Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. - Comprehensive overview of various practical methods and algorithms - Detailed description of the principles and procedures of the state-of-the-art algorithms - Real-world case studies open several chapters - More than 500 full-color figures and tables - Edited by top remote sensing experts with contributions from authors across the geosciences

International Journal of Advanced Remote Sensing and GIS (IJARSG, ISSN 2320 – 0243) is an open-access peer-reviewed scholarly journal publishes original research papers, reviews, case study, case reports, and methodology articles in all aspects of Remote Sensing and GIS including associated fields. This Journal commits to working for quality and transparency in its publishing by following standard Publication Ethics and Policies.

This book introduces the use of various remote sensing data such as microwave, hyperspectral and very high-resolution (VHR) satellite imagery; mapping techniques including pixel and object-based machine learning; and geostatistical modelling techniques including cellular automation, entropy and land fragmentation. Remote sensing plays a vital role in solving urban and environmental challenges at the landscape level. Globally, more than half of the urban population is facing severe environmental and social challenges, especially those relating to climate change, agricultural land encroachment, green infrastructure and environmental degradation, mobility due to rapid rural–urban transformation and anthropogenic interventions. Mapping and quantification of such threats at the landscape level are challenging for experts using traditional techniques; however, remote sensing technology provides diverse spatial data at a varying scale, volume and accessibility for mapping and modelling, and it also analyses challenges at urban and landscape levels. Together, they address challenges at urban and landscape levels to support the Sustainable Development Goals (SDGs).

The innovation in space technologies has generated a new method for observing and monitoring tsunamis from space. Most tsunami remote sensing studies focus on using classical image processing tools or conventional edge detection procedures. However, these methods do not use modern physics, applied mathematics, signal communication, remote sensing data and innovative space technologies. This book equips readers to understand how to monitor tsunamis from space with remote sensing technology art to create a better alarm warning system.

Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors’ perspective. Key Features of Volume IV: Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling. Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum. Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications. Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges. Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.

The advance in space machineries has created a novel technology for observing and monitoring the Earth from space. Most earth observation remote sensing considerations focus on using conventional image processing algorithms or classic edge detection tools. Nevertheless, these techniques do not implement modern physics, applied mathematics, signal communication, remote sensing data, and innovative space technologies. This book provides readers with methods to comprehend how to monitor coastal environments, disaster areas, and infrastructure from space with advanced talent remote sensing technology to bridge the gaps between modern space technology, image processing algorithms, mathematical models and the critical issue of the coastal and infrastructure investigations.

The first of its kind, this book reviews image processing tools and techniques including Independent Component Analysis, Mutual Information, Markov Random Field Models and Support Vector Machines. The book also explores a number of experimental examples based on a variety of remote sensors. The book will be useful to people involved in hyperspectral imaging research, as well as by remote-sensing data like geologists, hydrologists, environmental scientists, civil engineers and computer scientists.

Extreme weather and climate change aggravate the frequency and magnitude of disasters. Facing atypical and more severe events, existing early warning and response systems become inadequate both in scale and scope. Earth Observation (EO) provides today information at global, regional and even basin scales related to agrometeorological hazards. This book focuses on drought, flood, frost, landslides, and storms/cyclones and covers different applications of EO data used from prediction to mapping damages as well as recovery for each category. It explains the added value of EO technology in comparison with conventional techniques applied today through many case studies.

Re-envisioning Advances in Remote Sensing: Urbanization, Disasters and Planning aims at portraying varied advancements in remote sensing applications, particularly in the fields of urbanization, disaster management and regional planning perspectives. The book is organized into three sections of overlapping areas of research covering chief remote sensing applications. Apart from introducing the advances in remote sensing through Indian remote sensing developments, it depicts the broader themes of: urbanization and its impacts; geospatial technology for disaster management; and, remote sensing applications in models and planning. It also provides outlook to future research agenda for remote sensing. Features: • Depicts advances in remote sensing in major fields through applications of geospatial technologies. • Covers remote sensing applications in varied aspects of urbanization, urban problems and disasters. • Includes advancements in remote sensing in model building and planning perspectives. • Analyses the usage of smartphones and other digital devices in mapping urban problems and monitoring disaster risks. • Explores future agenda for remote sensing advances and its ever-widening horizon. This book would be of interest to all the researchers and graduate students pursuing studies in the fields of remote sensing, GIS, geospatial technologies, urbanizations, disaster management, regional planning, environmental sciences, natural resource management and related fields.