[1] 高谦. 中国苔藓志:第1卷[M]. 北京:科学出版社, 1994.
[2] Yu ZC. Northern peatland carbon stocks and dynamics:a review[J]. Biogeosciences, 2012, 9(10):4071-4085.
[3] Baird AJ, Belyea LR, Comas X, Reeve AS, Slater LD. Carbon Cycling in Northern Peatlands[DB/OL].[2019-03-05]. https://doi.org/10.1029/GM184.
[4] Huang XY, Pancost RD, Xue JT, Gu YS, Evershed RP, et al. Response of carbon cycle to drier conditions in the mid-Holocene in central China[J]. Nat Commun, 2018, 9(1):1369.
[5] Limpens J, Berendse F, Blodau C, Canadell J G, Freeman C, et al. Peatlands and the carbon cycle:from local processes to global implications-a synthesis[J]. Biogeosciences, 2008, 5(6):1475-1491.
[6] Treat C, Wisser D, Marchenko S, Frolking S. Modelling the effects of climate change and disturbance on permafrost stability in northern organic soils[J]. Mires Peat, 2013, 12(2):1-17.
[7] Limpens J, Granath G, Gunnarsson U, Aerts R, Bayley S, et al. Climatic modifiers of the response to nitrogen deposition in peat-forming Sphagnum mosses:a meta-analysis[J]. New Phytol, 2011, 191(2):496-507.
[8] Spahni R, Joos F, Stocker BD, Steinacher M, Yu ZC. Transient simulations of the carbon and nitrogen dynamics in northern peatlands:from the Last Glacial Maximum to the 21st century[J]. Clim Past, 2013, 9(3):1287-1308.
[9] Vogelmann JE, Moss DM. Spectral reflectance measurements in the genus Sphagnum[J]. Remote Sens Environ, 1993, 45(3):273-279.
[10] Bubier JL, Moore TR. An ecological perspective on methane emissions from northern wetlands[J]. Trends Ecol Evol, 1994, 9(12):460-464.
[11] Harris A, Bryant RG, Baird AJ. Detecting near-surface moisture stress in Sphagnum spp.[J]. Remote Sens Environ, 2005, 97(3):371-381.
[12] Harris A, Bryant RG, Baird AJ. Mapping the effects of water stress on Sphagnum:Preliminary observations using airborne remote sensing[J]. Remote Sens Environ, 2006, 100(3):363-378.
[13] Harris A. Spectral reflectance and photosynthetic properties of Sphagnum mosses exposed to progressive drought[J]. Ecohydrology, 2010, 1(1):35-42.
[14] Neta T, Cheng Q, Bello RL, Hu B. Lichens and mosses moisture content assessment through high-spectral resolution remote sensing technology:a case study of the Hudson Bay Lowlands, Canada[J]. Hydrol Process, 2010, 24(18):2617-2628.
[15] Neta T, Cheng Q, Bello RL, Hu B. Development of new spectral reflectance indices for the detection of lichens and mosses moisture content in the Hudson Bay Lowlands, Canada[J]. Hydrol Process, 2015, 25(6):933-944.
[16] Meingast KM, Falkowski MJ, Kane ES, Potvin L, Benscoter B, et al. Spectral detection of near-surface moisture content and water-table position in northern peatland ecosystems[J]. Remote Sens Environ, 2014, 152:536-546.
[17] 由佳, 张怀清, 陈永富, 高志海, 刘华. 基于GF-4号卫星影像东洞庭湖湿地植被类型监测能力比较研究[J]. 安徽农业科学, 2018, 46(3):152-156. You J, Zhang HQ, Chen YF, Gao ZH, Liu H. Based on the GF-4 satellite image for the east Dongting Lake wetland vegetation type monitoring ability[J]. Anhui Agricultural Science, 2018, 46(3):152-156.
[18] 柴颖, 阮仁宗, 傅巧妮, 岁秀珍. 面向对象的高光谱影像湿地植被信息提取[J]. 地理空间信息, 2015, 13(4):83-85. Chai Y, Ruan RZ, Fu QN, Sui XZ. Object-oriented information extraction of wetland vegetation using hyperspectral image data[J]. Geospatial Information, 2015, 13(4):83-85.
[19] 张雪薇, 韩震, 刘美君, 丁如一. 长江口南汇湿地植被的光谱吸收特征研究[J]. 海洋学研究, 2018, 36(2):50-54. Zhang XW, Han Z, Liu MJ, Ding RY. Study on spectral absorption characteristics of vegetation in Nanhui Wetland of Yangtze River estuary[J]. Journal of Marine Sciences, 2018, 36(2):50-54.
[20] 黄灵光, 周学林. 南矶湿地国家自然保护区典型植被光谱波段特征分析及建库[J]. 湖北农业科学, 2018, 57(11):103-106. Huang LG, Zhou XL. Characteristic analysis and database construction of typical vegetation spectral band in Nanji Wetland National Nature Reserve[J]. Hubei Agricultural Sciences, 2018, 57(11):103-106.
[21] 凌成星, 刘华, 鞠洪波, 张怀清, 孙华, 等. 基于地面成像光谱数据特征的湿地典型植被类型识别研究:以东洞庭湖核心区湿地为例[J]. 西北林学院学报, 2018, 33(3):208-213. Ling CX, Liu H, Ju HB, Zhang HQ, Sun H, et al. Identifying typical wetland vegetation types based on imaging spectrometer data:a case studying Dongting Lake Wetland area[J]. Journal of Northwest Forestry University, 2018, 33(3):208-213.
[22] 冯家莉, 刘凯, 朱远辉, 李勇, 柳林, 等. 无人机遥感在红树林资源调查中的应用[J]. 热带地理, 2015, 35(1):35-42. Feng JL, Liu K, Zhu YH, LI Yong, Liu L, et al. Application of unmanned aerial vehicles to mangrove resources monitoring[J]. Tropical Geography, 2015, 35(1):35-42.
[23] Adam E, Mutanga O, Rugege D. Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation:a review[J]. Wet Ecol Manag, 2010, 18(3):281-296.
[24] 杨立君, 马明栋, 唐立军. 基于TM影像的崇明东滩湿地植被分类研究[J]. 水土保持研究, 2013, 20(1):126-130. Yang LJ, Ma MD, Tang LJ. Research on wetland vegetation classification of Chongming Easter Tidal Flat based on TM image[J]. Research of Soil and Water Conservation, 2013, 20(1):126-130.
[25] 刘春燕, 张雪红, 陈健. 基于决策树的角度指数方法EO-1 ALI影像的红树林遥感识别[J]. 湿地科学, 2015, 13(4):451-455. Liu CY, Zhang XH, Chen J. Identifying mangrove forest with EO-1 ALI imagery combining decision tree with angle indices[J]. Wetland science, 2015, 13(4):451-455.
[26] Kokaly RF, Clark RN, Swayze GA, Livo KE, Hoefen TM, et al. USGS spectral library version 7[DB/OL].[2019-03-05]. https://doi.org/10.3133/ds1035.
[27] 王锦地, 张立新, 柳钦火, 等. 中国典型地物波谱知识库[M]. 北京:科学出版社, 2009.
[28] Liu ZY, Wu HF, Huang JF. Application of neural networks to discriminate fungal infection levels in rice panicles using hyperspectral reflectance and principal components analysis[J]. Comput Electron Agr, 2010, 72(2):99-106.
[29] 林海军, 张绘芳, 高亚琪, 李霞, 杨帆, 等. 基于马氏距离法的荒漠树种高光谱识别[J]. 光谱学与光谱分析, 2014, 34(12):3358-3362. Lin HJ, Zhang HF, Gao YQ, Li X, Yang F, et al. Maha-lanobis distance based hyperspectral characteristic discrimination of characteristic discrimination of leaves of different desert tree species[J]. Spectroscopy and spectral analysis, 2014, 34(12):3358-3362.
[30] 丁丽霞, 王志辉, 葛宏立. 基于包络线法的不同树种叶片高光谱特征分析[J].浙江林学院学报, 2010, 27(6):809-814. Ding LX, Wang ZH, Ge HL. Continuum removal based hyperspectral characteristic analysis of leaves of different tree species[J]. Journal of Zhejiang Forestry College, 2010, 27(6):809-814. |