Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery
Accurately identifying the distribution of vineyard cultivation is of great significance for the development of the grape industry and the optimization of planting structures. Traditional remote sensing techniques for vineyard identification primarily depend on machine learning algorithms based on s...
Saved in:
| Main Authors: | Xuemei Han, Huichun Ye, Yue Zhang, Chaojia Nie, Fu Wen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-10-01
|
| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/14/11/2542 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Synergistic mapping of urban tree canopy height using ICESat-2 data and GF-2 imagery
by: Xiaodi Xu, et al.
Published: (2025-02-01) -
Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection
by: Tuğçe Öznacar, et al.
Published: (2025-04-01) -
A Road Extraction Algorithm for the Guided Fusion of Spatial and Channel Features from Multi-Spectral Images
by: Lin Gao, et al.
Published: (2025-02-01) -
Fusion of MHSA and Boruta for key feature selection in power system transient angle stability
by: WANG Man, et al.
Published: (2025-01-01) -
A stacked learning framework for accurate classification of polycystic ovary syndrome with advanced data balancing and feature selection techniques
by: Heba M. Emara, et al.
Published: (2025-05-01)