Hussain, M.H.; Abuhani, D.A.; Khan, J.; ElMohandes, M.; Zualkernan, I.; Ali, T. A Light-Weight Cropland Mapping Model Using Satellite Imagery. Sensors2023, 23, 6729.
Hussain, M.H.; Abuhani, D.A.; Khan, J.; ElMohandes, M.; Zualkernan, I.; Ali, T. A Light-Weight Cropland Mapping Model Using Satellite Imagery. Sensors 2023, 23, 6729.
Hussain, M.H.; Abuhani, D.A.; Khan, J.; ElMohandes, M.; Zualkernan, I.; Ali, T. A Light-Weight Cropland Mapping Model Using Satellite Imagery. Sensors2023, 23, 6729.
Hussain, M.H.; Abuhani, D.A.; Khan, J.; ElMohandes, M.; Zualkernan, I.; Ali, T. A Light-Weight Cropland Mapping Model Using Satellite Imagery. Sensors 2023, 23, 6729.
Abstract
Many applications in agriculture as well as other related fields including natural resources, environment, health, and sustainability, depend on recent and reliable cropland maps. Cropland extent and intensity plays a critical input variable for the study of crop production and food security around the world. However, generating such variables manually is difficult, expensive, and time consuming. In this work, we discuss a cost effective, fast, and simple machine learning based approach to provide reliable cropland mapping model using satellite imagery. The study includes four test regions namely; Iran, Mozambique, Sri-Lanka, and Sudan where Sentinel-2 satellite imagery were obtained with assigned NDVI scores. The solution presented in this paper discusses a complete pipeline including data collection, time series reconstruction , and cropland extent and crop intensity mapping using machine learning models. The approach proposed managed to achieve high accuracy results ranging between 0.92 to 0.98 across the four test regions at hand.
Keywords
Cropland extent; Cropland intensity; Machine Learning; Time series; Normalized Difference Vegetation Index
Subject
Engineering, Other
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
