Analysis Of The Global Industry For Commercial High Resolution Optical Remote Sensing From Space

High spatial resolution remote sensing is an area of considerable current interest and builds on developments in object-based image analysis, commercial high-resolution satellite sensors, and UAVs. It captures more details through high and very high resolution images (10 to 100 cm/pixel). This unprecedented level of detail offers the potential extraction of a range of multi-resource management information, such as precision farming, invasive and endangered vegetative species delineation, forest gap sizes and distribution, locations of highly valued habitats, or sub-canopy topographic information. Information extracted in high spatial remote sensing data right after a devastating earthquake can help assess the damage to roads and buildings and aid in emergency planning for contact and evacuation. To effectively utilize information contained in high spatial resolution imagery, High Spatial Resolution Remote Sensing: Data, Analysis, and Applications addresses some key questions: What are the challenges of using new sensors and new platforms? What are the cutting-edge methods for fine-level information extraction from high spatial resolution images? How can high spatial resolution data improve the quantification and characterization of physical-environmental or human patterns and processes? The answers are built in three separate parts: (1) data acquisition and preprocessing, (2) algorithms and techniques, and (3) case studies and applications. They discuss the opportunities and challenges of using new sensors and platforms and high spatial resolution remote sensing data and recent developments with a focus on UAVs. This work addresses the issues related to high spatial image processing and introduces cutting-edge methods, summarizes state-of-the-art high spatial resolution applications, and demonstrates how high spatial resolution remote sensing can support the extraction of detailed information needed in different systems. Using various high spatial resolution data, the third part of this book covers a range of unique applications, from grasslands to wetlands, karst areas, and cherry orchard trees.

Remote sensing and geospatial data processing are rapidly evolving and increasingly important fields with widespread applications. In this monograph, Glackin and Peltzer trace the evolution of remote sensing satellites and their instruments and geospatial data processing, document the state of the art, and present key trends emerging for the next decade. The authors emphasize the increasing commercialization and international expansion of the field, particularly in the field of imaging satellites and the use of geographic information systems to make remote sensing data more accessible.

David Stevens Space-based information, which includes earth observation data, is increasingly becoming an integral part of our lives. We have been relying for decades on data obtained from meteorological satellites for updates on the weather and to monitor weather-related natural disasters such as hurricanes. We now count on our personal satellite-based navigation systems to guide us to the nearest Starbucks Coffee and use web-based applications such as Google Earth and Microsoft Virtual Earth to study the area of places we will or would like to visit. At the same time, satellite-based technologies have experienced impressive growth in recent years with an increase in the number of available sensors, an increase in spatial, temporal and spectral resolutions, an increase in the availability of radar satellites such as Terrasar-X and ALOS, and the launching of specific constellations such as the Disaster Monitoring Constellation (DMC), COSMO- SkyMed (COnstellation of small Satellites for the Mediterranean basin Observation) and RapidEye. Even more recent are the initiatives being set-up to ensure that space-based information is being accessed and used by decision makers, such as Sentinel Asia for the Asia and Pacific region and SERVIR for the Latin America and Caribbean region.

Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data. Challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, pattern classification and target recognition, visualization of high dimensional imagery.

Remote Sensing is of paramount importance for Earth Observation to monitor and analyze the Earth’s vital signs. In this Special Issue are reported the latest research results involving active optical remote sensing instruments, both from ground-based to satellite platforms, that are involved in analyzing the vertical and horizontal aerosol and cloud distribution, other than their geometrical, optical and microphysical properties. Those active optical remote sensing techniques are also very useful in determining pollutant dispersion and the dynamics inside the boundary layer. The published studies put in evidence the hidden mechanisms on how pollution from the source is advected transnationally in other countries and the interaction with local meteorology.

Remote Sensing provides information on how remote sensing relates to the natural resources inventory, management, and monitoring, as well as environmental concerns. It explains the role of this new technology in current global challenges. "Remote Sensing" will discuss remotely sensed data application payloads and platforms, along with the methodologies involving image processing techniques as applied to remotely sensed data. This title provides information on image classification techniques and image registration, data integration, and data fusion techniques. How this technology applies to natural resources and environmental concerns will also be discussed.

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.