Analysis of Remote Sensing Data for Evaluating Vegetation Resources
Author | : Forestry Remote Sensing Laboratory (Berkeley, Calif.) |
Publisher | : |
Total Pages | : 192 |
Release | : 1970 |
Genre | : Forests and forestry |
ISBN | : |
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Author | : Forestry Remote Sensing Laboratory (Berkeley, Calif.) |
Publisher | : |
Total Pages | : 192 |
Release | : 1970 |
Genre | : Forests and forestry |
ISBN | : |
Author | : University of California at Berkeley. Forestry Remote Sensing Laboratory |
Publisher | : |
Total Pages | : 197 |
Release | : 1971 |
Genre | : |
ISBN | : |
Author | : Forestry Remote Sensing Laboratory (Berkeley, Calif.) |
Publisher | : |
Total Pages | : 266 |
Release | : 1972 |
Genre | : Forests and forestry |
ISBN | : |
Author | : University of California, Berkeley. School of Forestry and Construction. Forestry Remote Sensing Laboratory |
Publisher | : |
Total Pages | : 197 |
Release | : 1971 |
Genre | : Forests and forestry |
ISBN | : |
Author | : Robert N. Colwell |
Publisher | : |
Total Pages | : 230 |
Release | : 1969 |
Genre | : Aerial photography in forestry |
ISBN | : |
Author | : University of California. Forestry Remote Sensing Laboratory |
Publisher | : |
Total Pages | : 266 |
Release | : 1972 |
Genre | : Forest surveys |
ISBN | : |
Author | : Robert N. Colwell |
Publisher | : |
Total Pages | : 207 |
Release | : 1969 |
Genre | : Forests and forestry |
ISBN | : |
Author | : Andrew Skidmore |
Publisher | : CRC Press |
Total Pages | : 268 |
Release | : 2017-08-11 |
Genre | : Technology & Engineering |
ISBN | : 0203302214 |
Most government agencies and private companies are investing significant resources in the production and use of geographical data. The capabilities of Geographical Information Systems (GIS) for data analysis are also improving, to the extent that the potential performance of GIS software and the data available for analysis outstrip the abilities of
Author | : Marcelo de Carvalho Alves |
Publisher | : CRC Press |
Total Pages | : 537 |
Release | : 2023-06-30 |
Genre | : Technology & Engineering |
ISBN | : 100089536X |
This new textbook on remote sensing and digital image processing of natural resources includes numerous, practical problem-solving exercises and applications of sensors and satellite systems using remote sensing data collection resources, and emphasizes the free and open-source platform R. It explains basic concepts of remote sensing and multidisciplinary applications using R language and R packages, by engaging students in learning theory through hands-on, real-life projects. All chapters are structured with learning objectives, computation, questions, solved exercises, resources, and research suggestions. Features Explains the theory of passive and active remote sensing and its applications in water, soil, vegetation, and atmosphere. Covers data analysis in the free and open-source R platform, which makes remote sensing accessible to anyone with a computer. Includes case studies from different environments with free software algorithms and an R toolset for active learning and a learn-by-doing approach. Provides hands-on exercises at the end of each chapter and encourages readers to understand the potential and the limitations of the environments, remote sensing targets, and process. Explores current trends and developments in remote sensing in homework assignments with data to further explore the use of free multispectral remote sensing data, including very high spatial resolution data sources for target recognition with image processing techniques. While the focus of the book is on environmental and agriculture engineering, it can be applied widely to a variety of subjects such as physical, natural, and social sciences. Students in upper-level undergraduate or graduate programs, taking courses in remote sensing, geoprocessing, civil and environmental engineering, geosciences, environmental sciences, electrical engineering, biology, and hydrology will also benefit from the learning objectives in the book. Professionals who use remote sensing and digital processing will also find this text enlightening.
Author | : Yuhong He |
Publisher | : CRC Press |
Total Pages | : 381 |
Release | : 2018-06-27 |
Genre | : Technology & Engineering |
ISBN | : 0429893000 |
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.