于DEM光照晕渲模拟的梯田自动提取方法

doi:10.3724/SP.J.1047.2017.00754

地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (6): 754-762.doi: 10.3724/SP.J.1047.2017.00754

• 地球信息科学理论与方法 • 上一篇下一篇

于DEM光照晕渲模拟的梯田自动提取方法

代文^1,^2,³(), 那嘉明^1,^2,³, 杨昕^1,^2,^3,^*(), 曹建军^1,^2,^3,⁴

1. 南京师范大学虚拟地理环境教育部重点实验室,南京 210023
2. 江苏省地理环境演化国家重点实验室培育建设点,南京 210023
3. 江苏省地理信息资源开发与利用协同创新中心,南京 210023
4. 南京晓庄学院环境科学学院,南京 211171

收稿日期:2016-10-11 修回日期:2017-04-17 出版日期:2017-06-20 发布日期:2017-06-20
通讯作者: 杨昕 E-mail:dwdaerte@qq.com;xxinyang@163.com
作者简介:
作者简介：代文（1995-）,男,贵州毕节人,硕士生,研究方向为空间数据挖掘。E-mail: dwdaerte@qq.com
基金资助:
国家自然科学基金项目（41271438、41401441）;江苏高校优势学科建设工程资助项目（164320H116）

An Automatic Retrieval Method for Artificial Terrace Based on Illumination Model of DEM Shading

DAI Wen^1,^2,³(), NA Jiaming^1,^2,³, YANG Xin^1,^2,^3,^*(), CAO Jianjun^1,^2,^3,⁴

1. Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 210023, China
2. Cultivation Base of State Key Laboratory of Geographical Environment Evolution of Jiangsu Province, Nanjing 210023, China
3. Collaborative Innovation Center for Geographical Information Resource Development and Application of Jiangsu Province, Nanjing 210023, China
4. School of Environmental Science, Nanjing Xiaozhuang College, Nanjing 211171, China

Received:2016-10-11 Revised:2017-04-17 Online:2017-06-20 Published:2017-06-20
Contact: YANG Xin E-mail:dwdaerte@qq.com;xxinyang@163.com

摘要/Abstract

摘要：

梯田作为黄土高原最为典型的人工地貌之一,有重要的农业生产和水土保持价值。传统的梯田自动提取仅限于梯田所在区域的范围划定,未能对梯田田坎线实现有效的自动化提取。鉴于此,本文提出了一种基于光照晕渲模拟的梯田快速提取方法。首先,对无人机航测生成的1 m分辨率的数字高程模型（DEM）进行4个方向的光照晕渲模拟,并相加取平均值;然后,通过适当的阈值对均值图像进行二值化,并掩膜掉沟谷等非梯田区域;最后,基于二值化图像自动矢量化得到梯田田坎线,并通过适当的长度阈值进行碎线过滤提高提取精度。本文以陕西省长武县王东沟流域为实验样区进行了实验,结果表明,该方法提取结果的准确率为89.09%,具有较好的提取精度。此外,对该方法涉及到的参数进行了讨论,表明光照模拟的方向角采用2个正交的对称方向对、高度角采用田坎坡度的反正切值、二值化阈值采用t=180-σ的经验公式,可以满足黄土高原的梯田自动快速提取。

关键词: DEM, 梯田, 光照晕渲, 黄土高原, GIS

Abstract:

As one of the most typical artificial landforms in loess plateau of China, artificial terraces have important value in agricultural production as well as soil and water conservation. The previous studies on terrace automatic extraction only focused on their boundaries and failed to achieve effective and automatic extraction of their ridge lines. In this study, a quick extraction method of terraces based on illumination and shading simulation of DEM is proposed. Firstly, illumination and shading simulation in four-direction is carried out using 1 m digital elevation model (DEM) generated by Unmanned Aerial Vehicle (UAV) technology and average value of four simulations was calculated. Secondly, the image of the mean value is binarized into a logistic image using a proper threshold. Also, valley and other non-terraced areas were masked off. Finally, terrace ridge lines were obtained by automatic vectorization of the logistic image. Some broken lines were filtered by a proper length threshold to improve the extraction precision. Taken Wangdonggou watershed, Changwu County, Shaanxi Province as the study area, the experiment results showed that this method had a preferable extraction accuracy of 89.09%. Furthermore, the parameters involved in this method were also discussed. The results showed that if we take two orthogonal symmetric direction angles as the direction angles, arctangent value of the slope of terrace ridges as the altitude angle, an empirical formula (t=180-σ) was used to calculate the threshold value of the logistic image, the quick automatic extraction of artificial terraces of loess plateau can be achieved.

Key words: DEM, artificial terrace, illumination of the shading, loess plateau, GIS

代文, 那嘉明, 杨昕, 曹建军. 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.DOI:10.3724/SP.J.1047.2017.00754

DAI Wen,NA Jiaming,YANG Xin,CAO Jianjun. An Automatic Retrieval Method for Artificial Terrace Based on Illumination Model of DEM Shading[J]. Journal of Geo-information Science, 2017, 19(6): 754-762.DOI:10.3724/SP.J.1047.2017.00754

图/表 12

图1

图2

图3

图4

图5

图6

图7

图8

图9

图10

图11

表1

参考文献 24

[1]	王翊人,赵牡丹,冯园,等.梯田对土壤侵蚀地形因子扰动特征研究[J].山东农业大学学报(自然科学版),2017,48(1):46-51. doi: 10.3969/j.issn.1000-2324.2017.01.010
	[ Wang Y R, Zhao M D, Feng Y, et al.Disturbed characteristics of terraces against terrain factors in soil erosion[J]. Journal of Shandong Agricultural University (Natural Science Edition), 2017,48(1):46-51. ] doi: 10.3969/j.issn.1000-2324.2017.01.010
[2]	刘晓燕,王富贵,杨胜天,等.黄土丘陵沟壑区水平梯田减沙作用研究[J].水利学报,2014(7):793-800.
	[ Liu X Y, Wang F G, Yang S T, et al.Sediment reduction effect of level terrace in the hilly-gully region in the Loess Plateau[J]. Journal of SHUILI, 2014,7:793-800. ]
[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:西北农林科技大学,2016.
	[ Zhang Y G.Terrace information extraction from remote sensing images based on object-oriented classification method[D]. Yangling: Northwest A&F University, 2016. ]
[4]	吴淑芳,吴普特.水土保持及土壤侵蚀动态机制研究现状及存在问题[J].水土保持研究,2010(2):37-40.
	[ Wu S F, Wu P T.Research status and existing problems on dynamic mechanism of soil and water conservation and soil erosion[J]. Research of Soil and Water Conservation, 2010,2:37-40. ]
[5]	刘宝元,刘瑛娜,张科利,等.中国水土保持措施分类[J].水土保持学报,2013(2):80-84.
	[ Liu B Y, Liu Y N, Zhang K L, et al.Classification for soil conservation practices in China[J]. Journal of Soil and Water Conservation, 2013,2:80-84. ]
[6]	Fu B, Chen L, Ma K, et al.The relationships between land use and soil conditions in the hilly area of the loess plateau in northern Shaanxi, China[J]. Catena, 2000,39(1):69-78. doi: 10.1016/S0341-8162(99)00084-3
[7]	Quine T, Walling D, Zhang X.Tillage erosion, water erosion and soil quality on cultivated terraces near Xifeng in the Loess Plateau, China[J]. Land Degradation & Development, 1999,10(3):251-274.
[8]	马红斌,李晶晶,何兴照,等.黄土高原水平梯田现状及减沙作用分析[J].人民黄河,2015(2):89-93. doi: 10.3969/j.issn.1000-1379.2015.02.024
	[ Ma H B, Li J J, He X Z, et al.The status and sediment reduction effects of level terrace in the Loess Plateau[J]. Yellow River, 2015,2: 89-93. ] doi: 10.3969/j.issn.1000-1379.2015.02.024
[9]	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. doi: 10.6046/gtzyyg.2008.02.10
	[ Yu H, Liu Z H, Zhang X P, et al.Extraction of terranced field texture features based on fourise transformation[J]. Romote sensing for land & resourse, 2008,22(2):39-42. ] doi: 10.6046/gtzyyg.2008.02.10
[10]	王杲,梁亮.基于高分辨率遥感影像的田坎系数测算[J].测绘与空间地理信息,2009,32(5):99-101. doi: 10.3969/j.issn.1672-5867.2009.05.030
	[ Wang G, Liang L.Extraction of terranced field texture features based on fourise transformation[J]. Geomatics & spatial information technology, 2009,32(5):99-101. ] doi: 10.3969/j.issn.1672-5867.2009.05.030
[11]	Diaz-Varela R, Zarco-Tejada P J, Angileri V, et al. Automatic identification of agricultural terraces through object-oriented analysis of very high resolution DSMs and multispectral imagery obtained from an unmanned aerial vehicle[J]. Journal of environmental management, 2014,134(117-126). doi: 10.1016/j.jenvman.2014.01.006 pmid: 24473345
[12]	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. doi: 10.3969/j.issn.1000-0941.2016.01.024
	[ Zhao X, Wang X J, Zhao Y, et al.Feasibility anlysis on methodology of terraced extraction by using fourier transformation based on domestic Hi-Resolution romote sensing images of GF-1 satellite[J]. Soil and water conservation in China, 2016,1: 63-65,73. ] doi: 10.3969/j.issn.1000-0941.2016.01.024
[13]	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.
	[ Xu J, Wang C, Zhang Y M, et al.Identification and extraction of flat-polygon terrains in grid DEM[J]. Science og Surveying, 2014,39(8):163-166. ]
[14]	Scott A T, Pinter N.Extraction of coastal terraces and shoreline-angle elevations from digital terrain models, Santa Cruz and Anacapa Islands, California[J]. Physical Geography, 2003,24(4):271-294. doi: 10.2747/0272-3646.24.4.271
[15]	Demoulin A, Bovy B, Rixhon G, et al.An automated method to extract fluvial terraces from digital elevation models: The Vesdre valley, a case study in eastern Belgium[J]. Geomorphology, 2007,91(1):51-64. doi: 10.1016/j.geomorph.2007.01.020
[16]	周启明,刘学军.数字地形分析[M].北京:科学出版社,2006.
	[ Zhou Q M, Liu X J.Digital terrain analysis[M]. Beijing: Science Publishing, 2006. ]
[17]	郭庆胜,王晓延.地貌晕渲中光源使用方法与用色规则的研究[J].武汉大学学报·信息科学版,2004,29(1):20-23,33. doi: 10.3321/j.issn:1671-8860.2004.01.004
	[ Guo Q S, Wang X Y.Study on Light Direction and Color in Hill-Shading[J]. Geomatics and Information Science of Wuhan University, 2004,29(1):20-23,33. ] doi: 10.3321/j.issn:1671-8860.2004.01.004
[18]	Oguchi T, Aoki T, Matsuta N.Identification of an active fault in the Japanese Alps from DEM-based hill shading[J]. Computers & Geosciences, 2003,29(7):885-891. doi: 10.1016/S0098-3004(03)00083-9
[19]	陈永刚,汤国安,周毅,等.基于多方位DEM地形晕渲的黄土地貌正负地形提取[J].地理科学,2012,32(1):105-109. doi: 10.1007/s11783-011-0280-z
	[ Chen Y G, Tang G A, Zhou Y, et al.The positive and negative terrain of loess plateau extraction based on the multi-azimuth DEM shaded relief[J]. Scientia Geographica Sinica, 2012,32(1):105-109. ] doi: 10.1007/s11783-011-0280-z
[20]	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(1): 295-300.
	[ Zhao W D, Tang G A, Xu Y, et al.Terrace morphological characteristis and its comprehensive digital classification[J]. Bulletin of Soil and Water Conservation, 2013(1):295-300. ]
[21]	赵卫东. 顾及梯田地形的数字高程模型研究[D].南京:南京师范大学,2011.
	[ Zhao W D.Research on digital elevation model considering terraced terrains[D]. Nanjing: Nanjing Normal University, 2011. ]
[22]	Burrough P A, Mcdonnell R A, Mcdonnell R, et al.Principles of geographical information systems [M]. Oxford: Oxford University Press, 2015.
[23]	刘玮,李发源,熊礼阳,等.基于区域生长的黄土地貌沟沿线提取方法与实验[J].地球信息科学学报,2016,18(2):220-226. doi: 10.3724/SP.J.1047.2016.00220
	[ Liu W, Li F Y, Xiong L Y, et al.Shoulder line extraction in the Loess Plateau based on region growing algorithm[J]. Journal of Geo-information Science, 2016,18(2):220-226. ] doi: 10.3724/SP.J.1047.2016.00220
[24]	李敏,杨昕,陈盼盼,等.面向点云数据的黄土丘陵沟壑区沟沿线自动提取方法[J].地球信息科学学报,2016,18(7):869-877. doi: 10.3724/SP.J.1047.2016.00869
	[ Li M, Yang X, Chen P P, et al.2016. Method of automatic shoulder line extraction in the Loess Hilly Area based on point cloud data[J]. Journal of Geo-information Science, 2016,18(7):869-877. ] doi: 10.3724/SP.J.1047.2016.00869

样区	落入缓冲区内长度/m	自身长度/m	精度/%
1	2150.344	2528.756	85.04
2	1556.658	1933.443	80.51
3	2146.149	2293.271	93.58
4	2524.383	2704.162	93.35
5	2486.654	2731.036	91.05
6	2306.565	2739.156	84.21
7	2612.080	2786.140	93.75
合计	15 782.833	17 715.964	89.09

于DEM光照晕渲模拟的梯田自动提取方法

An Automatic Retrieval Method for Artificial Terrace Based on Illumination Model of DEM Shading

RichHTML

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 24

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	曹中浩, 张健钦, 杨木, 贾礼朋, 邓少存. 基于GIS新冠智能体仿真模型及应用——以广州市为例[J]. 地球信息科学学报, 2021, 23(2): 297-306.
[2]	李锐, 石佳豪, 董广胜, 刘朝辉. 多粒度时空对象组成结构表达研究[J]. 地球信息科学学报, 2021, 23(1): 113-123.
[3]	宋关福, 陈勇, 罗强, 武梦瑶. GIS基础软件技术体系发展及展望[J]. 地球信息科学学报, 2021, 23(1): 2-15.
[4]	罗竹, 刘凯, 张春亢, 邓心远, 马荣华, 宋春桥. DEM在湖泊水文变化研究中的应用进展[J]. 地球信息科学学报, 2020, 22(7): 1510-1521.
[5]	姚可桢, 岳书平. 网络大数据下的中国现代食甜习惯空间分布特征及其影响因素研究[J]. 地球信息科学学报, 2020, 22(6): 1202-1215.
[6]	朱亚茹, 高峻, 邴振华, 张中浩, 付晶. 基于参与式制图方法的景观服务评估与空间结构研究[J]. 地球信息科学学报, 2020, 22(5): 1106-1119.
[7]	赵耀龙, 巢子豪. 历史GIS的研究现状和发展趋势[J]. 地球信息科学学报, 2020, 22(5): 929-944.
[8]	王英杰, 张桐艳, 李鹏, 虞虎. GIS在中国旅游资源研究与应用中的现状及趋势[J]. 地球信息科学学报, 2020, 22(4): 751-759.
[9]	熊礼阳, 汤国安. 黄土高原沟谷地貌发育演化研究进展与展望[J]. 地球信息科学学报, 2020, 22(4): 816-826.
[10]	杨艳昭, 郎婷婷, 张超, 贾琨. 基于GIS的“一带一路”地区气温插值方法比较研究[J]. 地球信息科学学报, 2020, 22(4): 867-876.
[11]	李思进, 代文, 熊礼阳, 汤国安. DEM分辨率对黄土侵蚀沟形态特征表达的不确定性分析[J]. 地球信息科学学报, 2020, 22(3): 338-350.
[12]	王春, 徐燕, 江岭, 赵明伟. 规则格网DEM局地坡面凸凹性精度分析[J]. 地球信息科学学报, 2020, 22(3): 361-369.
[13]	赵尚民, 程维明, 蒋经天, 沙文娟. 资源三号卫星DEM数据与全球开放DEM数据的误差对比[J]. 地球信息科学学报, 2020, 22(3): 370-378.
[14]	张鑫港, 闫浩文, 张黎明. 一种用于DEM数据认证与篡改定位的感知哈希算法[J]. 地球信息科学学报, 2020, 22(3): 379-388.
[15]	赵明伟, 金永林, 江岭, 王春, 杨灿灿, 徐燕. 多模型协同下的城郊地区DEM构建方法研究[J]. 地球信息科学学报, 2020, 22(3): 389-398.