학술논문

Forecasting Wheat Yield Using Remote Sensing: The ARYA Forecasting System
Document Type
Conference
Source
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS Geoscience and Remote Sensing Symposium IGARSS , 2021 IEEE International. :6419-6422 Jul, 2021
Subject
Aerospace
Geoscience
Photonics and Electrooptics
Signal Processing and Analysis
Temperature sensors
Temperature measurement
Adaptation models
Atmospheric modeling
Vegetation mapping
Predictive models
Land surface temperature
Agriculture
wheat
yield
MODIS
DVI
LST
Language
ISSN
2153-7003
Abstract
In this study we present a model to forecast wheat yield based on the evolution of the Difference Vegetation Index (DVI) and the Growing Degree Days (GDD), presented in Franch et al. (2015), but adapted to Franch et al. (2019) model. Additionally, we explore how the Land Surface Temperature (LST) can be included into the model and if this parameter adds any value to the model when combined with the optical information. This study is applied to MODIS data at 1km resolution to monitor the national and state level yield of winter wheat in the United States and Ukraine from 2001 to 2019.