Chapter 10
Crop Pattern and Status Monitoring
Eugene G. Yu and Zhengwei Yang
Abstract Statistical approaches are traditionally used in approximating crop pattern
and status monitoring which has limitations in timeliness and precision. Remote
sensing has been increasingly adopted in monitoring crop pattern and status with the
availability of observations in high spatial and temporal resolution. This
Chapter surveys the methods and technologies for crop condition monitoring using
remote sensing technologies. The advancements of remote sensing and related
processing capabilities make it possible to operationally monitor crop pattern and
crop status in very high spatial and temporal resolution. General workflows for
applying remote sensing in both crop pattern monitoring and crop status monitoring
are reviewed and described. Several operational cases are discussed in details. The
increasing constellation of satellite sensors with different spatial resolution improves
temporal resolution. Further development in machine learning and time series
analytics and massive parallel computing technologies will facilitate the timely
monitoring of crops up to field level. The application of remotely sensed data and
derived information on crop pattern and status will be further expanded into procession agriculture.
Keywords Crop pattern mapping · Crop status monitoring · Remote sensing ·
Feature selection · Classification · Cropland
E. G. Yu (*)
Center for Spatial Information Systems, George Mason University, Fairfax, VA, USA
e-mail: gyu@gmu.edu
Z. Yang
Research and Development Division, USDA National Agricultural Statistics Service,
Washington, DC, USA
e-mail: Zhengwei.Yang@nass.udsa.gov
© Springer Nature Switzerland AG 2021
L. Di, B. Üstündağ (eds.), Agro-geoinformatics, Springer Remote Sensing/
Photogrammetry, https://doi.org/10.1007/978-3-030-66387-2_10
175
Crop Pattern and Status Monitoring
Eugene G. Yu and Zhengwei Yang
Abstract Statistical approaches are traditionally used in approximating crop pattern
and status monitoring which has limitations in timeliness and precision. Remote
sensing has been increasingly adopted in monitoring crop pattern and status with the
availability of observations in high spatial and temporal resolution. This
Chapter surveys the methods and technologies for crop condition monitoring using
remote sensing technologies. The advancements of remote sensing and related
processing capabilities make it possible to operationally monitor crop pattern and
crop status in very high spatial and temporal resolution. General workflows for
applying remote sensing in both crop pattern monitoring and crop status monitoring
are reviewed and described. Several operational cases are discussed in details. The
increasing constellation of satellite sensors with different spatial resolution improves
temporal resolution. Further development in machine learning and time series
analytics and massive parallel computing technologies will facilitate the timely
monitoring of crops up to field level. The application of remotely sensed data and
derived information on crop pattern and status will be further expanded into procession agriculture.
Keywords Crop pattern mapping · Crop status monitoring · Remote sensing ·
Feature selection · Classification · Cropland
E. G. Yu (*)
Center for Spatial Information Systems, George Mason University, Fairfax, VA, USA
e-mail: gyu@gmu.edu
Z. Yang
Research and Development Division, USDA National Agricultural Statistics Service,
Washington, DC, USA
e-mail: Zhengwei.Yang@nass.udsa.gov
© Springer Nature Switzerland AG 2021
L. Di, B. Üstündağ (eds.), Agro-geoinformatics, Springer Remote Sensing/
Photogrammetry, https://doi.org/10.1007/978-3-030-66387-2_10
175