Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data.
Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data.
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DOI：
10.1371/journal.pone.0001408
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发表时间：
2008-01-09
期刊：
影响因子：
3.7
通讯作者：
Rogers DJ
中科院分区：
文献类型：
--
作者：
Scharlemann JP;Benz D;Hay SI;Purse BV;Tatem AJ;Wint GR;Rogers DJ
来自地球轨道卫星的遥感环境数据越来越多地用于模拟植物和动物物种的分布和丰富程度，特别是那些具有经济或保护重要性的物种。NASA的Terra和Aqua卫星上搭载的中分辨率成像光谱仪（MODIS）传感器的时间序列数据提供了通过时间傅里叶分析捕获环境热和植被季节性的潜力，比以前使用NOAA先进超高分辨率辐射计（AVHRR）传感器数据更准确。MODIS数据是由8天或16天的时间间隔合成的，这给时间傅里叶分析带来了独特的问题。应用标准技术对MODIS数据在估计傅里叶谐波的幅度和相位时可能会引入高达30%的误差。提出了一种新的基于样条的算法，克服了复合MODIS数据的处理问题。该算法在随机选择振幅和相位值生成的人工数据上进行了测试，并在所有条件下提供了对输入变量的准确估计。然后应用该算法生成能够捕捉2001年至2005年MODIS数据中的季节性的层。本文对1 km MODIS数据的中红外反射率、昼夜地表温度（LST）、归一化植被指数（NDVI）和增强植被指数（EVI）进行了全球时间傅里叶处理，用于生态学和流行病学应用。与以前的多时间数据集相比，更精细的空间和时间分辨率，加上MODIS仪器更高的地理和光谱精度，意味着这些数据可以更有信心地用于物种分布建模。
Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.
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DOI：
10.1109/tgrs.2002.802519
发表时间：
2002-08-01
影响因子：
8.2
作者：
Jönsson, P;Eklundh, L
通讯作者：
Eklundh, L
影响因子：
64.8
作者：
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通讯作者：
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影响因子：
5.9
作者：
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通讯作者：
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影响因子：
64.8
作者：
Gilbert, M;Mitchell, A;Wint, W
通讯作者：
Wint, W
影响因子：
13.5
作者：
Huete, A;Didan, K;Ferreira, LG
通讯作者：
Ferreira, LG