Toward efficient farm management with remote sensing technologies in lowland rice fields in Laos

• 資料種別: 図書
• タイトル: Toward efficient farm management with remote sensing technologies in lowland rice fields in Laos
• 著者・編者: Kawamura, Kensuke; Ikeura, Hiroshi; Matsumoto, Naruo; Asai, Hidetoshi; Phongchanmixay, Sengthong; Khanthavong, Phanthasin; Souvannasing, Soukasdachanh; Inthavong, Thavone
• 著者標目: Kawamura, Kensuke; Ikeura, Hiroshi; Matsumoto, Naruo; Asai, Hidetoshi; Phongchanmixay, Sengthong; Khanthavong, Phanthasin; Souvannasing, Soukasdachanh; Inthavong, Thavone
• 出版事項: Japan International Research Center for Agricultural Sciences
• 出版年月日等: 2020-03-19
• 出版年（W3CDTF）: 2020-03-19
• タイトル（掲載誌）: JIRCAS Working Report : Potential and Efficiency of Underused Agricultural and Fishery Resources in Laos
• 巻号年月日等（掲載誌）: 90
• 掲載巻: 90
• 掲載ページ: 15-22
• ISSN（掲載誌）: PISSN : 1341-710X
• 本文の言語コード: eng
• 空間的範囲: Laos; ラオス
• 対象利用者: 一般
• 一般注記: This paper reports our current activities in Laos for monitoring rice production with remote sensing technologies in lowland field toward efficient farm management at small farm scale (<1 km2) or local scale (village, <100 km2). At farm scale (Research 1), the grain yield of lowland rice was evaluated from field hyperspectral data of paddy fields during the reproductive stage to the ripening stage in conjunction with iterative stepwise elimination partial least squares (ISE-PLS) regression. At local scale (Research 2), we established a land infrastructure data set in a lowland rice field at Koudkher village combining with UAV images and geographic information system (GIS) in order to assess the potential yield and its environmental effects. In Research 1, the highest R2 values and the lowest root mean squared error of cross-validation (RMSECV) values were obtained from the ISEPLS model at the booting stage (R2 = 0.873, RMSECV = 22.903); the residual predictive deviation was >2.4. Selected hyperspectral (HS) wavebands in the ISE-PLS model were identified in the rededge (710–740 nm) and near-infrared (830 nm) regions. These results confirmed that the booting stage might be the best time for in-season rice grain assessment and that rice yield could be evaluated accurately from the HS sensing data via the ISE-PLS model. In Research 2, a GIS-based land infrastructure information dataset was established in rain-fed paddy field (Koudkher village) from UAV images and digital terrain model. Using the data set, Ikeura et al. (2019) assessed the relationship between rice yield and water/soil conditions in the rainfed rice fields in Koudkher village.
• DOI: 10.34556/0002000388
• 記録形式（IMT）: application/pdf
• 一次資料へのリンクURL: jircas_working_report90-_15-22 （fulltext）; https://jircas.repo.nii.ac.jp/record/2000388/files/jircas_working_report90-_15-22.pdf
• オンライン閲覧公開範囲: インターネット公開
• 掲載誌: DOI; https://doi.org/10.34556/0002000382
• 掲載誌（DOI）: 10.34556/0002000382
• 連携機関・データベース: 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）; https://irdb.nii.ac.jp
• 提供元機関・データベース: 国際農林水産業研究センター : 国際農研機関リポジトリ