As the real source of the Yangtze River, Dam Qu Watershed is covered with a large number of alpine wetlands. Due to the dispute on the determination of the source of the Yangtze River in early years and difficulties in scientific research caused by the harsh natural environment, Dam Qu Watershed has not received widespread attention.Consequently, research on wetlands in this area is limited, particularly in high-resolution wetland classification, leaving a significant gap in the literature. Based on Sentinel-2B images from August 19, 2020, the information on each category of alpine wetlands in Dam Qu Watershed was extracted by using the hierarchical classification method of object-oriented features, and the horizontal and vertical distribution characteristics of wetlands were summarized in combination with the surface morphology and texture of the study area. The results show that the alpine wetlands in Dam Qu Watershed are divided into three first-level categories and nine second-level categories, with a total area of 3 364.74 km2, of which the main part is marsh wetlands, with an area of 2 908.94 km2, accounting for 86.45% of the total area of wetlands. The areas of river wetlands and lake wetlands are similar, at 269.28 km2 and 186.52 km2, respectively. In addition to alpine wetlands, there are permanent glaciers and snow in the watershed, with an area of 107.17 km2.The horizontal distribution of wetlands in the watershed is generally characterized by more wetlands in the southeast and fewer in the northwest. These wetlands are mainly concentrated in the flat beach surrounded by hills or the catchment area with low terrain and poor drainage, as well as the foot of shady slope. In the vertical direction, alpine wetlands are mainly distributed in the range of 4 650-5 100 m above sea level. As the terrain rises, wetland resources gradually decrease. Areas above 5 400 m are mainly covered by glaciers and snow, with almost no alpine wetland. This study provides a scientific basis for the effective protection and rational utilization of wetland resources in the source of the Yangtze River.
[1] 吕宪国.湿地生态系统保护与管理[M].北京:化学工业出版社, 2004.
[2] 白军红,欧阳华,徐惠风,等.青藏高原湿地研究进展[J].地理科学进展, 2004, 23(4):1-9.DOI:10.11820/dlkxjz.2004.04.001.
[3] 张继平,张镱锂,刘峰贵,等.长江源区当曲流域高寒湿地类型划分及分布研究[J].湿地科学, 2011, 9(3):218-226. DOI:10.13248/j.cnki.wetlandsci.2011.03.011.
[4] 汪爱华,张树清,张柏.遥感和地理信息系统技术在湿地研究中的应用[J].遥感技术与应用, 2001, 16(3):200-204. DOI:10.3969/j.issn.1004-0323.2001.03.013.
[5] Di Vittorio C A, Georgakakos A P. Land cover classification and wetland inundation mapping using MODIS[J]. Remote Sensing of Environment, 2018, 204:1-17. DOI:10.1016/j.rse.2017.11.001.
[6] 张树文,颜凤芹,于灵雪,等.湿地遥感研究进展[J].地理科学, 2013, 33(11):1406-1412.DOI:10.13249/j.cnki.sgs.2013.11.012.
[7] 侯蒙京,高金龙,葛静,等.青藏高原东部高寒沼泽湿地动态变化及其驱动因素研究[J].草业学报, 2020, 29(1):13-27. DOI:10.11686/cyxb2019148.
[8] 褚琳,黄翀,刘高焕,等. 2000-2010年黄河源玛曲高寒湿地生态格局变化[J].地理科学进展, 2014, 33(3):326-335. DOI:10.11820/dlkxjz.2014.03.004.
[9] 王海军.川西高寒湿地多源遥感监测及其时空变化特征研究[D].成都:成都理工大学, 2021.DOI:10.26986/d.cnki.gcdlc.2021.000058.
[10] 康应东,李晓燕,毛德华,等.云贵高原国际重要湿地景观人为胁迫遥感解析[J].生态学杂志, 2020, 39(10):3379-3387. DOI:10.13292/j.1000-4890.202010.005.
[11] 燕云鹏,徐辉,邢宇,等. 1975-2007年间三江源不同源区湿地变化特点及对气候变化的响应[J].测绘通报, 2015(S2):5-10.DOI:10.13474/j.cnki.11-2246.2015.0674.
[12] 温兆飞,张树清,陈春,等.三江源区湖泊和沼泽遥感影像分类研究[J].湿地科学, 2010, 8(2):132-138. DOI:10.13248/j.cnki.wetlandsci.2010.02.013.
[13] 邹文涛,张怀清,鞠洪波,等.基于决策树的高寒湿地类型遥感分类方法研究[J].林业科学研究, 2011, 24(4):464-469.DOI:10.13275/j.cnki.lykxyj.2011.04.022.
[14] Landmann T, Schramm M, Colditz R R, et al. Wide area wetland mapping in semi-arid Africa using 250-meter MODIS metrics and topographic variables[J]. Remote Sensing, 2010, 2(7):1751-1766.DOI:10.3390/rs2071751.
[15] Dronova I, Gong P, Clinton N E, et al. Landscape analysis of wetland plant functional types:the effects of image segmentation scale, vegetation classes and classification methods[J]. Remote Sensing of Environment, 2012, 127:357-369. DOI:10.1016/j.rse.2012.09.018.
[16] 青海省测绘地理信息局,武汉大学.三江源头科学考察地图集[M].北京:中国地图出版社, 2015.
[17] 陈进.长江源--当曲水系及其生态系统特征探讨[J].长江科学院院报, 2014, 31(10):1-6.DOI:10.3969/j.issn.1001-5485.2014.10.02.
[18] 黄桂林.青海三江源区湿地状况及保护对策[J].林业资源管理, 2005(4):35-39.DOI:10.13466/j.cnki.lyzygl.2005.04.009.
[19] 贾岸斌,佘高杰,卢舟,等.基于数字高程模型的河网和流域边界提取[J].陕西气象, 2020(2):43-47. DOI:10.3969/j.issn.1006-4354.2020.02.008.
[20] 国家质量监督检验检疫总局,中国国家标准化管理委员会.湿地分类:GB/T 24708-2009[S].北京:中国标准出版社, 2010.
[21] 罗开盛,陶福禄.融合面向对象与缨帽变换的湿地覆被类别遥感提取方法[J].农业工程学报, 2017, 33(3):198-203. DOI:10.11975/j.issn.1002-6819.2017.03.027.
[22] Nedkov R. Orthogonal transformation of segmented images from the satellite Sentinel-2[J/OL]. Comptes rendus de l'Academie bulgare des Sciences, 2017, 70(5):687-691(2017-05-31)[2023-03-28]. https://www.researchgate.net/publication/329183655_ORTHOGONAL_TRANSFOR-MATION_OF_SEGMENTED_IMAGES_FROM_THE_SATELLITE_SENTINEL-2_Roumen_Nedkov.
[23] 徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报, 2005, 9(5):589-595. DOI:10.3321/j.issn:1007-4619.2005.05.012.
[24] Hill M J. Vegetation index suites as indicators of vegetation state in grassland and savanna:an analysis with simulated SENTINEL 2 data for a North American transect[J]. Remote Sensing of Environment, 2013, 137:94-111. DOI:10.1016/j.rse.2013.06.004.
[25] 黄昕.高分辨率遥感影像多尺度纹理、形状特征提取与面向对象分类研究[D].武汉:武汉大学, 2009.
[26] 侯群群,王飞,严丽.基于灰度共生矩阵的彩色遥感图像纹理特征提取[J].国土资源遥感, 2013, 25(4):26-32. DOI:10.6046/gtzyyg.2013.04.05.
[27] 黄慧萍,吴炳方.地物提取的多尺度特征遥感应用分析[J].遥感技术与应用, 2003, 18(5):276-281. DOI:10.3969/j.issn.1004-0323.2003.05.002.
[28] 赵英时,等.遥感应用分析原理与方法[M]. 2版.北京:科学出版社, 2013.
[29] 刘炜,王聪华,赵尔平,等.基于分层分级的遥感图像植被分类方法[J].中国矿业大学学报, 2016, 45(4):828-835. DOI:10.13247/j.cnki.jcumt.000544.
[30] 周宇津.基于决策树的多分类器遥感影像分层分类研究与系统实现[D].武汉:华中科技大学, 2012.
[31] 宋伟东,杨冬,李恩宝,等.盘锦市湿地信息提取与动态变化监测[J].测绘科学, 2016, 41(9):60-65, 79.DOI:10.16251/j.cnki.1009-2307.2016.09.013.
[32] 颜凤芹,于灵雪,杨朝斌,等.基于Landsat 8影像的湿地信息提取最佳波段组合[J].地球环境学报, 2014, 5(5):339-343, 352. DOI:10.7515/JEE201405005.
[33] 张继平,刘林山,张镱锂,等.面向对象的极高海拔区水体及冰川信息提取:以珠穆朗玛峰国家级自然保护区核心区为例[J].地球信息科学学报, 2010, 12(4):517-523.
[34] 杨朝辉,白俊武,陈志辉,等.利用Sentinel-2A影像的面向对象特征湿地决策树分类方法[J].测绘科学技术学报, 2019, 36(3):262-268.DOI:10.3969/j.issn.1673-6338.2019.03.008.
[35] 杨娅楠,习晓环,王成,等.基于缨帽变换与匹配滤波的大熊猫生境影像分类[J].中国科学院大学学报, 2015, 32(6):797-802.DOI:10.7523/j.issn.2095-6134.2015.06.011.
[36] 刘勇洪,牛铮,徐永明,等.多种分类器在华北地区土地覆盖遥感分类中的性能评价[J].中国科学院研究生院学报, 2005, 22(6):724-732.DOI:10.7523/j.issn.2095-6134.2005.6.011.
[37] 孙永军.黄河流域湿地遥感动态监测研究[D].北京:北京大学, 2008.
[38] 段鹏,姚步青,赵之重,等.黄河源区季节性湖泊湿地退化对土壤微生物碳源利用的影响[J].草地学报, 2022, 30(11):2975-2985.DOI:10.11733/j.issn.1007-0435.2022.11.014.
[39] 青海省市场监督管理局.高寒湿地遥感分类技术指南:DB63/T 1746-2019[S/OL].(2019-06-19)[2019-09-01].http://www.csres.com/detail/338757.html.
