Remote Sensing, Journal Year: 2025, Volume and Issue: 17(3), P. 550 - 550
Published: Feb. 6, 2025
The present survey examines the role of big data analytics in advancing remote sensing and geospatial analysis. increasing volume complexity are driving adoption machine learning (ML) artificial intelligence (AI) techniques, such as convolutional neural networks (CNNs) long short-term memory (LSTM) networks, to extract meaningful insights from large, diverse datasets. These AI methods enhance accuracy efficiency spatial temporal analysis, benefiting applications environmental monitoring, urban planning, disaster management. Despite these advancements, challenges related computational efficiency, integration, model transparency remain. This paper also discusses emerging trends highlights potential hybrid approaches, cloud computing, edge processing overcoming challenges. integration with is poised significantly improve our ability monitor manage Earth systems, supporting more informed sustainable decision-making.
Language: Английский