A'/> Detecting microrefugia in semi-arid landscapes from remotely sensed vegetation dynamics
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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Detecting microrefugia in semi-arid landscapes from remotely sensed vegetation dynamics
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Detecting microrefugia in semi-arid landscapes from remotely sensed vegetation dynamics

机译：从远程感测植被动态检测半干旱景观中的微生物

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Abstract 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. Highlights ? Refugia from disturbance & climate change are valuable for conserving biodiversity. ? Expert rules and extant spatial datasets are insufficient to identify & map microrefugia. ? Landsat time series (LTS) provide solutions for direct detection of microrefugia.
机译：<！[cdata [ 抽象 Microorfugia是具有稳定，高质量的栖息地的景观，其特征在于受气候变异性或生态干扰驱动的动态环境条件的景观。 。对Microorfugia的潜力提供了相当大的兴趣，以便为景观和生物多样性保护提供气候变化恢复能力。虽然有吸引力的概念上，但有关如何识别气候变化的指导措施，以便研究和保护它们，并且经常缺乏所需的数据。本研究表明，使用研究区域的所有可用LANDSAT图像的时间序列遥感如何，可用于直接检测在西澳大利亚西南部的半干旱景观中由水补贴维护的微型资料。 < CE：简单 - 段ID =“SP0050”视图=“全部”>微生物鉴定为具有丰富植被和湿润和干旱之间的植被动态的像素。在每个像素时，谐波模型适合从Landsat-5主题映射器（TM）档案中的Wettest岁月编制的植被指数值的植被指数值。然后使用该模型来预测该像素在该像素的最干燥年的象征循环。候选微粒患者被定义为具有（1）干燥岁月高植被活性的那些像素，（2）不管在给定年份所经历的天气状况如何，这是一致的高度可预测的效果。评估了候选微核和景观特征的空间关系，升高了水分可用性（思想在这些半干旱景观中推动气候微核）。候选人微生物表现出很大的承诺。对高分辨率图像的评估显示，候选微粒可能是对干旱的缓冲措施，尽管还检测到其他扰动，尤其是火灾的避难所。相比之下，预期的物理特征的空间代理未能充分地代表横跨景观的微细葡萄原的分布，可能是由于数据质量和微细胞的异质性。直接检测地球观测数据的微生物是在数据限制区域中的有希望的解决方案。 Landsat时间序列分析非常适合本申请，因为它们可以表征Microfugia的栖息地质量和稳定性方面。 突出显示 ？ 避难所的避难所。气候变化对于保护生物多样性是有价值的。 ？ 专家规则和扩展空间数据集不足以识别＆amp;地图Microorfugia。 ？ Landsat时间序列（LTS）提供用于直接检测Microorfugia的解决方案。

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