流域水环境遥感研究进展与思考

doi:10.18306/dlkxjz.2019.08.007

Abstract

Abstract:

Since ancient times, humans have lived near water, depending on water for survival and progress. There is a close link between the environmental quality of a lake or river basin and human activity, with the role of their ecological services being of vital importance to local communities. As an advanced technology, satellite remote sensing can monitor the spatial dynamics of the current situation, as well as look back to determine the temporal dynamics of aquatic environments. This allows, when combined with modeling, the possibility to project the future situation in order to improve planning and environmental management. Remote sensing can play an irreplaceable role for humans to understand, monitor, and manage basin environments for the present and future generations. This article focuses on the remote sensing of lake and river basins, exploring different research objectives, addressing the basic theoretical framework, analyzing the state-of-the-art in Chinese and international research programs, and pointing to priorities for future development.

Key words: water color remote sensing, water quality remote sensing, aquatic remote sensing, watershed geographic sciences, inland water, satellite remote sensing, review

DUAN Hongtao,LUO Juhua,CAO Zhigang,XUE Kun,XIAO Qitao,LIU Dong. Progress in remote sensing of aquatic environments at the watershed scale[J].PROGRESS IN GEOGRAPHY, 2019, 38(8): 1182-1195.

Figures/Tables 4

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卫星	传感器	类型	国家/组织	时段	波段数	空间分辨率/m
Nimbus-7	CZCS	极轨	美国	1978—1986年	6	825
HY-1A	COCTS	极轨	中国	2002—2004年	10	1100
JEM-EF	HICO	极轨	美国	2009—2014年	124	100
MERIS	ENVISAT	极轨	欧盟	2002—2012年	15	300
OrbView-2	SeaWFS	极轨	美国	1997—2011年	8	1100
HY-1B	COCTS	极轨	中国	2007年至今	10	1100
CMOS	GOCI	静止	韩国	2010年至今	8	500
GCOM-C	SGLI	极轨	日本	2017年至今	19	250
Terra/Aqua	MODIS	极轨	美国	1999年至今	36	1000^*
S-NPP/NOAA-20	VIIRS	极轨	美国	2017年至今	22	750
Sentinel-3 A/B	OLCI	极轨	欧盟	2016年至今	21	300

类别	参数	模型形式	适用范围	参考文献
经验模型	叶绿素a	R_rs(709)/R_rs(665)、NDCI	需要特定波段,目前支持MERIS、OLCI传感器	Duan et al, 2012; Mishra et al, 2012
	叶绿素a	多元逐步回归模型、EOF、神经网络	依赖于模型训练的数据范围	Qi et al, 2014b; Song et al, 2013
	悬浮物	单波段、波段比值及组合模型	波长越长的波段越适合高浑浊的水体	Cao et al, 2017; Knaeps et al, 2015
	藻蓝素	R_rs(709)/R_rs(620)、	需要特定波段,目前支持MERIS、OLCI	Hunter et al, 2009
	藻蓝素	PCI算法	适应范围广,不需要大气精校正,但目前支持MERIS、OLCI传感器	Qi et al, 2014a
	DOC	多元逐步回归模型	依赖于实测数据	Griffin et al, 2018
	POC	红光/近红外等经验比值算法	依赖于不同水体光学特性主导因子	Duan et al, 2014; Son et al, 2009
分析/半分析模型	叶绿素a	Gons方法、三波段等	依赖于特殊波段且模型中涉及的系数需要根据不同水体进行率定	Gitelson et al, 2008; Gons et al, 2008
	悬浮物	基于颗粒物后向散射系数的反演模型	适用于中低浑浊的水体	Nechad et al, 2010
	藻蓝素	Simis方法	依赖于特殊波段且模型中涉及的系数需要根据不同水体进行率定	Simis et al, 2005
	DOC	基于CDOM吸收系数的方法	CDOM吸收系数反演困难	Fichot et al, 2011
	POC	基于Gons、Simis等算法	藻类控制的富营养化湖泊	Jiang et al, 2015

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Progress in remote sensing of aquatic environments at the watershed scale

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