利用光学和SAR遥感数据的若尔盖湿地植被分类与变化监测
Classification and change detection of vegetation in the Ruoergai Wetland using optical and SAR remote sensing data
- 2023年27卷第6期 页码：1414-1425
收稿：2021-12-03，
纸质出版：2023-06-07
DOI： 10.11834/jrs.20221767
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摘要
湿地植被在固碳过程中扮演重要角色。作为高寒湿地生态系统的典型代表，若尔盖湿地的植被分类与变化监测对于研究其碳汇功能具有重要意义。光学遥感和微波遥感在植被监测中各有其优缺点，因此本研究提出结合Sentinel-2光学数据和Sentinel-1合成孔径雷达SAR（Synthetic Aperture Radar）数据的若尔盖湿地植被分类与变化监测方法。基于动态时间归整算法DTW（Dynamic Time Warping）提取Sentinel-1 SAR数据的时间序列物候特征，结合Sentinel-2多光谱数据的光谱特征，以2020年实地获取的植被样本及使用样本迁移得到的2017年样本，通过随机森林算法分别对两个时期的若尔盖湿地植被进行分类并对其变化进行分析。研究表明：（1）结合Sentinel-1和Sentinel-2数据，充分发挥各自多时相、多光谱的优势对若尔盖湿地植被进行分类得到可靠的分类结果，总精度达到了97.43%，Kappa系数为0.96。（2）基于样本迁移原理，本研究通过将2020年实地采集的样本迁移至2017年，解决了历史时期实地样本不可得的问题，并针对SAR数据的特点提出基于DTW的样本迁移方法，顺利实现了2017年的植被分类过程。（3）通过对2017年—2020年植被变化进行分析，发现近年来若尔盖湿地植被总体变化不大，演变类别以恢复演替为主，约占研究区面积的7%。
Abstract
Wetland vegetation plays an important role in the process of carbon sequestration. As a typical alpine wetland ecosystem
the Ruoergai wetland has been attracting increasing attention due to its carbon sink function
which makes the classification and change detection of its vegetation coverage crucial.
This study aims to present a method for mapping the vegetation of the Ruoergai wetland and monitor its change by integrating Sentinel-2 optical data and Sentinel-1 Synthetic Aperture Radar (SAR) data
taking advantage of their respective advantages.
We utilize the spectral characteristics of Sentinel-2 MSI data and adopt the dynamic time warping algorithm to extract the time-series phenological characteristics of Sentinel-1 SAR data; in this manner
different wetland vegetations can be differentiated easily. The random forest algorithm was used to combine both data for classifying wetland vegetation types. In-site samples obtained by UAV in 2020 are used and migrated to 2017 to train and validate the classification results.
The classification results have an overall accuracy of 97.43% and a Kappa coefficient of 0.96. Vegetation in the Ruoerge wetlands remains overall unchanged from 2017 to 2020
with the changed area exhibiting a recovery trend (~7% of the total area).
On the basis of the principle of sample migration
this study solved the problem in which the field samples were not available in the historical period. By combining Sentinel-1 and Sentinel-2 data
their respective multitemporal and multispectral advantages were fully exploited to obtain reliable classification results.
关键词
Keywords
references
Amani M , Salehi B , Mahdavi S , Granger J and Brisco B . 2017 . Wetland classification in Newfoundland and Labrador using multi-source SAR and optical data integration . GIScience and Remote Sensing , 54 ( 6 ): 779 - 796 [ DOI: 10.1080/15481603.2017.1331510 http://dx.doi.org/10.1080/15481603.2017.1331510 ]
Bajgain P , Rouse M N , Bulli P , Bhavani S , Gordon T , Wanyera R , Njau P N , Legesse W , Anderson J A and Pumphrey M O . 2015 . Association mapping of North American spring wheat breeding germplasm reveals loci conferring resistance to Ug99 and other African stem rust races . BMC Plant Biology , 15 : 249 [ DOI: 10.1186/s12870-015-0628-9 http://dx.doi.org/10.1186/s12870-015-0628-9 ]
Bourgeau-Chavez L L , Endres S , Powell R , Battaglia M J , Benscoter B , Turetsky M , Kasischke E S and Banda E . 2016 . Mapping boreal peatland ecosystem types from multitemporal radar and optical satellite imagery . Canadian Journal of Forest Research , 47 ( 4 ): 545 - 559 [ DOI: 10.1139/cjfr-2016-0192 http://dx.doi.org/10.1139/cjfr-2016-0192 ]
Breiman L . 2001 . Random forests . Machine Learning , 45 ( 1 ): 5 - 32 [ DOI: 10.1023/A:1010933404324 http://dx.doi.org/10.1023/A:1010933404324 ]
Davidson E A and Janssens I A . 2006 . Temperature sensitivity of soil carbon decomposition and feedbacks to climate change . Nature , 440 ( 7081 ): 165 - 173 [ DOI: 10.1038/nature04514 http://dx.doi.org/10.1038/nature04514 ]
Franklin S E , Skeries E M , Stefanuk M A and Ahmed O S . 2018 . Wetland classification using Radarsat-2 SAR quad-polarization and Landsat-8 OLI spectral response data: a case study in the Hudson Bay Lowlands Ecoregion . International Journal of Remote Sensing , 39 ( 6 ): 1615 - 1627 [ DOI: 10.1080/01431161.2017.1410295 http://dx.doi.org/10.1080/01431161.2017.1410295 ]
Gong P , Liu H , Zhang M N , Li C C , Wang J , Huang H B , Clinton N , Ji L Y , Li W Y , Bai Y Q , Chen B , Xu B , Zhu Z L , Yuan C , Suen H P , Guo J , Xu N , Li W J , Zhao Y Y , Yang J , Yu C Q , Wang X , Fu H H , Yu L , Dronova I , Hui F M , Cheng X , Shi X L , Xiao E J , Liu Q F and Song L C . 2019 . Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017 . Science Bulletin , 64 ( 6 ): 370 - 373 [ DOI: 10.1016/j.scib.2019.03.002 http://dx.doi.org/10.1016/j.scib.2019.03.002 ]
Hssina B , Merbouha A , Ezzikouri H and Erritali M . 2014 . A comparative study of decision tree ID3 and C4.5 . International Journal of Advanced Computer Science and Applications , 4 : 13 - 19 [ DOI: 10.14569/SpecialIssue.2014.040203 http://dx.doi.org/10.14569/SpecialIssue.2014.040203 ]
Huang H B , Wang J , Liu C X , Liang L , Li C C and Gong P . 2020 . The migration of training samples towards dynamic global land cover mapping . ISPRS Journal of Photogrammetry and Remote Sensing , 161 : 27 - 36 [ DOI: 10.1016/j.isprsjprs.2020.01.010 http://dx.doi.org/10.1016/j.isprsjprs.2020.01.010 ]
Ji H Y , Ren Z Q and Rao Z H . 2019 . Discriminant analysis of millet from different origins based on hyperspectral imaging technology . Spectroscopy and Spectral Analysis , 39 ( 7 ): 2271 - 2277
吉海彦 , 任占奇 , 饶震红 . 2019 . 基于高光谱成像技术的不同产地小米判别分析 . 光谱学与光谱分析 , 39 ( 7 ): 2271 - 2277 [ DOI: 10.3964/j.issn.1000-0593(2019)07-2271-07 http://dx.doi.org/10.3964/j.issn.1000-0593(2019)07-2271-07 ]
Kasischke E S and E S Bourgeau-Chavez L L . 1997 . Monitoring South Florida wetlands using ERS-1 SAR imagery . Photogrammetric Engineering and Remote Sensing , 63 ( 3 ): 281 - 291
Lee J S , Wen J H , Ainsworth T L , Chen K S and Chen A J . 2009 . Improved sigma filter for speckle filtering of SAR imagery . IEEE Transactions on Geoscience and Remote Sensing , 47 ( 1 ): 202 - 213 [ DOI: 10.1109/TGRS.2008.2002881 http://dx.doi.org/10.1109/TGRS.2008.2002881 ]
Liu H Y and Bai Y F . 2006 . Changing process and mechanism of wetland resources in Ruoergai Plateau, China . Journal of Natural Resources , 21 ( 5 ): 810 - 818
刘红玉 , 白云芳 . 2006 . 若尔盖高原湿地资源变化过程与机制分析 . 自然资源学报 , 21 ( 5 ): 810 - 818 [ DOI: 10.3321/j.issn:1000-3037.2006.05.015 http://dx.doi.org/10.3321/j.issn:1000-3037.2006.05.015 ]
Liu R Q , Li J L , Sun C , Sun W W , Cao L D and Tian P . 2021 . Classification of Yancheng coastal wetland vegetation based on vegetation phenological characteristics derived from Sentinel-2 time-series . Acta Geographica Sinica , 76 ( 7 ): 1680 - 1692
刘瑞清 , 李加林 , 孙超 , 孙伟伟 , 曹罗丹 , 田鹏 . 2021 . 基于Sentinel-2遥感时间序列植被物候特征的盐城滨海湿地植被分类 . 地理学报 , 76 ( 7 ): 1680 - 1692 [ DOI: 10.11821/dlxb202107008 http://dx.doi.org/10.11821/dlxb202107008 ]
Mao D H , Wang Z M , Du B J , Li L , Tian Y L , Jia M M , Zeng Y , Song K S , Jiang M and Wang Y Q . 2020 . National wetland mapping in China: a new product resulting from object-based and hierarchical classification of Landsat 8 OLI images . ISPRS Journal of Photogrammetry and Remote Sensing , 164 : 11 - 25 [ DOI: 10.1016/j.isprsjprs.2020.03.020 http://dx.doi.org/10.1016/j.isprsjprs.2020.03.020 ]
Maus V , Câmara G , Cartaxo R , Sanchez A , Ramos F M and de Queiroz G R . 2016 . A time-weighted dynamic time warping method for land-use and land-cover mapping . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 ( 8 ): 3729 - 3739 [ DOI: 10.1109/JSTARS.2016.2517118 http://dx.doi.org/10.1109/JSTARS.2016.2517118 ]
Mobasheri M R and Amani M . 2016 . Soil moisture content assessment based on Landsat 8 red, near-infrared, and thermal channels . Journal of Applied Remote Sensing , 10 ( 2 ): 026011 [ DOI: 10.1117/1.JRS.10.026011 http://dx.doi.org/10.1117/1.JRS.10.026011 ]
Mutanga O , Adam E and Cho M A . 2012 . High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm . International Journal of Applied Earth Observation and Geoinformation , 18 : 399 - 406 [ DOI: 10.1016/j.jag.2012.03.012 http://dx.doi.org/10.1016/j.jag.2012.03.012 ]
Ruiz L F C , Guasselli L A , Simioni J P D , Belloli T F and Fernandes P C B . 2021 . Object-based classification of vegetation species in a subtropical wetland using Sentinel-1 and Sentinel-2A images . Science of Remote Sensing , 3 : 100017 [ DOI: 10.1016/j.srs.2021.100017 http://dx.doi.org/10.1016/j.srs.2021.100017 ]
Slagter B , Tsendbazar N E , Vollrath A and Reiche J . 2020 . Mapping wetland characteristics using temporally dense Sentinel-1 and Sentinel-2 data: a case study in the St. Lucia wetlands, South Africa . International Journal of Applied Earth Observation and Geoinformation , 86 : 102009 [ DOI: 10.1016/j.jag.2019.102009 http://dx.doi.org/10.1016/j.jag.2019.102009 ]
Sun C , Li J L , Liu Y X , Liu Y C and Liu R Q . 2021 . Plant species classification in salt marshes using phenological parameters derived from Sentinel-2 pixel-differential time-series . Remote Sensing of Environment , 256 : 112320 [ DOI: 10.1016/j.rse.2021.112320 http://dx.doi.org/10.1016/j.rse.2021.112320 ]
Tang Y M , Ma W W , Li G , Xu G R , Zhang Y , Pan P X , Song L C , Long Y C and Chang W H . 2021 . Variations of soil organic nitrogen fractions during degradation succession in the Gahai Wet-land, Northwest China . Chinese Journal of Applied Ecology , 32 ( 11 ): 4077 - 4084
唐艳梅 , 马维伟 , 李广 , 徐国荣 , 张悦 , 潘平新 , 宋良翠 , 龙永春 , 常文华 . 2021 . 尕海湿地退化演替过程中土壤有机氮组分的变化特征 . 应用生态学报 , 32 ( 11 ): 4077 - 4084 [ DOI: 10.13287/j.1001-9332.202111.035 http://dx.doi.org/10.13287/j.1001-9332.202111.035 ]
Tian S H , Zhang X F , Tian J and Sun Q . 2016 . Random forest classification of wetland landcovers from multi-sensor data in the arid region of Xinjiang, China . Remote Sensing , 8 ( 11 ): 954 [ DOI: 10.3390/rs8110954 http://dx.doi.org/10.3390/rs8110954 ]
Tian Y B . 2005 . The vegetation type and its distribution regularity under different habitats in Ruoergai Plateau . Journal of Yangtze University (Natural Science Edition) , 2 ( 2 ): 1 - 5
田应兵 . 2005 . 若尔盖高原湿地不同生境下植被类型及其分布规律 . 长江大学学报(自科版) , 2 ( 2 ): 1 - 5 [ DOI: 10.3969/j.issn.1673-1409-C.2005.02.001 http://dx.doi.org/10.3969/j.issn.1673-1409-C.2005.02.001 ]
Tong Q X , Zheng L F , Wang J N , Wang X J , Dong W D , Hu Y M and Dang S X . 1997 . Study on imaging spectrometer remote sensing information for wetland vegetation . Journal of Remote Sensing , 1 ( 1 ): 50 - 57
童庆禧 , 郑兰芬 , 王晋年 , 王向军 , 董卫东 , 胡远满 , 党顺行 . 1997 . 湿地植被成象光谱遥感研究 . 遥感学报 , 1 ( 1 ): 50 - 57 [ DOI: 10.11834/jrs.19970108 http://dx.doi.org/10.11834/jrs.19970108 ]
Tsyganskaya V , Martinis S , Marzahn P and Ludwig R . 2018 . Detection of temporary flooded vegetation using sentinel-1 time series data . Remote Sensing , 10 ( 8 ): 1286 [ DOI: 10.3390/rs10081286 http://dx.doi.org/10.3390/rs10081286 ]
van der Putten W H . 1997 . Die-back of Phragmites australis in European wetlands: an overview of the European research programme on reed die-back and progression (1993-1994) . Aquatic Botany , 59 ( 3-4 ): 263 - 275 [ DOI: 10.1016/S0304-3770(97)00060-0 http://dx.doi.org/10.1016/S0304-3770(97)00060-0 ]
White L , Brisco B , Dabboor M , Schmitt A and Pratt A . 2015 . A collection of SAR Methodologies for monitoring wetlands . Remote Sensing , 7 ( 6 ): 7615 - 7645 [ DOI: 10.3390/rs70607615 http://dx.doi.org/10.3390/rs70607615 ]
Yan X and Niu Z G . 2021 . Reliability evaluation and migration of wetland samples . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 14 : 8089 - 8099 [ DOI: 10.1109/JSTARS.2021.3102866 http://dx.doi.org/10.1109/JSTARS.2021.3102866 ]
Zhang L , Gong Z N , Wang Q W , Jin D D and Wang X . 2019 . Wetland mapping of Yellow River Delta wetlands based on multi-feature optimization of Sentinel-2 images . Journal of Remote Sensing , 23 ( 2 ): 313 - 326
张磊 , 宫兆宁 , 王启为 , 金点点 , 汪星 . 2019 . Sentinel-2影像多特征优选的黄河三角洲湿地信息提取 . 遥感学报 , 23 ( 2 ): 313 - 326 [ DOI: 10.11834/jrs.20198083 http://dx.doi.org/10.11834/jrs.20198083 ]
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相关作者
何佳月 哈尔滨工程大学 信息与通信工程学院
宿南 哈尔滨工程大学 信息与通信工程学院
徐从安 海军航空大学 信息融合研究所
尹璐 北京市遥感信息研究所
廖艳苹 哈尔滨工程大学 信息与通信工程学院
闫奕名 哈尔滨工程大学 信息与通信工程学院
鞠琦 中山大学 测绘科学与技术学院/南方海洋科学与工程广东省实验室
李刚 中山大学 测绘科学与技术学院/南方海洋科学与工程广东省实验室
相关机构
哈尔滨工程大学 信息与通信工程学院
海军航空大学 信息融合研究所
北京市遥感信息研究所
中山大学 测绘科学与技术学院/南方海洋科学与工程广东省实验室
中国科学院空天信息创新研究院 国家遥感应用工程技术研究中心
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