干旱区土壤盐渍化遥感估测模型研究——以宁夏平罗县为例

以宁夏平罗县为研究靶区,以野外实测的高光谱数据和土壤含盐量为基础数据源,进行光谱反射率及其变换形式与土壤含盐量的相关分析,筛选敏感波段,建立高光谱土壤盐分指数模型;通过尺度转化,用原位采集的高光谱盐分指数修正传统遥感影像盐分指数,构建传统影像高精度土壤盐渍化遥感监测模型,并利用实测土壤含盐量对反演结果进行分析与验证。结果表明,高光谱盐分指数和实测土壤含盐量的相关性明显高于传统遥感影像光谱数据;将高光谱数据和传统Landsat-8 OLI影像数据结合,提取的区域土壤盐渍化信息精度明显提高,解决了实测数据和影像之间的时间滞后性问题。     

基于一种简单物理模型的叶面积指数反演

叶面积指数(LAI)是植被冠层结构最基本的参量之一,也是植被定量遥感的重要参数,反演方法主要有经验模型、半经验模型与物理模型.提出了一种基于四分量的简单物理模型,能快速准确地模拟森林冠层反射率并建立查找表,以Landsat-7ETM+遥感图像中单个像元作为测算单位,对大野口典型森林区叶面积指数进行反演,利用研究区地面实测数据对模型反演结果进行验证和精度分析.结果表明:相比二分量物理模型,改进的四分量物理模型能较好地描述遥感图像植被覆盖混合像元真实的物理组成,提高冠层光谱曲线模拟精度,使LAI反演准确度有所提高,R2(R为相关系数)由0.240 3提高到0.772 7,均方根误差由0.983 0降低到0.114 8,说明四分量模型能真实地反映研究区叶面积指数分布状况.     

基于水体特征指数的广西北部湾近岸海域叶绿素a 浓度反演

为了弥补传统水质监测的不足, 加强赤潮的风险管控, 基于Landsat 8 OLI 遥感影像和实地监测数据, 分析了遥感影像光谱特征对叶绿素a 浓度变化的响应关系, 统计各种水体指数(FAI、VB-FAH、NDCI等)与叶绿素a 实测浓度之间的相关关系, 对最佳的相关性指数FAI 进行改进; 再分别基于相关系数较高的水体指数(改进的FAI、 FAI、VB-FAH)建立叶绿素a 浓度反演模型, 并评价反演精度。结果表明: 改进的FAI 模型和叶绿素a 浓度的相关性最高, 相关系数R 达到0. 74; 构建的一阶线性反演模型的精度最高(R2为0. 79, RMSE 为1. 66, MAPE 为26%)。利用改进FAI 建立的一阶线性反演模型对整个研究区域的叶绿素a 浓度进行反演, 结果表明: 叶绿素a 浓度与到岸距离呈负相关关系, 河流入海口叶绿素a 浓度较高, 南流江入海口的叶绿素a 浓度值相较于其他入海口更高, 河流流域水质整体较差。改进的FAI 建立的一阶线性反演模型计算简单、精度较高, 可以快速有效地反演北部湾近岸海域的叶绿素a 浓度。     

融雪型洪水量级的流域积温分布模型研究及应用

鉴于对高寒山区融雪洪水预警精度的迫切需求,利用能量守恒原理和水量平衡原理,选取经典分布式水文模型反序架构,构建了基于融雪型洪水量级下的积温阈值及流域积温分布模型。首先利用流域集总算法计算流域面的平均积温,然后基于气温直减率进行分配,最终确定积温分布,该模型在本质上属于热传导方程的逆问题。在模型驱动数据方面,采用NCAR再分析资料用于模拟输出流域的总体平均温度,同时利用高光谱遥感数据计算出流域平均雪深,结合对新疆地区天山北坡中段军塘湖流域长期的雪特性观测、SWAT及DHSVM径流模拟试验中径流和下渗的相关性试验数据,获得了诱发得到的4次融雪型洪水过程流域的积温分布特征。最后,根据气温直减率,确定军塘湖流域面上的积温分布特征。在对研究区4场融雪型洪水进行模拟验证后发现,该模型的输出结果较为精确(纳什效率系数NSE为0.815)。然而由于模型的水文过程(下渗、蒸发等)仍存在一定的不确定性因素,因而模型结果与实际观测结果依旧存在一定差异(算术平均误差为10.65%)。研究认为,该积温模型的研制对于空间气象站点缺少区的高纬度融雪型洪水多发区的预警、预报具有较大的理论价值及应用价值。     

河口悬浮泥沙浓度遥感反演模型的探讨

介绍了河口区悬浮泥沙浓度遥感反演的理论基础及反演模型的建立方法,通过对国内外近年研究的主要悬浮泥沙遥感反演模型进行简单分类、对比分析得出其优缺点,并针对现有悬浮泥沙遥感反演模型的不足,在提高精度和普适性方面提出一些建议.     

基于GPS信噪比反演海平面高度研究

对反演所需数据的选择方法进行了研究,利用L-S谱分析方法结合GPS L2波段观测值和验潮站验潮数据对海平面高度进行反演并评定其精度。结果表明:依据站点观测环境、接收机观测卫星的天空视图以及有效反射区域反算的卫星高度角可以较好地对反演所需的数据进行选择;海平面高度反演结果与验潮仪验潮数据有较强相关性:受海面波浪急剧变化的影响,海面高度的反演精度只能达到米级、分米级。     

基于多源遥感数据的大襟岛海域悬浮泥沙观测

珠江口黄茅海大襟岛海域是中华白海豚栖息地. 为了对该海域的水质进行评估,采用集成机载光谱成像仪（CASI）影像对悬浮泥沙质量浓度进行观测,并根据实测光谱构建适用于CASI影像和中分辨率成像光谱仪（MODIS）影像的悬浮泥沙质量浓度单波段反演模型. 此外利用实测悬浮泥沙数据和MODIS影像对反演的悬浮泥沙质量浓度进行精度评定. 研究表明,基于CASI数据的单波段指数模型可以较好地反演研究海域的悬浮泥沙质量浓度,相对平均误差为11.16%,此外单波段指数模型也可以较好地应用在MODIS影像上,相对平均误差为15.18%. 研究区域悬浮泥沙质量浓度为0.48~12.15 mg/L,对海豚栖息区的生态环境未构成明显影响. 结合基于MODIS的珠江口海域悬浮泥沙遥感影像发现,研究区域悬浮泥沙主要输入来源为黄茅海西岸的陆源输入,黄茅海西岸陆域输入泥沙在由黄茅海向口外输送时,存在明显的分支现象,径流主轴在河口海域自西北向东南向海运输,沿岸流则沿着大襟岛自东北向西南向海运输,由此,在大襟岛北部出现低悬浮泥沙、高透明度海域,适合白海豚栖息.     

卫星遥感数据在流域数字化中的应用

流域要素数据的明显不足，制约着诸多水利工作的发展，采用当今信息技术，实施流域数字化，满足水利工作对流域要素数据的迫切需要，从适应快速发展的水利事业，卫星对地观测具有获取信息丰富，快速和可持续观测的优势，是流域数字化的重要支持技术之一，以遥感数据作为主要数据源，结合地面实测数据，在遥感图象处理，数据库，GIS等技术支持下，全面，准确，快速地获取流域要素数据，对流域数字化的实现起着至关重要的作用。     

云南石林喀斯特地区地表蒸散发遥感反演研究

云南石林喀斯特地区属于典型的生态脆弱区,地表蒸散是喀斯特地区的重要地表环境参数。采用Landsat5 TM遥感影像数据和地面气象测站辅助数据,利用改进的Priestlry-Tayley方程算法反演实验区地表蒸散,与传统方法相比,该方法不需要过多的气象参数和繁琐的计算,并且具有较好的反演精度。采用MOD16蒸散发数据和实际测站蒸散发数据与TM反演蒸散发数据进行精度检验,研究区TM反演蒸散发数据与实际测站数据进行对比分析,绝对误差为-0.32 mm,测站点处MOD16蒸散发数据与实际测站数据进行对比分析,绝对误差为-1.05 mm。最后随机选取地表土壤和植被类型的测试点,实验结果表明TM反演蒸散发数据和MOD16蒸散发数据在土壤测试点的平均绝对误差为-0.78 mm,植被测试点的平均绝对误差为3.795 mm。     

利用遥感数据反演渤海海域叶绿素的浓度

依据神经网络算法和叶绿素荧光算法的基本理论,处理海洋遥感数据,反演渤海海域叶绿素浓度,并将反演结果同实测海洋叶绿素浓度进行比较．神经网络算法无法精确地从云层覆盖区获得叶绿素浓度,而荧光算法则可以突破云层的干扰获得接近实际值的叶绿素浓度．     

滇中不同次生演替阶段植被类型对林冠截留的影响

主要研究了滇中地区半湿润常绿阔叶林不同次生演替阶段的四种植被类型（桉树人工林、云南松林、针阁混交林、次生常绿阔叶林）的林冠截留与降雨量关系,并系统研究了林冠截留与多样性指数、叶面积指数及乔木层盖度的关系。结果表明四种植被类型的林冠截留量与降雨量都成对数函数关系I=a×1nP＋b,随着群落结构复杂程度增高,则参数a值也相应的表现为桉树人工林（3.05）〈云南松林（6.04）〈针阔混交林（7.13）〈次生常绿阔叶林（7.33）;林冠截留率与降雨量成幂函数关系Ic=a×P^b。林冠截留量及林冠截留率与多样性指数、叶面积指数及乔木层盖度呈现线性关系。     

基于DART模型森林结构参数反演

为充分发挥多角度遥感技术在森林资源监测过程中的作用,首先需要认识遥感信号产生的机理,了解植被冠层辐射传输的过程,建立合适的数学模型进行定量描述,最终达到从遥感信号中提取植被信息的目的。利用CHRIS多角度遥感数据验证DART多角度物理模型,DART多角度物理模型确定影响双向反射率分布函数(BRDF)的不同敏感参数,根据试验区的特点设计并正演建立查找表,由平方差最小原则通过多角度遥感图像反演LAI。反演得到的LAI与样地实测数据比较分析,结果表明多角度遥感反演精度满足要求。     

The gap probability model for canopy thermal infrared emission with non-scattering approximation

To describe canopy emitting thermal radiance precisely and physically is one of the key researches in retrieving land surface temperature (LSI) over vegetation-covered regions by remote sensing technology. This work is aimed at establishing gap probability models to describe the thermal emission characteristics in continuous plant, including the basic model and the sunlit model. They are suitable respectively in the nighttime and in the daytime. The sunlit model is the basic model plus a sunlit correcting item which takes the hot spot effect into account. The researches on the directional distribution of radiance and its relationship to canopy structural parameters, such as the leaf area index (LAI) and leaf angle distribution (LAD), were focused. The characteristics of directional radiance caused by temperature differences among components in canopy, such as those between leaf and soil, and between sunlit leaf or soil and shadowed leaf or soil, were analyzed. A well fitting between experimental data an     

The gap probability model for canopy thermal infrared emission with non-scattering approximation

To describe canopy emitting thermal radiance precisely and physically is one of the key researches in retrieving land surface temperature (LST) over vegetation-covered regions by remote sensing technology. This work is aimed at establishing gap probability models to describe the thermal emission characteristics in continuous plant, including the basic model and the sunlit model. They are suitable respectively in the nighttime and in the daytime. The sunlit model is the basic model plus a sunlit correcting item which takes the hot spot effect into account. The researches on the directional distribution of radiance and its relationship to canopy structural parameters, such as the leaf area index (LAI) and leaf angle distribution (LAD), were focused. The characteristics of directional radiance caused by temperature differences among components in canopy, such as those between leaf and soil, and between sunlit leaf or soil and shadowed leaf or soil, were analyzed. A well fitting between experimental data and the theoretical calculations shows that the models are able to illustrate the canopy thermal emission generally.     

多云雾山丘地区遥感定量化理论及应用进展

在分析光学与微波遥感各自的应用现状及面临的挑战的基础上,从数据层、数据预处理和定量化理论与方法3个层面详细分析和总结了适用于多云雾山丘地区复杂环境的遥感定量化应用理论与方法,包括面向对象的反演策略、主被动遥感协同、时间序列建模、前向模型地形效应修正、弱敏感参数反演等。同时,结合研究团队近年在多云雾山丘地区遥感定量应用的研究实践,给出西南地区的土地连续变化监测、森林火灾风险评估、干旱监测、植被覆盖条件下的土壤水分主被动遥感反演等方面的应用实例。     

Response of sediment yield to vegetation restoration at a large spatial scale in the Loess Plateau

The impact of vegetation coverage on erosion and sediment yield in the Loess Plateau has been extensively studied, but the research has been primarily based on observations from slope runoff plots or secondary forest regions; the scaling method remains unresolved when it is applied at a large spatial scale, and it is difficult to apply to regions with severe soil and water loss given the predominance of herbs and shrubs. To date, there is little data on the quantitative impact of changes to vegetation on sediment concentration at a large spatial scale. This paper is based on vegetation information from remote sensing images, measured rainfall and sediment data over nearly 60 years, and results from previous runoff and sediment variation research on the Yellow River. We introduce the concepts of a sediment yield coefficient and the percentage of effective vegetation and erodible area, analyze the impact of different vegetation conditions on the flood sediment concentration and sediment yield, and evaluate the effect of rainfall intensity on sediment yield under different vegetation conditions at the watershed scale. We propose models to evaluate the impact of vegetation on sediment yield in the loess gully hilly region, which are based on remote sensing data and support an application at a large spatial scale. The models can be used to assess sediment reduction that results from the current significant improvement of vegetation in the Loess Plateau.     

Retrieval of canopy biophysical variables from remote sensing data using contextual information

In order to improve the accuracy of biophysical parameters retrieved from remotely sensing data, a new algorithm was presented by using spatial contextual to estimate canopy variables from high-resolution remote sensing images. The developed algorithm was used for inversion of leaf area index （LAI） from Enhanced Thematic Mapper Plus （ETM＋） data by combining with optimization method to minimize cost functions. The results show that the distribution of LAI is spatially consistent with the false composition imagery from ETM＋ and the accuracy of LAI is significantly improved over the results retrieved by the conventional pixelwise retrieval methods, demonstrating that this method can be reliably used to integrate spatial contextual information for inverting LAI from high-resolution remote sensing images.     

鄱阳湖区植被覆盖度的遥感估算

植被覆盖度是一个十分重要的生态学参数,其对于全球环境变化和监测研究具有重要意义.为了有效地从遥感资料中提取植被覆盖度,在像元二分模型两个重要参数推导的基础上,对已有模型进行了改进,建立了用归一化植被指数(NDVI)估算植被覆盖度的模型.运用该模型对鄱阳湖区2003年的植被覆盖度进行了估算,通过鄱阳湖部分地区的实地考察,对2003年的植被覆盖度估算结果进行了验证,结果表明使用此改进模型进行植被覆盖度遥感监测是有效可行的.     

The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model

Offshore oil slicks are significant for both the monitoring of marine spill accidents and the detection of marine oil resources.The use of remote sensing technology to detect the thickness of oil slicks is a major area of research.The reflected light from oil slicks changes with the thickness of the oil.This is the theoretical basis of research on optical remote sensing of offshore oil slicks.A two-beam interference model that considers the offshore oil slick as a flat plate has been developed in this study...     

A case study on fractal simulation of forest fire spread

This paper relates to the semi-empirical model based on fire field energy balance and the physical model based on land temperature, aiming to provide a practical way of describing fire spread. Fire spread is determined by the characteristics of combustible materials and the agency of meteorological factors and terrains. Combustible materials, such as surface area, have no featured scale, yet the process of forest fire spread contains the self-replicating feature, both of which contribute to the self-similarity of fire spread. Consequently, fire behavior can be described by fractal geometry. In this research, we select Wuchagou forest in Da Hinggan Mountains as the experimental site where a forest fire took place three years ago. The forest fire was detected on low-resolution NOAA-AVHRR images, and fire spread was simulated on high-resolution TM images as another attempt to merge information. Based on remote sensing and GIS, we adopted the method of limited spreading lumping (DLA) to describe growing phe