Akademik Veri Yönetim Sistemi
Landscape Architecture II, Prof. Dr. Murat DAL, Editör, BIDGE Publications, Ankara, ss.98-113, 2024
Data science and statistics have become indispensable disciplines, especially with the rapid technological advancements reshaping various industries. The integration of innovative technologies such as big data analytics, artificial intelligence, and machine learning is transforming how decisions are made across diverse fields, including business, healthcare, and urban planning. In landscape architecture, these disciplines hold the potential to revolutionize the way we design, analyze, and sustain landscapes, offering data-driven insights that enhance both environmental and societal outcomes.
Data science involves extracting meaningful information from large data sets, encompassing processes such as data collection, cleaning, analysis, and interpretation. These processes enable practitioners to make well-informed decisions by understanding complex data patterns. Statistics plays a vital role in these processes, providing scientific methodologies for analyzing and deriving insights from data. Applied together, data science and statistics have become pivotal in areas like climate adaptation, urban design, biodiversity conservation, and resource management. This section explores the current applications, future development trends, and societal impacts of data science and statistics in landscape architecture. By examining the innovations and methodologies shaping this intersection, we can uncover new opportunities for addressing environmental challenges and advancing sustainable landscape practices.