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Detecting microrefugia in semi-arid landscapes from remotely sensed vegetation dynamics

机译:从遥感植被动态中检测半干旱景观的微反射

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摘要

Microrefugia are sites with stable, high quality habitat within landscapes characterized by dynamic environmental conditions driven by climate variability or ecological disturbances. There is considerable interest in the potential of microrefugia to provide climate change resilience to landscapes and to biodiversity conservation. Although attractive conceptually, there is yet little guidance on how to identify climate change microrefugia in order to study and protect them, and the data required to do so are often lacking. This study demonstrates how time series remote sensing, using all available Landsat images of a study area, can be used to directly detect microrefugia maintained by water subsidies in a semi-arid landscape in southwest Western Australia. Microrefugia were identified as pixels with abundant vegetation and consistent vegetation dynamics between wet and dry years. At every pixel, a harmonic model was fit to the intra-annual time series of vegetation index values compiled from the wettest years in the Landsat-5 Thematic Mapper (TM) archive. This model was then used to predict the phenological cycle of the driest years at that pixel. Candidate microrefugia were defined to be those pixels with (1) high vegetation activity in dry years and (2) highly predictable phenologies that are consistent regardless of the weather conditions experienced in a given year. Spatial relationships between candidate microrefugia and landscape features associated with elevated moisture availability (thought to drive climate microrefugia in these semi-arid landscapes) were assessed. The candidate microrefugia show great promise. Evaluations against high-resolution imagery reveal that candidate microrefugia most likely buffer against drought, although refugia from other disturbances, especially fire, were also detected. In contrast, spatial proxies of the physical features expected to maintain microrefugia failed to adequately represent the distribution of microrefugia across the landscape, likely due to data quality and the heterogeneity of microrefugia. Direct detection of microrefugia with Earth observation data is a promising solution in data limited regions. Landsat time series analyses are well suited to this application as they can characterize both the habitat quality and stability aspects of microrefugia.
机译:Microrefugia是在景观中具有稳定,高质量栖息地的场所,其特征是由气候变化或生态干扰驱动的动态环境条件。人们对微型避难所具有极大的兴趣,它具有为景观和生物多样性保护提供气候变化适应力的潜力。尽管从概念上讲是有吸引力的,但是对于如何识别气候变化微不足之处进行研究和保护的指导却很少,而且通常缺乏这样做所需的数据。这项研究展示了如何使用研究区域的所有可用Landsat影像进行时间序列遥感,以直接检测西澳大利亚州西南半干旱景观中水补贴维持的微区系。微区被鉴定为在湿年和干年之间具有丰富植被和一致的植被动态的像素。在每个像素处,均将谐波模型拟合到Landsat-5 Thematic Mapper(TM)档案库中从最湿年份收集的植被指数值的年内时间序列。然后将该模型用于预测该像素处最干旱年份的物候周期。候选微区被定义为具有以下特征的像素:(1)干旱年份的植被活跃度高;(2)高度可预测的物候态,无论给定年份的天气状况如何,其物候一致。评估了候选微区和与增加水分供应量相关联的景观特征之间的空间关系(以推动这些半干旱地区的气候微区)。候选微refugia显示出很大的希望。对高分辨率图像的评估表明,虽然还检测到其他干扰(尤其是火灾)造成的干扰,但候选微避难最有可能抵御干旱。相比之下,可能由于数据质量和微避难所的异质性,预期维持微避难所的物理特征的空间代理不能充分代表微避难所在整个景观中的分布。利用地球观测数据直接检测微区系是在数据有限区域中很有希望的解决方案。 Landsat时间序列分析非常适合此应用程序,因为它们可以表征微型避难所的栖息地质量和稳定性。

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  • 作者

    Andrew, M.E.; Warrener, H.;

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  • 年度 2017
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  • 正文语种 eng
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