This paper examines and discusses issues concerning the smallholder teak forestry in taungya style in southern Laos. The Provincial department of Agriculture and Forestry of Champasack Province introduced teak forestry for two reasons; poverty reduction and reforestation. We have conducted surveys in a rural village which has typical features of population size and ethnic. Questionnaire survey and field survey with GPS were conducted to collect household-level information and to produce an accurate land-use map respectively. This paper focuses on effects on household income due to the introduction of the teak forestry, degree of compliance with land-use regulation, and difference of degree of dependence on natural resources between teak forest owners and forest-landless villagers.By analyzing household incomes, we revealed that teak forestry didn’t increase the owners’ income though expansion of teak forests without considering land-use regulation was obviously identified on the map of teak forests distribution.Furthermore villagers have continually depended on natural forests while they have engaged in teak forestry. Another style of livelihood based on many kinds of local resources might be required for sustainable developments.
Current vegetation surveys are mainly conducted through the visual observation of coverage and species. This method has the disadvantage that it is not quantitative or reproducible. The aim of this study was to develop an objective method to survey vegetation using ground images obtained in the field. The data used in this paper were obtained in August 2012 at the Tottori Sand Dunes. The data were divided into training data and test data. First, we selected training data from our dataset and applied texture analysis. Then, classification models were obtained by using the texture characters as variables. Variables used in the models were selected as follows: 1) variables highly correlated with other variables were excluded based on the Pearson product-moment correlation coefficient, 2) multinomial logistic regression analysis was conducted to obtain the best combination of variables for classification, and 3) the accuracy of the models was estimated by linear discriminant analysis using the best combination of variables. Estimation was performed based on three categories: plant and soil classification, class classification (i.e., distinction between monocotyledon and dicotyledon) and species classification. A comparison of the RGB combined model and the NIR single model was also conducted. In the plant and soil classification, the accuracy of the RGB model and the NIR model were 96% and 87%, respectively. While the soil recall rate of the NIR model was low (lower than 50%), the RGB model showed high rates in all categories. In the class classification, the accuracy of the RGB model and the NIR model were 86% and 74%, respectively. Although the NIR model showed low rates in some categories (i.e., the recall rate of monocotyledons was 28%), the RGB model showed a high rate in all categories (higher than 70%), which was similar to the plant and soil classification. In the species classification, both the RGB model and the NIR model showed low accuracy (RGB: 55%, NIR: 39%). The accuracy differed largely among species (0 - 95%) and many of the misclassifications occurred within the same class. These results demonstrate the potential of coverage estimation and plant classification using this method.
The policy term “Food Security” has been used since a worldwide food crises in early 1970s. In 1980s Japanese Government led the discussion on food security in the international organizations such as FAO. Food security became the main theme of the 1996 world food summit. The food security for Japan means maintain stable food supply both from domestic production and import under the declining trend of food self-sufficiency and deepening dependence on food import. Not only Japan but also European food importing countries are promoting domestic food production and preparing for controlling (rationing) national food demand in emergency case. Even food exporting countries such as the United States have legal system for a food shortage emergency. Securing food is the most important interest for people in developing countries especial in the least developed countries. Food security in the developing countries is closely linked with poverty eradication in recent years. Securing enough food supply against ever rising food demand in the world and overcoming food market price instability under the global warming trend, the 2011 G20 Cannes Summit decided to promote “the Group on Earth Observations led Initiative for GLOBAL AGRICULTURAL MONITORING (GEO-GLAM)”, which was an international network using remote sensing, to improve a prediction of agricultural production and a weather forecast. The whole world is eagerly waited for practical use of agricultural information system based on remote sensing.
Agricultural statistics or early warning information from satellite earth observations is useful tool for food security related decision-making. In cooperation with foreign and Japanese universities, research institutes and end-users, Japan AerospaceExploration Agency (JAXA) have been working on the application of earth observation data to food security area. A comprehensive crop monitoring system utilizing earth observation data consists of mainly three subsystems: (1) crop area mapping; (2) agro-weather and crop condition monitoring; and (3) yield and production estimation. We have already developed prototype systems for rice cultivation area mapping and agro-weather monitoring such as soil moisture or drought index. At present, some systems are used in end-user agencies for daily operations. In this paper, we introduce the international framework for global agriculture monitoring by earth observation data and prototype systems for agricultural monitoring developed by JAXA.