{"title":"Environmental assessment and monitoring with image characterization and modeling system using multiscale remote sensing data","authors":"Nina Siu-ngan Lam, Dale Quattrochi, Hong-lie Qiu, Wei Zhao","doi":"10.1002/(SICI)1520-6319(199822)2:2<77::AID-AGS1>3.0.CO;2-O","DOIUrl":null,"url":null,"abstract":"<p>With the rapid increase in spatial data, especially in the NASA–EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called ICAMS (Image Characterization And Modeling System) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph–MGE and the Arc/Info Unix and Windows–NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this article, we demonstrate the main applications of ICAMS on the Intergraph–MGE platform using Landsat–Thematic Mapper images from the city of Lake Charles, Louisiana. Through the availability of ICAMS to a wider scientific community, we hope to generate various studies so that improved algorithms and more reliable models for environmental assessment and monitoring can be developed. © 1998 John Wiley & Sons, Inc.</p>","PeriodicalId":100107,"journal":{"name":"Applied Geographic Studies","volume":"2 2","pages":"77-93"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1520-6319(199822)2:2<77::AID-AGS1>3.0.CO;2-O","citationCount":"33","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geographic Studies","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/%28SICI%291520-6319%28199822%292%3A2%3C77%3A%3AAID-AGS1%3E3.0.CO%3B2-O","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 33
Abstract
With the rapid increase in spatial data, especially in the NASA–EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called ICAMS (Image Characterization And Modeling System) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph–MGE and the Arc/Info Unix and Windows–NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this article, we demonstrate the main applications of ICAMS on the Intergraph–MGE platform using Landsat–Thematic Mapper images from the city of Lake Charles, Louisiana. Through the availability of ICAMS to a wider scientific community, we hope to generate various studies so that improved algorithms and more reliable models for environmental assessment and monitoring can be developed. © 1998 John Wiley & Sons, Inc.
基于多尺度遥感数据的环境评价与监测图像表征与建模系统
随着空间数据的快速增长,特别是在NASA-EOS(地球观测系统)时代,有必要开发高效和创新的工具来处理和分析这些数据,以便对环境状况进行评估和监测。地理学家和环境科学家在环境评估和测量中面临的一个主要困难是空间分析工具不容易获得。我们最近开发了一个名为ICAMS(图像表征和建模系统)的遥感/地理信息系统软件模块,为卫星和其他形式的空间数据的测量和表征提供专门的空间分析工具。ICAMS可以在Intergraph-MGE和Arc/Info Unix和Windows-NT平台上运行。ICAMS的主要技术包括分形测量方法、变异函数分析、空间自相关统计、纹理测量、聚集技术、归一化植被指数(NDVI)以及陆地/水和植被/非植被边界的划分。在本文中,我们使用来自路易斯安那州查尔斯湖市的Landsat-Thematic Mapper图像,演示了ICAMS在Intergraph-MGE平台上的主要应用。通过ICAMS向更广泛的科学界开放,我们希望开展各种研究,从而开发出改进的算法和更可靠的环境评估和监测模型。©1998 John Wiley &儿子,Inc。
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