...
首页> 外文期刊>Estuarine Coastal and Shelf Science >Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery
【24h】

Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery

机译:使用基于对象的多传感器卫星图像分类来绘制最大的连续亚马逊红树林带中的变化

获取原文
获取原文并翻译 | 示例
           

摘要

Mapping and monitoring mangrove ecosystems is a crucial objective for tropical countries, particularly where human disturbance occurs and because of uncertainties associated with sea level and climatic fluctuation. In many tropical regions, such efforts have focused largely on the use of optical data despite low capture rates because of persistent cloud cover. Recognizing the ability of Synthetic Aperture Radar (SAR) for providing cloud-free observations, this study investigated the use of JERS-1 SAR and ALOS PALSAR data, acquired in 1996 and 2008 respectively, for mapping the extent of mangroves along the Brazilian coastline, from east of the Amazon River mouth, Para State, to the Bay of Sao Jose in Maranhao. For each year, an object-orientated classification of major land covers (mangrove, secondary vegetation, gallery and swamp forest, open water, intermittent lakes and bare areas) was performed with the resulting maps then compared to quantify change. Comparison with available ground truth data indicated a general accuracy in the 2008 image classification of all land covers of 96% (kappa = 90.6%, tau = 92.6%). Over the 12 year period, the area of mangrove increased by 718.6 km2 from 6705 m~2 to 7423.60 km~2, with 1931.0 km~2 of expansion and 1213 km~2 of erosion noted; 5493 km~2 remained unchanged in extent. The general accuracy relating to changes in mangroves was 83.3% (Kappa 66.1%; tau 66.7%). The study confirmed that these mangroves constituted the largest continuous belt globally and were experiencing significant change because of the dynamic coastal environment and the influence of sedimentation from the Amazon River along the shoreline. The study recommends continued observations using combinations of SAR and optical data to establish trends in mangrove distributions and implications for provision of ecosystem services (e.g., fish/invertebrate nurseries, carbon storage and coastal protection).
机译:绘制和监测红树林生态系统是热带国家的重要目标,特别是在发生人为干扰并且由于海平面和气候波动带来的不确定性的国家。在许多热带地区,尽管由于持续的云层覆盖而捕获率较低,但此类努力主要集中在光学数据的使用上。认识到合成孔径雷达(SAR)提供无云观测的能力,本研究调查了分别于1996年和2008年获得的JERS-1 SAR和ALOS PALSAR数据用于绘制巴西海岸线上的红树林范围的地图,从帕拉州亚马逊河河口以东到Maranhao的圣何塞湾。每年,对主要的土地覆被(红树林,次生植被,画廊和沼泽森林,开阔水域,间断的湖泊和裸露的区域)进行面向对象的分类,然后将其与生成的地图进行比较以量化变化。与可用的地面真实数据进行的比较表明,在所有土地覆被的2008年图像分类中,总体准确性为96%(kappa = 90.6%,tau = 92.6%)。在过去的12年中,红树林面积从6705 m〜2增加到7423.60 km〜2,增加了718.6 km2,其中有1931.0 km〜2的扩张和1213 km〜2的侵蚀。 5493 km〜2范围保持不变。与红树林变化有关的一般精度为83.3%(卡帕66.1%;牛头66.7%)。研究证实,这些红树林构成了全球最大的连续带,并且由于动态的沿海环境和沿海岸线的亚马孙河的沉积影响而正在发生重大变化。该研究建议继续使用SAR和光学数据进行观察,以建立红树林分布趋势及其对提供生态系统服务的意义(例如鱼类/无脊椎动物苗圃,碳储存和沿海保护)。

著录项

  • 来源
    《Estuarine Coastal and Shelf Science》 |2013年第20期|83-93|共11页
  • 作者单位

    Universidade Federal do Para, Institute de Geociencias, Cidade Universitaria, PO Box 8608, 66075-110 Belem, Para, Brazil;

    Universidade Federal do Para, Institute de Geociencias, Cidade Universitaria, PO Box 8608, 66075-110 Belem, Para, Brazil,Vale Institute of Technology Sustainable Development, Rua Boaventura da Silva, 955, 66055-090 Belem, Para, Brazil;

    Institut de Recherche pour le Developpement (IRD), UMR AMAP, Boulevard de la Lironde, TA A5I-PS2, Montpellier Cedex 5 F-34398, France;

    Aberystwyth University, Institute of Geography and Earth Sciences, Llandinum Building, Aberystwyth, Ceredigion SY23 3AD, UK;

    Solo Earth Observation (soloEO), TIT Mid-Tower 1708, Kachidoki 6-3-2, Chuo-ku, Tokyo 104-0054, Japan;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    ALOS PALSAR; GIS; JERS; mangroves; synthetic aperture radar; coastal changes;

    机译:ALOS PALSAR;地理信息系统JERS;红树林;合成孔径雷达沿海变化;

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