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To reconstruct the history of forest loss in Cambodia, the literature and national/provincial statistics of landuse patterns and the socio-economic situation were investigated. Forest cover in the 1960s was 73.3 % (13.3 Mha). However, this drastically decreased to 47.3% (8.6 Mha) in 2016. In the 1960s, the forest was less-disturbed. From 1970 to 1993, the forest was lost gradually owing to the political instability caused by the Cambodian Civil War. In the post-war reconstruction period from 1993 to around 2002, the need for reconstruction, international demand for timber, and forest logging concessions led to a significant increase in timber production. In the rapid economic growth period from 2002 until present, while several political actions were taken to combat rapid deforestation, economic land concessions, which promoted agroindustrial plantations, as well as small-scale agriculture has been leading to the rapid expansion of arable land and deforestation since 2009.

This study quantified the effect of weeding frequency and weeding schedules on weeding operation time in a sugi (Cryptomeria japonica) plantation stand. A weeding operation time estimation model was developed; then the cumulative weeding operation time after six growing seasons was simulated using the developed model. The developed model included weed height, relative height of weeds to sugi, and initial planting density. The simulated cumulative weeding operation time decreased approximately 6% for each one-treatment decrease in weeding frequency. Under a three-treatment weeding frequency scenario, the simulated cumulative operation time when weeding was conducted during non-consecutive years was longer than that when weeding was conducted during three consecutive years. The results suggest that carrying out weeding treatment during consecutive years is the more effective for reduction of weeding costs. We conclude that weeding schedule as well as weeding frequency must be considered for reduction of weeding operation time.

SummaryIncreasing attention has been given to evaluating the effectiveness of forest conservation projects, but it is not well known whether different methods yield similar results when evaluating changes in forest resources. The present study compares forest cover maps and local people’s perceptions for evaluating the effectiveness of the Chambok community-based ecotourism (CBET) programme in Cambodia. We assessed forest cover changes from 2000 to 2012 using published global maps and used a covariate matching method to compare forest sites in CBET and non-CBET areas. We also analysed local people’s perceptions of forest resource changes by interviewing 174 households. The forest cover maps showed that the Chambok CBET was effective at reducing deforestation, although the outcome was not completely robust to unobserved heterogeneity. Local people’s perceptions concurred with the effectiveness observed in the forest cover maps, in that 64% of the people perceived that forest resources increased and 75% thought that the local community could protect its own forest resources. We conclude that the Chambok CBET performed effectively for forest conservation and suggest that mixed-method approaches are essential for evaluating the effectiveness of conservation programmes.

Community-based ecotourism (CBET) has become a popular tool, especially in developing countries, for biodiversity conservation and livelihood improvement, but there is a lack of studies that use quantitative data to evaluate the effectiveness of CBET using a before-after-control-intervention (BACI), BA, or CI design. We conducted a case study of the flagship Chambok CBET program in Cambodia to quantify the contribution of CBET to household income and livelihood changes for CBET and non-CBET members. We conducted an interview survey of 173 households (77 CBET and 96 non-CBET members) that were selected systematically from every two households along roads within the same villages. There was no significant difference between the total income of member and non-member households; the median CBET income was 1.22 USD per month, which is only 1.65% of the total income. The inequality of income from CBET among the CBET members was higher than that from other income sources. The perceptions of livelihood changes differed considerably before and after the establishment of the Chambok CBET program, although this difference was not attributed to CBET but rather to general socioeconomic changes in the country. We conclude that it is challenging to employ CBET to achieve poverty reduction and livelihood improvement.

Firewood and charcoal are the main energy sources in developing countries, but much fewer quantitative data have been collected for charcoal consumption. This study compared firewood and charcoal consumption rates and patterns in a rural area of Yedashe Township, Myanmar. Household interviews were conducted for randomly selected households, resulting in 147 firewood users and 34 charcoal users. Forest inventory data was used to estimate forest area needed to meet woodfuel demand. Average per capita consumption rates were 780 and 280 kg year−1 for firewood and charcoal, respectively. Distinct differences were found in fuel sources and sizes; only 16% of firewood was collected from living trees in natural forests, of which 72% was from trees

This study evaluated the uncertainty of individual tree biomass estimated by allometric models by both including and excluding tree height independently. Using two independent sets of measurements on the same trees, the errors in the measurement of diameter at breast height and tree height were quantified, and the uncertainty of individual tree biomass estimation caused by errors in measurement was calculated. For both allometric models, the uncertainties of the individual tree biomass estimation caused by the use of a specific allometric model were also calculated. Finally, the overall uncertainty of individual tree biomass by combining the two uncertainties was calculated. The allometric model including tree height was 6 % more accurate than that excluding tree height when the uncertainty caused by allometric models became the only consideration. However, in terms of the uncertainty caused by measurement, the allometric model excluding tree height was three times more accurate than allometric model including tree height. As a result, the allometric model excluding tree height was 5 % more accurate than the allometric model including tree height when both causes of uncertainty, the allometric model and measurement errors were considered. In conclusion, errors in tree height measurement have the potential to increase the error of aboveground biomass estimation.

This study investigated the effect of weeding on the height growth of planted sugi (Cryptomeria japonica) saplings in southwestern Japan. First, we developed stand-level sugi and weed annual height growth models that accounted for tree spacing, slope aspect, and mean sugi height at the end of prior growing season and mean weed height just after weeding. Then, we simulated sugi heights after the sixth growing season under 64 different weeding schedules, using the developed model to examine the effects of the weeding frequency and the timing of weeding. The selected model for sugi height growth was expressed in terms of mean sugi height, mean weed height, slope aspect, and the relative height of weeds to sugi. In the case of weeds, the selected model was expressed in terms of mean sugi height, slope aspect, and the relative height of weeds to sugi. The simulation showed that sugi height decreased approximately 20% for every one-time reduction in the number of weeding. The simulation also showed that...

Logging damage to residual trees is an important parameter when considering the sustainability of selective logging in tropical natural forests. Here, we applied a proposed tree-based approach to e...

We examined a new method to detect the biodiversity hotspots in terms of complex patch mosaics at a regional scale in East Java, Indonesia, in order to develop the safeguard against further expansion of monocultures by REDD+. A land-cover map consisting of five major land-cover types (forest, agricultural land, bare land, water, and residential) was generated with a 30 m x 30 m resolution by the unsupervised classification of a Landsat8-OLI image. Shannon’s diversity index ( H’ ) was calculated for each of 10.98 ha (11 x 11 pixels) landscape throughout the study area based on the dominance of the land-cover types by five calculation methods with different combinations of land-cover types. Then, the landscapes of upper 5 % in H’ was selected as the potential hotspots in terms of highly complex patch mosaics. Among the five potential hotspots, the calculation of H’ with four land-cover types (forest, agriculture, water, and bare land) was thought to be most suitable to set conservation targets at a regional scale, because the potential hotspots by this method showed aggregated distribution patterns, and was less sensitive to the small residential patches. While, no clear distribution trend was observed along the environmental gradients.

The restoration of degraded forests is the focus of global attention. Effective restoration requires information on the condition of degraded forests. This study aimed to understand the conditions of illegally logged stands that had also experienced inappropriately short rotations between legal logging cycles in natural production forests in Myanmar. Four rectangular plots (each 0.64 ha) were established in 2013. The plots included illegally logged stumps in three compartments where the latest legal logging was conducted in 2011 after very short rotations between legal logging cycles (up to five harvests between 1995 and 2011, compared with a recommended 30-year logging cycle). Using data from the field measurements in 2013 on the legal and illegal stumps and living trees, we reconstructed stand structure just before and after legal logging in 2011. Before the legal logging in 2011, there were variations in stand structure and the composition of commercial species among four plots. Illegal logging (14&ndash, 31 trees ha&minus, 1) was much higher than legal logging (0&ndash, 11 trees ha&minus, 1). Illegal logging targeted six to nine species that were suitable for high-quality charcoal from various sized trees, while legal logging targeted one or two timber species with a diameter at breast height (DBH) larger than 58 cm. The number of remaining trees in 2013 ranged from 33 to 181 trees ha&minus, 1. There was a negative relationship with the number of bamboo clumps, which varied from 6 to 145 clumps ha&minus, 1. Bamboo-dominated stands with a low remaining stock of commercial trees may need active restoration such as bamboo cutting and replanting of commercial species. Bamboo cutting could generate income for the local community.

SUMMARY Reduced-impact logging (RIL) is widely expected to maximize conservation values of selectively logged tropical forests; however, there remains a lack of supporting data to confirm the effectiveness of individual RIL practices. This study evaluates the extent of damage to residual stands and soil caused by directional felling, elephant skidding, and road construction in a tropical mixed deciduous forest under the Myanmar Selection System (MSS). The felling damage number was consistently larger for bamboo clumps than for trees over the range of felled tree size and felling intensity. Soil disturbed by road construction made up 4.6% of the 9-ha study area, but no visible damage to residual trees and soil from elephant skidding was found three months after the operation. Directional felling toward bamboos and elephant skidding of MSS are effective as RIL practices, producing the lowest level of damage to residual trees and soil as compared with other RIL studies.

Appropriate cutting cycles and annual allowable cuts are crucial to ensure sustainability of tropical selective logging, but there have been limited field data to verify long-term effects of different cutting cycles. This study reveals some evidence of forest degradation in selectively logged production forests of Myanmar, which are subject to inappropriate cutting frequency. We compared stand structure, commercial species composition, and incidence of illegal logging between two compartments with low (LCF; 1 time) and high (HCF; 5 times) cutting frequency over a recent 18 years. Prior to the latest cutting, LCF had 176 trees ha − 1 with an inverted-J shape distribution of diameter at breast height (DBH), including a substantial amount of teak ( Tectona grandis ) and other commercially important species in each DBH class. HCF prior to the latest cut had only 41 trees ha − 1 without many commercially important species. At HCF, nearly half the standing trees of various species and size were illegally cut following legal operations; this was for charcoal making in nearby kilns. At LCF, two species, teak and Xylia xylocarpa , were cut illegally and sawn for timber on the spot. More extensive and systematic surveys are needed to generalize the findings of forest degradation and illegal logging. However, our study calls for urgent reconsideration of logging practices with high cutting frequency, which can greatly degrade forests with accompanying illegal logging, and for rehabilitating strongly degraded, bamboo-dominated forests. To reduce illegal logging, it would be important to pay more attention on a MSS regulation stating that logging roads should be destroyed after logging operations.

Some previous studies along an elevational gradient on a tropical mountain documented that plant species richness decreases with increasing elevation. However, most of studies did not attempt to standardize the amount of sampling effort. In this paper, we employed a standardized sampling effort to study tree species richness along an elevational gradient on Mt. Bokor, a table-shaped mountain in southwestern Cambodia, and examined relationships between tree species richness and environmental factors. We used two methods to record tree species richness: first, we recorded trees taller than 4 m in 20 uniform plots (5 × 100 m) placed at 266–1048-m elevation; and second, we collected specimens along an elevational gradient from 200 to 1048 m. For both datasets, we applied rarefaction and a Chao1 estimator to standardize the sampling efforts. A generalized linear model (GLM) was used to test the relationship of species richness with elevation. We recorded 308 tree species from 20 plots and 389 tree species from the general collections. Species richness observed in 20 plots had a weak but non-significant correlation with elevation. Species richness estimated by rarefaction or Chao1 from both data sets also showed no significant correlations with elevation. Unlike many previous studies, tree species richness was nearly constant along the elevational gradient of Mt. Bokor where temperature and precipitation are expected to vary. We suggest that the table-shaped landscape of Mt. Bokor, where elevational interval areas do not significantly change between 200 and 900 m, may be a determinant of this constant species richness.

We developed an empirical model to estimate aboveground carbon density with variables derived from airborne Light Detection and Ranging (LiDAR) in tropical seasonal forests in Cambodia, and assessed the effects of LiDAR pulse density on the accurate estimation of aboveground carbon density. First, we tested the applicability of variables used for estimating aboveground carbon density with the original LiDAR pulse density data (26 pulse m−2). Aboveground carbon density was regressed against variables derived from airborne LiDAR. Three individual height variable models were developed along with a canopy density model, and three other models combined canopy height and canopy density variables. The influence of forest type on model accuracy was also assessed. Next, the relationship between pulse density and estimation accuracy was investigated using the best regression model. The accuracy of the models were compared based on seven LiDAR point densities consisting of 0.25, 1, 2, 3, 4, 5 and 10 pulse m−2. The best model was obtained using the single mean canopy height (MCH) model (R 2 = 0.92) with the original pulse density data. The relationship between MCH and aboveground carbon density was found to be consistent under different forest types. The differences between predicted and measured residual mean of squares of deviations were less than 1.5 Mg C ha−1 between each pulse density. We concluded that aboveground carbon density can be estimated using MCH derived from airborne LiDAR in tropical seasonal forests in Cambodia even with a low pulse density of 0.25 pulse m−2 without stratifying the study area based on forest type.

In many tropical regions, rural households often depend on forests for cash income, but there is still little knowledge on how forest use strategies differ among people living in different locations. This study aimed to detect differences in forest use strategies and forest cash income dependency between households living outside and inside selectively logged production forests, known as Reserved Forests (RFs), in Bago Township, Myanmar. A questionnaire survey was conducted with 146 and 48 households living outside and inside the RFs, respectively. The inside-households (encroachers) had a much higher forest cash income dependency (83%), with charcoal production as the main forest use activity, than the outside-households (32%), with bamboo cutting as the main activity. Higher forest dependency was found for outside-households that had less farmland, better accessibility to forest and more recognition of prohibited access to RFs in forest law. This study revealed evidence of substantial forest use for commercial purposes in RFs by households living both inside and outside the RFs, despite local recognition of the illegality of the use. Implementing community forestry practices for local communities may be a better option to reduce illegal dependence on selectively logged production forests.

Community forestry (CF) is increasingly used in developing countries to achieve both the socioeconomic outcome of poverty reduction and an ecological outcome. There have been many single case studies in a specific region to identify the factors affecting the success or failure of CF. Other studies have used large-N data collected from multiple countries. However, there is a dearth of large-N studies within a single country. In this study, we used a country scale dataset of 197 CF projects, established between 1994 and 2005 across Cambodia, to identify the biophysical factors that affected forest cover changes from 2005 to 2016. A mixed-effects logistic regression model was used for a total of 71,252 randomly sampled data pixels nested in the 197 CF. Results showed that deforestation in CF was likely to increase with increasing size of CF area at lower elevations and on gentler slopes. Deforestation also increased if CF was located close to villages, markets and CF boundaries, but further away from main roads. These findings on biophysical factors can help the government to decide on priority locations for further conservation interventions or for the establishment of new CF projects.

Developing countries that intend to implement the United Nations REDD-plus (Reducing Emissions from Deforestation and forest Degradation, and the role of forest conservation, sustainable management of forests, and enhancement of forest carbon stocks) framework and obtain economic incentives are required to estimate changes in forest carbon stocks based on the IPCC guidelines. In this study, we developed a method to support REDD-plus implementation by estimating tropical forest aboveground biomass (AGB) by combining airborne LiDAR with very-high-spatial-resolution satellite data. We acquired QuickBird satellite images of Kampong Thom, Cambodia in 2011 and airborne LiDAR measurements in some parts of the same area. After haze reduction and atmospheric correction of the satellite data, we calibrated reflectance values from the mean reflectance of the objects (obtained by segmentation from areas of overlap between dates) to reduce the effects of the observation angle and solar elevation. Then, we performed object-based classification using the satellite data (overall accuracy = 77.0%, versus 92.9% for distinguishing forest from non-forest land). We used a two-step method to estimate AGB and map it in a tropical environment in Cambodia. First, we created a multiple-regression model to estimate AGB from the LiDAR data and plotted field-surveyed AGB values against AGB values predicted by the LiDAR-based model (R2 = 0.90, RMSE = 38.7 Mg/ha), and calculated reflectance values in each band of the satellite data for the analyzed objects. Then, we created a multiple-regression model using AGB predicted by the LiDAR-based model as the dependent variable and the mean and standard deviation of the reflectance values in each band of the satellite data as the explanatory variables (R2 = 0.73, RMSE = 42.8 Mg/ha). We calculated AGB of all objects, divided the results into density classes, and mapped the resulting AGB distribution. Our results suggest that this approach can provide the forest carbon stock per unit area values required to support REDD-plus.

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 (R2 = 0.94) and was comparable to the model using CHMPL (R2 = 0.93). The model using CHMPP yielded the lowest accuracy (R2 = 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.

The quality of diameter measurements for natural old-growth forest was evaluated by comparing repeated field measurements in a diameter census and tree-ring chronologies. The diameter census was repeated three times from 1973 at 10- to 19-year intervals in old-growth Cryptomeria japonica forests on Yakushima Island, Japan. The diameter growth in the three intervals between (1) first and second measurement (15–19 years), (2) second and third measurement (10–13 years), and (3) first and third measurement (28–30 years) were calculated. The diameter growth of each interval was also measured using tree-ring chronologies as a control. There were significant differences in paired t tests for diameter growth calculated from the diameter census data and from the tree-ring chronologies when the interval was 27 years. The average percentage differences (APDs) were relatively high for every interval and for all diameter classes, but the APDs for the 28- to 30-year intervals were better than the 10- to 19-year intervals. The APDs followed a rising trend with increasing diameter at breast height for every interval. In conclusion, data from an interval of >27 years is required for accurate estimation of diameter growth. Furthermore, extra care should be taken when measuring large diameter trees. The results from this study demonstrated the difficulty of using a diameter census in natural old-growth forest.

In this study, we test and demonstrate the utility of disturbance and recovery information derived from annual Landsat time series to predict current forest vertical structure (as compared to the more common approaches, that consider a sample of airborne Lidar and single-date Landsat derived variables). Mean Canopy Height (MCH) was estimated separately using single date, time series, and the combination of single date and time series variables in multiple regression and random forest (RF) models. The combination of single date and time series variables, which integrate disturbance history over the entire time series, overall provided better MCH prediction than using either of the two sets of variables separately. In general, the RF models resulted in improved performance in all estimates over those using multiple regression. The lowest validation error was obtained using Landsat time series variables in a RF model (R2 = 0.75 and RMSE = 2.81 m). Combining single date and time series data was more effective when the RF model was used (opposed to multiple regression). The RMSE for RF mean canopy height prediction was reduced by 13.5% when combining the two sets of variables as compared to the 3.6% RMSE decline presented by multiple regression. This study demonstrates the value of airborne Lidar and long term Landsat observations to generate estimates of forest canopy height using the random forest algorithm.

Summary In central Cambodia, rapid growing non-endemic species are planted for future timber production. However, less is understood about the impact of the introduction of non-endemic species on the transpiration characteristics of the forest, which has been composed of native species that adapted to the highly seasonal environments. Sap flux of two native and one non-endemic tree species in central Cambodia was measured to reveal its seasonal trends and variability in the Monsoon Asia region. Measurements were carried out in a 10- to 15-year-old forest in the dry and rainy seasons that were defined by differing rainfall patterns. The seasonal trend in depth to water table differed from that of rainfall; groundwater table depth reached zero late in the rainy season and increased gradually after the onset of the dry season. The ratio of sap flux to an equilibrium evaporation condition of the native species, Popel ( Shorea roxburghii ), showed a sharp decline at the end of the dry season, whereas that of a non-endemic species, eucalyptus ( Eucalyptus camaldulensis ), decreased in the mid rainy season while Tbeng ( Dipterocarpus obtusifolius ) did not show a clear trend. The ratio of sap flux to an equilibrium evaporation was negatively correlated with the depth to water table in Popel, but was positively correlated in eucalyptus, possibly because of the negative effects of flooding. In addition to the large seasonal variation, intra-species variation in sap flux was also large and was a major controlling factor for tree-level water uptake at this young forest site in both dry and rainy seasons. In conclusion, the transpiration characteristics of this forest were species-specific and were controlled more by the fluctuating depths to groundwater rather than the onset of the rainy/dry seasons defined by rainfall events.

Globalization and urbanization have significantly increased the food and non-food commodity demand for the last century, and it is vital to consider a business strategy with economical and ecological sustainability. The objective of this study was to project the contribution of wood to the financial performance of rubber plantations. We adopted cost and revenue data of rubber plantations in Cambodia and utilized land expectation value (LEV) as the criterion for profitability analysis. Among the top-ten rubber-producing countries in pan-tropics, the areas of rubber plantation were equivalent to from 1% to 90% of forest plantations and 0.3%–10.2% of total forest areas. Rubberwood revenue accounts for about 4%–10% of the 30th year LEV in rubber plantations at discount rates of 2% y−1–10% y−1, and this was sufficient to cover the cost of re-establishing the plantations. The proportion of the 30th year LEV contributed by wood revenue increased under conditions normally associated with a more difficult business environment, i.e., at higher wage costs, and lower latex revenue. We found that the wood revenue can improve the profitability of rubber plantations by up to 40% depending on the price of the rubberwood. We assert that timber from wood producing commodity plantations should be encouragingly utilized as industrial timber by linking the wood production in the management strategy of the plantations.

Deforestation and forest degradation in the tropics have importance to the global carbon budget and biodiversity conservation disproportionately greater than the area concerned. Many studies have examined the patterns and processes of deforestation, but information about factors influencing forest degradation is still limited. In this study, we examined the factors influencing both deforestation and forest degradation in production forests of the central Bago Mountain area, Myanmar, which have been managed under the Myanmar Selection System (MSS) since 1856. We used forest canopy density maps derived from 1989 and 2006 satellite imagery together with environmental factors, locational attributes and selective logging records in logistic regression models. Our results showed that elevation and distance to the nearest town strongly influenced the likelihood of both deforestation and forest degradation, while logging intensity and distance to the nearest village were correlated only with the likelihood of forest degradation and not deforestation. We conclude that selective logging in this study area does not cause forest degradation provided that logging intensity is below the allowable cut prescribed under the MSS, but above that intensity, the likelihood of forest degradation increases markedly.

Although a number of image classification approaches are available to estimate forest canopy density FCD using satellite data, assessment of their relative performances with tropical mixed deciduous vegetation is lacking. This study compared three image classification approaches – maximum likelihood classification MLC, multiple linear regression MLR and FCD Mapper – in estimating the FCD of mixed deciduous forest in Myanmar. The application of MLC and MLR was based on spectral reflectance of vegetation, whereas FCD Mapper was operated on integrating the biophysical indices derived from the reflectance of the vegetation. The FCD was classified into four categories: closed canopy forest CCF; FCD ≥ 70%, medium canopy forest MCF; 40% ≥ FCD < 70%, open canopy forest OCF; 10% ≥ FCD < 40% and non-forest NF; FCD < 10%. In the three classification approaches, producer's and user's accuracies were higher for more homogeneous vegetation such as NF and CCF than for heterogeneous vegetation density VD such as OCF and MCF. FCD Mapper produced the best overall accuracy and kappa coefficient. This study revealed that only spectral reflectance is not enough to get good results in estimating FCD in tropical mixed deciduous vegetation. This study indicates that FCD Mapper, an inexpensive approach because it requires only validation data and thus saves time, can be applied to monitor tropical mixed deciduous vegetation over time at lower cost than alternative methods.

We examined the contribution of rubberwood to the timber export markets of Malaysia and Thailand. In Malaysia, rubberwood has grown from 26% of total exported wood products in 1998 to 35% in 2007. A high proportion of furniture products (80%) is rubberwood, whereas the contribution of rubberwood to other wooden products is less than 20%. Only 10% of sawn timber and logs is rubberwood. In Thailand, rubberwood contributes to around 60% of total exported wood products, arising from a high share of not only furniture products (70%) but also other wood products (around 50%) and sawn timber and logs, which have increased in share from 40% in 1998 to 79% in 2007. We conclude that the high proportion of rubberwood products in the wood export markets of these two countries is a result of: (1) scarcity of raw wood materials because of strict controls on the logging of natural forests; and (2) governmental support to rubberwood production, including financial support to rubber planters and technical assistance to downstream timber processors.

For object-based forest stand type classification using high resolution satellite data, the relation of the parameter of segmentation and classification accuracy was investigated. A target area is forested landscape in the Kirishima area over both Ebino city of Miyazaki and Kirishima city of Kagoshima, the southern part of Kyushu Island. A pan-sharpen IKONOS data (1-m of spatial resolution) was employed in this analysis. In addition to varying the scale parameter from 100 to 1000, some combinations of color and shape criterion were examined. As a result of measuring the accuracy of forest stand type classification, when scale parameter was 300, the highest classification accuracy was achieved. It was indicated that the color criterion also affects classification accuracy in this study. Consequently, it would be greatly concerned with classification accuracy whether target patches are delineated adequately by segmentation, and this paper indicated that quantitatively.