Assessing integration of intensity,polarimetric scattering,interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification

Synthetic aperture radar (SAR) is an important alternative to optical remote sensing due to its ability to acquire data regardless of weather conditions and day/night cycle. The Phased Array type L-band SAR (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) provided new opportunities for vegetation and land cover mapping. Most previous studies employing PALSAR investigated the use of one or two feature types (e.g. intensity, coherence); however, little effort has been devoted to assessing the simultaneous integration of multiple types of features. In this study, we bridged this gap by evaluating the potential of using numerous metrics expressing four feature types: intensity, polarimetric scattering, interferometric coherence and spatial texture. Our case study was conducted in Central New York State, USA using multitemporal PALSAR imagery from 2010. The land cover classification implemented an ensemble learning algorithm, namely random forest. Accuracies of each classified map produced from different combinations of features were assessed on a pixel-by-pixel basis using validation data obtained from a stratified random sample. Among the different combinations of feature types evaluated, intensity was the most indispensable because intensity was included in all of the highest accuracy scenarios. However, relative to using only intensity metrics, combining all four feature types increased overall accuracy by 7%. Producer’s and user’s accuracies of the four vegetation classes improved considerably for the best performing combination of features when compared to classifications using only a single feature type.     

浅析地理国情普查内容分类体系

为确保第一次全国地理国情普查的顺利进行,需要对普查内容分类体系有一致、深入的理解与认识。本文先后分析了地理国情普查内容分类的原则和采用的三级分类与编码体系,讨论了不同门类普查数据的表示方法,提出了基于决策树思想的一级类可靠判译方法,最后通过比较分析,指出了该分类体系与其他已有体系的异同,可为深入理解地理国情普查内容提供有益参考。     

地理国情（市情）普查外业信息采集

地理国情监测不仅扩大了测绘行业的内涵,更重要的是,对我国总体布局和规划提供了可靠的依据。目前,在全国范围内逐步开展地理国情普查工作,我分院按照安排,以厦门市为试点,对其进行了外业的调查与核查工作。结合实地作业情况来看,可以在地理国情普查内容与指标基本不变的前提下,依据地域的不同增加分类或修改部分类别的内涵。为今后全面普查工作的顺利开展,对现有的作业方式和作业内容都应有一定的规范。     

基于DEM的地形分类方法研究

坡度是描述地表形态的基本指标。利用ArcGIS软件对已有的1∶10 000 DEM数据进行坡度分析,能够正确高效地识别地形特征,确定对应图幅所属的地形类别。研究成果已正式应用于河北省第一次全国地理国情普查和其他测绘地理信息管理工作。     

基于资源三号卫星影像的城市绿地信息提取方法探讨

我国高分遥感卫星的发展为城市绿地的规划、建设和改造提供有力的技术支持。研究利用资源三号卫星全色和多光谱影像,以国内某城市为例,采用基于规则的面向对象分类技术获取城市绿地。研究提出的技术方案,简单易行,具有较好的应用性。对于推动资源三号卫星在国土资源和城市规划方面的应用具有重要意义。     

水产养殖遥感监测及信息自动提取方法研究

以海南省文昌地区为例,在沿海地区尝试利用遥感监测的手段提取水产养殖地块和面积.采用面向对象的分类方法进行监测,取得了理想效果,同时也提出了提高分类精度的建议.     

改进的P-SVM支持向量机与遥感数据分类

本文介绍了将P-SVM算法引入多光谱/高分辨率遥感数据的分类, 并且展示了卫星ASTER和航空ADS40数字影像分类的技术过程和结果验证。结果表明：P-SVM方法的分类精度不低于SVM, 并减少了时耗。     

基于地物特征提取的车载激光点云数据分类方法

车载激光扫描测量方法较传统摄影测量方法具有更多优点,它能快速采集大面积、高精度的三维空间数据,具有广阔的应用前景。针对车载激光扫描数据的分类问题,提出了一种基于地物特征提取的点云数据分类方法,即采用主成分分析(PCA)方法,在提取多种街区地物点云数据几何特征和总结地物对象特征知识规则的基础上,根据选取的主特征设计一套阶层式的分类方法,并利用该方法对一套车载激光点云数据进行了分类试验。结果表明,该方法的分类效果良好,具有一定的实用性。     

Geostatistical incorporation of spatial coordinates into supervised classification of hyperspectral data

 This paper presents a methodology to incorporate both hyperspectral properties and spatial coordinates of pixels in maximum likelihood classification. Indicator kriging of ground data is used to estimate, for each pixel, the prior probabilities of occurrence of classes which are then combined with spectral-based probabilities within a Bayesian framework. In the case study (mapping of in-stream habitats), accounting for spatial coordinates increases the overall producer's accuracy from 85.8% to 93.8%, while the Kappa statistic rises from 0.74 to 0.88. Best results are obtained using only indicator kriging-based probabilities, with a stunning overall accuracy of 97.2%. Significant improvements are observed for environmentally important units, such as pools (Kappa: 0.17 to 0.74) and eddy drop zones (Kappa: 0.65 to 0.87). The lack of benefit of using hyperspectral information in the present study can be explained by the dense network of ground observations and the high spatial continuity of field classification which might be spurious. Received: 12 April 2001 / Accepted: 7 September 2001     

基于图像特征的烟叶分级

讨论了基于图像特征的烤烟烟叶分级系统的建模及其实现,给出了烟叶分级模型的数学描述,探讨了模型库的优化和特征隶属度及烟叶模式的可信度的计算问题,并通过试验分析了FTGS系统的性能和有效性。