植被季相变化对三维激光测量切沟地形的影响

doi:10.16843/j.sswc.2021.01.016

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Abstract [Background] With the vegetation restorating, vegetation in the hilly-gully region of the Loess Plateau has been gradually improving. However, due to the shelter of vegetation, the Digital Elevation Model (DEM) cannot well describe the real undulation of ground surface. But the vegetation in the hilly-gully region of the Loess Plateau are quite different between the growing season and the non-growing season, thus this study mainly analyzed the influence of vegetation seasonal changes on the production of high-precision DEMs. [Methods] This study took Qiaogou, Suide county, Shaanxi province as the typical hilly-gully region of the Loess Plateau. Three different sites were selected and surveyed by 3D laser scanning. Based on the point cloud obtained by 3D laser scanning in September and December 2018, after vegetation filtering and interpolating (Kriging or triangular irregular network, TIN), the difference of DEMs obtained by two surveys was compared and analyzed. [Results] 1) Vegetation seasonal change presented effects on point cloud surveyed by 3D laser scanner. The mean elevation of point cloud in Sept. was higher than that in Dec. by 0.22, 0.47 and 0.07 m in site A, B and C, respectively. That result was mainly from the vegetation seasonal changes. 2) Slope-based filtering increased the accuracy of DEM. The mean elevation of point cloud in Sept. after filtering was still higher than that in Dec. by 0.15 m, indicating the effects of vegetation seasonal change cannot be eliminated completely by slope-based filtering. 3) Compared with the Kriging, the DEM generated by the TIN was in high accuracy. The gully geomorphological parameters, e.g., gully length and gully depth obtained by Kriging method in Dec. were both often larger than those by TIN. This might result from that Kriging can roughly remove tall vegetation during the vegetation growing season and made the gully edges smooth during the non-growing season. The DEMs interpolated by TIN were closer to the real geomorphology than that by Kriging. [Conclusions] Seasonal change of vegetation shows certain effect on DEMs generation. Most of the vegetation can be removed by point cloud vegetation filtering algorithms, and the DEMs generated are closer to the real geomorphology. Regarding different DEMs interpolated methods, the accuracy of both Kriging and TIN can meet the needs of production and research but the accuracy of Kriging is less than that by TIN. The accuracy of DEMs can be effectively improved by choosing the non-growing season for point cloud survey and applying the appropriate vegetation filtering algorithms and interpolation.

Key words： 3D laser scanning point cloud filtering interpolation methods seasonal vegetation Loess Plateau

Received: 12 November 2019

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	WANG Jiaxi
	DENG Jiayong
	ZHANG Yan
	SONG Xiaopeng
	MA Rui

Cite this article:

WANG Jiaxi,DENG Jiayong,ZHANG Yan, et al. Effects of vegetation seasonal change on 3D laser survey in gullied region[J]. SSWC, 2021, 19(1): 132-140.

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http://journal12.magtechjournal.com/Jweb_stbc/EN/10.16843/j.sswc.2021.01.016 OR http://journal12.magtechjournal.com/Jweb_stbc/EN/Y2021/V19/I1/132

[1]	MARZOLFF I, POESEN J. The potential of 3D gully monitoring with GIS using high-resolution aerial photography and a digital photogrammetry system[J]. Geomorphology, 2009, 111(1/2):48.
[2]	PERROY R L, BOOKHAGEN B, ASNER G P, et al. Comparison of gully erosion estimates using airborne and ground-based LiDAR on Santa Cruz Island, California[J]. Geomorphology, 2010, 118(3/4):288.
[3]	李镇, 张岩, 杨松, 等. QuickBird影像目视解译法提取切沟形态参数的精度分析[J].农业工程学报, 2014, 30(20):179. LI Zhen, ZHANG Yan, YANG Song, et al. Error assessment of extracting morphological parameters of bank gullies by manual visual interpretation based on QuickBird imagery[J]. Transactions of the CSAE, 2014, 30(20):179.
[4]	唐杰, 张岩, 范聪慧, 等. 使用高分遥感立体影像提取黄土丘陵区切沟参数的精度分析[J].农业工程学报, 2017, 33(18):111. TANG Jie, ZHANG Yan, FAN Conghui, et al. Accuracy assessment of gully morphological parameters from high resolution remote sensing stereoscopic satellite images on hilly Loess Plateau[J]. Transactions of the CSAE, 2017, 33(18):111.
[5]	景可. 黄土高原沟谷侵蚀研究[J]. 地理科学, 1986, 6(4):340. JING Ke. A study on gully erosion on the Loess Plateau[J]. Scientia Geographica Sinica, 1986, 6(4):340.
[6]	WEHR A, LOHR U. Airborne laser scanning:an introduction and overview[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 1999, 54(2/3):68.
[7]	刘经南, 张小红. 激光扫描测高技术的发展与现状[J]. 武汉大学学报(信息科学版), 2003, 28(2):132. LIU Jingnan, ZHANG Xiaohong, Progress of airborne laser scanning altimetry[J]. Geomatics and Information Science of Wuhan University, 2003, 28(2):132.
[8]	胡刚, 伍永秋, 刘宝元, 等. GPS和GIS进行短期沟蚀研究初探:以东北漫川漫岗黑土区为例[J]. 水土保持学报, 2004, 18(4):16. HU Gang, WU Yongqiu, LIU Baoyuan, et al. Preliminary research on short-term channel erosion using GPS and GIS[J]. Journal of Soil and Water Conservation, 2004, 18(4):16.
[9]	TOUTIN T. ASTER DEMs for geomatic and geoscientific applications:A review[J]. International Journal of Remote Sensing, 2008, 29(7):1855.
[10]	DABA S, RIEGER W, STRAUSS P. Assessment of gully erosion in eastern Ethiopia using photogrammetric techniques[J]. Catena, 2003, 50(2/4):273.
[11]	花向红, 赵不钒, 陈西江, 等. 地面三维激光扫描点云质量评价技术研究与展望[J]. 地理空间信息, 2018, 16(8):1. HUA Xianghong, ZHAO Bufan, CHEN Xijiang, et al. Research and prospect of terrestrial 3D laser scanning pointcloud quality evaluation technology[J]. Geospatial Information, 2018, 16(8):1.
[12]	SITHOLE G, VOSSELMAN G. Experimental comparison of filter algorithms for bare-earth extraction from airborne laser scanning point clouds[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2004, 59(1-2):85.
[13]	MENG Xuelian, CURRIT N, ZHAO Kaiguang. Ground filtering algorithms for airborne LiDAR data a review of critical issues[J]. Remote Sensing, 2010, 2(3):833.
[14]	ARUN P V. A comparative analysis of different DEM interpolation methods[J]. The Egyptian Journal of Remote Sensing and Space Sciences, 2013, 16(2), 133.
[15]	KRAUS K, PFEIFER N. Determination of terrain model in wooded areas with airborne laser scanning data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 1998, 53(4):193.
[16]	李忠, 李梅, 杜绪奎. 平坦地区DSM到DEM的试验[J]. 测绘与空间地理信息, 2008, 31(2):29. LI Zhong, LI Mei, DU Xukui. DSM to DEM in flat area[J]. Geomatics and Spatial Information Technology, 2008, 31(2):29.
[17]	王明华, 张小红, 郭斐, 等. 陡坡林区的LIDAR点云滤波方法[J]. 测绘信息与工程, 2008, 33(6):1. WANG Minghua, ZHANG Xiaohong, GUO Fei, et al. Filtering algorithm for LiDAR point cloud in forestry with steep slope[J]. Journal of Geomatics, 2008, 33(6):1.
[18]	VEGA E C, DURRIEU S, MOREL J, et al. A sequential iterative dual-filter for Lidar terrain modeling optimized for complex forested environments[J]. Computers and Geosciences, 2012, 44:31.
[19]	喻龙华, 王雷光, 吴楠, 等. 复杂地形DSM的地面点识别及DEM提取[J]. 测绘通报, 2018(5):59. YU Longhua, WANG Leiguang, WU Nan, et al. Ground points recognition and DEM extraction based on DSM in complex terrain[J]. Bulletin of Surveying and Mapping, 2018(5):59.
[20]	CHENG Liang, ZHAO Wei, HAN Peng, et al. Building region derivation from LiDAR data using a reversed iterative mathematic morphological algorithm[J]. Optics Communications, 2013, 286:244.
[21]	VOSSELMAN G. Slope based filtering of laser altimetry data[J].International Archives of Photogrammetry and Remote Sensing, 2000,33(B3/2; PART 3):935.
[22]	马鼎, 李斌兵. 黄土沟壑区切沟植被的激光点云滤波及地形构建[J]. 农业工程学报, 2013, 29(15):162. MA Ding, LI Binbing. Vegetation filtering in gully region of loess plateau based on laser scanning point cloud's intensity attenuation model and its terrain construct[J]. Transactions of the CSAE, 2013, 29(15):162.
[23]	潘少奇, 田丰. 三维激光扫描提取DEM的地形及流域特征研究[J]. 水土保持研究, 2009, 16(6):102. PAN Shaoqi, TIAN Feng. Landform and hydrological character extraction based on high-precision DEM[J]. Research of Soil and Water Conservation, 2009, 16(6):102.
[24]	EL-ASHMAWY K L A. A comparison between analytical aerial photogrammetry, laser scanning, total station and global positioning system surveys for generation of digital terrain model[J]. Geocarto International, 2015, 30(2):154.
[25]	BANDARA K R M U, SAMARAKOON L, SHRESTHA R P, et al. Automated generation of digital terrain model using point clouds of digital surface model in forest area[J]. Remote Sensing, 2011, 3(5):845.
[26]	王志强, 刘宝元, 张岩. 不同植被类型对厚层黄土剖面水分含量的影响[J]. 地理学报, 2008, 63(7):703. WANG Zhiqiang, LIU Baoyuan, ZHANG Yan. Effects of different vegetation types on soil moisture in deep loess soil profiles[J]. Acta Geographica Sinica, 2008, 63(7):703.
[27]	WANG Tianming, KOU Xiaojun, XIONG Youcai, et al, Temporal and spatial patterns of NDVI and their relationship to precipitation in the Loess Plateau of China[J]. International Journal of Remote Sensing,2010,31(7):1943.
[28]	杨秋丽, 魏建新, 郑江华, 等. 离散点云构建数字高程模型的插值方法研究[J].测绘科学,2019,44(7):22. YANG Qiuli, WEI Jianxin, ZHENG Jianghua, et al. Comparison of interpolation methods of digital elevation model using discrete point cloud data[J]. Science of Surveying and Mapping,2019, 44(7):22.
[29]	WANG Cheng, MENENTI M, STOLL M P, et al. Separation of ground and low vegetation signatures in LiDAR measurements of salt-marsh environments[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(7):2014.