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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.

Detecting forest disturbances is an important task in formulating mitigation strategies for deforestation and forest degradation in the tropics. Our study investigated the use of Landsat time series imagery combined with a trajectory-based analysis for detecting forest disturbances resulting exclusively from selective logging in Myanmar. Selective logging was the only forest disturbance and degradation indicator used in this study as a causative force, and the results showed that the overall accuracy for forest disturbance detection based on selective logging was 83.0% in the study area. The areas affected by selective logging and other factors accounted for 4.7% and 5.4%, respectively, of the study area from 2000 to 2014. The detected disturbance areas were underestimated according to error assessments; however, a significant correlation between areas of disturbance and numbers of harvested trees during the logging year was observed, indicating the utility of a trajectory-based, annual Landsat imagery time series analysis for selective logging detection in the tropics. A major constraint of this study was the lack of available data for disturbances other than selective logging. Further studies should focus on identifying other types of disturbances and their impacts on future forest conditions.

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.

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.

Monitoring forest changes based on numerous satellite images has been recently conducted in the tropics. Preparation of a time series of satellite images, sometimes referred to as preprocessing, is essential for conducting robust detection of forest change. To create consistent and stable conditions in satellite images, the best methods have to be used in each step to correct various sources of noise. This study assessed three atmospheric correction methods, six topographic correction methods, and eight gap-filling methods to produce the best possible time series of Landsat images of tropical seasonal forests. The results showed that the best methods for atmospheric and topographic correction were relative corrections using a Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS), which is based on a 6S radiative transfer model, and the C-correction, respectively. Weighted linear regression and multiple linear regression models were selected as the best models for the filling of data gaps associated with Scan Line Corrector-off and clouds, respectively. This study provided the best possible image preprocessing for trajectory-based change detection using annual Landsat images. Although the best possible preprocessing methods might vary depending on the change detection methods used in different study areas, the results highlight the preferable preprocessing methods, even for different types of time series analysis.

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.

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.

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.

Tropical forests are highly threatened by human activities, even within the protected areas that have been established to conserve biodiversity. Human activities may have different degrees of impact on vegetation structure, composition and diversity. Some studies have measured direct evidence of human activities in forming disturbance gradients, while others have quantified canopy cover as a proxy for disturbance. When measurement is confined to human activities, disturbance may be underestimated in areas of poor canopy cover where forest degrading activities have ceased. Where measurements are restricted to canopy cover, disturbance may be underestimated in areas of extensive canopy cover that may have been subject to past disturbances, and overestimated for areas where canopy cover is naturally sparse. Combining indicators of past and present disturbances is therefore necessary to examine the full spectrum of human disturbances. Forest vegetation in Popa Mountain Park, Myanmar was surveyed and classified into three levels of disturbance—undisturbed, medium disturbed and highly disturbed—derived from evidence of cutting and canopy cover. The forests are second or third growth after clearing for agriculture in the early 20th century. All trees with ≥10 cm diameter at breast height in 168 sample plots (10 m × 10 m) were identified and measured. Density, basal area and diversity decreased and dominance rose when disturbance increased. Canonical correspondence analysis (CCA) clearly discriminated three forest stands and CCA axes were significantly correlated to soil moisture, soil nitrogen, elevation, slope, aspect, distance from park boundary and distance from villages. Abstract in Myanmar is available at http://www.blackwell-synergy.com/loi/btp.

再造林放棄地の発生状況を定量化することを目的として, 九州本島全域を対象として各県別の放棄地発生率を算出し, さらに放棄地の発生場所を空間的に明示した。針葉樹人工林伐採跡地の再造林の有無を確認するため, 多時期リモートセンシングデータを用いた画像解析から得られた森林変化点を用いた。また, 今回1998∼2002年 (前期), 2002年以降 (後期) で集計を行い, この2期間で放棄地の発生状況がどのように変化したのか提示した。点数ベースでみてみると九州本島全域での放棄地発生率は前期が24.3%, 後期が30.9%であった。放棄地の分布状況をGISで図化した結果, 前期, 後期とも共通して, 放棄地は九州本島全域の森林域に満遍なく存在しているというよりは, 特定のエリアに集中していた。2次メッシュ単位で人工林伐採面積, 放棄地面積を集計し, メッシュ単位で放棄地発生率を求めた。放棄地が著しく多く発生している箇所 (発生率50%以上) がみられた箇所を前期と後期で比べてみると, その多くが一致しておらず, 放棄地発生箇所が移動していることがわかった。また, 少なくともこの2期間では後期の方で放棄地の発生場所が広く分散するようになっていることが確認できた。

主間伐等の施業を行う際, 用材以外に端材, 枝条, 形質不良材, 切り捨て材等の残材が発生する。近年, 化石燃料価格の高騰等の外部環境の変化により, これらのエネルギー資源としての価値が高まってきつつあるが, 未利用残材収集を考慮した場合の林分経営に関する研究は少ない。そこで本研究では未利用残材収集を考慮した場合の最適林分経営を, 動的計画法を用いて検討し, 最適林分経営戦略とその収支の変化を観察した。一般的な九州地方のスギ一斉林における全木・全幹集材施業を想定し, 残材発生量は丸太歩留率の損失分とし, 間伐に関しては全量を残材とする間伐を選択肢に組み込んだ。残材価格を3.0∼9.0円/kgで変化させたシミュレーションの結果, 最適輪伐期や間伐計画に大きな差はみられなかったが, 残材価格の上昇に従い間伐の内容は全量残材向けの間伐へとシフトしていくことがわかった。林業経営体の経営収支に関しては, 残材価格の上昇に従いSEVは増加し, 残材価格6.0円/kgの場合, 残材収集を行わない場合と比較してSEVが約15∼63%増加した。その効果は主に主伐時の残材収集によるものであり, 間伐由来の残材収集が与える影響は比較的小さかった。

Shifting cultivation is a widely practiced agriculture system in the tropics. Regardless of the dominant land use, the dynamics of shifting cultivation over large areas are of limited knowledge. We conducted patch-based assessments and characterization of shifting cultivation extracted from already developed dataset, which detected shifting cultivation by a trajectory-based analysis using annual Landsat TM/ETM+/OLI time series images from 2000 to 2014 in Myanmar. An accuracy assessment was conducted in terms of the size and number of cleared areas compared with reference polygons of shifting cultivation, which were manually delineated by visual interpretation using Landsat and high-resolution satellite images from Google Earth&trade, in the selected areas. The producer&rsquo, s and user&rsquo, s accuracies in detecting the number of shifting cultivation patches were 78.1% and 88.4%, respectively. In whole study area, the probability of disturbances caused by shifting cultivation was significantly affected by distance to the nearest village, indicating the importance of accessibility from residences. The number of shifting cultivation patches showed a decreasing trend in this region and it will lead to less cleared forests such as located far from residences. These dynamics of shifting cultivation have possibility to affect the mosaic patterns of landscape and function maintained in the landscape in this region.

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.

The lumber from sugi plantations in Japan displays large intra- and intertree variation in mechanical properties, even within a stand. These variations seem to be induced by the effects of the characteristics of cultivars as well as the effects of growth traits on mechanical properties. Therefore, the effects of growth traits on mechanical properties per cultivar need to be precisely examined. In this study, we focused on the effects of growth traits, especially height-to-diameter ratio (H/D ratio), on stem stiffness per cultivar. Sixteen cultivars were classified into three groups according to the relationships between stem stiffness and growth traits. In cultivars that showed a close correlation between growth traits and stem stiffness, it was assumed that stem stiffness could be controlled to a certain extent by silvicultural practices using the H/D ratio as an indicator. In cultivars that showed a weak correlation between growth traits and stem stiffness, selecting cultivars for the production of logs with higher mechanical properties seemed to be effective; in this study, Kumotoshi, Tanoaka, and Edanaga were found to be suitable. Tree age and site index may be important factors for producing wood with higher mechanical properties.

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.

下層植生からみた剥皮害の発生傾向を明らかにすることを目的として，熊本県球磨地域のヒノキ人工林77地点を対象に，剥皮害木本数と下層植生との関連性を検討した。まず，下層植生の繁茂状況をデジタルカメラを用いて撮影し，定量化した。また，下層植生の種組成データを基に，TWINSPANにより調査点を三つの植生タイプに分類した（スズタケタイプ，先駆種タイプ，常緑高木種タイプ）。次に，下層植生が繁茂している調査点では剥皮害木本数が低く抑えられているのか，ブートストラップ法により検討した。その結果，常緑高木種タイプの調査点においてのみ，下層植生の繁茂状況が剥皮害木本数の多寡に影響していたことが明らかとなった。これは，下層植生による物理的，視覚的な遮蔽効果によるものであると考えられた。

竹林の分光反射特性の季節変動を把握することを目的として, 多時期衛星データ (SPOT/HRVデータ8シーン, LANDSAT/TMデータ9シーン) の解析および地上での分光反射測定から竹林, 広葉樹林, 針葉樹人工林の分光反射特性の季節変動を把握した。その結果, 衛星データと地上分光反射データにはいくつかの共通点がみられた。4～6月の可視赤色域においては, 竹林は他の森林タイプよりも反射係数およびデジタルナンバーが高い傾向にあった。近赤外域では, 竹林と広葉樹林で春から夏にかけて順位の入れ替わりがあった。短波長赤外域は, 衛星データにおいて竹林が年間を通して最も高い値をとった。また, 5～7月の近赤外域およびほとんどのシーンの短波長赤外域において全森林タイプ間でデジタルナンバーに有意差がみられた。竹林の分光反射特性の季節変動には, 葉替わりが大きく関与しているものと思われた。

Timber harvest plan in forest management should be flexible to meet changing social and environmental needs. We need to collect and process the proper forest information, which will enhance the efficiency of working process in the harvest plan. Especially, GIS and RS techniques have been considered to have a benefit in processing the multidirnensional information. The purpose of this study is to present strategic forest planning procedure that can support the identification of forest structures and the maxirnum use of forest functions through GIS, RS and LP techniques. In this study, forest information such as compartment structure and forest road was entered into GIS to construct FMIS. DEM was constructed using base maps of 1/5000 for the geographic analysis. Aerial photographs and DEMS Were used to create orthophoto. Orthophoto was used to classify forest into 3 types, artificial, natural and bare forest. And then geographical attributes of each forest type were identified. Sugi (Cryptomeria japonica) forest area of each forest type was used in the harvest simulation. A spatial constraint, distance from a forest road, is taken into consideration in the LP. New groupmg umt so called "harvest unit", was introduced as the forest management unit. Strategic forest planning based on the "harvest unit" was proposed that considering both of the economic and environmental aspects