Laser Scanning and Aerial Photography with UAV in Studying the Structure of Forest-Tundra Stands in the Khibiny Mountains

Studying the structure of stands is a key point in assessing the role of trees in carbon deposition. Information on the spatial structure of ground vegetation at the upper treeline is still insufficiently presented in modern studies. High resolution remote sensing can provide important data to understand the properties and dynamics of vegetation in these conditions. We test the applicability of ground-based mobile laser scanning of the terrain and aerial photography for the rapid and high-precision assessment of the characteristics of tree stands in the forest-tundra ecotone. We obtained canopy height models (CHMs) of the forest and supplemented them with aerial photographs of the research area on the southeastern slope of the Khibiny Mountains. Using CHMs we have delineated boundaries of tree crowns. The height and projection area were determined for each tree. The first characteristic obtained by laser scanning was compared to the heights of the same trees estimated by field measurements. This was done for the purposes of verification. The comparison revealed that laser scanning data allow to set heights closest to field measurements in case the heights are determined by the maximum values of brightness of pixels of CHMs with manual correction of values when outliers are detected (R2 = 0.84). Since manual correction of outliers is time-consuming, we proposed a way to automate the measurements by determining tree heights using the sum of the average value of pixel brightness and the standard deviation multiplied by 2.5 (R2 = = 0.79). We compared the area characteristics of the stands obtained by laser scanning and the unmanned aerial vehicle (UAV) photography. Thus, we obtained detailed information on the spatial location and size of 4424 trees in an area of about 10 ha and compared the results of measuring tree characteristics obtained by different methods. It was also found that with increasing height from 290 to 425 m above sea level on the studied slope, the average height of stands decreases gradually from 4.5–5.0 to 1.1–1.6 m with small fluctuations (0.2–0.4 m), while the density of stands changes from 4620–5860 to 145 m2/ha in a non-linear way.

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Assessing tree crown volume—a review

Forestry An International Journal of Forest Research ◽

10.1093/forestry/cpaa037 ◽

2020 ◽

Author(s):

Zihui Zhu ◽

Christoph Kleinn ◽

Nils Nölke

Keyword(s):

Laser Scanning ◽

Forest Biomass ◽

Field Measurements ◽

Data Sources ◽

Aerial Photographs ◽

Pollution Reduction ◽

Tree Crown ◽

Crown Volume ◽

Geometric Solids ◽

Environmental Functions

Abstract Tree crown volume is a fundamental tree characteristic. It correlates to forest biomass production and most relevant ecosystem and environmental functions, such as carbon sequestration and air pollution reduction. When researching these relationships, it is necessary to clearly define and then quantify tree crown variables in a both accurate and operational manner. In this paper, we review the reported literature on the assessment of tree crown volume. First, we compile the varying definitions of crown volume and other tree crown variables that may be used as inputs to quantify crown volume. Then, we examine the data sources for quantifying these variables, including field measurements, terrestrial photographs, aerial photographs and laser scanning. Furthermore, we compare the published approaches on translating these crown variable measurements into tree crown volume. These approaches include the approximation of simple geometric solids, approaches of computational geometry and voxelization. We also compare the reported accuracies and major challenges of these approaches. From this literature review, the reader may craft a suitable approach for the assessment of crown volume.

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Assessing woody vegetation cover change in north-west Australian savanna using aerial photography

International Journal of Wildland Fire ◽

10.1071/wf03022 ◽

2003 ◽

Vol 12 (4) ◽

pp. 359 ◽

Cited By ~ 45

Author(s):

R. J. Fensham ◽

R. J. Fairfax

Keyword(s):

Structural Change ◽

Aerial Photography ◽

Vegetation Cover ◽

Grazing Intensity ◽

Field Measurements ◽

Aerial Photographs ◽

Woody Vegetation ◽

North West ◽

Land Type ◽

Calibration Models

Models to calibrate tree and shrub cover assessed from aerial photography with field measurements were developed for a range of vegetation types in north-western Australia. The models verify previous studies indicating that woody cover can be successfully determined from aerial photography. The calibration models were applied to estimates of woody vegetation cover determined for 279 randomly located sample areas in the Ord–Victoria Rivers region using aerial photography from 1948 to 1950 and 1988 to 1997. Overstorey cover increased from a regional average of 11.5% to 13.5% and understorey cover increased from 1.3% to 2.0%. Downs, Limestone Hills and Alluvia land-types showed the most substantial increases in overstorey cover while overstorey cover in the Limestone plains land-type decreased. Relatively open structured vegetation is most susceptible to thickening. Rainfall records reveal an extreme multi-year rainfall deficit in the study area in the 1930s and relatively wet times in the 1970s and 1980s. Interpretation of a limited set of aerial photographs taken between 1964 and 1972 suggests that most of the increases in cover have occurred since this time. The study highlights the possibility that the average trend of vegetation thickening represents recovery during the relatively wet times after the 1970s. There was no relationship between structural change and a grazing intensity surrogate (distance of sample points to stock watering-points). However, the causes of structural change are undoubtedly multi-factored and the relative contributions of climate, fire and grazing vary for different landscapes and tree species.

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Corrigendum to: Assessing woody vegetation cover change in north-west Australian savanna using aerial photography

International Journal of Wildland Fire ◽

10.1071/wf03022_co ◽

2004 ◽

Vol 13 (1) ◽

pp. 131

Author(s):

R. J. Fairfax ◽

R. J. Fensham

Keyword(s):

Structural Change ◽

Aerial Photography ◽

Vegetation Cover ◽

Grazing Intensity ◽

Field Measurements ◽

Aerial Photographs ◽

Woody Vegetation ◽

North West ◽

Land Type ◽

Calibration Models

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Dynamics of a savanna-forest mosaic in the Australian monsoon tropics inferred from stand structures and historical aerial photography

Australian Journal of Botany ◽

10.1071/bt04141 ◽

2005 ◽

Vol 53 (3) ◽

pp. 185 ◽

Cited By ~ 25

Author(s):

Daniel S. Banfai ◽

David M. J. S. Bowman

Keyword(s):

Aerial Photography ◽

Activity Index ◽

Field Measurements ◽

Aerial Photographs ◽

Annual Rainfall ◽

Australian Monsoon ◽

Closed Forest ◽

Fire Activity ◽

Forest Mosaic ◽

Ground Truthing

Stratified ground-truthing was undertaken within an area of approximately 30 km2 of tropical savanna across an abrupt sandstone escarpment in the monsoon tropics of Australia. Comparison of aerial photographs from 1941 and 1994 had previously revealed a landscape-wide expansion of closed forest and contraction of grassland patches. Good congruence between field measurements and the vegetation classifications from the 1994 aerial photography supported the authenticity of the vegetation changes. The relative abundance of rainforest and non-rainforest tree species also concurred with mapped vegetation transitions. Changes in individual size classes of rainforest species, which are relatively fire sensitive, were consistent with the primacy of fire in controlling the distribution of the closed-forest formation. Fire scars previously mapped from satellite imagery were used to derive a fire activity index for contrasting vegetation transitions. Savannas that had converted to closed forest had lower fire activity than did stable savannas. Conversely, closed forests that converted to savanna had the highest fire activity index. The landscape-wide expansion of rainforest is associated with the cessation of Aboriginal fire management, possibly in conjunction with elevated CO2 and increasing annual rainfall.

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DTM-based analysis of the spatial distribution of topolineaments

Open Geosciences ◽

10.1515/geo-2020-0059 ◽

2020 ◽

Vol 12 (1) ◽

pp. 1185-1199

Author(s):

Mirosław Kamiński

Keyword(s):

Laser Scanning ◽

Digital Terrain Model ◽

Research Area ◽

Tectonic Structures ◽

Empirical Bayesian ◽

Scanning Method ◽

Empirical Bayesian Kriging ◽

Terrain Model ◽

Digital Terrain ◽

Airborne Laser

AbstractThe research area is located on the boundary between two Paleozoic structural units: the Radom–Kraśnik Block and the Mazovian–Lublin Basin in the southeastern Poland. The tectonic structures are separated by the Ursynów–Kazimierz Dolny fault zone. The digital terrain model obtained by the ALS (Airborne Laser Scanning) method was used. Classification and filtration of an elevation point cloud were performed. Then, from the elevation points representing only surfaces, a digital terrain model was generated. The model was used to visually interpret the course of topolineaments and their automatic extraction from DTM. Two topolineament systems, trending NE–SW and NW–SE, were interpreted. Using the kernel density algorithm, topolineament density models were generated. Using the Empirical Bayesian Kriging, a thickness model of quaternary deposits was generated. A relationship was observed between the course of topolineaments and the distribution and thickness of Quaternary formations. The topolineaments were compared with fault directions marked on tectonic maps of the Paleozoic and Mesozoic. Data validation showed consistency between topolineaments and tectonic faults. The obtained results are encouraging for further research.

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Regional Modeling of Forest Fuels and Structural Attributes Using Airborne Laser Scanning Data in Oregon

Remote Sensing ◽

10.3390/rs13020261 ◽

2021 ◽

Vol 13 (2) ◽

pp. 261

Author(s):

Francisco Mauro ◽

Andrew T. Hudak ◽

Patrick A. Fekety ◽

Bryce Frank ◽

Hailemariam Temesgen ◽

...

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Field Measurements ◽

Point Clouds ◽

Semiparametric Models ◽

Airborne Laser Scanning ◽

Parametric Models ◽

Fuel Load ◽

Forest Fuels ◽

Airborne Laser

Airborne laser scanning (ALS) acquisitions provide piecemeal coverage across the western US, as collections are organized by local managers of individual project areas. In this study, we analyze different factors that can contribute to developing a regional strategy to use information from completed ALS data acquisitions and develop maps of multiple forest attributes in new ALS project areas in a rapid manner. This study is located in Oregon, USA, and analyzes six forest structural attributes for differences between: (1) synthetic (i.e., not-calibrated), and calibrated predictions, (2) parametric linear and semiparametric models, and (3) models developed with predictors computed for point clouds enclosed in the areas where field measurements were taken, i.e., “point-cloud predictors”, and models developed using predictors extracted from pre-rasterized layers, i.e., “rasterized predictors”. Forest structural attributes under consideration are aboveground biomass, downed woody biomass, canopy bulk density, canopy height, canopy base height, and canopy fuel load. Results from our study indicate that semiparametric models perform better than parametric models if no calibration is performed. However, the effect of the calibration is substantial in reducing the bias of parametric models but minimal for the semiparametric models and, once calibrations are performed, differences between parametric and semiparametric models become negligible for all responses. In addition, minimal differences between models using point-cloud predictors and models using rasterized predictors were found. We conclude that the approach that applies semiparametric models and rasterized predictors, which represents the easiest workflow and leads to the most rapid results, is justified with little loss in accuracy or precision even if no calibration is performed.

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Nonlinear absorption and scattering of a single plasmonic nanostructure characterized by x-scan technique

Beilstein Journal of Nanotechnology ◽

10.3762/bjnano.10.211 ◽

2019 ◽

Vol 10 ◽

pp. 2182-2191 ◽

Cited By ~ 1

Author(s):

Tushar C Jagadale ◽

Dhanya S Murali ◽

Shi-Wei Chu

Keyword(s):

Laser Scanning ◽

Detection System ◽

Nonlinear Behavior ◽

Optical Nonlinearity ◽

Research Area ◽

Confocal Laser Scanning Microscope ◽

Confocal Laser ◽

Thin Sample ◽

Channel Detection ◽

Novel Method

Nonlinear nanoplasmonics is a largely unexplored research area that paves the way for many exciting applications, such as nanolasers, nanoantennas, and nanomodulators. In the field of nonlinear nanoplasmonics, it is highly desirable to characterize the nonlinearity of the optical absorption and scattering of single nanostructures. Currently, the common method to quantify optical nonlinearity is the z-scan technique, which yields real and imaginary parts of the permittivity by moving a thin sample with a laser beam. However, z-scan typically works with thin films, and thus acquires nonlinear responses from ensembles of nanostructures, not from single ones. In this work, we present an x-scan technique that is based on a confocal laser scanning microscope equipped with forward and backward detectors. The two-channel detection offers the simultaneous quantification for the nonlinear behavior of scattering, absorption and total attenuation by a single nanostructure. At low excitation intensities, both scattering and absorption responses are linear, thus confirming the linearity of the detection system. At high excitation intensities, we found that the nonlinear response can be derived directly from the point spread function of the x-scan images. Exceptionally large nonlinearities of both scattering and absorption are unraveled simultaneously for the first time. The present study not only provides a novel method for characterizing nonlinearity of a single nanostructure, but also reports surprisingly large plasmonic nonlinearities.

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Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning

Forests ◽

10.3390/f9050237 ◽

2018 ◽

Vol 9 (5) ◽

pp. 237 ◽

Cited By ~ 5

Author(s):

Tim Ritter ◽

Arne Nothdurft

Keyword(s):

Laser Scanning ◽

Three Dimensional ◽

Terrestrial Laser Scanning ◽

Point Clouds ◽

Projection Area ◽

Automatic Assessment ◽

Crown Projection Area

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Inoptimality losses in forest management decisions caused by errors in an inventory based on airborne laser scanning and aerial photographs

Canadian Journal of Forest Research ◽

10.1139/x10-185 ◽

2010 ◽

Vol 40 (12) ◽

pp. 2427-2438 ◽

Cited By ~ 7

Author(s):

Md. Nurul Islam ◽

Mikko Kurttila ◽

Lauri Mehtätalo ◽

Timo Pukkala

Keyword(s):

Input Data ◽

Laser Scanning ◽

Basal Area ◽

Airborne Laser Scanning ◽

Aerial Photographs ◽

Stand Age ◽

Inventory Data ◽

Airborne Laser ◽

Mean Diameter ◽

The Mean

Errors in inventory data may lead to inoptimal decisions that ultimately result in financial losses for forest owners. We estimated the expected monetary losses resulting from data errors that are similar to errors in laser-based forest inventory. The mean loss was estimated for 67 stands by simulating 100 realizations of inventory data for each stand with errors that mimic those in airborne laser scanning (ALS) based inventory. These realizations were used as input data in stand management optimization, which maximized the present value of all future net incomes (NPV). The inoptimality loss was calculated as the difference between the NPV of the optimal solution and the true NPV of the solution obtained with erroneous input data. The results showed that the mean loss exceeded €300·ha–1 (US$425·ha–1) in 84% of the stands. On average, the losses increased with decreasing stand age and mean diameter. Furthermore, increasing errors in the basal area weighted mean diameter and basal area of spruce were found to significantly increase the loss. It has been discussed that improvements in the accuracy of ALS-based inventory could be financially justified.

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Geomorphological mapping based on DEMs and GIS: A review

Abstracts of the ICA ◽

10.5194/ica-abs-1-275-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-1

Author(s):

Takashi Oguchi

Keyword(s):

Remote Sensing ◽

Laser Scanning ◽

Aerial Photographs ◽

Topographic Maps ◽

Formation Processes ◽

Geomorphological Mapping ◽

Topographic Data ◽

Aerial Photogrammetry ◽

Landform Classification ◽

Shape Characteristics

Abstract. Geomorphology is a scientific discipline dealing with the characteristics, origin, and evolution of landforms. It utilizes topographic data such as spot height information, contour lines on topographic maps, and DEMs (Digital Elevation Models). Topographic data were traditionally obtained by ground surveying, but introduction of aerial photogrammetry in the early 20th century enabled more efficient data acquisition based on remote sensing. In recent years, active remote sensing methods including airborne and terrestrial laser scanning and applications of satellite radar have also been employed, and aerial photogrammetry has become easier and popular thanks to drones and a new photogrammetric method, SfM (Structure from Motion). The resultant topographic data especially raster DEMs are combined with GIS (Geographic Information Systems) to obtain derivatives such as slope and aspect as well as to conduct efficient geomorphological mapping. Resultant maps can depict various topographic characteristics based on surface height and DEM derivatives, and applications of advanced algorithms and some heuristic reasoning permit semi-automated landform classification. This quantitative approach differs from traditional and more qualitative methods to produce landform classification maps using visual interpretation of analogue aerial photographs and topographic maps as well as field observations.For scientific purposes, landforms need to be classified based on not only shape characteristics but also formation processes and ages. Among them, DEMs only represent shape characteristics, and understanding formation processes and ages usually require other data such as properties of surficial deposits observed in the field. However, numerous geomorphological studies indicate relationships between shapes and forming-processes of landforms, and even ages of landforms affect shapes such as a wider distribution of dissected elements within older landforms. Recent introduction of artificial intelligence in geomorphology including machine learning and deep learning may permit us to better understand the relationships of shapes with processes and ages. Establishing such relationships, however, is still highly challenging, and at this moment most geomorphologists think landform classification maps based on the traditional methods are more usable than those from the DEM-based methods. Nevertheless, researchers of some other fields such as civil engineering more appreciate the DEM-based methods because they can be conducted without deep geomorphological knowledge. Therefore, the methods should be developed for interdisciplinary understanding. This paper reviews and discusses such complex situations of geomorphological mapping today in relation to historical development of methodology.

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