[1] BabinM, MorelA, GentiliB. Remote sensing of sea surface Sun-induced chlorophyll fluorescence: Consequences of natural variations in the optical characteristics of phytoplankton and the quantum yield of chlorophyll a fluorescence[J]. International Journal of Remote Sensing, 17, 2417-2448(1996).
[2] O'ReillyJ E, MaritorenaS, MitchellB G et al. Ocean color chlorophyll algorithms for SeaWiFS[J]. Journal of Geophysical Research Oceans, 103, 24937-24953(1998).
[3] KoponenS, AttilaJ, PulliainenJ et al. A case study of airborne and satellite remote sensing of a spring bloom event in the Gulf of Finland[J]. Continental Shelf Research, 27, 228-244(2007).
[4] LeC, HuC, CannizzaroJ et al. Evaluation of chlorophyll-a remote sensing algorithms for an optically complex estuary[J]. Remote Sensing of Environment, 129, 75-89(2013).
[5] DekkerA G, BrandoV E, AnsteeJ M. Retrospective seagrass change detection in a shallow coastal tidal Australian lake[J]. Remote Sensing of Environment, 97, 415-433(2005).
[6] GonsH J, AuerM T, EfflerS W. MERIS satellite chlorophyll mapping of oligotrophic and eutrophic waters in the Laurentian Great Lakes[J]. Remote Sensing of Environment, 112, 4098-4106(2008).
[7] LeC, LiY M, ZhaY et al. A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China[J]. Remote Sensing of Environment, 113, 1175-1182(2009).
[8] MatsushitaB, YangW, YuG et al. A hybrid algorithm for estimating the chlorophyll-a concentration across different trophic states in Asian inland waters[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 102, 28-37(2015).
[9] ZhangF F, LiJ S, ShenQ et al. Algorithms and schemes for chlorophyll a estimation by remote sensing and optical classification for turbid lake Taihu, China[J]. IEEE Journal of Selected Topics in Applied Earth Observations & remote sensing, 8, 350-364(2015).
[10] SmithM E, RobertsonL L, BernardS. An optimized chlorophyll a switching algorithm for MERIS and OLCI in phytoplankton-dominated waters[J]. Remote Sensing of Environment, 215, 217-227(2018).
[11] TassanS. Local algorithms using SeaWiFS data for the retrieval of phytoplankton, pigments, suspended sediment, and yellow substance in coastal waters[J]. Applied Optics, 33, 2369-2378(1994).
[12] 潘洋洋. SVM模型在叶绿素a非线性定量遥感反演中的应用研究[D]. 武汉:华中科技大学, 2017. [ PanY Y. Application of SVM model to chlorophyll-a nonlinear quantitative remote sensing retrieval[D]. Wuhan: Huazhong University of Science and Technology, 2017. ] [ Pan Y Y. Application of SVM model to chlorophyll-a nonlinear quantitative remote sensing retrieval[D]. Wuhan: Huazhong University of Science and Technology, 2017. ]
[13] 石绥祥, 王蕾, 余璇, 等. 长短期记忆神经网络在叶绿素a浓度预测中的应用[J]. 海洋学报, 2020,42(2):134-142. [ ShiS X, WangL, YuX, et al. Application of long term and short term memory neural network in prediction of chlorophyll a concentration[J]. Acta Oceanologica Sinica, 2020,42(2):134-142. ] [ Shi S X, Wang L, Yu X, et al. Application of long term and short term memory neural network in prediction of chlorophyll a concentration[J]. Acta Oceanologica Sinica, 2020,42(2):134-142. ]
[14] GitelsonA, KeydanG, ShishkinV. Inland waters quality assessment from satellite data in visible range of the spectrum[J]. Soviet Remote Sensing, 6, 28-36(1985).
[16] 郭宇龙, 李云梅, 李渊, 等. 一种基于GOCI数据的叶绿素a浓度三波段估算模型[J]. 环境科学, 2015,36(9):3175-3185. [ GuoY L, LiY M, LiY. et al. Three band chlorophyll-a concentration estimation model based on GOCI imagery[J]. Environmental Science, 2015,36(9):3175-3185. ] [ Guo Y L, Li Y M, Li Y. et al. Three band chlorophyll-a concentration estimation model based on GOCI imagery[J]. Environmental Science, 2015,36(9):3175-3185. ]
[17] 徐升, 顾长梅, 钱贞兵, 等. 基于四波段模型的巢湖水体藻蓝素浓度反演[J]. 绿色科技, 2016(16):18-22,25. [ XuS, GuC M, QianZ B, et al. Retrieval of the concentration of phycocyanobilin in Chaohu Lake based on four-band model[J]. Journal of Green Science and Technology, 2016(16):18-22,25. ] [ Xu S, Gu C M, Qian Z B, et al. Retrieval of the concentration of phycocyanobilin in Chaohu Lake based on four-band model[J]. Journal of Green Science and Technology, 2016(16):18-22,25. ]
[18] AnasE A, KaremC, IsabelleL et al. Comparative analysis of four models to estimate chlorophyll-a concentration in case-2 waters using MODerate Resolution Imaging Spectroradiometer (MODIS) imagery[J]. Remote Sensing, 4, 2373-2400(2012).
[19] 刘文雅, 邓孺孺, 梁业恒, 等. 基于辐射传输模型的巢湖叶绿素a浓度反演[J]. 国土资源遥感, 2019,31(2):102-110. [ LiuW Y, DengR R, LiangY H, et al. Retrieval of chlorophyll-a concentration in Chaohu based on radiative transfer model[J]. Remote Sensing for Land and Resources, 2019,31(2):102-110. ] [ Liu W Y, Deng R R, Liang Y H, et al. Retrieval of chlorophyll-a concentration in Chaohu based on radiative transfer model[J]. Remote Sensing for Land and Resources, 2019,31(2):102-110. ]
[20] 李云梅, 黄家柱, 韦玉春, 等. 用分析模型方法反演水体叶绿素的浓度[J]. 遥感学报, 2006,10(2):27-33. [ LiY M, HuangJ Z, WeiY C. et al. Inversing chlorophyll concentration of Taihu Lake by analytic model[J]. Journal of Remote Sensing, 2006,10(2):27-33. ] [ Li Y M, Huang J Z, Wei Y C. et al. Inversing chlorophyll concentration of Taihu Lake by analytic model[J]. Journal of Remote Sensing, 2006,10(2):27-33. ]
[21] GowerJ F R, DoerfferR, BorstadG A. Interpretation of the 685nm peak in water-leaving radiance spectra in terms of fluorescence, absorption and scattering, and its observation by MERIS[J]. International Journal of Remote Sensing, 20, 1771-1786(1999).
[22] GowerJ, KingS, BorstadG et al. Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer[J]. International Journal of Remote Sensing, 26, 2005-2012(2005).
[23] ShenF, ZhouY X, LiD J et al. Medium Resolution Imaging Spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary[J]. International Journal of Remote Sensing, 31, 4635-4650(2010).
[24] 陈芸芝, 郑高强, 汪小钦, 等. 基于GSM01融合的多传感器数据叶绿素a浓度反演[J]. 地球信息科学学报, 2013,15(6):911-917. [ ChenY Z, ZhengG Q, WangQ Q, et al. Retrieval of chlorophyll a concentration with multi-sensor data by GSM01 merging algorithm[J]. Journal of Geo-information Science, 2013,15(6):911-917. ] [ Chen Y Z, Zheng G Q, Wang Q Q, et al. Retrieval of chlorophyll a concentration with multi-sensor data by GSM01 merging algorithm[J]. Journal of Geo-information Science, 2013,15(6):911-917. ]
[25] GurlinD, GitelsonA A, MosesW J. Remote estimation of chl-a concentration in turbid productive waters: Return to a simple two-band NIR-red model?[J]. Remote Sensing of Environment, 115, 3479-3490(2011).
[26] 张运林, 冯胜, 马荣华, 等. 太湖秋季光学活性物质空间分布及其遥感估算模型研究[J]. 武汉大学学报·信息科学版, 2008,33(9):967-972. [ ZhangY L, FengS, MaR H, et al. Spatial variation and estimation of optically active substances in Taihu Lake in autumn[J]. Geomatics and Information Science of Wuhan University, 2008,33(9):967-972. ] [ Zhang Y L, Feng S, Ma R H, et al. Spatial variation and estimation of optically active substances in Taihu Lake in autumn[J]. Geomatics and Information Science of Wuhan University, 2008,33(9):967-972. ]
[27] BindingC E, GreenbergT A, BukataR P. The MERIS Maximum Chlorophyll Index; its merits and limitations for inland water algal bloom monitoring[J]. Journal of Great Lakes Research, 39, 100-107(2013).
[28] 阎福礼, 刘韶菲, 王世新, 等. 太湖浮游藻类的后向散射分离及其叶绿素a浓度反演[J]. 地球信息科学学报, 2014,16(6):989-996. [ YanF L, LiuY F, WangS X, et al. Phytoplankton backscattering coefficients partitioning and its applications in retrieving chlorophyll-a concentrations in Taihu Lake[J]. Journal of Geo-information Science, 2014,16(6):989-996. ] [ Yan F L, Liu Y F, Wang S X, et al. Phytoplankton backscattering coefficients partitioning and its applications in retrieving chlorophyll-a concentrations in Taihu Lake[J]. Journal of Geo-information Science, 2014,16(6):989-996. ]
[29] GonsH J. A chlorophyll-retrieval algorithm for satellite imagery (Medium Resolution Imaging Spectrometer) of inland and coastal waters[J]. Journal of Plankton Research, 24, 947-951(2002).
[31] 高庆, 艾里西尔·库尔班, 肖昊. 巴音布鲁克地区植物物候时空动态变化及其驱动分析[J]. 干旱区研究, 2018,35(6):1418-1426. [ GaoQ, AlishirK, XiaoH. Spatiotemporal variation of vegetation phenology and its driving factors in the Bayanbulak region[J]. Arid Zone Research, 2018,35(6):1418-1426. ] [ Gao Q, Alishir K, Xiao H. Spatiotemporal variation of vegetation phenology and its driving factors in the Bayanbulak region[J]. Arid Zone Research, 2018,35(6):1418-1426. ]
[32] 陈文玲, 何雨. 草原生态旅游资源开发评价体系构建与应用研究——以新疆巴音布鲁克草原为例[J]. 资源开发与市场, 2016,32(11):1394-1397. [ ChenW L, HeY. Research on establishment and application of evaluation system for the development of grassland ecotourism resources: A case study of Bayanbulak Grassland in Xinjiang[J]. Resource Development & Market, 2016,32(11):1394-1397. ] [ Chen W L, He Y. Research on establishment and application of evaluation system for the development of grassland ecotourism resources: A case study of Bayanbulak Grassland in Xinjiang[J]. Resource Development & Market, 2016,32(11):1394-1397. ]
[33] 徐晓龙, 王新军, 朱新萍, 等. 1996-2015年巴音布鲁克天鹅湖高寒湿地景观格局演变分析[J]. 自然资源学报, 2018,33(11):39-53. [ XuX L, WangX J, ZhuX P, et al. Landscape pattern changes in alpine wetland of Bayanbulak Swan Lake during 1996-2015[J]. Journal of Natural Resources, 2018,33(11):39-53. ] [ Xu X L, Wang X J, Zhu X P, et al. Landscape pattern changes in alpine wetland of Bayanbulak Swan Lake during 1996-2015[J]. Journal of Natural Resources, 2018,33(11):39-53. ]
[34] CarlsonR E. Estimating trophic state[J]. LakeLine, 27, 25-28(2007).
[35] 唐军武, 田国良, 汪小勇, 等. 水体光谱测量与分析Ⅰ:水面以上测量法[J]. 遥感学报, 2004,8(1):37-44. [ TangJ W, TianG L, WangX Y, et al. The methods of water spectra measurement and analysis Ⅰ: Above-Water Method[J]. Journal of Remote Sensing, 2004,8(1):37-44. ] [ Tang J W, Tian G L, Wang X Y, et al. The methods of water spectra measurement and analysis Ⅰ: Above-Water Method[J]. Journal of Remote Sensing, 2004,8(1):37-44. ]
[36] KnaepsE, DoxaranD, DogliottiA et al. The SeaSWIR dataset[J]. Earth System Science Data, 10, 1439-1449(2018).
[37] GitelsonA A, GurlinD, MosesW J et al. A bio-optical algorithm for the remote estimation of the chlorophyll-a concentration in case 2 waters[J]. Environmental Research Letters, 4, 1-5(2009).
[38] QiL, HuC, DuanH et al. A novel MERIS algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: Theoretical basis and practical considerations[J]. Remote Sensing of Environment, 154, 298-317(2014).
[39] ZimbaP V, GitelsonA. Remote estimation of chlorophyll concentration in hyper-eutrophic aquatic systems: model tuning and accuracy optimization[J]. Aquaculture, 256, 272-286(2006).
[40] ThiemannS, KaufmannH. Determination of chlorophyll content and trophic state of lakes using field spectrometer and IRS-1C satellite data in the Mecklenburg Lake District, Germany[J]. Remote Sensing of Environment, 73, 227-235(2000).
[41] [online]. ESA Copernicus Open Access Hub(2019). https://scihub.copernicus.eu/
[42] 苏伟, 张明政, 蒋坤萍, 等. Sentinel-2卫星影像的大气校正方法[J]. 光学学报, 2018,38(1):322-331. [ SuW, ZhangM, JiangK, et al. Atmospheric correction method for sentinel-2 satellite imagery[J]. Acta Optica Sinica, 2018,38(1):322-331. ] [ Su W, Zhang M, Jiang K, et al. Atmospheric correction method for sentinel-2 satellite imagery[J]. Acta Optica Sinica, 2018,38(1):322-331. ]
[44] HeX Q, BaiY, PanD et al. Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters[J]. Remote Sensing of Environment, 133, 225-239(2013).
[45] SiswantoE, TangJ, YamaguchiH et al. Empirical ocean-color algorithms to retrieve chlorophyll-a, total suspended matter, and colored dissolved organic matter absorption coefficient in the Yellow and East China Seas[J]. Journal of Oceanography, 67, 627-650(2011).
[46] MishraS, MishraD R. Normalized difference chlorophyll index: A novel model for remote estimation of chlorophyll-a concentration in turbid productive waters[J]. Remote Sensing of Environment, 117, 394-406(2012).
[47] ReynoldsC S, DescyJ P, PadisákJ. Are phytoplankton dynamics in rivers so different from those in shallow lakes?[J]. Hydrobiologia, 289, 1-7(1994).
[48] CarneiroF M, NaboutJ C, VieiraL G et al. Determinants of chlorophyll-aconcentration in tropical reservoirs[J]. Hydrobiologia, 740, 89-99(2014).
[49] StaehrP A, BaastrupS L, SandJ K et al. Lake metabolism scales with lake morphometry and catchment conditions[J]. Aquatic Sciences, 74, 155-169(2012).
[50] 慈晖, 张强. 新疆NDVI时空特征及气候变化影响研究[J]. 地球信息科学学报, 2017,19(5):662-671. [ CiH, ZhangQ. Spatio-temporal patterns of NDVI variations and possible relations with climate changes in Xinjiang province[J]. Journal of Geo-information Science, 2017,19(5):662-671. ] [ Ci H, Zhang Q. Spatio-temporal patterns of NDVI variations and possible relations with climate changes in Xinjiang province[J]. Journal of Geo-information Science, 2017,19(5):662-671. ]
[51] 周梦甜, 李军, 朱康文. 近15a新疆不同类型植被NDVI时空动态变化及对气候变化的响应[J]. 干旱区地理, 2015,38(4):779-787. [ ZhouM T, LiJ, ZhuK W. Spatial-temporal dynamics of different types of vegetation NDVI and its response to climate change in Xinjiang during 1998-2012[J]. Arid Land Geography, 2015,38(4):779-787. ] [ Zhou M T, Li J, Zhu K W. Spatial-temporal dynamics of different types of vegetation NDVI and its response to climate change in Xinjiang during 1998-2012[J]. Arid Land Geography, 2015,38(4):779-787. ]
