Spatio-temporal sensitivity of MODIS land surface temperature anomalies indicates high potential for large-scale land cover change detection in Arctic permafrost landscapes
Spatio-temporal sensitivity of MODIS land surface temperature anomalies indicates high potential for large-scale land cover change detection in Arctic permafrost landscapes
复制标题
DOI：
10.1016/j.rse.2015.06.017
复制
发表时间：
2014-12
影响因子：
13.5
通讯作者：
Sina Muster;M. Langer;A. Abnizova;K. Young;J. Boike
中科院分区：
文献类型：
--
作者：
Sina Muster;M. Langer;A. Abnizova;K. Young;J. Boike
北极气候的加速变暖可能会改变当地和区域的地表能量平衡，而地表温度的变化是一个关键指标。模拟当前和预期的地表能量平衡变化需要了解LST和土地覆盖之间的时空相互作用，这两者都可以通过空间测量进行全球监测。本文探讨了准确性的MODIS LST/ECONOMY每日L3全球1公里V005产品和时空敏感性，在加拿大高北极永久冻土景观的土地表面特性。土地覆盖范围从完全植被的湿苔苔原到贫瘠的岩石。中分辨率成像光谱仪的LST进行了比较，从2008年7月至2010年7月，包括夏季和冬季条件下收集的湿苔原地区的原位辐射计测量。在整个观测期内，中分辨率成像分光光度计LST的精度为-1.1 °C，均方根误差为3.9 °C。协议是最低的冻结回期间，MODIS LST表现出冷偏差可能是由于晴朗的天空条件的过度代表性。LST空间异常的多年分析，即，MODIS LST和MODIS LST区域平均值之间的差异，揭示了一个强大的时空模式。最高的变化，LST异常被发现在冻结和解冻期间，以及开放的水面在初夏由于存在或不存在的雪或冰。夏季异常模式是相似的，尽管降水，气温和净辐射的强烈差异。区域平均LST高于5.0 °C的夏季表现出最大的空间多样性，有四个不同的2.0 °C类。夏季异常范围为-4.5 °C至2.6 °C，平均标准差为1.8 °C。干燥的山脊地区温度最高，而湿地地区和植被稀少的基岩干燥地区温度最低。观测到的夏季LST异常可以作为一个基线，以评估过去和未来的变化，在陆地表面的属性，涉及到表面能量平衡。夏季异常类主要反映了降水和地面湿度的组合。因此，应进一步探讨利用这一工具监测北极地表干燥和湿润的可能性。将热卫星测量与光学和雷达图像相结合的多传感器方法有望成为动态的、基于过程的生态系统监测计划的有效工具。
The accelerated warming of the Arctic climate may alter the local and regional surface energy balances, for which changing land surface temperatures (LSTs) are a key indicator. Modeling current and anticipated changes in the surface energy balance requires an understanding of the spatio-temporal interactions between LSTs and land cover, both of which can be monitored globally by measurements from space. This paper investigates the accuracy of the MODIS LST/Emissivity Daily L3 Global 1 km V005 product and its spatio-temporal sensitivity to land surface properties in a Canadian High Arctic permafrost landscape. The land cover ranged from fully vegetated wet sedge tundra to barren rock. MODIS LSTs were compared with in situ radiometer measurements from wet tundra areas collected over a 2-year period from July 2008 to July 2010 including both summer and winter conditions. The accuracy of the MODIS LSTs was − 1.1 °C with a root mean square error of 3.9 °C over the entire observation period. Agreement was lowest during the freeze-back periods where MODIS LST showed a cold bias likely due to the overrepresentation of clear-sky conditions. A multi-year analysis of LST spatial anomalies, i.e., the difference between MODIS LSTs and the MODIS LST regional mean, revealed a robust spatio-temporal pattern. Highest variability in LST anomalies was found during freeze-up and thaw periods as well as for open water surface in early summer due to the presence or absence of snow or ice. The summer anomaly pattern was similar for all three years despite strong differences in precipitation, air temperature and net radiation. Summer periods with regional mean LSTs above 5.0 °C showed the greatest spatial diversity with four distinct 2.0 °C classes. Summer anomalies ranged from − 4.5 °C to 2.6 °C with an average standard deviation of 1.8 °C. Dry ridge areas heated up the most, while wetland areas and dry areas of sparsely vegetated bedrock with a high albedo remained coolest. The observed summer LST anomalies can be used as a baseline against which to evaluate both past and future changes in land surface properties that relate to the surface energy balance. Summer anomaly classes mainly reflected a combination of albedo and surface wetness. The potential to use this tool to monitor surface drying and wetting in the Arctic should therefore be further explored. A multi-sensor approach combining thermal satellite measurements with optical and radar imagery promises to be an effective tool for a dynamic, process-based ecosystem monitoring scheme.