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Remote Sens., Volume 3, Issue 7 (July 2011) – 13 articles , Pages 1284-1552

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790 KiB  
Article
Urban Heat Island Analysis Using the Landsat TM Data and ASTER Data: A Case Study in Hong Kong
by Lin Liu and Yuanzhi Zhang
Remote Sens. 2011, 3(7), 1535-1552; https://doi.org/10.3390/rs3071535 - 13 Jul 2011
Cited by 443 | Viewed by 29656
Abstract
In this paper, the effect of urban heat island is analyzed using the Landsat TM data and ASTER data in 2005 as a case study in Hong Kong. Two algorithms were applied to retrieve the land surface temperature (LST) distribution from the Landsat [...] Read more.
In this paper, the effect of urban heat island is analyzed using the Landsat TM data and ASTER data in 2005 as a case study in Hong Kong. Two algorithms were applied to retrieve the land surface temperature (LST) distribution from the Landsat TM and ASTER data. The spatial pattern of LST in the study area is retrieved to characterize their local effects on urban heat island. In addition, the correlation between LST and the normalized difference vegetation index (NDVI), the normalized difference build-up index (NDBI) is analyzed to explore the impacts of the green land and the build-up land on the urban heat island by calculating the ecological evaluation index of sub-urban areas. The results indicate that the effect of urban heat island in Hong Kong is mainly located in three sub-urban areas, namely, Kowloon Island, the northern Hong Kong Island and Hong Kong International Airport. The correlation between LST and NDVI, NDBI also indicates that the negative correlation of LST and NDVI suggests that the green land can weaken the effect on urban heat island, while the positive correlation between LST and NDBI means that the built-up land can strengthen the effect of urban heat island in our case study. Although satellite data (e.g., Landsat TM and ASTER thermal bands data) can be applied to examine the distribution of urban heat islands in places such as Hong Kong, the method still needs to be refined with in situ measurements of LST in future studies. Full article
(This article belongs to the Special Issue Urban Remote Sensing)
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1655 KiB  
Article
Shoreline Change along Sheltered Coastlines: Insights from the Neuse River Estuary, NC, USA
by Lisa Cowart, D. Reide Corbett and J.P. Walsh
Remote Sens. 2011, 3(7), 1516-1534; https://doi.org/10.3390/rs3071516 - 12 Jul 2011
Cited by 35 | Viewed by 9196
Abstract
Coastlines are constantly changing due to both natural and anthropogenic forces, and climate change and associated sea level rise will continue to reshape coasts in the future. Erosion is not only apparent along oceanfront areas; shoreline dynamics in sheltered water bodies have also [...] Read more.
Coastlines are constantly changing due to both natural and anthropogenic forces, and climate change and associated sea level rise will continue to reshape coasts in the future. Erosion is not only apparent along oceanfront areas; shoreline dynamics in sheltered water bodies have also gained greater attention. Additional estuarine shoreline studies are needed to better understand and protect coastal resources. This study uses a point-based approach to analyze estuarine shoreline change and associated parameters, including fetch, wave energy, elevation, and vegetation, in the Neuse River Estuary (NRE) at two contrasting scales, Regional (whole estuary) and Local (estuary partitioned into eight sections, based on orientation and exposure). With a mean shoreline-change rate of –0.58 m yr−1, the majority (93%) of the NRE study area is eroding. Change rates show some variability related to the land-use land-cover classification of the shoreline. Although linear regression analysis at the Regional Scale did not find significant correlations between shoreline change and the parameters analyzed, trends were determined from Local Scale data. Specifically, erosion rates, fetch, and wave exposure increase in the down-estuary direction, while elevation follows the opposite trend. Linear regression analysis between mean fetch and mean shoreline-change rates at the Local Scale provide a first-order approach to predict shoreline-change rates. The general trends found in the Local Scale data highlight the presence of underlying spatial patterns in shoreline-change rates within a complex estuarine system, but Regional Scale analysis suggests shoreline composition also has an important influence. Full article
(This article belongs to the Special Issue Remote Sensing in Coastal Ecosystem)
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885 KiB  
Article
Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering
by Jonathan S. Barton and Michael F. Jasinski
Remote Sens. 2011, 3(7), 1492-1515; https://doi.org/10.3390/rs3071492 - 11 Jul 2011
Cited by 12 | Viewed by 6851
Abstract
A method is presented for estimating subaqueous integrated backscatter using near-nadir viewing satellite lidar. The algorithm takes into account specular reflection of laser light, laser scattering by wind-generated foam as well as sun glint and solar scattering from foam. The formulation is insensitive [...] Read more.
A method is presented for estimating subaqueous integrated backscatter using near-nadir viewing satellite lidar. The algorithm takes into account specular reflection of laser light, laser scattering by wind-generated foam as well as sun glint and solar scattering from foam. The formulation is insensitive to the estimate of wind speed but sensitive to the estimate of transmittance used in the atmospheric correction. As a case study, CALIOP data over Tampa Bay were compared to MODIS 645 nm remote sensing reflectance, which previously has been shown to be nearly linearly related to turbidity. The results indicate good correlation on nearly all CALIOP cloud-free dates during the period 2006 through 2007, particularly those with relatively high atmospheric transmittance. The correlation decreases when data are composited over all dates but is still statistically significant, a possible indication of variability in the biogeochemical composition in the water. Overall, the favorable results show promise for the application of satellite lidar integrated backscatter in providing information about subsurface backscatter properties, which can be extracted using appropriate models. Full article
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1617 KiB  
Article
Evaluation of a LIDAR Land-Based Mobile Mapping System for Monitoring Sandy Coasts
by Maja Bitenc, Roderik Lindenbergh, Kourosh Khoshelham and A. Pieter Van Waarden
Remote Sens. 2011, 3(7), 1472-1491; https://doi.org/10.3390/rs3071472 - 08 Jul 2011
Cited by 55 | Viewed by 9746
Abstract
The Dutch coast is characterized by sandy beaches flanked by dunes. Understanding the morphology of the coast is essential for defense against flooding of the hinterland. Because most dramatic changes of the beach and the first dune row happen during storms, it is [...] Read more.
The Dutch coast is characterized by sandy beaches flanked by dunes. Understanding the morphology of the coast is essential for defense against flooding of the hinterland. Because most dramatic changes of the beach and the first dune row happen during storms, it is important to assess the state of the coast immediately after a storm. This is expensive and difficult to organize with Airborne Laser Scanning (ALS). Therefore, the performance of a Land-based Mobile Mapping System (LMMS) in mapping a stretch of sandy Dutch coast of 6 km near the municipality of Egmond is evaluated in this research. A test data set was obtained by provider Geomaat using the StreetMapper LMMS system. Both the relative quality of laser point heights and of a derived Digital Terrain model (DTM) are assessed. First, the height precision of laser points is assessed a priori by random error propagation, and a posteriori by calculating the height differences between close-by points. In the a priori case, the result is a theoretical laser point precision of around 5 cm. In the a posteriori approach it is shown that on a flat beach a relative precision of 3 mm is achieved, and that almost no internal biases exist. In the second analysis, a DTM with a grid size of 1 m is obtained using moving least squares. Each grid point height includes a quality description, which incorporates both measurement precision and terrain roughness. Although some problems remain with the scanning height of 2 m, which causes shadow-effect behind low dunes, it is concluded that a laser LMMS enables the acquisition of a high quality DTM product, which is available within two days. Full article
(This article belongs to the Special Issue 100 Years ISPRS - Advancing Remote Sensing Science)
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962 KiB  
Article
Remote Sensing-Based Characterization of Settlement Structures for Assessing Local Potential of District Heat
by Christian Geiß, Hannes Taubenböck, Michael Wurm, Thomas Esch, Michael Nast, Christoph Schillings and Thomas Blaschke
Remote Sens. 2011, 3(7), 1447-1471; https://doi.org/10.3390/rs3071447 - 08 Jul 2011
Cited by 43 | Viewed by 12572
Abstract
In Europe, heating of houses and commercial areas is one of the major contributors to greenhouse gas emissions. When considering the drastic impact of an increasing emission of greenhouse gases as well as the finiteness of fossil resources, the usage of efficient and [...] Read more.
In Europe, heating of houses and commercial areas is one of the major contributors to greenhouse gas emissions. When considering the drastic impact of an increasing emission of greenhouse gases as well as the finiteness of fossil resources, the usage of efficient and renewable energy generation technologies has to be increased. In this context, small-scale heating networks are an important technical component, which enable the efficient and sustainable usage of various heat generation technologies. This paper investigates how the potential of district heating for different settlement structures can be assessed. In particular, we analyze in which way remote sensing and GIS data can assist the planning of optimized heat allocation systems. In order to identify the best suited locations, a spatial model is defined to assess the potential for small district heating networks. Within the spatial model, the local heat demand and the economic costs of the necessary heat allocation infrastructure are compared. Therefore, a first and major step is the detailed characterization of the settlement structure by means of remote sensing data. The method is developed on the basis of a test area in the town of Oberhaching in the South of Germany. The results are validated through detailed in situ data sets and demonstrate that the model facilitates both the calculation of the required input parameters and an accurate assessment of the district heating potential. The described method can be transferred to other investigation areas with a larger spatial extent. The study underlines the range of applications for remote sensing-based analyses with respect to energy-related planning issues. Full article
(This article belongs to the Special Issue Urban Remote Sensing)
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1005 KiB  
Article
Evaluating the Remote Sensing and Inventory-Based Estimation of Biomass in the Western Carpathians
by Magdalena Main-Knorn, Gretchen G. Moisen, Sean P. Healey, William S. Keeton, Elizabeth A. Freeman and Patrick Hostert
Remote Sens. 2011, 3(7), 1427-1446; https://doi.org/10.3390/rs3071427 - 06 Jul 2011
Cited by 48 | Viewed by 8590
Abstract
Understanding the potential of forest ecosystems as global carbon sinks requires a thorough knowledge of forest carbon dynamics, including both sequestration and fluxes among multiple pools. The accurate quantification of biomass is important to better understand forest productivity and carbon cycling dynamics. Stand-based [...] Read more.
Understanding the potential of forest ecosystems as global carbon sinks requires a thorough knowledge of forest carbon dynamics, including both sequestration and fluxes among multiple pools. The accurate quantification of biomass is important to better understand forest productivity and carbon cycling dynamics. Stand-based inventories (SBIs) are widely used for quantifying forest characteristics and for estimating biomass, but information may quickly become outdated in dynamic forest environments. Satellite remote sensing may provide a supplement or substitute. We tested the accuracy of aboveground biomass estimates modeled from a combination of Landsat Thematic Mapper (TM) imagery and topographic data, as well as SBI-derived variables in a Picea abies forest in the Western Carpathian Mountains. We employed Random Forests for non-parametric, regression tree-based modeling. Results indicated a difference in the importance of SBI-based and remote sensing-based predictors when estimating aboveground biomass. The most accurate models for biomass prediction ranged from a correlation coefficient of 0.52 for the TM- and topography-based model, to 0.98 for the inventory-based model. While Landsat-based biomass estimates were measurably less accurate than those derived from SBI, adding tree height or stand-volume as a field-based predictor to TM and topography-based models increased performance to 0.36 and 0.86, respectively. Our results illustrate the potential of spectral data to reveal spatial details in stand structure and ecological complexity. Full article
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1009 KiB  
Article
Photorealistic Building Reconstruction from Mobile Laser Scanning Data
by Lingli Zhu, Juha Hyyppä, Antero Kukko, Harri Kaartinen and Ruizhi Chen
Remote Sens. 2011, 3(7), 1406-1426; https://doi.org/10.3390/rs3071406 - 06 Jul 2011
Cited by 55 | Viewed by 9538
Abstract
Nowadays, advanced real-time visualization for location-based applications, such as vehicle navigation or mobile phone navigation, requires large scale 3D reconstruction of street scenes. This paper presents methods for generating photorealistic 3D city models from raw mobile laser scanning data, which only contain georeferenced [...] Read more.
Nowadays, advanced real-time visualization for location-based applications, such as vehicle navigation or mobile phone navigation, requires large scale 3D reconstruction of street scenes. This paper presents methods for generating photorealistic 3D city models from raw mobile laser scanning data, which only contain georeferenced XYZ coordinates of points, to enable the use of photorealistic models in a mobile phone for personal navigation. The main focus is on the automated processing algorithms for noise point filtering, ground and building point classification, detection of planar surfaces, and on the key points (e.g., corners) of building derivation. The test site is located in the Tapiola area, Espoo, Finland. It is an area of commercial buildings, including shopping centers, banks, government agencies, bookstores, and high-rise residential buildings, with the tallest building being 45 m in height. Buildings were extracted by comparing the overlaps of X and Y coordinates of the point clouds between the cutoff-boxes at different and transforming the top-view of the point clouds of each overlap into a binary image and applying standard image processing technology to remove the non-building points, and finally transforming this image back into point clouds. The purpose for using points from cutoff-boxes instead of all points for building detection is to reduce the influence of tree points close to the building facades on building extraction. This method can also be extended to transform point clouds in different views into binary images for various other object extractions. In order to ensure the building geometry completeness, manual check and correction are needed after the key points of building derivation by automated algorithms. As our goal is to obtain photorealistic 3D models for walk-through views, terrestrial images were captured and used for texturing building facades. Currently, fully automatic generation of high quality 3D models is still challenging due to occlusions in both the laser and image data and due to significant illumination changes between the images. Especially when the scene contains both trees and vehicles, fully automated methods cannot achieve satisfactory visual appearance. In our approach, we employed the existing software for texture preparation and mapping. Full article
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1068 KiB  
Article
Geospatial Technologies to Improve Urban Energy Efficiency
by Geoffrey J. Hay, Christopher Kyle, Bharanidharan Hemachandran, Gang Chen, Mir Mustafizur Rahman, Tak S. Fung and Joseph L. Arvai
Remote Sens. 2011, 3(7), 1380-1405; https://doi.org/10.3390/rs3071380 - 05 Jul 2011
Cited by 38 | Viewed by 13800
Abstract
The HEAT (Home Energy Assessment Technologies) pilot project is a FREE Geoweb mapping service, designed to empower the urban energy efficiency movement by allowing residents to visualize the amount and location of waste heat leaving their homes and communities as easily as clicking [...] Read more.
The HEAT (Home Energy Assessment Technologies) pilot project is a FREE Geoweb mapping service, designed to empower the urban energy efficiency movement by allowing residents to visualize the amount and location of waste heat leaving their homes and communities as easily as clicking on their house in Google Maps. HEAT incorporates Geospatial solutions for residential waste heat monitoring using Geographic Object-Based Image Analysis (GEOBIA) and Canadian built Thermal Airborne Broadband Imager technology (TABI-320) to provide users with timely, in-depth, easy to use, location-specific waste-heat information; as well as opportunities to save their money and reduce their green-house-gas emissions. We first report on the HEAT Phase I pilot project which evaluates 368 residences in the Brentwood community of Calgary, Alberta, Canada, and describe the development and implementation of interactive waste heat maps, energy use models, a Hot Spot tool able to view the 6+ hottest locations on each home and a new HEAT Score for inter-city waste heat comparisons. We then describe current challenges, lessons learned and new solutions as we begin Phase II and scale from 368 to 300,000+ homes with the newly developed TABI-1800. Specifically, we introduce a new object-based mosaicing strategy, an adaptation of Emissivity Modulation to correct for emissivity differences, a new Thermal Urban Road Normalization (TURN) technique to correct for scene-wide microclimatic variation. We also describe a new Carbon Score and opportunities to update city cadastral errors with automatically defined thermal house objects. Full article
(This article belongs to the Special Issue Urban Remote Sensing)
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370 KiB  
Article
Transmittance of Airborne Laser Scanning Pulses for Boreal Forest Elevation Modeling
by Eero Ahokas, Juha Hyyppä, Xiaowei Yu and Markus Holopainen
Remote Sens. 2011, 3(7), 1365-1379; https://doi.org/10.3390/rs3071365 - 04 Jul 2011
Cited by 4 | Viewed by 6918
Abstract
The transmittance of laser pulses through the forest canopy was studied as a function of forest attributes (inventory parameters) and the scanning angle from the point of view of elevation modeling. Here transmittance is defined as the ratio of the number of pulses [...] Read more.
The transmittance of laser pulses through the forest canopy was studied as a function of forest attributes (inventory parameters) and the scanning angle from the point of view of elevation modeling. Here transmittance is defined as the ratio of the number of pulses within a threshold of the detected elevation model to the total number of transmitted pulses. Airborne laser scanning (ALS) using a Leica ALS50-II scanner took place on 25 July 2009 in the Evo test area in Southern Finland. The total number of circular field test plots with a radius of 10 meters was 246. Several of the test plots were observed from two different flight lines, and this resulted in 454 observations. Multiple regression analysis was applied to calculate statistical parameters for the scanning angle and the forest attributes. The canopy layer is an important factor that influences the number of ground hits. We found that the characteristics of the trees determine the number of transmitted pulses penetrating down to the ground level. When using scanning angles between 0 to 15 degrees in forested areas, the results showed that the scanning angle did not have a statistically significant effect on the vegetation penetration nor on the number of ground hits. It appears to be feasible to increase the scanning angle for boreal forest elevation modeling if some degree of local shadowing can be accepted in the data. By increasing the scanning angle, it is also possible to perform laser scanning and digital aerial photography simultaneously even over forested areas. Nationwide laser scanning in Finland and Sweden is carried out with scanning angles of ±20 degrees, but further studies are needed to assess the results when using even larger scanning angles. Full article
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663 KiB  
Article
Comparison of the Noise Robustness of FVC Retrieval Algorithms Based on Linear Mixture Models
by Kenta Obata and Hiroki Yoshioka
Remote Sens. 2011, 3(7), 1344-1364; https://doi.org/10.3390/rs3071344 - 04 Jul 2011
Cited by 4 | Viewed by 4958
Abstract
The fraction of vegetation cover (FVC) is often estimated by unmixing a linear mixture model (LMM) to assess the horizontal spread of vegetation within a pixel based on a remotely sensed reflectance spectrum. The LMM-based algorithm produces results that can vary to a [...] Read more.
The fraction of vegetation cover (FVC) is often estimated by unmixing a linear mixture model (LMM) to assess the horizontal spread of vegetation within a pixel based on a remotely sensed reflectance spectrum. The LMM-based algorithm produces results that can vary to a certain degree, depending on the model assumptions. For example, the robustness of the results depends on the presence of errors in the measured reflectance spectra. The objective of this study was to derive a factor that could be used to assess the robustness of LMM-based algorithms under a two-endmember assumption. The factor was derived from the analytical relationship between FVC values determined according to several previously described algorithms. The factor depended on the target spectra, endmember spectra, and choice of the spectral vegetation index. Numerical simulations were conducted to demonstrate the dependence and usefulness of the technique in terms of robustness against the measurement noise. Full article
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7462 KiB  
Article
Accuracy Enhancement of ASTER Global Digital Elevation Models Using ICESat Data
by Hossein Arefi and Peter Reinartz
Remote Sens. 2011, 3(7), 1323-1343; https://doi.org/10.3390/rs3071323 - 01 Jul 2011
Cited by 50 | Viewed by 8954
Abstract
Global Digital Elevation Models (GDEM) are considered very attractive for current research and application areas due to their free and wide range accessibility. The ASTER Global Digital Elevation Model exhibits the highest spatial resolution data of all global DEMs and it is generated [...] Read more.
Global Digital Elevation Models (GDEM) are considered very attractive for current research and application areas due to their free and wide range accessibility. The ASTER Global Digital Elevation Model exhibits the highest spatial resolution data of all global DEMs and it is generated for almost the whole globe. Unfortunately, ASTERGDEM data include many artifacts and height errors that decrease the quality and elevation accuracy significantly. This study provides a method for quality improvement of the ASTER GDEM data by correcting systematic height errors using ICESat laser altimetry data and removing artifacts and anomalies based on a segment-based outlier detection and elimination algorithm. Additionally, elevation errors within water bodies are corrected using a water mask produced from a high-resolution shoreline data set. Results indicate that the accuracy of the corrected ASTER GDEM is significantly improved and most artifacts are appropriately eliminated. Nevertheless, artifacts containing lower height values with respect to the neighboring ground pixels are not entirely eliminated due to confusion with some real non-terrain 3D objects. The proposed method is particularly useful for areas where other high quality DEMs such as SRTM are not available. Full article
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974 KiB  
Article
Towards Detecting Swath Events in TerraSAR-X Time Series to Establish NATURA 2000 Grassland Habitat Swath Management as Monitoring Parameter
by Christian Schuster, Iftikhar Ali, Peter Lohmann, Annett Frick, Michael Förster and Birgit Kleinschmit
Remote Sens. 2011, 3(7), 1308-1322; https://doi.org/10.3390/rs3071308 - 29 Jun 2011
Cited by 52 | Viewed by 9331 | Correction
Abstract
Spatial monitoring tools are necessary to respond to the threat of global biodiversity loss. At the European scale, remote sensing tools for NATURA 2000 habitat monitoring have been requested by the European Commission to fulfill the obligations of the EU Habitats Directive. This [...] Read more.
Spatial monitoring tools are necessary to respond to the threat of global biodiversity loss. At the European scale, remote sensing tools for NATURA 2000 habitat monitoring have been requested by the European Commission to fulfill the obligations of the EU Habitats Directive. This paper introduces a method by which swath events in semi-natural grasslands can be detected from multi-temporal TerraSAR-X data. The investigated study sites represent rare and endangered habitats (NATURA 2000 codes 6410, 6510), located in the Döberitzer Heide nature conservation area west of Berlin. We analyzed a time series of 11 stripmap images (HH-polarization) covering the vegetation period affected by swath (June to September 2010) at a constant 11-day acquisition rate. A swath detection rule was established to extract the swath events for the NATURA 2000 habitats as well as for six contrasting pasture sites not affected by swath. All swath events observed in the field were correctly allocated. The results indicate the potential to allocate semi-natural grassland swath events to 11-day-periods using TerraSAR-X time series. Since the conservation of semi-natural grassland habitats requires compliance with specific swath management rules, the detection of swath events may thus provide new parameters for the monitoring of NATURA 2000 grassland habitats. Full article
(This article belongs to the Special Issue Remote Sensing in Support of Environmental Policy)
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2170 KiB  
Article
Portable and Airborne Small Footprint LiDAR: Forest Canopy Structure Estimation of Fire Managed Plots
by Claudia M.C.S. Listopad, Jason B. Drake, Ron. E. Masters and John F. Weishampel
Remote Sens. 2011, 3(7), 1284-1307; https://doi.org/10.3390/rs3071284 - 27 Jun 2011
Cited by 19 | Viewed by 8719
Abstract
This study used an affordable ground-based portable LiDAR system to provide an understanding of the structural differences between old-growth and secondary-growth Southeastern pine. It provided insight into the strengths and weaknesses in the structural determination of portable systems in contrast to airborne LiDAR [...] Read more.
This study used an affordable ground-based portable LiDAR system to provide an understanding of the structural differences between old-growth and secondary-growth Southeastern pine. It provided insight into the strengths and weaknesses in the structural determination of portable systems in contrast to airborne LiDAR systems. Portable LiDAR height profiles and derived metrics and indices (e.g., canopy cover, canopy height) were compared among plots with different fire frequency and fire season treatments within secondary forest and old growth plots. The treatments consisted of transitional season fire with four different return intervals: 1-yr, 2-yr, 3-yr fire return intervals, and fire suppressed plots. The remaining secondary plots were treated using a 2-yr late dormant season fire cycle. The old growth plots were treated using a 2-yr growing season fire cycle. Airborne and portable LiDAR derived canopy cover were consistent throughout the plots, with significantly higher canopy cover values found in 3-yr and fire suppressed plots. Portable LiDAR height profile and metrics presented a higher sensitivity in capturing subcanopy elements than the airborne system, particularly in dense canopy plots. The 3-dimensional structures of the secondary plots with varying fire return intervals were dramatically different to old-growth plots, where a symmetrical distribution with clear recruitment was visible. Portable LiDAR, even though limited to finer spatial scales and specific biases, is a low-cost investment with clear value for the management of forest canopy structure. Full article
(This article belongs to the Special Issue Terrestrial Laser Scanning)
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