{"title":"基于异速标度理论的滤波器改进定量结构模型","authors":"Jan Hackenberg, Jean-Daniel Bontemps","doi":"10.1007/s12518-023-00537-4","DOIUrl":null,"url":null,"abstract":"<div><p>Quantitative structure models (<span>QSMs</span>) are topological ordered cylinder models of trees which cover the complete branching structure from the stem’s base up to all tips. But the thin branches appear too large in the input point clouds. This leads to a well known problem, the overestimation of the QSM cylinders’ volumes and radii in thin branches. We present here a solution to this problem by introducing two <span>QSM</span> filters correcting the radii of such cylinders. The filters itself are build upon the theoretical fundamentals of allometric scaling theories. For validation we use <span>QSMs</span> produced from an open point cloud data set of tree clouds with the SimpleForest software. We compare the QSM volume against the harvested reference data for 65 felled trees. We also found <span>QSM</span> data of TreeQSM, a competitive and broadly accepted <span>QSM</span> modeling tool utilizing a different filter method. Our method performed more accurate on three different error measures. We quantify the error of our method with a RMSE of 127 <span>\\(\\mathtt {dm^{3}}\\)</span>, a <span>\\(\\mathtt {r^{2}_{adj.}}\\)</span> of 0.96 and a <span>CCC</span> of 0.97. With those filters the accuracy of estimating total or partial volume of trees does significantly increase.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving quantitative structure models with filters based on allometric scaling theory\",\"authors\":\"Jan Hackenberg, Jean-Daniel Bontemps\",\"doi\":\"10.1007/s12518-023-00537-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Quantitative structure models (<span>QSMs</span>) are topological ordered cylinder models of trees which cover the complete branching structure from the stem’s base up to all tips. But the thin branches appear too large in the input point clouds. This leads to a well known problem, the overestimation of the QSM cylinders’ volumes and radii in thin branches. We present here a solution to this problem by introducing two <span>QSM</span> filters correcting the radii of such cylinders. The filters itself are build upon the theoretical fundamentals of allometric scaling theories. For validation we use <span>QSMs</span> produced from an open point cloud data set of tree clouds with the SimpleForest software. We compare the QSM volume against the harvested reference data for 65 felled trees. We also found <span>QSM</span> data of TreeQSM, a competitive and broadly accepted <span>QSM</span> modeling tool utilizing a different filter method. Our method performed more accurate on three different error measures. We quantify the error of our method with a RMSE of 127 <span>\\\\(\\\\mathtt {dm^{3}}\\\\)</span>, a <span>\\\\(\\\\mathtt {r^{2}_{adj.}}\\\\)</span> of 0.96 and a <span>CCC</span> of 0.97. With those filters the accuracy of estimating total or partial volume of trees does significantly increase.</p></div>\",\"PeriodicalId\":46286,\"journal\":{\"name\":\"Applied Geomatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12518-023-00537-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-023-00537-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Improving quantitative structure models with filters based on allometric scaling theory
Quantitative structure models (QSMs) are topological ordered cylinder models of trees which cover the complete branching structure from the stem’s base up to all tips. But the thin branches appear too large in the input point clouds. This leads to a well known problem, the overestimation of the QSM cylinders’ volumes and radii in thin branches. We present here a solution to this problem by introducing two QSM filters correcting the radii of such cylinders. The filters itself are build upon the theoretical fundamentals of allometric scaling theories. For validation we use QSMs produced from an open point cloud data set of tree clouds with the SimpleForest software. We compare the QSM volume against the harvested reference data for 65 felled trees. We also found QSM data of TreeQSM, a competitive and broadly accepted QSM modeling tool utilizing a different filter method. Our method performed more accurate on three different error measures. We quantify the error of our method with a RMSE of 127 \(\mathtt {dm^{3}}\), a \(\mathtt {r^{2}_{adj.}}\) of 0.96 and a CCC of 0.97. With those filters the accuracy of estimating total or partial volume of trees does significantly increase.
期刊介绍:
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements