B. Trisasongko, D. R. Panuju, A. Griffin, D. Paull
{"title":"全偏振l波段合成孔径雷达估算橡胶林林分生产力的树周长","authors":"B. Trisasongko, D. R. Panuju, A. Griffin, D. Paull","doi":"10.3390/geographies2020012","DOIUrl":null,"url":null,"abstract":"This article explores a potential exploitation of fully polarimetric radar data for the management of rubber plantations, specifically for predicting tree circumference as a crucial information need for sustainable plantation management. Conventional backscatter coefficients along with Eigen-based and model-based decomposition features served as the predictors in models of tree girth using ten regression approaches. The findings suggest that backscatter coefficients and Eigen-based decomposition features yielded lower accuracy than model-based decomposition features. Model-based decompositions, especially the Singh decomposition, provided the best accuracies when they were coupled with guided regularized random forests regression. This research demonstrates that L-band SAR data can provide an accurate estimation of rubber plantation tree girth, with an RMSE of about 8 cm.","PeriodicalId":38507,"journal":{"name":"Human Geographies","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fully Polarimetric L-Band Synthetic Aperture Radar for the Estimation of Tree Girth as a Representative of Stand Productivity in Rubber Plantations\",\"authors\":\"B. Trisasongko, D. R. Panuju, A. Griffin, D. Paull\",\"doi\":\"10.3390/geographies2020012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article explores a potential exploitation of fully polarimetric radar data for the management of rubber plantations, specifically for predicting tree circumference as a crucial information need for sustainable plantation management. Conventional backscatter coefficients along with Eigen-based and model-based decomposition features served as the predictors in models of tree girth using ten regression approaches. The findings suggest that backscatter coefficients and Eigen-based decomposition features yielded lower accuracy than model-based decomposition features. Model-based decompositions, especially the Singh decomposition, provided the best accuracies when they were coupled with guided regularized random forests regression. This research demonstrates that L-band SAR data can provide an accurate estimation of rubber plantation tree girth, with an RMSE of about 8 cm.\",\"PeriodicalId\":38507,\"journal\":{\"name\":\"Human Geographies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Geographies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/geographies2020012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Geographies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/geographies2020012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Fully Polarimetric L-Band Synthetic Aperture Radar for the Estimation of Tree Girth as a Representative of Stand Productivity in Rubber Plantations
This article explores a potential exploitation of fully polarimetric radar data for the management of rubber plantations, specifically for predicting tree circumference as a crucial information need for sustainable plantation management. Conventional backscatter coefficients along with Eigen-based and model-based decomposition features served as the predictors in models of tree girth using ten regression approaches. The findings suggest that backscatter coefficients and Eigen-based decomposition features yielded lower accuracy than model-based decomposition features. Model-based decompositions, especially the Singh decomposition, provided the best accuracies when they were coupled with guided regularized random forests regression. This research demonstrates that L-band SAR data can provide an accurate estimation of rubber plantation tree girth, with an RMSE of about 8 cm.