空撮画像解析と隠れマルコフモデルによるクズ (Pueraria lobata (Willd.) Ohwi) の空間動態の評価
無人航空機（UAV）画像に基づく雑草群落の空間動態のモデリングは、時間的・空間的に高い解像度で拡大の過程を評価するのに有用である。隠れマルコフモデルは対象に応じて柔軟に改変でき、誤分類の確率を明示的に組み込むことができるため、占有範囲の遷移を記述するのに適している。本研究は、空撮画像分類とサイト占有モデルによってクズの空間動態のパラメータを推定し、刈り払い後の拡大を評価することを目的とした。河川敷のクズ群落のUAV画像を取得し、教師あり分類によりグリッド（0.25 m2）ごとクズの占有状態を判別した。階層モデルは、分類の不確実性を表すモデルと各グリッドの占有状態の遷移を表すモデルで構成した。パ...
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| Published in | システム農学 Vol. 40; no. 3; pp. 33 - 44 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English Japanese |
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システム農学会
25.11.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0913-7548 2189-0560 |
| DOI | 10.14962/jass.40.3_33 |
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| Abstract | 無人航空機（UAV）画像に基づく雑草群落の空間動態のモデリングは、時間的・空間的に高い解像度で拡大の過程を評価するのに有用である。隠れマルコフモデルは対象に応じて柔軟に改変でき、誤分類の確率を明示的に組み込むことができるため、占有範囲の遷移を記述するのに適している。本研究は、空撮画像分類とサイト占有モデルによってクズの空間動態のパラメータを推定し、刈り払い後の拡大を評価することを目的とした。河川敷のクズ群落のUAV画像を取得し、教師あり分類によりグリッド（0.25 m2）ごとクズの占有状態を判別した。階層モデルは、分類の不確実性を表すモデルと各グリッドの占有状態の遷移を表すモデルで構成した。パラメータの事後分布をマルコフ連鎖モンテカルロ(MCMC)法で推定したところ、拡大速度は7月の刈り払い後が8月の刈り払い後よりも高かった。この結果は、8月以降の刈り払い後の占有範囲の回復は比較的緩やかであることを示唆した。画像解析と階層的モデリングの組み合わせにより、管理スケールでの雑草の空間動態をシミュレートし、広範囲にわたる侵入雑草の影響を減らすために管理を最適化することができると考えられる。 |
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| AbstractList | 無人航空機（UAV）画像に基づく雑草群落の空間動態のモデリングは、時間的・空間的に高い解像度で拡大の過程を評価するのに有用である。隠れマルコフモデルは対象に応じて柔軟に改変でき、誤分類の確率を明示的に組み込むことができるため、占有範囲の遷移を記述するのに適している。本研究は、空撮画像分類とサイト占有モデルによってクズの空間動態のパラメータを推定し、刈り払い後の拡大を評価することを目的とした。河川敷のクズ群落のUAV画像を取得し、教師あり分類によりグリッド（0.25 m2）ごとクズの占有状態を判別した。階層モデルは、分類の不確実性を表すモデルと各グリッドの占有状態の遷移を表すモデルで構成した。パラメータの事後分布をマルコフ連鎖モンテカルロ(MCMC)法で推定したところ、拡大速度は7月の刈り払い後が8月の刈り払い後よりも高かった。この結果は、8月以降の刈り払い後の占有範囲の回復は比較的緩やかであることを示唆した。画像解析と階層的モデリングの組み合わせにより、管理スケールでの雑草の空間動態をシミュレートし、広範囲にわたる侵入雑草の影響を減らすために管理を最適化することができると考えられる。 |
| Author | 岩本, 啓己 渡邉, 修 安田, 泰輔 |
| Author_xml | – sequence: 1 fullname: 岩本, 啓己 organization: 信州大学大学院総合工学系研究科 – sequence: 1 fullname: 安田, 泰輔 organization: 山梨県富士山科学研究所 – sequence: 1 fullname: 渡邉, 修 organization: 信州大学農学部 |
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| References | Pagel, J. and Schurr, F. M., 2012, Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics. Global Ecology and Biogeography, Vol. 21, pp. 293-304. https://doi.org/10.1111/j.1466-8238.2011.00663.x Tsugawa, H. and Kayama, R., 1981, Studies on dry matter production and leaf area expansion of kudzu vines (Pueraria lobata Ohwi) II. The difference in dry matter and leaf area productivity between the main stem and the branches of the current year’s stem. Journal of Japanese Grassland Science, Vol. 27, pp. 272-276. https://doi.org/10.14941/grass.27.272 Stolen, E. D., Oddy, D. M., Gann, S. L., Holloway-Adkins, K. G., Legare, S. A., Weiss, S. K., and Breininger, D. R., 2019, Accounting for heterogeneity in false-positive detection rate in southeastern beach mouse habitat occupancy models. Ecosphere, Vol. 10, e02893. https://doi.org/10.1002/ecs2.2893 Miller, J. H. and Edwards, B., 1983, Kudzu: where did it come from? And how can we stop it? Southern Journal of Applied Forestry, Vol. 7, pp. 165-169. https://doi.org/10.1093/sjaf/7.3.165 Gimenez, O., Blanc, L., Besnard, A., Pradel, R., Doherty, P.F.J., Marboutin, E. and Choquet, R., 2014, Fitting occupancy models with E-SURGE: hidden Markov modelling of presence - absence data. Methods in Ecology and Evolution, Vol. 5, pp. 592 - 597. https://doi.org/10.1111/2041-210X.12191 Su, Y. and Yajima, M., 2015, R2jags: Using R to Run 'JAGS'. R package version 0.5-7. https://CRAN.R-project.org/package=R2jags Plummer, M., 2003, JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Proceedings of the 3rd international workshop on distributed statistical computing, Vol. 124, 125. Asada, M., Osada, Y., Fukasawa, K. and Ochiai, K., 2014, Bayesian estimation of reeves’ muntjac (Muntiacus reevesi) populations using state-space models. Mammalian Science, Vol. 54, pp. 53-72. https://doi.org/10.11238/mammalianscience.54.53 Forseth, J. I. N. and Innis, A. F., 2004, Kudzu (Pueraria montana): History, physiology, and ecology combine to make a major ecosystem threat. Critical Reviews in Plant Sciences, Vol. 23, pp. 401-413. https://doi.org/10.1080/07352680490505150 Denwood, M. J., 2016, runjags: An R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS. Journal of Statistical Software, Vol. 71, pp. 1–25. Tsugawa, H., Sasek, T. W., Tange, M. and Nishikawa, K., 1987, Studies on dry matter production and leaf area expansion of kudzu vines (Pueraria lobata Ohwi) III. The emergence of current year’s stems from overwintering stems. Journal of Japanese Grassland Science, Vol. 32, pp. 337-347. https://doi.org/10.14941/grass.32.337 Nishino, A., Maebara, Y., Hasimoto, K., Uchida, T. and Hayasaka, D., 2019, Search for the eradication techniques on the noxious liana kudzu (Pueraria lobata (Willd.) Ohwi) in consideration of cut-slope vegetation recovery. Journal of Japanese Society Revegetation Technology, Vol. 44, pp. 596-605. https://doi.org/10.7211/jjsrt.44.596 Komuro, T. and Koike, F., 2005, Colonization by woody plants in fragmented habitats of a suburban landscape. Ecologocal Applications, Vol. 15, pp. 662-673. https://doi.org/10.1890/03-5232 R Core Team, 2019, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.r-project.org/ (2024.8.29. access comfirmed) Gelman, A. and Rubin, D. B., 1992, Inference from iterative simulation using multiple sequences. Statistical Science, Vol. 7, pp. 457-472. https://doi.org/10.1214/ss/1177011136 Tanaka, J., Horie, N. and Hayakawa, N., 2009, The test of get rid of invaded Pueraria lobata (Willd.) Ohwi at slope planting (II): Two years after. Journal of the Japanese Society of Revegetation Technology, Vol. 35, pp. 170-173. https://doi.org/10.7211/jjsrt.35.170 Fukaya, K., 2016, Dynamic site occupancy models: statistical inference of site occupancy dynamics accounting for state uncertainty. Proceedings of the Institute of Statistical Mathematics, Vol. 64, pp. 3-22. Arase, T., Suzuki, A. and Maruyama, J., 2002, Growth and seed yield of Amphicarpaea edgeworthii Benth. in a field cropping. Japanese Journal of Crop Science, Vol. 71, pp. 84-90. https://doi.org/10.1626/jcs.71.84 Tanaka, J., Horie, N. and Hayakawa, N., 2008, The test of get rid of invaded Pueraria lobata (Willd.) Ohwi at slope planting. Journal of the Japanese Society of Revegetation Technology, Vol. 34, pp. 215-218. https://doi.org/10.7211/jjsrt.34.215 Iwamoto, H. and Watanabe, O., 2021, Estimation of leaf area index based on spectral reflectance and its application to the evaluation of the spatial distribution of a kudzu-dominated community. Journal of Weed Science and Technology, Vol. 66, pp. 133-140. https://doi.org/10.3719/weed.66.133 Iwamoto, H. and Watanabe, O., 2020, Detection and spatial occupancy evaluation of kudzu community based on supervised classification of UAV imagery. Journal of Weed Science and Technology, Vol. 65, pp. 95-102. https://doi.org/10.3719/weed.65.95 Lamiter, A. M., Wu, S., Gelfand, A. E. and Silander Jr., J. A., 2006, Building statistical models to analyze species distributions. Ecological Applications, Vol. 16, pp. 33-50. https://doi.org/10.1890/04-0609 Aurambout, J. P. and Endress, A. G., 2018, A model to simulate the spread and management cost of kudzu (Pueraria montana var. lobata) at landscape scale. Ecological Informatics, Vol. 43, pp. 146-156. https://doi.org/10.1016/j.ecoinf.2017.12.004 Hughes, M. J., Johnson, E. G. and Armsworth, P. R., 2014, Optimal spatial management of an invasive plant using a model with above- and below-ground components. Biological Invasions, Vol. 16, pp. 1009-1020. https://doi.org/10.1007/s10530-013-0553-5 McClintock, B. T., Langrock, R., Gimenez, O., Cam, E., Borchers, D. L., Glennie, R. and Patterson, T. A., 2020, Uncovering ecological state dynamics with hidden Markov models. Ecological Letters 23, pp. 1878-1903. https://doi.org/10.1111/ele.13610 Rashid, Md. H., Uddin, Md. N., Asaeda, T. and Robinson, R. W., 2017, Seasonal variations of carbohydrates in Pueraria lobata related to growth and phenology. Weed Biology and Management, Vol. 17, pp. 103-111. https://doi.org/10.1111/wbm.12124 Louvrier, J., Chambert, T. Marboutin, E. and Gimenez, O., 2018, Accounting for misidentification and heterogeneity in occupancy studies using hidden Markov models. Ecological modelling, Vol. 387, pp. 61-69. https://doi.org/10.1016/j.ecolmodel.2018.09.002 Karatzoglou, A., Smola, A., Hornik, K. and Zeileis, A., 2004, kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software, Vol. 11(9), pp. 1–20. Muranaka, T. and Washitani, I., 2003, The population expansion predicted by a simulation model of an invasive alien species, Eragrostis curvula, in a middle-reach floodplain. Japanese Journal of Conservation Ecology, Vol. 8, pp. 51-62. https://doi.org/10.18960/hozen.8.1_51 Hoffberg, S. L., Mauricio, R. and Hall, R. J., 2018, Control or re-treat? Model-based guidelines for managing established plant invasions. Biological Invasions, Vol. 20, pp. 1387-1402. https://doi.org/10.1007/s10530-017-1632-9 |
| References_xml | – reference: Muranaka, T. and Washitani, I., 2003, The population expansion predicted by a simulation model of an invasive alien species, Eragrostis curvula, in a middle-reach floodplain. Japanese Journal of Conservation Ecology, Vol. 8, pp. 51-62. https://doi.org/10.18960/hozen.8.1_51 – reference: Su, Y. and Yajima, M., 2015, R2jags: Using R to Run 'JAGS'. R package version 0.5-7. https://CRAN.R-project.org/package=R2jags – reference: Tanaka, J., Horie, N. and Hayakawa, N., 2009, The test of get rid of invaded Pueraria lobata (Willd.) Ohwi at slope planting (II): Two years after. Journal of the Japanese Society of Revegetation Technology, Vol. 35, pp. 170-173. https://doi.org/10.7211/jjsrt.35.170 – reference: Tsugawa, H. and Kayama, R., 1981, Studies on dry matter production and leaf area expansion of kudzu vines (Pueraria lobata Ohwi) II. The difference in dry matter and leaf area productivity between the main stem and the branches of the current year’s stem. Journal of Japanese Grassland Science, Vol. 27, pp. 272-276. https://doi.org/10.14941/grass.27.272 – reference: Lamiter, A. M., Wu, S., Gelfand, A. E. and Silander Jr., J. A., 2006, Building statistical models to analyze species distributions. Ecological Applications, Vol. 16, pp. 33-50. https://doi.org/10.1890/04-0609 – reference: Arase, T., Suzuki, A. and Maruyama, J., 2002, Growth and seed yield of Amphicarpaea edgeworthii Benth. in a field cropping. Japanese Journal of Crop Science, Vol. 71, pp. 84-90. https://doi.org/10.1626/jcs.71.84 – reference: Rashid, Md. H., Uddin, Md. N., Asaeda, T. and Robinson, R. W., 2017, Seasonal variations of carbohydrates in Pueraria lobata related to growth and phenology. Weed Biology and Management, Vol. 17, pp. 103-111. https://doi.org/10.1111/wbm.12124 – reference: Asada, M., Osada, Y., Fukasawa, K. and Ochiai, K., 2014, Bayesian estimation of reeves’ muntjac (Muntiacus reevesi) populations using state-space models. Mammalian Science, Vol. 54, pp. 53-72. https://doi.org/10.11238/mammalianscience.54.53 – reference: Gimenez, O., Blanc, L., Besnard, A., Pradel, R., Doherty, P.F.J., Marboutin, E. and Choquet, R., 2014, Fitting occupancy models with E-SURGE: hidden Markov modelling of presence - absence data. Methods in Ecology and Evolution, Vol. 5, pp. 592 - 597. https://doi.org/10.1111/2041-210X.12191 – reference: Plummer, M., 2003, JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Proceedings of the 3rd international workshop on distributed statistical computing, Vol. 124, 125. – reference: Tsugawa, H., Sasek, T. W., Tange, M. and Nishikawa, K., 1987, Studies on dry matter production and leaf area expansion of kudzu vines (Pueraria lobata Ohwi) III. The emergence of current year’s stems from overwintering stems. Journal of Japanese Grassland Science, Vol. 32, pp. 337-347. https://doi.org/10.14941/grass.32.337 – reference: Iwamoto, H. and Watanabe, O., 2020, Detection and spatial occupancy evaluation of kudzu community based on supervised classification of UAV imagery. Journal of Weed Science and Technology, Vol. 65, pp. 95-102. https://doi.org/10.3719/weed.65.95 – reference: Denwood, M. J., 2016, runjags: An R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS. Journal of Statistical Software, Vol. 71, pp. 1–25. – reference: Iwamoto, H. and Watanabe, O., 2021, Estimation of leaf area index based on spectral reflectance and its application to the evaluation of the spatial distribution of a kudzu-dominated community. Journal of Weed Science and Technology, Vol. 66, pp. 133-140. https://doi.org/10.3719/weed.66.133 – reference: Karatzoglou, A., Smola, A., Hornik, K. and Zeileis, A., 2004, kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software, Vol. 11(9), pp. 1–20. – reference: McClintock, B. T., Langrock, R., Gimenez, O., Cam, E., Borchers, D. L., Glennie, R. and Patterson, T. A., 2020, Uncovering ecological state dynamics with hidden Markov models. Ecological Letters 23, pp. 1878-1903. https://doi.org/10.1111/ele.13610 – reference: Nishino, A., Maebara, Y., Hasimoto, K., Uchida, T. and Hayasaka, D., 2019, Search for the eradication techniques on the noxious liana kudzu (Pueraria lobata (Willd.) Ohwi) in consideration of cut-slope vegetation recovery. Journal of Japanese Society Revegetation Technology, Vol. 44, pp. 596-605. https://doi.org/10.7211/jjsrt.44.596 – reference: Louvrier, J., Chambert, T. Marboutin, E. and Gimenez, O., 2018, Accounting for misidentification and heterogeneity in occupancy studies using hidden Markov models. Ecological modelling, Vol. 387, pp. 61-69. https://doi.org/10.1016/j.ecolmodel.2018.09.002 – reference: Forseth, J. I. N. and Innis, A. F., 2004, Kudzu (Pueraria montana): History, physiology, and ecology combine to make a major ecosystem threat. Critical Reviews in Plant Sciences, Vol. 23, pp. 401-413. https://doi.org/10.1080/07352680490505150 – reference: Pagel, J. and Schurr, F. M., 2012, Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics. Global Ecology and Biogeography, Vol. 21, pp. 293-304. https://doi.org/10.1111/j.1466-8238.2011.00663.x – reference: Tanaka, J., Horie, N. and Hayakawa, N., 2008, The test of get rid of invaded Pueraria lobata (Willd.) Ohwi at slope planting. Journal of the Japanese Society of Revegetation Technology, Vol. 34, pp. 215-218. https://doi.org/10.7211/jjsrt.34.215 – reference: R Core Team, 2019, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.r-project.org/ (2024.8.29. access comfirmed) – reference: Aurambout, J. P. and Endress, A. G., 2018, A model to simulate the spread and management cost of kudzu (Pueraria montana var. lobata) at landscape scale. Ecological Informatics, Vol. 43, pp. 146-156. https://doi.org/10.1016/j.ecoinf.2017.12.004 – reference: Hughes, M. J., Johnson, E. G. and Armsworth, P. R., 2014, Optimal spatial management of an invasive plant using a model with above- and below-ground components. Biological Invasions, Vol. 16, pp. 1009-1020. https://doi.org/10.1007/s10530-013-0553-5 – reference: Fukaya, K., 2016, Dynamic site occupancy models: statistical inference of site occupancy dynamics accounting for state uncertainty. Proceedings of the Institute of Statistical Mathematics, Vol. 64, pp. 3-22. – reference: Gelman, A. and Rubin, D. B., 1992, Inference from iterative simulation using multiple sequences. Statistical Science, Vol. 7, pp. 457-472. https://doi.org/10.1214/ss/1177011136 – reference: Komuro, T. and Koike, F., 2005, Colonization by woody plants in fragmented habitats of a suburban landscape. Ecologocal Applications, Vol. 15, pp. 662-673. https://doi.org/10.1890/03-5232 – reference: Hoffberg, S. L., Mauricio, R. and Hall, R. J., 2018, Control or re-treat? Model-based guidelines for managing established plant invasions. Biological Invasions, Vol. 20, pp. 1387-1402. https://doi.org/10.1007/s10530-017-1632-9 – reference: Miller, J. H. and Edwards, B., 1983, Kudzu: where did it come from? And how can we stop it? Southern Journal of Applied Forestry, Vol. 7, pp. 165-169. https://doi.org/10.1093/sjaf/7.3.165 – reference: Stolen, E. D., Oddy, D. M., Gann, S. L., Holloway-Adkins, K. G., Legare, S. A., Weiss, S. K., and Breininger, D. R., 2019, Accounting for heterogeneity in false-positive detection rate in southeastern beach mouse habitat occupancy models. Ecosphere, Vol. 10, e02893. https://doi.org/10.1002/ecs2.2893 |
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| SubjectTerms | クズ サイト占有モデル リモートセンシング 教師あり判別 空間動態 隠れマルコフモデル |
| Title | 空撮画像解析と隠れマルコフモデルによるクズ (Pueraria lobata (Willd.) Ohwi) の空間動態の評価 |
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