基于规则的高分影像不透水层提取技术研究

为满足城市环境评价、城市规划监测、城市水循环评价对城市不透水层检测的需求,本文以国产高分卫星多光谱数据为研究基础,提出了一种新颖的基于规则的高分辨率多光谱影像不透水层提取方法,该方法利用归一化指数模型,融合对象统计特征,制定综合判定规则,可有效提升城市区域不透水层的提取精度。同时利用国产卫星数据,选择了典型的10个城市进行实验验证,取得了良好的效果。该方法可广泛应用于城市外轮廓提取、城市环境评估、城市扩展评估等研究领域。     

植物在不同形态和不同状态下的荧光光谱特征研究

本文从光合作用的角度出发,讨论了植物叶片在不同形态、不同状态下的荧光光谱特征以及它们对荧光光谱的影响。文章涉及了以下几方面的内容:(1)植物在离体形态和活体形态下的荧光光谱特征;(2)叶片正面与反面的荧光光谱特征;(3)植物不同器官对荧光光谱的影响;(4)叶片放置时间对荧光光谱的影响;(5)叶片经不同处理时对荧光光谱的影响等。其目的是为激光荧光技术用于植被遥感的实施提供基础数据。     

延河流域植物光谱特征分析

介绍了延河流域主要植物的光谱特征,分析了形成植物光谱特征差异的主要内在原因和影响因素,即植物体内的叶绿素(维生素a,b)、胡萝卜素、氮、木质素、纤维素的含量是决定植物光谱特征的根本因素,植被覆盖度、太阳高度角、大气特征、背景地物、观测几何及植被的生长阶段等是植物光谱特征差异的主要影响因素.     

微量元素在植物光谱中的响应机理研究

微量元素与植物光谱特征的研究是光学遥感定量化研究的重要内容之一。本研究利用高光谱地面光谱仪（GER）在湖南黔阳地区不同地质地球化学背景下的同一垂直剖面上分别测量了岩石、土壤植物（林灌草）的反射光谱曲线和植物叶片的8种微量元素含量。通过研究微量元素Fe,Mn,Cu,Zn,Co,Cr,Mo,B与植物（包括林灌草）反射光谱间的相关性研究发现Co的含量与植物光谱绿区（0．56μm附近）反射率存在强的负相关，Mn,B,Mo和Zn分别在可见光、近红外、短波红外存在较好的相关性和光谱响应。     

植物叶面铁尾矿粉尘光谱测试与定量反演实验

目前我国累计堆存的铁尾矿量高达约50亿t,所产生的尾矿粉尘污染极其严重。为此,使用辽宁鞍山矿区铁尾矿粉尘进行实景观测实验,采用人工模拟降尘与光谱测量手段,研究了降尘量对植物叶片光谱的影响规律;并利用降尘量与植物叶片光谱相关性最好的优势波段与铁元素的光谱吸收特征,分别建立了叶面降尘量的基于植物叶片的优势波段反射率和基于铁元素的独特光谱吸收指数的2种定量反演模型。研究表明:随着铁尾矿粉尘降尘量逐渐增大,植物叶片反射光谱曲线与粉尘的光谱曲线差异逐渐减小;2种反演方式中降尘量与植物叶片光谱变量均呈极显著相关,但基于铁元素光谱吸收特征的定量反演模型精度更高。研究结果可为高光谱遥感应用于矿区降尘量定量监测提供基础模型与技术依据。     

应用荧光光谱特征作受害植物判别指标的研究

本文讨论了几种植物在正常、受害及衰老状况下的荧光光谱特征及其变化。结果表明,叶绿素两个荧光峰强度的消长与植物受害程度有着内在的联系,利用这种关系可预测植物长势和进行植物生理状态的研究。     

典型地物光谱空间结构特征与基本统计参数分析

分别从光谱曲线及光谱特征空间入手,对内蒙古突泉与青海同仁研究区野外实测岩石、土壤和植被等3类典型地物的光谱数据进行了分析,发现研究区无论在光谱曲线空间,还是在光谱特征空间,同类地物的分布形态基本一致,而不同之处是由不同地区的地质地貌、生态环境与气候因素决定的,但不影响其空间分布形态的整体特征.通过分析与实验,发现了几种能够在光谱特征空间对上述3类特征地物进行较好区分的波段组合,可以利用这几种波段组合指导根据遥感图像生成的二维散点图对这3类地物的分类,有助于改进遥感蚀变信息提取方法.     

基于CGCS2000的苏州平面坐标系建立

苏州市及其各区（市）均建立了基于克拉索夫斯基椭球的城市平面坐标系,在国家全面推广使用CGCS2000和苏州市域一体化建设的背景下,亟需建立CGCS2000椭球下全市统一的坐标系。通过分析CGCS2000（国家标准3°带高斯投影）和现行苏州城市平面坐标系在苏州地区的适宜性后,研究了结合苏州市地理位置和地形地貌特征,以“中央子午线和参考椭球面为最佳选取”的坐标系建立综合比选方案。在此基础上,建立了苏州2000坐标系,并实现了将CGCS2000引入苏州以及现行苏州城市平面坐标系与CGCS2000的联系,可为国内建立基于CGCS2000的城市相对独立平面坐标系提供参考。     

高光谱遥感在植物多样性研究中的应用进展与趋势

人类活动、极端气候、物种入侵等事件导致植物的生物多样性丧失加剧,生物多样性保护迫切需要快速准确地收集陆地植物多样性信息。高光谱遥感的出现,为大空间尺度上的植物多样性研究提供了技术基础,为群落和景观水平的生物多样性相关理论的验证提供了契机。本文简要回顾了近年来高光谱遥感技术的发展及其在植物多样性研究中的应用。重点介绍了两类高光谱遥感反演多样性的手段,即直接反演和间接反演。直接反演手段以光谱变异假说为理论基础,从光谱曲线特征入手直接建立光谱信息与植物多样性的关系;间接反演手段则通过植被指数将光谱信息关联植物多样性,或通过定量反演功能性状计算功能多样性指标,进而实现植物多样性的间接估测。论文进一步结合实例,论述了高光谱遥感技术在大尺度生物多样性相关研究中的应用,如物种入侵监测、物种分布及多样性格局制图、生物多样性与生态系统功能关系研究。最后分析了高光谱遥感技术在生态研究应用中的局限性。随着多源遥感技术的发展日渐成熟,高光谱遥感技术与地面通量监测、激光雷达、计算机可视化等其他技术的协同应用可能是在生物多样性研究领域中一个新的发展方向。     

地面成像和非成像地物光谱仪在不同水分环境下湿地植被光谱特征对比研究——以东洞庭湖湿地区域苔草植被光谱特征为例

利用SOC710VP成像光谱仪和ASD Field Spec 3地物光谱仪在湿地区域获取了典型湿地植被苔草光谱反射数据信息,比较了在不同水分环境下两个仪器在400—1 000 nm波长范围的光谱特征,对两种仪器的光谱结果进行了9种典型植被指数运算和比较。结果表明,在不同的水分环境下(土壤含水率51%、32%、14%三个区域比较分析)SOC710VP的反射率曲线和地物光谱仪ASD Field Spec 3的趋势相近,二者有很好的一致性,表现在550 nm和730 nm的反射峰,690 nm和970 nm的吸收谷,以及连续的近红外反射平台。二者也有非常明显的区别:1)SOC710VP在3个土壤水分环境下的苔草叶片光谱值都大于ASD Field Spec 3所采集到的苔草叶片光谱反射值;2)SOC710VP反射率曲线没有ASD Field Spec 3测出的原始光谱曲线平滑,波动幅度变化更大,在近红外波段较明显,变化更清晰,利于后续的光谱端元聚类分析。综上证明:成像光谱仪获取的数据具有图谱合一、光谱曲线特征可靠的特征,在湿地近地高光谱遥感研究中具有很大潜力,拓展了湿地资源遥感监测的技术手段。     

Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice

The common spectra wavebands and vegetation indices (VI) were identified for indicating leaf nitrogen accumulation (LNA), and the quantitative relationships of LNA to canopy reflectance spectra were determined in both wheat (Triticum aestivum L.) and rice (Oryza sativa L.). The 810 and 870 nm are two common spectral wavebands indicating LNA in both wheat and rice. Among all ratio vegetation indices (RVI), difference vegetation indices (DVI) and normalized difference vegetation indices (NDVI) of 16 wavebands from the MSR16 radiometer, RVI (870, 660) and RVI (810, 660) were most highly correlated to LNA in both wheat and rice. In addition, the relations between VIs and LNA gave better results than relations between single wavebands and LNA in both wheat and rice. Thus LNA in both wheat and rice could be indicated with common VIs, but separate regression equations are better for LNA monitoring.     

高光谱反演水稻叶面积指数的主成分分析法

为了通过水稻冠层反射光谱来提取水稻叶面积指数信息，尝试利用辐射传输模型PROSPECT+SAIL来模拟水稻冠层反射光谱， 比较了各植被指数中叶面积指数(LAI)和叶绿素浓度的相关性。在观察光谱曲线后发现，红边位置光谱可以较好地区分LAI和叶绿素 浓度二者引起光谱变化的差异。由此提出对700 nm~750 nm区间内的反射光谱做主成分变换，并利用第2主成分与LAI建立反演模型( 即主成分分析法)，取得了较好效果，表明在植被指数趋近于饱和以至于无法区分二者相关性时，主成分分析法可以作为一种简单 而有效提取水稻叶面积指数信息的补充手段。     

用卫星高光谱数据提取德兴铜矿区植被污染信息

在深入分析研究德兴铜矿矿区植被光谱特征的基础上,利用美国EO-1卫星Hyperion高光谱数据,通过反演表征植物生理状态的光谱特征参数(红边位置和最大吸收深度)变异,提取与污染相关的信息,获取了矿山植被污染生态效应概况,为矿山污染的诊断和监测提供新技术和知识支撑。     

我国东部某地油气微渗漏的遥感研究

我国东部某地一些油气田区的遥感图像(本文为国土卫星彩红外片)上,常见有一些灰白色、浅褐色云雾状色调异常,经过地植物、土壤的地面光谱测试和土壤气体化探检查,发现色调；异常范围内、外植物和土壤光谱存在一定差异,异常内还发现有烃类气体异常,这种色调异常极有可能与油气微渗漏有关。对这种遥感图像上的色调异常进行的计算机增强处理研究表明,正规化与频谱变量、时间变量标准化交换组合处理效果较好,处理后的图像上色调异常显示十分明显。据永安地区国土卫星彩红外片正规化、标准化组合处理图像上显示的色调异常与已知油气田十分吻合,说明该处理方法是有效的。     

INTERPRETATION OF ECOLOGICAL-SOIL CHARACTERISTICS OF WOODED STEPPE ZONE IN THE CENTRAL RUSSIAN UPLAND

The authors describe how remote sensing imagery can be employed in the identification of different types of chernozem soils in a predominantly agricultural zone (forest steppe), where natural vegetation (normally one of the best vegetation indicators) has been largely displaced by farm fields. A multi-stage methodology is outlined whereby small-scale imagery is used to delineate large regions of similar bioclimatic-geologic characteristics, from which areas of similar soil formation conditions are distinguished. Multispectral and multitemporal space imagery then is employed to detect less salient ecological-soil differences that can affect phototone and image texture. Translated by Edward Torrey, Alexandria, VA 22308 from: G. V. Dobrovol'skiy and V. L. Andronikov, eds., Aerokosmicheskiye metody v pochvovedenii i ikh ispol'zovaniye v sel'skom khozyaystve: sbornik nauchnykh trudov [Remote Sensing Methods in Soil Science and Their Utilization in Agriculture: A Collection of Scientific Works]. Moscow: Nauka, 1990, pp 103–109.     

基于TM图像的农业区域植被覆盖变化检测

以交叉相关光谱匹配(cross correlogram spectral matching,CCSM)为基础构建土地覆盖变化强度指标,利用华北农业植被覆盖区2期不同时相的TM图像计算该地区土地覆盖变化强度图像.认为变化强度图像任意二阶邻域中像素的变化强度服从隐马尔可夫模型,用马尔可夫随机场-最大后验估计(maxium a psteriori estimationof markov random field,MRF - MAP)的方法从变化强度图像中提取植被变化区域.实验证明:该方法能够有效识别各种外源噪声造成的农业植被覆盖区域同物异谱的现象,可准确提取植被变化区域;但对于水体区域存在误判现象.     

Comparison of Two Data Smoothing Techniques for Vegetation Spectra Derived From EO-1 Hyperion

Hyperspectral data are generally noisier compared to broadband multispectral data because their narrow bandwidth can only capture very little energy that may be overcome by the self-generated noise inside the sensors. It is desirable to smoothen the reflectance spectra. This study was carried out to see the effect of smoothing algorithms - Fast-Fourier Transform (FFT) and Savitzky–Golay (SG) methods on the statistical properties of the vegetation spectra at varying filter sizes. The data used in the study is the reflectance spectra data obtained from Hyperion sensor over an agriculturally dominated area in Modipuram (Uttar Pradesh). The reflectance spectra were extracted for wheat crop at different growth stages. Filter sizes were varied between 3 and 15 with the increment of 2. Paired t-test was carried out between the original and the smoothed data for all the filter sizes in order to see the extent of distortion with changing filter sizes. The study showed that in FFT, beyond filter size 11, the number of locations within the spectra where the smooth spectra were statistically different from its original counterpart increased to 14 and reaches 21 at the filter size 15. However, in SG method, number of statistically different locations were more than those found in the FFT, but the number of locations did not changing drastically. The number of statistically disturbed locations in SG method varied between 16 and 19. The optimum filter size for smoothing the vegetation spectra was found to be 11 in FFT and 9 in SG method.     

Evaluation of MIVIS Hyperspectral Data for Mapping Soil Degradation in an Upland Ecosystem of Southern Italy

Abstract

This paper describes the first stage of an experiment aiming to evaluate the potential and limitations of MIVIS data for mapping the degradational state of soils in a sub‐scene of a southern Apennines study area (Italy). After radiometric rectification of the image data and the collection of a field/laboratory spectral library, linear spectral mixture modelling (SMA) was used to decompose image spectra into fractions of spectrally distinct mixing components. Spectral endmember selection was based upon a principal component analysis (PCA) applied to a set of soil spectra, collected from the spectral library. The resulting abundance estimates (fractions) trough SMA were then analysed to identify soil conditions and to obtain an improved measure of dry and green vegetation cover. A map of soil conditions and dry‐green vegetation abundance, based upon MIVIS data was then derived from normalised fractions of soil‐vegetation endmembers obtained from SMA.     

Estimating soil salinity in Pingluo County of China using QuickBird data and soil reflectance spectra

Soil salinization is a worldwide environmental problem with severe economic and social consequences. In this paper, estimating the soil salinity of Pingluo County, China by a partial least squares regression (PLSR) predictive model was carried out using QuickBird data and soil reflectance spectra. At first, a relationship between the sensitive bands of soil salinity acquired from measured reflectance spectra and the spectral coverage of seven commonly used optical sensors was analyzed. Secondly, the potentiality of QuickBird data in estimating soil salinity by analyzing the correlations between the measured reflectance spectra and reflectance spectra derived from QuickBird data and analyzing the contributions of each band of QuickBird data to soil salinity estimation Finally, a PLSR predictive model of soil salinity was developed using reflectance spectra from QuickBird data and eight spectral indices derived from QuickBird data. The results indicated that the sensitive bands covered several bands of each optical sensor and these sensors can be used for soil salinity estimation. The result of estimation model showed that an accurate prediction of soil salinity can be made based on the PLSR method (R² = 0.992, RMSE = 0.195). The PLSR model's performance was better than that of the stepwise multiple regression (SMR) method. The results also indicated that using spectral indices such as intensity within spectral bands (Int1, Int2), soil salinity indices (SI1, SI2, SI3), the brightness index (BI), the normalized difference vegetation index (NDVI) and the ratio vegetation index (RVI) as independent model variables can help to increase the accuracy of soil salinity mapping. The NDVI and RVI can help to reduce the influences of vegetation cover and soil moisture on prediction accuracy. The method developed in this paper can be applied in other arid and semi-arid areas, such as western China.     

基于色调饱和度亮度模型的可见光植被提取

针对遥感影像只具有红（R）、绿（G）、蓝（B）3个可见光波段时无法利用归一化植被指数（NDVI）方法提取植被信息的现状,本文提出了一种基于色调饱和度亮度（HSL）模型的可见光植被提取方法。利用自主研发的系统,将影像从RGB彩色空间变换至HSL彩色空间,构建归一化色调亮度植被指数（NHLVI）,通过分析植被与非植被信息在HSL彩色空间中的特征,以及NHLVI、H、S、L、R、G、B各分量的特征,确定协同NHLVI、S分量提取植被信息,利用B分量特征剔除结果中的非植被信息,从而实现植被信息提取,并提高提取精度。研究表明,该方法在现有NHLVI指数方法基础上,加入S分量,提升了可见光植被提取的精度及方法的适用性。