基于DEM的小班坡度自动提取算法及其验证

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英文篇名：Automatic Extraction Algorithm and Verification of Subcompartment Slope Based on DEM 作者：陈晨 ; 陈永刚 ; 徐文兵 ; 梁丹 英文作者：Chen Chen;Chen Yonggang;Xu Wenbing;Liang Dan;Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration,Zhejiang A &F University;School of Surveying and Geoinformatics,Tongji University; 关键词：DEM ; 小班 ; 坡度 ; 异常的高低起伏点 ; 斜平面模型 英文关键词：digital elevation model;;subcompartment;;slope;;abnormal highs and lows;;inclined plane model 中文刊名：西南林业大学学报(自然科学) 英文刊名：Journal of Southwest Forestry University(Natural Sciences) 机构：浙江农林大学浙江省森林生态系统碳循环与固碳减排重点实验室;同济大学测绘与地理信息学院; 出版日期：2019-06-28 出版单位：西南林业大学学报(自然科学) 年：2019 期：04 基金：浙江省自然科学基金项目(LY16D010009)资助;; 浙江省基础公益研究计划项目(LGN18C160004)资助 语种：中文; 页：89-94 页数：6 CN：53-1218/S ISSN：2095-1914 分类号：S757.2

摘要

针对现有的小班坡度计算方法存在的复杂地形适应能力较差、提取结果准确度不高的问题,提出了一种基于DEM的小班坡度自动提取算法,通过与其他2种传统方法进行对比分析,检验了该方法的准确性与实用性。结果表明:该方法剔除了小班内的异常的高低起伏点,并获取了小班所在的斜平面模型,综合考虑了小班整体情况。该算法得到的结果更准确、更实用,能够适应地形复杂度较高的区域,替代人工完成小班坡度值的测量,节省时间、人力和物力。
        Aiming at the problem that the existing subcompartment gradient calculation method has poor adaptability to complex terrain and low accuracy of extraction results, a subcompartment automatic extraction algorithm based on DEM was proposed. The accuracy and practicability of the method were tested by comparison with other 2 traditional methods. Results show that the method eliminates the abnormal high and low fluctuation points in the subcompartment, and obtains the oblique plane model of the subcompartment, taking into account the overall situation of the subcompartment. The result obtained by the algorithm is more accurate and practical, and can adapt to the area with high terrain complexity, instead of manually completing the measurement of the subcompartment value, saving time, manpower and material resources.

引文

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