基于聚类的高光谱图像非监督波段选择方法

非监督波段选择方法是高光谱图像降维的主要方法,但现有方法应用到实际高光谱图像分类时,分类精度并不理想。本文提出一种改进的基于聚类的高光谱图像非监督波段选择方法,主要通过对传统的K-means聚类算法进行两方面改进:一方面是相似性度量函数;另一方面是聚类中心的选取。然后,通过实验数据用支持向量机法(SVM)对所提算法及现有的三种非监督波段选择方法进行分类。最后,用总体精度(OA)和Kappa系数评价分类结果。表明本文所提方法在分类精度方面优于其他现有方法。     

辽河盆地及其邻区遥感图像的石油地质分析

通过对不同种类、不同波段及不同处理方法所获得图像的分析表明, 一种卫片组合图像处理 方法, 即线性拉伸-直方圆调整-局部增强-彩色级上色所产生的图像, 对了解辽河盆地前第三 系基底起伏状况及其结构特点具有良好效果。 地质解译分析肯定了北东(含北北东)向线性构造的主导作用, 但同时遥感信息强烈地反映 了北西向线性构造对盆地构造格架的影响。地质解译还表明, 辽河盆地的环形影像具有两个明显 特点:(1)浅色影像以反映正向构造为主;(2)深色影像以反映负向构造为主, 而已知油田在 标准假彩色图像上也具有明亮的浅色圆形或块状影像特征。因此, 可结合其它地质资料的综合分 析, 以类比方法来预测新的油气田。     

江汉-洞庭盆地及华容隆起新构造运动特征遥感分析

长江流域基础地质遥感调查与监测,采用2000年左右获取的1:25万Landsat ETM图像进行地貌、第四纪地质和新构造遥感调查与研究.针对洞庭湖重点区,采用航片、ALOS、SPOT等高分辨率数据进行1:5万详细遥感调查.通过调查与综合分析认为:江汉-洞庭盆地为-燕山晚期至新生代形成的断陷盆地,总体处于沉降状态,盆地内部因差异抬升作用形成华容次级隆起,从而在山区广泛沉积了河湖相、冲洪积相及山麓相的第四纪沉积物,盆地内部第四系基本为连续沉积.江汉-洞庭盆地周围隆起区则呈间歇性抬升.新构造运动主要表现为隆起与拗陷、掀斜和断裂等几种形式,其构造沉降与周边山体隆升主要受盆地边缘和盆地内部断裂的控制.     

应用遥感图像对南襄盆地断裂系统及盆地形成机制的研究

南襄盆地是中新生代含油气沉积盆地,它们形成演化与断裂活动密切相关。通过应用1∶20万卫星TM图像进行线性构造解译,确定了区内3种线性构造类型,明确了盆地基底构造与区域构造的关系,并编制了盆地构造格架图和断裂密度图等图件,为油气预测提供了重要依据。作者还应用应变场的反演理论模拟了凹陷的受力方式,认为断裂作用引起的地幔隆起是凹陷形成的重要原因之一。     

基于AVHRR/2 10 d合成数据的青藏高原亚像元雪填图

为了满足水文和气象模型对长时段积雪面积数据的需求,基于第二代甚高分辨率辐射计（second series of advanced very high resolution radiometer,AVHRR/2）的10 d合成数据提出了一种青藏高原地区AVHRR/2数据亚像元雪填图算法,将中分辨率遥感数据亚像元级积雪面积数据集延伸至30 a时间跨度。本文算法以多端元线性光谱混合分析模型为基础,以归一化植被指数、第一波段、第二波段等作为选取端元的指标,直接从AVHRR/2图像中自动选取所需雪端元与非雪端元。基于TM数据对该算法的AVHRR/2数据亚像元雪填图结果进行验证,其均方根误差接近0.1,在青藏高原山区具有较高的精度。     

针对MODIS数据的大气水汽含量反演及31和32波段透过率计算

 针对MODIS的波段特征,首先,用近红外波段反演大气水汽含量; 然后,通过LOWTRAN模拟大气水汽含量与MODIS 31和32热红 外波段透过率的统计关系; 最后,计算31和32波段的透过率。该方法克服了以往一景图像只用1个透过率的局限性,使得透过率的求 算精确到每1个像元,同时保证参数获取的实时性。     

泊江海子油气环状构造的发现及其对铀成矿的重要作用

 通过对鄂尔多斯盆地北部ETM遥感图像的解译和分析，发现了泊江海子环形构造，并对其进行了野外验证。研究认为，该环形构造不仅其成因与油气有关，而且对鄂尔多斯盆地北部砂岩型铀矿的成矿有重要的作用。     

基于优势集聚类和马尔科夫随机场的高光谱图像分类算法

为充分利用高光谱图像自身丰富的光谱信息和空间信息,提出一种基于优势集聚类和马尔科夫随机场相结合的高光谱图像分类算法。首先,分析高光谱图像局部空谱一致性,完成对波段信息量和差异程度的度量,构造无向加权图,利用优势集聚类方法选择出保留良好结构信息的最优波段子集;其次,通过马尔科夫随机场对波段选择后的相邻像元建立局部空谱一致性,有效利用图像空间上下文信息;最后,根据贝叶斯定理,将高光谱图像分类问题转化为最大后验概率的求解问题,从而获得分类结果。2个经典数据集(Indian Pines和Pavia University)的实验表明,相比其他同类算法,该算法能达到更高的总体分类精度和Kappa系数。     

改进的表观热惯量法反演土壤含水量

提出一种改进的表观热惯量计算模型,以中科院栾城农业生态系统试验站为基地,通过实测的模型参数,利用提出的表观热惯量模型计算不同植被覆盖下、不同实验区土壤含水量的热惯量值,并与土壤含水量进行相关性分析,以找到热惯量方法可以用来反演土壤含水量的适用条件(归一化植被指数NDVI的阈值).实验结果表明,该模型监测土壤含水量是可行的,在植被覆盖度较低的情况下(NDVI≤O.35)具有较高的精度,在植被覆盖度较高(NDVI＞0.35)时,热惯量模型失效,因此用热惯量方法反演土壤含水量植被覆盖时将NDVI阈值的最大值设为0.35.将该方法应用到MODIS数据中,以河北省栾城县、赵县、藁城市3市县为研究区,分别反演该区土壤含水量,反演结果与实际情况相符合.实地取点人工监测土壤含水量为25.1％,栾城站模型计算结果为22.4％,匹配性较好,该方法在遥感数据中得到了很好的应用.     

用MODIS影像和单窗算法反演环渤海地区的地表温度

在对地观测卫星MODIS的16个热红外波段中,其中有5个波段是针对地表温度来设计的,其中第31(10.78-11、28μm)和32(11．77-12．27μm)与TM的第6波段区间基本相同。运用单窗算法分别对这2个波段建立方程,然后通过对布郎克方程的辐射率和温度计算模拟,发现温度和辐射率近似线性相关,由此建立辐射率与温度T的线性方程,从而可以简化单窗算法的计算过程一最后运用单窗算法对31和32通道分别反演了环渤海地区的温度分布,并对环渤海地区的土地资源环境作了分析.     

松辽盆地西部斜坡区烃渗漏蚀变信息遥感探测

使用陆地卫星ETM+7图像对松辽盆地西部斜坡区进行稠油探测,图像增强方法有主成分分析、波段比值和假彩色合成等.主成分因子1,3,4,5-PC3(1,3,4,5主成分分析的第3主成分),1,3,5,7-PC3,2,3,5,7-PC3和3,4,5,7-PC4与波段比值3/1,4/3,7/5和(4/3)-(2/3)等用丁假彩色合成,在合成影像上圈定烃渗漏蚀变区域.结果表明烃渗漏蚀变区域与地质背景密切相关,与下伏油藏的分布大致相符.     

南中国海海洋油气遥感调查研究

对NOAA-11资料进行除云、大气订正和几何纠正后,用CH4、CH5波段进行SST处理,用CH5、CH2、CH1作假彩色合成图,并对CH1、CH4、CH5波段灰度值与南海相关研究点的海面温度、重力、磁力异常和热流值等实测数据进行多元相关分析,通过观测比较和理论分析,解决了海洋油气遥感技术和应用模型等问题,为海洋油气资源的探测提供科学依据.     

遥感技术预测油气勘探靶区

应用遥感技术预测油气勘探靶区具有低成本、高效率的特点。目前有直接和间接两种油气遥感方法用于预测油气勘探靶区。简单介绍了这两种方法的原理,重点对遥感影像中的线-环影像构造异常和烃渗漏异常所表现的特征进行了全面总结,最后对遥感技术在预测油气勘探靶区的应用前景进行了展望。     

遥感技术预测油气勘探靶区

应用遥感技术预测油气勘探靶区具有低成本、高效率的特点。目前有直接和间接两种油气遥感方法用于预测油气勘探靶区。本文简单介绍了这两种方法的原理，重点对遥感影像中的线-环影像构造异常和烃渗漏异常所表现的特征进行了全面的总结，最后对遥感技术在预测油气勘探靶区的应用前景进行了展望。     

利用TM高光谱图像提取青藏高原喀喇昆仑山区现代冰川边界

采用阈值法、监督分类、非监督分类、谱间关系法对冰川的TM图像进行了分类,证明利用比值图像取阈值是对冰川区图像分类的有效手段。对图像处理的结果进行了分析和解释,并指出了存在的问题。     

Delineation of surface waterlogged areas in parts of bihar using IRS-1C LISS-III data

Pre-monsoon and post-monsoon surface waterlogged areas were delineated using satellite remote sensing data for Muzaffarpur, Vaishali and Saran districts of North Bihar. Digital data of IRS-1C LISS-III sensor acquired on December 7, 1998 and April 6, 1999 were analyzed using digital image processing software-ERDAS Imagine 8.3.1. The surface waterlogged areas were delineated using modeling technique which is the most advanced and accurate method. Using the modeling technique, a pixel is classified as water if the digital number (DN) value of its Near Infra Red (NIR) band is less than the DN value of the Red band and the Green band, and the Normalized Difference Water Index (NDWI) is greater than or equal to 0.32. The pre-monsoon surface waterlogged areas are found to be 14.02, 23.61 and 9.61 km² while the post-monsoon surface waterlogged areas are found to be 231.83, 118.19 and 176.06 km² for Muzaffarpur, Vaishali and Saran districts, respectively. Also, land use/land cover maps were prepared.     

Evaluation of Landsat TM data for forest cover type and landuse classification in subtropical forests of Kumaon Himalaya (U.P.)

LANDSAT-TM has been evaluated for forest cover type and landuse classification in subtropical forests of Kumaon Himalaya (U.P.) Comparative evaluation of false colour composite generated by using various band combinations has been made. Digital image processing of Landsat-TM data on VIPS-32 RRSSC computer system has been carried out to stratify vegetation types. Conventional band combination in false colour composite is Bands 2, 3 and 4 in Red/Green/Blue sequence of Landsat TM for landuse classification. The present study however suggests that false colour combination using Landsat TM bands viz., 4, 5 and 3 in Red/Green/Blue sequence is the most suitable for visual interpretation of various forest cover types and landuse classes. It is felt that to extract full information from increased spatial and spectral resolution of Landsat TM, it is necessary to process the data digitally to classify land cover features like vegetation. Supervised classification using maximum likelihood algorithm has been attemped to stratify the forest vegetation. Only four bands are sufficient enough to classify vegetaton types. These bands are 2,3,4 and 5. The classification results were smoothed digitaly to increase the readiability of the map. Finally, the classification carred out using digital technique were evaluated using systematic sampling design. It is observed that forest cover type mapping can be achieved upto 80% overall mapping accuracy. Monospecies stand Chirpine can be mapped in two density classes viz., dense pine (<40%) with more than 90% accuracy. Poor accuracy (66%) was observed while mapping pine medium dense areas. The digital smoothening reduced the overall mapping accuracy. Conclusively, Landsat-TM can be used as operatonal sensor for forest cover type mapping even in complex landuse-terrain of Kumaon Himalaya (U.P.)     

Spatial statistical techniques for aggregating point objects extracted from high spatial resolution remotely sensed imagery

 Using a local maximum filter, individual trees were extracted from a 1 m spatial resolution IKONOS image and represented as points. The spatial pattern of individual trees was determined to represent forest age (a surrogate for forest structure). Point attributes, based on the spatial pattern of trees, were generated via nearest neighbour statistics and used as the basis for aggregating points into forest structure units. The forest structure units allowed for the mapping of a forested area into one of three age categories: young (1–20 years), intermediate (21–120 years), and mature (>120 years). This research indicates a new approach to image processing, where objects generated from the processing of image data (rather than pixels or spectral values) are subjected to spatial statistical analysis to estimate an attribute relating an aspect of forest structure. Received: 22 April 2002 / Accepted: 23 November 2002     

Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China

Abstract

Determining oil slick thickness plays an important role in assessing oil spill volume and its environmental impacts on the ocean. In this study, we used a Hyperion image of an oil spill accident area and seawater and fresh crude oil samples collected in the Bohai Sea of China. A well-controlled laboratory experiment was designed to simulate spectral responses to different oil slick thicknesses. Spectral resampling and normalization methods were used to reduce the differences in spectral reflectances between the experimental background seawater sample and real background seawater. Fitting the analysis with laboratory experimental data results showed a linear relationship between normalized oil slick reflectance and normalized oil slick thickness [20th band (R ²=0.92938, n=49, p<0.01), 26th band (R ²=0.93806, n=49, p<0.01), 29th band (R ²=0.93288, n=49, p<0.01)]. By using these statistical models, we successfully determined the normalized oil slick thickness with the Hyperion image. Our results indicate that hyperspectral remote sensing technology is an effective method to monitor oil spills on water. The spectral ranges of visible green and red light were the optimal bands for estimating oil slick thickness in case 2 water. The high, stabilized spectral reflectance of background seawater will be helpful in oil slick thickness inversion.     

基于Hyperion影像的涩北气田油气信息提取

 对柴达木地区涩北气田地质地理环境下的蚀变矿物进行分析，结合卫星高光谱遥感数据Hyperion的图谱，对已知气田区与背景区光谱特征进行相关分析，确定了932.64~1 346.25 nm与2 002.06~2 385.5 nm为油气信息识别的有利波长范围； 利用光谱角制图（SAM）技术提取了涩北气田油气的空间分布信息和台吉乃尔含气构造等远景区，为高光谱遥感油气勘探提供了有效技术方法与途径。