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SUMMARYThe effectiveness of protected areas (PAs) has often been measured by comparing deforestation or land cover loss before and after PA establishment or within and outside the PA. Such evaluations ignore forest degradation or the decline in quality of the ecological values of the forest. Landsat image processing and geographical information systems were used to study forest cover changes in and around Popa Mountain Park (central Myanmar). Deforestation inside the Park was lower than outside the Park, but forest degradation, namely the net area that changed from dense forest to open forest, within the Park had grown at rates exceeding those outside the Park. The effectiveness of the PA was overestimated by adopting deforestation as the only indicator of conservation effectiveness. Forest degradation studies can be used to evaluate the effectiveness of PAs.

Information about forest biomass distribution is important for sustainable forest management and monitoring fuelwood supply. The objective of this study is to develop an accurate forest biomass map for Kampong Thom Province, Cambodia. We used a new technique (object-based approach) and a conventional technique (pixel-based approach) for the estimation of forest biomass using Landsat Enhanced Thematic Mapper Plus (ETM+). The object-based approach created segments of images, and calculated statistical and textural attributes. Our results showed that estimation accuracy of the object-based approach, with the use of band 1 and an exponential fit, was the best (R2 = 0.76), and this accuracy was comparable to that of the pixel-based approach (R2 = 0.67). Although several textural variables were related to forest biomass, they did not contribute significantly to improvement of estimation accuracy. However, the object-based method can be used for image segmentation so that the image objects are spectrally more homogeneous within individual regions than with their neighbors. Hence, they can be regarded as management units for policy-related spatial decisions. Therefore, it is possible to select either of the two methods depending upon what the situation demands.

The mountain zone of Yakushima Island is covered with a mixed conifer-broadleaved forest dominated by old-growth Cryptomeria japonica (L.f.) D. Don trees. Even though Yakushima Island has been frequently struck by typhoons with wind velocities exceeding 55 m s−1, the Cr. japonica trees in the mountain zone have survived for thousands of years without fatal damage. To evaluate the effect of storms on tree growth, the relationships between the stem diameter at breast height (DBH) and the heights of Cr. japonica and coexistent tree species were investigated. Two models based on an expanded allometric equation and a discontinuous piecewise allometric equation, respectively, to represent DBH–height relationships were evaluated. In all plots, the DBH–height relationship of Cr. japonica was discontinuous between small DBH and large DBH individuals. The tops of the large DBH individuals of Cr. japonica were lost to strong winds. However in each instance, they occupied the highest position in the canopy, even if they had lost their tops. In contrast, the DBH–height relationships of subcanopy broadleaved species were continuous in many plots and the equilibrium heights of the dominant broadleaved species were similar and almost in the same order regardless of the canopy heights of Cr. japonica. These results revealed a constant vertical structure in the Cr. japonica forest on Yakushima Island. Our results demonstrate a vertical niche segregation in the forest under high wind pressures and such vertical structure enables effective use of forest space and increases the basal area density.

The k-nearest neighbors (kNN) method is widely employed in national forest inventory applications using remote sensing data. The objective of this study was to evaluate the kNN method for stand volume estimation by combining LANDSAT/ETM+ data with 622 field sample plots from the Japanese National Forest Inventory (NFI) in Kyushu, Japan. The root mean square error (RMSE) and relative RMSE of the volume estimates rapidly decreased as the number of nearest neighbors (k) increased up to five, and then it slightly declined. They were consistently smaller for the Euclidean distance than for the Mahalanobis distance. The estimation errors (RMSE and relative RMSE) were 169.2 m3/ha and 66.2%, respectively (k = 10). The relative RMSE was similar to the previous studies. The estimated values were more accurate towards the mean value of the total volume, with an overestimation of the low volumes and an underestimation of the high volumes. We found a significant linear relationship between the observed stand volumes and estimated errors, which suggests that systematic errors may be reduced using this linearity. This research concluded that the kNN method is suitable for estimating stand volumes in Kyushu.

Our objective was to investigate the differences in the spectral trajectory of the LANDSAT Thematic Mapper with stand volume development between Japanese larch (Larix kaempferi) and Japanese oak (Quercus mongolica var. crispula) in the experimental forest of Kyushu University, Hokkaido, Japan. We used nonlinear regression and a categorical variable to investigate the relationship between spectral reflectance factor and stand volume for each forest type. This research showed that the reflectance factor of Japanese larch and Japanese oak reached saturation and that both forest types had different spectral trajectories with stand development. In addition, we found that middle of development stage (stand volume was between 100 and 200 m3/ha) of each forest type had similarity in reflectance factor.

To detect non-thinned stands using very-high-resolution imagery, we assessed the relationship between the texture statistics derived from the gray level co-occurrence matrix (GLCM) and the density of Cryptomeria japonica stands. Because it was difficult to make the condition, like stand age and slope, consistent using real images and stands, simulated images were used. The results showed that each texture statistic had a unique pattern of variation, owing to stand density. Moreover, the amount of thinning affected the texture statistics. Because the values of the texture statistics varied according to the amount of it even if the stand density was the same, it was indicated that it was difficult to predict stand density using the texture derived from GLCM. Nevertheless, it should be possible to extract stands that have not been thinned using the texture statistics from very-high-resolution imagery, especially the homogeneity and the angular second moment.

The objectives of this study are to: (1) evaluate accuracy of tree height measurements of manual stereo viewing on a computer display using digital aerial photographs compared with airborne LiDAR height measurements, and (2) develop an empirical model to estimate stand-level aboveground biomass with variables derived from manual stereo viewing on the computer display in a Cambodian tropical seasonal forest. We evaluate observation error of tree height measured from the manual stereo viewing, based on field measurements. RMSEs of tree height measurement with manual stereo viewing and LiDAR were 1.96 m and 1.72 m, respectively. Then, stand-level aboveground biomass is regressed against tree height indices derived from the manual stereo viewing. We determined the best model to estimate aboveground biomass in terms of the Akaike’s information criterion. This was a model of mean tree height of the tallest five trees in each plot (R2 = 0.78, RMSE = 58.18 Mg/ha). In conclusion, manual stereo viewing on the computer display can measure tree height accurately and is useful to estimate aboveground stand biomass.

Ecological communities including tropical rainforest are rapidly changing under various disturbances caused by increasing human activities. Recently in Cambodia, illegal logging and clear-felling for agriculture have been increasing. Here, we study the effects of logging, mortality and recruitment of plot trees on phylogenetic community structure in 32 plots in Kampong Thom, Cambodia. Each plot was 0.25 ha; 28 plots were established in primary evergreen forests and four were established in secondary dry deciduous forests. Measurements were made in 1998, 2000, 2004 and 2010, and logging, recruitment and mortality of each tree were recorded. We estimated phylogeny using rbcL and matK gene sequences and quantified phylogenetic α and β diversity. Within communities, logging decreased phylogenetic diversity, and increased overall phylogenetic clustering and terminal phylogenetic evenness. Between communities, logging increased phylogenetic similarity between evergreen and deciduous plots. On the other hand, recruitment had opposite effects both within and between communities. The observed patterns can be explained by environmental homogenization under logging. Logging is biased to particular species and larger diameter at breast height, and forest patrol has been effective in decreasing logging.