Remote Sensing provides information on how remote sensing relates to the natural resources inventory, management, and monitoring, as well as environmental concerns.
Imagine yourself as a military officer in a conflict zone trying to identify locations of weapons caches supporting road-side bomb attacks on your country's troops.
Every amateur astronomer has at least heard of the many different catalogs of deep-sky objects; the most well known are the Messier, the Caldwell, the Herschel, and the NGC.
Until the publication of the first edition of 'Star Maps,' books were either general histories of astronomy using examples of antiquarian celestial maps as illustrations, or catalogs of celestial atlases that failed to trace the flow of sky map development over time.
Remote sensing has witnessed a renaissance as new sensor systems, data collection capabilities and image processing methodologies have expanded the technological capabilities of this science into new and important applications areas.
Modern airborne and spaceborne imaging radars, known as synthetic aperture radars (SARs), are capable of producing high-quality pictures of the earth's surface while avoiding some of the shortcomings of certain other forms of remote imaging systems.
Deep Learning for Multi-Sensor Earth Observation addresses the need for transformative Deep Learning techniques to navigate the complexity of multi-sensor data fusion.
This comprehensive handbook covers Geospatial Artificial Intelligence (GeoAI), which is the integration of geospatial studies and AI machine (deep) learning and knowledge graph technologies.
Hyperspectral Imaging: Techniques for Spectral Detection and Classification is an outgrowth of the research conducted over the years in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County.
Methods and Materials for Remote Sensing: Infrared Photo-Detectors, Radiometers and Arrays presents the basic principles and the guidelines for the design of IR and microwave radiometers intended for the detection of weak electromagnetic signals in a noisy background.
Statistical Processing Techniques for Noisy Images presents a statistical framework to design algorithms for target detection, tracking, segmentation and classification (identification).
Top space experts from around the world have collaborated to produce this comprehensive, authoritative, and clearly illustrated reference guide to the fast growing, multi-billion dollar field of satellite applications and space communications.
Land Remote Sensing and Global Environmental Change: The Science of ASTER and MODIS is an edited compendium of contributions dealing with ASTER and MODIS satellite sensors aboard NASA's Terra and Aqua platforms launched as part of the Earth Observing System fleet in 1999 and 2002 respectively.
Earth Observation interacts with space, remote sensing, communication, and information technologies, and plays an increasingly significant role in Earth related scientific studies, resource management, homeland security, topographic mapping, and development of a healthy, sustainable environment and community.
From officially sanctioned, high-tech operations to budget spy cameras and cell phone video, this updated and expanded edition of a bestselling handbook reflects the rapid and significant growth of the surveillance industry.
This book presents the fundamentals of polarimetric radar remote sensing through understanding wave scattering and propagation in geophysical media filled with hydrometers and other objects.
Because prevailing atmospheric/troposcopic conditions greatly influence radio wave propagation above 10 GHz, the unguided propagation of microwaves in the neutral atmosphere can directly impact many vital applications in science and engineering.
Understand the current concept of wetland and methods for identifying, describing, classifying, and delineating wetlands in the United States with Wetland Indicators - capturing the current state of science's role in wetland recognition and mapping.
Rip Currents: Beach Safety, Physical Oceanography, and Wave Modeling is the culmination of research from over 100 coastal scientists, engineers, forecast meteorologists, lifeguard chiefs, and other practitioners from around the world who participated in the 1st International Rip Current Symposium.
Describing a field that has been transformed by the recent availability of data from a new generation of space and airborne systems, the authors offer a synthetic geometrical approach to the description of synthetic aperture radar, one that addresses physicists, radar specialists, as well as experts in image processing.
This book discusses machine learning algorithms, such as artificial neural networks of different architectures, statistical learning theory, and Support Vector Machines used for the classification and mapping of spatially distributed data.
Through-the-wall radar imaging (TWRI) allows police, fire and rescue personnel, first responders, and defense forces to detect, identify, classify, and track the whereabouts of humans and moving objects.
As coastal environments around the world face unprecedented natural and anthropogenic threats, advancements in the technologies that support geospatial data acquisition, imaging, and computing have profoundly enhanced monitoring capabilities in coastal studies.
The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed.
