Synergistic Integration of Optical and Microwave Satellite Data for Crop Yield Estimation
Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave) remote sensing data for crop yield estimation and forecasting using two novel approaches. We first propose the lag between Enhanced Vegetation Index derived from MODIS and Vegetation Optical Depth derived from SMAP as a new joint metric combining the information from the two satellite sensors in a unique feature or descriptor. Our second approach avoids summarizing statistics and uses machine learning to combine full time series of EVI and VOD. This study considers two statistical methods, a regularized linear regression and its nonlinear extension called kernel ridge regression to directly estimate the county-level surveyed total production, as well as individual yields of the major crops grown in the region: corn, soybean and wheat. The study area includes the US Corn Belt, and we use agricultural survey data from the National Agricultural Statistics Service (USDA-NASS) for year 2015 for quantitative assessment.
Code (0)
등록된 구현이 없습니다.
Tasks
Earth ObservationregressionTime SeriesTime Series AnalysisMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Reconfigurable On-chip Photoconductive Switches
Microwave photonics uses light to carry and process microwave signals over a photonic link. However, light can instead be used as a stimulus to microwave devices that directly control microwave signals. Such optically co…
Picosecond-precision optical time transfer in free space using flexible binary offset carrier modulation
Free-space optical time transfer that features high precision and flexibility will act a crucial role in near-future ground-to-satellite/inter-satellite clock networks and outdoor timing services. Here we propose a free-…
Universal Silicon Microwave Photonic Spectral Shaper
Optical modulation plays arguably the utmost important role in microwave photonic (MWP) systems. Precise synthesis of modulated optical spectra dictates virtually all aspects of MWP system quality including loss, noise f…
BlockingSemantic segmentation on multi-resolution optical and microwave data using deep learning
Presently, deep learning and convolutional neural networks (CNNs) are widely used in the fields of image processing, image classification, object identification and many more. In this work, we implemented convolutional n…
Deep Learningimage-classificationImage ClassificationMulti-Label Classification+2Seamlessly merging radar ranging/imaging, wireless communications, and spectrum sensing, for 6G empowered by microwave photonics
Integration of radar, wireless communications, and spectrum sensing is being investigated for 6G with an increased spectral efficiency. Microwave photonics (MWP), a technique that combines microwave engineering and photo…