Please wait a minute...
 
国土资源遥感  2017, Vol. 29 Issue (1): 170-177    DOI: 10.6046/gtzyyg.2017.01.26
  技术应用 本期目录 | 过刊浏览 | 高级检索 |
基于物候特征参数的山西煤矿区典型复垦植被分类
张彦彬1, 安楠2, 刘佩艳1, 贾坤3, 姚云军3
1. 山西省自动化研究所, 太原 030012;
2. 堪萨斯州立大学农学系环境与农业空间分析实验室, 堪萨斯州 66506, 美国;
3. 北京师范大学地理学与遥感科学学院, 北京 100875
Typical reclamation vegetation classification based on phenological feature parameters for coalfields in Shanxi Province
ZHANG Yanbin1, AN Nan2, LIU Peiyan1, JIA Kun3, YAO Yunjun3
1. Shanxi Automation Research Institute, Taiyuan 030012, China;
2. Ecology & Agriculture Spatial Analysis Laboratory, Department of Agronomy, Kansas State University, Kansas 66506, USA;
3. School of Geography, Beijing Normal University, Beijing 100875, China
全文: PDF(3865 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 

基于2001-2013年获取的MOD13Q1 NDVI数据,采用低通平滑Savitzky-Golay(S-G)滤波方法、插值法及切比雪夫多项式(Chebyshev Polynomial)拟合对NDVI时序数据进行重构;通过提取植被生长季开始日期、生长季长度、生长季结束日期、生长季NDVI最大值及NDVI最大值出现日期等关键物候特征参数,对研究区典型复垦植被类型进行分类。结果表明:研究区不同植被的物候特征具有显著差异,从生长季开始日期及NDVI最大值出现日期来看,农作物较有规律;而林地的生长季NDVI累积总值则明显区别于农作物及草地;农作物、草地和林地基于植被物候特征参数分类取得了较好结果,总体分类精度达到89.67%,优于采用多时相非监督分类的结果;该研究为山西省煤炭矿区生态环境恢复评价提供了一定的数据基础。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
张恩兵
秦昆
岳梦雪
张晔
曾诚
关键词 变差函数格网划分居民区稳健性纹理差值曲线空间结构    
Abstract

In this paper, the authors reconstructed MOD13Q1 time-series NDVI data from 2001 to 2013 using Savitzky-Golay filter and Chebyshev Polynomial methods for classifying vegetation types in the six coalfields in Shanxi Province. The key phenological parameters were extracted from the reconstructed NDVI data, such as the beginning dates of the growing season, length of the growing season, the ending dates of the growing season, the maximum NDVI value and the responding dates. The results show that different vegetation types of the six major coalfields in Shanxi have different phenological features. Cropland has distinguishable differences from grass and forest. Similarly, forest is distinguished from grass and cropland by integration of total growth. It is shown that the classification of vegetation types can achieve better results by extracting and analyzing the phonological parameters compared with multi-temporal unsupervised classification. The overall classification accuracy reaches 89.67%. This study provides a robust method for assessing long-term ecological conditions and monitoring vegetation coverage changes of the six major coalfields in Shanxi Province.

Key wordsvariogram    grid division    residential areas    robustness    texture difference curve    spatial structure
收稿日期: 2015-09-29      出版日期: 2017-01-23
:  TP79  
  S127  
基金资助:

国际合作项目“利用卫星遥感技术对煤矿复垦生态环境的动态监测及分析”(编号:2013DFA91870)和中国科学院数字地球重点实验室开放基金项目“低空间分辨率遥感数据时相特征改善高分辨率数据农作物分类精度研究”(编号:2014LDE011)共同资助。

通讯作者: 贾坤(1983-),男,博士,副教授,主要从事定量遥感和土地覆盖分类方面的研究。Email:jiakun@bnu.edu.cn。
作者简介: 张彦彬(1967-),男,高级工程师,主要从事遥感应用方面的研究。Email:zyb9633@163.com。
引用本文:   
张彦彬, 安楠, 刘佩艳, 贾坤, 姚云军. 基于物候特征参数的山西煤矿区典型复垦植被分类[J]. 国土资源遥感, 2017, 29(1): 170-177.
ZHANG Yanbin, AN Nan, LIU Peiyan, JIA Kun, YAO Yunjun. Typical reclamation vegetation classification based on phenological feature parameters for coalfields in Shanxi Province. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 170-177.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2017.01.26      或      https://www.gtzyyg.com/CN/Y2017/V29/I1/170

[1] 贾坤,李强子,田亦陈,等.遥感影像分类方法研究进展[J].光谱学与光谱分析,2011,31(10):2618-2623. Jia K,Li Q Z,Tian Y C,et al.A review of classification methods of remote sensing imagery[J].Spectroscopy and Spectral Analysis,2011,31(10):2618-2623.
[2] 贾坤,李强子.农作物遥感分类特征变量选择研究现状与展望[J].资源科学,2013,35(12):2507-2516. Jia K,Li Q Z.Review of features selection in crop classification using remote sensing data[J].Resources Science,2013,35(12):2507-2516.
[3] Jia K,Liang S L,Wei X Q,et al.Land cover classification of landsat data with phenological features extracted from time series MODIS NDVI data[J].Remote Sensing,2014,6(11):11518-11532.
[4] 郭芬芬,范建容,边金虎,等.基于MODIS NDVI时间序列数据的藏北草地类型识别[J]. 遥感技术与应用,2011,26(6):821-826. Guo F F,Fan J R,Bian J H,et al.Grassland types identification based on time-series MODIS NDVI data in northern Tibet[J].Remote Sensing Technology and Application,2011,26(6):821-826.
[5] 宫攀,陈仲新,唐华俊,等.基于MODIS温度/植被指数的东北地区土地覆盖分类[J].农业工程学报,2006,22(9):94-99. Gong P,Chen Z X,Tang H J,et al.Land cover classification based on MODIS temperature-vegetation index time-series data in northeastern China[J].Transactions of the CSAE,2006,22(9):94-99.
[6] Pringle M J,Denham R J,Devadas R.Identification of cropping activity in central and southern Queensland,Australia,with the aid of MODIS MOD13Q1 imagery[J].International Journal of Applied Earth Observation and Geoinformation,2012,19:276-285.
[7] Mkhabela M S,Bullock P,Raj S,et al.Crop yield forecasting on the Canadian Prairies using MODIS NDVI data[J].Agricultural and Forest Meteorology,2011,151(3):385-393.
[8] 那晓东,张树清,李晓峰,等.MODIS NDVI时间序列在三江平原湿地植被信息提取中的应用[J]. 湿地科学,2007,5(3):227-236. Na X D,Zhang S Q,Li X F,et al.Application of MODIS NDVI time series to extracting wetland vegetation information in the Sanjiang Plain[J].Wetland Science,2007,5(3):227-236.
[9] 潘耀忠,李乐,张锦水,等.基于典型物候特征的MODIS-EVI时间序列数据农作物种植面积提取方法——小区域冬小麦实验研究[J].遥感学报,2011,15(3):578-594. Pan Y Z,Li L,Zhang J S,et al.Crop area estimation based on MODIS-EVI time series according to distinct characteristics of key phenology phases:A case study of winter wheat area estimation in small-scale area[J].Journal of Remote Sensing,2011,15(3):578-594.
[10] 郝鹏宇,牛铮,王力,等.基于历史时序植被指数库的多源数据作物面积自动提取方法[J].农业工程学报,2012,28(23):123-131. Hao P Y,Niu Z,Wang L,et al.Multi-source automatic crop pattern mapping based on historical vegetation index profiles[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(23):123-131.
[11] 康峻,侯学会,牛铮,等.基于拟合物候参数的植被遥感决策树分类[J].农业工程学报,2014,30(9):148-156. Kang J,Hou X H,Niu Z,et al.Decision tree classification based on fitted phenology parameters from remotely sensed vegetation data[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(9):148-156.
[12] 夏传福,李静,柳钦火.植被物候遥感监测研究进展[J].遥感学报,2013,17(1):1-16. Xia C F,Li J,Liu Q H.Review of advances in vegetation phenology monitoring by remote sensing[J].Journal of Remote Sensing,2013,17(1):1-16.
[13] 李正国,杨鹏,周清波,等.基于时序植被指数的华北地区作物物候期/种植制度的时空格局特征[J].生态学报,2009,29(11):6216-6226. Li Z G,Yang P,Zhou Q B,et al.Research on spatiotemporal pattern of crop phenological characteristics and cropping system in north China based on NDVI time series data[J].Acta Ecologica Sinica,2009,29(11):6216-6226.
[14] Beck P S A,Atzberger C,Høgda K A,et al.Improved monitoring of vegetation dynamics at very high latitudes:A new method using MODIS NDVI[J].Remote Sensing of Environment,2006,100(3):321-334.
[15] 宫攀.基于MODIS数据关键物候特征参数的东北地区植被覆盖分类[J].资源科学,2010,32(6):1154-1160. Gong P.Vegetation classification based on phenology indices derived from MODIS data in northeastern China[J].Resources Science,2010,32(6):1154-1160.
[16] Murakami T,Ogawa S,Ishitsuka N,et al.Crop discrimination with multitemporal SPOT/HRV data in the Saga Plains,Japan[J].International Journal of Remote Sensing,2001,22(7):1335-1348.
[17] 杨延征,赵鹏翔,郝红科,等.基于SPOT-VGT NDVI的陕北植被覆盖时空变化[J].应用生态学报,2012,23(7):1897-1903. Yang Y Z,Zhao P X,Hao H K,et al.Spatiotemporal variation of vegetation in northern Shaanxi of northwest China based on SPOT-VGT NDVI[J].Chinese Journal of Applied Ecology,2012,23(7):1897-1903.
[18] 边金虎,李爱农,宋孟强,等.MODIS植被指数时间序列Savitzky-Golay滤波算法重构[J].遥感学报,2010,14(4):725-741. Bian J H,Li A N,Song M Q,et al.Reconstruction of NDVI time-series datasets of MODIS based on Savitzky-Golay filter[J].Journal of Remote Sensing,2010,14(4):725-741.
[19] 范锦龙,吴炳方.复种指数遥感监测方法[J].遥感学报,2004,8(6):628-636. Fan J L,Wu B F.A methodology for retrieving cropping index from NDVI profile[J].Journal of Remote Sensing,2004,8(6):628-636.
[20] Congalton R G.A review of assessing the accuracy of classifications of remotely sensed data[J].Remote Sensing of Environment,1991,37(1):35-46.

[1] 岳梦雪, 秦昆, 张恩兵, 张晔, 曾诚. 基于数据场和密度聚类的高分辨率影像居民区提取[J]. 国土资源遥感, 2017, 29(3): 92-97.
[2] 张恩兵, 秦昆, 岳梦雪, 张晔, 曾诚. 基于变差函数和格网划分的居民区特征描述与提取[J]. 国土资源遥感, 2016, 28(4): 149-155.
[3] 张远飞, 袁继明, 杨自安, 吕伟艳, 张思颖. 基于物理意义的二维散点图类型划分与遥感蚀变信息提取[J]. 国土资源遥感, 2013, 25(2): 57-62.
[4] 王冬寅, 朱谷昌, 张远飞. 典型地物光谱空间结构特征与基本统计参数分析[J]. 国土资源遥感, 2012, 24(4): 138-145.
[5] 张远飞, 吴德文, 袁继明, 朱谷昌, 杨自安, 胡波. 遥感蚀变信息多层次分离技术模型与应用研究[J]. 国土资源遥感, 2011, 23(4): 6-13.
[6] 张远飞, 袁继明, 朱谷昌, 吴德文, 李红. 基于遥感数据随机模型的空间结构分与蚀变信息提取[J]. 国土资源遥感, 2010, 22(4): 34-39.
[7] 李红, 朱谷昌, 张远飞, 杨自安. 矿化蚀变区典型地物光谱特征分析与空间结构研究——以内蒙古突泉县—扎鲁特旗成矿带为例[J]. 国土资源遥感, 2010, 22(1): 89-95.
[8] 李淑坤, 李培军, 程涛. 加入多时相纹理的遥感变化检测[J]. 国土资源遥感, 2009, 21(3): 35-40.
[9] 姜腾龙, 赵书河, 肖鹏峰, 陈淑兴. 基于光谱夹角的水体信息提取方法研究[J]. 国土资源遥感, 2009, 21(2): 102-105.
[10] 李小涛, 李纪人, 黄诗峰, 宋小宁. 变差函数和神经网络结合的遥感影像分类方法研究[J]. 国土资源遥感, 2006, 18(1): 18-21.
[11] 黄颖端, 李培军, 李争晓. 基于地统计学的图像纹理在岩性分类中的应用[J]. 国土资源遥感, 2003, 15(3): 45-49.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
版权所有 © 2015 《自然资源遥感》编辑部
地址:北京学院路31号中国国土资源航空物探遥感中心 邮编:100083
电话:010-62060291/62060292 E-mail:zrzyyg@163.com
本系统由北京玛格泰克科技发展有限公司设计开发