首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Regional-scale seagrass habitat mapping in the Wider Caribbean region using Landsat sensors: Applications to conservation and ecology
【24h】

Regional-scale seagrass habitat mapping in the Wider Caribbean region using Landsat sensors: Applications to conservation and ecology

机译:使用Landsat传感器在大加勒比地区进行区域尺度海草栖息地制图:在保护和生态方面的应用

获取原文
获取原文并翻译 | 示例
           

摘要

Seagrass meadows occupy a large proportion of the world's coastal oceans and are some of the most productive systems on Earth. Direct and indirect human-derived impacts have led to significant seagrass declines worldwide and the alteration of services linked to their biodiversity. Effective conservation and the provision of sustainable recovery goals for ecologically significant species are limited by the absence of reliable information on seagrass extent. This is especially true for the Wider Caribbean region (WCR) where many conservation initiatives are under way, but are impaired by the lack Of accurate baseline habitat maps. To assist with such a fundamental conservation need using high-resolution remote sensing data, both environmental and methodological challenges need to be tackled. First, the diversity of environments, the heterogeneity of habitats, and the vast extent of the targeted region mean that local expertise and field data of adequate quality and resolution are seldom available. Second, large-scale high-resolution mapping requires several hundred Landsat 5 and 7 images, which poses substantial processing problems. The main goal of this study was to test the feasibility of achieving Landsat-based large-scale seagrass mapping with limited ground-truth data and acceptable accuracies. We used the following combination of methods to map seagrass throughout the WCR: geomorphological segmentation, contextual editing, and supervised classifications. A total of 40 Landsat scenes (path-row) were processed. Three major classes were derived ('dense seagrass', 'medium-sparse seagrass', and a generic 'other' class). Products' accuracies were assessed against (i) selected in situ data; (ii) patterns detectable with very high-resolution IKONOS images; and (iii) published habitat maps with documented accuracies. Despite variable overall classification accuracies (46-88%), following their critical evaluation, the resulting thematic maps were deemed acceptable to (i) regionally Provide an adequate baseline for further large-scale conservation programs and research actions; and (ii) regionally re-assess carrying capacity estimates for green turtles. They certainly represent a drastic improvement relative to current regional databases. (C) 2008 Elsevier Inc. All rights reserved.
机译:海草草甸占世界沿海海洋的很大一部分,是地球上生产力最高的一些系统。人类直接或间接的影响已导致全球海草大量减少,以及与其生物多样性有关的服务发生了变化。由于缺乏有关海草范围的可靠信息,有效保护和为具有生态意义的物种提供了可持续的恢复目标受到了限制。对于正在实施许多保护措施但由于缺乏准确的基线生境图而受到损害的大加勒比地区(WCR)尤其如此。为了利用高分辨率的遥感数据满足这种基本的保护需求,需要解决环境和方法上的挑战。首先,环境的多样性,生境的异质性和目标区域的广泛性意味着很少有足够的质量和分辨率的当地专业知识和现场数据。第二,大规模的高分辨率制图需要数百个Landsat 5和7图像,这带来了实质性的处理问题。这项研究的主要目的是测试在有限的地面数据和可接受的精度下实现基于Landsat的大规模海草制图的可行性。我们使用以下方法组合在整个WCR中绘制海草地图:地貌分割,上下文编辑和监督分类。总共处理了40个Landsat场景(路径行)。派生了三个主要类别(“密集海草”,“中等稀疏海草”和通用“其他”类别)。根据(i)选定的现场数据评估产品的准确性; (ii)用超高分辨率IKONOS图像可检测到的图案; (iii)已发布的栖息地地图以及已记录的准确性。尽管总体分类的准确性各不相同(46-88%),但经过严格的评估后,得出的专题图仍被认为可以(i)在区域范围内为进一步的大规模保护计划和研究活动提供适当的基线; (ii)在区域范围内重新评估绿海龟的承载能力估计。相对于当前的区域数据库,它们无疑代表了巨大的进步。 (C)2008 Elsevier Inc.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号