湖冰遥感监测方法综述
Review of Lake Ice Monitoring by Remote Sensing
查看参考文献53篇
|
文摘
|
本文综述了多光谱和微波数据监测湖冰冻结、消融及冰厚的方法, 并比较了各种方法的优缺点, 最后运用 MODIS和AMSR-E监测了纳木错2007/2008冬半年冰情. 湖冰监测方法主要有阈值法和指数法. 阈值法是根据冰水反射率、温度、后向散射系数等特征因子的不同直接区分冰水, 精度较高, 误差在5天以内. 指数法主要是根据冰水波谱特性和极化特性, 做波段运算后间接区分冰水. 冰厚监测常采用经验公式法, 用实测数据与反射率、极化比、亮温等建立关系式反演整个湖泊冰厚, 此方法适用于特定的某个湖泊. 冰厚识别是湖冰监测的难点, 主动微波比多光谱数据更适合监测冰厚. 从数据本身来讲, 热红外、被动微波等高时间分辨率数据比可见光、主动微波等高空间分辨率影像更适合监测大面积湖泊冰情. 基于多源遥感数据, 发展自动反演算法将是湖冰遥感监测发展趋势之一. |
|
其他语种文摘
|
This paper summarized and compared several methods of monitoring lake ice freezingon and breaking up and ice thickness by multi-spectral and microwave remote sensing data. Finally, we monitored the lake ice in Nam Co by two methods during the winter half year of 2007/ 2008.Generally, researchers usually take threshold and index methods to monitor lake ice. According to the differences between ice and water, such as their reflectivity, temperature and backward scattering coefficients, the threshold model can distinguish ice and water directly.It has a high precision with an error of less than 5 days. While the index method recognizes ice and water indirectly by calculations based on spectral and polarization characteristics of ice and water. Additionally, researchers use empirical correlations between ice thickness and its reflectivity, polarization, temperature brightness or other properties to invert thickness. Ice thickness recognition is difficult in lake ice monitoring. Active microwave data is more suitable for ice thickness monitoring than multi-spectral data. Data with high time resolution such as thermal infrared and passive microwave data is more suitable for monitoring lake ice with large areas than the data with high spatial resolutions such as visible, near infrared and active microwave data. Based on multisource remote sensing data, automatic inversion algorithm will be one of the development trends of lake ice monitoring by remote sensing. |
|
来源
|
地理科学进展
,2010,29(7):803-810 【核心库】
|
|
关键词
|
湖冰识别
;
冰厚
;
多光谱
;
微波
;
监测
|
|
地址
|
1.
中国科学院研究生院, 中国科学院青藏高原环境变化与地表过程重点实验室, 北京, 100085
2.
中国科学院青藏高原研究所, 中国科学院青藏高原环境变化与地表过程重点实验室;;遥感科学国家重点实验室, 北京, 100085
|
|
语种
|
中文 |
|
ISSN
|
1007-6301 |
|
学科
|
自然地理学 |
|
基金
|
中国科学院青藏高原研究所环境变化与地表过程实验室领域前沿项目
;
中国科学院遥感应用研究所遥感信息科学国家重点实验室项目
;
公益性行业（气象）科研专项
;
国家自然科学基金
;
国家973计划
|
|
文献收藏号
|
CSCD:3921083
|
参考文献 共
53
共3页
|
|
1.
姚檀栋. 冰芯研究与全球变化.
中国科学院院刊,1996(5):368-371
|
CSCD被引
5
次
|
|
|
|
|
2.
陈拓. 从树轮纤维素δ~（13）C序列看树木生长对大气CO_2浓度变化的响应.
冰川冻土,2001,23(1):41-45
|
CSCD被引
15
次
|
|
|
|
|
3.
王君波. 青藏高原湖泊沉积与环境演变研究现状与展望.
地理科学进展,2005,24(5):1-12
|
CSCD被引
15
次
|
|
|
|
|
4.
Kouraev A V. Observations of Lake Baikal ice from satellite altimetry and radiometry.
Remote Sensing of Environment,2007,108(3):240-253
|
CSCD被引
11
次
|
|
|
|
|
5.
Marszelewski W. Ice cover as an indicator of winter air temperature changes:Case study of the Polish Lowland lakes.
Hydrological Sciences Journal-Journal Des Sciences Hydrologiques,2006,51(2):336-349
|
CSCD被引
16
次
|
|
|
|
|
6.
Gould M. Temperature variations in lake ice in central Alaska, USA.
Annals of Glaciology,2005,40(1):89-94
|
CSCD被引
5
次
|
|
|
|
|
7.
Johnson S L. Indicators of climate warming in Minnesota:Lake ice covers and snowmelt runoff.
Climate Change,2006,75(4):421-453
|
CSCD被引
12
次
|
|
|
|
|
8.
Todd M C. Large-scale climate controls on Lake Baikal ice cover.
Journal of Climate,2003,16(19):3186-3199
|
CSCD被引
11
次
|
|
|
|
|
9.
Ghanbari R N. Coherence between lake ice cover, local climate and teleconnections.
Journal of Hydrology,2009,374(3/4):282-293
|
CSCD被引
10
次
|
|
|
|
|
10.
Wynne R H. Satellite observation of lake ice as a climate indicator:Initial results from statewide monitoring in Wisconsin.
Photogrammetric Engineering& Remote Sensing,1993,59(6):1023-1031
|
CSCD被引
6
次
|
|
|
|
|
11.
Rees W G. Remote Sensing of Snow and Ice.
Boca Raton:CRC Press Taylor& Francis Group,2006:183-188
|
CSCD被引
1
次
|
|
|
|
|
12.
Bryan M L. The study of fresh-water lake ice using multiplexed imaging radar.
Journal of Glaciology,1975,14(72):445-457
|
CSCD被引
2
次
|
|
|
|
|
13.
陈贤章. 青藏高原湖冰及其遥感监测.
冰川冻土,1995,17(3):241-246
|
CSCD被引
24
次
|
|
|
|
|
14.
殷青军. 基于EOS/MODIS数据的青海湖遥感监测.
湖泊科学,2005,17(4):356-360
|
CSCD被引
32
次
|
|
|
|
|
15.
车涛. 利用被动微波遥感低频亮温数据监测青海湖封冻与解冻期.
科学通报,2009,54(6):787-791
|
CSCD被引
19
次
|
|
|
|
|
16.
Duguay C R. Ice-cover variability on shallow lakes at high latitudes:Model simulations and observations.
Hydrological Processes,2003,17(17):3465-3483
|
CSCD被引
16
次
|
|
|
|
|
17.
Jeffries M O. Lake ice growth and decay in central Alaska, USA:Observations and computer simulations compared.
Annals of Glaciology,2005,40(1):195-199
|
CSCD被引
3
次
|
|
|
|
|
18.
Menard P. Simulation of ice phenology on Great Slave Lake, Northwest Territories, Canada.
Hydrological Processes,2002,16(18):3691-3706
|
CSCD被引
8
次
|
|
|
|
|
19.
Morris K. Model simulation of the effects of climate variability and change on lake ice in central Alaska, USA.
Annals of Glaciology,2005,40(1):113-118
|
CSCD被引
2
次
|
|
|
|
|
20.
Reid T. A thermodynamic model of freshwater Antarctic lake ice.
Ecological modeling,2008,210(3):231-241
|
CSCD被引
4
次
|
|
|
|
|
了解气象卫星更多信息，请访问