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Dynamics in mangroves assessed by high-resolution and multi-temporal satellite data: a case study in Zhanjiang Mangrove National Nature Reserve (ZMNNR), P. R. China

机译:通过高分辨率和多时相卫星数据评估红树林动态:中国中国湛江红树林国家级自然保护区(ZmNNR)的案例研究

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摘要

Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc.) to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China) were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively). Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (-36%) was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%), the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements) (August–September, 2009) as well as spectral reflectance values (obtained from pansharpened GeoEye-1), both and small are distinguishable at 73–100% accuracy, whereas tall was correctly classified at only 53% due to its mixed vegetation stands with (overall classification accuracy: 85%). In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m) for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e.g. ) at Gaoqiao. Despite limitations such as geometric distortion and single panchromatic band, the 42 yr old Corona declassified images are invaluable for land-use/cover change detections when compared to recent satellite data sets.
机译:红树林在全球范围内正在减少,这主要是由于人为干预,因此需要评估其过去和现在的状况(例如面积,物种水平分布等),以实施更好的保护和管理策略。本文利用1967年,2000年和2009年的卫星图像(分别为传感器Corona KH-4B,Landsat ETM +和GeoEye-1)对高桥(中国PR)的红树林动态进行了评估。首先,对卫星数据进行了多时间分析,其次,通过对高分辨率卫星图像进行监督分类,分析了不同红树林林分之间的生物和非生物差异。 1967年至2009年,由于水稻种植和水产养殖,红树林覆盖率大幅下降(-36%)。此外,堤防建设阻止了红树林向内扩展。尽管在2000年至2009年之间,红树林面积有所增加(+ 24%),但由于增加了水产养殖面积,红树林/水产养殖的比例仍在下降,但以附近的水稻种植为代价。来自基于地面真实数据(基于5×5 m的树图测量)的土地利用/覆盖图(2009年8月至9月)以及光谱反射率值(从pansharpened GeoEye-1获得),无论大小可以以73-100%的准确度区分,而高大的树木由于其植被混合而被正确分类为仅53%(总分类准确度:85%)。就沉积物而言,三种红树林类型之间的沙子比例明显不同。总的来说,很好的证明了高分辨率的卫星图像(如GeoEye-1(0.5 m))用于红树林空间异质性评估和/或物种水平判别的优势,以及为非优势物种提供精确分类的复杂性(例如)在高桥。尽管存在几何失真和单个全色带等局限性,但与最近的卫星数据集相比,这幅具有4​​2年历史的Corona解密图像对于土地利用/覆盖变化检测而言具有不可估量的价值。

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