面向对象分类提取高分辨率多光谱影像建筑物

初步测试利用基于知识规则的面向对象分类方法从高分辨率Ikonos卫星影像上提取建筑物,包括:融合1 m全色和4 m多光谱波段影像,生成1 m分辨率的多光谱融合影像;分割融合影像;利用影像对象的光谱和空间特征执行基于对象的分类。面向对象分类提取结果与传统的基于像元最大似然分类结果进行对比,表明面向对象分类方法更适用于提取高分辨率遥感影像中的建筑物。     

基于不同分辨率遥感影像的分类方法对比研究

基于4种不同分辨率的遥感影像数据,分别为30 m分辨率的Landsat-8数据,融合Landsat-8多光谱波段和全色波段的15 m分辨率数据,5.8 m分辨率的资源3号卫星数据以及融合后2.1 m分辨率的资源3号卫星数据。采用ISO-DATA、最大似然分类法和面向对象分类法对影像进行分类,对分类方法的效果以及分辨率变化对面向对象分类方法的精度影响进行分析。结果显示在低分辨率影像中,面向对象方法受到限制,分类效果相比传统方法没有太大改善;而在高分辨率影像中,面向对象方法分类效果很好,并且随着分辨率提高分类精度也相应的提高。     

地表覆盖水面信息动态监测方法探索

遥感技术提取水面信息是目前高效的方法,文中通过梳理现有水面提取方法,对关键技术进行分析,提出依据应用需求可采用基于中低空间分辨率、高时间分辨率遥感影像的大区域水面信息提取,以及基于长时间序列遥感影像的水面空间分布变化监测等不同监测模式的思路。通过选取实验区,开展水面范围变化动态监测,对提出的思路进行验证,为水面范围变化动态监测提供方法参考。     

遥感技术支持下的下龙湾西岸养殖塘变化监测及其对“三生用地”影响分析

下龙湾西岸是越南北部沿海的养殖大区,随着水产养殖用地规模的逐渐扩大,周边三生用地（生产用地、生活用地、生态用地）空间格局受到影响。本文以下龙湾西岸的5个沿海地区为研究区,利用1990、2000、2010、2015年4期无云Landsat TM/OLI遥感数据,采用分类回归树方法,对1990—2015年的土地利用变化进行监测。通过土地利用净变化量、土地利用动态度模型、相关性分析等方法,定量分析养殖塘时空格局演变特征及对三生用地的影响。结果表明：①25年间,养殖塘面积呈“单峰”式先增后减变化,净增加66.65 km²,2000年面积为156.65 km²,较1990年面积增长113%,2015年较2000年面积减少11%。总体呈现数量上“北增南减”、速率上“东快西慢”的面积变化特征。②养殖塘转入面积中,生产用地对养殖塘转移面积占31%,生活用地占4%,生态用地占65%。空间格局整体以白藤江及陆地中轴为界线,呈南北分区、东西分界的转入转出规律。③养殖塘占用生活用地7.24 km²,二者呈正相关关系,R²为0.46;养殖塘分别占用生产用地和生态用地55.14、115.14 km²,并与两者成负相关关系,R²分别为-0.96和-0.81。由此可知,利用遥感技术监测养殖塘时空变迁对土地资源的规划配置与可持续发展具有重意义。     

高分辨率影像解译理论与应用方法中的一些研究问题

近年来，不断发展的遥感技术使遥感数据呈现出高空间分辨率、高光谱分辨率和高时间采集频率的特点。卫星图像空间分辨率已经提高到0．6m级，而航空遥感数字影像分辨率高达0．1m以上。光谱分辨率高达3—4nm。不断发展的高分辨率遥感数据能够提高信息提取和监测精度，并拓展遥感数据的应用范围。目前，国外已经加快对高分辨率图像，特别是高空间分辨率影像，在城市环境、精准农业、交通及道路设施、林业测量、军事目标识别和灾害评估中的应用。但是总的情况是自动化程度不高。介绍高空间分辨率影像信息提取、高光谱和偏振影像信息提取、影像数据融合和高分辨率遥感变化探测等方面迫切需要研究的一些科学问题及其意义。建议建立图像知识库，改善数据共享环境，为有志于从事这方面研究的学者提供参考。     

基于多源卫星测高数据的青海湖水位变化研究

针对单颗卫星空间、时间分辨率受限及湖泊边界复杂地形条件引起湖泊监测精度较低的问题，提出结合多源卫星测高数据监测水位变化并建立边界缓冲区筛选数据的方法。以青海湖为研究对象，基于ERS-1/2、Envisat、Cryosat-2测高数据，构建了1995—2021年近26 a的水位时间序列，结合Grace卫星数据分析湖泊水位、面积、水储量与气候因素间的关系。结果表明：青海湖水位以2004年为节点呈现先下降后上升的变化，整体上升2.97 m,增长量为0.114 m/a,季节性变化明显，与降水量、径流量和蒸散发量相关系数分别为0.295、0.66、-0.24;湖泊面积与水位变化趋势一致，增长量为9.66 km²/a, 2001—2020年等效水柱高增长量为1.68 mm/a,与水文站及其他湖泊库水位序列相关系数均在0.9以上，具有良好基一致性。     

全色/多光谱融合影像的MVG无参考质量评价

同时具有高空间分辨率和高光谱保真度的全色/多光谱融合影像具有广泛的应用前景.然而,一方面全色/多光谱融合方法通常会产生不同的空间畸变或光谱失真;另一方面,受卫星成像系统限制,无法获取真实高空间分辨率多光谱参考影像,因此,如何在无真实参考影像情况下有效评估融合影像质量具有重要意义.为此,本文提出了一种基于多元高斯模型(M...     

面向对象的高分辨率遥感影像湿地信息分层提取

针对湿地的类型多样和光谱特征不确定性,在高分辨遥感影像上可人工目视判读,而自动化解译困难。文章在面向对象技术支持下,提出了多特征融合的高分辨率遥感数据湿地信息分层提取。该方法首先通过面向对象分割技术转象元为基元,实现光谱相似象元的聚类;然后分析湿地景观格局依存关系和不同类型湿地的提取难以程度,决定提取的先后顺序;再挖掘不同类型湿地的光谱、空间形态、空间分布和空间关系等多种属性特征;最后通过分层分类,由易到难,融入空间知识,逐层构建规则集,实现高分辨率遥感影像湿地信息自动监测。通过高空间分辨率Quickbird卫星数据对玛纳斯国家湿地公园区进行遥感监测。试验结果表明：该方法能够快速实现区域范围内湿地信息自动识别和快速提取,总体分类精度达到了87.5%,Kappa系数超过0.83,基本满足应用的需求,可为同行领域应用提供技术参考。     

ALOS在土地资源调查与监测中的应用研究

ALOS卫星是日本宇航研究开发机构（JAXA）于2006年1月24日成功发射的新一代陆地观测卫星,其全色影像的最高空间分辨率是2.5 m,多光谱影像的分辨率是10 m,在土地资源调查与监测领域中有一定的应用潜力。本文通过与同为2.5 m和10 m分辨率的SPOT5影像在卫星参数、影像质量、应用精度等方面进行比较试验,研究ALOS卫星在土地领域中的应用效果和应用潜力。     

基于多分辨率分析的GF-5和GF-1遥感影像空—谱融合

针对空间分辨率比率较大尺度差异下的高分五号(GF-5)与高分一号(GF-1)卫星影像的空—谱融合问题,提出多传感器影像融合策略:一方面,通过现有空—谱融合方法的分步融合得到融合影像;另一方面,在分步融合理论基础上,推导得出一体化融合基础框架,并进一步提出基于多分辨率分析的多传感器一体化融合方法,缓解现有方法因空间分辨率比率过大导致影像空、谱互补信息难以有效集成的问题。其中,提出的一体化融合方法基于调制传递函数MTF (Modulation Transfer Function)滤波对多传感器影像空间(高频)和光谱(低频)分量进行分解提取,并充分考虑多传感器高空间分辨率影像与高光谱分辨率影像之间的关系,以及高光谱分辨率影像波段间关系,设计合理的融合权重,最终可得到具有最高空间分辨率和最高光谱分辨率的融合影像。通过GF-1全色影像、GF-1多光谱影像、GF-5高光谱影像数据对提出方法进行实验验证,结果表明:本文方法可有效集成多传感器影像间的空、谱互补信息,得到较优融合结果。     

防城港-钦州的海岸线遥感监测与时空分析

海岸线是海陆动态的分界线.国内外对防城港-钦州海岸线的时空变迁研究甚少.基于Landsat系列卫星遥感数据,利用ENVI(environment visualizing images)、Arc-Map平台,采用归一化水体指数半自动提取5期海岸线,定量、定性分析海岸线时空演变.研究发现:①1999-2018年海岸线增长了...     

基于GF-1与Landsat-8影像的山区苹果园地信息提取

GF-1卫星影像具有空间和时间分辨率高、纹理信息丰富等优势,而Landsat-8卫星影像具有多波段、光谱信息充足等优势。针对两种影像的特点,本文分别用面向对象分类方法进行苹果园地信息提取研究,结果表明:两种影像的分类精度都比较高,但由于研究区域属于山区,地块分布不均匀,GF-1影像发挥其空间分辨率较高的优势,苹果园地面积提取精度比Landsat-8高1.19%。     

Assessing Optimal Image Fusion Methods for Very High Spatial Resolution Satellite Images to Support Coastal Monitoring

This study examines best image fusion approaches for generating pansharpened very high resolution (VHR) multispectral images to be utilized for monitoring coastal barrier island development. Selected fusion techniques assessed in this research come from the three categories of spectral substitution (e.g., Brovey transform and multiplicative merging), arithmetic merging (e.g., modified intensity-hue-saturation and principal component analysis), and spatial domain (e.g., high-pass filter, and subtractive resolution merge). The image fusion methods selected for this study were capable of producing pansharpened VHR images with more than three bands. Comparisons of fusion techniques were applied to images from three satellite sensors: United States commercial satellites IKONOS and QuickBird, and the Korean KOMPSAT II. Pansharpened VHR multispectral images were assessed by spectral and spatial quality measurements. Results satisfying both spectral and spatial quality revealed optimum pansharpened techniques necessary for regular coastal mapping of barrier islands. These techniques may also be used to assess the quality of recently available VHR imagery acquired by numerous international, government, and commercial VHR satellite programs.     

基于天宫一号高光谱数据与Landsat TM数据的湿地利用变化监测

本文利用2013年4月18日获取的天宫一号高光谱成像仪数据和1985年5月1日获取的Landsat TM数据,对黄河入海口地区湿地的土地利用状况进行了监测研究.通过对比分类结果发现,该地区近30年来人类活动对湿地的影响强烈,滩涂开垦、水产养殖业占用自然水面现象严重.同时由于天宫一号高光谱成像仪数据具有更高的光谱和空间分辨率,其分类精度优于Landsat TM,更适合于湿地的监测.     

Classification of boreal macrotidal littoral zone habitats in the Gulf of Maine: comparison of IKONOS and CASI multispectral imagery

Increasingly, remote sensing has become a useful tool for mapping and measuring terrestrial and aquatic environments. Advances in the spatial and spectral resolution of satellite-borne sensors have allowed affordable investigations of littoral macrotidal coastal systems that previously required more costly aircraft-based imagery. In this communication, we compare the results from analysis of a 4 m spatial resolution, multispectral IKONOS satellite image of the intertidal habitats of Islesboro, Maine, USA with that of an aerial compact airborne spectral imager survey of the same regions captured 4 years earlier. There was 72% agreement between the surveys in spite of the temporal gaps between the images. Accuracy varied by habitat class and the perceived error can be assigned to temporal and definitional issues rather than basic acquisition and analytic protocols. Most of the error can be explained by: (1) inadequacy of training sites, (2) temporal variations and (3) class definitions. We conclude that IKONOS imagery provides sufficient spatial and spectral resolution to map and monitor diverse intertidal habitats as found in the macrotidal Gulf of Maine.     

Spectral unmixing ofcompact airborne spectrographic imager (CASI) data for quantifying sub-pixel proportions of biophysical parameters in a coastal dune system

In environmentally sensitive and large coastal dune systems, identification and mapping of favourable (sandy), and unfavourable (scrub rich) habitats form the key to coastal conservation and management. In highly mixed floral environments, however, such an identification is difficult with low resolution multispectral imagery. In such cases, spectral unmixing is useful to resolve the “mixed pixel” effects. The Kenfig NNR (National Nature Reserve), South Wales. UK, bestowed with high biodiversity, is facing loss of successionally young slack habitats due to dune stabilisation and vegetation succession. To map such habitats, linear spectral unmixing of airborne MSS (CASI-Compact Airborne Spectrographic Imager) data was performed using the Constrained Least Square (CLS) method, and the sub-pixel proportions of the spectral end members viz. sand, vegetation and shade/moisture were defined. Comparison of the estimated fractions with the growth forms of the dominant vegetation species Salix repens (Creeping willow) with classified digital aerial photographs shows a positive correlation, thus giving us confidence in the mixture modelling technique. Apart from aiding in conservation management, such a fuzzy classification of multi-date imagery helps to delineate sandy and vegetated areas for change detection and landscape/ habitat succession studies.     

Object- and pixel-based classifications of macroalgae farming area with high spatial resolution imagery

Macroalgae plays an important role in coastal ecosystems. The accurate delineation of macroalgae areas is important for environmental management. This study compared the pixel- and object-based methods using Gaofen satellite no. 2 image to explore an efficient classification approach. Expert system rules and nearest neighbour classifier were adopted for object-based classification, whereas maximum likelihood classifier was implemented in the pixel-based approach. Normalized difference vegetation index, normalized difference water index, mean value of the blue band and geometric characteristics were selected as features to distinguish macroalgae farms by considering the spectral and spatial characteristics. Results show that the object-based method achieved a higher overall accuracy and kappa coefficient than the pixel-based method. Moreover, the object-based approach displayed superiority in identifying Porphyra class. These findings suggest that the object-based method can delineate macroalgae farming areas efficiently and be applied in the future to monitor the macroalgae farms with high spatial resolution imagery.     

Fully constrained linear spectral unmixing based global shadow compensation for high resolution satellite imagery of urban areas

Shadows commonly exist in high resolution satellite imagery, particularly in urban areas, which is a combined effect of low sun elevation, off-nadir viewing angle, and high-rise buildings. The presence of shadows can negatively affect image processing, including land cover classification, mapping, and object recognition due to the reduction or even total loss of spectral information in shadows. The compensation of spectral information in shadows is thus one of the most important preprocessing steps for the interpretation and exploitation of high resolution satellite imagery in urban areas. In this study, we propose a new approach for global shadow compensation through the utilization of fully constrained linear spectral unmixing. The basic assumption of the proposed method is that the construction of the spectral scatter plot in shadows is analogues to that in non-shadow areas within a two-dimension spectral mixing space. In order to ensure the continuity of land covers, a smooth operator is further used to refine the restored shadow pixels on the edge of non-shadow and shadow areas. The proposed method is validated using the WorldView-2 multispectral imagery collected from downtown Toronto, Ontario, Canada. In comparison with the existing linear-correlation correction method, the proposed method produced the compensated shadows with higher quality.     

高精度作物分布图制作

中国自然条件复杂 ,农业种植结构多样 ,地块小而分散 ,利用遥感影像制作作物分布图的精度很难满足农业遥感估产的需求。该文利用目前最高分辨率的商用遥感卫星 (QuickBird)影像 ,采用面向对象的影像分析方法提取耕地种植地块图 ,结合详细的地面调查制作高精度的作物分布图 ,为农业遥感估产服务。