XバンドおよびCバンドSARデータを併用した機械学習アルゴリズムによる作物分類の高精度化・効率化に関する検討
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| Published in | 写真測量とリモートセンシング Vol. 59; no. 6; pp. 259 - 274 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | Japanese |
| Published |
一般社団法人 日本写真測量学会
2020
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| Online Access | Get full text |
| ISSN | 0285-5844 1883-9061 |
| DOI | 10.4287/jsprs.59.259 |
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| Author | 谷, 宏 薗部, 礼 望月, 貫一郎 山谷, 祐貴 小林, 伸行 王, 秀峰 |
|---|---|
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| EndPage | 274 |
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| References | Cloude, S.R., Pottier, E., 1996. A review of target decomposition theorems in radar polarimetry. IEEE Transactions on Geoscience and Remote Sensing, 34(2), 498-518. 齋藤元也，石塚直樹，坂本利弘，2017．日本における農業リモートセンシング研究の軌跡．日本リモートセンシング学会誌，37(3)，193-203 Xu, J., Li, Z., Tian, B.S., Huang, L., Chen, Q., Fu, S.T., 2014. Polarimetric analysis of multi-temporal RADARSAT-2 SAR images for wheat monitoring and mapping. International Journal of Remote Sensing, 35(10), 3840-3858. NGA GEOnet Names Server, 2013. Earth Gravitational Model 2008 (EGM2008), United States. http://earth-info.nga.mil/GandG/wgs84/gravitymod/egm2008 (accessed 7 Mar. 2017) R Core Team, 2014. R : A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org (accessed 29 Jan. 2017) 高度情報通信ネットワーク社会推進戦略本部，2014．農業情報創成・流通促進戦略，http://www.kantei.go.jp/jp/singi/it2/kettei/pdf/senryakuzenbun_140603.pdf.（2020年３月22日確認） 山谷祐貴，谷 宏，王, 秀峰，薗部, 礼，小林伸行，望月貫一郎，野田 萌，2018．XバンドおよびCバンドSARデータを併用した機械学習アルゴリズムによる圃場の作物分類．写真測量とリモートセンシング，57(2)，78-83 Yamaguchi, Y., Moriyama, T., Ishido, M., Yamada, H., 2005. Four-component scattering model for polarimetric SAR image decomposition. IEEE Transactions on Geoscience and Remote Sensing, 43(8), 1699-1706. Immitzer, M., Vuolo, F., Atzberger, C., 2016. First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe. Remote Sensing, 8(3). Congalton, R.G., Green, K., 2008. Assessing the accuracy of remotely sensed data : Principles and practices. CRC Press, Boca Raton, Florida, United States, 137. Hartfield, K.A., Marsh, S.E., Kirk, C.D., Carriere, Y., 2013. Contemporary and historical classification of crop types in Arizona. International Journal of Remote Sensing, 34(17), 6024-6036. 山谷祐貴，薗部, 礼，谷 宏，王, 秀峰，小林伸行，望月貫一郎，2017a．TerraSAR-Xデータを使用したランダムフォレストによる作付作物の分類．北海道大学農学部紀要，34(2)，１-11 Cloude, S.R., 2007. The dual-polarization entropy/alpha decomposition : a pulsar case study. Proc. POLInSAR, Frascati, Italy, 1-6. 石塚直樹，大内和夫，2017．合成開口レーダの農業への応用．日本リモートセンシング学会誌，37(3)，182-192 Zhao, L.L., Yang, J., Li, P.X., Zhang, L.P., 2014. Characteristics Analysis and Classification of Crop Harvest Patterns by Exploiting High-Frequency Multi Polarization SAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(9), 3773-3783. Breiman, L., 2001. Random forests. Machine Learning, 45(1), 5-32. MDA, 2004. RADARSAT-1 Data Products Specifications, Canada. http://gs.mdacorporation.com/includes/documents/R1_PROD_SPEC.pdf (accessed 6 Jun. 2016) Blaes, X., Vanhalle, L., Defourny, P., 2005. Efficiency of crop identification based on optical and SAR image time series. Remote Sensing of Environment, 96(3-4), 352-365. Jiao, X.F., Kovacs, J.M., Shang, J.L., McNairn, H., Walters, D., Ma, B.L., Geng, X.Y., 2014. Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data. ISPRS Journal of Photogrammetry and Remote Sensing, 96, 38-46. Sonobe R., Tani H., Wang X., Kobayashi N., Shimamura H., 2014. Random forest classification of crop type using multi-temporal TerraSAR-X dual-polarimetric data. Remote Sensing Letters, 5(2), 157-164. 野口 伸，2016．ICT農業とリモートセンシング．日本ロボット学会誌，34(2)，100-102 山谷祐貴，谷 宏，王, 秀峰，薗部, 礼，小林伸行，望月貫一郎，野田 萌，2017b．CバンドSARデータを利用した機械学習アルゴリズムによる圃場の作物分類．写真測量とリモートセンシング，56(4)，143-148 Airbus Defence and Space, 2015. Radiometric Calibration of TerraSAR-X Data, Germany. http://www.geo-airbusds.com/files/pmedia/public/r465_9_tsx-x-itd-tn-0049-radiometric_calculations_i3.00.pdf (accessed 1 Jun. 2016) Van Zyl, J.J., 1990. Calibration of polarimetric radar images using only image parameters and trihedral corner reflector responses. IEEE Transactions on Geoscience and Remote Sensing, 28(3), 337-348. Mascolo, L., Forino, G., Nunziata, F., Pugliano, G., Migliaccio, M., 2019. A New Methodology for Rice Area Monitoring With COSMO-SkyMed HH－VV PingPong Mode SAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(4), 1076-1084. Nordkvist, K., Granholm, A., Holmgren, J., Olssona, H., Nilsson, M., 2012. Combining optical satellite data and airborne laser scanner data for vegetation classification. Remote Sensing Letters, 3(5), 393-401. 石塚直樹，2016．マイクロ波合成開口レーダを用いた農地計測事例．計測と制御，55(9)，814-817 国土地理院，2016．基盤地図情報ダウンロードサービス，http://fgd.gsi.go.jp/download.（2017年３月７日確認） Liaw, A., Wiener, M., 2002. Classification and Regression by Random Forest. R News 2, 18-22. Van Zyl, J.J., Arii, M., Kim, Y., 2011. Model-Based Decomposition of Polarimetric SAR Covariance Matrices Constrained for Nonnegative Eigenvalues. IEEE Transactions on Geoscience and Remote Sensing, 49(9), 3452-3459. Freeman, A., Durden, S.L., 1998. A three-component scattering model for polarimetric SAR data. IEEE Transactions on Geoscience and Remote Sensing, 36(3), 963-973. 辻野照久，2014．衛星画像を利用した農業生産統計．科学技術動向，145，26-30 ESA, 2015. ESA science toolbox exploitation platform, France. http://step.esa.int/main (accessed 18 Mar. 2019) |
| References_xml | – reference: Mascolo, L., Forino, G., Nunziata, F., Pugliano, G., Migliaccio, M., 2019. A New Methodology for Rice Area Monitoring With COSMO-SkyMed HH－VV PingPong Mode SAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(4), 1076-1084. – reference: Zhao, L.L., Yang, J., Li, P.X., Zhang, L.P., 2014. Characteristics Analysis and Classification of Crop Harvest Patterns by Exploiting High-Frequency Multi Polarization SAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(9), 3773-3783. – reference: ESA, 2015. ESA science toolbox exploitation platform, France. http://step.esa.int/main (accessed 18 Mar. 2019) – reference: Breiman, L., 2001. Random forests. Machine Learning, 45(1), 5-32. – reference: Sonobe R., Tani H., Wang X., Kobayashi N., Shimamura H., 2014. Random forest classification of crop type using multi-temporal TerraSAR-X dual-polarimetric data. Remote Sensing Letters, 5(2), 157-164. – reference: 齋藤元也，石塚直樹，坂本利弘，2017．日本における農業リモートセンシング研究の軌跡．日本リモートセンシング学会誌，37(3)，193-203． – reference: Blaes, X., Vanhalle, L., Defourny, P., 2005. Efficiency of crop identification based on optical and SAR image time series. Remote Sensing of Environment, 96(3-4), 352-365. – reference: 辻野照久，2014．衛星画像を利用した農業生産統計．科学技術動向，145，26-30． – reference: R Core Team, 2014. R : A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org (accessed 29 Jan. 2017) – reference: NGA GEOnet Names Server, 2013. Earth Gravitational Model 2008 (EGM2008), United States. http://earth-info.nga.mil/GandG/wgs84/gravitymod/egm2008 (accessed 7 Mar. 2017) – reference: Xu, J., Li, Z., Tian, B.S., Huang, L., Chen, Q., Fu, S.T., 2014. Polarimetric analysis of multi-temporal RADARSAT-2 SAR images for wheat monitoring and mapping. International Journal of Remote Sensing, 35(10), 3840-3858. – reference: Yamaguchi, Y., Moriyama, T., Ishido, M., Yamada, H., 2005. Four-component scattering model for polarimetric SAR image decomposition. IEEE Transactions on Geoscience and Remote Sensing, 43(8), 1699-1706. – reference: 石塚直樹，2016．マイクロ波合成開口レーダを用いた農地計測事例．計測と制御，55(9)，814-817． – reference: 山谷祐貴，薗部, 礼，谷 宏，王, 秀峰，小林伸行，望月貫一郎，2017a．TerraSAR-Xデータを使用したランダムフォレストによる作付作物の分類．北海道大学農学部紀要，34(2)，１-11． – reference: Van Zyl, J.J., 1990. Calibration of polarimetric radar images using only image parameters and trihedral corner reflector responses. IEEE Transactions on Geoscience and Remote Sensing, 28(3), 337-348. – reference: Nordkvist, K., Granholm, A., Holmgren, J., Olssona, H., Nilsson, M., 2012. Combining optical satellite data and airborne laser scanner data for vegetation classification. Remote Sensing Letters, 3(5), 393-401. – reference: Cloude, S.R., Pottier, E., 1996. A review of target decomposition theorems in radar polarimetry. IEEE Transactions on Geoscience and Remote Sensing, 34(2), 498-518. – reference: 山谷祐貴，谷 宏，王, 秀峰，薗部, 礼，小林伸行，望月貫一郎，野田 萌，2017b．CバンドSARデータを利用した機械学習アルゴリズムによる圃場の作物分類．写真測量とリモートセンシング，56(4)，143-148． – reference: Cloude, S.R., 2007. The dual-polarization entropy/alpha decomposition : a pulsar case study. Proc. POLInSAR, Frascati, Italy, 1-6. – reference: Hartfield, K.A., Marsh, S.E., Kirk, C.D., Carriere, Y., 2013. Contemporary and historical classification of crop types in Arizona. International Journal of Remote Sensing, 34(17), 6024-6036. – reference: 石塚直樹，大内和夫，2017．合成開口レーダの農業への応用．日本リモートセンシング学会誌，37(3)，182-192． – reference: 野口 伸，2016．ICT農業とリモートセンシング．日本ロボット学会誌，34(2)，100-102． – reference: Immitzer, M., Vuolo, F., Atzberger, C., 2016. First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe. Remote Sensing, 8(3). – reference: Congalton, R.G., Green, K., 2008. Assessing the accuracy of remotely sensed data : Principles and practices. CRC Press, Boca Raton, Florida, United States, 137. – reference: Freeman, A., Durden, S.L., 1998. A three-component scattering model for polarimetric SAR data. IEEE Transactions on Geoscience and Remote Sensing, 36(3), 963-973. – reference: 高度情報通信ネットワーク社会推進戦略本部，2014．農業情報創成・流通促進戦略，http://www.kantei.go.jp/jp/singi/it2/kettei/pdf/senryakuzenbun_140603.pdf.（2020年３月22日確認） – reference: Van Zyl, J.J., Arii, M., Kim, Y., 2011. Model-Based Decomposition of Polarimetric SAR Covariance Matrices Constrained for Nonnegative Eigenvalues. IEEE Transactions on Geoscience and Remote Sensing, 49(9), 3452-3459. – reference: 山谷祐貴，谷 宏，王, 秀峰，薗部, 礼，小林伸行，望月貫一郎，野田 萌，2018．XバンドおよびCバンドSARデータを併用した機械学習アルゴリズムによる圃場の作物分類．写真測量とリモートセンシング，57(2)，78-83． – reference: Airbus Defence and Space, 2015. Radiometric Calibration of TerraSAR-X Data, Germany. http://www.geo-airbusds.com/files/pmedia/public/r465_9_tsx-x-itd-tn-0049-radiometric_calculations_i3.00.pdf (accessed 1 Jun. 2016) – reference: Jiao, X.F., Kovacs, J.M., Shang, J.L., McNairn, H., Walters, D., Ma, B.L., Geng, X.Y., 2014. Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data. ISPRS Journal of Photogrammetry and Remote Sensing, 96, 38-46. – reference: MDA, 2004. RADARSAT-1 Data Products Specifications, Canada. http://gs.mdacorporation.com/includes/documents/R1_PROD_SPEC.pdf (accessed 6 Jun. 2016) – reference: Liaw, A., Wiener, M., 2002. Classification and Regression by Random Forest. R News 2, 18-22. – reference: 国土地理院，2016．基盤地図情報ダウンロードサービス，http://fgd.gsi.go.jp/download.（2017年３月７日確認） |
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