Journal of the Japanese Agricultural Systems Society
Online ISSN : 2189-0560
Print ISSN : 0913-7548
ISSN-L : 0913-7548
Volume 27 , Issue 1
Showing 1-3 articles out of 3 articles from the selected issue
Contributed Paper
  • Hasan Muhammad ABDULLAH, Tsuyoshi AKIYAMA, Michio SHIBAYAMA, Yoshio AW ...
    2011 Volume 27 Issue 1 Pages 1-8
    Published: January 10, 2011
    Released: June 04, 2015
    Leaf Area Index (LAI) estimation of crops in cropland and non-crop vegetation in abandoned croplands is important to understand the contributions of crops and vegetation to primary productivity. We used a field spectra-based Normalized Difference Vegetation Index (NDVI) and sampled the LAI of crop and non-crop vegetations (CNCVs) including cultivated and abandoned croplands to develop a simple LAI estimation model. The measured LAI was significantly correlated with field-based NDVI (R2=0.70, p<0.001). QuickBird (QB) imagery of 12 April and 23 May was used for agricultural land (AL) classification, and image obtained on 8 July 2007, was used to validate the field-based LAI estimation model and LAI mapping. Four classes including paddy, corn, abandoned cropland and poly house were classified by the ISODATA clustering technique. Overall accuracy of the classification was 94% with Kappa statistics of 0.92. The final classified image was used to produce a LAI distribution map of CNCVs. The LAI estimation model was evaluated by incorporating it into the July QB image to obtain the observed LAI. The relationship between field-measured and QB-observed LAI appeared to be linear (R2=0.70). Finally, a field-based LAI estimation model was applied to the July QB NDVI image in the area of paddy, corn and abandoned cropland. The LAI map gives us information regarding the status of LAI in CNCVs ranged between <1 to >4. In the LAI map, LAI appeared to be higher in the abandoned croplands than in the croplands. Our LAI maps gave satisfactory estimates of the LAI in each land type. Thus, models using field-spectra based NDVI and sampled LAI could be applied to QB images for remote estimation and mapping of LAI.
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  • Hiroyuki IMURA, Hiroyuki SASAKI, Kun SHI, Nobuo MORIMOTO
    2011 Volume 27 Issue 1 Pages 9-20
    Published: January 10, 2011
    Released: June 04, 2015
    To conserve pasture dung beetles that feed and decompose animal dung and utilize their beneficial ecosystem functions for sustainable livestock production, we surveyed scarabaeoid dung beetles and predicted the landscape conditions of pastures favorable for rich dung beetle diversity by analyzing surrounding landscape of the pastures. We collected dung beetles monthly during the grazing period (May - October) from 1999 to 2001 on 18 pastures in the north-eastern part of Tochigi prefecture using dung-baited traps. We chose 10 major landscape elements (broad-leaved deciduous forest, coniferous forest, artificial forest, shrub land, grassland, paddy field, crop field, pasture, urban area, and water area) that possibly cause dung beetle habitation from the GIS data (5th ed., Ministry of Environment) and calculated the fractal dimension of each element in 4 km square area around the survey points by the box-counting method. In total, 49,577 individuals form 25 species belonging to Geotrupinae, Scarabaeinae and Aphodiinae were caught. Except for the forest specialists of Phelotrupes laevistriatus, Copris acutidens and Onthophagus nitidus, the species were those inhabiting grasslands, or both grasslands and forests. Species richness varied from 7 to 17 across the pastures. By stepwise multiple regression analysis setting species richness as dependent variable and fractal dimensions of the landscape elements as independent variables, we obtained a prediction model explained by fractal dimensions of broad-leaved deciduous forest and pasture having a positive coefficient and that of artificial forest having negative coefficient. Based on the model, we drew a contour map that predicts species richness of dung beetles in this area.
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  • Satoshi ASANO, Kei MIZUNO, Shintaro KOBAYASHI
    2011 Volume 27 Issue 1 Pages 21-29
    Published: January 10, 2011
    Released: June 04, 2015
    This paper examines and discusses on impacts and changes on swidden agriculture caused by forest policies in Champasack province, Lao PDR. The Lao government has regulated swidden agriculture for protecting forests for more than 20 years.In 1980s, provincial agriculture and forestry office (PAFO) encouraged villagers to own teak plantation in our study site, and some villagers accepted this. PAFO introduced land tax exemption for teak plantation larger than 1 ha, and imposed the tariff not on foresters but on firms when they export teak timbers. These actions made teak plantation popular among villagers.In 1993, the government established “National Biodiversity Conservation Area” (NBCA), for the preservation of forest ecosystem and biodiversity. 20 NBCAs were put in national land, three of which were in Champasack province.NBCA affected the village in our study site to make a rule about logging among villagers. The rule banned logging for business and opening lands adjacent to water source.In 1996, a concrete policy of “Land Forest Allocation” (LFA) was launched following Forestry Law. The law classified the nation's forests into 5 types and encouraged forest utilization by rural inhabitants. LFA aimed implementation of the law and poverty reduction by distribution of farm lands to those who doesn't have enough.In Champasack province, however, the goal was not achieved. Swidden agriculture continues nowadays and forests are opened continuously. The cause of failure was mismatch of policies between national level and provincial level. As the results of teak forests extension in village forests, they had lack of fallows in which they would open next land for swidden agriculture. Teak plantation required more than 20 years before foresters obtained the benefits. Incomplete policies impacted land use patterns and crop calendar of swidden agriculture in this area.
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