南京大学学报(自然科学版) ›› 2019, Vol. 55 ›› Issue (4): 699–707.doi: 10.13232/j.cnki.jnju.2019.04.020

• • 上一篇    

基于遥感数据定位老龄树群

王博闻1,史江峰1,2(),史逝远1,张伟杰1,马晓琦1,赵业思1   

  1. 1. 南京大学地理与海洋科学学院，南京，210023
    2. 亚利桑那大学树木年轮研究实验室，Tucson，AZ85721，USA
  • 收稿日期:2019-05-24 出版日期:2019-07-30 发布日期:2019-07-23
  • 通讯作者: 史江峰 E-mail:shijf@nju.edu.cn
  • 基金资助:
    江苏省科技厅自然科学基金(BK20161394);国家自然科学基金(41671193);国家留学基金委青年骨干教师出国研修(201806195033);国家重点研究发展计划(2016YFA0600503)

Locating old trees based on remote sensing data

Bowen Wang1,Jiangfeng Shi1,2(),Shiyuan Shi1,Weijie Zhang1,Xiaoqi Ma1,Yesi Zhao1   

  1. 1. School of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China
    2. Laboratory of Tree?Ring Research, School of Environment, The University of Arizona, Tucson, AZ85721, USA
  • Received:2019-05-24 Online:2019-07-30 Published:2019-07-23
  • Contact: Jiangfeng Shi E-mail:shijf@nju.edu.cn

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摘要：

在野外找到老龄树群，是树木年轮气候学研究的一个关键环节.目前还没有在大尺度空间上连续的高精度的树龄数据可供使用，尝试建立一种基于遥感数据定位老龄树群的方法.以30 m分辨率的卫星Landsat 8 OLI (Operational Land Imager)遥感影像一景为例，首先在该影像范围内收集了22个已发表的树轮宽度年表长度数据，根据经纬度定点提取年表对应的归一化植被指数(Normalized Difference Vegetation Index,NDVI)值，然后用R语言建立树轮宽度年表的长度与NDVI之间的一元线性回归模型，利用遥感影像数据良好的监测地表空间异质性的能力，实现对树轮年表长度在空间上连续的高分辨率的估算.将该信息作为树龄的一种近似替代，可以辅助树木年轮工作者快速、准确、定量地寻找到老龄树群.

关键词: 老龄树群, 遥感数据, 树轮年表长度, 归一化植被指数, R语言

Abstract:

In dendroclimatological studies,old trees should be sampled in order to reconstruct longer past climate. It has always taken a lot of efforts for dendrochronologists to find old trees in the fields,especially where old trees were cut for different purposes. However,there are not continuous and high?esolution data of tree ages in a large spatial scale at present in China. Therefore,to find a way to quickly locate old tree groups is urgently needed in tree?ring and even ecological communities. In this paper a method is proposed to locate old tree groups that uses the relationship between remote sensing data and published tree age data. The method is based on the well demonstrated recognition that some indicator calculated from remote sensing data and stand ages often have a significant relationship. A Landsat 8 OLI (Operational Land Imager/Thermal Infrared Sensor) 131/38 remoting sensing image,acquired on 3 October 2016,is used to calculate NDVI (Normalized Difference Vegetation Index) values. Generally,a tree?ring chronology is established using dozens of tree cores with missing rings and false rings being corrected for each core using the classical cross?dating technique. Therefore,the length of a chronology can represent the stand age well at the sampling site,and the lengths of the chronologies found in the study region are used as the stand age data. The stand age data are from 22 published tree?ring sampling sites which have specific tree?ring width chronologies’ lengths. Then,a simple linear regression model between the two proxies is established using R language. Finally,potential locations of old tree stands are indicated using the relationship between NDVI values and the lengths of the chronologies. The method proposed in this study could as an alternative to tree?age information,to help tree?ring researchers locate old tree stands quickly and accurately.

Key words: old trees, remote sensing data, tree?ring chronology’s length, normalized difference vegetation index, R language

中图分类号: 

  • TP301

图1

遥感影像Landsat 8 OLI 131/38"

表1

22个已发表树轮样点信息表"

文献来源

经度

(°E)

纬度(°N)起始年份终止年份校正后年表长度(a)NDVI

海拔

(m)

树种
郭明明等[18]102.80031.650184820111690.6382881铁杉(Tsuga chinensis)
102.85031.617176320112540.6313199岷江冷杉(Abies faxoniana)
102.78331.650176820112490.6463864岷江冷杉
102.73331.867183620111810.5893809四川红杉(Larix mastersiana)
郭明明等[19]102.26731.750179120122260.6003405岷江冷杉
102.03331.900169320123240.4182456岷江柏(Cupressus chengiana)
李金建等[20]101.71031.510171520103020.5833900-
吴普等[17]102.00031.500191720021000.7323234高山松(Pinus densata)
吴普等[21]101.00032.170169820033190.4992643红豆杉(Taxus chinensis)
102.07031.850176020022570.6103820鳞皮冷杉(Abies squamata)
102.08031.870178320032340.7333235铁杉
肖丁木等[22]101.70031.517171320103040.5893900川西云杉(Picea likiangensis var. balfouriana)
徐宁等[23]102.80831.689186320111540.6353095岷江冷杉
102.81331.675185720111600.7023453岷江冷杉
102.80131.700184220111750.6033773岷江冷杉
喻树龙等[24]100.81131.107170720053100.4623810川西云杉
102.16031.340176520052520.5623880川西云杉
101.80231.463175820052590.6074040鳞片冷杉
102.47632.161165920053580.4223630川西红杉
101.46332.545178720052300.5173680川西云杉
102.28831.716167920053380.5743800川西红杉

图2

回归模型及诊断结果(n=22)"

图3

树轮年表长度空间分布估算"

表2

Landsat 8 OLI 131/38遥感影像各年龄段像元数占比统计"

80~100年100~200年200~300年300~400年400~500年>500年
百分比(%)0.0938.8954.155.330.840.70
1 CookE R,KairiukstisL A. Methods of dendrochronology：Applications in the environ?mental sciences. Netherlands:Springer,1990：123-132.
2 吴祥定. 树木年轮与气候变化. 气象出版社,1990,145.
3 LiJ B,ShiJ F,ZhangD D,et al. Moisture increase in response to high?altitude warming evidenced by tree?rings on the southeastern Tibetan Plateau. Climate Dynamics,2017,48(1-2):649-660.
4 ShiJ F,LiJ B,ZhangD D,et al. Two centuries of April–July temperature change in southeastern China and its influence on grain productivity. Science Bulletin,2017,62(1)：40-45.
5 ShiJ F,LuH Y,LiJ B,et al. Tree?ring based February?April precipitation reconstruction for the lower reaches of the Yangtze River,southeastern China. Global and Planetary Change,2015,131：82-88.
6 ShiS Y,LiJ B,ShiJ F,et al. Three centuries of winter temperature change on the southeastern Tibetan Plateau and its relationship with the Atlantic Multidecadal Oscillation. Climate Dynamics,2017,49(4)：1305-1319.
7 ZhaoY S,ShiJ F,ShiS Y,et al. Tree?ring latewood width based July?August SPEI reconstruction in South China since 1888 and its possible connection with ENSO. Journal of Meteorological Research,2017,31(1)：39-48.
8 ZhaoY S,ShiJ F,ShiS Y,et al. Summer climate implications of tree–ring latewood width：a case study of Tsuga longibracteata in South China. Asian Geographer,2017,34(2)：131-146.
9 CohenW B,SpiesT A,FiorellaM. Estimating the age and structure of forests in a multi?ownership landscape of western Oregon,U.S.A. International Journal of Remote Sensing,1995,16(4)：721-746.
10 JensenJ R,QiuF,JiM H. Predictive modelling of coniferous forest age using statistical and artificial neural network approaches applied to remote sensor data. International Journal of Remote Sensing,1999,20(14)：2805-2822.
11 ChenB Q,CaoJ H,WangJ K,et al. Estimation of rubber stand age in typhoon and chilling injury afflicted area with Landsat TM data：A case study in Hainan Island,China. Forest Ecology and Management,2012,274：222-230.
12 KimC,HeoJ,LeeJ B,et al. A synergetic approach to estimating timber age using integrated remotely sensed optical image and InSAR height data. International Journal of Remote Sensing,2012,33(1)：243-260.
13 LiD Q,JuW M,FanW Y,et al. Estimating the age of deciduous forests in northeast China with Enhanced Thematic Mapper Plus data acquired in different phenological seasons. Journal of Applied Remote Sensing,2014,8(1)：083670.
14 TanK P,KanniahK D,CracknellA P. Use of UK?DMC 2 and ALOS PALSAR for studying the age of oil palm trees in southern peninsular Malaysia. International Journal of Remote Sensing,2013,34(20)：7424-7446.
15 XuC,MorgenrothJ,ManleyB. Integrating data from discrete return airborne LiDAR and optical sensors to enhance the accuracy of forest description：A review. Current Forestry Reports,2015,1(3)：206-219.
16 RouseJ W. Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation. NASA/GSFG,Type II Report. 1973–3.
17 吴普,王丽丽,邵雪梅. 采用高山松最大密度重建川西高原近百年夏季气温. 地理学报,2005,60(6)：998-1006.
WuP,WangL L,ShaoX M,. Reconstruction of summer temperature from maximum latewood density of Pinus densata in west Sichuan. Acta Geographica Sinica,2005,60(6)：998-1006.
18 郭明明,张远东,王晓春等. 川西米亚罗林区主要树木生长对气候响应的差异. 应用生态学报,2015,26(8)：2237-2243.
GuoM M,ZhangY D,WangX C,et al. Difference in responses of major tree species growth to climate in the Miyaluo Mountains,western Sichuan,China. Chinese Journal of Applied Ecology,2015,26(8)：2237-2243.
19 郭明明,张远东,王晓春等. 升温突变对川西马尔康树木生长的影响. 生态学报,2015,35(22)：7464-7474.
GuoM M,ZhangY D,WangX C,et al. Effects of abrupt warming on main conifer tree rings in Markang,Sichuan,China. Acta Ecologica Sinica,2015,35(22)：7464-7474.
20 李金建,邵雪梅,李媛媛等. 1854-2010年川西高原北部初夏气温变化与全球海表温度关系初探. 中国沙漠,2015,35(4)：1024-1035.
LiJ J,ShaoX M,LiY Y,et al. The relationship between early summer air temperature and the global sea surface temperature in the north of Western Sichuan Plateau from 1854 to 2010. Journal of Desert Research,2015,35(4)：1024-1035.
21 吴普,王丽丽,黄磊. 五个中国特有针叶树种树轮宽度对气候变化的敏感性. 地理研究,2006,25(1)：43-52.
WuP,WangL L,HuangL,. A preliminary study on the tree?ring sensitivity to climate change of five endemic conifer species in China. Geographical Research,2006,25(1)：43-52.
22 肖丁木,秦宁生,李金建等. 树轮记录的川西金川1713—2010年6月平均气温变化. 气候变化研究进展,2013,9(4)：252-257.
XiaoD M,QinN S,LiJ J,et al. Variations of june air temperature derived from tree-ring records in 1713-2010 in Jinchuan,West Sichuan Plateau,China. Progressus Inquisitiones De Mutatione Climatis,2013,9(4)：252-257.
23 徐宁,王晓春,张远东等. 川西米亚罗林区不同海拔岷江冷杉生长对气候变化的响应. 生态学报,2013,33(12)：3742-3751.
XuN,WangX C,ZhangY D,et al. Climate-growth relationships of Abies faxoniana from different elevations at Miyaluo,western Sichuan,China. Acta Ecologica Sinica,2013,33(12)：3742-3751.
24 喻树龙,袁玉江,魏文寿等. 川西高原6—7月最低气温场重建研究. 中国沙漠,2012,32(4)：1010-1016.
YuS L,YuanY J,WeiW S,et al. Reconstruction of minimum temperature field in June–July during 1787-2005 in the West Sichuan plateau. Journal of Desert Research,2012,32(4)：1010-1016.
25 田庆久,闵祥军. 植被指数研究进展. 地球科学进展,1998,13(4)：327-333.
Tian Q J,Min X J,. Advances in study on vegetation indices. Advance in Earth Science,1998,13(4)：327-333.
26 MiltonM.深入浅出数据分析.李芳译.北京：电子工业出版社，2012，330.
27 何晓群. 实用回归分析. 北京：高等教育出版社,2008,96-103.
28 李诗羽,张飞,王正林. 数据分析：R语言实战. 北京：电子工业出版社,2014,198.
29 唐年胜,李会琼. 应用回归分析. 北京：科学出版社,2014,104.
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