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Retrieve the Latent Heat Flux in the Typical Sample Region of the Three Gorges Reservoir Area Based on Remote Sensing

Author: ZhangXueQing
Tutor: LuoHongXia
School: Southwestern University
Course: Cartography and Geographic Information Systems
Keywords: Latent Heat Flux Empirical Formula Landsat-5TM ThreeGorges Reservoir Area Surface Cover
CLC: TP79
Type: Master's thesis
Year: 2012
Downloads: 50
Quote: 1
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Abstract


In this research, the part area of the middle reaches area is the typical sample region for the research on the Latent Heat Flux. And it is very important to simulate the climate effects of the Surface Cover change. As the important part during the process of the water cycle and energy balance, Latent Heat Flux plays a powerful role in the vapor flux process between the land surface and atmosphere exchange. The water carries the Latent Heat during the terrestrial hydrological process, there will be certain exchanging between the sea and the inside land. During this exchange process, Latent Heat Flux regulates the global water and the energy distribution. Because of the climate is very sensitive to the land surface Latent Heat Flux; the climate change will directly affect the space-time distribution of water resource, and will affect the region economy development in some extent. Thus, the research on the Latent Heat Flux of the typical sample region, that is very helpful to scientific understand climate effects. According to its changing rules, the production practice will be guided better.This paper summarized the theory and method about the Latent Heat Flux estimation based on remote sensing, and using the method of remote sensing to retrieve the Latent Heat Flux. Firstly, Using ENVI to calibration and Atmospheric correction for elimination of atmospheric remote sensing image effects. Secondly, retrieving the surface parameters based on the calibration and Atmospheric correction:1. Assuming the surface is Lambertian, Using narrowband to broadband conversion formula for the study area to retrieval of surface albedo;2. Using the Landsat-5TM data band3and band4to calculate vegetation index, then estimation the vegetation coverage;3. This paper divided the surface cover into three types:Water, building and natural surface;4. Assuming the surface is Lambertian. according to the heat radiation intensity which is observed by satellite remote sensing, after acquiring the relative parameters, retrieving the Land Surface Temperature;5. Based on the relative parameters, through the surface net short-wave radiation and the long-wave radiation, this paper calculated the Surface Net Radiation;6. Using Bastiaanssen Empirical Formula to retrieve the soil heat flux. Lastly, this paper retrieves the Latent Heat Flux using the Empirical Formula about the relationship among the Latent Heat Flux, the Surface Net Radiation and the Soil heat flux; based on the related sinusoidal model calculation the day Latent Heat Flux.During the research process, using the simple and practical algorithm to retrieve the land surface parameters. Grantee the land surface Latent Heat Flux is accurate and credible, the first thing is that ensure that the land surface parameters are more accurate. Under the different Surface Cover, the Latent Heat Flux is difference with its unique properties. With the Surface Cover change, the spatial distribution of Latent Heat Flux has significant variation.During verification process in this research, combined with some meteorological law, the writer used the meteorological formula that is FAO Penman-Monteith to calculate the Latent Heat Flux of climate stations, and then using ANUSPLIN to interpolation. Under the limited data and resource conditions, the writer studies the Latent Heat Flux in the typical sample region. In the contrast between the Day Latent Heat Flux which is retrieve by remote sensing, and the Latent Heat Flux that is calculated by FAO Penman-Monteith, it is found that this remote sensing retrieve method has certain validity and usability in the research, and it is practical significance on the climate effects simulation.

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