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airborne laser scanning of natural forests in New Zealand reveals the influences of wind on forest carbon

Forest Ecosystems 2018年第2期5卷 126-139页

作者： David A. Coomes Daniel Safka James Shepherd Michele Dalponte Robert Holdaway Department of Plant Sciences University of Cambridge Downing Street CB2 3EA Cambridge UK Landcare Research Riddet Rd Massey University Palmerston North 4474 Palmerston North New Zealand Department of Sustainable Agro-Ecosystems and Bioresources Reserch and Innovation Centre Fondazione Edmund Math via E. Math 138010 San Michele all'Adige (TN) Italy Landcare Research 54 Gerald Street Lincoln 7608 Lincoln New Zealand.

Background： Forests are a key component of the global carbon cycle, and research is needed into the effects of human-driven and natural processes on their carbon pools. airborne laser scanning （ALS） produces detailed 3D maps of forest canopy structure from which aboveground carbon density can be estimated. Working with a ALS dataset collected over the 8049-km2 Wellington Region of New Zealand we create maps of indigenous forest carbon and evaluate the influence of wind by examining how carbon storage varies with aspect. Storms flowing from the west are a common cause of disturbance in this region, and we hypothesised that west-facing forests exposed to these winds would be shorter than those in sheltered east-facing sites. Methods： The aboveground carbon density of 31 forest inventory plots located within the ALS survey region were used to develop estimation models relating carbon density to ALS information. Power-law models using rasters of top-of-the-canopy height were compared with models using tree-level information extracted from the ALS dataset. A forest carbon map with spatial resolution of 25 m was generated from ALS maps of forest height and the estimation models. The map was used to evaluate the influences of wind on forests. Results： Power-law models were slightly less accurate than tree-centric models （RMSE 35% vs 32%） but were selected for map generation for computational efficiency. The carbon map comprised 4.5 million natural forest pixels within which canopy height had been measured by ALS, providing an unprecedented dataset with which to examine drivers of carbon density. Forests facing in the direction of westerly storms stored less carbon, as hypothesised. They had much greater above-ground carbon density for a given height than any of 14 tropical forests previously analysed by the same approach, and had exceptionally high basal areas for their height. We speculate that strong winds have kept forests short without impeding basal area growth. Concl

关键词： Forest LiDAR airborne laser scanning Remote sensing Carbon Climate change Cyclone Wind New Zealand LUCAS

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Using mixed integer programming and airborne laser scanning to generate forest management units

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Journal of Forestry Research 2022年第1期33卷 217-226页

作者： Adrián Pascual Sándor FTóth Forest Research Centre School of AgricultureUniversity of LisbonTapada da Ajuda1349-017 LisboaPortugal School of Forest Sciences University of Eastern FinlandP.O.Box 11180101 JoensuuFinland School of Environmental and Forest Sciences University of WashingtonSeattleWAUSA

airborne laser scanning(ALS)has been widely applied to estimate tree and forest attributes,but it can also drive the segmentation of forest *** algorithms are the dominant technique in segmentation but spatial optimization using exact methods remains *** study presents a novel approach to segmentation based on mixed integer programming to create forest management units(FMUs).This investigation focuses on using raster information derived from ALS *** mainstream clustering algorithms were compared to the new MIP formula that simultaneously accounts for area and adjacency restrictions,FMUs size and homogeneity in terms of vegetation *** optimal problem solution was found when using less than 150 cells,showing the problem formulation is *** results for MIP were better than for the clustering algorithms;FMUs were more compact based on the intravariation of canopy height and the variability in size was *** MIP model allows the user to strictly control the size of FMUs,which is not possible in heuristic optimization and in the clustering algorithms *** definition of forest management units based on remote sensing data is an important operation and our study pioneers the use of MIP ALS-based optimal segmentation.

关键词： Segmentation Precision forestry Optimization Mathematical programming airborne laser scanning

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Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data

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Frontiers of Earth Science 2017年第1期11卷 11-19页

作者： Menglong YAN Thomas BLASCHKE Hongzhao TANG Chenchao XIAO Xian SUN Daobing ZHANG Kun FU Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Z GIS - Centre for Geoinformatics and Department for Geography and Geology University of Salzburg Salzburg A-5020 Austria Satellite Mapping Application Center State Bureau of Surveying and Mapping Beijing 100048 China China Aero Geophysical Survey and Remote Sensing Center for Land and Resources Beijing 100083 China

airborne laser scanning （ALS） is a technique used to obtain Digital Surface Models （DSM） and Digital Terrain Models （DTM） efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of object- based analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation. We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing （ESRGG） algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.

关键词： airborne laser scanning object-based analysis surface complexity information filtering algorithm

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Mapping tree canopies in urban environments using airborne laser scanning (ALS):a Vancouver case study

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Forest Ecosystems 2018年第4期5卷 429-437页

作者： Giona Matasci Nicholas C.Coops David A.R.Williams Nick Page Department of Forest Resource Management Unlversity of British Columbia2424Main MallVancouverBC V6T IZ4Canada Vancouver Board of Parks and Recreation 2099Beach AvenueVancouverBC V6G IZ4Canada

Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water ***: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or ***: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open ***: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.

关键词： Urban forest Large trees Light detection and ranging airborne laser scanning

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Influence of sampling intensity on performance of two-phase forest inventory using airborne laser scanning

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Forest Ecosystems 2020年第4期7卷 871-886页

作者： Marek Lisańczuk Krzysztof Mitelsztedt Karolina Parkitna Grzegorz Krok Krzysztof Stereńczak Emilia Wysocka-Fijorek Stanisław Miścicki Department of Geomatics Forest Research InstituteSękocin StaryBraci Leśnej st.305-090 RaszynPoland. Department of Forest Management Planning Faculty of ForestryWarsaw University of Life Sciences(SGGW)Nowoursynowska st.15902-776 WarszawaPoland.

Background: Forest inventories have always been a primary information source concerning the forest ecosystem state. Various applied survey approaches arise from the numerous important factors during sampling scheme planning. Paramount aspects include the survey goal and scale, target population inherent variation and patterns,and available resources. The last factor commonly inhibits the goal, and compromises have to be made. airborne laser scanning(ALS) has been intensively tested as a cost-effective option for forest inventories. Despite existing foundations, research has provided disparate results. Environmental conditions are one of the factors greatly influencing inventory performance. Therefore, a need for site-related sampling optimization is well ***, as stands are the basic operational unit of managed forest holdings, few related studies have presented stand-level results. As such, herein, we tested the sampling intensity influence on the performance of the ALSenhanced stand-level ***: Distributions of possible errors were plotted by comparing ALS model estimates, with reference values derived from field surveys of 3300 sample plots and more than 300 control stands located in 5 forest districts. No improvement in results was observed due to the scanning density. The variance in obtained errors stabilized in the interval of 200–300 sample plots, maintaining the bias within +/-5% and the precision above 80%. The sample plot area affected scores mostly when transitioning from 100 to 200 m2. Only a slight gain was observed when bigger plots were ***: ALS-enhanced inventories effectively address the demand for comprehensive and detailed information on the structure of single stands over vast areas. Knowledge of the relation between the sampling intensity and accuracy of ALS estimates allows the determination of certain sampling intensity thresholds. This should be useful when matching the required sample size and accuracy

关键词： Forest inventory Sampling intensity airborne laser scanning Growing stock volume Regression

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Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data:a case study in the Sierra Nevada Mountains,California

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International Journal of Digital Earth 2018年第5期11卷 485-503页

作者： Qin Ma Yanjun Su Shengli Tao Qinghua Guo School of Engineering Sierra Nevada Research InstituteUniversity of California at MercedMercedCAUSA State Key Laboratory of Vegetation and Environmental Change Chinese Academy of SciencesInstitute of BotanyBeijingPeople’s Republic of China Department of Ecology College of Urban and Environmental Sciencesand Key Laboratory for Earth Surface Processes of the Ministry of EducationPeking UniversityBeijingPeople’s Republic of China

Improved monitoring and understanding of tree growth and its responses to controlling factors are important for tree growth *** laser scanning(ALS)can be used to enhance the efficiency and accuracy of large-scale forest surveys in delineating three-dimensional forest structures and under-canopy *** study proposed an ALSbased framework to quantify tree growth and ***-temporal ALS data were used to quantify tree growth in height(ΔH),crown area(ΔA),crown volume(ΔV),and tree competition for 114,000 individual trees in two conifer-dominant Sierra Nevada *** analyzed the correlations between tree growth attributes and controlling factors(*** sizes,competition,forest structure,and topographic parameters)at multiple *** the individual tree level,ΔH had no consistent correlations with controlling factors,ΔA andΔV were positively related to original tree sizes(R>0.3)and negatively related to competition indices(R0.7),ΔV was positively related to original tree sizes(|R|>0.8).Multivariate regression models were simulated at individual tree level forΔH,ΔA,andΔV with the R2 ranged from 0.1 to *** ALS-based tree height estimation and growth analysis results were consistent with field measurements.

关键词： airborne laser scanning change detection tree growth tree competition Sierra Nevada

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Building reconstruction from airborne laser scanning data

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Geo-Spatial Information Science 2013年第1期16卷 35-44页

作者： HUANG Xianfeng Future Cities Laboratory Department of ArchitectureETH ZurichZurich8092Switzerland

The research on building model reconstruction has been a long-term hot topic in both the photogrammetry and computer vision *** airborne laser scanning technique provides new opportunities for building model *** many investigations on building reconstruction using point clouds,there are still many unresolved problems that need further research,especially fully automatic methods and intelligent user-friendly *** article surveys the methods,tools and problems of building model reconstruction using point clouds *** article also points out some important but unnoticed problems in building reconstruction according to our previous *** hope our comments article can be helpful for researchers in understanding their position and for new researcher in acquiring general information.

关键词： building model reconstruction airborne laser scanning point clouds

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Automated tree detection and crown delineation using airborne laser scanner data in heterogeneous East-Central Europe forest with different species mix

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Journal of Forestry Research 2017年第5期28卷 1049-1059页

作者： Róbert Smreek Ivan Sakov Zuzana Michnová Ján Tuek Department of Forest Management and Geodesy Technical University in Zvolen Department of Forest Policy Economics and Forest ManagementNational Forest Centre-Forest Research Institute Zvolen

Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree positions. In this paper, we present a raster-based method for determining tree position and delineating crown coverage. We collected data from nine research plots that supported different mixes of species. We applied a raster-based method to raster layers with six different spatial resolutions and used terrestrial measurement data as reference data. Tree identification at a spatial resolution of 1.5 m was demonstrated to be the most accurate, with an average identification ratio (IR) of 95% and average detection ratio of 68% being observed. At a higher spatial resolution of 0.5 m, IR was overestimated by more than 600%. At a lower spatial resolution of 3 m, IR was underestimated at less than 44% of terrestrial measurements. The inventory process was timed to enable evaluation of the time efficiency of automatic methods.

关键词： airborne laser scanning East-Central Europe Individual tree Mixed forest Tree crown delineation

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Analysis of forest structural complexity using airborne LiDAR data and aerial photography in a mixed conifer–broadleaf forest in northern Japan

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Journal of Forestry Research 2018年第2期29卷 473-487页

作者： Sadeepa Jayathunga Toshiaki Owari Satoshi Tsuyuki Department of Global Agricultural Sciences Graduate School of Agricultural and Life SciencesThe University of Tokyo The University of Tokyo Hokkaido Forest Graduate School of Agricultural and Life SciencesThe University of Tokyo

Determining forest structural complexity,i.e.,a measure of the number of different attributes of a forest and the relative abundance of each attribute,is important for forest management and *** this study,we examined the structural complexity of mixed conifer–broadleaf forests by integrating multiple forest structural attributes derived from airborne Li DAR data and aerial *** sampled 76 plots from an unmanaged mixed conifer–broadleaf forest reserve in northern ***-level metrics were computed for all plots using both field and remote sensing data to assess their ability to capture the vertical and horizontal variations of forest structure.A multivariate set of forest structural attributes that included three Li DAR metrics(95 th percentile canopy height,canopy density and surface area ratio) and one image metric(proportion of broadleaf cover),was used to classify forest structure into structural complexity *** results revealed significant correlation between field and remote sensing metrics,indicating that these two sets of measurements captured similar patterns of structure in mixed conifer–broadleaf ***,cluster analysis identified six forest structural complexity classes includingtwo low-complexity classes and four high-complexity classes that were distributed in different elevation *** this study,we could reliably analyze the structural complexity of mixed conifer–broadleaf forests using a simple and easy to calculate set of forest structural attributes derived from airborne Li DAR data and high-resolution aerial *** study provides a good example of the use of airborne Li DAR data sets for wider purposes in forest ecology as well as in forest management.

关键词： airborne laser scanning High resolution imagery Hokkaido Forest structure Pan-mixed forests

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International Journal of Digital Earth 2018年第12期11卷 1205-1218页

作者： Ruben Valbuena Ana Hernando Jose Antonio Manzanera Eugenio Martínez-Falero Antonio García-Abril Blas Mola-Yudego Department of Plant Sciences Forest Ecology and ConservationUniversity of CambridgeCambridgeUK School of Forest Sciences University of Eastern FinlandJoensuuFinland College of Forestry and Natural Environment Research Group SILVANETUniversidad Politécnica de MadridCiudad UniversitariaMadridSpain

In the context of predicting forest attributes using a combination of airborne LIDAR and multispectral(MS)sensors,we suggest the inclusion of normalized difference vegetation index(NDVI)metrics along with the more traditional LIDAR height *** the data fusion method consists of back-projecting LIDAR returns onto original MS images,avoiding co-registration *** prediction method is based on nonparametric imputation(the most similar neighbor).Predictor selection and accuracy assessment include hypothesis tests and over-fitting prevention *** show improvements when using combinations of LIDAR and MS compared to using either of them *** MS sensor has little explanatory capacity for forest variables dependent on tree height,already well determined from LIDAR ***,there is potential for variables dependent on tree diameters and their *** combination of LIDAR and MS sensors can be very beneficial for predicting variables describing forests structural heterogeneity,which are best described from synergies between LIDAR heights and NDVI *** demonstrate the potential of NDVI metrics to increase prediction accuracy of forest *** inclusion in the predictor dataset may,however,in a few cases be detrimental to accuracy,and therefore we recommend to carefully assess the possible advantages of data fusion on a case-by-case basis.

关键词： airborne laser scanning forest attribute prediction multispectral imagery data fusion nearest neighbor

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