Slope Instability on Pyroclastic Deposits： Landslide Distribution and Risk Mapping in Zacapoaxtla, Sierra Norte De Puebla, Mexico

Introduction The impact produced by landsliding in diverse regions of the world has given rise to the development and implementation of different methods, techniques and tools to understand the mechanisms of movements involved, as well as to create maps o…     

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.     

Rule-based classification of high-resolution imagery over urban areas in New York City

This paper describes the integration of results from different feature extraction algorithms using spectral and spatial attributes to detect specific urban features. Methodology includes segmentation of IKONOS data, computing attributes for creating image objects and classifying the objects with fuzzy logic and rule-based algorithms. Previous research reported low class accuracies for two specific classes – dark and grey roofs. A modified per-field approach was employed to extract urban features. New rule-sets were used on image objects having similar or near-similar spectral and spatial characteristics. Different algorithms using spectral and spatial attributes were developed to extract specific urban features from a time-series of Multi-Spectral Scanner (MSS) (4 m × 4 m) IKONOS data. The modified approach resulted in a remarkable improvement in the accuracy of classes that registered low spectral seperability and therefore low accuracy. The spectral and spatial based classification model may be useful in mapping heterogeneous and spectrally similar urban features.     

高分辨率卫星遥感数据在土地利用动态监测中的应用研究

选择土地利用变化类型较多的北京市大兴区为试验区,通过分析印度IRS、韩国KOMPSAT-1、美国IKONOS等高分辨率卫星数据的获取途径、覆盖周期、卫星运行状况、监测成本估算、技术条件和设备要求,对其在土地利用动态监测中的可行性进行了研究;测算了高分辨率卫星数据的主要技术参数;分析原始图像上各主要土地类型的灰度分布范围及其直方图特征,总结不同土地利用覆盖类型与融合图像变化信息的光谱特征。通过精度测算,确定了最大成图比例尺。比较利用高分辩率卫星IRS、KOMPSAT-1和SPOT与陆地卫星TM多光谱数据组合的土地利用动态监测结果(识别率、判对率、图斑边界吻合精度、可监测的最小图斑面积等),确定了不同高分辨率卫星数据与TM多光谱卫星数据组合后对土地利用类型的识别能力,建立了土地利用动态监测解译标志。在解决了若干关键技术问题的基础上,形成了一套可推广的、实用的技术方法和工作流程.     

Mapping seagrass coverage and spatial patterns with high spatial resolution IKONOS imagery

Seagrass habitats in subtidal coastal waters provide a variety of ecosystem functions and services and there is an increasing need to acquire information on spatial and temporal dynamics of this resource. Here, we explored the capability of IKONOS (IKO) data of high resolution (4 m) for mapping seagrass cover [submerged aquatic vegetation (%SAV) cover] along the mid-western coast of Florida, USA. We also compared seagrass maps produced with IKO data with that obtained using the Landsat TM sensor with lower resolution (30 m). Both IKO and TM data, collected in October 2009, were preprocessed to calculate water depth invariant bands to normalize the effect of varying depth on bottom spectra recorded by the two satellite sensors and further the textural information was extracted from IKO data. Our results demonstrate that the high resolution IKO sensor produced a higher accuracy than the TM sensor in a three-class % SAV cover classification. Of note is that the OA of %SAV cover mapping at our study area created with IKO data was 5–20% higher than that from other studies published. We also examined the spatial distribution of seagrass over a spatial range of 4–240 m using the Ripley’s K function [L(d)] and IKO data that represented four different grain sizes [4 m (one IKO pixel), 8 m (2 × 2 IKO pixels), 12 m (3 × 3 IKO pixels), and 16 m (4 × 4 IKO pixels)] from moderate-dense seagrass cover along a set of six transects. The Ripley’s K metric repeatedly indicated that seagrass cover representing 4 m × 4 m pixels displayed a dispersed (or slightly dispersed) pattern over distances of <4–8 m, and a random or slightly clustered pattern of cover over 9–240 m. The spatial pattern of seagrass cover created with the three additional grain sizes (i.e., 2 × 24 m IKO pixels, 3 × 34 m IKO pixels, and 4 × 4 m IKO pixels) show a dispersed (or slightly dispersed) pattern across 4–32 m and a random or slightly clustered pattern across 33–240 m. Given the first report on using satellite observations to quantify seagrass spatial patterns at a spatial scale from 4 m to 240 m, our novel analyses of moderate-dense SAV cover utilizing Ripley’s K function illustrate how data obtained from the IKO sensor revealed seagrass spatial information that would be undetected by the TM sensor with a 30 m pixel size. Use of the seagrass classification scheme here, along with data from the IKO sensor with enhanced resolution, offers an opportunity to synoptically record seagrass cover dynamics at both small and large spatial scales.     

利用IKONOS卫星影像测制新疆边境1:10 000比例尺地形图

在不能实施基础航空摄影的新疆边境地带,利用高分辨率遥感卫星影像来弥补无航空摄影资料区域对1∶10000地形图的需求。本文简要介绍利用IKONOS立体卫星影像,在平地、丘陵地及山地测制1∶10000比例尺地形图的技术方案,并对不同数量控制点进行定向精度分析。     

面向对象的矿山地表要素信息提取方法研究

矿山地表要素提取,可为矿山的合理开发利用、尾矿的管理、土地复垦、生态修复提供数据支撑,具有重要的实践意义。本文以湘西花垣县某铅锌矿区IKONOS影像为数据源,使用4种融合方法:Brovey变换、主成分(PCA)变换、Gram-Schmidt Pan变换、缨帽(KT)变换,对全色影像及多光谱波段进行融合,发现与原始影像相比,KT变换融合影像的光谱信息、空间信息保持得最好。基于ENVI中面向对象分层分类的方法,提取研究区内的典型地物,主要包括植被、裸地、道路、建筑物、矿石堆、尾矿库及蓄水池,并进行识别精度评价,总体精度达86.12%,Kappa系数为0.834 7。结果表明,面向对象分层分类的方法能有效地应用于复杂铅锌矿区的地物提取。     

Evaluation of various satellite sensors for waterline extraction in a coral reef environment: Majuro Atoll, Marshall Islands

The ability of five satellite sensor bands (IKONOS band 4, Terra ASTER bands 3 and 4, and Landsat ETM+ bands 4 and 5) was examined to extract the waterline at coral reef coasts (Majuro Atoll, Marshall Islands) using different wavelength regions (near infrared [NIR] and shortwave infrared [SWIR]) and different spatial resolutions (4, 15, and 30 m). After performing georeferencing and normalization of the images, density slicing was used to extract the waterline. Comparisons of extracted waterline positions with ground-level data for eight transects and global positioning system (GPS) tracks of the island shorelines showed that NIR bands were superior to SWIR bands because of the characteristics of the coral reef coasts, including a lack of foam and suspended sediments (which can affect the NIR wavelength region, if present) and the presence of remnant water on reef flats during low tide (which can affect the SWIR wavelength region). A linear relationship was found between the estimation errors of waterline positions and the spatial resolutions of the NIR sensors. Analysis on estimation errors and image costs showed that Terra ASTER band 3 was the most cost-effective sensor for extracting waterlines with reasonable accuracy. The results serve as general guidelines for using satellite-derived data to estimate intertidal topography and detect and monitor shorelines in coral reef environments.     

IKONOS等高分辨率遥感技术的发展与应用分析

对以IKONOS卫星为代表的高分辨率卫星遥感技术的发展作了分析,分析了米级分辨率卫星遥感技术在20世纪90年代中后期能快速发展的原因：首先,随着“冷战”的结束,国际政治形势出现了新变化,原来被各国军事部门限制的高分辨率卫星遥感技术逐渐解禁。第二,由于技术科学的发展,特别是军事部门在高分辨率卫星遥感技术方面已历经摸索、试验期,为该技术的大范围应用创造了条件。第三,20世纪90年代之前,卫星遥感资料的用户主要是政府部门。但进入90年代以后,经济的飞速发展使得卫星遥感资料的使用者范围逐渐扩大,对卫星遥感数据的需求量日益增加,这为卫星遥感技术创造了商业化运作条件。另外分析了高分辨率卫星遥感数据的应用领域,包括测绘、城市规划、土地管理、环境、农业等部门,并就具体的应用前景提出见解。最后,结合高分辨率卫星遥感数据的特点,对遥感数据分类技术和数据共享问题作了探讨。     

利用IKONOS影像生产1:10 000测绘产品

本文简要介绍了IKONOS卫星遥感影像适用于生产测绘产品的特点,总结了利用IKONOS影像进行1∶10 000测绘产品生产试验的主要结论,分析了利用IKONOS影像作为数据源实际生产1∶10 000测绘产品的情况。