基于厘米级无人机影像的水土保持措施精准识别

夏晨真; 张月

doi:10.13870/j.cnki.stbcxb.2020.05.016

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基于厘米级无人机影像的水土保持措施精准识别

更新时间：2025-03-12

- 基于厘米级无人机影像的水土保持措施精准识别
- Accurate Identification of Soil and Water Conservation Measures Based on Centimeter-resolution UAV Images
- 水土保持学报 2020年34卷第5期页码：111-118
- 作者机构：
  
  1. 吉林农业大学资源与环境学院,长春,130118
  2. 吉林省商品粮基地土壤资源可持续利用重点实验室,长春,130118
- 作者简介：
  
  [ "夏晨真(1997-),男,在读硕士研究生,主要从事农业遥感研究。E-mail:Summul_R@163.com" ]
- 基金信息：
  
  国家自然科学基金项目（U19A2061）国家重点研发计划项目（2006YFE0202900）吉林省教育厅科学技术研究项目（JJKH20190915KJ）
- DOI：10.13870/j.cnki.stbcxb.2020.05.016
  中图分类号： S157.1
- 纸质出版：2020
- 稿件说明：
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夏晨真, 张月. 基于厘米级无人机影像的水土保持措施精准识别[J]. 水土保持学报, 2020,34(5):111-118.

XIA Chenzhen, ZHANG Yue. Accurate Identification of Soil and Water Conservation Measures Based on Centimeter-resolution UAV Images[J]. 2020, 34(5): 111-118.
夏晨真, 张月. 基于厘米级无人机影像的水土保持措施精准识别[J]. 水土保持学报, 2020,34(5):111-118. DOI： 10.13870/j.cnki.stbcxb.2020.05.016.

XIA Chenzhen, ZHANG Yue. Accurate Identification of Soil and Water Conservation Measures Based on Centimeter-resolution UAV Images[J]. 2020, 34(5): 111-118. DOI： 10.13870/j.cnki.stbcxb.2020.05.016.

摘要

基于厘米级高分辨率无人机影像，应用面向对象方法（Object-Based Image Analysis，OBIA）对吉林省伊通县椽子沟流域的横坡改垄、地埂植物带、生态恢复乔木林、生态恢复草地等水土保持措施进行自动精准识别。应用超绿指数（Excess Green Index，ExG）、超红指数（Excess Red Index，ExR）、归一化差异指数（Normalized Difference Index，NDI）等光谱指数，形状的主方向、形状指数等形状特征，均值（Mean）、方差（Variance）、对比度（Contrast）等纹理特征进行措施的特征提取。结果表明：研究区水土保持措施识别的总体精度可达91.24%，Kappa系数为0.87；对垄台、垄沟等线性水土保持措施总体精度可达72.33%，Kappa系数为0.63。基于厘米级无人机影像，应用面向对象方法基本可实现对黑土区水土保持措施的精准识别，也可对垄台垄沟等线性措施进行自动识别，研究结果可为水土保持措施实施范围及完好程度的动态监测提供参考依据。

Abstract

Based on the centimeter-resolution Unmanned Aerial Vehicles (UAV) image

the Object-Based Image Analysis (OBIA) was applied to identify the soil and water conservation (SWC) measures

including contour ridges

ridge plants

ecological restoration forest

ecological restoration grassland

in the Chuanzigou catchment of Yitong district

Jilin province. Spectral indices including Excess Green Index (ExG)

Excess Red Index (ExR)

Normalized Difference Index (NDI)

shape features including principal direction and shape index

and texture features including mean

variance and contrast were used to extract the features of SWC measures. Finally

the overall accuracy and Kappa coefficient of the identification of SWC measures in the study area was 91.24% and 0.87

respectively. The overall accuracy of the identification of linear SWC measures such as ridges and ridge-furrows was 72.33% with a Kappa coefficient of 0.63. The research showed that the centimeter-resolution UAV image

combined with the OBIA methods had the ability to accurately identify SWC measures in black soil area. They can also identify linear measures such as ridges and ridge-furrows automatically. The research can provide a reference basis for the dynamic monitoring of the implementation scope and integrity of SWC measures.

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references

王岩松,姜艳艳,常诚,等.2018年度松辽流域水土流失动态监测结果分析[J].中国水土保持,2019(12):7-10.

刘震.我国水土保持情况普查及成果运用[J].中国水土保持科学,2013,11(2):1-5.

赵帮元,马宁,杨娟,等.基于不同分辨率遥感影像提取的水土保持措施精度分析[J].水土保持通报,2012,32(4):154-157.

侯群群.面向对象的遥感影像水土保持措施信息提取研究[D].陕西杨凌:西北农林科技大学,2013.

党恬敏.基于高分影像的黄土高原梯田提取技术研究[D].陕西杨凌:西北农林科技大学,2017.

Zhang Y, Shi M C, Zhao X, et al. Methods for automatic identification and extraction of terraces from high spatial resolution satellite data (China-GF-1)[J].International Soil and Water Conservation Research,2017,5(1):17-25.

Alessandra C, Lammert K, Lorenzo B. A novel approach for detecting agricultural terraced landscapes from historical and contemporaneous photogrammetric aerial photos[J].International Journal of Applied Earth Observation and Geoinformation,2018,73:800-810.

赵俊喜.无人机遥感监测在水土保持监测中的应用[J].中国新技术新产品,2018(10):9-10.

汪传建,赵庆展,马永建,等.基于卷积神经网络的无人机遥感农作物分类[J].农业机械学报,2019,50(11):161-168.

松辽委水土保持处.松辽流域应用无人机遥感技术开展水土保持监管成效显著[J].中国水土保持,2016(12):79.

常虹,詹福雷,杨国东,等.面向对象的高分遥感影像信息提取技术研究[J].测绘通报,2015(1):99-101,130.

陈宇琼,李晓燕,钟太洋.伊通县土壤侵蚀敏感性分析[J].江西农业学报,2016,28(1):98-103.

陈杰.高分辨率遥感影像面向对象分类方法研究[D].长沙:中南大学,2010.

Yang J, He Y H, Caspersen J, et al. A discrepancy measure for segmentation evaluation from the perspective of object recognition[J]. Journal of Photogrammetry and Remote Sensing,2015,101:186-192.

岳安志,杨建宇,张超,等.基于多尺度形态学滤波的高分辨率遥感影像分割[J].农业工程学报,2013,29(增刊1):89-95.

Meyer G E, Neto J C. Verification of color vegetation indices for automated crop imaging applications[J].Computers&Electronics in Agriculture,2008,63(2):282-293.

Tucker P W, Hazen E E, Cotton F A. Staphylococcal nuclease reviewed:A prototypic study in contemporary enzymology[J].Molecular&Cellular Biochemistry,1979,23(2):67-86.

Woebbecke D M, Meyer G E, Von Bargen K, et al. Color indices for weed identification under various soil, residue, and lighting conditions[J].Transactions of the ASAE,1995,38:259-269.

Neto J C, Mayer G E. Crop Species Identification Using Machine Vision of Compute Extracted Individual Leaves//Bellingham. Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality. WA:SPIE,2005:599-608.

Kataoka T, Kaneko T, Okamoto H, et al. Crop Growth Estimation System Using Machine Vision//Piscataway. ASME International Conference on Advanced Intelligent Mechatronics(AIM 2003). NJ:IEEE,2003:1079-1083.

Hagur T, Tillett N D, Wheeler H. Automated crop and weed monitoring in widely spaced cereals[J].Precision Agriculture,2006,7(1):21-32.

Guijarro M,Pajares G,Riomoros I, et al. Automatic Segmentation of Relevant Textures in Agricultural Images[J].Computers&Electronics in Agriculture,2011,75(1):75-83.

Barling R D, Moore I D, Grayson R B. A quasi-dynamic wetness index for characterizing the spatial distribution of zones of surface saturation and soil water content[J].Water Resource Research,1994,30:1029-1044.

胡玉福,邓良基,匡先辉,等.基于纹理特征的高分辨率遥感图像土地利用分类研究[J].地理与地理信息科学,2011,27(5):42-45,68.

Zhong Y F, Zhao B, Zhang L P. Multiagent object-based classifier for high spatial resolution imagery[J].IEEE Transactions on Geoscience and Remote Sensing,2014,52(2):841-857.

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