Semantic segmentation of land cover from high resolution multispectral satellite images by spectral-spatial convolutional neural network
Author:
Affiliation:
1. Depertment of Geomatics Engineering, Karadeniz Technical University, Trabzon, Turkey
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/10106049.2020.1734871
Reference62 articles.
1. Improvements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification
2. Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey
3. Collective Sensing: Integrating Geospatial Technologies to Understand Urban Systems—An Overview
4. A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks
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