遥感GPP模型在高寒草甸的应用比较

随着遥感数据时空分辨率的提高,大范围实时监测总初级生产力GPP(Gross Primary Productivity)的变化成为可能。本研究收集了黑河流域阿柔冻融观测站的气象观测资料和MODIS数据,驱动VPM、TG、VI和EC-LUE4个模型估算了该站点的GPP,并应用涡动相关观测的GPP验证了模拟结果,并比较了这4个模型的模拟精度。结果表明:阿柔站2009年的涡动相关观测的GPP、NEE(Net Ecosystem Exchange)和ER(Ecosystem Respiration)分别为:804.2gC/m2/yr、129.6gC/m2/yr和673.6gC/m2/yr。该站点光合作用固定的碳有83.8%通过生态系统的呼吸作用释放到大气中。基于遥感的GPP模型能够很好地模拟高寒草甸的GPP,全年的判定系数在0.94以上,生长季的判定系数大于0.84。     

基于Biome-BGC模型的小兴安岭森林碳通量时空分析

全球气候变化是当前人类生存和发展所面临的严峻挑战,森林生态系统在减缓温室效应和维持全球碳平衡中发挥着重要作用.本文以黑龙江省小兴安岭地区森林为研究对象,将通量观测和生态过程模型相结合,采用Biome-BGC模型估算森林碳通量,使用M-K方法和EOF方法进行了时空分析,并发现了2000—2015年小兴安岭森林碳通量的时空特征规律.研究结果表明:在时间上,具有明显的年际变化特征,且呈波动下降的总趋势;在空间上,具有同向分布模式和反向分布模式的空间分布特征.本研究成果将为我国制定应对全球变化的战略决策,以及生态文明建设和环境保护提供科学参考依据.     

基于光能利用率模型的玉米遥感估产研究

农作物长势监测和产量预测对于国家制定相关粮食政策、农业发展等都具有重要的意义,如何获得高效、宏观、精确的估产方法一直是学者关注的重点问题。以吉林省德惠市的玉米作为研究对象,利用光能利用率模型对玉米进行产量估算的研究,并且使用空间数据插值方法中的反距离权重法获得了每月平均温度数据的格网数据。通过玉米的净初级生产力NPP的累计值以及玉米的收获指数来获得最终的玉米产量值,利用验证点实测产量值与估算值的相关性和相对误差进行精度验证,相关系数R^2为0.649 9,平均相对误差值为1.676%,证明基于光能利用率模型的玉米估产在研究区具有一定的可行性。     

遥感地质信息提取集成与矿物遥感地质分析模型

结合遥感技术的现状、发展趋势和资源环境应用需求，从遥感地质应用出发，提出多源遥感数据分层识别集成、基于岩矿识别技术体系集成和基于岩矿识别谱系集成的基本思路与框架，强调矿物或矿物集合体在遥感地质分类与识别中的重要性，初步建立矿物遥感地质分析模型，分析集成与模型在蚀变与矿化信息提取、地质环境评价等中的可应用性。     

Multiple Classifier Systems for Hyperspectral Remote Sensing Data Classification

One of the most widely used outputs of remote sensing technology is Hyperspectral image. This large amount of information can increase classification accuracy. But at the same time, conventional classification techniques are facing the problem of statistical estimation in high-dimensional space. Recently in remote sensing, support vector machines (SVMs) have shown very suitable performance in classifying high dimensionality problem. Another strategy that has recently been used in remote sensing is multiple classifier system (MCS). It can also improve classification accuracy by combining different classifier methods or by a diversity of the same classifier. This paper aims to classify a Hyperspectral data using the most common methods of multiple classifier systems i.e. adaboost and bagging and a MCS based on SVM. The data used in the paper is an AVIRIS data with 224 spectral bands. The final results show the high capability of SVMs and MCSs in classifying high dimensionality data.     

成像光谱数据在城市遥感中的应用研究

采用高空间分辨率的航片与高光谱数据对城市进行遥感研究。利用高空间分辨率数据丰富的空间信息,以及高光谱分辨率数据丰富的光谱信息,提出了基于图像边缘检测和光谱分析的新型高光谱遥感图像分类方法,对城市地物覆盖以图斑为单位进行分类。从而证明对复杂的城市环境进行遥感研究,这种方法是有效的。     

Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data

Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R ² value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.     

小波变换在遥感图像数据融合中的应用

用小波变换实现了一种新的遥感图像数据融合方法 ,该方法采用梯度算法对不同尺度子带数据进行融合 ,用加权法对基带数据进行融合。给出了 SAR图像与 TM图像的融合结果的定性评价 ,并用熵及平均梯度进行了定量评价     

A Multiple SVM System for Classification of Hyperspectral Remote Sensing Data

With recent technological advances in remote sensing sensors and systems, very high-dimensional hyperspectral data are available for a better discrimination among different complex land-cover classes. However, the large number of spectral bands, but limited availability of training samples creates the problem of Hughes phenomenon or ‘curse of dimensionality’ in hyperspectral data sets. Moreover, these high numbers of bands are usually highly correlated. Because of these complexities of hyperspectral data, traditional classification strategies have often limited performance in classification of hyperspectral imagery. Referring to the limitation of single classifier in these situations, Multiple Classifier Systems (MCS) may have better performance than single classifier. This paper presents a new method for classification of hyperspectral data based on a band clustering strategy through a multiple Support Vector Machine system. The proposed method uses the band grouping process based on a modified mutual information strategy to split data into few band groups. After the band grouping step, the proposed algorithm aims at benefiting from the capabilities of SVM as classification method. So, the proposed approach applies SVM on each band group that is produced in a previous step. Finally, Naive Bayes (NB) as a classifier fusion method combines decisions of SVM classifiers. Experimental results on two common hyperspectral data sets show that the proposed method improves the classification accuracy in comparison with the standard SVM on entire bands of data and feature selection methods.     

利用IRS-P6卫星数据制作遥感影像地图

本文介绍了以IRS-P6卫星数据作为信息源完成大兴安岭林区的遥感影像地图制作的方法, 通过试验初步认识到:利用IRS-P6卫星数据制作遥感影像地图,可以满足1:50000、 1:25000比例尺的平面制图精度要求,在一些专业和专题应用中可以放大到1:15000比例尺使用。     

Gondwana-Derived Terranes Structural Mapping Using PALSAR Remote Sensing Data

Gondwana-derived terranes are now separated by major faults or suture zone, which are rarely simple and easily recognizable lineaments. Different association of ore mineral systems such as deposits of sediment-hosted/orogenic gold and granite-related minerals is discovered in collision and subduction zones of the Gondwana-derived terranes. They are associated with large-scale, terrane-bounding fault systems and broad areas of deformation. Mineralization mostly associated with structurally-controlled complex lodes, veins, sheeted veins and veinlets in diverse orientations. Recognizing the structural significance of lineaments and curvilinear is very difficult in tropical, arid and Antarctic regions due to environmental obstacles. Remote sensing data could be used to detect geological structures associated with suture zones between Gondwana-derived terranes especially for large inaccessible regions where fieldwork is limited or nonexistent. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR) satellite remote sensing data were used to map major geological structures in the Bentong-Raub Suture Zone of Peninsular Malaysia. It is one of the major structural zones in Sundaland, Southeast Asia, which forms the boundary between the Gondwana-derived the Sibumasu terrane and Sukhothai-Indochina arc. Structural features associated with sediment-hosted/orogenic gold deposits in the Central Gold Belt and tin mineralization in S-type granites in the Main Range were investigated using PALSAR data and comprehensive fieldwork. Results indicate that main faults strike along 340° to 350° that are intersected by many shear or lateral fault zones are high potential zone for gold mineralization in the Central Gold Belt. Hydrothermally alteration mineral zones and cataclastic rocks are also the other indicators of gold mineralized veins in the gold belt. High potential zones for tin mineralization are N–S strike-slip faults, fault zones and shear zones trending E–W, NE–SW and WNW–ESE in dissected crystalline granitic rocks that are associated with hydrothermal alteration zones in the Western Tin Belt. Lineament analysis using PALSAR satellite remote sensing data is a useful tool for mapping major geological structural features and detection of the boundary between the Gondwana-derived terranes and detailed structural analysis of fault systems and deformation with high potential for a variety of mineral resources, especially in tropical, arid and Antarctic regions.     

利用可变形部件模型检测遥感影像道路交叉口

为了解决高分辨率遥感影像道路交叉口位置检测与类型识别问题,提出了一种基于可变形部件模型的道路交叉口检测方法。首先,分析了道路交叉口在高分辨率遥感影像上的表征形式;然后,借鉴面向对象的思想,利用可变形部件模型,通过训练和学习其整体和部件组成的空间布局特征获取目标对象模型参数;最后,通过滑动窗口搜索匹配方法获取道路交叉口位置和其对应的类型。由仿真与实验结果可知,此算法不仅能够自动、准确地检测道路交叉口的几何位置,而且能够识别其几何形状类型,可有效提高道路网络拓扑结构构建效率。     

高山冰川遥感提取方法研究

遥感的应用使得对冰川大尺度全覆盖、多时相变化的监测成为可能,然而冰川信息遥感提取方法的误差大等难题成为影响冰川监测的障碍。本文综合分析比较了目前已有的多种冰川提取方法的有效性,得出提取冰川范围精度最高的是面向对象的目视判读方法,其次是最大似然法监督分类、面向对象的自动分类、比值阈值法、雪盖指数法等。各自动方法提取冰川面积均有较大误差,且误差主要出现在冰舌末端、阴影区、薄冰区和云层遮盖范围等区域。本文将面向对象的目视判读法应用于冰川提取中,在保证信息提取精度的同时提高了传统解译的效率。