of the LiDAR topo-bathymetric DTM reveals an overall vertical data precision of 3 cm and an overall vertical data accuracy of 15.4 cm (1σ) (Profe et al. 2016). The 3D characterization of tufa landscapes facilitates the identification of monitoring and drilling sites for subsequent hydrological and geochemical studies that deepen our knowledge about the complex barrage formation processes. In the advent of UAV-borne LiDAR platforms, we are convinced that it becomes possible to reduce data uncertainty and to better represent e.g. tufa overhangs, vegetation cover and
Alonzo, M.; Cook, B.; Andersen, H. E.; Babcock, C. R.; Morton, D. C.
Fire in boreal forests initiates a cascade of biogeochemical and biophysical processes. Over typical fire return intervals, net radiative forcing from boreal forest fires depends on the offsetting impacts of greenhouse gas emissions and post-fire changes in land surface albedo. Whether boreal forest fires warm or cool the climate over these multi-decadal intervals depends on the magnitude of fire emissions and the time scales of decomposition, albedo changes, and forest regrowth. Our understanding of vegetation and surface organic matter (SOM) changes from boreal forest fires is shaped by field measurements and moderate resolution remote sensing data. Intensive field plot measurements offer detailed data on overstory, understory, and SOM changes from fire, but sparse plot data can be difficult to extend across the heterogeneous boreal forest landscape. Conversely, satellite measurements of burn severity are spatially extensive but only provide proxy measures of fire effects. In this research, we seek to bridge the scale gap between existing intensive and extensive methods using a combination of airborne lidar data and time series of Landsat data to evaluate pre- and post-fire conditions across Alaska's Kenai Peninsula. Lidar-based estimates of pre-fire stand structure and composition were essential to characterize the loss of canopy volume from fires between 2001 and 2014, quantify transitions from live to dead standing carbon pools, and isolate vegetation recovery following fire over 1 to 13 year time scales. Results from this study demonstrate the utility of lidar for estimating pre-fire structure and species composition at the scale of individual tree crowns. Multi-temporal airborne lidar data also provide essential insights regarding the heterogeneity of canopy and SOM losses at a sub-Landsat pixel scale. Fire effects are forest-structure and species dependent with variable temporal lags in carbon release due to delayed mortality (>5 years post fire) and
Qin, Haiming; Wang, Cheng; Xi, Xiaohuan; Tian, Jianlin; Zhou, Guoqing
Forest aboveground biomass (AGB) is critical for assessing forest productivity and evaluating carbon sequestration rates. Discrete-return LiDAR has been widely used to estimate forest AGB, however, fewer studies have estimated the coniferous forest AGB using airborne small-footprint full-waveform LiDAR data. The objective of this study was to extract a suite of newly proposed metrics from airborne small-footprint full-waveform LiDAR data and to evaluate the ability of these metrics in estimating coniferous forest AGB. To achieve this goal, each waveform was first preprocessed, including de-noising, smoothing, and normalization. Next, all the waveforms within each plot were aggregated into a large pseudo waveform and the return energy profile was generated. Then, the foliage profile was retrieved from the return energy profile based on the Geometric Optical and Radiative Transfer (GORT) model. Finally, a series of new return energy profile metrics and foliage profile metrics were extracted to estimate forest AGB. Simple linear regression was conducted to assess the correlation between each LiDAR metric and forest AGB. Stepwise multiple regression analysis was then carried out to select important prediction metrics and establish the optimal forest AGB estimation model. Results indicated that both return energy profile and foliage profile based height-related metrics were strongly correlated to forest AGB. The energy weighted canopy height (H Eweight ) (R = 0.88) and foliage area weighted height (H Fweight ) (R = 0.89) all had the highest correlation coefficients with forest AGB in return energy profile metrics and foliage profile metrics respectively. Energy height percentiles and foliage height percentiles also had the ability to explain AGB variation. The energy-related metrics, foliage area-related metrics, and bounding volume-related metrics derived from the return energy profile and foliage profile were not all sensitive to forest AGB. This study also concluded
Silvestri, S.; Viezzoli, A.; Pfaffhuber, A. A.; Vettore, A.
Peatlands are extraordinary reservoirs of organic carbon that can be found over a wide range of latitudes, in tropical, to temperate, to (sub)polar climates. According to some estimates, the carbon stored in peatlands almost match the atmospheric carbon pool. Peatlands degradation due to natural and anthropogenic factors releases every year large amount of CO2 and other green house gasses into the atmosphere. The conservation of peatlands is therefore a key measure to reduce emissions and to mitigate climate change. An effective plan to prevent peatlands degradation must move from a precise estimate of the volume of peat stored across vast territories around the world. One example are the several bogs that characterize large surfaces in Norway. Our research combines the use of high spatial resolution satellite optical data with Airborne Electromagnetic (AEM) and field measurements in order to map the extension and thickness of peat in Brøttum, Ringsaker province, Norway. The methodology allows us to quantify the volume of peat as well as the organic carbon stock. The variable thickness typical of Norwegian bogs allows us to test the limits of the AEM methodology in resolving near surface peat layers. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 747809. Start date: 1 June 2017. Duration: 24 months
Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Yu, Jirong
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.
Adolph, Winny; Jung, Richard; Schmidt, Alena; Ehlers, Manfred; Heipke, Christian; Bartholomä, Alexander; Farke, Hubert
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.
Gu, Chengyan; Clevers, Jan G. P. W.; Liu, Xiao; Tian, Xin; Li, Zhouyuan; Li, Zengyuan
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.
Obu, Jaroslav; Lantuit, Hugues; Grosse, Guido; Günther, Frank; Sachs, Torsten; Helm, Veit; Fritz, Michael
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.
Full Text Available The purposes of this study were 1 to estimate the biomass in the mangrove forests using satellite imagery and airborne LiDAR data, and 2 to estimate the amount of carbon stock changes using biomass estimated. The study area is located in the coastal area of the South Sumatra state, Indonesia. This area is approximately 66,500 ha with mostly flat land features. In this study, the following procedures were carried out: (1 Classification of types of tree species using Satellite imagery in the study area, (2 Development of correlation equations between spatial volume based on LiDAR data and biomass stock based on field survey for each types of tree species, and estimation of total biomass stock and carbon stock using the equation, and (3 Estimation of carbon stock change using Chronological Satellite Imageries. The result showed the biomass and the amount of carbon stock changes can be estimated with high accuracy, by combining the spatial volume based on airborne LiDAR data with the tree species classification based on satellite imagery. Quantitative biomass monitoring is in demand for projects related to REDD+ in developing countries, and this study showed that combining airborne LiDAR data with satellite imagery is one of the effective methods of monitoring for REDD+ projects.
Bywater-Reyes, Sharon; Wilcox, Andrew C.; Diehl, Rebecca M.
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.
Abshire, James B.; Riris, Haris; Weaver, Clark J.; Mao, Jianping; Allan, Graham R.; Hasselbrack, William E.; Browell, Edward V.
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.
Feng, Jian-mei; Xing, Ting-wen; Lin, Wi-mei
The aim of this paper is to explore a high-precision, a wide range of a frequency discrimination technique, and to study the application of this technique in the optical air data system (MOADS). To overcome the traditional equipment's shortcomings of short velocity detecting range such as pilot static tubes and wind wane, this technique can provide precision aviation data for various aerocrafts , without influencing pneumatic shape and performance of aerocraft. A tunable dual channel Fabry-Perot interferometer is used as a frequency discriminator in an airborne wind lidar system. This new frequency discriminator has been proposed to overcome the exiting frequency discriminator shortcoming. By adjusting the cavity length of interferometer, the speed of aerocraft can be detected and cut into several dynamic range. By this way, the Doppler wind lidar system can detect atmospheric parameters at the meantime, such as speed of aerocraft and temperature of atmosphere around the aerocraft, by analyzing the information of Rayleigh backscattering light. There are three main contribution in this paper: the first is discussing the basic theory of MOADS, calculational method and mathematic model of relative wind velocity between aircraft and wind are put forward.; the second is the parameter optimization of the dual-channel Fabry-Perot interferometer and the structure design of the interferometer; the third is the simulation of the performance and the accuracy of this system. Theory analysis and simulation results show this method is reasonable and practical.
Abshire, James B; Riris, Haris; Weaver, Clark J; Mao, Jianping; Allan, Graham R; Hasselbrack, William E; Browell, Edward V
We report on airborne CO(2) 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 CO(2) 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 8-10 km, and the majority of measurements for the column within it had precisions between 0.2 and 0.9 ppm.
Razak, K.A.; Bucksch, A.; Straatsma, M.W.; Abu Bakar, R.; Jong, S.M. de; Westen, C.J. van
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
Hamraz, Hamid; Contreras, Marco A.; Zhang, Jun
Airborne LiDAR point cloud representing a forest contains 3D data, from which vertical stand structure even of understory layers can be derived. This paper presents a tree segmentation approach for multi-story stands that stratifies the point cloud to canopy layers and segments individual tree crowns within each layer using a digital surface model based tree segmentation method. The novelty of the approach is the stratification procedure that separates the point cloud to an overstory and multiple understory tree canopy layers by analyzing vertical distributions of LiDAR points within overlapping locales. The procedure does not make a priori assumptions about the shape and size of the tree crowns and can, independent of the tree segmentation method, be utilized to vertically stratify tree crowns of forest canopies. We applied the proposed approach to the University of Kentucky Robinson Forest - a natural deciduous forest with complex and highly variable terrain and vegetation structure. The segmentation results showed that using the stratification procedure strongly improved detecting understory trees (from 46% to 68%) at the cost of introducing a fair number of over-segmented understory trees (increased from 1% to 16%), while barely affecting the overall segmentation quality of overstory trees. Results of vertical stratification of the canopy showed that the point density of understory canopy layers were suboptimal for performing a reasonable tree segmentation, suggesting that acquiring denser LiDAR point clouds would allow more improvements in segmenting understory trees. As shown by inspecting correlations of the results with forest structure, the segmentation approach is applicable to a variety of forest types.
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.
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.
Dorninger, Peter; Briese, Christian; Nothegger, Clemens; Klauser, Armin
Digital terrain models derived from airborne LiDAR (often referred to as airborne laser scanning) are commonly used for various applications in geomorphology. The ongoing development in sensor technology makes flight campaigns with some 10 points per square meter economically feasible for large areas. Simultaneously, the achievable accuracy of the originally acquired points as well as those of the derived products increases due to improved measurement techniques. Additionally, full-waveform (FWF) laser scanning systems record the time-dependent strength of the backscattered signal. This allows for the determination of numerous points (i.e. echoes) for one emitted laser beam hitting multiple targets within its footprint. Practically, about five echoes may be determined from the digitized signal form. Furthermore, additional attributes can be determined for each echo. These are, for example, a reflectivity measure (amplitude), the widening of the echo (echo width), or the sequence of the echoes of a single shot. By considering the polar measurement range and atmospheric conditions, a physical calibration of such measurements is possible. The application of FWF information to increase the accuracy and the reliability of digital terrain models especially in areas with dense vegetation was shown by Doneus & Briese (2006). However, these additional attributes are rarely used for object or landcover classification. This is still the domain of automated image interpretation (e.g. Zebedin et al., 2006). Nevertheless, image interpretation has well known deficiencies in areas with vegetation or if shadows occur. Therefore, we tested a hybrid approach which uses conventional first echo / last echo (FE/LE) airborne laser scanning data (first and last pulse) and an RGB-orthophoto. The testing site is located in an alpine area in Tyrol, Austria. For the classification, topographic models, a slope map, a local roughness measure and a penetration ratio were determined from the
Luciane Sato; Vitor Gomes; Yosio Shimabukuro; Michael Keller; Egidio Arai; Maiza dos-Santos; Irving Brown; Luiz Aragão
Fire is one of the main factors directly impacting Amazonian forest biomass and dynamics. Because of Amazoniaâs large geographical extent, remote sensing techniques are required for comprehensively assessing forest fire impacts at the landscape level. In this context, Light Detection and Ranging (LiDAR) stands out as a technology capable of retrieving direct...
Abshire, J. B.; Weaver, C. J.; Riris, H.; Mao, J.; Sun, X.; Allan, G. R.; Hasselbrack, W. E.; Browell, E. V.
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
Ewing, R. C.; Smith, V. B.; Mohrig, D. C.; Kocurek, G.
One explanation for the emergence of bedform-field patterns is self-organization via the interactions between the bedforms themselves. Models, remote images, field studies and lab experiments have identified bedform interactions that involve whole bedforms, only bedform defects, or that are remote interactions between bedforms. Observations suggest interactions form a spectrum from constructive to regenerative. Constructive interactions push the system toward fewer, larger, more widely spaced bedforms and regenerative interactions push the system toward a more initial state. Here we use time-series airborne LiDAR from White Sands Dune Field, New Mexico along with wind data from nearby Holloman Air Force Base to show spatial changes in erosion and deposition related to secondary airflow patterns across different types of interactions. Difference maps showing patterns of erosion and deposition of targeted interactions are generated from June 2007, June 2008, January 2009 and September 2009 LiDAR surveys. Secondary airflow maps based upon wind data are superimposed upon the difference maps to show how surface erosion and deposition covary with secondary airflow patterns. Results indicate that the portions of a dune with a crestline transverse to any given wind have the highest rates of deposition and change the fastest, whereas oblique and longitudinal portions of a crestline act primarily as bypassing crestline elements with only minor amounts of erosion and deposition. As the main dune body and defects approach one another secondary airflow patterns are modified to promote deposition or erosion along the downwind crestline. This, in turn, propagates the interaction. Because of the boundary condition of a strong seasonal variation in the wind regime at White Sands a portion of a crestline may be transverse, oblique or longitudinal depending on time of year, which affects the patterns of deposition and erosion through an interaction. Overall, the patterns of secondary
Carlos Alberto Silva; Carine Klauberg; Samuel de Padua Chaves e Carvalho; Andrew T. Hudak; e Luiz Carlos Estraviz. Rodriguez
Fast growing plantation forests provide a low-cost means to sequester carbon for greenhouse gas abatement. The aim of this study was to evaluate airborne LiDAR (Light Detection And Ranging) to predict aboveground carbon (AGC) stocks in Eucalyptus spp. plantations. Biometric parameters (tree height (Ht) and diameter at breast height (DBH)) were collected from...
Jim McKean; Dave Nagel; Daniele Tonina; Philip Bailey; Charles Wayne Wright; Carolyn Bohn; Amar Nayegandhi
The high-resolution Experimental Advanced Airborne Research LIDAR (EAARL) is a new technology for cross-environment surveys of channels and floodplains. EAARL measurements of basic channel geometry, such as wetted cross-sectional area, are within a few percent of those from control field surveys. The largest channel mapping errors are along stream banks. The LIDAR data...
Kiemle, Christoph; Groß, Silke; Wirth, Martin; Bugliaro, Luca
During the NARVAL (Next Generation Aircraft Remote Sensing for Validation Studies) field experiments in December 2013 and August 2016 the DLR lidar WALES (Water vapor Lidar Experiment in Space) was operated on board the German research aircraft HALO. The lidar simultaneously provided two-dimensional curtains of atmospheric backscatter and humidity along the flight track with high accuracy and spatial resolution, in order to help improve our knowledge on the coupling between water vapor, clouds, and circulation in the trades. The variability of water vapor, ubiquitous in our measurements, poses challenges to climate models because it acts on the small-scale low-cloud cover. Aloft, the very dry free troposphere in the subsiding branch of the Hadley cell acts as an open window in a greenhouse, efficiently cooling the lower troposphere. Secondary circulations between radiatively heated and cooled regions are supposed to occur, adding complexity to the situation. After recently having identified them to be mainly responsible for the uncertainty in global climate sensitivity, such interactions between shallow convection, circulation and radiation are at the heart of present scientific debate, endorsed by the WCRP (World Climate Research Programme) "Grand Challenge on Clouds, Circulation and Climate Sensitivity". Out of the wealth of about 30 winter and 60 summer flight hours totaling 75000 km of data over the Tropical Atlantic Ocean east of Barbados, several representative lidar segments from different flights are presented, together with Meteosat Second Generation (MSG) images and dropsonde profiles. All observations indicate high heterogeneity of the humidity in the lowest 5 km, as well as high variability of the depth of the cloud layer (1 - 2 km thick) and of the sub-cloud boundary layer ( 1 km thick). Layer depths and partial water vapor columns within the layers may vary by up to a factor of 2, and on a large range of horizontal scales. Occasionally, very dry, up
Hatten, James R.
The Mount Graham red squirrel (Tamiasciurus hudsonicus grahamensis) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.
Full Text Available An Ultra-Violet Rayleigh-Mie lidar has been integrated aboard the French research aircraft Falcon20 in order to monitor the ash plume emitted by the Eyjafjallajökul volcano in April–May 2010. Three operational flights were carried out on 21 April, 12 and 16 May 2010 inside French, Spanish and British air spaces, respectively. The original purpose of the flights was to provide the French civil aviation authorities with objective information on the presence and location of the ash plume. The present paper presents the results of detailed analyses elaborated after the volcano crisis. They bear on the structure of the ash clouds and their optical properties such as the extinction coefficient and the lidar ratio. Lidar ratios were measured in the range of 43 to 50 sr, in good agreement with the ratios derived from ground-based lidar near Paris (France in April 2010 (~48 sr. The ash signature in terms of particulate depolarization was consistent during all flights (between 34 ± 3 % and 38 ± 3%. Such a value seems to be a good identification parameter for volcanic ash. Using specific cross-sections between 0.19 and 1.1 m2 g−1, the minimum (maximal mass concentrations in the ash plumes derived for the flights on 12 and 16 May were 140 (2300 and 250 (1500 μg m−3, respectively. It may be rather less than, or of the order of the critical level of damage (2 mg m−3 for the aircraft engines, but well above the 200 μg m−3 warning level.
Chen, Tao; Zhang, Pei Zhen; Liu, Jing; Li, Chuan You; Ren, Zhi Kun; Hudnut, Kenneth W.
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.
Abshire, J. B.; Weaver, C. J.; Riris, H.; Mao, J.; Sun, X; Allan, G. R.; Hasselbrack, W. E.; Browell, E. V.
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 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 CO2 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 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 altitude. The
Vlaminck, Michiel; Luong, Hiep; Philips, Wilfried
In this work we present Liborg, a spatial mapping and localization system that is able to acquire 3D models on the y using data originated from lidar sensors. The novelty of this work is in the highly efficient way we deal with the tremendous amount of data to guarantee fast execution times while preserving sufficiently high accuracy. The proposed solution is based on a multi-resolution technique based on octrees. The paper discusses and evaluates the main benefits of our approach including its efficiency regarding building and updating the map and its compactness regarding compressing the map. In addition, the paper presents a working prototype consisting of a robot equipped with a Velodyne Lidar Puck (VLP-16) and controlled by a Raspberry Pi serving as an independent acquisition platform.
Full Text Available This contribution investigates the effects of wave patterns on 3D point coordinate accuracy in LiDAR bathymetry. The finite diameter refracted laser pulse path passing the air/water interface is modelled differentially and in a strict manner. Typical wave patterns are simulated and their impact on the 3D coordinates at the bottom of the water body are analysed. It can be shown that the effects of waves within small LiDAR bathymetry footprints on the depth and planimetry coordinates is significant. Planimetric effects may reach several decimetres or even metres, and depth coordinate errors also reach several decimetres, even in case of horizontal water body bottom. The simplified assumption of averaging wave effects often made in many ALB applications is not only fulfilled in cases of a very large beam divergence under certain wave pattern conditions. Modern smaller beam divergence systems will mostly experience significant wave pattern dependent coordinate errors. The results presented here thus form a basis for a more strict coordinate correction if the wave pattern can be modelled from the LiDAR bathymetry water surface reflections or other observations. Moreover, it will be shown that the induced coordinate errors contain systematic parts in addition to the local wave surface dependent quasi-random part, which allows for the formulation of wave pattern type dependent correction terms.
Swirski, A.; LaRocque, D. P.; Shaker, A.; Smith, B.
Traditional lidar designs have been restricted to using a single laser channel operating at one particular wavelength. Single-channel systems excel at collecting high-precision spatial (XYZ) data, with accuracies down to a few centimeters. However, target classification is difficult with spatial data alone, and single-wavelength systems are limited to the strengths and weaknesses of the wavelength they use. To resolve these limitations in lidar design, Teledyne Optech developed the Titan, the world's first multispectral lidar system, which uses three independent laser channels operating at 532, 1064, and 1550 nm. Since Titan collects 12 bit intensity returns for each wavelength separately, users can compare how strongly targets in the survey area reflect each wavelength. Materials such as soil, rock and foliage all reflect the wavelengths differently, enabling post-processing algorithms to identify the material of targets easily and automatically. Based on field tests in Canada, automated classification algorithms have combined this with elevation data to classify targets into six basic types with 78% accuracy. Even greater accuracy is possible with further algorithm enhancement and the use of an in-sensor passive imager such as a thermal, multispectral, CIR or RGB camera. Titan therefore presents an important new tool for applications such as land-cover classification and environmental modeling while maintaining lidar's traditional strengths: high 3D accuracy and day/night operation. Multispectral channels also enable a single lidar to handle both topographic and bathymetric surveying efficiently, which previously required separate specialized lidar systems operating at different wavelengths. On land, Titan can survey efficiently from 2000 m AGL with a 900 kHz PRF (300 kHz per channel), or up to 2500 m if only the infrared 1064 and 1550 nm channels are used. Over water, the 532 nm green channel penetrates water to collect seafloor returns while the infrared
Almasi S. Maguya
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.
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.
Full Text Available Lidar measurements of ozone and aerosol were conducted from a Twin Otter aircraft above the oil sands region of northern Alberta. For the majority of the flights, significant amounts of aerosol were observed within the boundary layer, up to an altitude of 2.0 km above sea level (ASL, while the ozone concentration remained at background levels (30-45 ppb downwind of the industry. On August 24th the lidar measured a separated layer of aerosol above the boundary layer, at a height of 2.0 km ASL, in which the ozone mixing ratio increased to 70 ppb. Backward trajectory calculations revealed that the air containing this separated aerosol layer had passed over an area of forest fires. Directly below the layer of forest fire smoke, pollution from the oil sands industry was observed. Measurements of the backscatter linear depolarization ratio were obtained with a ground based lidar operated by Environment Canada within the oil sands region. The depolarization measurements aided in discriminating between the separate sources of pollution from industry and forest fires. The depolarization ratio was 5-6% in forest fire smoke and 7-10% in the industrial pollution.
Nicholas R. Vaughn; Greg P. Asner; Christian P. Giardina
The structure of a forest canopy is the key determinant of light transmission, use and understory availability. Airborne light detection and ranging (LiDAR) has been used successfully to measure multiple canopy structural properties, thereby greatly reducing the fieldwork required to map spatial variation in structure. However, lidar metrics to date do not reflect the...
Singh, Upendra N.; Kavaya, Michael J.; Koch, Grady; Yu, Jirong; Ismail, Syed
NASA Langley Research Center has been developing 2-micron lidar technologies over a decade for wind measurements, utilizing coherent Doppler wind lidar technique and carbon dioxide measurements, utilizing Differential Absorption Lidar (DIAL) technique. Significant advancements have been made towards developing state-of-the-art technologies towards laser transmitters, detectors, and receiver systems. These efforts have led to the development of solid-state lasers with high pulse energy, tunablility, wavelength-stability, and double-pulsed operation. This paper will present a review of these technological developments along with examples of high resolution wind and high precision CO2 DIAL measurements in the atmosphere. Plans for the development of compact high power lasers for applications in airborne and future space platforms for wind and regional to global scale measurement of atmospheric CO2 will also be discussed.
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.
Burton, S. P.; Hair, J. W.; Kahnert, M.; Ferrare, R. A.; Hostetler, C. A.; Cook, A. L.; Harper, D. B.; Berkoff, T. A.; Seaman, S. T.; Collins, J. E.; Fenn, M. A.; Rogers, R. R.
Linear particle depolarization ratio is presented for three case studies from the NASA Langley airborne High Spectral Resolution Lidar-2 HSRL-2). Particle depolarization ratio from lidar is an indicator of non-spherical particles and is sensitive to the fraction of non-spherical particles and their size. The HSRL-2 instrument measures depolarization at three wavelengths: 355, 532, and 1064 nm. The three measurement cases presented here include two cases of dust-dominated aerosol and one case of smoke aerosol. These cases have partial analogs in earlier HSRL-1 depolarization measurements at 532 and 1064 nm and in literature, but the availability of three wavelengths gives additional insight into different scenarios for non-spherical particles in the atmosphere. A case of transported Saharan dust has a spectral dependence with a peak of 0.30 at 532 nm with smaller particle depolarization ratios of 0.27 and 0.25 at 1064 and 355 nm, respectively. A case of aerosol containing locally generated wind-blown North American dust has a maximum of 0.38 at 1064 nm, decreasing to 0.37 and 0.24 at 532 and 355 nm, respectively. The cause of the maximum at 1064 nm is inferred to be very large particles that have not settled out of the dust layer. The smoke layer has the opposite spectral dependence, with the peak of 0.24 at 355 nm, decreasing to 0.09 and 0.02 at 532 and 1064 nm, respectively. The depolarization in the smoke case may be explained by the presence of coated soot aggregates. We note that in these specific case studies, the linear particle depolarization ratio for smoke and dust-dominated aerosol are more similar at 355 nm than at 532 nm, having possible implications for using the particle depolarization ratio at a single wavelength for aerosol typing.
Michael H. Young
Full Text Available The Southwestern United States desert serves as the host for several threatened and endangered species, one of which is the desert tortoise (Gopherus agassizii. The goal of this study was to develop a fine-scale, remote-sensing-based approach that indicates favorable burrow locations for G. agassizii in the Boulder City (Nevada Conservation Easement area (35,500 ha. This was done by analyzing airborne LiDAR data (5–7 points/m2 and color imagery (four bands, 0.15-m resolution and determining the percent vegetation cover; shrub height and area; Normalized Difference Vegetation Index (NDVI; and several geomorphic characteristics including slope, azimuth, and roughness. Other field data used herein include estimates of canopy area and species richness using 1271 line transects, and shrub height and canopy area using plant-specific measurements of ~200 plants. Larrea tridentata and Ambrosia dumosa shrubs were identified using an algorithm that obtained an optimum combination of NDVI and average reflectance of the four bands (IR, R, G, and B from pixels in each image. The results, which identified more than 65 million shrubs across the study area, indicate that percent vegetation cover from aerial imagery across the site (13.92% compared favorably (14.52% to the estimate obtained from line transects, though the LiDAR method yielded shrub heights approximately 60% those of measured shrub heights. Landscape and plant properties were combined with known locations of tortoise burrows, as visually observed in 2014. Masks were created using roughness coefficient, slope percent, azimuth of burrow openings, elevation, and percent vegetation cover to isolate areas more likely to host burrows. Combined, the masks isolated 55% of the total survey area, which will help target future field surveys. Overall, the approach provides areas where tortoise burrows are more likely to be found, though additional ecological data would help refine the overall method.
Jawak, S. D.; Panditrao, S. N.; Luis, A. J.
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
National Aeronautics and Space Administration — Lidar high-resolution elevation digital elevation model data and low-resolution shaded relief maps of Antarctica are available for download from the U.S. Antarctic...
M. A. Dogon-Yaro
Full Text Available Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition 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 trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.
Dogon-Yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.
Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition 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 trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.
In this paper, a texture approach is presented for building and vegetation extraction from LIDAR and aerial images. The texture is very important attribute in many image analysis or computer vision applications. The procedures developed for texture problem can be subdivided into four categories: structural approach, statistical approach, model based approach and filter based approach. In this paper, different definitions of texture are described, but complete emphasis is given on filter based methods. Examples of filtering methods are Fourier transform, Gabor and wavelet transforms. Here, Gabor filter is studied and its implementation for texture analysis is explored. This approach is inspired by a multi-channel filtering theory for processing visual information in the human visual system. This theory holds that visual system decomposes the image into a number of filtered images of a specified frequency, amplitude and orientation. The main objective of the article is to use Gabor filters for automatic urban object and tree detection. The first step is a definition of Gabor filter parameters: frequency, standard deviation and orientation. By varying these parameters, a filter bank is obtained that covers the frequency domain almost completely. These filters are used to aerial images and LIDAR data. The filtered images that possess a significant information about analyzed objects are selected, and the rest are discarded. Then, an energy measure is defined on the filtered images in order to compute different texture features. The Gabor features are used to image segmentation using thresholding. The tests were performed using set of images containing very different landscapes: urban area and vegetation of varying configurations, sizes and shapes of objects. The performed studies revealed that textural algorithms have the ability to detect buildings and trees. This article is the attempt to use texture methods also to LIDAR data, resampling into regular grid cells. The
Ewing, R. C.
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
Full Text Available Use of a compact, low power commercial lidar onboard a small aircraft for aerosol studies is demonstrated. A Micro Pulse Lidar fitted upside down in a Beech Superking aircraft is used to measure the vertical distribution of aerosols in and around Hyderabad, an urban location in the central India. Two sorties were made, one on 17 February 2004 evening hours and the other on 18 February 2004 morning hours for a total flight duration of four hours. Three different algorithms, proposed by Klett (1985, Stephens et al. (2001 and Palm et al. (2002 for deriving the aerosol extinction coefficient profile from lidar data are studied and is shown that the results obtained from the three methods compare within 2%. The result obtained from the airborne lidar is shown more useful to study the aerosol distribution in the free troposphere than that obtained by using the same lidar from ground. Using standard radiative transfer model the aerosol radiative forcing is calculated and is shown that knowledge on the vertical distribution of aerosols is very important to get more realistic values than using model vertical profiles of aerosols. We show that for the same aerosol optical depth, single scattering albedo and asymmetry parameter but for different vertical profiles of aerosol extinction the computed forcing values differ with increasing altitude and improper selection of the vertical profile can even flip the sign of the forcing at tropopause level.
Lin, B. C.; You, R. J.
A quality prediction method is proposed to evaluate the quality of the automatic reconstruction of building models. In this study, LiDAR data and topographic maps are integrated for building model reconstruction. Hence, data registration is a critical step for data fusion. To improve the efficiency of the data fusion, a robust least squares method is applied to register boundary points extracted from LiDAR data and building outlines obtained from topographic maps. After registration, a quality indicator based on the tensor analysis of residuals is derived in order to evaluate the correctness of the automatic building model reconstruction. Finally, an actual dataset demonstrates the quality of the predictions for automatic model reconstruction. The results show that our method can achieve reliable results and save both time and expense on model reconstruction.
J. A. Seabrook
Full Text Available A differential absorption lidar (DIAL for measurement of atmospheric ozone concentration was operated aboard the Polar 5 research aircraft in order to study the depletion of ozone over Arctic sea ice. The lidar measurements during a flight over the sea ice north of Barrow, Alaska, on 3 April 2011 found a surface boundary layer depletion of ozone over a range of 300 km. The photochemical destruction of surface level ozone was strongest at the most northern point of the flight, and steadily decreased towards land. All the observed ozone-depleted air throughout the flight occurred within 300 m of the sea ice surface. A back-trajectory analysis of the air measured throughout the flight indicated that the ozone-depleted air originated from over the ice. Air at the surface that was not depleted in ozone had originated from over land. An investigation into the altitude history of the ozone-depleted air suggests a strong inverse correlation between measured ozone concentration and the amount of time the air directly interacted with the sea ice.
Moore, Alvah S., Jr.; Brown, Kevin E.; Hall, William M.; Barnes, James C.; Edwards, William C.; Petway, Larry B.; Little, Alan D.; Luck, William S., Jr.; Jones, Irby W.; Antill, Charles W., Jr.
The Lidar Atmospheric Sensing Experiment (LASE) Instrument is the first fully-engineered, autonomous Differential Absorption Lidar (DIAL) System for the measurement of water vapor in the troposphere (aerosol and cloud measurements are included). LASE uses a double-pulsed Ti:Sapphire laser for the transmitter with a 30 ns pulse length and 150 mJ/pulse. The laser beam is "seeded" to operate on a selected water vapor absorption line in the 815-nm region using a laser diode and an onboard absorption reference cell. A 40 cm diameter telescope collects the backscattered signals and directs them onto two detectors. LASE collects DIAL data at 5 Hz while onboard a NASA/Ames ER-2 aircraft flying at altitudes from 16-21 km. LASE was designed to operate autonomously within the environment and physical constraints of the ER-2 aircraft and to make water vapor profile measurements across the troposphere to better than 10% accuracy. LASE has flown 19 times during the development of the instrument and the validation of the science data. This paper describes the design, operation, and reliability of the LASE Instrument.
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.
H. M. Pagkalinawan
Full Text Available The Agricultural Resources Extraction from LiDAR Surveys (PARMAP project component of the Nationwide Detailed Resources Assessment using LiDAR (Phil-LiDAR 2 Program aims to produce detailed agricultural maps using LiDAR. Agricultural land cover at crop level was classified through object based image analysis using Support Vector Machine as classifier and LiDAR derivatives from point cloud (2 points per sq.m. and orthophoto (0.5-meter resolution as inputs. An accuracy of at least 90 %, assessed using validation points from the field and through image interpretation, was required before proceeding to post-processing and map lay-out. Knowledge sharing and capacity development facilitated by the University of the Philippines Diliman (UPD enabled partner universities across the Philippines to produce outputs for their assigned region. Considering output layers were generated by multiple teams working on different landscape complexities with some degree of data quality variability, quality checking is crucial to ensure accuracy standards were met. UPD PARMap devised a centralized and end-to-end scheme divided into four steps – land classification, GIS post-processing, schema application, and map lay-out. At each step, a block is reviewed and, subsequently, either approved or returned with documentation on required revisions. Turnaround time of review is at least one block (area ranging from 10 to 580 sq. km. per day. For coastal municipalities, an additional integration process to incorporate mapped coastal features was applied. Common problems observed during quality checking include misclassifications, gaps between features, incomplete attributes and missing map elements. Some issues are particular to specific blocks such as problematic LiDAR derivatives. UPD addressed these problems through discussion and mentoring visits to partner universities. As of March 2017, a total of 336 municipal agricultural maps have been turned-over to various
Ramanathan, A. K.; Mao, J.; Abshire, J. B.; Kawa, S. R.
Remote sensing measurements of CO2 from space can help improve our understanding of the carbon cycle and help constrain the global carbon budget. However, such measurements need to be sufficiently accurate to detect small (1 ppm) changes in the CO2 mixing ratio (XCO2) against a large background (~ 400 ppm). Satellite measurements of XCO2 using passive spectrometers, such as those from the Japanese GOSAT (Greenhouse gas Observing Satellite) and the NASA OCO-2 (Orbiting Carbon Observatory-2) are limited to daytime sunlit portions of the Earth and are susceptible to biases from clouds and aerosols. For this reason, NASA commissioned the formulation study of ASCENDS a space-based lidar mission. NASA Goddard Space Flight Center's CO2 Sounder lidar is one candidate approach for the ASCENDS mission. The NASA GSFC CO2 Sounder measures the CO2 mixing ratio using a pulsed multi-wavelength integrated path differential absorption (IPDA) approach. The CO2 Sounder has flown in the 2011, 2013 and 2014 ASCENDS airborne campaigns over the continental US, and has produced measurements in close agreement with in situ measurements of the CO2 column. In 2014, the CO2 Sounder upgraded its laser with a precision step-locked diode laser source to improve the lidar wavelength position accuracy. It also improved its optical receiver with a low-noise, high efficiency, HgCdTe avalanche photo diode detector. The combination of these two technologies enabled lidar XCO2 measurements with unprecedented accuracy. In this presentation, we show analysis from the ASCENDS 2014 field campaign, exploring: (1) Horizontal XCO2 gradients measured by the lidar, (2) Comparisons of lidar XCO2 measurements against the Parameterized Chemistry Transport Model (PCTM), and (3) Lidar column water vapor measurements using a HDO absorption line that occurs next to the CO2 absorption line. This can reduce the uncertainty in the dry air column used in XCO2 retrievals.
Hill, John M.; Krenek, Brendan D.; Kunz, Terry D.; Krabill, William; Stetina, Fran
The National Aeronautics and Space Administration (NASA) at Goddard Space Flight Center (GSFC) has developed a laser ranging device (LIDAR) which provides accurate and timely data of earth features. NASA/GSFC recently modified the sensor to include a scanning capability to produce LIDAR swaths. They have also integrated a Global Positioning System (GPS) and an Inertial Navigation System (INS) to accurately determine the absolute aircraft location and aircraft attitude (pitch, yaw, and roll), respectively. The sensor has been flown in research mode by NASA for many years. The LIDAR has been used in different configurations or modes to acquire such data as altimetry (topography), bathymetry (water depth), laser-induced fluorosensing (tracer dye movements, oil spills and oil thickness, chlorophyll and plant stress identification), forestry, and wetland discrimination studies. NASA and HARC are developing a commercial version of the instrument for topographic mapping applications. The next phase of the commercialization project will be to investigate other applications such as wetlands mapping and coastal bathymetry. In this paper we report on preliminary laboratory measurements to determine the feasibility of making accurate depth measurements in relatively shallow water (approximately 2 to 6 feet deep) using a LIDAR system. The LIDAR bathymetry measurements are relatively simple in theory. The water depth is determined by measuring the time interval between the water surface reflection and the bottom surface reflection signals. Depth is then calculated by dividing by the index of refraction of water. However, the measurements are somewhat complicated due to the convolution of the water surface return signal with the bottom surface return signal. Therefore in addition to the laboratory experiments, computer simulations of the data were made to show these convolution effects in the return pulse waveform due to: (1) water depth, and (2) changes in bottom surface
Currier, W. R.; Giulia, M.; Pflug, J. M.; Jonas, T.; Jessica, L.
Snow depth within a typical hydrologic model grid cell (150 m or 1 km) can vary from 0.5 meters to 6 meters, or more. This variability is driven by the meteorological conditions throughout the winter as well as the forest architecture. To better understand this variability, we used airborne LiDAR from Olympic National Park, WA, Yosemite National Park, CA, Jemez Caldera, NM, and Niwot Ridge, CO to determine unique spatial patterns of snow depth in forested regions. Specifically, we compared snow depth distributions along north facing forest edges and south facing forest edges to those in the open or directly under the canopy. When categorizing the north facing and south facing edges based on distance from the canopy, distances relative to tree height, and distances relative to the fraction of the sky that is visible (sky view factor) we found unique snow depth patterns for each of these regions. In all regions besides Olympic National Park, WA, north facing edges contained more snow than open areas, forested areas, or along the south facing edges. These snow distributions were relatively consistent regardless of the metric used to define the forest edge and the size of the domain (150 m through 1 km). The absence of the forest edge effect in Olympic National Park was attributed to the meteorological data and climate conditions, which showed significantly less incoming shortwave radiation and more incoming longwave radiation. Furthermore, this study evaluated the effect that wind speed and direction have on the spatial distribution of snow depth.
Full Text Available As one of the key steps in the processing of airborne light detection and ranging (LiDAR data, filtering often consumes a huge amount of time and physical memory. Conventional sequential algorithms are often inefficient in filtering massive point clouds, due to their huge computational cost and Input/Output (I/O bottlenecks. The progressive TIN (Triangulated Irregular Network densification (PTD filter is a commonly employed iterative method that mainly consists of the TIN generation and the judging functions. However, better quality from the progressive process comes at the cost of increasing computing time. Fortunately, it is possible to take advantage of state-of-the-art multi-core computing facilities to speed up this computationally intensive task. A streaming framework for filtering point clouds by encapsulating the PTD filter into independent computing units is proposed in this paper. Through overlapping multiple computing units and the I/O events, the efficiency of the proposed method is improved greatly. More importantly, this framework is adaptive to many filters. Experiments suggest that the proposed streaming PTD (SPTD is able to improve the performance of massive point clouds processing and alleviate the I/O bottlenecks. The experiments also demonstrate that this SPTD allows the quick processing of massive point clouds with better adaptability. In a 12-core environment, the SPTD gains a speedup of 7.0 for filtering 249 million points.
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.
Maher Ibrahim Sameen
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
Gleason, C. J.; Im, J.
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
Korb, C. Laurence; Schwemmer, Geary K.; Dombrowski, Mark; Weng, Chi Y.
The first high accuracy remote measurements of the atmospheric pressure profile have been made. The measurements were made with a differential absorption lidar system that utilizes tunable alexandrite lasers. The absorption in the trough between two lines in the oxygen A-band near 760 nm was used for probing the atmosphere. Measurements of the two-dimensional structure of the pressure field were made in the troposphere from an aircraft looking down. Also, measurements of the one-dimensional structure were made from the ground looking up. Typical pressure accuracies for the aircraft measurements were 1.5-2 mbar with a 30-m vertical resolution and a 100-shot average (20 s), which corresponds to a 2-km horizontal resolution. Typical accuracies for the upward viewing ground based measurements were 2.0 mbar for a 30-m resolution and a 100-shot average.
Full Text Available For multi-sensor integrated systems, such as the mobile mapping system (MMS, data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.
Full Text Available Large-scale coastal reclamation has caused significant changes in Spartina alterniflora (S. alterniflora distribution in coastal regions of China. However, few studies have focused on estimation of the wetland vegetation biomass, especially of S. alterniflora, in coastal regions using LiDAR and hyperspectral data. In this study, the applicability of LiDAR and hypersectral data for estimating S. alterniflora biomass and mapping its distribution in coastal regions of China was explored to attempt problems of wetland vegetation biomass estimation caused by different vegetation types and different canopy height. Results showed that the highest correlation coefficient with S. alterniflora biomass was vegetation canopy height (0.817, followed by Normalized Difference Vegetation Index (NDVI (0.635, Atmospherically Resistant Vegetation Index (ARVI (0.631, Visible Atmospherically Resistant Index (VARI (0.599, and Ratio Vegetation Index (RVI (0.520. A multivariate linear estimation model of S. alterniflora biomass using a variable backward elimination method was developed with R squared coefficient of 0.902 and the residual predictive deviation (RPD of 2.62. The model accuracy of S. alterniflora biomass was higher than that of wetland vegetation for mixed vegetation types because it improved the estimation accuracy caused by differences in spectral features and canopy heights of different kinds of wetland vegetation. The result indicated that estimated S. alterniflora biomass was in agreement with the field survey result. Owing to its basis in the fusion of LiDAR data and hyperspectral data, the proposed method provides an advantage for S. alterniflora mapping. The integration of high spatial resolution hyperspectral imagery and LiDAR data derived canopy height had significantly improved the accuracy of mapping S. alterniflora biomass.
Skou, Niels; Kristensen, Steen Savstrup; Søbjærg, Sten Schmidl
A 350 km × 350 km area near the Concordia station on the high plateau of Dome-C in Antarctica has been mapped by an airborne L-band radiometer system. The area was expected to display a rather uniform brightness temperature (TB) close to the yearly mean temperature-well suited for calibration...
Skou, Niels; Kristensen, Steen Savstrup; Søbjærg, Sten Schmidl
A 350 × 350 km area near the Concordia station on the high plateau of Dome C in Antarctica has been mapped by an airborne L-band radiometer system. The area was expected to display a rather uniform brightness temperature close to the yearly mean temperature — well suited for calibration checks...
Razak, Khamarrul Azahari; van Westen, C.J.; Straatsma, Menno; ... [et al.],
Mapping elements at risk for landslides in the tropics pose as a challenging task. Aerial-photograph, satellite imagery, and synthetic perture radar images are less effective to accurately provide physical presence of objects in a relatively short time. In this paper, we utilized an airborne laser
Jeong, J.; Lee, I.
Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.
Full Text Available Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.
Alexander, Cici; Moeslund, Jesper Erenskjold; Bøcher, Peder Klith
on the average Ellenberg indicator values for light for the plant species present in a given plot. The correlations of Ellenberg values with ALS-based canopy closure were higher (r2: 0.47) than those with ALS-based canopy cover (r2: 0.26) and densiometer readings (r2: 0.41) for the forest sites. ALS-based canopy......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...... 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...
Simard, M.; Denbina, M. W.
Using data collected by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Land, Vegetation, and Ice Sensor (LVIS) lidar, we have estimated forest canopy height for a number of study areas in the country of Gabon using a new machine learning data fusion approach. Using multi-baseline polarimetric synthetic aperture radar interferometry (PolInSAR) data collected by UAVSAR, forest heights can be estimated using the random volume over ground model. In the case of multi-baseline UAVSAR data consisting of many repeat passes with spatially separated flight tracks, we can estimate different forest height values for each different image pair, or baseline. In order to choose the best forest height estimate for each pixel, the baselines must be selected or ranked, taking care to avoid baselines with unsuitable spatial separation, or severe temporal decorrelation effects. The current baseline selection algorithms in the literature use basic quality metrics derived from the PolInSAR data which are not necessarily indicative of the true height accuracy in all cases. We have developed a new data fusion technique which treats PolInSAR baseline selection as a supervised classification problem, where the classifier is trained using a sparse sampling of lidar data within the PolInSAR coverage area. The classifier uses a large variety of PolInSAR-derived features as input, including radar backscatter as well as features based on the PolInSAR coherence region shape and the PolInSAR complex coherences. The resulting data fusion method produces forest height estimates which are more accurate than a purely radar-based approach, while having a larger coverage area than the input lidar training data, combining some of the strengths of each sensor. The technique demonstrates the strong potential for forest canopy height and above-ground biomass mapping using fusion of PolInSAR with data from future spaceborne lidar missions such as the upcoming Global Ecosystems
Full Text Available A 2013 survey of a 40 square kilometer area surrounding Mayapán, Yucatan, Mexico used high-density LiDAR data to map prehispanic architecture and related natural features. Most of the area is covered by low canopy dense forest vegetation over karstic hilly terrain that impedes full coverage archaeological survey. We used LiDAR at 40 laser points per square meter to generate a bare earth digital elevation model (DEM. Results were evaluated with comparisons to previously mapped areas and with traditional archaeological survey methods for 38 settlement clusters outside of the city wall. Ground checking employed full coverage survey of selected 500 m grid squares, as well as documentation of the chronology and detail of new public and domestic settlement features and cenotes. Results identify the full extent of continued, contemporary Postclassic settlement (A.D. 1150–1450 outside of the city wall to at least 500 meters to the east, north, and west. New data also reveal an extensive modified landscape of terraformed residential hills, rejolladas, and dense settlement dating from Preclassic through Classic Periods. The LiDAR data also allow for the identification of rooms, benches, and stone property walls and lanes within the city.
Gu, H.; Townsend, P. A.; Singh, A.
Urban forests provide important ecosystem services related to climate, nutrients, runoff and aesthetics. Assessment of variations in urban forest growth is critical to urban management and planning, as well as to identify responses to climate and other environmental changes. We estimated annual relative basal area increment by tree rings from 37 plots in Madison, Wisconsin and neighboring municipalities. We related relative basal area growth to variables of vegetation traits derived from remote sensing, including structure (aboveground biomass, diameter, height, basal area, crown width and crown length) from discrete-return airborne lidar, and biochemical variables (foliar nitrogen, carbon, lignin, cellulose, fiber and LMA), spectral indices (NDVI, NDWI, PRI, NDII etc.) and species composition from AVIRIS hyperspectral imagery. Variations in tree growth was mainly correlated with tree species composition (R2 = 0.29, RMSE = 0.004) with coniferous stands having a faster growth rate than broadleaf plots. Inclusion of stand basal area improved model prediction from R2 = 0.29 to 0.35, with RMSE = 0.003. Then, we assessed the growth by functional type, we found that foliar lignin concentration and the proportion of live coniferous trees explained 57% variance in the growth of conifer stands. In contrast, broadleaf forest growth was more strongly correlated with species composition and foliar carbon (R2 = 0.59, RMSE = 0.003). Finally, we compared the relative basal area growth by species. In our study area, red pine and white pine exhibited higher growth rates than other species, while white oak plots grew slowest. There is a significant negative relationship between tree height and the relative growth in red pine stands (r = -0.95), as well as a strong negative relationship between crown width and the relative growth in white pine stands (r = -0.87). Growth declines as trees grow taller and wider may partly be the result of reduced photosynthesis and water availability
Mao, J.; Ramanathan, A. K.; Rodriguez, M.; Allan, G. R.; Hasselbrack, W. E.; Abshire, J. B.; Riris, H.; Kawa, S. R.
NASA Goddard is developing an integrated-path, differential absorption (IPDA) lidar approach to measure atmospheric CO2 concentrations from space as a candidate for NASA's ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons) mission. The approach uses pulsed lasers to measure both CO2 and O2 absorption simultaneously in the vertical path to the surface at a number of wavelengths across a CO2 line at 1572.335 nm and an O2 line doublet near 764.7 nm. Measurements of time-resolved laser backscatter profiles from the atmosphere allow the technique to estimate column CO2 and O2 number density and range to cloud tops in addition to those to the ground. This allows retrievals of CO2 column above clouds and cloud top pressure, and all-sky measurement capability from space. This additional information can be used to evaluate atmospheric transport processes and other remote sensing carbon data in the free atmosphere, improve carbon data assimilation in models and help global and regional carbon flux estimates. We show some preliminary results of this capability using airborne lidar measurements from the summers of 2011 and 2014 ASCENDS science campaigns. These show simultaneous retrievals of CO2 and O2 column densities for laser returns from low-level marine stratus clouds in the west coast of California. This demonstrates the supplemental capability of the future space carbon mission to measure CO2 above clouds, which is valuable particularly for the areas with persistent cloud covers, e.g, tropical ITCZ, west coasts of continents with marine layered clouds and southern ocean with highest occurrence of low-level clouds, where underneath carbon cycles are active but passive remote sensing techniques using the reflected short wave sunlight are unable to measure accurately due to cloud scattering effect. We exercise cloud top pressure retrieval from O2 absorption measurements during the flights over the low-level marine stratus cloud decks, which is one of
Gross, S.; Gutleben, M.; Wirth, M.; Ewald, F.
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
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)
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)
Zhang, J.; Emmitt, G. D.; Atlas, R. M.; Bucci, L. R.; Ryan, K. E.; O'Handley, C.; Marks, F.
This talk presents analysis of the Doppler Wind Lidar (DWL) measured wind profiles in Tropical Storm (TS) Erika (2015) by NOAA's P3 aircraft. This work was funded by NOAA's Sandy Supplemental Program that supports new technologies such as the DWL for hurricane research. It is for the first time, the DWL onboard a NOAA P3 has become operational in hurricane reconnaissance missions and collected high-quality wind profile data. The DWL wind profiles were first verified against the collocated dropsonde and Doppler radar observations, showing good agreement. To the authors' knowledge, the DWL data collected in TS Erika provided the best data coverage in the boundary layer of any given TS. This data set allows us to investigate the detailed boundary layer structure, including the boundary layer height, the strength of the inflow and outflow, and their asymmetric distributions. Composite analysis of the DWL data shows that the axisymmetric boundary layer structure of TS Erika is largely different from that of a typical hurricane from previous dropsonde observations. The vorticity budget conducted using the DWL data suggests that the boundary layer of TS Erika is far from being in vorticity balance. The large magnitude of boundary-layer divergence and the small magnitude of mass flux above the boundary layer may explain why TS Erika did not intensify during the period of observation. The boundary-layer structure asymmetry is found to be tied to the vortex tilt that is induced by the environmental vertical wind shear.
Pelon, J.; Flamant, C.; Trouillet, V.; Flamant, P. H.
Cloud parameters derived from measurements performed with the airborne backscatter lidar LEANDRE 1 during mission 206 of the EUCREX '94 campaign are reported. A new method has been developed to retrieve the extinction coefficient at the top of the dense stratocumulus deck under scrutiny during this mission. The largest extinction values are found to be related to the highest cloud top altitude revealing the small-scale structure of vertical motions within the stratocumulus field. Cloud optical depth (COD) is estimated from extinction retrievals, as well as cloud top and cloud base altitude using nadir and zenith lidar observations, respectively. Lidar-derived CODs are compared with CODs deduced from radiometric measurements made onboard the French research aircraft Avion de Recherche Atmosphérique et de Télédétection (ARAT/F27). A fair agreement is obtained (within 20%) for COD's larger than 10. Our results show the potential of lidar measurements to analyze cloud properties at optical depths larger than 5.
Alshaiba, Omar; Amparo Núñez-Andrés, M.; Lantada, Nieves
Mobile LiDAR system provides a new technology which can be used to update geospatial information by direct and rapid data collection. This technology is faster than the traditional survey ways and has lower cost. Abu Dhabi Municipal System aims to update its geospatial system frequently as the government entities have invested heavily in GIS technology and geospatial data to meet the repaid growth in the infrastructure and construction projects in recent years. The Emirate of Abu Dhabi has witnessed a huge growth in infrastructure and construction projects in recent years. Therefore, it is necessary to develop and update its basemap system frequently to meet their own organizational needs. Currently, the traditional ways are used to update basemap system such as human surveyors, GPS receivers and controller (GPS assigned computer). Then the surveyed data are downloaded, edited and reviewed manually before it is merged to the basemap system. Traditional surveying ways may not be applicable in some conditions such as; bad weather, difficult topographic area and boundary area. This paper presents a proposed methodology which uses the Mobile LiDAR system to update basemap in Abu Dhabi by using daily transactions services. It aims to use and integrate the mobile LiDAR technology into the municipality's daily workflow such that it becomes the new standard cost efficiency operating procedure for updating the base-map in Abu Dhabi Municipal System. On another note, the paper will demonstrate the results of the innovated workflow for the base-map update using the mobile LiDAR point cloud and few processing algorithms.
Tabor, Rowland W.; Booth, Derek B.; Troost, Kathy Goetz
For this map, we interpreted a 6-ft-resolution lidar digital elevation model combined with the geology depicted on the Geologic Map of the Poverty Bay 7.5' Quadrangle, King and Pierce Counties, Washington (Booth and others, 2004b). The authors of the 2004 map described, interpreted, and located the geology on the 1:24,000-scale topographic map of the Poverty Bay 7.5' quadrangle.
Ponsardin, Patrick; Grossmann, Benoist E.; Browell, Edward V.
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.
Full Text Available Three extended airborne Differential Absorption Lidar (DIAL sections of tropospheric water vapour across the tropical and sub-tropical Atlantic in March 2004 are compared to short-term forecasts of the European Centre for Medium Range Weather Forecasts (ECMWF. The humidity fields between 28° S and 36° N exhibit large inter air-mass gradients and reflect typical transport patterns of low- and mid-latitudes like convection (e.g. Hadley circulation, subsidence and baroclinic development with stratospheric intrusion. These processes re-distribute water vapour vertically such that locations with extraordinary dry/moist air-masses are observed in the lower/upper troposphere, respectively. The mixing ratios range over 3 orders of magnitude. Back-trajectories are used to trace and characterize the observed air-masses.
Overall, the observed water vapour distributions are largely reproduced by the short-term forecasts at 0.25° resolution (T799/L91, the correlation ranges from 0.69 to 0.92. Locally, large differences occur due to comparably small spatial shifts in presence of strong gradients. Systematic deviations are found associated with specific atmospheric domains. The planetary boundary layer in the forecast is too moist and to shallow. Convective transport of humidity to the middle and upper troposphere tends to be overestimated. Potential impacts arising from data assimilation and model physics are considered. The matching of air-mass boundaries (transport is discussed with repect to scales and the representativity of the 2-D sections for the 3-D humidity field. The normalized bias of the model with respect to the observations is 6%, 11% and 0% (moist model biases for the three along-flight sections, whereby however the lowest levels are excluded.
Schmiemann, J.; Harms, H.; Schattenberg, J.; Becker, M.; Batzdorfer, S.; Frerichs, L.
In this paper we are presenting work done within the joint development project ANKommEn. It deals with the development of a highly automated robotic system for fast data acquisition in civil disaster scenarios. One of the main requirements is a versatile system, hence the concept embraces a machine cluster consisting of multiple fundamentally different robotic platforms. To cover a large variety of potential deployment scenarios, neither the absolute amount of participants, nor the precise individual layout of each platform shall be restricted within the conceptual design. Thus leading to a variety of special requirements, like onboard and online data processing capabilities for each individual participant and efficient data exchange structures, allowing reliable random data exchange between individual robots. We are demonstrating the functionality and performance by means of a distributed mapping system evaluated with real world data in a challenging urban and rural indoor/outdoor scenarios.
Full Text Available In this paper we are presenting work done within the joint development project ANKommEn. It deals with the development of a highly automated robotic system for fast data acquisition in civil disaster scenarios. One of the main requirements is a versatile system, hence the concept embraces a machine cluster consisting of multiple fundamentally different robotic platforms. To cover a large variety of potential deployment scenarios, neither the absolute amount of participants, nor the precise individual layout of each platform shall be restricted within the conceptual design. Thus leading to a variety of special requirements, like onboard and online data processing capabilities for each individual participant and efficient data exchange structures, allowing reliable random data exchange between individual robots. We are demonstrating the functionality and performance by means of a distributed mapping system evaluated with real world data in a challenging urban and rural indoor/outdoor scenarios.
Jung, Jaewook; Jwa, Yoonseok; Sohn, Gunho
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