20 research outputs found
Mangrove Forest Restoration by Fisheries Communities in Lampung Bay: A study based on perceptions, willingness to pay, and management strategy
Mangroves provide benefits and various services to local communities living along coastal areas, particularly fishery communities. Fishery community perceptions are significant in determining attitudes towards improving mangrove conditions, which can also be addressed through restoration activities. This research was conducted to analyze fisheries communities perceptions, willingness to pay (WTP) for mangroves restoration, and mangrove forest management strategies. Field surveys were conducted from July-August 2019 and February-March 2020. Primary data were collected from respondents in four regions (Kalianda Regency, South Lampung Regency, Bandar Lampung City, and Pesawaran Regency) in Lampung Province, Indonesia, which consist of fishers, shrimp farmers, crab and wood seekers, and finfish farmers. The respondents were 193 people, and four experts were involved in the policy scenario analysis. Results revealed a gap in the value of WTP among fishery community groups, in which the average value for fishers is lower than shrimp farmers. The years of formal education significantly influenced the WTP for mangrove restoration. Based on the scenario analysis, scenario 01 become a priority strategy, where four policies (P1 = Mangrove ecotourism development in Lampung Bay; P2 = Mangrove knowledge education and training on processing mangrove based products; P3 = Restoration and conservation of mangrove forests; and P4 = Community-based management for mangrove forests utilization) show high likelihoods to be simultaneously implemented for mangroves management, with mangrove ecotourism policy as the most decisive policy. For future research, other explanatory variables can be added, such as information on family member characteristics, and to develop a bottom-up policy scenario by identifying and involving the role of the local community
スイトウ ホジョウ ブンルイ ノ タメノ ジケイレツ MODIS NDVI ニ タイスル Wavelet ヘンカン ノ オウヨウ
本報は,MODIS(Moderate Resolution Imaging Spectroradiometer)センサから取得された画像データより得られる正規化植生指数(NDVI)に対し,Wavelet 変換による時間周波数応答解析を適用し水稲圃場を分類するアルゴリズムを提案する。NDVI の波形から計算される Wavelet パワーは,水稲作期に対応しており,水稲圃場の特徴抽出に利用できる。そこで,Wavelet パワーの値により水稲圃場の特徴を決定した後,NDVIの統計情報とWaveletパワーを組み合わせた線形判別分析を行い,判別関数の値から自動的に土地利用分類を行う手法を提案する。本研究では,ベトナム南部のメコンデルタ地域を解析対象とする。本報では,250 m 解像度の10日間コンポジット画像から作成された,2009年 1月から 2011年 12月までの 3ヶ年の NDVI データを使用し解析を実施した。解析結果から,MODIS センサのような空間的に低解像度の衛星画像データを使用した場合であっても,NDVI の Wavelet パワーと基本統計量の組み合わせによる線形判別分析が,水稲圃場分類において効果的である事が確認できた。さらに,水稲圃場分類に必要な NDVI データの解析開始時期を播種期に一致させて計算することで,最も妥当な分類結果が得られることが判明した。しかし,現地の正確な土地利用データが不在であることから,提案手法の精度検証が今後の課題として残った。An algorithm for the classification of paddy area was proposed by utilizing wavelet transform as time frequency analysis of Normalized Difference Vegetation Index (NDVI) data series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The calculated wavelet powers of the NDVI wave correspond to the rice cropping calendar, and were used to obtain the characteristics of paddy area. After determining features of the paddy area, Linear Discriminant Analysis (LDA) is assessed for land-use classification using statistical values of NDVI data series and calculated wavelet powers. This research was conducted in the Mekong Delta, southern Vietnam. Three years, NDVI data series (January 2009 up to December 2011) of 10-day composite images with 250 m spatial resolution were applied. The result shows that the combination of wavelet powers and statistical values of NDVI data for LDA worked well for the classification, even when low resolution satellite images like MODIS were used. Furthermore, paddy classification can obtain the most appropriate result if the starting point of the calculation is adjusted to the rice planting period. However, verification of accuracy has not yet been done due to lack of the latest land-use data of the study area, and still remains as a future subject
ショクセイシスウ ノ ジカンシュウハスウオウトウカイセキ ニ ヨル スイトウホジョウチュウシュツ ニ カンスル ケンキュウ
本研究では,衛星リモートセンシングより得られる正規化植生指数(NDVI)を時系列に整備し,NDVI波形を一次元離散ウェーブレット変換により時間周波数応答解析し,ウェーブレットパワーをはじめとする各種パラメータを用いた線形判別関数を導出することで,土地利用分類を自動的に行うための手法を提案する。特に,水稲の生育状況変化に対応した波形特徴を抽出し,水稲作付面積を自動的に推定する手法を提案する。解析対象地域は,ベトナム南部メコンデルタ地域とする。本論では,SPOT衛星により取得された1998年6月から4年間の時系列NDVIデータを用いて行った解析結果について報告する。検討結果から,提案手法による水稲圃場分類は1年間程度の時系列NDVIデータで実施可能であることが示されるなどの成果が得られたが,比較のための現地データが不在であることから,提案手法の精度検証が課題として残った。This paper presents an algorithm for the classification of paddy fields based on the timefrequency analysis of the series of Normalized Difference Vegetation Index (NDVI) obtained by remote sensing. The discrete wavelet transform is selected as the method for time-frequency analysis and the calculated wavelet powers of the waves of NDVI are used for extraction of characteristics of paddy fields corresponding to the calendar of rice cropping. The wavelet powers and statistical data of NDVI are used for the parameters of the linear discrimination functions for the automatic classification. The analytical area for this study is Mekong delta, in the southern part of Vietnam. In this paper, the authors discuss the classification results using the four years NDVI data from June 1998 observed by the earth observation satellite SPOT. The results show that the present method can well classify paddy fields as well as being applied to almost one year NDVI data. However the verification of accuracy of the present method has not yet been carried out because of the lack of accurate land use data of the target area, so this is a future subject for study
ショクセイシスウ ノ ジカンシュウハスウオウトウカイセキ ニ ヨル スイトウホジョウチュウシュツ ニ カンスル ケンキュウ
本研究では,衛星リモートセンシングより得られる正規化植生指数(NDVI)を時系列に整備し,NDVI波形を一次元離散ウェーブレット変換により時間周波数応答解析し,ウェーブレットパワーをはじめとする各種パラメータを用いた線形判別関数を導出することで,土地利用分類を自動的に行うための手法を提案する。特に,水稲の生育状況変化に対応した波形特徴を抽出し,水稲作付面積を自動的に推定する手法を提案する。解析対象地域は,ベトナム南部メコンデルタ地域とする。本論では,SPOT衛星により取得された1998年6月から4年間の時系列NDVIデータを用いて行った解析結果について報告する。検討結果から,提案手法による水稲圃場分類は1年間程度の時系列NDVIデータで実施可能であることが示されるなどの成果が得られたが,比較のための現地データが不在であることから,提案手法の精度検証が課題として残った。This paper presents an algorithm for the classification of paddy fields based on the timefrequency analysis of the series of Normalized Difference Vegetation Index (NDVI) obtained by remote sensing. The discrete wavelet transform is selected as the method for time-frequency analysis and the calculated wavelet powers of the waves of NDVI are used for extraction of characteristics of paddy fields corresponding to the calendar of rice cropping. The wavelet powers and statistical data of NDVI are used for the parameters of the linear discrimination functions for the automatic classification. The analytical area for this study is Mekong delta, in the southern part of Vietnam. In this paper, the authors discuss the classification results using the four years NDVI data from June 1998 observed by the earth observation satellite SPOT. The results show that the present method can well classify paddy fields as well as being applied to almost one year NDVI data. However the verification of accuracy of the present method has not yet been carried out because of the lack of accurate land use data of the target area, so this is a future subject for study
Broiler-house environment monitoring system using sensor network and mail delivery system
ショクヒンチョウキカイジョウユソウ ノ タメ ノ コンテナナイブジョウキョウリアルタイムカンシシステム ノ カイハツジレイ
コンテナを用いた食品の長期海上輸送では,不適切な空調により食料品に荷傷みが発生したとしても発生状況の特定が困難であり,責任の所在が不明確な場合が多く,トレーサビリティや食の安全に関わる問題を有している。そこで本研究では,センサネットワーク技術を用いたリアルタイム温湿度計測システムを開発し,コンテナによる長期海上輸送における空調状況を衛星通信とインターネット経由で監視する簡易技術を開発した。このシステムを実際のコンテナに搭載し,2008年11∼12月の期間,東京·ドバイ航路にて実証実験を行った。その結果,シンガポール港における積み替え時においてコンテナ内部の異常な温湿度上昇を検知するなど,提案するシステムが異常検知に効果的であることが確認できた。しかし,イリジウム衛星によるデータ通信では通信エラーが連続して発生する場合もあり,対策が必要なことを確認した。Since the immediate detection of the damage to foods due to inadequate control of air condition in container is not an easy task and responsibility for any trouble is usually unclear, the transportation of agricultural products overseas from Japan is known to have problems concerned with traceability and food security. In order to find a solution to this problem, the authors have developed a real-time monitoring system of internal air conditions of container through satellite communication and the Internet using sensor network technologies for long-term marine transport of agricultural products. In this paper, we report on the experiment of marine transportation to Dubai from Tokyo in the period of November to December, 2008. Throughout the experiment, it is validated that the present system is one of the most cost-effective real-time monitoring systems and the system could successfully detect a rapid change of temperature and humidity of the container in transshipment at Singapore Port. However, a series of data communication errors often occurred and it was understood that improvement in establishing stable data communication by Iridium satellite must be one of the important future subjects of this study
SPATIOTEMPORAL ANALYSIS OF SMALL SCALE GREENHOUSE MICROCLIMATE BASED ON SMART AGRICULTURE SYSTEM
There is a need for high cutting-edge technological ICT application in agriculturein order to embark on the current decline in agriculture labor force in Japan.However, few small-scale farmers are able or willing to risk significant capital onsensing technologies. There is a challenge in horticultural greenhouse farming toprovide a well-controlled microclimate environment to meet well-developed cropswith high yield and quality crop production while using fewer resources. In thisstudy, a cost-effective simplified smart agriculture system was developed anddeployed in small-scale tomato greenhouse farming in Nara, Japan. The systemreal-time information capability is used for monitoring crop environment for propercrop management. A spatiotemporal analysis was done to assess variations andunderstand the underlying microclimate conditions in the partitioned tomatogreenhouse (blocks). Crop production is done all year around (An average of 2.5times cropping cycle per one greenhouse block). Spatiotemporal analysis andstatistical analysis results show well-defined micro-climate control strategies thatcould relatively be used in greenhouse facility management to enhance cropcultivation while using less energy resource that is relatively cost-effective. Thereliability of the system data makes it efficient and consequently it could be usedfor accurate crop production planning, improvement in cultivation managementand support in decision-making regarding cultivation activities