A Two-Step Filtering approach for detecting maize and soybean phenology with time-series MODIS data
A Two-Step Filtering approach for detecting maize and soybean phenology with time-series MODIS data
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DOI：
10.1016/j.rse.2010.04.019
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发表时间：
2010-10-15
影响因子：
13.5
通讯作者：
Arkebauer, Timothy J.
中科院分区：
文献类型：
--
作者：
Sakamoto, Toshihiro;Wardlow, Brian D.;Arkebauer, Timothy J.
作物发育阶段代表了灌溉调度/肥料管理，了解季节性生态系统二氧化碳（CO2）交换和评估作物生产力的重要信息。在这项研究中，我们设计了一种方法，称为两步过滤（TSF）检测玉米和大豆的物候期从时间序列宽动态范围植被指数（WDRVI）数据来自中分辨率成像光谱仪（MODIS）250米的观测。TSF方法由两步滤波方案组成，该方案包括：（i）用基于小波的滤波器平滑时间WDRVI数据，以及（ii）从形状模型拟合过程导出最佳缩放参数。然后，通过使用最佳缩放参数和形状模型上的特定物候日期的初始值来估计关键作物发育阶段的日期，所述形状模型是参考地面作物生长阶段观测而初步定义的。形状模型是具有典型季节特征的特定作物WDRVI曲线，其通过对从灌溉玉米和大豆研究站点收集的MODIS 250-m数据的平滑的多年WDRVI剖面进行平均来定义。TSF方法被应用于6年期间的MODIS导出的WDRVI数据（2003年至2008年），两个灌溉点和一个灌溉点种植玉米或大豆，作为内布拉斯加大学林肯分校碳封存计划（CSP）的一部分。卫星反演与CSP在这三个地点的六个生长季节收集的地面作物生长阶段观测结果的比较表明，TSF方法可以准确估计玉米四个关键物候期的日期（V2.5：营养生长早期，R1：吐丝期，R5：凹痕期，R6：成熟期）和大豆（V1：营养生长早期，R5：开始种子，R6：饱满种子和R7：开始成熟）。玉米和大豆的物候期估计的均方根误差分别为2.9 [R1]~ 7.0 [R5] d和32 [R6]~ 6.9 [R7] d。此外，TSF方法也适用于两年（2001年和2002年）在内布拉斯加州东部，以测试其能力，这些关键的物候阶段在一个更大的地理区域的时空格局的特点。MODIS衍生的作物物候期日期与美国农业部（USDA）国家农业统计局（NASS）报告的内布拉斯加州东部三个作物农业统计区（ASD）的统计作物进展数据一致。在ASD水平上，玉米物候期估计的RMSE范围为1.6 [R1]至5.6 [R5]天，大豆为2.5 [R7]至5.3 [R5]天。(C)2010年爱思唯尔公司All rights reserved.
The crop developmental stage represents essential information for irrigation scheduling/fertilizer management, understanding seasonal ecosystem carbon dioxide (CO2) exchange, and evaluating crop productivity. In this study, we devised an approach called the Two-Step Filtering (TSF) for detecting the phenological stages of maize and soybean from time-series Wide Dynamic Range Vegetation Index (WDRVI) data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m observations. The TSF method consists of a Two-Step Filtering scheme that includes: (i) smoothing the temporal WDRVI data with a wavelet-based filter and (ii) deriving the optimum scaling parameters from shape-model fitting procedure. The date of key crop development stages are then estimated by using the optimum scaling parameters and an initial value of the specific phenological date on the shape model, which are preliminary defined in reference to ground-based crop growth stage observations. The shape model is a crop-specific WDRVI curve with typical seasonal features, which were defined by averaging smoothed, multi-year WDRVI profiles from MODIS 250-m data collected over irrigated maize and soybean study sites.In this study, the TSF method was applied to MODIS-derived WDRVI data over a 6-year period (2003 to 2008) for two irrigated sites and one rainfed site planted to either maize or soybean as part of the Carbon Sequestration Program (CSP) at the University of Nebraska-Lincoln. A comparison of satellite-based retrievals with ground-based crop growth stage observations collected by the CSP over the six growing seasons for these three sites showed that the TSF method can accurately estimate the date of four key phenological stages of maize (V2.5: early vegetative stage, R1: silking stage, R5: dent stage and R6: maturity) and soybean (V1: early vegetative stage, R5: beginning seed, R6: full seed and R7: beginning maturity). The root mean square error (RMSE) of phenological-stage estimation for maize ranged from 2.9 [R1] to 7.0 [R5] days and from 32 [R6] to 6.9 [R7] days for soybean, respectively. In addition, the TSF method was also applied for two years (2001 and 2002) over eastern Nebraska to test its ability to characterize the spatio-temporal patterns of these key phenological stages over a larger geographic area. The MODIS-derived crop phenological stage dates agreed well with the statistical crop progress data reported by the United State Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) for eastern Nebraska's three crop agricultural statistic districts (ASDs). At the ASD-level, the RMSE of phenological-stage estimation ranged from 1.6 [R1] to 5.6 [R5] days for maize and from 2.5 [R7] to 5.3 [R5] days for soybean. (C) 2010 Elsevier Inc. All rights reserved.