首页> 外文会议>ASPRS Annual Conference,Prospecting for Geospatial Information Integration >TIDAL WETLAND CLASSIFICATION FROM LANDSAT IMAGERY USING AN INTEGRATED PIXEL-BASED AND OBJECT-BASED CLASSIFICATION APPROACH
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TIDAL WETLAND CLASSIFICATION FROM LANDSAT IMAGERY USING AN INTEGRATED PIXEL-BASED AND OBJECT-BASED CLASSIFICATION APPROACH

机译:使用基于综合像素和基于对象的分类方法,潮湿地分类来自Landsat图像

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The tidal wetlands within the Long Island Sound estuary serve a critical role in maintaining the health of the Sound. Over the past two centuries, there has been significant disturbance and loss of tidal wetlands along the Sound due primarily to anthropogenic activities. Researchers at the University of Connecticut and Wesleyan University are continuing on the second year of a two year project to document the extent and vegetative composition of coastal marshes using moderate resolution Landsat ETM+ and Terra ASTER satellite imagery and high resolution QuickBird satellite and Leica ADS40 aerial imagery in conjunction with in situ field measurements of plant spectra. This paper will detail research to classify tidal wetlands throughout Long Island Sound from Landsat satellite imagery. The goal of this portion of the project was to produce an accurate base map that identifies the location of tidal wetlands. An integrated classification approach which uses both pixel-based and object-based classification techniques was utilized. The classification serves as a base map to compare with subsequent dates of imagery to monitor any changes in tidal wetland extent and also compared with existing land cover maps to identify any upland changes in close proximity to the wetlands that could cause potential detrimental impacts to the tidal marsh system. The results of this research will provide a beneficial tool for coastal wetland management and monitoring along the Long Island Sound estuary.
机译:长岛海峡内的潮滩湿地河口在保持声音的健康起到至关重要的作用。在过去的两个世纪中,出现了显著的干扰,沿着声音潮汐湿地的消失,主要是由于人类活动。在康涅狄格州和卫斯理大学大学的研究人员正在继续上两年项目的第二年,以文件的范围内,并使用中等分辨率的Landsat ETM +和Terra ASTER卫星影像和高分辨率的QuickBird卫星和徕卡ADS40航空影像的沿海沼泽地的营养成分在与植物光谱的原位现场测量结合。本文将详细研究分类滩涂湿地遍布长岛将Landsat卫星图像。该项目的该部分的目标是产生准确的基本地图识别潮汐湿地的位置。其中同时使用基于像素的和基于对象的分类技术被利用集成的分类方法。分类作为底图与图像的后续日期比较监测潮汐湿地范围内的任何变化,并与现有的土地覆盖图,以确定在靠近任何旱地变为湿地,可能会造成潮汐潜在有害影响比较湿地系统。这项研究的结果将为滨海湿地管理和监控沿长岛海湾河口有益工具。

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