[1]赵 飞,熊礼阳,姚 瑾,等.基于无人机高精度DEM数据的梯田自动提取算法[J].南京师范大学学报(工程技术版),2020,20(02):059-65.[doi:10.3969/j.issn.1672-1292.2020.02.009]
 Zhao Fei,Xiong Liyang,Yao Jin,et al.An Automatic Extraction Algorithm for Terraced FieldsBased on UAV High Precision DEM Data[J].Journal of Nanjing Normal University(Engineering and Technology),2020,20(02):059-65.[doi:10.3969/j.issn.1672-1292.2020.02.009]
点击复制

基于无人机高精度DEM数据的梯田自动提取算法
分享到:

南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
20卷
期数:
2020年02期
页码:
059-65
栏目:
测绘科学与技术
出版日期:
2020-05-15

文章信息/Info

Title:
An Automatic Extraction Algorithm for Terraced FieldsBased on UAV High Precision DEM Data
文章编号:
1672-1292(2020)02-0059-07
作者:
赵 飞123熊礼阳123姚 瑾4方 炫1235代 文123汤国安123
(1.南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023)(2.南京师范大学地理科学学院,江苏 南京 210023)(3.江苏省地理信息资源开发与利用协同创新中心,江苏 南京 210023)(4.自然资源部第一地理信息制图院,陕西 西安 710054)(5.南京晓庄学院环境科学学院,江苏 南京 211171)
Author(s):
Zhao Fei123Xiong Liyang123Yao Jin4Fang Xuan1235Dai Wen123Tang Guoan123
(1.Key Laboratory of Virtual Geographic Environment of Ministry of Education,Nanjing Normal University,Nanjing 210023,China)(2.School of Geography,Nanjing Normal University,Nanjing 210023,China)(3.Jiangsu Center for Collaborative Innovation in Geographi
关键词:
DEM梯田提取无人机高精度DEM
Keywords:
DEMterraced extractionhigh precision DEM of UAV
分类号:
S284
DOI:
10.3969/j.issn.1672-1292.2020.02.009
文献标志码:
A
摘要:
提出一种基于无人机高精度DEM数据的梯田自动提取算法. 首先,基于无人机航测技术获取1m分辨率的DEM数据,在此基础上计算地面坡度. 此时,梯田田坎处于坡度的极大值区. 其次,采用坡面流水模拟算法实现对该极值区的提取. 最后,对提取结果进行掩膜滤波,消除非梯田区域,得到最终梯田提取结果. 以陕西省长武县王东沟流域为实验样区,进行梯田提取实验,并将实验提取结果与梯田目视解译结果及光照晕渲模拟方法提取结果进行对比. 结果显示,相比目视真值,该方法提取梯田的准确率为90.67%,具有较高的提取精度; 相比光照晕渲模拟方法,该方法可提取出更为完整和连续的梯田结果. 该梯田快速提取方法及结果可为水土保持、农业发展、生态环境治理等研究提供依据.
Abstract:
This paper proposes an automatic extraction algorithm for terraced fields based on DEM slope characteristics. Firstly,one-meter resolution DEM is obtained with the basis of UAV aerial survey technology,and slope is calculated on this basis. Meanwhile,terrace line is located in the maximum area of slope digital terrain model. Secondly,the slope flow simulation algorithm is used to extract the extreme value region. Finally,the extraction results are masked to eliminate the non-terraced areas,and the final terraced extraction results are obtained. Taking Wangdonggou watershed in Changwu County of Shaanxi Province as an experimental sample area,the experimental results are compared with the results of terrace extraction,which are labeled by visual interpretation based on remote sensing image,or extracted from illumination model of DEM shading. The comparison results show that the accuracy of this method is 90.67%. Compared with true value of visual interpretation,it has a higher extraction accuracy. Compared with the results of illumination model of DEM shading,this method can provide more complete and continuous result of terrace. The rapid extraction method and results of the terrace can provide a basis for the research of soil and water conservation,agricultural development and ecological environment control.

参考文献/References:

[1] 代文,那嘉明,杨昕,等. 基于DEM光照晕渲模拟的梯田自动提取方法[J]. 地球信息科学学报,2017,19(6):754-762.
[2]刘芬. 黄土高原梯田DEM地形特征研究[D]. 西安:西北大学,2015.
[3]张雨果. 基于面向对象的遥感影像梯田信息提取研究[D]. 杨凌:西北农业科技大学,2016.
[4]赵护兵,刘国彬,吴瑞俊. 黄土丘陵区不同类型农地的养分循环平衡特征[J]. 农业工程学报,2006,22(1):58-64.
[5]熊利锋. 梯田发展现状概述[J]. 甘肃水利水电技术,2015,51(4):55-57.
[6]党恬敏. 基于高分影像的黄土高原梯田提取技术研究[D]. 杨凌:西北农业科技大学,2017.
[7]于浩,刘志红,张晓萍,等. 基于傅立叶变换的梯田纹理特征提取[J]. 国土资源遥感,2008,20(2):39-42.
[8]赵汉青. 梯田自动提取及特征分析[D]. 南京:南京师范大学,2016.
[9]张雨果,王飞,孙文义,等. 基于面向对象的SPOT卫星影像梯田信息提取研究[J]. 水土保持研究,2016,23(6):345-351.
[10]薛牡丹. 基于面向对象分析的无人机影像梯田田面提取研究[D]. 杨凌:西北农林科技大学,2018.
[11]张宏鸣,胡勇,杨勤科,等. 基于影像与坡度数据融合的梯田田块分割方法[J]. 农业机械学报,2018,49(4):249-256.
[12]胡勇. 面向无人机影像和坡度数据的梯田田块提取方法研究[D]. 杨凌:西北农林科技大学,2018.
[13]赵文礼. 黄河流域的梯田[J]. 中国水土保持,1983(2):36-40.
[14]赵卫东,汤国安,徐媛,等. 梯田地形形态特征及其综合数字分类研究[J]. 水土保持通报,2013,33(1):295-300.
[15]GONG J Y,ZHOU Q M,TANG G A. A study of accuracy and algorithms for calculating slope and aspect based on grid digital elevation model(DEM)[J]. Acta Geodaetica Et Cartographic Sinica,2004,33(3):258-263.
[16]PEUCKER T K,DOUGLAS D H. Detection of surface-specific points by local parallel processing of discrete terrain elevation data[J]. Computer Graphics & Image Processing,1975,4(4):375-387.
[17]周启鸣,刘学军. 数字地形分析[M]. 北京:北京科学出版社,2006.
[18]王婷婷. 黄土小流域沟壑的种群特征研究初探[D]. 南京:南京师范大学,2015.
[19]赵欣,王晓晶,赵院,等. 国产高分一号卫星数据傅里叶变换提取梯田影像可行性分析[J]. 中国水土保持,2016(1):63-65,73.
[20]徐静,王春,张耀民,等. 规则格网DEM中平直面状特征地形识别与提取[J]. 测绘科学,2014,39(8):163-166.

备注/Memo

备注/Memo:
收稿日期:2019-09-26.
基金项目:国家自然科学基金项目(41601411、41671389、41871313).
通讯作者:熊礼阳,博士,副教授,研究方向:黄土继承性DEM数字地形分析研究. E-mail:xiongliyang@njnu.edu.cn
更新日期/Last Update: 2020-05-15