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Abstract:We investigated the capabilities of a canopy height model (CHM) derived from aerial photographs using the Structure from Motion (SfM) approach to estimate aboveground biomass (AGB) in a tropical forest. Aerial photographs and airborne Light Detection and Ranging (LiDAR) data were simultaneously acquired under leaf-on canopy conditions. A 3D point cloud was generated from aerial photographs using the SfM approach and converted to a digital surface model (DSMP). We also created a DSM from airborne LiDAR data (DSML). From each of DSMP and DSML, we constructed digital terrain models (DTM), which are DTMP and DTML, respectively. We created four CHMs, which were calculated from (1) DSMP and DTMP (CHMPP); (2) DSMP and DTML (CHMPL); (3) DSML and DTMP (CHMLP); and (4) DSML and DTML (CHMLL). Then, we estimated AGB using these CHMs. The model using CHMLL yielded the highest accuracy in four CHMs (R 2 = 0.94) and was comparable to the model using CHMPL (R 2 = 0.93). The model using CHMPP yielded the lowest accuracy (R 2 = 0.79). In conclusion, AGB can be estimated from CHM derived from aerial photographs using the SfM approach in the tropics. However, to accurately estimate AGB, we need a more accurate DTM than the DTM derived from aerial photographs using the SfM approach.

Daily transpiration before and after thinning was measured on six individual trees in a 31-year-old Chamaecyparis obtusa Endl. stand by the heat pulse method. After thinning, daily transpiration of a tree at a given level of solar radiation increased, and the difference between before and after thinning increased with solar radiation. The increase after thinning was related to a high rate of crown transpiration caused by greater canopy exposure and, subsequently, to the increase in foliage biomass per tree. Stand transpiration was calculated on the basis of two parameters, daily solar radiation and daily maximum vapor saturation deficit of the air. During the growing season (April to September), transpiration of a tree increased following thinning whereas transpiration of the stand decreased 21% after thinning. This decrease was associated with a 24% decrease in leaf mass of the stand following thinning.

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A simplified method for estimating CO 2 emissions from deforestation is the calculation of carbon stock change by monitoring forest land and periodically summing up the land area and its averaged carbon stock for important forest types. As a feasibility study for applying this methodology to a tropical dry-land forest, we estimated carbon stock and its chronosequential change in 4 carbon pools (aboveground and belowground biomass, deadwood, and litter) of tropical dry-land natural forests in Cambodia. Carbon stock differed among forest types. Most of the carbon stock (84 ± 12% (SD)) existed in tree biomass. Growth of carbon stock has a positive relationship to the carbon stock itself. By moderately classifying forest types, determining averaged tree biomass of each forest type, and using land-area data on each forest type, a reasonably accurate estimation of carbon stock can be expected. However, considering that rapidly progressing deforestation and wood extraction may reduce the carbon stock in forests, systematic sampling with a sufficient number of extra plots and frequent updating of forest land area and averaged carbon stock data are vital for an accurate estimation of CO 2 emissions from forests under pressure of land-use change and forestry activities.Discipline: Forestry and forest products Additional key words: biomass, deforestation, forest degradation, REDD, tropical forest This paper reports the results obtained in the collaborative research project on the "Joint implementation of carbon stock estimation by forest measurement to contribute to sustainable forest management in Cambodia"