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纸质出版日期： 2022-03-07 ，
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江鑫，何心悦，王大山，邹俊宇，曾振中.2022.利用高分辨率森林覆盖影像实现高山林线的自动提取.遥感学报，26（3）： 456-467
Jiang X， He X Y， Wang D S， Zou J Y and Zeng Z Z. 2022. Automatic alpine treeline extraction using high-resolution forest cover imagery. National Remote Sensing Bulletin， 26（3）：456-467
快速准确地提取高山林线对标定全球气候变化、科学管理森林资源具有重要意义。秦岭高山林线位于高海拔的生态交错带，垂直带谱分布明显，为本文提供了理想的试验区域。遥感技术具有重访周期短、观测范围大和不受地理环境等条件限制的特点，克服了传统实地调查方法效率低、成本高等缺点。本文基于全球首套30 m空间分辨率森林覆盖数据，结合数字高程模型以及秦岭山脉分布数据，提出一种基于遥感的自动提取高山林线的算法；结合高分辨率的Google Earth影像和GPS地面站点观测数据以及NDVI数据，验证高山林线提取结果的准确性；基于高程数据系统分析研究区高山林线分布与地形特征的关系。结果表明：（1）本文结果与Google Earth影像中实际林线分布基本一致，进一步说明本文提出的林线搜索算法的优越性；（2）秦岭林线高程分布特征呈现显著的坡向差异，呈现南坡林线高于北坡，东坡林线高于西坡的特征。鉴于遥感技术的大范围对地观测的能力，以及卫星影像数据较高的数据质量和易获取性，本文提出的分块迭代搜索策略适用于寻找不同级别的高山林线分布，可进一步推广至全球高山林线制图研究，以期为全球山地生态系统监测、保护和恢复提供技术支撑。
Alpine treeline is not only an important source in calibrating global climate change but also a fundamental element in scientifically managing forest resources. Furthermore
the location
area size
and change patterns of forest lines are also used as essential information in monitoring and modeling the environment. The alpine forest line of the Qinling Mountains is located in the ecological staggered zone at high altitude
with an obvious distribution of altitudinal spectrum
which is an important north-south geographical dividing line in China. Therefore
a novel approach for the rapid and accurate identification of alpine treeline in the Qinling Mountains must be developed.
We propose a remote-sensor-based algorithm for extracting alpine treelines in the Qinling Mountains by combining the high-resolution global forest cover data in 2000 with a digital elevation model and mountain distribution data. Specifically
tree cover is first extracted from the forest cover data. Next
the highest point of the study area is determined from the elevation data. Finally
the 8-connected domain search algorithm is employed to find the boundary between forest and non-forest covers to determine the alpine treeline. The algorithm is validated by high-resolution Google Earth images
GPS ground-based data
and the NDVI dataset. Further
we systematically investigate the relationship between the alpine treeline distribution and geographical factors (elevation
slope
and aspect) in the study area using the elevation data.
The distribution of treelines in this paper is consistent with the actual treelines distribution in Google Earth images
further demonstrating the performance of the proposed algorithm. The elevation of treelines in the Qinling Mountains ranges from 2400 m to 3800 m. The treelines are concentrated in steep slope areas ranging from 15° to 55°. The distribution of alpine treeline elevation shows significant slope differences
with the treeline on the south slope being higher than those on the north slope
and the treelines on the east slope being higher than those on the west slope.
The treelines obtained by our algorithm match the actual treelines in the Google Earth images of the study area well
showing an outstanding performance in the integrity and boundary connectivity of treelines. Given the capability of remote sensing technology to observe the Earth in a large scale and the high data quality and accessibility of satellite image data
the proposed algorithm for extracting alpine treelines can be further applied to global treeline mapping to provide technical support for global mountain ecosystem monitoring
conservation
and restoration.
高山林线遥感自动提取空间分布全球
alpine treelineremote sensingautomatic extractionspatial distributionglobal
Bai H Y, Zhang S H and Zhang J. 2011. A study on the spatial and temporal variation of vegetation in the Taibai Mountains and its alpine line change. Beijing: China Environmental Science Press: 2886-2897
白红英, 张善红, 章杰. 2011. 太白山植被时空变化及其高山林线变化研究//中国环境科学学会学术年会论文集. 北京: 中国环境科学出版社: 2886-2897
Bharti R R, Adhikari B S and Rawat G S. 2012. Assessing vegetation changes in timberline ecotone of Nanda Devi National Park, Uttarakhand. International Journal of Applied Earth Observation and Geoinformation, 18: 472-479 [DOI: 10.1016/j.jag.2011.09.018http://dx.doi.org/10.1016/j.jag.2011.09.018]
Bian R, Gou X H and Nian Y Y. 2020. Spatial distribution and influencing factors of Picea crassifolia treelines on northern slopes of the Qilian Mountains. Journal of Lanzhou University (Natural Sciences), 56(6): 711-717
边瑞, 勾晓华, 年雁云. 2020. 祁连山北坡青海云杉林线的空间分布及影响因素. 兰州大学学报(自然科学版), 56(6): 711-717 [DOI: 10.13885/j.issn.0455-2059.2020.06.001http://dx.doi.org/10.13885/j.issn.0455-2059.2020.06.001]
Chen J, Liao A P, Chen J, Peng S, Chen L J and Zhang H W. 2017. 30-meter global land cover data product-GlobeLand30. WorldGeomatics, 24(1): 1-8
陈军, 廖安平, 陈晋, 彭舒, 陈利军, 张宏伟. 2017. 全球30 m地表覆盖遥感数据产品-GlobeLand30. 地理信息世界, 24(1): 1-8
Cui H T. 1983. On the delineation of the alpine and subalpine zones in the North China Mountains. Chinese Science Bulletin, 28(8): 494-497
崔海亭. 1983. 关于华北山地高山带和亚高山带的划分问题. 科学通报, 28(8): 494-497
Dai J H, Cui H T, Tang Z Y and Huang Y M. 2001. Characteristics of alpine physical environment on Taibai Mountain. Journal of Mountain Science, 19(4): 299-305
戴君虎, 崔海亭, 唐志尧, 黄永梅. 2001. 太白山高山带环境特征. 山地学报, 19(4): 299-305 [DOI: 10.3969/j.issn.1008-2786.2001.04.002http://dx.doi.org/10.3969/j.issn.1008-2786.2001.04.002]
Dang H S, Zhang Y L, Zhang Y J, Zhang K R and Zhang Q F. 2015. Variability and rapid response of subalpine fir (Abies fargesii) to climate warming at upper altitudinal limits in north-central China. Trees, 29(3): 785-795 [DOI: 10.1007/s00468-015-1156-9http://dx.doi.org/10.1007/s00468-015-1156-9]
Deng C H, Bai H Y, Gao S, Huang X Y, Meng Q, Zhao T, Zhang Y, Su K and Guo S Z. 2018. Comprehensive effect of climatic factors on plant phenology in Qinling Mountains region during 1964-2015. Acta Geographica Sinica, 73(5): 917-931
邓晨晖, 白红英, 高山, 黄晓月, 孟清, 赵婷, 张扬, 苏凯, 郭少壮. 2018. 1964-2015年气候因子对秦岭地区植物物候的综合影响效应. 地理学报, 73(5): 917-931 [DOI: 10.11821/dlxb201805011http://dx.doi.org/10.11821/dlxb201805011]
Fiorio C and Gustedt J. 1996. Two linear time Union-Find strategies for image processing. Theoretical Computer Science, 154(2): 165-181 [DOI: 10.1016/0304-3975(94)00262-2http://dx.doi.org/10.1016/0304-3975(94)00262-2]
Food and Agriculture Organization (FAO). 2018. Global Forest Resources Assessment 2020: Terms and Definitions. FAO
Gehrig-Fasel J, Guisan A and Zimmermann N E. 2007. Tree line shifts in the Swiss Alps: climate change or land abandonment?. Journal of Vegetation Science, 18(4): 571-582 [DOI: 10.1111/j.1654-1103.2007.tb02571.xhttp://dx.doi.org/10.1111/j.1654-1103.2007.tb02571.x]
Gong P. 2021. Intelligent mapping with remote sensing, iMap. National Remote Sensing Bulletin, 25(2): 527-529
宫鹏. 2021. 智慧遥感制图(iMap). 遥感学报, 25(2): 527-529 [DOI: 10.11834/jrs.20211010http://dx.doi.org/10.11834/jrs.20211010]
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 F 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.2019.03.002http://dx.doi.org/10.1016/j.scib.2019.03.002]
Gruber A, Baumgartner D, Zimmermann J and Oberhuber W. 2009. Temporal dynamic of wood formation in Pinus cembra along the alpine treeline ecotone and the effect of climate variables. Trees, 23(3): 623-635 [DOI: 10.1007/s00468-008-0307-7http://dx.doi.org/10.1007/s00468-008-0307-7]
Hansen M C, Potapov P V, Moore R, Hancher M, Turubanova S A, Tyukavina A, Thau D, Stehman S V, Goetz S J, Loveland T R, Kommareddy A, Egorov A, Chini L, Justice C O and Townshend J R G. 2013. High-resolution global maps of 21st-century forest cover change. Science, 342(6160): 850-853 [DOI: 10.1126/science.1244693http://dx.doi.org/10.1126/science.1244693]
Jing X J. 2019. Inversion of Soil Water Content Based on Sentinel-1A and Landsat-8 OLI Images—Beiluhe of northern Tibet. Beijing: China University of Geosciences
荆雪娟. 2019. 基于Sentinel-1A SAR与Landsat-8 OLI影像的土壤含水量反演—北麓河流域. 北京: 中国地质大学(北京)) [DOI: 10.27493/d.cnki.gzdzy.2019.000682http://dx.doi.org/10.27493/d.cnki.gzdzy.2019.000682]
Körner C and Paulsen J. 2004. A world-wide study of high altitude treeline temperatures. Journal of Biogeography, 31(5): 713-732 [DOI: 10.1111/j.1365-2699.2003.01043.xhttp://dx.doi.org/10.1111/j.1365-2699.2003.01043.x]
Král K. 2009. Classification of current vegetation cover and alpine treeline ecotone in the Praděd reserve (Czech Republic), using remote sensing. Mountain Research and Development, 29(2): 177-183 [DOI: 10.1659/mrd.1077http://dx.doi.org/10.1659/mrd.1077]
Kullman L. 2001. 20th century climate warming and tree-limit rise in the southern Scandes of Sweden. Ambio, 30(2): 72-80 [DOI: 10.1579/0044-7447-30.2.72http://dx.doi.org/10.1579/0044-7447-30.2.72.]
Li M H and Kräuchi N. 2005. The state of knowledge on alpine treeline and suggestions for future research. Journal of Sichuan Forestry Science and Technology, 26(4): 36-42
李迈和, Kräuchi N. 2005. 全球高山林线研究现状与发展方向. 四川林业科技, 26(4): 36-42 [DOI: 10.16779/j.cnki.1003-5508.2005.04.006http://dx.doi.org/10.16779/j.cnki.1003-5508.2005.04.006]
Li N. 2019. Study on the Regeneration Characteristics and Population Diffusion of Larix chinensis Forest. Yangling: Northwest A&F University
李娜. 2019. 太白红杉林更新特征与种群扩散研究. 杨凌: 西北农林科技大学
Liu L Y, Zhang X, Gao Y, Chen X D, Shuai X and Mi J. 2021. Finer-resolution mapping of global land cover: recent developments, consistency analysis, and prospects. Journal of Remote Sensing, 2021: 5289697 [DOI: 10.34133/2021/5289697http://dx.doi.org/10.34133/2021/5289697]
Liu T and Kang M Y. 2016. Primary study on alpine timberline of Helan mountain using RS and GIS. Journal of Natural Resources, 31(6): 973-981
刘锬, 康慕谊. 2016. 基于RS和GIS的贺兰山高山林线初步研究. 自然资源学报, 31(6): 973-981 [DOI: 10.11849/zrzyxb.20150707http://dx.doi.org/10.11849/zrzyxb.20150707]
Liu X P, Huang Y H, Xu X C, Li X C, Li X, Ciais P, Lin P R, Gong K, Ziegler A D, Chen A P, Gong P, Chen J, Hu G H, Chen Y M, Wang S J, Wu Q S, Huang K N, Estes L and Zeng Z Z. 2020. High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. Nature Sustainability, 3(7): 564-570 [DOI: 10.1038/s41893-020-0521-xhttp://dx.doi.org/10.1038/s41893-020-0521-x]
Lu X M, Liang E Y, Wang Y F, Babst F and Camarero J J. 2021. Mountain treelines climb slowly despite rapid climate warming. Global Ecology and Biogeography, 30(1): 305-315 [DOI: 10.1111/geb.13214http://dx.doi.org/10.1111/geb.13214]
Luo G P and Dai L. 2013. Detection of alpine tree line change with high spatial resolution remotely sensed data. Journal of Applied Remote Sensing, 7(1): 073520 [DOI: 10.1117/1.JRS.7.073520http://dx.doi.org/10.1117/1.JRS.7.073520]
Ma X P. 2015. The Timberline of Qinling Mountains and its Response to Climate Change. Xi’an: Northwest University: 15-33
马新萍. 2015. 秦岭林线及其对气候变化的响应. 西安: 西北大学: 15-33
Malyshev L. 1993. Levels of the upper forest boundary in northern Asia. Vegetatio, 109(2): 175-186 [DOI: 10.1007/BF00044749http://dx.doi.org/10.1007/BF00044749]
Qin J, Bai H Y, Liu R J, Zhai D P, Su K, Wang J and Li S H. 2017. Reconstruction of March-June mean air temperature along the timberline of Mount Taibai, Qinling mountains, northwest China, over the last 144 years. Acta Ecologica Sinica, 37(22): 7585-7594
秦进, 白红英, 刘荣娟, 翟丹平, 苏凯, 王俊, 李书恒. 2017. 近144年来秦岭太白山林线区3-6月平均气温的重建. 生态学报, 37(22): 7585-7594 [DOI: 10.5846/stxb201609191884http://dx.doi.org/10.5846/stxb201609191884]
Shao J Y, Du J H, Li S F, Huang Y X, Liang W N and Liao J Q. 2019. Tree seedling distribution, regeneration mechanism and response to climate change in alpine treeline ecotone. Chinese Journal of Applied Ecology, 30(8): 2854-2864
邵佳怡, 杜建会, 李升发, 黄一鑫, 梁伟诺, 廖家强. 2019. 高山林线生态交错区木本植物幼苗分布特征、更新机制及其对气候变化的响应. 应用生态学报, 30(8): 2854-2864 [DOI: 10.13287/j.1001-9332.201908.007http://dx.doi.org/10.13287/j.1001-9332.201908.007]
Shi H, Zhou Q, Xie F L, He N J, He R, Zhang K R, Zhang Q F and Dang H S. 2020. Disparity in elevational shifts of upper species limits in response to recent climate warming in the Qinling Mountains, North-central China. Science of the Total Environment, 706: 135718 [DOI: 10.1016/j.scitotenv.2019.135718http://dx.doi.org/10.1016/j.scitotenv.2019.135718]
Shi J. 2002. Study on GIS for the Management and Sharing of Forest Resource Information in Mao’r mountain. Harbin: Northeast Forestry University
史军. 2002. 帽儿山地区森林资源信息管理及共享的GIS研究. 哈尔滨: 东北林业大学
Solaimani K and Shokrian F. 2011. Detection of ecotone environment based on satellite and field techniques (A case study; Northern Alborz, Iran). African Journal of Microbiology Research, 5(25): 4267-4272 [DOI: 10.5897/AJMR10.658http://dx.doi.org/10.5897/AJMR10.658]
Tang X M, Li S J, Li T, Gao Y D, Zhang S B, Chen Q F and Zhang X. 2021. Review on global digital elevation products. National Remote Sensing Bulletin, 25(1): 167-181
唐新明, 李世金, 李涛, 高延东, 张书毕, 陈乾福, 张祥. 2021. 全球数字高程产品概述. 遥感学报, 25(1): 167-181 [DOI: 10.11834/jrs.20210210http://dx.doi.org/10.11834/jrs.20210210]
Tang Z Y, Dai J H and Huang Y M. 1999. Quantitative analysis of the vegetation near the alpine timberline of Taibai mountain. Journal of Mountain Science, 17(4): 294-298
唐志尧, 戴君虎, 黄永梅. 1999. 太白山高山林线植被的数量分析. 山地学报, 17(4): 294-298
Theurillat J P and Guisan A. 2001. Potential impact of climate change on vegetation in the European Alps: a review. Climatic Change, 50(1): 77-109 [DOI: 10.1023/A:1010632015572http://dx.doi.org/10.1023/A:1010632015572]
Tranquillini W. 1979. Physiological Ecology of the Alpine Timberline: Tree Existence at High Altitudes with Special Reference to the European Alps. Berlin, Heidelberg: Springer [DOI: 10.1007/978-3-642-67107-4http://dx.doi.org/10.1007/978-3-642-67107-4]
Wang X C, Zhou X F and Sun Z H. 2005. Research advances in the relationship between alpine timberline and climate change. Chinese Journal of Ecology, 24(3): 301-305
王晓春, 周晓峰, 孙志虎. 2005. 高山林线与气候变化关系研究进展. 生态学杂志, 24(3): 301-305
Wang X P, Zhang L and Fang J Y. 2004. Geographical differences in alpine timberline and its climatic interpretation in China. Acta Geographica Sinica, 59(6): 871-879
王襄平, 张玲, 方精云. 2004. 中国高山林线的分布高度与气候的关系. 地理学报, 59(6): 871-879 [DOI: 10.11821/xb200406009http://dx.doi.org/10.11821/xb200406009]
Wang Y F, Lu X M, Zhu H F and Liang E Y. 2020. Field survey and research approaches at apine treelines. Advances in Earth Science, 35(1): 38-51
王亚锋, 芦晓明, 朱海峰, 梁尔源. 2020. 高山树线的调查与研究方法. 地球科学进展, 35(1): 38-51 [DOI: 10.11867/j.issn.1001-8166.2020.004http://dx.doi.org/10.11867/j.issn.1001-8166.2020.004]
Wang Y J, Liu L Y and Wang Z H. 2015. Land Cover mapping based on Landsat time-series stacks in Sanjiang Plain. Remote Sensing Technology and Application, 30(5): 959-968
王颖洁, 刘良云, 王志慧. 2015. 基于时序Landsat数据的三江平原植被地表类型变化遥感探测研究. 遥感技术与应用, 30(5): 959-968 [DOI: 10.11873/j.issn.1004-0323.2015.5.0959http://dx.doi.org/10.11873/j.issn.1004-0323.2015.5.0959]
Wu K S, Otoo E and Shoshani A. 2005. Optimizing connected component labeling algorithms//Proceedings Volume 5747, Medical Imaging 2005: Image Processing. San Diego, California, United States: SPIE: 1965-1976 [DOI: 10.1117/12.596105http://dx.doi.org/10.1117/12.596105]
Yang X Y, Gao Y S, Cheng Y, Wang H Y and Liu H Y. 2020. Response of different altitude vegetation to climate change in Taibai Mountain alpine zone during the past about 2000 years. Acta Scientiarum Naturalium Universitatis Pekinensis, 56(5): 844-854
杨秀云, 高艺珅, 程颖, 王红亚, 刘鸿雁. 2020. 近2000年来太白山高山带不同海拔植被对气候变化的响应. 北京大学学报(自然科学版), 56(5): 844-854 [DOI: 10.13209/j.0479-8023.2020.053http://dx.doi.org/10.13209/j.0479-8023.2020.053]
Zhang Y, Kong Z C, Yan S, Yang Z J and Ni J. 2006. Fluctuation of Picea timber-line and paleo-environment on the northern slope of Tianshan Mountains during the late Holocene. Chinese Science Bulletin, 51(14): 1747-1756 [DOI: 10.1007/s11434-006-2029-9http://dx.doi.org/10.1007/s11434-006-2029-9]
Zheng H R, Du P J, Chen J K, Xia J S, Li E Z, Xu Z G, Li X J and Yokoya N. 2017. Performance evaluation of downscaling Sentinel-2 imagery for land use and land cover classification by spectral-spatial features. Remote Sensing, 9(12): 1274 [DOI: 10.3390/rs9121274http://dx.doi.org/10.3390/rs9121274]
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