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Earth Observation in Urban Monitoring: Techniques and Challenges presents the latest techniques of remote sensing in urban monitoring, along with methods for quantitative and qualitative assessment using state-of-the-art Earth observation technologies. The book details the advances of remote sensing technologies in urban environmental monitoring for a range of practical and research applications, Earth observation datasets, remote sensing of environmental considerations, geostatistical techniques and resilience perspectives. Chapters cover sensor applications, urban growth modelling, SAR applications, surveying techniques, satellite time series analysis and a variety of other remote sensing technologies for urban monitoring.
Each chapter includes detailed case studies at a variety of scales and from a variety of geographies, offering up-to-date, global, urban monitoring methodologies for researchers, scientists and academics in remote sensing, geospatial research, environmental science and sustainability.
Focuses on a variety of interdisciplinary applications using Earth observation data, GIS and soft computing techniques to address various challenges in urban monitoring Provides numerous case studies at a variety of scales, from local to global, to aid readers in implementing urban monitoring techniques at any level Includes theoretical and applied research contributions along with background information on the use of concurrent technologies in the disciplines of urban studies
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Big Data Analytics in Agriculture focuses on the quantitative and qualitative assessment of agricultural systems using state-of-the-art technologies to deliver practical improvements in agricultural production. Addressing the challenge of translating data into real-world applications, the book provides a comprehensive mapping of the entire data lifecycle-from data generation, storage, and curation to processing and implementation. It guides readers through the steps required to produce high-quality, reliable information that supports effective decision-making. Following a logical progression, the volume demonstrates how diverse data streams converge into decision-support systems and how they can be transformed into actionable outcomes, aligned with intelligent, efficient, technologically advanced, economically viable, and politically and culturally sustainable practices. The book further explores the integration of information and communication technologies (ICT) and the Internet of Things (IoT) for managing rural assets and enhancing economic and environmental performance in spatially and temporally variable agricultural environments. Topics covered include big data analytics, data management and processing, and a range of algorithms and applications relevant to agriculture. Subtopics encompass artificial intelligence- and machine-learning-enabled smart and precision irrigation, disease and pest management, microclimatic forecasting, preventive fertigation and chemigation, data-driven smart farming through the Internet of Everything (IoE), and supply-chain analytics for improved farm-level operations.
Introduces readers to the evolution from conventional analytical approaches to large-scale analytical paradigms through a stepwise, sectioned framework that supports progressive skill developmentExamines practical considerations surrounding storage architectures, multi-source datasets, scalability constraints, and cost trade-offs in agricultural computing environmentsDetails algorithm-centric workflows, including feature construction, model calibration, and comparative performance evaluation across diverse agricultural contextsShowcases a wide range of sector-specific implementations, covering crop monitoring, irrigation planning, weed control, nutrient stress identification, climate assessment, pest detection, and agri-food supply-chain operations in both advanced and resource-limited settings