A Study of the Numerical Analysis of ICT and Sensor Network Applications toward Sustainable Coastal Fishery

2015東京農業大

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

Usability and acceptance of crowd-based early warning of harmful algal blooms

Crowdsensing has become an alternative solution to physical sensors and apparatuses. Utilizing citizen science communities is undoubtedly a much cheaper solution. However, similar to other participatory-based applications, the willingness of community members to be actively involved is paramount to the success of implementation. This research investigated factors that affect the continual use intention of a crowd-based early warning system (CBEWS) to mitigate harmful algal blooms (HABs). This study applied the partial least square-structural equation modeling (PLS-SEM) using an augmented technology acceptance model (TAM). In addition to the native TAM variables, such as perceived ease of use and usefulness as well as attitude, other factors, including awareness, social influence, and reward, were also studied. Furthermore, the usability factor was examined, specifically using the System Usability Scale (SUS) score as a determinant. Results showed that usability positively affected the perceived ease of use. Moreover, perceived usefulness and awareness influenced users’ attitudes toward using CBEWS. Meanwhile, the reward had no significant effects on continual use intention