Boreas Te-18 Landsat TM Maximum Likelihood Classification Image of the Ssa PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Boreas Te-18 Landsat TM Maximum Likelihood Classification Image of the Ssa PDF full book. Access full book title Boreas Te-18 Landsat TM Maximum Likelihood Classification Image of the Ssa by National Aeronautics and Space Adm Nasa. Download full books in PDF and EPUB format.
Author: National Aeronautics and Space Adm Nasa Publisher: Independently Published ISBN: 9781724099853 Category : Languages : en Pages : 32
Book Description
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep- 1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC). Hall, Forrest G. (Editor) and Knapp, David Goddard Space Flight Center NASA/TM-2000-209891/VOL175, Rept-2000-03136-0/VOL175, NAS 1.15:209891/VOL175
Author: National Aeronautics and Space Adm Nasa Publisher: Independently Published ISBN: 9781724099853 Category : Languages : en Pages : 32
Book Description
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep- 1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC). Hall, Forrest G. (Editor) and Knapp, David Goddard Space Flight Center NASA/TM-2000-209891/VOL175, Rept-2000-03136-0/VOL175, NAS 1.15:209891/VOL175
Author: National Aeronautics and Space Administration (NASA) Publisher: Createspace Independent Publishing Platform ISBN: 9781721239504 Category : Languages : en Pages : 32
Book Description
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 20-Aug-1988 was used to derive this classification. A standard supervised maximum likelihood classification approach was used to produce this classification. The data are provided in a binary image format file. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC). Hall, Forrest G. (Editor) and Knapp, David Goddard Space Flight Center NASA/TM-2000-209891/VOL172, Rept-2000-03136-0/VOL172, NAS 1.15:209891/VOL172
Author: Ph.D., Prasad S. Thenkabail Publisher: CRC Press ISBN: 1482217872 Category : Technology & Engineering Languages : en Pages : 698
Book Description
A volume in the Remote Sensing Handbook series, Remotely Sensed Data Characterization, Classification, and Accuracies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Land Resources Monitoring, Modeling, and Mapping with Remote Sensing, and Remote Sensing of
Author: Prasad Thenkabail Publisher: CRC Press ISBN: 1482282674 Category : Technology & Engineering Languages : en Pages : 2262
Book Description
A volume in the three-volume Remote Sensing Handbook series, Remote Sensing of Water Resources, Disasters, and Urban Studies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data Characterization, Classification, and Accuracies, and Land Reso
Author: Prasad S. Thenkabail Publisher: CRC Press ISBN: 1040194338 Category : Technology & Engineering Languages : en Pages : 507
Book Description
Volume II of the Six Volume Remote Sensing Handbook, Second Edition, is focused on digital image processing including image classification methods in land cover and land use. It discusses object-based segmentation and pixel-based image processing algorithms, change detection techniques, and image classification for a wide array of applications including land use/land cover, croplands, urban studies, processing hyperspectral remote sensing data, thermal imagery, light detection and ranging (LiDAR), geoprocessing workflows, frontiers of GIScience, and future pathways. This thoroughly revised and updated volume draws on the expertise of a diverse array of leading international authorities in remote sensing and provides an essential resource for researchers at all levels interested in using remote sensing. It integrates discussions of remote sensing principles, data, methods, development, applications, and scientific and social context. Features Provides the most up-to-date comprehensive coverage of digital image processing. Highlights object-based image analysis (OBIA) and pixel-based classification methods and techniques of digital image processing. Demonstrates practical examples of image processing for a myriad of applications such as land use/land cover, croplands, and urban. Establishes image processing using different types of remote sensing data that includes multispectral, radar, LiDAR, thermal, and hyperspectral. Highlights change detection, geoprocessing, and GIScience. This volume is an excellent resource for the entire remote sensing and GIS community. Academics, researchers, undergraduate and graduate students, as well as practitioners, decision makers, and policymakers, will benefit from the expertise of the professionals featured in this book, and their extensive knowledge of new and emerging trends.
Author: Kumar Navulur Publisher: CRC Press ISBN: 1420043072 Category : Technology & Engineering Languages : en Pages : 206
Book Description
Bringing a fresh new perspective to remote sensing, object-based image analysis is a paradigm shift from the traditional pixel-based approach. Featuring various practical examples to provide understanding of this new modus operandi, Multispectral Image Analysis Using the Object-Oriented Paradigm reviews the current image analysis methods and demonstrates advantages to improve information extraction from imagery. This reference describes traditional image analysis techniques, introduces object-oriented technology, and discusses the benefits of object-based versus pixel-based classification. It examines the creation of object primitives using image segmentation approaches and the use of various techniques for object classification. The author covers image enhancement methods, how to use ancillary data to constrain image segmentation, and concepts of semantic grouping of objects. He concludes by addressing accuracy assessment approaches. The accompanying downloadable resources present sample data that enable the use of different approaches to problem solving. Integrating remote sensing techniques and GIS analysis, Multispectral Image Analysis Using the Object-Oriented Paradigm distills new tools to extract information from remotely sensed data.
Author: National Aeronautics and Space Adm Nasa
Author: National Aeronautics and Space Adm Nasa
Author: 
Author: 
Author: 
Author: National Aeronautics and Space Administration (NASA)
Author: Ph.D., Prasad S. Thenkabail
Author: Prasad Thenkabail
Author: Prasad S. Thenkabail
Author: 
Author: Kumar Navulur