基于多源遥感影像的雪盖及雪表面温度反演
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摘要
积雪作为融雪径流模型的重要输入参数，其数据的准确性将直接影响到融雪径流的模拟和预报结果。遥感以其宏观、综合、动态及快速的优势成为积雪研究的重要手段，目前对于积雪的遥感研究因受传感器及应用需求的影响，多集中在中尺度和大尺度的研究，而对小的流域尺度的研究不多。随着我国对融雪径流模拟预报研究的深入开展，对融雪期流域积雪数据的准确获取和动态监测需求迫切。
本文即在此需求的基础上，从经济、准确、快速且尽可能多的获得连续数据的角度出发，选择我国自行研制的专门用于环境与灾害监测的环境与灾害监测预报小卫星（HJ-1A/1B）及MODIS数据，以地处新疆天山北坡昌吉州呼图壁县境内的军塘湖流域作为典型研究区，对基于两种数据源的雪盖及雪表面温度遥感定量反演展开了较为系统和深入的研究。
本文开展的主要研究内容包括以下几个方面：
开展了积雪在可见光、近红外及热红外波段的光谱特性研究，对融雪期的积雪光谱特性、影响因素等进行细致的分析和研究，为研究区积雪参数的遥感定量反演提供相应的物理基础。结果表明，融雪期间，积雪物理状态的快速变化会造成明显的积雪反射差异，从而对积雪的定量遥感研究产生影响。
探讨常用几种大气校正方法在HJ-1A/1B卫星影像大气校正中的适用性，并针对HJ-1A/1B卫星影像观测角大的特点，研究利用MODTRAN模型模拟构建了不同观测条件下的大气校正参数查找表。结果表明，查找表法的大气校正效果最好，能有效提高大气校正精度，若对大气校正精度要求不高，不考虑观测天顶角变化的影响时，FLAASH模型不失为一种简便有效的大气校正方法。
根据研究区特点及每天能够获取的实际数据情况，开展不同情况下的雪盖提取方法研究，构建针对不同数据源和不同融雪状态的雪盖提取方法。提出融合TM影像获取的研究区林区覆盖本底数据进行雪盖提取，提高了林区雪盖提取精度；分析了HJ-1A/1B影像在不同融雪状态下的雪盖指数最优波段组合及判别阈值；当只有CCD数据时，采用纹理辅助的SVM分类方法能提高雪盖提取精度；此外对于MODIS数据，根据研究区状况模拟构建了林区与非林区的分段雪盖率反演模型，提出利用NDSI阈值修订模型系数的方法，该模型明显提高了MODIS在小流域尺度上的雪盖反演精度，且通过对模型系数的快速调整，能适应不同融雪状态下雪盖率反演，避免固定系数因融雪差异而产生的较大误差。
针对HJ-1B IRS和MODIS数据，进行了雪表面温度反演方法研究。探讨利用HJ-1BIRS数据进行雪表面温度反演，开展低温地表下QK&B及JM&S两种单通道温度反演算法及参数获取研究，借助大气辐射传输模型MODTRAN进行低温环境下的算法验证和敏感性分析，结果表明在不考虑参数误差的情况下，两种算法在低温环境下均会造成1K左右的误差，其中QK&B算法随雪表面温度升高误差迅速增大，而JM&S算法则变化不大，误差相对稳定，总的来说，两种算法均能准确反映雪表面温度的空间分布趋势和差异，但普遍高估了雪表面温度，其中JM&S算法精度略高于QK&B算法；对于MODIS影像，首先模拟了低温环境下Plank函数的线性化系数，其次提出以像元雪盖率及林区本底数据为基础的混合像元组成结构假设，并以此推导出了亚像元雪表面温度反演公式，最后提出了一种基于像元雪盖率及林区本底数据的MODIS积雪像元地表平均比辐射率估算方法，实验表明，该方法相对传统组分温度反演方法简单且易于操作实现，一定程度上提高了MODIS的雪表面温度反演精度，特别是对于混合像元较为明显的区域，如林区。
As the snowmelt runoff model input parameters, the accuracy of the snow parameterswill directly affect the snowmelt runoff modeling and forecasting results. Because of themacro, comprehensive, dynamic and fast advantages, remote sensing has become animportant means for snow study. At present, due to the influence of the sensor and applicationrequirements, remote sensing is often used for mesoscale and large-scale snow study but littlefor watershed scale snow study. With the in-depth study on the forecasts of snowmelt runoffsimulation, there is an urgent need to obtain accurate snow data in river basin during thesnowmelt period.
This study is based on the above requirements, select the JunTanghu River basin as atypical study area, and choose HJ-1A/1B and MODIS data used for snow cover and snowsurface temperature inversion study.
The main research contents include the following aspects:
Explore the spectral characteristics of the snow in the visible, near infrared and thermalinfrared band. Analysis of the spectral characteristics and influencing factors of snow in thesnowmelt period, to provide the physical basis of remote sensing quantitative retrieval ofsnow parameters for the study area. The results show that, during the snowmelt, the snowphysical state rapidly changes will cause obvious change of snow reflectance, which willaffect the snow parameters quantitative inversion.
Some commonly used atmosphere correction methods are used to corrected theatmospheric distortion for HJ-1A/1B data and discussed the feasibility of these methods.According to the characteristics that observation angle is biger in HJ-1A/1B, usingMODTRAN model building atmosphere correction parameter look-up table in differentobservation condition. The results indicate that, the method of look-up table is best inatmosphere correction. If the demand for accuracy is not high, can use the FLAASH model for atmospheric correction.
According to the characteristics of the study area and the type of data source, to carry outthe snow cover extraction method research, and build snow cover extraction methods fordifferent data sources and snowmelt state. Fusion inversion forest data by TM image for snowcover extraction, the method can improve the snow cover extraction accuracy in forest area.Research the optimum band combination of the snow cover index and discriminationthreshold in different snowmelt state for HJ-1A/1B image. If only use CCD data, textureassisted SVM method can improve the snow cover extraction accuracy. In addition, for theMODIS data, to build a segmented snow cover fraction inverse model according to the statusof the study area and proposed use NDSI threshold to revision model coefficients. Themethod significantly improves the retrieval accuracy of snow cover on a watershed scale, andby the rapid adjustment of the model coefficients, can adapt the fraction of snow coverinversion under the different snowmelt state.
To carry out the snow surface temperature inversion method study based on the HJ-1BIRS and MODIS data. Using IRS data to retrieved the snow surface temperature, and carriedout the research on QK&B and JM&S two single-channel algorithms and the parametersacquisition methods. Atmospheric radiative transfer model MODTRAN was used to carry outthe validation of the two algorithms errors and sensitivity analysis at low temperatures. Theresults show that in low temperature, if do not take into account the parameter errors, the twoalgorithms will produce to1K error. QK&B algorithm error rapidly increasedwith the snowsurface temperature increases, the error that caused by JM&S algorithm is little change. Ingeneral, both algorithms can accurately reflect the space distribution trends and thedifferences of the snow surface temperature, but both generally overestimated the snowsurface temperature, the accuracy of the JM&S algorithm slightly higher than the QK&Balgorithm. For MODIS image, firstly, simulate the linear coefficient of the Plank function inlow temperature environment, then to deduce the sub-pixel snow surface temperature inversion formula, and based on the snow cover fraction and forest areas and then proposed asurface average emissivity estimation methods. the result indicate that, compared to thetraditional component temperature inversion method this algorithm is simple and easy tooperate and it can improve the MODIS snow surface temperature retrieval accuracy in acertain extent, especially for the mixed pixel area, such as forest areas.
本文即在此需求的基础上，从经济、准确、快速且尽可能多的获得连续数据的角度出发，选择我国自行研制的专门用于环境与灾害监测的环境与灾害监测预报小卫星（HJ-1A/1B）及MODIS数据，以地处新疆天山北坡昌吉州呼图壁县境内的军塘湖流域作为典型研究区，对基于两种数据源的雪盖及雪表面温度遥感定量反演展开了较为系统和深入的研究。
本文开展的主要研究内容包括以下几个方面：
开展了积雪在可见光、近红外及热红外波段的光谱特性研究，对融雪期的积雪光谱特性、影响因素等进行细致的分析和研究，为研究区积雪参数的遥感定量反演提供相应的物理基础。结果表明，融雪期间，积雪物理状态的快速变化会造成明显的积雪反射差异，从而对积雪的定量遥感研究产生影响。
探讨常用几种大气校正方法在HJ-1A/1B卫星影像大气校正中的适用性，并针对HJ-1A/1B卫星影像观测角大的特点，研究利用MODTRAN模型模拟构建了不同观测条件下的大气校正参数查找表。结果表明，查找表法的大气校正效果最好，能有效提高大气校正精度，若对大气校正精度要求不高，不考虑观测天顶角变化的影响时，FLAASH模型不失为一种简便有效的大气校正方法。
根据研究区特点及每天能够获取的实际数据情况，开展不同情况下的雪盖提取方法研究，构建针对不同数据源和不同融雪状态的雪盖提取方法。提出融合TM影像获取的研究区林区覆盖本底数据进行雪盖提取，提高了林区雪盖提取精度；分析了HJ-1A/1B影像在不同融雪状态下的雪盖指数最优波段组合及判别阈值；当只有CCD数据时，采用纹理辅助的SVM分类方法能提高雪盖提取精度；此外对于MODIS数据，根据研究区状况模拟构建了林区与非林区的分段雪盖率反演模型，提出利用NDSI阈值修订模型系数的方法，该模型明显提高了MODIS在小流域尺度上的雪盖反演精度，且通过对模型系数的快速调整，能适应不同融雪状态下雪盖率反演，避免固定系数因融雪差异而产生的较大误差。
针对HJ-1B IRS和MODIS数据，进行了雪表面温度反演方法研究。探讨利用HJ-1BIRS数据进行雪表面温度反演，开展低温地表下QK&B及JM&S两种单通道温度反演算法及参数获取研究，借助大气辐射传输模型MODTRAN进行低温环境下的算法验证和敏感性分析，结果表明在不考虑参数误差的情况下，两种算法在低温环境下均会造成1K左右的误差，其中QK&B算法随雪表面温度升高误差迅速增大，而JM&S算法则变化不大，误差相对稳定，总的来说，两种算法均能准确反映雪表面温度的空间分布趋势和差异，但普遍高估了雪表面温度，其中JM&S算法精度略高于QK&B算法；对于MODIS影像，首先模拟了低温环境下Plank函数的线性化系数，其次提出以像元雪盖率及林区本底数据为基础的混合像元组成结构假设，并以此推导出了亚像元雪表面温度反演公式，最后提出了一种基于像元雪盖率及林区本底数据的MODIS积雪像元地表平均比辐射率估算方法，实验表明，该方法相对传统组分温度反演方法简单且易于操作实现，一定程度上提高了MODIS的雪表面温度反演精度，特别是对于混合像元较为明显的区域，如林区。
As the snowmelt runoff model input parameters, the accuracy of the snow parameterswill directly affect the snowmelt runoff modeling and forecasting results. Because of themacro, comprehensive, dynamic and fast advantages, remote sensing has become animportant means for snow study. At present, due to the influence of the sensor and applicationrequirements, remote sensing is often used for mesoscale and large-scale snow study but littlefor watershed scale snow study. With the in-depth study on the forecasts of snowmelt runoffsimulation, there is an urgent need to obtain accurate snow data in river basin during thesnowmelt period.
This study is based on the above requirements, select the JunTanghu River basin as atypical study area, and choose HJ-1A/1B and MODIS data used for snow cover and snowsurface temperature inversion study.
The main research contents include the following aspects:
Explore the spectral characteristics of the snow in the visible, near infrared and thermalinfrared band. Analysis of the spectral characteristics and influencing factors of snow in thesnowmelt period, to provide the physical basis of remote sensing quantitative retrieval ofsnow parameters for the study area. The results show that, during the snowmelt, the snowphysical state rapidly changes will cause obvious change of snow reflectance, which willaffect the snow parameters quantitative inversion.
Some commonly used atmosphere correction methods are used to corrected theatmospheric distortion for HJ-1A/1B data and discussed the feasibility of these methods.According to the characteristics that observation angle is biger in HJ-1A/1B, usingMODTRAN model building atmosphere correction parameter look-up table in differentobservation condition. The results indicate that, the method of look-up table is best inatmosphere correction. If the demand for accuracy is not high, can use the FLAASH model for atmospheric correction.
According to the characteristics of the study area and the type of data source, to carry outthe snow cover extraction method research, and build snow cover extraction methods fordifferent data sources and snowmelt state. Fusion inversion forest data by TM image for snowcover extraction, the method can improve the snow cover extraction accuracy in forest area.Research the optimum band combination of the snow cover index and discriminationthreshold in different snowmelt state for HJ-1A/1B image. If only use CCD data, textureassisted SVM method can improve the snow cover extraction accuracy. In addition, for theMODIS data, to build a segmented snow cover fraction inverse model according to the statusof the study area and proposed use NDSI threshold to revision model coefficients. Themethod significantly improves the retrieval accuracy of snow cover on a watershed scale, andby the rapid adjustment of the model coefficients, can adapt the fraction of snow coverinversion under the different snowmelt state.
To carry out the snow surface temperature inversion method study based on the HJ-1BIRS and MODIS data. Using IRS data to retrieved the snow surface temperature, and carriedout the research on QK&B and JM&S two single-channel algorithms and the parametersacquisition methods. Atmospheric radiative transfer model MODTRAN was used to carry outthe validation of the two algorithms errors and sensitivity analysis at low temperatures. Theresults show that in low temperature, if do not take into account the parameter errors, the twoalgorithms will produce to1K error. QK&B algorithm error rapidly increasedwith the snowsurface temperature increases, the error that caused by JM&S algorithm is little change. Ingeneral, both algorithms can accurately reflect the space distribution trends and thedifferences of the snow surface temperature, but both generally overestimated the snowsurface temperature, the accuracy of the JM&S algorithm slightly higher than the QK&Balgorithm. For MODIS image, firstly, simulate the linear coefficient of the Plank function inlow temperature environment, then to deduce the sub-pixel snow surface temperature inversion formula, and based on the snow cover fraction and forest areas and then proposed asurface average emissivity estimation methods. the result indicate that, compared to thetraditional component temperature inversion method this algorithm is simple and easy tooperate and it can improve the MODIS snow surface temperature retrieval accuracy in acertain extent, especially for the mixed pixel area, such as forest areas.
引文
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