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Analysis of regional vegetation changes with medium and high resolution imagery

机译:用中高分辨率图像分析区域植被变化

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摘要

The singular characteristics of the Canarian archipelago (Spain) and, in particular, of the Gran Canaria island have allowed the development of a unique biological richness. Almost half of its territory is protected to preserve the natural environment and, in consequence, the monitoring of vegetated regions plays an important role for regional administrations which aim to develop the corresponding policies for the conservation of such ecosystems. The Normalized Difference Vegetation Index (NDVI) is a common index applied for vegetation studies. It is important to emphasize that NDVI is sensor-dependent, and changes are affected by soil background, irradiance, solar position, atmospheric attenuation, season, hydric situation and climate of the area. So, a fixed threshold cannot be set, even for the same sensor or season, to properly segment vegetated areas. In this context, a robust methodology has been applied to ensure a reliable estimation of changes using the same sensor in multiple dates or different sensors. To that respect, a supervised procedure is presented consisting on the selection of different regions within each image to precisely map each cover with its associated NDVI values and, in consequence, obtain for each individual image the optimal threshold to properly segment vegetation without the need to perform the complex preprocessing required to estimate the ground reflectivity. On the other hand, fires are an important aspect of an ecosystem and their study, a fundamental task to perform a complete assessment of the environmental and economic damage. In our work we have also analyzed in detail the fire occurring during 2007 and precisely assessed the results.
机译:加那利群岛(西班牙),尤其是大加那利群岛的独特特征,使人们拥有了独特的生物资源。其几乎一半的领土受到保护,以保护自然环境,因此,对植被区的监视对于旨在制定相应的生态系统保护政策的区域行政机构起着重要的作用。归一化植被指数(NDVI)是用于植被研究的常用指数。需要特别强调的是,NDVI取决于传感器,其变化会受到土壤背景,辐照度,太阳位置,大气衰减,季节,含水状况和该地区气候的影响。因此,即使对于相同的传感器或季节,也无法设置固定的阈值以正确分割植被区域。在这种情况下,已应用一种可靠的方法来确保使用多个日期中的相同传感器或不同传感器来可靠地估计变化。为此,提出了一种监督程序,该程序包括选择每个图像内的不同区域,以精确地将每个覆盖物及其相关的NDVI值映射到地图上,从而为每个单独的图像获得最佳阈值,以正确地分割植被,而无需执行估计地面反射率所需的复杂预处理。另一方面,火灾是生态系统及其研究的重要方面,是对环境和经济损害进行全面评估的基本任务。在我们的工作中,我们还详细分析了2007年发生的火灾并精确评估了结果。

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  • 来源
  • 会议地点 Edinburgh(GB)
  • 作者单位

    Institute for Oceanography and Global Change, Universidad de Las Palmas de G.C.,Campus Universitario de Tafira, 35017 Las Palmas de Gran Canada, Spain;

    Institute for Oceanography and Global Change, Universidad de Las Palmas de G.C.,Campus Universitario de Tafira, 35017 Las Palmas de Gran Canada, Spain;

    Institute for Oceanography and Global Change, Universidad de Las Palmas de G.C.,Campus Universitario de Tafira, 35017 Las Palmas de Gran Canada, Spain;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Vegetation index; NDVI; change detection; Landsat; Spot; Deimos;

    机译:植被指数; NDVI;变更检测;陆地卫星点;德莫斯;

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