Endre Hofstad Hansen

Modeling Aboveground Biomass in Dense Tropical Submontane Rainforest Using Airborne Laser Scanner Data

Successful implementation of projects under the REDD+ mechanism, securing payment for storing forest carbon as an ecosystem service, requires quantification of biomass. Airborne laser scanning (ALS) is a relevant technology to enhance estimates of biomass in tropical forests. We present the analysis and results of modeling aboveground biomass (AGB) in a Tanzanian rainforest utilizing data from a small-footprint ALS system and 153 field plots with an area of 0.06–0.12 ha located on a systematic grid. The study area is dominated by steep terrain, a heterogeneous forest structure and large variation in AGB densities with values ranging from 43 to 1147 Mg·ha−1, which goes beyond the range that has been reported in existing literature on biomass modeling with ALS data in the tropics. Root mean square errors from a 10-fold cross-validation of estimated values were about 33% of a mean value of 462 Mg·ha−1. Texture variables derived from a canopy surface model did not result in improved models. Analyses showed that (1) variables derived from echoes in the lower parts of the canopy and (2) canopy density variables explained more of the AGB density than variables representing the height of the canopy.

Effects of pulse density on digital terrain models and canopy metrics using airborne laser scanning in a tropical rainforest

Airborne laser scanning (ALS) is increasingly being used to enhance the accuracy of biomass estimates in tropical forests. Although the technological development of ALS instruments has resulted in ever-greater pulse densities, studies in boreal and sub-boreal forests have shown consistent results even at relatively small pulse densities. The objective of the present study was to assess the effects of reduced pulse density on (1) the digital terrain model (DTM), and (2) canopy metrics derived from ALS data collected in a tropical rainforest in Tanzania. We used a total of 612 coordinates measured with a differential dual frequency Global Navigation Satellite System receiver to analyze the effects on DTMs at pulse densities of 8, 4, 2, 1, 0.5, and 0.025 pulses·m−2. Furthermore, canopy metrics derived for each pulse density and from four different field plot sizes (0.07, 0.14, 0.21, and 0.28 ha) were analyzed. Random variation in DTMs and canopy metrics increased with reduced pulse density. Similarly, increased plot size reduced variation in canopy metrics. A reliability ratio, quantifying replication effects in the canopy metrics, indicated that most of the common metrics assessed were reliable at pulse densities >0.5 pulses·m−2 at a plot size of 0.07 ha.

Relative efficiency of ALS and InSAR for biomass estimation in a Tanzanian rainforest

Forest inventories based on field sample surveys, supported by auxiliary remotely sensed data, have the potential to provide transparent and confident estimates of forest carbon stocks required in climate change mitigation schemes such as the REDD+ mechanism. The field plot size is of importance for the precision of carbon stock estimates, and better information of the relationship between plot size and precision can be useful in designing future inventories. Precision estimates of forest biomass estimates developed from 30 concentric field plots with sizes of 700, 900, …, 1900 m 2 , sampled in a Tanzanian rainforest, were assessed in a model-based inference framework. Remotely sensed data from airborne laser scanning (ALS) and interferometric synthetic aperture radio detection and ranging (InSAR) were used as auxiliary information. The findings indicate that larger field plots are relatively more efficient for inventories supported by remotely sensed ALS and InSAR data. A simulation showed that a pure field-based inventory would have to comprise 3.5-6.0 times as many observations for plot sizes of 700-1900 m 2 to achieve the same

Accurate single-tree positions from a harvester: a test of two global satellite-based positioning systems

ABSTRACT Accurate positioning of single trees registered automatically during harvesting operations opens up new possibilities for reducing the field sampling effort in forest inventories utilising remotely sensed data. In the present study, we propose to use a harvester to collect single-tree data during regular harvest operations and use these data to substitute or supplement traditional measurements on sample plots. Today’s harvesters are capable of recording single-tree information such as species and diameter at breast height, and a cut-to-length harvester was equipped with an integrated accurate positioning system based on real-time kinematic global satellite positioning, as well as a low-cost global navigation satellite system (GNSS) receiver mounted directly on the harvester head. Positions from 73 trees were evaluated and compared to coordinates obtained using a total station. At the single-tree level, the mean error for the integrated positioning system was 0.94 m. The low-cost GNSS receiver mounted on the harvester head yielded a mean error of 7.00 m. The sub-meter accuracy obtained with the integrated system suggests that data acquired with a harvester using this positioning system may have a great potential as a method for single-tree field data acquisition.

Predicting dynamic modulus of elasticity of Norway spruce structural timber by forest inventory, airborne laser scanning and harvester-derived data

ABSTRACT Norway spruce structural timber is one of the most important products of the Norwegian sawmilling industry, and a high grade-yield of structural timber is therefore important for the economic yield. Presorting of logs suited for production of structural timber might be one option to increase the grade yield. In this study, dynamic modulus of elasticity (Edyn) of structural timber was predicted based on forest inventory data at site level and single-tree data from airborne laser scanning (ALS) and harvester. The models were based on 611 boards from 4 sites in southeastern Norway. Important variables at site level were elevation, site index (SI), and mean stand age. However, when combining data from all information sources, mean stand age and site index were the only significant variables at site level. Tree height and variables describing the crown, like crown length and crown volume, were important vaiables extracted from ALS data. Stem diameter measures and tapering were important variables measured by the harvester. The combined model with variables from all three information sources reduced the variance the most, especially when using individual tree age instead of average stand age. However, combining all these data requires accurate positioning of the trees by the harvester.