遥感反演蒸散发时间尺度拓展方法研究进展
文献类型:期刊论文
作者 | 夏浩铭1,2![]() ![]() ![]() ![]() |
刊名 | 农业工程学报
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出版日期 | 2015-12-23 |
卷号 | 31期号:24页码:162-173 |
关键词 | 遥感 蒸散发 不确定性分析 时间尺度 拓展方法 |
ISSN号 | 1002-6819 |
其他题名 | Review of temporal scale expansion for evapotranspiration retrieved by remote sensing data |
通讯作者 | 李爱农 |
中文摘要 | 区域尺度蒸散发的精确估算对农业生态系统和水文循环至关重要。由于地表空间异质性,传统点上测量和反演方法只能代表有限站点周围区域的蒸散发情况,遥感能够克服传统蒸散发的空间尺度拓展问题。由于遥感只能提供卫星过境时刻的瞬时值,根据其反演的蒸散发是瞬时蒸散发,现实生产活动中通常需要更长时间尺度的蒸散发值。围绕如何解决遥感反演蒸散发时间尺度拓展问题,该文系统介绍了遥感反演蒸散发时间尺度拓展方法,总结了每种方法的基本原理、优缺点、适用性和误差来源,对比了不同时间尺度拓展方法估算精度,并给出选取合适时间尺度拓展方法的可量化意见,简要分析了遥感反演蒸散发模型应用中的地表参数、时间尺度拓展方法本身算法、方法验证及适用性的不确定性,最后对遥感反演蒸散发时间尺度拓展方法的发展趋势进行了探讨。 |
英文摘要 | The accurate estimation of evapotranspiration (ET) at regional scale is vital for agricultural ecosystem and hydrologic cycle. Remote sensing can overcome the limitation of spatial scale from traditional ET measurement and inversion approaches. However, remote sensing only obtains the instantaneous ET estimates at the overpassing time of satellite. In the practical application, temporal upscaling of instantaneous ET to daily or longer temporal scale is required. This study reviewed the methods for the temporal upscaling of ET, compared the applicability of different methods, gave quantifiable advice on how to choose the different methods, and assessed the uncertainties from model itself, model parameterization, along with model evaluation. Future research should address the following issues: 1) The precision of remote sensing for obtaining surface parameters needs to be further improved. Land surface temperature, surface albedo, emissivity, normalized difference vegetation index (NDVI), fractional vegetation cover, soil moisture and leaf area index (LAI) have significant impact on the partition of the 4 energy components in the energy balance models and consequently on the accuracy of the retrieval regional ET. More attention should be paid to the physical interpretation of these surface variables, and understanding the mechanism of remote sensing radiative transfer needs to deepen. 2) Now, more than 2000 terrestrial flux stations have been established all over the world, which almost cover the major ecosystem types of the world. However, the comparative research on existing methods of temporal scale expansion is less. Therefore, relying on the existing field data of long-term ground observation stations, further comparison of the applicability between different temporal upscaling methods is definitely required in different climate zones and crop types, which can provide reference on how to select the appropriate temporal scale expansion method based on the characteristics of study area. 3) The temporal upscaling method of remote sensing ET has its own advantages, disadvantages and suitable conditions, and hence it needs to be further improved and perfected. For example, although the constant reference evaporative fraction method has higher estimation precision than other methods, a variable canopy resistance would be introduced for the reference grass instead of using the fixed value. 4) In the future, we can introduce hyperspectral data to improve the accuracy of surface temperature inversion, use microwave data which is less affected by weather to estimate the ET of rainy days, and combine new technology and method such as large aperture scintillation detector (LAS) to carry out satellite-aircraft-ground simultaneous observation experiment; and integrated use of multi-source, multi-scale remote sensing data to expand temporal scale of ET based on the characteristics of study area, is a breakthrough for future research. 5) Based on data assimilation methods, land surface process and atmospheric general circulation model, relying on the existing field data of long-term ground observation stations, the land surface data assimilation system of ET can be constructed, which can integrate multi-source/scale direct and indirect observations data. Achieving dynamic monitoring and forecasting of ET in agro-ecosystem is one of the future trends. |
学科主题 | TP79 ; S127 |
收录类别 | EI ; CSCD ; 北大中文核心 |
语种 | 中文 |
CSCD记录号 | CSCD:5592561 |
源URL | [http://ir.imde.ac.cn/handle/131551/17229] ![]() |
专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
作者单位 | 1.中国科学院水利部成都山地灾害与环境研究所 2.中国科学院大学 |
推荐引用方式 GB/T 7714 | 夏浩铭,李爱农,赵伟,等. 遥感反演蒸散发时间尺度拓展方法研究进展[J]. 农业工程学报,2015,31(24):162-173. |
APA | 夏浩铭,李爱农,赵伟,&边金虎.(2015).遥感反演蒸散发时间尺度拓展方法研究进展.农业工程学报,31(24),162-173. |
MLA | 夏浩铭,et al."遥感反演蒸散发时间尺度拓展方法研究进展".农业工程学报 31.24(2015):162-173. |
入库方式: OAI收割
来源:成都山地灾害与环境研究所
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