Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

DOI： 10.1007/s10745-018-9994-x

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS LTD  

Estimation of the current successional status of long-lived coniferous forests is difficult especially after several hundred years of human disturbance. However, in Cryptomeria japonica forest on Yakushima Island, the stumps generated by logging activities from the seventeenth to nineteenth centuries remain almost intact without intense rotting. From an inventory of these stumps and long-term monitoring of current stands for more than 25 years, we estimated the forest condition before logging and evaluated the current status of secondary succession. The size structure of Cr. japonica stumps suggested the stumps were composed of two different generations: the stumps of trees present before initiation of logging; and those of trees that regenerated after initiation of logging. In the current forest, the stem number of canopy species is decreasing and that of understory broad-leaved species is increasing. Regenerating Cr. japonica individuals are rare. Before the logging, the forest contained a larger number of larger Cr. japonica trees than the current forest. The results of monitoring the current forest suggested that all coniferous species, including Cr. japonica, were still undergoing self-thinning. The current Cr. japonica forest is in an intermediate stage of secondary succession, but the processes of succession are markedly different between the study plots, depending on their location or previous logging intensity.

DOI： 10.1080/13416979.2016.1273085

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Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

[in Japanese]

DOI： 10.11519/jfsc.127.0_55

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER GMBH  

The Crested Ibis, became extinct in the wild in Japan in 1981; however, a captive breeding facility was established on Sado Island, Niigata Prefecture in 1999 in the hope of conserving the species. Following successful breeding at the facility, a group of birds was released on Sado Island on 25th September 2008, with further reintroductions in subsequent years. Habitat restoration is also necessary to facilitate the re-introduction program of this endangered species. The aim of this study was to detect suitable nesting areas for the released ibises on Sado Island for subsequent nature restoration. Since little ibis nesting information was available for Sado Island, the nesting model was constructed from nesting information from China, from which results were extrapolated for Sado Island. Land usage was assessed using LAND-SAT/ETM+ data for China and SPOT/HRG images for Sado Island. In this study, land-use information was used to define the environmental parameters related to nest site selection of the Crested Ibis. For the nesting model, a generalized linear mixed model, with seven environmental factors, was employed. The multi-spatial scale for Crested Ibis nesting was also analyzed. We took the spatial scale into consideration at intervals of 100 m from a buffer size of 100 m to 2500 m. Because nest site selection was influenced by the results of the previous year, nesting location data in 2005 and 2006 were distinguished and models built accordingly. Several important environmental factors were identified for nest site selection: the ratio of broadleaved deciduous forest to coniferous forest; the shape of the forest edge; and, the distance from rice fields and other wetlands. The model's accuracy was verified using the Boyce index, and shows the validity of the model's results. Suitable nesting areas for the Crested Ibis were found mainly on: the Kuninaka plain; the ridgeline between the Kuninaka plain and the Osado or Kosado mountain ranges; the area around Lake Kamo; and, the midwestern area of the Kosado region. Suitable nesting sites for the Crested Ibis were all found to be concentrated in what is known as Yatsuda, a traditional Japanese landscape structure providing a complex mosaic of forest and rice fields with complex ecotones. Eastern Kosado, the region that has been designated by the Ministry of the Environment as the conservation area for the reintroduced birds, was not judged to provide suitable nesting habitat for the Crested Ibis. Unfortunately, no evaluation of habitat suitability was made prior to the release of the first captive-bred Crested Ibis into the wild on Sado Island. Had an evaluation of habitat suitability been performed prior to release, more effective nature restoration could have been planned. (C) 2015 Elsevier GmbH. All rights reserved.

DOI： 10.1016/j.jnc.2015.08.002

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER JAPAN KK  

The swash zone of sandy shores is a transitional habitat between the sea and land where the physical environment is the primary factor influencing the distribution of shore macrofauna. We constructed cumulative logit models using Bayesian inference to predict the ranked abundance of three species of peracarid crustaceans (Haustorioides japonicus, Excirolana chiltoni, and Archaeomysis kokuboi) that dominate the sandy shores of the Niigata coastline, Sea of Japan. Additionally, we estimated the importance of 14 environmental factors at explaining the variation in abundance. The environmental factors were grouped into three categories: swash zone, landward, and offshore. Optimum models were selected among the null model, the basic model (swash zone factors only), and additional models with landward and/or offshore factors. The optimal model for each of the three species was obtained when landward and/or offshore factors were added to the basic model, suggesting the importance of these regional factors. Combinations of significant factors differed between the three peracarid species. Some differences can be explained by accounting for life history characteristics. The slope of the offshore seafloor was the only common significant factor for the three species. Therefore, a decrease in the size of the shallow area off the sandy shore was associated with a decrease in the density of the three species. Because the peracarid crustaceans play an important role in trophic links in sandy shore ecosystems, our study results predict that an increase of coastal erosion leading to change of near-shore bathymetry will reduce the ecological function of the swash zone.

DOI： 10.1007/s11284-014-1215-5

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.18941/venus.73.1-2_51

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Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.18960/seitai.64.3_233

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：The Ecological Society of Japan  

Application of the satellite remote sensing techniques to wildlife research began from discernment of the individual animal and/or evaluation of animal behavior from the photography experiments. Satellite remote sensing to wildlife research at the present has applied for the purpose of evaluating the animal habitat. Trends in satellite remote sensing for wildlife are evaluating the index of wildlife habitat and estimating relationship with an environmental variables and animal distribution. By mapping whether wildlife is suitable for what kind of environment such as potential habitat and habitat suitability, appropriate wildlife management including zoning becomes possible in animal conservation or human-wildlife conflicts. In this paper, we propose the examples in the adaptation of satellite remote sensing techniques to wildlife problems (conservation and management) in recent years. First, the studies about satellite remote sensing of habitat indicator and habitat fragmentation in giant panda conservation were described. Furthermore, the change in potential distribution of Japanese macaques in the long period is introduced as a case study of habitat suitability research. The objective of this study was to determine changes in habitat suitability by combining satellite remote sensing and habitat model. Finally, we propose the possibility of the wildlife research using satellite remote sensing techniques.

DOI： 10.18960/seitai.64.3_253

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Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.5738/jale.19.127

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Language：Japanese   Publisher：日本森林学会  

DOI： 10.11519/jjsk.72.0_32

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Language：English   Publishing type：Research paper (scientific journal)  

A resource selection function is one that yields values proportional to the probability of use of a resource unit. This quantity is influenced by the heterogeneity of landscape structures, which occurs over multiple spatial scales. To provide input into wildlife management strategies, we investigated the scale dependency and functional responses of Japanese macaques using multiple scale analysis. The multiple buffers with radii of 100, 500, 1000, 1500, 2000, and 2500m were defined as the spatial scale. Crop damage was predicted at the within-home range scale, using the Random Forests algorithm with environmental variables linked to resource selection of Japanese macaques. Sixteen environmental variables were defined, covering aspects of landscape configuration, human disturbance, topography, and adopted countermeasures. Crop damage was most accurately predicted within a buffer zone of 1000m, although radii exceeding 1000m were also highly accurate. Although the importance of variables differed among spatial extents, the functional responses for each environmental variable were independent of spatial extent. These results suggest that the limiting factors of crop damage depend on spatial extent, while functional responses in resource selection remain constant across spatial extents. We also compared a multi-scale gradient map with a typical binary map to demonstrate the uncertainty in damage predictions at different spatial scales. Our results may aid wildlife management planning, for which differences in resource selection across different spatial scales are critically important. © 2013 Elsevier Ltd.

DOI： 10.1016/j.apgeog.2013.04.016

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Other Link： http://hdl.handle.net/10191/22567

Language：English   Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Forest Planning  

Vegetation mapping provides basic information for forest management and planning. In remote sensing research, the process of creating an accurate vegetation map is an important subject. Recently, there has been growing research interest in the object-oriented image classification techniques. The object-oriented image classification consists of multi-dimensional features including object features and thus requires multi-dimensional image classification approaches. For example, a linear model such as the maximum likelihood method of pixelbased classification cannot characterize the patterns or relations of multi-dimensional data. In multi-dimensional image classification, data mining and ensemble learning have been shown to increase accuracy and exibility. This study examined the use of the object-oriented image classification by Random Forest classification for vegetation mapping. Vegetation maps were also created using the Nearest Neighbor method and the Classification and Regression Tree method for comparison of classification accuracy. The study area was Sado Island in Niigata Prefecture, Japan. SPOT/HRG imagery (June 2007) was used and classified into the following seven classes: broadleaved deciduous forest, Japanese cedar, Japanese red pine, bamboo forest, paddy field, urban/road, and bare land. We employed eCognition software for the object-oriented image classification. We selected 18 object features: the mean, standard deviation, ratio, shape, length, and compactness for each band and normalized difference vegetation index value. High accuracy was found for the vegetation maps produced using the Random Forest and Nearest Neighbor methods. The accuracies of these two methods were significantly different from that of the Classification and Regression Tree method, as shown by kappa analysis. Among the three techniques, the Random Forest method showed the highest classification accuracies when class accuracies such as user's accuracy and producer's accuracy were considered. This study demonstrates that the Random Forest classification is effective for vegetation mapping by multi-dimensional image classification.

DOI： 10.20659/jfp.18.2_127

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Association for Landscape Ecology  

Crop damage by wildlife is becoming a serious problem in Japan. We estimated the seasonal change of the habitat use, and the factor caused to crop damage for one troop of the crop-raiding Japanese macaques in Shibata City, Niigata Prefecture. The location data acquired by radio-tracking method from 2006 to 2008 were employed. Moreover, we applied ALOS/AVNIR-2 data for detecting the land-cover within macaques habitat. At first, the seasonal change of habitat use by the Japanese macaques was evaluated using Manlys resource selection index. We also estimated the environmental factors which contributed to the occurrence of crop damage by generalized linear mixed model. As the results, habitat use by crop-raiding Japanese macaques was different by season. Japanese macaques preferred to the agricultural land during August to November. Japanese macaques were used the agricultural land as their foraging sites. Habitat use by Japanese macaques was related to the locations of the foraging sites. Especially, the dependence to the agricultural land becomes high level in the summer and winter which are the food scare seasons. The results of the generalized linear mixed model showed the difference among seasons in the environmental factors contributed to crop damage. The most important environmental factor which relate to crop damage was the minimum distance between the locations of crop damage and forest edge. As the other environmental variables which contributed to the prediction of crop damage, resources which are able to use in each season were selected (i.e., late spring: corn, other crops, and grass land, summer: corn and other crops, early winter: Kaki Persimmon). In conclusion, we propose to use the countermeasures properly in each season following the change of the environmental variables related to the occurrence of crop damage.

DOI： 10.5738/jale.18.159

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Forest Planning  

We propose a new method of extracting plantation boundary through multi-temporal image analysis using past aerial photos which have been taken by the Forestry Agency and the Geographical Survey Institute, Japan. The seven aerial photo images from 1963 to 2002 were ortho-rectified, the succeeding two-year images were combined, and image classification of this two-year composite data was carried out. Clear cut and planted sites were extracted with the second principal component of the principal component analysis of a two-year composite image of brightness or DSM data This proposed method presented the possibility to delineate the boundary of the planation. Comparing the final map with existing GIS data, the unconformity of boundary information and the inconsistency of stand age were pointed out, consequently the validity of this new method was confirmed.

DOI： 10.20659/jjfp.47.2_83

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Association for Landscape Ecology  

In this study, we evaluated the pattern of agricultural landscape mosaic in Niigata Prefecture using the Satoyama Index (SI), which is a simple index composed by agricultural landscape heterogeneity and the ratio of nonagricultural land cover. At first, land cover map based on LANDSAT imagery was classified by supervised classification method. Next, we calculated landscape heterogeneity among the 400 grid cells (20 × 20 grid cells: 600m×600m) comprising each agricultural landscape unit from the agricultural landscape heterogeneity index (ALHI). We obtained index values by multiplying the ALHI by the proportion of grid cells classified as nonagricultural landscape elements without urban within the basic landscape spatial unit. SI value was high in the bordering area between slope and flat area such as edge zone of forested area and agricultural lands. In addition, SI value was high also in the portions of along the main river or the coastal forests. There was no inconsistency in the number of landscape elements and SI value within the spatial unit by comparing the spatial pattern of land cover and the SI value. Since SI evaluates the heterogeneity in the agricultural landscape, SI showed zero in the homogenized area such as the broad-leaved deciduous forests. From our results, we pointed out that SI can just quantify the degree of heterogeneity of agricultural landscape, and it is inappropriate to evaluate the biodiversity in a region only with SI value.

DOI： 10.5738/jale.18.15

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.124.0.427.0

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.124.0.288.0

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Asian Association on Remote Sensing  

There are two methods of estimating canopy height from remote sensing data
stereo pair aerial photos and airborne LiDAR. In this study, canopy height estimation using airborne remotely sensed data was attempted at a secondary broadleaved forest. For creating digital height model (DHM), in this research, we examined three kinds of combination of digital surface model (DSM) and digital elevation model (DEM). Those combinations were a) both DSM and DEM from LiDAR, b) DSM from aerial photo and DEM from LiDAR, and c) DSM from aerial photo and DEM from public distributed data (Geospatial Information Authority of Japan). Three types of canopy height maps were created, their accuracies were evaluated, and the usefulness of each method was discussed. Consequently, DHM derived from LiDAR DSM and LiDAR DEM indicated best accuracy. Next is one from aerial photo DSM and LiDAR DEM. Although it was an ideal to carry out LiDAR measurement each time, it was confirmed that the height information derived from digital aerial photo is also useful for secondary broadleaved forest monitoring. Copyright © (2013) by the Asian Association on Remote Sensing.

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Language：English   Publisher：Japan Society of Forest Planning  

DOI： 10.20659/jfp.17.2_67_2

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Language：English   Publishing type：Research paper (international conference proceedings)  

Appropriate wildlife management is important in order to resolve human-wildlife conflicts. Prediction of wildlife distribution is essential for wildlife management. The objective of this study is clarifying the relationship between animal distribution and environmental variables derived from remote sensing data and geo-information in Honshu (the Mainland of Japan). MODIS data which has the advantage of high observation frequency, multi bands, and swath dimensions was used for preparing land cover data and Normalized Difference Vegetation Index (NDVI) data. Our target species are Sika deer (Cervus nippon), Wild boar (Sus scrofa), Japanese macaques (Macaca fuscata), Asiatic black bear (Ursus thibetanus), and Japanese serow (Capricornis crispus). Generalized linear model (GLM) was applied to specification of the environmental variables which contributes to distribution of each animal species and predicting animal distributions. There is a similar tendency in the ecological indicator which affects distribution. All species avoided human disturbance as agricultural area and urban area. And they preferred high altitude area and mixed broadleaved forest. However the effect of coniferous forest and snow cover for animal distributions differed with the difference of resource use and the adaptation-to-environment between animal species. Finally, overlay analysis was applied to the distribution maps of target species, and the mammal hot spots in Honshu were extracted.

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Language：English   Publishing type：Research paper (international conference proceedings)  

Land cover mapping provides basic information for advanced science such as ecological management, biodiversity conservation, forest planning and so on. In remote sensing research, the process of creating an accurate land cover map is an important subject. Recently, there has been growing research interest in the object-oriented image classification techniques. The object-oriented image classification consists of multidimensional features including object features and thus requires multi-dimensional image classification approaches. For example, a linear model such as the maximum likelihood method of pixel-based classification cannot characterize the patterns or relations of multi-dimensional data. In multi-dimensional image classification, data mining and ensemble learning have been shown to increase accuracy and flexibility. This study examined the use of the object-oriented image classification by the multiple machine learning algorithms for land cover mapping. We applied four classifiers: Classification and regression tree (CART), Decision tree with Boosting, Decision tree with Bagging, and Random Forest. The study area was Sado Island in Niigata Prefecture, Japan. Pan-sharpened SPOT/HRG imagery (June 2007) was used and classified into the following eight classes: broad-leaved deciduous forest, Japanese cedar, Japanese red pine, bamboo forest, paddy field, urban area, road, and bare land. We prepared four data sets with the object based features including textural information. The number of features is increased from data set I through IV. As the result, CART was unsuitable for multi-dimensional classification. Random Forest and Decision tree with Boosting showed high classification accuracies. Furthermore, in the data set with the limited features, Decision tree with Boosting was the accurate classifier. Finally, we propose two machine learning algorithms to every datasets. Random Forest is effective in the case of the multi-dimensional image classification such as data set II, III, and IV. Decision tree with Boosting is effective in the case of the image classification with the limited features such as data set I.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCIENCE BV  

The aim of this study was to evaluate changes in macaque habitat selection during a 29-year period. We focused on the 1970s, when little crop damage was caused by Japanese macaques (Macaca fuscata), and the 2000s, when the damage became remarkable. Landsat/MSS from 1978 and ALOS/AVNIR-2 from 2007 were employed for land-cover mapping. For the 2007 land-cover classification, we applied an object-oriented image classification and a classification and regression tree. The Kappa coefficient of the 2007 land-cover map was 0.89. For the 1978 land-cover classification, change detection using principal component analysis and object-oriented image classification were applied to reduce resolution difference errors. The Kappa coefficient of the 1978 land-cover map was 0.84. We applied a Random Forest model for machine learning and data mining to predict the habitat selection of macaques. Several important environmental factors were identified for macaque habitat selection: the ratio of coniferous forest to farmland, distance to farmland, and maximum snow depth. The Random Forest model was extrapolated to the 1978 land-cover map. Over the 29-year period, coniferous forest changed to broad-leaved forest and/or mixed forest within the macaque habitat area. Coniferous forests were not selected as food resources by Japanese macaques. Furthermore, large-scale patches of farmland were used as food resources over the 29-year period. These changes indicated that habitat selection by Japanese macaques changed over the study period. The results show that the home range of macaques expanded, and macaques may now be distributed over a wider area as a result of changes in landscape configuration. Thus, forest planning, such as sustainable management of artificial conifer forests, is important for reducing crop damage. (C) 2011 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.jag.2011.02.006

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：THE JAPANESE FORESTRY SOCIETY  

We investigated the planting density of Sugi (<I>Cryptomeia japonica</I>) at two experimental density plots of Obi-sugi trees in the south forest district of the national forest, Miyazaki Prefecture. There were established in 1974. Both have the same systematic experimental design formulated by Nelder (1962) with 10 density blocks in the range of 376∼10,000 stems/ha and 36 repetitions. The weakness was identified in the extreme high and low density classes on the basis of the tree size, growth rate and wood quality. The high density class included the higher volume density per ha, which became constant with a volume density greater than 1,615 stems/ha. This class included trees with lower wood quality, while the low density class included those with the lower volume density per ha. From the above analysis, we concluded that the moderate planting density, which is approximately 2,000-2,800 stems per ha, is the appropriate density for low-cost forestry.

DOI： 10.4005/jjfs.93.303

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：THE JAPANESE FORESTRY SOCIETY  

Since 1990&rsquo;s, In Kyushu region, the abandonment of sites after clear-cutting plantations is increasing rapidly in Japan. Abandoned clear-cut sites may result in reduced soil and water conservation. In this study, we investigated erosions, landslides and factors limiting vegetation recovery (e.g. Damage caused by browsing by sika deer and invasion by bamboo and luxuriant vine species) in 199 abandoned clear-cut sites in the Kyushu region. Among 199 sites, 8 sites (4.2%) showed severe erosions and landslides. However, 125 sites (62.8%) showed some factors limiting vegetation recovery. Thus, the abandoned clear-cut sites are problematic, and browsing by sika deer and invasion by bamboo or vine may add limiting vegetation recovery to this problem, although a few of severe erosions and landslides currently.

DOI： 10.4005/jjfs.93.288

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Other Link： https://agriknowledge.affrc.go.jp/RN/2010830038

Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：THE JAPANESE FORESTRY SOCIETY  

To quantify non-reforested area (NRA) in the Kyushu region, we analyzed the occurrence rate of NRAs in each prefecture and their spatial distribution. To determine reforestation after coniferous plantation forest clear cutting, we analyzed images to determine changes in area using multi-temporal remotely sensed imagery. We studied two periods, from 1998 to 2002 (first period) and after 2002 (second period), to determine changes in NRA between the two periods. Point-based analysis showed that the NRA occurrence rate for the entire Kyushu main island in the first and second periods was 30.9 and 24.3%, respectively. Mapping the NRA spatial distribution using GIS showed that NRAs were concentrated in specific areas in both the first and second periods, rather than being distributed uniformly in the forested regions of Kyushu. The cut area of coniferous plantation forests and NRA were totaled using the Japanese secondary mesh unit, with the NRA occurrence rate calculated via mesh unit. In comparing the first and second periods, we found that most of the meshes showing extremely high NRAs (occurrence rate >50%) were not located in the same place in the two periods. Thus, the occurrence of NRAs shifted between the two periods, with NRAs distributed more widely in the second period.

DOI： 10.4005/jjfs.93.280

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Language：English   Publishing type：Research paper (scientific journal)  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier B.V.  

The aim of this study was to evaluate changes in macaque habitat selection during a 29-year period. We focused on the 1970s, when little crop damage was caused by Japanese macaques (Macaca fuscata), and the 2000s, when the damage became remarkable. Landsat/MSS from 1978 and ALOS/AVNIR-2 from 2007 were employed for land-cover mapping. For the 2007 land-cover classification, we applied an object-oriented image classification and a classification and regression tree. The Kappa coefficient of the 2007 land-cover map was 0.89. For the 1978 land-cover classification, change detection using principal component analysis and object-oriented image classification were applied to reduce resolution difference errors. The Kappa coefficient of the 1978 land-cover map was 0.84. We applied a Random Forest model for machine learning and data mining to predict the habitat selection of macaques. Several important environmental factors were identified for macaque habitat selection: the ratio of coniferous forest to farmland, distance to farmland, and maximum snow depth. The Random Forest model was extrapolated to the 1978 land-cover map. Over the 29-year period, coniferous forest changed to broad-leaved forest and/or mixed forest within the macaque habitat area. Coniferous forests were not selected as food resources by Japanese macaques. Furthermore, large-scale patches of farmland were used as food resources over the 29-year period. These changes indicated that habitat selection by Japanese macaques changed over the study period. The results show that the home range of macaques expanded, and macaques may now be distributed over a wider area as a result of changes in landscape configuration. Thus, forest planning, such as sustainable management of artificial conifer forests, is important for reducing crop damage. © 2011 Elsevier B.V.

DOI： 10.1016/j.jag.2011.02.006

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Language：Japanese   Publisher：Japan Association for Landscape Ecology  

DOI： 10.5738/jale.16.53

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.123.0.B16.0

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.123.0.Pb095.0

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.123.0.Pb098.0

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Language：English   Publishing type：Research paper (international conference proceedings)  

Crop damage by wild Japanese macaques is becoming an increasingly serious problem in Japan. The countermeasure of driving monkeys away from farmland to inner forest regions is currently an area of focus. However, when enforcing this measure, the environment where the troop can be established in inner forest regions is indispensable in order to avoid trespass upon farmland again. In this study, the nut species as a food resource were mapped to detect the habitat suitability area of Japanese macaques in inner forest regions. In mapping, after classifying vegetation regions approximately, the lower level classes were prepared in the specific upper level class, and the detailed classification was carried out in the lower level class. In the results, the nut species could be extracted from the remotely sensed data with a Kappa accuracy of 0.649. However, many broad-leaved deciduous forests other than the nut species were contained as an incorrect classification. Moreover, since there are few field survey points, the possibility that deviation arose in accuracy verification is high. It is necessary to acquire accurate training samples and test samples from the whole study area for the improvement in accuracy of the image classification.

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Language：English   Publishing type：Research paper (international conference proceedings)  

The aim of this study was to evaluate changes in macaque habitat selection during a 29-year period. We focused on the 1970s, when little crop damage was caused by Japanese macaques (Macaca fuscata), and the 2000s, when the damage became remarkable. Landsat/MSS from 1978 and ALOS/AVNIR-2 from 2007 were employed for land-cover mapping. For the 2007 land-cover classification, we applied an object-oriented image classification and a classification and regression tree. The Kappa coefficient of the 2007 land-cover map was 0.89. For the 1978 land-cover classification, change detection using principal component analysis and object-oriented image classification were applied to reduce resolution difference errors. The Kappa coefficient of the 1978 land-cover map was 0.84. We applied a Random Forest model for machine learning and data mining to predict the habitat selection of macaques. Several important environmental factors were identified for macaque habitat selection: the ratio of coniferous forest to farmland, distance to farmland, and maximum snow depth. The Random Forest model was extrapolated to the 1978 land-cover map. Over the 29-year period, coniferous forest changed to broad-leaved forest and/or mixed forest within the macaque habitat area. Coniferous forests were not selected as food resources by Japanese macaques. Furthermore, large-scale patches of farmland were used as food resources over the 29-year period. These changes indicated that habitat selection by Japanese macaques changed over the study period. The results show that the home range of macaques expanded, and macaques may now be distributed over a wider area as a result of changes in landscape configuration. Thus, forest planning, such as sustainable management of artificial conifer forests, is important for reducing crop damage.

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Language：Japanese   Publisher：Japan Society of Photogrammetry and Remote Sensing  

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.

DOI： 10.4287/jsprs.49.159

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Language：English   Publishing type：Research paper (scientific journal)  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Forest Planning  

In most countries, the positional accuracy of National Forest Inventory (NFI) plots is unknown, even though the NFI is expected to provide geo-referenced ground data for remote sensing. The present study evaluated the positional error of Japanese NFI plots that had already been located using a Global Positioning System (GPS) for navigational assistance toward target coordinates on a 4-km grid. The actual positions of 82 plots in 4 prefectures were measured using a high-precision GPS with dual-frequency carrier-phase observation in comparison with the target coordinates. The positional error was found to be significantly related to GPS types that had been used for navigation during the establishment of the plot, but not with terrain, canopy types and stand density. The mean error when using differential GPS (DGPS) navigation was 6.2m; significantly lower than the 20.0m obtained using autonomous GPS. We conclude that the positional accuracy of the NFI plots in Japan is acceptable for use as a ground reference for the widely used Landsat satellite images with 30-m resolution if the plots had been located using DGPS navigation. In addition, the position of plots located without the use of DGPS should be re-measured to enhance the availability of NFI data.

DOI： 10.20659/jfp.15.2_73

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Detecting the occurrence of clear-cutting is a practical use for remotely sensed data, and the image differencing method is one technique that can be used. This method is simple and powerful, but a systematic evaluation of its accuracy and a statistical determination of threshold values have not been established. We examined the accuracy of image differencing methods using a single band or band combinations, or scene combinations, to detect clear-cuts with LANDSAT/ TM data. Furthermore, we examined the relationship between clear-cut size and detection accuracy with a focus on the most effective bands. Results showed that bands 3 and 7 are optimal because they detect clear-cut areas with less error. Accuracy varied with the clear-cut size, and clear-cut regions less than 1 ha in area exhibited more error.

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Language：English   Publishing type：Research paper (international conference proceedings)  

Although the crested ibis lived over the East Asia, the population decreased drastically by overhunting or urban development by the beginning of the 20th century. In Japan, crested ibis was extinct in 2003, and now, the re-introduction project of the crested ibis has been carried out. When formulating the conservation measure, it is important to examine why crested ibis decreased. It was reported the change of the feeding area has contributed greatly to reduction of crested ibis. Therefore, it is important to detect the change of the feeding area quantitatively. In this study, multi-temporal land-cover maps were compared, and it aimed at clarifying change of the feeding environment in a crested ibis habitat. The study area was Shaanxi province of China that is main habitat for crested ibis. We used multi-temporal Landsat series data that represent the 1970s, the 1980s and the 2000s land-cover condition. In the 2000s land-cover classification, object-oriented image classification was applied. In the 1970s and 1980s land-cover classification, we combined object-oriented image classification and the change detection using principal component analysis. The kappa coefficient of three land-cover maps were 0.85 (2002), 0.77 (1988) and 0.74 (1978). Urban development and/or the crop diversification from paddy field to wheat was extracted in the change of land-cover from past to present. The study area is enacted as a nature preserve and the large-scale deforestation or land development are not progressed. Also in such area, it is suggested that management of feeding environment for crested ibis is not enough. Therefore, we suggest that the land-cover changes such as urban development or the crop diversification affect crested ibis behavior.

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER JAPAN KK  

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 (R (2) = 0.76), and this accuracy was comparable to that of the pixel-based approach (R (2) = 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.

DOI： 10.1007/s10310-009-0125-9

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Language：Japanese   Publisher：Japan Association for Landscape Ecology  

Crop damage by wildlife is becoming an increasingly problem in Japan. A troop of Japanese macaque, Otsuki troop, has been tracked using radio-telemetry near the city of Shibata, Niigata Prefecture. Home range and the core area were determined by the fixed kernel method. Core area of the troop was located around the peninsular-shaped forest sticking out in the crop fields. Landcover was classified using ALOS/AVNIR-2 images. Logistic regression analysis was used to examine the environmental factors contributing the presence /absence of crop damage by the troop. In the model of home range, 3 factors were extracted; distance between crop field and forest edge, distance between crop field and settlement, distance between crop field and road. In the model of core area, distance between crop field and forest edge was chosen as a contributing factor. These results indicated crop fields near forests were vulnerable to the damage by macaques. Peninsular-shaped forests were frequently used as corridors connecting crop fields and forest habitat, and facilitate the expansion of damage by macaques.

DOI： 10.5738/jale.14.109

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DOI： 10.1007/s11284-008-0574-1

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Language：Japanese   Publisher：Japan Society of Forest Planning  

To reveal factors affecting the intensity of trunk damage caused by sika deer (bark-stripping and fraying), we developed regression models to explain the bark-stripping intensity in Japanese cypress (Chamaecyparis obtusa) plantation forests in the Kuma district of Kumamoto Prefecture. We applied the zero-inflated negative binomial model to point-surveyed trunk damage data collected by Kumamoto Prefecture using landscape level and stand level factors as explanatory variables. The best fitted model had three explanatory variables, which were the ratio of plantation forest area around the surveyed sites and distance to the nearest road (landscape level factor), and the amount of understorey vegetation (stand level factor). This result suggested that not only landscape level factors but also stand level factors should be considered when formulating plans to prevent trunk damage damage by Sika deer in plantation forests.

DOI： 10.20659/jjfp.42.1_69

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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 m 3 /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. © 2008 The Japanese Forest Society and Springer.

DOI： 10.1007/s10310-008-0077-5

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Language：Japanese   Publisher：日本写真測量学会  

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 <I>Cryptomeria japonica</I> 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.

DOI： 10.4287/jsprs.46.6_4

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Rubber trees (Hevea brasiliensis) in Cambodia are important sources for not only natural rubber but also wood products. This study was conducted to set up stem volume equations to estimate the stand volume and the volume increment for rubber trees in Cambodia. Krek Rubber Plantation located in Kompong Cham Province was selected for study area. Sixty trees of the clone PR107 at the age of 36, 44, 45 and 46 were felled and cut into segments of one meter long to formulate the volume equation. The DBH and total height of 450 standing trees (15 plots) at different ages (6-10 and 36-48) were measured to estimate volume per hectare and the mean annual increment (MAI). This study revealed that the volume equation for standing rubber trees clone PR107 is V=0.00018381 D^<2.23961> H^<0.15334> or V=0.00024884 D^<2.29535> where V is the over bark volume (m^3), D is diameter at breast height (cm), H is total height (m). Using the two-variable equation, rubber wood volume at the rotation length of 25-30 years was estimated at about 240 - 270m^3 ha^<-1> with the MAI of 9.33 m^3 ha^<-1> yr^<-1>.

DOI： 10.20659/jfp.13.2_335

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER TOKYO  

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 m(3)/ha) of each forest type had similarity in reflectance factor.

DOI： 10.1007/s10310-007-0030-z

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To select suitable sites for restoring plantations to natural Abies firma and Tsuga sieboldii forests in the Kirishima mountain region, the likelihood of the existence of Abies seedlings was predicted using logistic regression analysis. Using information on natural forest patches and individual mature trees as seed sources, the results of the model selection procedure showed that the existence of seedlings was best predicted when the distance from a mature tree and the basal area of the mature tree in a natural forest were considered. In other words, Abies seedlings tend to exist near large mature trees in a plantation. Moreover, to select a suitable site for restoration, information on individual mature trees is indispensable for predicting the likelihood of seedling existence with high accuracy.

DOI： 10.4005/jjfs.89.407

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The relationship between the number of bark-stripped trees and understory vegetation was examined in cypress (Chamaecyparis obtusa) plantations in the Kuma region of Kumamoto Prefecture, Japan. First, the amount of understory vegetation was quantified by taking images using a digital camera. Using TWINSPAN, the 77 surveyed sites were classified into three vegetation types based on the species composition of the understory vegetation: Sasamorpha borealis, pioneer species, and evergreen-tree species. Then, we used the bootstrap method and examined whether there were fewer bark- stripped trees at the surveyed sites with much understory vegetation. The quantity of understory vegetation influenced the number of bark-stripped trees only in the evergreen-tree species category, which suggests that physical and visual shielding by understory vegetation is very useful for preventing bark-stripping.

DOI： 10.4005/jjfs.89.208

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.118.0.412.0

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DOI： 10.11519/jfsc.118.0.224.0

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DOI： 10.11519/jfsc.118.0.713.0

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DOI： 10.11519/jfsc.118.0.159.0

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DOI： 10.11519/jfsc.118.0.136.0

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Language：Japanese   Publisher：Japanese Forestry Society  

Seasonal variation in the spectra of bamboo, broadleaved forests, and coniferous forests was examined using multi-temporal SPOT/HRV and LANDSAT/TM data and ground-based spectral measurements. The satellite- and ground-based data revealed some common characteristics. In the visible red region, bamboo forests had the highest digital number and reflectance factor from April to June. In the near-infrared region, bamboo and broadleaved forests exchanged ranks from spring to summer. In the short-wavelength infrared region, bamboo forests had higher digital number than broadleaved and coniferous forests throughout the year. The three forest types showed significant differences in the near-infrared region from May to July and in the short-wavelength infrared region during the almost entire year. It is suggested that "leaf exchange" greatly affects seasonal variations in the spectra of bamboo forests.

DOI： 10.4005/jjfs.88.473

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Language：English   Publisher：Japan Society of Forest Planning  

This study confirmed the usefulness of short wavelength infrared (SWIR) in the discrimination and classification of evergreen forest types. A forested area near Hisayama and Sasaguri in Fukuoka Prefecture, Japan, served as the study area. Warm-temperate forest vegetation dominates the study site vegetation. Coniferous plantation forest, natural broad-leaved forest, and bamboo forest were analyzed using LANDSAT5/TM and SPOT4/HRVIR remote sensing data. Samples were extracted for the three forest types, and reflectance factors were compared for each band. Kappa coefficients of various band combinations were also compared by classification accuracy. For the LANDSAT5/TM data observed in April, October, and November, Bands 5 and 7 showed significant differences between bamboo, broad-leaved, and coniferous forests. The same significant difference was not recognized in the visible or near-infrared regions. Classification accuracy, determined by supervised classification, indicated distinct improvements in band combinations with SWIR, as compared to those without SWIR. Similar results were found for both LANDSAT5/TM and SPOT4/HRVIR data. This study identified obvious advantages in using SWIR data in forest-type discrimination and classification.

DOI： 10.20659/jfp.12.2_81

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

We analyzed the characteristics of 283 sites where sika deer caused bark-stripping damage in plantation forests in Kumamoto Prefecture, between 2000 and 2001. We developed four prediction models of the occurrence probability of bark-stripping damage using logistic regression. As independent variables, we used 16 factors, including topographic (elevation and slope angle), geographic (distance from the nearest road, <I>etc</I>.), vegetation (the number of cells used for forestry, agriculture, <I>etc</I>.), and stand (planted species and stand age) factors. The model with the lowest Akaike Information Criterion (AIC) and the greatest accuracy of classification showed that bark-stripping damage was strongly related to elevation, slope angle, and distance from the nearest road. The accuracy of the model was improved when the factors "planted species" and "stand age" were added. Finally, we drew a map showing the probability of bark-stripping damage. Such information should prove very useful in forest management planning.

DOI： 10.4005/jjfs.87.111

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Language：Japanese   Publisher：THE JAPANESE FORESTRY SOCIETY  

Multi-temporal aerial photos were processed into digital orthophotos to examine temporal range shifts of bamboo stands in relation to adjacent landcover. In both study areas, in Sasaguri and Tachibana, in Fukuoka Prefecture, Japan, the area of bamboo stands increased 1.3 to 1.7 times over about 30 years. Broadleaved forest occupied at least 40% of the area into which bamboo expanded. Areas of reduction of bamboo stands were also identified; the major cause was land alteration by humans. The bamboo invasion ratio was calculated as the ratio of the length of the adjacent edge initially to that after expansion in both study areas. The highest value was for grassy sites, followed by broadleaved forest. The bamboo front moved at about 1.11.6 m annually, and no difference among landcover types was found.

DOI： 10.4005/jjfs.87.402

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.116.0.74.0

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Language：English   Publisher：Japan Society of Forest Planning  

Since 1972, an experimental management system for Japanese oak (Quercus mongolica var. grosseserrata) has been studied in a natural Japanese oak forest, approximately 200ha in area, in the Kyushu University Forest in Hokkaido. The management system was based on the clearcutting system in tongue-shaped blocks surrounded by shelterbelts; rotation was 150 years. The silvicultural process in this management system was designed to produce high-quality timber. For 30 years between 1973 and 2002, the number of first-year oak seedling established by the silvicultural process averaged 55,000 per ha per year. For 30 years between 1972 and 2002, the area managed averaged 9.11 ha per year. For 30-years, the timber volume derived from thinning and final cutting averaged 198m^3 per year. The revenue obtained by selling this timber averaged 892,000 yen per year. The cost of silvicultural process averaged 557,000 yen per year, excluding the costs of staff and other factors owing to the Kyushu University Forest. Thus the average net revenue per year was 335,000 yen for the 30-years.

DOI： 10.20659/jfp.11.1_33

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.116.0.749.0

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：THE JAPANESE FORESTRY SOCIETY  

DOI： 10.11519/jfsc.116.0.758.0

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DOI： 10.11519/jfsc.116.0.748.0

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In vegetation remote sensing, classification accuracy cannot be fixed, due to seasonal variations in spectral reflectance characteristics. This study aims to clarify the seasonal variability of classification accuracy by forest-cover type. In particular, this paper describes seasonal variability by each band or band combinations. The study area is located in the vicinities of Hisayama and Sasaguri in Fukuoka Prefecture, Japan. Natural broadleaved, coniferous plantation, and bamboo forests were studied. Supervised classification was applied to six SPOT/HRV images taken in 1997. Kappa analysis was applied to assess the classification accuracy and compare any two error matrices. The results revealed that some single band or two-band combinations were as accurate as, or more accurate than, the full band (all three bands). The disadvantages of using a full band were especially apparent in the season with high classification accuracy. This study indicates that using all given bands does not necessarily result in the highest classification accuracy. This study also suggests that band selection within the scope of forest type and seasonal variability can contribute to better forest-cover-type classifications.

DOI： 10.1007/s10310-004-0075-1

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：日本森林学会  

1．はじめに&lt;BR&gt;近年，「森林原則声明」と「アジェンダ21」で示されているように，持続可能な森林経営の重要性が国際的に認識されている。わが国もヨーロッパ以外の温帯林と北方林諸国とで，モントリオールプロセスとして温帯林等の保全と持続可能な森林経営を評価するための基準・指標を合意した。わが国はこれまで森林簿のみを基礎とした森林資源の把握を行ってきたが，森林簿による森林情報からでは，この基準・指標に対応できない項目が多い。そこで1999年度からわが国でも森林資源モニタリング調査（以下モニタリング調査と記す）が行われることになった。&lt;BR&gt;現在九州のモニタリング調査点の内，スギ，ヒノキ人工林は多く，適正に人工林を管理することが重要になっている。今回，収量比数（Ry）を林分密度の指標としてとりあげ，民有林の密度管理図からRyを算出しその値により林分がどのような状態にあるかを把握し，適正な林分と判断できるものを抽出した。そ

DOI： 10.11519/jfs.115.0.P2076.0

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Language：Japanese   Publisher：Japan Society of Photogrammetry and Remote Sensing  

Minnaert correction method is one of the most appropriate models that correct topographic effects on remotely sensed data. However, the variations of the Minnaert constants have not been examined for any forest types. The purpose of this research was to investigate the extent of the variation of the Minnaert constant in three different forest types. Three forest types were selected for the analysis ; broad-leaved natural forest, coniferous plantations, and bamboo forest. 7 scenes of SPOT/HRV data observed in 1997 were selected and orthorectified with digital elevation models and digital topographic maps. The Minnaert constants were obtained through a regression analysis between solar incidence angles and the original satellite data. The results showed bands 1 and 2 indicated the seasonal variation of Minnaert constant, which had the peak in summer. In those bands, there were negative correlations between the solar zenith angles and the Minnaert constants. On the other hand, the band 3 indicated unclear variations in the Minnaert constants rather slight fluctuations. Then there was not significant correlation between the solar zenith angles and the Minnaert constants of the band 3. The results of this study suggested that visible band and near infrared one differ in the annual change pattern of the Minnaert constant.

DOI： 10.4287/jsprs.41.47

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Nine scenes of SPOT/HRV data obtained in eight different months in 1997 were evaluated for crop discrimination in the Saga Plains, Japan. All images were atmospherically corrected with the 6S code. Annual Normalized Difference Vegetation Index (NDVI) profiles were generated to characterize seasonal trends in six cropping systems (rice, rice-winter cereal, soybean, soybean-winter cereal, lotus, and rush). The dataset of this study showed the unique temporal change patterns of NDVI for each cropping system. Separability analyses determined optimal scene combinations for the highest accuracy in classifying the cropping systems. The scene combinations for the accurate classification of cropping systems were obtained from three separability measurements (Euclidean spectral distance, divergence, and Jeffries-Matsushita distance). Kappa statistics were applied to evaluate the classification accuracies. The four-scene combination that was derived from April, June, July and September classified the cropping systems almost as well as those combinations including more scenes. A colour composition technique applied to the three-scene combination that showed the highest separability also discriminated each cropping system. Based on these results, we can request observations during specific time intervals considering local crop calendars and environmental conditions.

DOI： 10.1080/01431160151144378

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DOI： 10.11440/rssj1981.21.330

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Forest Planning  

We calculated three topographical factors (effective relief, topographical exposure and slope-center angle) with the "Digital Map 50-m grid", a digital elevation model (DEM) published by the Geographical Survey Institute, Japan. The objectives of this study were to show new algorithms for the calculation of the topographical factors from DEM, and to evaluate their accuracy. We proposed new algorithms for the topographical exposure and the slope-center angle. Both topographical factors measured on topographical maps and calculated from DEM were compared. The Digital Map 50-m grid data were resampled by the cubic convolution interpolation. The root mean squared (RMS) error for the elevation value of the DEM was 7.15m and gave good agreement with the theoretical value (7.2m). The RMS error of the effective relief was 8.61m, the topographical exposure was 27.39 degrees, and the slope-center angle was 13.57 degrees. The correlations between the errors of elevation on DEM and the errors of each topographical factor were also examined. The errors of elevation on DEM correlated positively with the errors of the topographical exposure and the slope-center angle, and negatively with those of the effective relief.

DOI： 10.20659/jjfp.34.1_13

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DOI： 10.20659/jjfp.29.0_89

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Other Link： http://hdl.handle.net/10191/22574

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Other Link： http://hdl.handle.net/10191/22572

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Language：English   Publisher：Field Science Center, Graduate School of Agricultural Science, Tohoku University  

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The Minnaert constant of the Minnaert topographic correction method is based on a specific surface; however, few studies have examined how the Minnaert constant may vary with the observed scene. This study compared Minnaert constants derived from remote sensing data from three different forest types. A Minnaert constant for each forest type was computed using data for similar topographical conditions (i.e., slope angle and slope azimuth), and significant difference tests were performed. Minnaert constants from random sample data stratified only by topographical conditions without specifying a forest type were also obtained and had similar values. The study focused on a forested area in the Sangun mountainous region near Fukuoka, Japan. Data were obtained from seven scenes observed by the SPOT/HRV satellite in 1997. No significant differences were found among the Minnaert constants for the three forest types from the sample data with similar topographic conditions. The random topographic data also indicated no significant differences in the Minnaert constants for all scenes and bands. These results suggest that even if the sample set were changed, a stable Minnaert constant could be acquired by stratifying data based on topographical conditions.

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