Remote sensing phenological monitoring framework to characterize corn and soybean physiological growing stages

被引:74
作者
Diao, Chunyuan [1 ]
机构
[1] Univ Illinois, Dept Geog & Geog Informat Sci, Urbana, IL 61801 USA
基金
美国国家科学基金会;
关键词
Time series analysis; MODIS; Phenology; Agriculture; Crop progress; NDVI TIME-SERIES; LAND-SURFACE PHENOLOGY; CROP PHENOLOGY; VEGETATION PHENOLOGY; FOREST PHENOLOGY; SPRING PHENOLOGY; YIELD ESTIMATION; CLIMATE-CHANGE; MODEL; DYNAMICS;
D O I
10.1016/j.rse.2020.111960
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The phenological dynamics of crops reflect the response and feedback of agricultural systems to climate and environmental constraints, and have significant controls on carbon and nutrient cycling across the globe. Remote monitoring of crop phenological dynamics in a consistent and systematic manner is vitally crucial for optimizing the farm management activities and evaluating the agricultural resilience to extreme weather conditions and future climate change. Yet our ability to retrieve crop growing stages with satellite time series is limited. The remotely sensed phenological transition dates may not be characteristic of crop physiological growing stages. The objective of this study is to develop a remote sensing phenological monitoring framework that can reconcile satellite-based phenological measures with ground-based crop growing observations, with corn and soybean in Illinois as a case study. The framework comprises three key components: time series phenological pre-processing, time series phenological modeling, and time series phenological characterization. As an exploratory prototype, the framework retrieved a total of 56 phenological transition dates that were subsequently evaluated with the district-level ground phenological observations. The results indicated that the devised framework can adequately retrieve a wide range of physiological growing stages for corn and soybean in Illinois, with R square greater than 0.6 and RMSE less than 1 week for most stages. The devised framework largely extends the limited satellite phenological measures to a range of phenological transition dates that are characteristic of essential crop growing stages. It paves the way for formulating standard crop phenological monitoring protocols via remote sensing. The wealth of retrieved phenological characteristics open up unique opportunities to enhance our understanding of the complex mechanisms underlying the crop growth in response to varying environmental stresses, and to make more adaptive farm management strategies towards sustained agricultural development.
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页数:18
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