基于手机相片的草地植被盖度估算方法研究

doi:10.3969/j.issn.1004-1524.2017.06.23

浙江农业学报 ›› 2017, Vol. 29 ›› Issue (6): 1017-1025.DOI: 10.3969/j.issn.1004-1524.2017.06.23

基于手机相片的草地植被盖度估算方法研究

丁肖¹, 邱新法^2,*, 高佳琦³, 龚敬瑜⁴

1.南京信息工程大学地理与遥感学院,江苏南京 210044;
2.南京信息工程大学应用气象学院,江苏南京 210044;
3.南京信息工程大学大气科学学院,江苏南京 210044;
4.南京信息工程大学大气物理学院,江苏南京 210044

收稿日期:2016-12-27 出版日期:2017-06-20 发布日期:2017-09-07
通讯作者: 邱新法,E-mail: xfqiu135@nuist.edu.cn
作者简介:丁肖(1991—),男,山东枣庄人,硕士研究生,主要从事草地植被盖度估算方法研究。E-mail: dingxiao0618@163.com
基金资助:
国家自然科学基金项目(41330529); 江苏省第四期“333高层次人才培养工程” 科研项目(BRA2014373)

Research on estimation approach of grassland vegetation coverage based on cellphone photo

DING Xiao¹, QIU Xinfa^2,*, GAO Jiaqi³, GONG Jingyu⁴

1. School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China;
2. School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;
3. College of Atmospheric Science, Nanjing University of Information Science & Technology, Nanjing 210044, China;
4. School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China

Received:2016-12-27 Online:2017-06-20 Published:2017-09-07

摘要/Abstract

摘要： 选取6种基于RGB通道信息的植被指数(VEG、CIVE、EXG、EXGR、NGRDI、COM),借助自主开发的手机APP对6种方法展开对比研究,从草绿度、天气条件、盖度3个角度分析估算误差的变化规律,并从阈值随光照变化角度评估每种方法的稳定性。研究表明,6种方法估算精度均高于90%,其中,COM方法最高,达到95.41%,NGRDI方法估算精度最低,为92.87%。每种方法对深绿色草的估算误差均小于对黄绿色草,在阴天条件下(云量≥70%)的估算误差小于晴天条件下(云量≤10%)。盖度增加时,VEG、CIVE、EXG、COM方法估算误差增大,EXGR、NGRDI方法无明显变化规律。同日内不同时次,随着太阳高度角、光照强度的变化,6种方法阈值无明显变化(阈值波动≤0.02)。不同天气条件下,VEG、CIVE方法的阈值基本无变化(阈值波动≤0.01),其余方法变化明显(阈值波动≥0.03)。综上,6种方法均可满足在手机平台中应用的要求,COM方法精度最高,NGRDI方法精度最低。VEG、CIVE方法阈值设定无须考虑光照变化影响,较其他方法具有更好的通用性。

关键词: 植被盖度, 数字相片, 草地, 植被指数

Abstract: In the present study, 6 kinds of vegetation indexes (VEG, CIVE, EXG, EXGR, NGRDI, COM) were selected to estimate vegetation coverage of grassland based on RGB channel information, and their effects were compared with self-developed APP. Meanwhile, the influence on estimation error was discussed from 3 aspects including the green degree, weather conditions and vegetation coverage. Besides, the stability of each method was estimated from the perspective of threshold variation with illumination. It was shown that the estimation accuracy of 6 methods was higher than 90%. COM method reached the maximum accuracy of 95.41%, while, NGRDI method exhibited the lowest accuracy of 92.87%. The estimation error of each method for dark green grass was smaller than that of yellow green grass, and the estimation error in cloudy condition (cloudiness≥70%) was smaller than that in sunny condition (cloudiness≤10%). With the increase of vegetation coverage, the estimation error of VEG, CIVE, EXG, COM increased, while, no regular changes on estimation error of EXGR, NGRDI method were found. All 6 methods showed no obvious changes (threshold fluctuation≤0.02) with the changes of solar zenith angle and light intensity in a day. Under different weather conditions, the thresholds of VEG, CIVE methods had no obvious change (threshold fluctuation≤0.01), while, the thresholds of the remaining methods changed significantly (threshold fluctuation≥0.03). In short, all the 6 methods could satisfy the application in cellphone platform. As there was no need to consider the impact of illumination changes, VEG and CIVE possessed better versatility compared with the other methods.

Key words: vegetation coverage, digital photos, grassland, vegetation index

中图分类号:

S812.5

丁肖, 邱新法, 高佳琦, 龚敬瑜. 基于手机相片的草地植被盖度估算方法研究[J]. 浙江农业学报, 2017, 29(6): 1017-1025.

DING Xiao, QIU Xinfa, GAO Jiaqi, GONG Jingyu. Research on estimation approach of grassland vegetation coverage based on cellphone photo[J]. , 2017, 29(6): 1017-1025.

参考文献

[1] 秦伟,朱清科,张学霞,等.植被覆盖度及其测算方法研究进展[J].西北农林科技大学学报(自然科学版),2006,34(9):163-170.
QIN W, ZHU Q K, ZHANG X X, et al. Review of vegetation covering and its measuring and calculating method[J]. Journal of Northwest A&F University ( Natural Science Edition ), 2006,34(9):163-170.(in Chinese with English abstract)
[2] 张学霞,朱清科,吴根梅,等.数码照相法估算植被盖度[J].北京林业大学学报, 2008, 30(1):164-169.
ZHANG X X, ZHU Q K, WU G M, et al. Vegetation coverage assessment by digital photos[J]. Journal of Beijing Forestry University , 2008, 30(1):164-169. (in Chinese with English abstract)
[3] 陈祖刚,巴图娜存,徐芝英,等.基于数码相机的草地植被盖度测量方法对比研究[J].草业学报,2014,23(6):20-27.
CHEN Z G, BATU N C, XU Z Y, et al. Measuring grassland vegetation cover using digital camera images[J]. Acta Prataculturae Sinica , 2014,23(6):20-27. (in Chinese with English abstract)
[4] 章文波,符素华,刘宝元.目估法测量植被覆盖度的精度分析[J].北京师范大学学报(自然科学版),2001,37(3):402-408.
ZHANG W B, FU S H, LIU B Y. Error assessment of visual estimation plant coverage[J]. Journal of Beijing Normal University ( Natural Science ), 2001,37(3):402-408. (in Chinese with English abstract)
[5] 任世龙,宜树华,陈建军,等.基于不同数码相机和图像处理方法的高寒草地植被盖度估算的比较[J].草业科学,2014, 31(6):1007-1013.
REN S L,YI S H,CHEN J J, et al. Comparisons of alpine grassland fractional vegetation cover estimation using different digital cameras and different image analysis methods[J]. Pratacultural Science , 2014, 31(6):1007-1013. (in Chinese with English abstract)
[6] 张云霞,张云飞,李晓兵.地面测量与ASTER影像综合计算植被盖度[J].生态学报,2007,27(3):964-976.
ZHANG Y X, ZHANG Y F, LI X B. The synthetically estimating vegetation fractional coverage of grassland using field data and ASTER remote sensing imagine[J]. Acta Ecologica Sinica , 2007,27(3):964-976. (in Chinese with English abstract)
[7] 高志强,刘纪远,庄大方.基于遥感和GIS的中国土地利用/土地覆盖的现状研究[J].遥感学报,1999,3(2):134-138.
GAO Z Q,LIU J Y,ZHUANG D F.The research of Chinese land-use/land-cover present situations[J]. Journal of Remote Sensing , 1999,3(2):134-138. (in Chinese with English abstract)
[8] 张云霞,李晓兵,陈云浩.草地植被盖度的多尺度遥感与实地测量方法综述[J].地球科学进展,2003,18(1):85-93.
ZHANG Y X,LI X B,CHEN Y H. Overview of field and multi-scale remote sensing measurement approaches to grassland vegetation coverage[J]. Advance in Earth Sciences , 2003,18(1):85-93. (in Chinese with English abstract)
[9] 顾祝军,曾志远.遥感植被盖度研究[J].水土保持研究,2005,12(2):18-21.
GU Z J, ZENG Z Y. Overview of researches on vegetation coverage in remote sensing[J] . Research of Soil and Water Conservation , 2005,12(2):18-21. (in Chinese with English abstract)
[10] 池宏康,周广胜,许振柱,等.草地植被盖度的近距离遥感测定[J].草业学报,2007,16(2):105-110.
CHI H K,ZHOU G S,XU Z Z,et al. Measuring coverage of grassland vegetation using remote sensing over short distances[J]. Acta Prataculturae Sinica , 2007,16(2):105-110. (in Chinese with English abstract)
[11] LALIBERTE A S, RANGO A, HERRICK J E, et al. An object-based image analysis approach for determining fractional cover of senescent and green vegetation with digital plot photography [J]. Journal of Arid Environments , 2007, 69(1):1-14.
[12] 张清平,章山山,陈露,等.应用WinCAM软件判识分析草坪盖度[J].草业科学,2010,27(7):13-17.
ZHANG Q P,ZHANG S S, CHEN L,et al. Identification and analysis of turf coverage with WinCAM software[J]. Pratacultural Science , 2010,27(7):13-17. (in Chinese with English abstract)
[13] 宋雪峰,董永平,单丽燕,等.用数码相机测定草地盖度的研究[J].内蒙古草业,2004(4):1-6.
SONG X F,DONG Y P,SHAN L Y,et al. A method for measuring grassland coverage using the digital camera[J]. Inner Mongolia Prataculture , 2004(4):1-6. (in Chinese with English abstract)
[14] 章超斌,李建龙,张颖,等.基于RGB模式的一种草地盖度定量快速测定方法研究[J].草业学报,2013,22(4):220-226.
ZHANG C B,LI J L,ZHANG Y,et al. A quantitative analysis method for measuring grassland coverage based on the RGB model[J]. Acta Prataculturae Sinica , 2013,22(4):220-226. (in Chinese with English abstract)
[15] 胡健波,张璐,黄伟,等.基于数码相片的草地植被覆盖度快速提取方法[J].草业科学,2011,28(9):1661-1665.
HU J B, ZHANG L, HUANG W, et al. Quickly determining grassland cover using the digital image[J]. Pratacultural Science , 2011,28(9):1661-1665. (in Chinese with English abstract)
[16] HAGUE T, TILLETT N D, WHEELER H. Automated crop and weed monitoring in widely spaced cereals[J]. Precision Agriculture , 2006, 7(1):21-32.
[17] KATAOKA T, KANEKO T, OKAMOTO H, et al. Crop growth estimation system using machine vision[C]//IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2003.
[18] WOEBBECKE D M, MEYER G E, VON BARGEN K, et al. Color indices for weed identification under various soil, residue, and lighting conditions[C]// American Society of Agricultural Engineers Meeting, 1994.
[19] NETO J C. A combined statistical-soft computing approach for classification and mapping weed species in minimum-tillage systems[EB/OL]. (2004-09-01) [2016-12-27]. http://search.proquest.com/docview/305161252.
[20] GITELSON A A, KAUFMAN Y J, STARK R, et al. Novel algorithms for remote estimation of vegetation fraction[J]. Remote Sensing of Environment , 2002, 80(1):76-87.
[21] GUIJARRO M, PAJARES G, RIOMOROS I, et al. Automatic segmentation of relevant textures in agricultural images[J]. C omputers & Electronics in Agriculture , 2011, 75(1):75-83.
[22] BAUER T, STRAUSS P. A rule-based image analysis approach for calculating residues and vegetation cover under field conditions[J]. Catena , 2014, 113:363-369.
[23] 胡云峰,陈祖刚,董群,等.安卓手机的草地信息协同采集系统设计与实现[EB/OL]. (2016-11-09)[2016-12-17]http://www.cnki.net/kcms/detail/11.4415.p.20161109.0936.048.html.
[24] 顾祝军.植被覆盖度的照相法测算及其与植被指数关系研究[D].南京:南京师范大学, 2005.
GU Z J. Study on the measurement of photography method for vegetation coverage and its relationship with vegetation index[D].Nanjing: Nanjing Normal University, 2005.

基于手机相片的草地植被盖度估算方法研究

Research on estimation approach of grassland vegetation coverage based on cellphone photo

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