From TLS to VLS: Biomass Estimation at Individual Tree Level

This study explores the applicability of vehicle-based laser scanning (VLS) for biomass estimation at individual tree level, since biomass serves as an essential biophysical parameter indicating tree health. Previous work suggests that terrestrial laser scanning (TLS) has been primarily validated for biomass prediction, however, in subject to laborious relocation in practice. VLS, as an advanced mode of TLS with more flexible mobility and also high sampling density, can work as a new efficient technique for surveying single trees. Combined with the positive binds between the biomass and TLS-samplings during manual defoliation, this work aims to seek the relations between biomass and VLS-samplings, by correlating the VLS- and TLS-samplings within the same crowns during natural foliation. The resulting R2 values of the two correlations after normalization are larger than 0.88 and 0.61, respectively, and the associated root mean square errors (RMSEs) are less than 0.051 and 0.076. VLS, thus, can be validated for estimating biomass at the individual tree level, with the TLS-investigated data as a bridging reference.

[1]  Christian Früh,et al.  Data Processing Algorithms for Generating Textured 3D Building Facade Meshes from Laser Scans and Camera Images , 2005, International Journal of Computer Vision.

[2]  Christian Früh,et al.  Data Processing Algorithms for Generating Textured 3D Building Facade Meshes from Laser Scans and Camera Images , 2002, Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission.

[3]  J. Hyyppä,et al.  Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions , 2004 .

[4]  Toshinori Kojima,et al.  Stand biomass estimation method by canopy coverage for application to remote sensing in an arid area of Western Australia , 2006 .

[5]  Harri Kaartinen,et al.  Remote Sensing Radiometric Calibration of Terrestrial Laser Scanners with External Reference Targets , 2022 .

[6]  Terje Gobakken,et al.  Improved estimates of forest vegetation structure and biomass with a LiDAR‐optimized sampling design , 2009 .

[7]  Sorin C. Popescu,et al.  Mapping surface fuel models using lidar and multispectral data fusion for fire behavior , 2008 .

[8]  G. Hunter,et al.  DEVELOPMENT OF A COMMERCIAL LASER SCANNING MOBILE MAPPING SYSTEM-STREETMAPPER , 2006 .

[9]  Emilio Chuvieco,et al.  Aboveground biomass assessment in Colombia: a remote sensing approach. , 2009 .

[10]  Randolph H. Wynne,et al.  Estimating plot-level tree heights with lidar : local filtering with a canopy-height based variable window size , 2002 .

[11]  S. Popescu Estimating biomass of individual pine trees using airborne lidar , 2007 .

[12]  Juha Hyyppä,et al.  Combination of low-pulse ALS data and TerraSar-X radar images in the estimation of plot-level forest variables , 2009 .

[13]  E. Næsset Practical large-scale forest stand inventory using a small-footprint airborne scanning laser , 2004 .

[14]  Juha Hyyppä,et al.  Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping , 2008, Sensors.

[15]  Peter Bunting,et al.  Retrieving forest biomass through integration of CASI and LiDAR data , 2008 .

[16]  W. Cohen,et al.  Lidar Remote Sensing for Ecosystem Studies , 2002 .

[17]  Andreas Koschan,et al.  3D reconstruction of road surfaces using an integrated multi-sensory approach , 2007 .

[18]  Erik Næsset,et al.  Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning , 2006 .

[19]  J. Hyyppä,et al.  DETECTING AND ESTIMATING ATTRIBUTES FOR SINGLE TREES USING LASER SCANNER , 2006 .

[20]  Y. Hu,et al.  Mapping the height and above‐ground biomass of a mixed forest using lidar and stereo Ikonos images , 2008 .

[21]  Wolfgang Lucht,et al.  Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D , 2005 .

[22]  E. Næsset Accuracy of forest inventory using airborne laser scanning: evaluating the first nordic full-scale operational project , 2004 .

[23]  Yi Lin,et al.  Three-level frame and RD-schematic algorithm for automatic detection of individual trees from MLS point clouds , 2012 .

[24]  C. Tao Mobile Mapping Technology for Road Network Data Acquisition , 2001 .

[25]  S. Popescu,et al.  Lidar remote sensing of forest biomass : A scale-invariant estimation approach using airborne lasers , 2009 .

[26]  J. Cihlar,et al.  Quantification of the regional carbon cycle of the biosphere: policy, science and land-use decisions. , 2007, Journal of environmental management.

[27]  Valerie Ussyshkin Mobile Laser Scanning Technology for Surveying Application: From Data Collection to End-Products , 2009 .

[28]  B. Marcotegui,et al.  FILTERING OF ARTIFACTS AND PAVEMENT SEGMENTATION FROM MOBILE LIDAR DATA , 2009 .

[29]  S. Goetz,et al.  Importance of biomass in the global carbon cycle , 2009 .

[30]  K. J. Wessels,et al.  Relationship between herbaceous biomass and 1‐km2 Advanced Very High Resolution Radiometer (AVHRR) NDVI in Kruger National Park, South Africa , 2006 .

[31]  Juha Hyyppä,et al.  Accuracy of High-Resolution Radar Images in the Estimation of Plot-Level Forest Variables , 2009, AGILE Conf..

[32]  Kenji Omasa,et al.  Voxel-Based 3-D Modeling of Individual Trees for Estimating Leaf Area Density Using High-Resolution Portable Scanning Lidar , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[33]  W. Mackaness,et al.  Lecture Notes in Geoinformation and Cartography , 2006 .

[34]  Ryosuke Shibasaki,et al.  A vehicle-borne urban 3-D acquisition system using single-row laser range scanners , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[35]  Philip J. Radtke,et al.  Laser point-quadrat sampling for estimating foliage-height profiles in broad-leaved forests , 2001 .

[36]  J. Townshend,et al.  Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm , 2003 .

[37]  E. Næsset Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .

[38]  K. Omasa,et al.  Mapping of tree position of Larix leptolepis woods and estimation of diameter at breast height (DBH) and biomass of the trees using range data measured by a portable scanning lidar , 2002 .

[39]  S. Reutebuch,et al.  Estimating forest canopy fuel parameters using LIDAR data , 2005 .

[40]  F. Goulette,et al.  An integrated on-board laser range sensing system for on-the-way city and road modelling , 2006 .

[41]  Thomas R. Crow,et al.  Estimating aboveground biomass using Landsat 7 ETM+ data across a managed landscape in northern Wisconsin, USA , 2004 .

[42]  N. Coops,et al.  Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests , 2003 .

[43]  C. Woodcock,et al.  Estimating forest LAI profiles and structural parameters using a ground-based laser called 'Echidna'. , 2008, Tree physiology.

[44]  P. Gong,et al.  Isolating individual trees in a savanna woodland using small footprint lidar data , 2006 .

[45]  Juha Hyyppä,et al.  ROAD ENVIRONMENT MAPPING SYSTEM OF THE FINNISH GEODETIC INSTITUTE - FGI ROAMER - , 2007 .

[46]  R. Houghton,et al.  Aboveground Forest Biomass and the Global Carbon Balance , 2005 .