Mapping the height and above‐ground biomass of a mixed forest using lidar and stereo Ikonos images

Our objective was to assess the accuracy of the forest height and biomass estimates derived from an Ikonos stereo pair and a lidar digital terrain model (DTM). After the Ikonos scenes were registered to the DTM with submetric accuracy, tree heights were measured individually by subtracting the photogrammetric elevation of the treetop from the lidar ground‐level elevation of the tree base. The low residual error (1.66 m) of the measurements confirmed the joint geometric accuracy of the combined models. Matched images of the stereo pair were then used to create a digital surface model. The latter was transformed to a canopy height model (CHM) by subtracting the lidar DTM. Plotwise height percentiles were extracted from the Ikonos‐lidar CHM and used to predict the average dominant height and above‐ground biomass. The coefficient of determination reached 0.91 and 0.79 for average height and biomass, respectively. In both cases, the accuracy of the Ikonos‐lidar CHM predictions was slightly lower than that of the all‐lidar reference CHM. Although the CHM heights did not saturate at moderate biomass levels, as do multispectral or radar images, values above 300 Mg ha−1 could not be predicted accurately by the Ikonos‐lidar or by the all‐lidar CHM.

[1]  S. Brais,et al.  Keys for soil moisture regime evaluation for northwestern Quebec , 1992 .

[2]  Kevin Patrick,et al.  IKONOS geometric characterization , 2003 .

[3]  Brendan Mackey,et al.  Estimating forest biomass using satellite radar: an exploratory study in a temperate Australian Eucalyptus forest , 2003 .

[4]  D. Lu The potential and challenge of remote sensing‐based biomass estimation , 2006 .

[5]  T. Sarjakoski,et al.  Lehto, L. and T. Sarjakoski, 2004. Schema translations by XSLT for GML-encoded geospatial data in heterogeneous Web-service environment. Proceedings of the XXth ISPRS Congress, July 2004, Istanbul, Turkey, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, , 2007 .

[6]  João Roberto dos Santos,et al.  Savanna and tropical rainforest biomass estimation and spatialization using JERS-1 data , 2002 .

[7]  H. Balzter Forest mapping and monitoring with interferometric synthetic aperture radar (InSAR) , 2001 .

[8]  A. D. Cameron,et al.  The application of digital photogrammetry and image analysis techniques to derive tree and stand characteristics , 2005 .

[9]  Frank W. Gerlach,et al.  IKONOS satellite, imagery, and products , 2003 .

[10]  W. Kurz,et al.  Developing Canada's National Forest Carbon Monitoring, Accounting and Reporting System to Meet the Reporting Requirements of the Kyoto Protocol , 2006 .

[11]  R. Treuhaft,et al.  The calculated performance of forest structure and biomass estimates from interferometric radar , 2004 .

[12]  Matching of Ikonos stereo and multitemporal GEO Images for DSM Generation , 2002 .

[13]  Th. Toutin,et al.  DSM generation and evaluation from QuickBird stereo imagery with 3D physical modelling , 2004 .

[14]  K. Halbritter,et al.  Remote sensing for quantifying structural diversity in forests for forest biodiversity assessment. , 1999 .

[15]  Clive S. Fraser,et al.  Accuracy assessment of QuickBird stereo imagery , 2004 .

[16]  Cédric Véga,et al.  Measuring individual tree height using a combination of stereophotogrammetry and lidar , 2004 .

[17]  B. St-Onge,et al.  Combining Stereo-photogrammetry and Lidar to Map Forest Canopy Height , 2003 .

[18]  Cs Fraser,et al.  High-Precision Geopositioning from Ikonos Satellite Imagery , 2002 .

[19]  Thierry Toutin,et al.  Block bundle adjustment of Ikonos in-track images , 2003 .

[20]  Christopher P. Quine,et al.  An investigation of the potential of digital photogrammetry to provide measurements of forest characteristics and abiotic damage , 2000 .

[21]  S. Spurr Photogrammetry and Photo-Interpretation , 1960 .

[22]  F. Raulier,et al.  Canadian national tree aboveground biomass equations , 2005 .

[23]  W. W. Carson,et al.  A COMPARISON OF FOREST CANOPY MODELS DERIVED FROM LIDAR AND INSAR DATA IN A PACIFIC NORTHWEST CONIFER FOREST , 2003 .

[24]  T. Dawson,et al.  Quantifying forest above ground carbon content using LiDAR remote sensing , 2004 .

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

[26]  E. Baltsavias,et al.  POTENTIAL OF IKONOS AND QUICKBIRD IMAGERY FOR ACCURATE 3D POINT POSITIONING, ORTHOIMAGE AND DSM GENERATION , 2004 .

[27]  Lars T. Waser,et al.  Tree height measurements and tree growth estimation in a mire environment using digital surface models , 2006 .

[28]  Y. Hu,et al.  Mapping canopy height using a combination of digital stereo‐photogrammetry and lidar , 2008 .

[29]  Yong Hu Understanding the Rational Function Model : Methods and Applications , 2004 .

[30]  D. Lu Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon , 2005 .

[31]  K. Lim,et al.  Estimation of above ground forest biomass from airborne discrete return laser scanner data using canopy-based quantile estimators , 2004 .

[32]  Dean B. Gesch,et al.  CLICK: The new USGS Center for Lidar Information Coordination and Knowledge , 2006 .

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

[34]  K. Lim,et al.  Lidar remote sensing of biophysical properties of tolerant northern hardwood forests , 2003 .

[35]  Mikko Inkinen,et al.  A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners , 2001, IEEE Trans. Geosci. Remote. Sens..

[36]  M. Flood,et al.  LiDAR remote sensing of forest structure , 2003 .

[37]  Yanhong Tang,et al.  Overestimated Biomass Carbon Pools of the Northern mid- and High Latitude Forests , 2006 .

[38]  C. Fraser,et al.  Quality Assessment Of Digital Surface Models Generated From IKONOS Imagery , 2005 .