Crop Type Identification for Smallholding Farms: Analyzing Spatial, Temporal and Spectral Resolutions in Satellite Imagery. (arXiv:2205.03104v1 [cs.CV])

Web: http://arxiv.org/abs/2205.03104

The integration of the modern Machine Learning (ML) models into remote
sensing and agriculture has expanded the scope of the application of satellite
images in the agriculture domain. In this paper, we present how the accuracy of
crop type identification improves as we move from
medium-spatiotemporal-resolution (MSTR) to high-spatiotemporal-resolution
(HSTR) satellite images. We further demonstrate that high spectral resolution
in satellite imagery can improve prediction performance for low spatial and
temporal resolutions (LSTR) images. The F1-score is increased by 7% …

arxiv cv identification satellite type