CBERS-02B星在轨测试数据国土资源应用评价

以中巴地球资源一号卫星02B星（CBERS-02B,以下简称为02B星）多光谱CCD数据和HR数据的2级产品为准,按照国土资源调查与监测的相关标准与技术规范,结合多光谱CCD和HR数据的影像质量、波段配准、几何畸变以及制图能力,从国土资源日常性调查业务、行政性监管与执法职能出发,对02B星在土地资源调查与监测、地质解译、矿化蚀变异常信息提取、地质灾害调查与监测、矿产资源开发状况调查与监测、区域生态地质环境调查等领域的遥感应用特点、关注的地类与地质要素的差异等方面开展应用评价。对02B星CCD和HR数据的国土资源调查与监测的应用能力进行了总结,对存在的问题进行了初步分析。该项研究对指导02B星数据的应用与后续星的研发具有重要意义。     

CBERS-02B星模拟数据地质资源专题应用评估

从遥感地质解译、矿化蚀变信息提取、矿产资源开发现状调查及环境变化信息提取等多方面对02B星模拟数据开展了应用试验评估,评价了02B星地质资源专题应用能力。     

CBERS-02星数据在三江平原湿地生态环境调查中的应用

为了探讨CBERS-02星（简称02星）数据在生态环境遥感调查中的应用价值,以三江平原湿地研究为例,通过与TM数据的对比,分析了02星数据的优势与不足。结果表明, 02星数据对各类湿地有较强的分辨能力,且数据价位优势突出,在平原区可以替代TM数据,应用前景广阔。     

资源三号02星激光测高精度分析与验证

资源三号02星搭载了我国首台对地观测的卫星激光测高试验性载荷,对该载荷的精度进行了理论分析,并采用多个区域进行了实际精度验证,同时对其在航天测绘中的应用进行了试验。资源三号02星激光测高仪在平坦地区(坡度≤2°)的理论高程精度为0.85m、平面精度14.2m。试验表明,资源三号02星激光测高仪获得的有效测高数据约占23.89%,检校场区域其高程精度为0.89m,平面精度为14.76m;华北地区高精度DSM地形数据验证其高程精度为1.09m,内陆渤海海面上的激光高程精度为0.47m。将激光足印点作为高程控制点时,在陕西渭南试验区能将资源三号02星立体影像无地面控制的高程精度从11.54m提高到1.90m。虽然资源三号02星激光测高仪为试验性载荷,但试验结果证实国产卫星激光测高数据能有效提高立体影像无地面控制的高程精度,在全球测图工程中具有推广应用价值,建议后续立体测图卫星搭载业务化应用的激光测高仪。     

基于CBERS-02B星HR影像的多源遥感数据融合研究

为寻求更加适合与CBERS-02B星HR数据融合的多光谱数据及融合方法,应用PCA、Brovey、SVR、IHS 4种变换方法,分别将CBERS-02B星HR数据与CBERS-02BCCD、ASTER、ALOS的多光谱数据进行融合,从光谱和空间信息两个方面对融合效果进行分析。结果表明:①CBERS-02B星HR数据与ALOS多光谱数据的融合图像质量高于其他两种组合,其中IHS变换法融合图像空间细节及光谱信息保持度最高,色调鲜明,地物可辨别能力强;②ASTER、CBERS-02BCCD参与融合时,SVR变换法比较适合;二者相比较ASTER数据参与融合质量较高;③CBERS-02B星HR数据与ALOS和ASTER多光谱匹配度高,在CBERS-02B星HR数据的使用过程中应尽量寻求其他来源的多光谱数据进行融合。     

CBERS-02B星数据融合方法评价

CBERS—02B星(以下简称02B星)多光谱CCD数据与全色HR数据空间分辨率相差较大,给图像融合带来一定困难。在对IHS变换、主成分分析变换、Brovey 变换、GS变换等融合算法分析的基础上,利用02B星数据进行了融合试验。通过对试验结果的目视评价与定量分析发现,PC变换和GS变换方法融合图像纹理信息较清晰,光谱保真度较好。在GS变换融合中,可利用02B星CCD相机第5波段模拟GS变换的低分辨率输入,融合结果统计值优于PC变换。     

CBERS-02B星数据质量评价及其铀成矿要素解译应用研究

利用遥感影像处理技术和数理统计方法,评价了中巴地球资源一号卫星02B星（CBERS—02B,以下简称02B星）遥感数据的空间特性和辐射特征,并与ETM＋多光谱数据主要特征参数进行了对比分析。在此基础上,以江西桃山花岗岩型铀矿田为试验区,结合航空放射性数据,开展了基于02B星遥感数据的控矿断裂带、热液蚀变带及主要成矿岩体等铀成矿要素的光谱特征识别与提取,并对该数据的地学应用潜力进行了评价。     

CBERS-02B星数据质量评价及铀成矿要素解译应用研究

利用遥感影像处理技术和数理统计方法,评价了中巴地球资源卫星02B星(CBERS-02B,以下简称02B星)遥感数据的空间特性和辐射特征,并与ETM+多光谱数据主要特性参数进行了对比分析.在此基础上,以江西桃山花岗岩型铀矿田为试验区,结合航空放射性数据,开展了基于02B星遥感数据的控矿断裂带、热液蚀变带及主要成矿岩体等铀成矿要素的光谱特征识别与提取,并对该数据的地学应用潜力进行了评价.     

CBERS-02B星数据土地利用动态遥感监测方法研究

研究了CBERS-02B星(简称02B星)HR和CCD数据在土地利用动态遥感监测中的应用,综合分析了目前常用的5种土地利用变化检测方法及其应用效果,提出了各种方法的适用条件和范围,为规模化应用02B星数据开展土地利用动态遥感监测奠定了技术基础.     

序

2007年9月19日,我国成功发射了中巴地球资源卫星02B星（以下简称02B星）,为我国遨游太空的国产卫星大家庭又增添了一位璀璨的新成员。02B星是中巴地球资源卫星02星的补充星,也是我国迄今为止空间分辨率最高的民用资源卫星。     

热带森林植被的动态变化遥感监测

本文讨论了以热带森林植被为主体的再生资源的面积动态变化监测。研究中包括两个部分。首先,我们利用多时相遥感图像对大面积的西双版纳州进行地类判读,系统地分析了森林植被的动态变化。其次,利用Landsat MSS和TM数据对自然保护区的动态变化进行了包含无监督分类和归一化差值植被指数分析的数字图像处理,变化分类也相当符合实际。总的实验结果表明,这种监测方法是很有效的,可在再生资源监测中特别是在森林植被监测中加以推广应用。     

Modelling for forest growing stock assessment using satellite data — A case study

The satellite digital vegetation index data has been correlated with the forest growing stock by fitting linear regression models. The goodness of fit was tested. The analysis showed that the vegetation index which is the ratio of reflectance of vegetation in near infrared band to red wave band of electromagnetic spectrum is highly correlated to forest growing stock and the same can be used to predict the volume in remote forest areas for quick assessment purpose. Implications for future forest inventory are discussed.     

利用MODIS BRDF估算中国东北森林背景反射率——以大兴安岭加格达奇地区为例

基于MODIS二向反射分布函数(BRDF)模型参数产品数据,利用4-scale模型建立查找表,以中国东北大兴安岭加格达奇地区为研究区,反演森林背景反射率,并分析不同森林类型二向反射与背景反射率特性及其季节变化。研究结果表明:(1)研究区针叶林和混交林二向反射特征较为相似,夏季阔叶林在红光波段的二向反射率值均低于针叶林和混交林,而在近红外波段则相反;不同森林类型二向反射率均存在明显的季节变化,其中阔叶林二向反射率季节变化最为明显;(2)研究区夏季森林背景反射率在红光波段较低,均在0.1以下,近红外波段背景反射率普遍高于0.3,且空间差异较大;(3)不同森林类型的背景反射率季节变化趋势大致相同,但变化幅度存在差异:阔叶林的背景反射率值季节差异最大,尤其在近红外波段。     

Large area forest inventory using Landsat ETM+: A geostatistical approach

Large area forest inventory is important for understanding and managing forest resources and ecosystems. Remote sensing, the Global Positioning System (GPS), and geographic information systems (GIS) provide new opportunities for forest inventory. This paper develops a new systematic geostatistical approach for predicting forest parameters, using integrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, GPS, and GIS. Forest parameters, such as basal area, height, health conditions, biomass, or carbon, can be incorporated as a response variable, and the geostatistical approach can be used to predict parameter values for uninventoried points. Using basal area as the response and Landsat ETM+ images of pine stands in Georgia as auxiliary data, this approach includes univariate kriging (ordinary kriging and universal kriging) and multivariable kriging (co-kriging and regression kriging). The combination of bands 4, 3, and 2, as well as the combination of bands 5, 4, and 3, normalized difference vegetation index (NDVI), and principal components (PCs) were used in this study with co-kriging and regression kriging. Validation based on 200 randomly sampling points withheld field inventory was computed to evaluate the kriging performance and demonstrated that band combination 543 performed better than band combination 432, NDVI, and PCs. Regression kriging resulted in the smallest errors and the highest R-squared indicating the best geostatistical method for spatial predictions of pine basal area.     

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.)     

基于双树复小波的CBERS-02B星遥感影像融合及评价

以CBERS-02星全色、多光谱图像及IKONOS多光谱图像为数据源,利用离散小波变换和双树复小波变换进行融合试验。结果表明,双树复小波变换在空间细节表现力和光谱保持方面能够较好地达到平衡,较离散小波变换更能提高图像融合质量。通过融合方法对比分析可知,02B星全色波段不仅与其多光谱波段融合能够得到信息更加丰富的图像,而且与其它传感器数据融合同样有很好的目视效果和可读性,具有较大的应用前景。     

Predicting forest carbon stocks from high resolution satellite data in dry forests of Zimbabwe: exploring the effect of the red-edge band in forest carbon stocks estimation

In this study, we tested whether the inclusion of the red-edge band as a covariate to vegetation indices improves the predictive accuracy in forest carbon estimation and mapping in savanna dry forests of Zimbabwe. Initially, we tested whether and to what extent vegetation indices (simple ratio SR, soil-adjusted vegetation index and normalized difference vegetation index) derived from high spatial resolution satellite imagery (WorldView-2) predict forest carbon stocks. Next, we tested whether inclusion of reflectance in the red-edge band as a covariate to vegetation indices improve the model's accuracy in forest carbon prediction. We used simple regression analysis to determine the nature and the strength of the relationship between forest carbon stocks and remotely sensed vegetation indices. We then used multiple regression analysis to determine whether integrating vegetation indices and reflection in the red-edge band improve forest carbon prediction. Next, we mapped the spatial variation in forest carbon stocks using the best regression model relating forest carbon stocks to remotely sensed vegetation indices and reflection in the red-edge band. Our results showed that vegetation indices alone as an explanatory variable significantly (p < 0.05) predicted forest carbon stocks with R² ranging between 45 and 63% and RMSE ranging from 10.3 to 12.9%. However, when the reflectance in the red-edge band was included in the regression models the explained variance increased to between 68 and 70% with the RMSE ranging between 9.56 and 10.1%. A combination of SR and reflectance in the red edge produced the best predictor of forest carbon stocks. We concluded that integrating vegetation indices and reflectance in the red-edge band derived from high spatial resolution can be successfully used to estimate forest carbon in dry forests with minimal error.     

利用天宫一号和Landsat7对地观测数据的森林变化检测

由于自然演替和一些干扰因素的影响,森林覆盖处在不断的变化中.结合云南省西双版纳地区的天宫一号高光谱数据以及Landsat影像,研究了热带森林覆盖制图与变化检测的自动化识别方法.首先分析了每景影像中红光波段的光谱属性,依据直方图提取出纯净森林像元,然后计算影像中各像元与纯净森林像元之间的光谱相似性,从而得到森林指数并以此为依据提取出每景影像对应的森林覆盖图,将多期的森林覆盖专题图进行叠加分析即可得到森林变化专题图.结果表明:(1)使用天宫一号高光谱影像可以进行森林覆盖自动化提取,生成的森林覆盖图合理地反映了森林分布状况;(2)与多期遥感影像结合进行森林变化信息提取,提取结果很好地体现了森林减少和森林恢复情况,对新恢复的未郁闭森林也可以进行有效检测.     

TM 图像的信息量分析及特征信息提取的研究

图像信息量分析是图像处理的基础,为此,本文研究了三个不同植被覆盖类型区,即多林区(森林覆盖在40％以上)、一般林地分布的丘陵区(森林覆盖10-30％)和农田为主的丘陵与平原区的图像信息量。分析同一地区冬夏两季的图像信息特征后得知,红外波段的信息量高于可见光波段,其中信息量最大的是TM5波段,最小的是TM2波段。同时对不同情况下波段间的相关性、均值和标准差等统计特征值也进行了分析。据此就图像增强、信息特征提取方法,如主成分分析、缨帽变换(KT变换)、比值等方法以及波段组合等进行了系统研究,并就其实用条件进行了探讨和评价。