Generating Land Cover Maps in Semi-arid Regions Based on a 3D Semantic Segmentation Architecture Using Multi-temporal Sentinel-2 Satellite Images: A Case Study of Ludhiana District in Punjab, India

Using satellite imagery for land cover mapping is of utmost importance due to its role played in environmental management and protection, assessment of natural resources and human activities and planning for sustainable development. The objective of this research study is to generate high-resolution...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of the Indian Society of Remote Sensing Jg. 52; H. 2; S. 383 - 398
Hauptverfasser:	Buttar, Preetpal Kaur, Sachan, Manoj Kumar
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New Delhi Springer India 01.02.2024 Springer Nature B.V
Schlagworte:	Agricultural land Algorithms Arid regions Arid zones case studies Classification cropland data collection Datasets Deep learning Earth and Environmental Science Earth Sciences Environmental management humans image analysis Image segmentation India Land cover Land use Mapping Natural resources Neural networks Population decline Population growth Remote sensing Remote Sensing/Photogrammetry Research Article Satellite imagery satellites Semantic segmentation Semantics Semi arid areas Semiarid zones shrinkage Sustainable development urban population Urban populations Punjab India India Land cover mapping 3D encoder–decoder architecture Semantic segmentation Semi-arid regions Remote sensing Sentinel-2
ISSN:	0255-660X, 0974-3006
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!