Stellite-based classification of tillage practices in the U.S.
Abstract
The number of applications based on Machine learning algorithms applied to satellite images has been increasing steadily in last few years. While in the context of agricultural monitoring these techiques are most commonly used for land cover type and crop classification, they also show a great potential for monitoring management practices. In this study, we present some preliminary results on classifying tillage practices in the U.S. midwest using Landsat 8 and Sentinel 2 data.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.B51C1820A
- Keywords:
-
- 0402 Agricultural systems;
- BIOGEOSCIENCES;
- 0430 Computational methods and data processing;
- BIOGEOSCIENCES;
- 0434 Data sets;
- BIOGEOSCIENCES;
- 0480 Remote sensing;
- BIOGEOSCIENCES