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Monitoring and forecasting ecosystem dynamics using the Terrestrial Observation and Prediction System (TOPS)

机译:使用陆地观测和预报系统(TOPS)监测和预测生态系统动态

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摘要

We present an approach for monitoring and forecasting landscape level indicators of the condition of protected area (PA) ecosystems including changes in snowcover, vegetation phenology and productivity using the Terrestrial Observation and Prediction System (TOPS). TOPS is a modeling framework that integrates operational satellite data, microclimate mapping, and ecosystem simulation models to characterize ecosystem status and trends. We have applied TOPS to investigate trends and patterns in landscape indicators using test cases at both national and park-level scales to demonstrate the potential utility of TOPS for supporting efforts by the National Park Service to develop standardized indicators for protected area monitoring. Our analysis of coarse resolution satellite-derived normalized difference vegetation index (NDVI) measurements for North America from 1982-2006 indicates that all but a few PAs are located in areas that exhibited a sustained decline in vegetation condition. We used Yosemite National Park as our park-level test case, and while no significant trends in NDVI were detected during the same period, evidence of drought-induced vegetation mortality and recovery patterns dominated the 25 year record. In our Yosemite analysis, we show that analyzing MODIS (Moderate Resolution Imaging Spectroradiometer) products (vegetation indices, absorbed radiation, land surface temperature and gross primary production) in conjunction with ground-based measurements, such as runoff, lends additional utility to satellite-based monitoring of ecosystems indicators, as together they provide a comprehensive view of ecosystem condition. Analyses of MODIS products from 2001-2006 show that year-to-year changes in the onset of spring at Yosemite were as large as 45 days, and this signal in the satellite data record is corroborated by observed changes in spring runoff patterns. Finally, we applied TOPS to assess long-term climate impacts on ecosystem condition at the scale of an individual park. When driven by projected climatic changes at Yosemite of 4-6 degrees C warming by 2100 with no changes in precipitation patterns, TOPS predicts significantly reduced winter snowpack and an earlier onset of the growing season, resulting in prolonged summer drought and reduced vegetation productivity.
机译:我们提供了一种使用陆地观测和预测系统(TOPS)来监视和预测保护区(PA)生态系统状况的景观水平指标的方法,其中包括积雪,植被物候和生产力的变化。 TOPS是一个建模框架,集成了运行中的卫星数据,微气候制图和生态系统模拟模型,以表征生态系统的状态和趋势。我们已经使用TOPS来利用国家和公园级别的测试案例来调查景观指标的趋势和模式,以证明TOPS在支持国家公园管理局开发保护区监测标准化指标方面的潜在效用。我们对1982年至2006年北美地区的卫星粗分辨率归一化差异植被指数(NDVI)进行的测量分析表明,除少数PA外,所有PA都位于植被状况持续下降的地区。我们以优胜美地国家公园作为公园级别的测试案例,虽然同期未发现NDVI的显着趋势,但干旱导致的植被死亡和恢复模式的证据主导了25年的记录。在我们的优胜美地分析中,我们表明分析MODIS(中等分辨率成像光谱仪)产品(植被指数,吸收辐射,地表温度和初级总产值)并结合地面测量(例如径流)可以为卫星-基于生态系统指标的监控,它们一起提供了生态系统状况的全面视图。对2001年至2006年MODIS产品的分析表明,优胜美地春季开始的逐年变化多达45天,而卫星数据记录中的这一信号被观察到的春季径流模式变化所证实。最后,我们运用TOPS评估了单个公园规模的长期气候对生态系统状况的影响。 TOPS预测,到2100年,在约塞米蒂4-6摄氏度变暖的预估气候变化的驱动下,降水量不会改变,TOPS预测冬季积雪会大大减少,生长期会更早开始,从而导致夏季干旱延长和植被生产力下降。

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