TY  - JOUR
N2  - ARC is a new method to generates time series of a full set of biophysical parameters derived from optical EO. Here, we examine relationships between this ?full? set and maize yield. 15 Parameters per pixel are estimated over the US corn belt using ARC, to fully describe the phenology, soil, and crop status over time for typical behaviour. ARC is tested for a new model over an area of irrigated and rain-fed winter crop in South Africa. We find that care must be taken for episodic events, and robust filtering methods should be developed for ARC, but average magnitude and timing is well-expressed. We find that a robust yield model (over time and space) can be created at the county-level for maize using only EO parameters with RMSE of 704-938 kg/ha using a non-linear model, but the results are only slightly poorer if a linear model is used. It compares well to a model that also includes weather data, showing that a model can be driven by optical EO data alone.
VL  - X-3
ID  - discovery10201557
SN  - 2194-9050
N1  - Copyright © Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).
EP  - 206
JF  - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
AV  - public
SP  - 199
UR  - https://doi.org/10.5194/isprs-annals-x-3-2024-199-2024
TI  - Crop Yield Mapping with ARC using only Optical Remote Sensing
KW  - Remote Sensing
KW  -  Radiative Transfer
KW  -  Big Data
KW  -  Crop Monitoring
KW  -  Crop Yield
KW  -  Sentinel-2 MSI
KW  -  Biophysical Parameters
A1  - Lewis, Philip E
A1  - Yin, Feng
A1  - Gómez-Dans, Jose Luis
A1  - Weiß, Thomas
A1  - Adam, Elhadi
PB  - Copernicus GmbH
Y1  - 2024/11/04/
ER  -