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Remote Sens., Volume 3, Issue 3 (March 2011), Pages 416-649

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Open AccessArticle Airborne Lidar: Advances in Discrete Return Technology for 3D Vegetation Mapping
Remote Sens. 2011, 3(3), 416-434; doi:10.3390/rs3030416
Received: 30 December 2010 / Revised: 9 February 2011 / Accepted: 10 February 2011 / Published: 25 February 2011
Cited by 24 | PDF Full-text (786 KB) | HTML Full-text | XML Full-text
Abstract
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
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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 information for modeling and analysis, which have traditionally been applied mostly to full waveform data. Full article
(This article belongs to the Special Issue 100 Years ISPRS - Advancing Remote Sensing Science)
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Open AccessArticle GPS Bias Correction and Habitat Selection by Mountain Goats
Remote Sens. 2011, 3(3), 435-459; doi:10.3390/rs3030435
Received: 23 December 2010 / Revised: 24 February 2011 / Accepted: 24 February 2011 / Published: 28 February 2011
Cited by 6 | PDF Full-text (934 KB) | HTML Full-text | XML Full-text
Abstract
In Washington State, USA, mountain goats (Oreamnos americanus) have experienced a long-term population decline. To assist management, we created annual and seasonal (summer and winter) habitat models based on 2 years of data collected from 38 GPS-collared (GPS plus collar v6,
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In Washington State, USA, mountain goats (Oreamnos americanus) have experienced a long-term population decline. To assist management, we created annual and seasonal (summer and winter) habitat models based on 2 years of data collected from 38 GPS-collared (GPS plus collar v6, Vectronic-Aerospace GmbH, Berlin, Germany) mountain goats in the western Cascades. To address GPS bias of position acquisition, we evaluated habitat and physiographic effects on GPS collar performance at 543 sites in the Cascades. In the western Cascades, total vegetation cover and the quadratic mean diameter of trees were shown to effect GPS performance. In the eastern Cascades, aspect and total vegetation cover were found to influence GPS performance. To evaluate the influence of bias correction on the analysis of habitat selection, we created resource selection functions with and without bias correction for mountain goats in the western Cascades. We examined how well the resultant habitat models performed with reserved data (25% of fixes from 38 study animals) and with data from 9 other GPS-collared mountain goats that were both temporally and spatially independent. The statistical properties of our GPS bias correction model were similar to those previously reported explaining between 20 and 30% of the variation, however, application of bias correction improved the accuracy of the mountain goat habitat model by only 1–2% on average and did not alter parameter estimates in a meaningful, or consistent manner. Despite statistical limitations, our habitat models, most notably during the winter, provided the widest extent and most detailed models of the distribution of mountain goat habitat in the Cascades yet developed. Full article
(This article belongs to the Special Issue Global Positioning Systems (GPS) and Applications)
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Open AccessArticle Mapping Fish Community Variables by Integrating Field and Satellite Data, Object-Based Image Analysis and Modeling in a Traditional Fijian Fisheries Management Area
Remote Sens. 2011, 3(3), 460-483; doi:10.3390/rs3030460
Received: 22 December 2010 / Revised: 1 February 2011 / Accepted: 21 February 2011 / Published: 1 March 2011
Cited by 13 | PDF Full-text (697 KB) | HTML Full-text | XML Full-text
Abstract
The use of marine spatial planning for zoning multi-use areas is growing in both developed and developing countries. Comprehensive maps of marine resources, including those important for local fisheries management and biodiversity conservation, provide a crucial foundation of information for the planning process.
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The use of marine spatial planning for zoning multi-use areas is growing in both developed and developing countries. Comprehensive maps of marine resources, including those important for local fisheries management and biodiversity conservation, provide a crucial foundation of information for the planning process. Using a combination of field and high spatial resolution satellite data, we use an empirical procedure to create a bathymetric map (RMSE 1.76 m) and object-based image analysis to produce accurate maps of geomorphic and benthic coral reef classes (Kappa values of 0.80 and 0.63; 9 and 33 classes, respectively) covering a large (>260 km2) traditional fisheries management area in Fiji. From these maps, we derive per-pixel information on habitat richness, structural complexity, coral cover and the distance from land, and use these variables as input in models to predict fish species richness, diversity and biomass. We show that random forest models outperform five other model types, and that all three fish community variables can be satisfactorily predicted from the high spatial resolution satellite data. We also show geomorphic zone to be the most important predictor on average, with secondary contributions from a range of other variables including benthic class, depth, distance from land, and live coral cover mapped at coarse spatial scales, suggesting that data with lower spatial resolution and lower cost may be sufficient for spatial predictions of the three fish community variables. Full article
(This article belongs to the Special Issue Remote Sensing in Coastal Ecosystem)
Open AccessArticle Advantages of the Boresight Effect in Hyperspectral Data Analysis
Remote Sens. 2011, 3(3), 484-502; doi:10.3390/rs3030484
Received: 18 December 2010 / Revised: 16 February 2011 / Accepted: 18 February 2011 / Published: 1 March 2011
Cited by 4 | PDF Full-text (1157 KB) | HTML Full-text | XML Full-text
Abstract
Dual pushbroom hyperspectral sensors consist of two different instruments (covering different wavelengths) that are usually mounted on the same optical bench. This configuration leads to problems, such as co-registration of pixels and squint of the field of view, known as the boresight effect.
[...] Read more.
Dual pushbroom hyperspectral sensors consist of two different instruments (covering different wavelengths) that are usually mounted on the same optical bench. This configuration leads to problems, such as co-registration of pixels and squint of the field of view, known as the boresight effect. Determination of image-orientation parameters is due to the combination of an inertial measurement system (IMU) and global position system (GPS). The different positions of the IMU, the GPS antenna and the imaging sensors cause the orientation and boresight effect. Any small change in the correction of the internal orientation affects the co-registration between images extracted from the two instruments. Correcting the boresight effect is a key and almost automatic task performed by all dual-system users to better analyze the full spectral information of a given pixel. Thus, the boresight effect is considered to be noise in the system and a problem that needs to be corrected prior to any (thematic) data analysis. We propose using the boresight effect, prior to its correction, as a tool to monitor and detect spectral phenomena that can provide additional information not present in the corrected images. The advantage of using this effect was investigated with the AISA-Dual sensor, composed of an EAGLE sensor for the VIS-NIR (VNIR) region (400–970 nm) and HAWK for the SWIR region (980–2,450 nm). During the course of more than six years of operating this sensor, we have found that the boresight effect provides a new capacity to analyze hyperspectral data, reported herein. Accordingly, we generated a protocol to use this effect for three applications: (1) enhancing the shadow effect; (2) generating a 3-D view; and (3) better detecting spectral/spatial anomalies based on sub-pixel edge detection. This paper provides examples of these applications and suggests possible uses from an airborne platform. Full article
(This article belongs to the Special Issue 100 Years ISPRS - Advancing Remote Sensing Science)
Open AccessArticle Roughness Mapping on Various Vertical Scales Based on Full-Waveform Airborne Laser Scanning Data
Remote Sens. 2011, 3(3), 503-523; doi:10.3390/rs3030503
Received: 7 January 2011 / Revised: 28 February 2011 / Accepted: 1 March 2011 / Published: 4 March 2011
Cited by 20 | PDF Full-text (1981 KB) | HTML Full-text | XML Full-text
Abstract
Roughness is an important input parameter for modeling of natural hazards such as floods, rock falls and avalanches, where it is basically assumed that flow velocities decrease with increasing roughness. Seeing roughness as a multi-scale level concept (i.e., ranging from fine-scale soil
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Roughness is an important input parameter for modeling of natural hazards such as floods, rock falls and avalanches, where it is basically assumed that flow velocities decrease with increasing roughness. Seeing roughness as a multi-scale level concept (i.e., ranging from fine-scale soil characteristics to description of understory and lower tree layer) various roughness raster products were derived from the original full-waveform airborne laser scanning (FWF-ALS) point cloud using two different types of roughness parameters, the surface roughness (SR) and the terrain roughness (TR). For the calculation of the SR, ALS terrain points within a defined height range to the terrain surface are considered. For the parameterization of the SR, two approaches are investigated. In the first approach, a geometric description by calculating the standard deviation of plane fitting residuals of terrain points is used. In the second one, the potential of the derived echo widths are analyzed for the parameterization of SR. The echo width is an indicator for roughness and the slope of the target. To achieve a comparable spatial resolution of both SR layers, the calculation of the standard deviation of detrended terrain points requires a higher terrain point density than the SR parameterization using the echo widths. The TR describes objects (i.e., point clusters) close but explicitly above the terrain surface, with 20 cm defined as threshold height value for delineation of the surface layer (i.e., forest floor layer). Two different empirically defined vegetation layers below the canopy layer were analyzed (TR I: 0.2 m to 1.0 m; TR II: 0.2 m to 3.0 m). A 1 m output grid cell size was chosen for all roughness parameters in order to provide consistency for further integration of high-resolution optical imagery. The derived roughness parameters were then jointly classified, together with a normalized Digital Surface Model (nDSM) showing the height of objects (i.e., trees) above ground. The presented approach enables the classification of forested areas in patches of different vegetation structure (e.g., varying soil roughness, understory, density of natural cover). For validation purposes in situ reference data were collected and cross-checked with the classification results, positively confirming the general feasibility of the proposed vertical concept of integrated roughness mapping on various vertical levels. Results can provide valuable input for forest mapping and monitoring, in particular with regard to natural hazard modeling. Full article
(This article belongs to the Special Issue 100 Years ISPRS - Advancing Remote Sensing Science)
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Open AccessArticle Wildfire Detection and Tracking over Greece Using MSG‑SEVIRI Satellite Data
Remote Sens. 2011, 3(3), 524-538; doi:10.3390/rs3030524
Received: 7 January 2011 / Revised: 17 February 2011 / Accepted: 21 February 2011 / Published: 9 March 2011
Cited by 16 | PDF Full-text (674 KB) | HTML Full-text | XML Full-text
Abstract
Greece is a high risk Mediterranean country with respect to wildfires. This risk has been increasing under the impact of climate change, and in summer 2007 approximately 200,000 ha of vegetated land were burnt. The SEVIRI sensor, on board the Meteosat Second Generation
[...] Read more.
Greece is a high risk Mediterranean country with respect to wildfires. This risk has been increasing under the impact of climate change, and in summer 2007 approximately 200,000 ha of vegetated land were burnt. The SEVIRI sensor, on board the Meteosat Second Generation (MSG) geostationary satellite, is the only spaceborne sensor providing five and 15-minute observations of Europe in 12 spectral channels, including a short-wave infrared band sensitive to fire radiative temperature. In August 2007, when the bulk of the destructive wildfires started in Greece, the receiving station, operated by the Institute for Space Applications and Remote Sensing, provided us with a time series of MSG-SEVIRI images. These images were processed in order to test the reliability of a real‑time detection and tracking system and its complementarity to conventional means provided by the Fire Brigade. EUMETSAT’s Active Fire Monitoring (FIR) image processing algorithm for fire detection and monitoring was applied to SEVIRI data, then fine-tuned according to Greek conditions, and evaluated. Alarm announcements from the Fire Brigade’s archives were used as ground truthing data in order to assess detection reliability and system performance. During the examined period, MSG-SEVIRI data successfully detected 82% of the fire events in Greek territory with less than 1% false alarms. Full article
Open AccessArticle Temporal Stability of the Velodyne HDL-64E S2 Scanner for High Accuracy Scanning Applications
Remote Sens. 2011, 3(3), 539-553; doi:10.3390/rs3030539
Received: 10 February 2011 / Revised: 5 March 2011 / Accepted: 8 March 2011 / Published: 14 March 2011
Cited by 27 | PDF Full-text (670 KB) | HTML Full-text | XML Full-text
Abstract
The temporal stability and static calibration and analysis of the Velodyne HDL‑64E S2 scanning LiDAR system is discussed and analyzed. The mathematical model for measurements for the HDL-64E S2 scanner is updated to include misalignments between the angular encoder and scanner axis of
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The temporal stability and static calibration and analysis of the Velodyne HDL‑64E S2 scanning LiDAR system is discussed and analyzed. The mathematical model for measurements for the HDL-64E S2 scanner is updated to include misalignments between the angular encoder and scanner axis of rotation, which are found to be a marginally significant source of error. It is reported that the horizontal and vertical laser offsets cannot reliably be obtained with the current calibration model due to their high correlation with the horizontal and vertical offsets. By analyzing observations from two separate HDL-64E S2 scanners it was found that the temporal stability of the horizontal angle offset is near the quantization level of the encoder, but the vertical angular offset, distance offset and distance scale are slightly larger than expected. This is felt to be due to long term variations in the scanner range, whose root cause is as of yet unidentified. Nevertheless, a temporally averaged calibration dataset for each of the scanners resulted in a 25% improvement in the 3D planar misclosure residual RMSE over the standard factory calibration model. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
Open AccessArticle Camera-Variant Calibration and Sensor Modeling for Practical Photogrammetry in Archeological Sites
Remote Sens. 2011, 3(3), 554-569; doi:10.3390/rs3030554
Received: 13 January 2011 / Revised: 1 March 2011 / Accepted: 2 March 2011 / Published: 14 March 2011
Cited by 6 | PDF Full-text (736 KB) | HTML Full-text | XML Full-text
Abstract
With the appearance of low-cost and high-resolution consumer-grade digital cameras, a practical three-dimensional (3D) measurement system using a consumer-grade digital camera is greatly anticipated in various fields. In these circumstances, the authors have been concentrating on developing a practical 3D measurement system that
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With the appearance of low-cost and high-resolution consumer-grade digital cameras, a practical three-dimensional (3D) measurement system using a consumer-grade digital camera is greatly anticipated in various fields. In these circumstances, the authors have been concentrating on developing a practical 3D measurement system that includes photogrammetric software called the Image Based Integrated Measurement (IBIM) system. The IBIM system device consists of full/half-mirrors, a consumer-grade digital camera, and a laser distance meter. The most remarkable advantage of the system is its ability to calculate exterior orientation parameters, interior orientation parameters, and pseudo ground control points (GCPs) without using scale bars or the GCPs in the object field. The system has the ability to calibrate multiple cameras of different resolutions using a camera-variant parameter set. However, there remains one issue that needs to be resolved before this system can be effectively used, namely, improvement of the system which does not depend on the IBIM system device. With this motive, a practical photogrammetry method using a consumer-grade digital cameras and a hand-held laser distance meter is proposed. To test our proposed method, the bundle of distances from the center camera position to the feature points in the object field were measured individually at archaeological sites in Greece. In order to evaluate the possibility and practicability of the proposed photogrammetry method, this paper describes and evaluates the camera calibration techniques using images from multiple cameras of different resolutions and a bundle of distances. Full article
(This article belongs to the Special Issue Remote Sensing in Natural and Cultural Heritage)
Open AccessArticle Design and Development of a Multi-Purpose Low-Cost Hyperspectral Imaging System
Remote Sens. 2011, 3(3), 570-586; doi:10.3390/rs3030570
Received: 13 January 2011 / Revised: 19 February 2011 / Accepted: 28 February 2011 / Published: 15 March 2011
Cited by 2 | PDF Full-text (3369 KB) | HTML Full-text | XML Full-text
Abstract
Hyperspectral image analysis is gaining momentum in a wealth of natural resources and agricultural applications facilitated by the increased availability of low-cost imaging systems. In this study, we demonstrate the development of the Vegetation Mobile Mapping System (VMMS), a low-cost hyperspectral sensing system
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Hyperspectral image analysis is gaining momentum in a wealth of natural resources and agricultural applications facilitated by the increased availability of low-cost imaging systems. In this study, we demonstrate the development of the Vegetation Mobile Mapping System (VMMS), a low-cost hyperspectral sensing system that is supported by consumer-grade digital camera(s). The system was developed using off-the-shelf imaging and navigation components mainly for ground-based applications. The system integrates a variety of components including timing and positioning GPS receivers and an Inertial Measurement Unit (IMU). The system was designed to be modular and interoperable allowing the imaging components to be used with different navigation systems. The technique used for synchronizing captured images with GPS time was presented. A relative radiometric calibration technique utilizing images of homogeneous targets to normalize pixel gain and offset parameters was used. An empirical spectral calibration method was used to assign wavelengths to image bands. Data acquisition parameters to achieve appropriate spatial coverage were presented. The system was tested in ground-based data collection and analysis experiments that included water quality and vegetation studies. Full article
Open AccessArticle Mapping Topography Changes and Elevation Accuracies Using a Mobile Laser Scanner
Remote Sens. 2011, 3(3), 587-600; doi:10.3390/rs3030587
Received: 10 February 2011 / Revised: 7 March 2011 / Accepted: 8 March 2011 / Published: 17 March 2011
Cited by 36 | PDF Full-text (785 KB) | HTML Full-text | XML Full-text
Abstract
Laser measurements have been used in a fluvial context since 1984, but the change detection possibilities of mobile laser scanning (MLS) for riverine topography have been lacking. This paper demonstrates the capability of MLS in erosion change mapping on a test site located
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Laser measurements have been used in a fluvial context since 1984, but the change detection possibilities of mobile laser scanning (MLS) for riverine topography have been lacking. This paper demonstrates the capability of MLS in erosion change mapping on a test site located in a 58 km-long tributary of the River Tenojoki (Tana) in the sub-arctic. We used point bars and river banks as example cases, which were measured with the mobile laser scanner ROAMER mounted on a boat and on a cart. Static terrestrial laser scanner data were used as reference and we exploited a difference elevation model technique for describing erosion and deposition areas. The measurements were based on data acquisitions during the late summer in 2008 and 2009. The coefficient of determination (R2) of 0.93 and a standard deviation of error 3.4 cm were obtained as metrics for change mapping based on MLS. The root mean square error (RMSE) of MLS‑based digital elevation models (DEM) for non-vegetated point bars ranged between 2.3 and 7.6 cm after correction of the systematic error. For densely vegetated bank areas, the ground point determination was more difficult resulting in an RMSE between 15.7 and 28.4 cm. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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Open AccessArticle Virtual Interpretation of Earth Web-Interface Tool (VIEW-IT) for Collecting Land-Use/Land-Cover Reference Data
Remote Sens. 2011, 3(3), 601-620; doi:10.3390/rs3030601
Received: 20 January 2011 / Revised: 18 February 2011 / Accepted: 14 March 2011 / Published: 21 March 2011
Cited by 34 | PDF Full-text (1089 KB) | HTML Full-text | XML Full-text
Abstract
Web-based applications that integrate geospatial information, or the geoweb, offer exciting opportunities for remote sensing science. One such application is a Web‑based system for automating the collection of reference data for producing and verifying the accuracy of land-use/land-cover (LULC) maps derived from satellite
[...] Read more.
Web-based applications that integrate geospatial information, or the geoweb, offer exciting opportunities for remote sensing science. One such application is a Web‑based system for automating the collection of reference data for producing and verifying the accuracy of land-use/land-cover (LULC) maps derived from satellite imagery. Here we describe the capabilities and technical components of the Virtual Interpretation of Earth Web-Interface Tool (VIEW-IT), a collaborative browser-based tool for “crowdsourcing” interpretation of reference data from high resolution imagery. The principal component of VIEW-IT is the Google Earth plug-in, which allows users to visually estimate percent cover of seven basic LULC classes within a sample grid. The current system provides a 250 m square sample to match the resolution of MODIS satellite data, although other scales could be easily accommodated. Using VIEW-IT, a team of 23 student and 7 expert interpreters collected over 46,000 reference samples across Latin America and the Caribbean. Samples covered all biomes, avoided spatial autocorrelation, and spanned years 2000 to 2010. By embedding Google Earth within a Web-based application with an intuitive user interface, basic interpretation criteria, distributed Internet access, server-side storage, and automated error-checking, VIEW-IT provides a time and cost efficient means of collecting a large dataset of samples across space and time. When matched with predictor variables from satellite imagery, these data can provide robust mapping algorithm calibration and accuracy assessment. This development is particularly important for regional to global scale LULC mapping efforts, which have traditionally relied on sparse sampling of medium resolution imagery and products for reference data. Our ultimate goal is to make VIEW-IT available to all users to promote rigorous, global land-change monitoring. Full article
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Open AccessArticle Airborne Remote Sensing of a Biological Hot Spot in the Southeastern Bering Sea
Remote Sens. 2011, 3(3), 621-637; doi:10.3390/rs3030621
Received: 27 January 2011 / Revised: 7 March 2011 / Accepted: 14 March 2011 / Published: 21 March 2011
Cited by 7 | PDF Full-text (95 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Intense, ephemeral foraging events within localized hot spots represent important trophic transfers to top predators in marine ecosystems, though the spatial extent and temporal overlap of predators and prey are difficult to observe using traditional methods. The southeastern Bering Sea has high marine
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Intense, ephemeral foraging events within localized hot spots represent important trophic transfers to top predators in marine ecosystems, though the spatial extent and temporal overlap of predators and prey are difficult to observe using traditional methods. The southeastern Bering Sea has high marine productivity along the shelf break, especially near marine canyons. At a hot spot located near Bering Canyon, we observed three foraging events over a 12 day period in June 2005. These were located by aerial surveys, quantified by airborne lidar and visual counts, and characterized by ship-based acoustics and net catches. Because of the high density of seabirds, the events could be seen in images from space-based synthetic aperture radar. The events developed at the shelf slope, adjacent to passes between the Aleutian Islands, persisted for 1 to 8 days, then abruptly disappeared. Build-up and break down of the events occurred on 24 hr time scales, and diameters ranged from 10 to 20 km. These events comprised large concentrations of euphausiids, copepods, herring, other small pelagic fishes, humpback whales, Dall’s porpoise, short-tailed shearwaters, northern fulmars, and other pelagic seabirds. The lidar and acoustic remote sensing data demonstrated that prey densities inside the events were several times higher than those outside, indicating the importance of including events in forage fish surveys. This implies a need for either very intensive traditional surveys covering large expanses or for adaptive surveys guided by remote sensing. To our knowledge, this is the first time that an Alaskan hot spot was monitored with the combination of airborne and satellite remote sensing. Full article
(This article belongs to the Special Issue Remote Sensing in Coastal Ecosystem)
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Open AccessLetter A Comparison of Two Open Source LiDAR Surface Classification Algorithms
Remote Sens. 2011, 3(3), 638-649; doi:10.3390/rs3030638
Received: 20 January 2011 / Revised: 15 February 2011 / Accepted: 9 March 2011 / Published: 22 March 2011
Cited by 22 | PDF Full-text (371 KB) | HTML Full-text | XML Full-text
Abstract
With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a
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With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published results. Two of the latter are the multiscale curvature classification and the Boise Center Aerospace Laboratory LiDAR (BCAL) algorithms. This study investigated the accuracy of these two algorithms (and a combination of the two) to create a digital terrain model from a raw LiDAR point cloud in a semi-arid landscape. Accuracy of each algorithm was assessed via comparison with >7,000 high precision survey points stratified across six different cover types. The overall performance of both algorithms differed by only 2%; however, within specific cover types significant differences were observed in accuracy. The results highlight the accuracy of both algorithms across a variety of vegetation types, and ultimately suggest specific scenarios where one approach may outperform the other. Each algorithm produced similar results except in the ceanothus and conifer cover types where BCAL produced lower errors. Full article

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