黑河中游绿洲灌溉区土地覆盖与种植结构空间格局遥感监测

以高空间分辨率、高光谱分辨率CASI航空遥感数据作为采样带,对黑河中游绿洲灌溉区土地覆盖和农作物种植结构空间格局进行遥感监测。设计了分层分类方法,综合采用基于像素和基于对象的2种遥感图像分类方法对航空样带区域进行土地覆盖制图。根据实地土地覆盖类型调查与目视解译,对样带土地覆盖和农作物种植结构的分类结果进行精度评价,总体分类精度为84.2%,Kappa系数为0.793。与样带区域2007年Landsat TM/ETM+土地覆盖产品相比,高分辨率CASI航空数据能够对树木、草地与农作物类别进行有效监测。监测结果表明,中游绿洲灌溉区内接近59.1%的地区为裸地与建筑用地;植被覆盖区域占39.8%,其中,农田34.9%,树木5.3%,草地仅有0.1%;而在农田区域中玉米为大宗作物,分类成数占96.1%。研究结果表明高质量与高分辨率的航空遥感数据能够实现对流域下垫面异质性进行有效监测,为生态—水文过程研究提供高分辨率的下垫面类型信息。     

Optimization of Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) imagery,in situ data with chemometrics to evaluate nutrients in the Shenandoah River,Virginia

Abstract

Phosphorus and nitrogen have a strong influence on water resource and remote sensing technology has demonstrated that water quality monitoring over a greater range of temporal and spatial scales can be used to overcome these constraints. This research was designed to demonstrate the feasibility of combining remotely-sensed water quality observation and chemometric techniques to estimate water quality in the Shenandoah River. We used Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) imagery, combined with a partial least squares analysis to characterize the spatial distribution of nutrients in the Sheanadoah river. ARCHER retrievals for phosphorous with cross-validation show high sensitivity in estimating water quality in the Shenandoah River with the Bentonville in the South Fork, with an R2 of 0.93 sensitivity. Using the significance level of 0.05, data from the summer of 2014 showed that the p-value was 0.00 for both nitrogen and phosphorous. Results show retrieval method is transferable.     

基于叶绿素荧光峰特征的浑浊水体悬浮物浓度遥感反演

内陆水体光学特性复杂,其水质参数遥感反演是当前环境遥感研究的热点与难点.2004年10月在太湖实测了67个站点的遥感反射率与相应站点水质参数浓度,通过对水体反射率光谱的分析发现,秋季太湖悬浮物主导了水体光学特性,叶绿素荧光峰的特征主要体现为悬浮物浓度的变化.据此建立了基于水面实测岛光谱遥感反射率数据的叶绿素荧光峰特征与悬浮物浓度之间的拟合关系,发现二者具有很好的响应关系.具体分析了叶绿素荧光峰绝对高度、基线高度、归一化高度(分别归一化到560nm附近最大反射率波段与近红外810nm附近最大反射率波段)及荧光峰积分面积(包括积分总面积、基线以下面积与基线以上面积)等儿种光谱特征与悬浮物浓度之间的关系,其相关系数(R2)分别为0.8822、0.7483、0.8901、0.8547、0.8927、0.8877、0.8632,平均相对误差分别为27.25%、41.03%、27.11%、25.75%、24.91%、25.47%、27.54%.总体反演精度较高,其中总积分面积法效果最好,基线高度法效果最差,而叶绿索荧光峰波段的位移与悬浮物浓度之间不存在明显的相关性.研究结果表明叶绿素荧光峰特征在浑浊内陆水体悬浮物浓度信息提取中具有很好的应用前景,该方法可为浑浊的二类水体悬浮物遥感反演提供了一个新思路.     

An assessment of independent component analysis for detection of military targets from hyperspectral images

Hyperspectral data acquired over hundreds of narrow contiguous wavelength bands are extremely suitable for target detection due to their high spectral resolution. Though spectral response of every material is expected to be unique, but in practice, it exhibits variations, which is known as spectral variability. Most target detection algorithms depend on spectral modelling using a priori available target spectra In practice, target spectra is, however, seldom available a priori. Independent component analysis (ICA) is a new evolving technique that aims at finding out components which are statistically independent or as independent as possible. The technique therefore has the potential of being used for target detection applications. A assessment of target detection from hyperspectral images using ICA and other algorithms based on spectral modelling may be of immense interest, since ICA does not require a priori target information. The aim of this paper is, thus, to assess the potential of ICA based algorithm vis a vis other prevailing algorithms for military target detection. Four spectral matching algorithms namely Orthogonal Subspace Projection (OSP), Constrained Energy Minimisation (CEM), Spectral Angle Mapper (SAM) and Spectral Correlation Mapper (SCM), and four anomaly detection algorithms namely OSP anomaly detector (OSPAD), Reed–Xiaoli anomaly detector (RXD), Uniform Target Detector (UTD) and a combination of Reed–Xiaoli anomaly detector and Uniform Target Detector (RXD–UTD) were considered. The experiments were conducted using a set of synthetic and AVIRIS hyperspectral images containing aircrafts as military targets. A comparison of true positive and false positive rates of target detections obtained from ICA and other algorithms plotted on a receiver operating curves (ROC) space indicates the superior performance of the ICA over other algorithms.     

水稻叶片不同光谱形式反演叶绿素含量的对比分析研究

通过对常优1号和武粳15两个品种水稻叶片的反射率R、lg(1/R)、反射率一阶微分（FD）和反射率归一化（BN）等光谱形式的测量和计算，分析了叶片光谱不同变化形式与叶绿素含量的相关关系，建立了统计方程，并进行了比较与评价，同时，对反演方程的最佳波段选择进行了探讨。结果表明，叶绿素含量与反射率一阶微分光谱方程的相关性最强，而采用lg(1/R)的光谱形式能够提高遥感反演叶绿素含量的效果。经验证，两个水稻品种叶绿素含量的模拟值与实测值的复相关系数R2分别达到0.641和0. 818。     

基于光谱相似性的多光谱数据纹理编码算法研究

基于多光谱纹理“映射模式”概念，提出了基于光谱数据相似性的多光谱、高光谱数据的编码方法。利用光谱相似测度对不同类型的纹理进行编码，表征地物的全局纹理特征，将纹理提取的算法扩展到多维光谱图像分析中，提出了多尺度纹理组合算法。试验证明，该方法合理有效，可大大提高分类的准确性和精度。     

星载高光谱成像光谱仪的特性与应用

介绍了星载高光谱成像光谱仪的种类、技术参数和数据特点,指出了成像光谱数据处理软件包应具有的功能,概括了成像光谱仪数据的应用前景。     

推帚式超光谱成像仪(PHI)关键技术

成像光谱仪把二维成像技术和光谱技术有机地结合在一起,是具有重大潜力的对地观测仪器。近年来,随焦平面探测器推帚成像技术的发展,先进国家研制成功了超光谱成像仪,成为成像光谱技术的又一生长点。本文结合工作经验,介绍以硅面阵电荷耦合器件（ＣＣＤ）为探测器的推帚式超光谱成像仪ＰＨＩ的关键技术及发展前景。     

Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping

Hyperspectral images have wide applications in the fields of geology, mineral exploration, agriculture, forestry and environmental studies etc. due to their narrow band width with numerous channels. However, these images commonly suffer from atmospheric effects, thereby limiting their use. In such a situation, atmospheric correction becomes a necessary pre-requisite for any further processing and accurate interpretation of spectra of different surface materials/objects. In the present study, two very advance atmospheric approaches i.e. QUAC and FLAASH have been applied on the hyperspectral remote sensing imagery. The spectra of vegetation, man-made structure and different minerals from the Gadag area of Karnataka, were extracted from the raw image and also from the QUAC and FLAASH corrected images. These spectra were compared among themselves and also with the existing USGS and JHU spectral library. FLAASH is rigorous atmospheric algorithm and requires various parameters to perform but it has capability to compensate the effects of atmospheric absorption. These absorption curves in any spectra play an important role in identification of the compositions. Therefore, the presence of unwanted absorption features can lead to wrong interpretation and identification of mineral composition. FLAASH also has an advantage of spectral polishing which provides smooth spectral curves which helps in accurate identification of composition of minerals. Therefore, this study recommends that FLAASH is better than QUAC for atmospheric correction and correct interpretation and identification of composition of any object or minerals.