REMOTE SENSING – ADVANCED TECHNIQUES AND PLATFORMS Edited by Boris Escalante-Ramírez Remote Sensing – Advanced Techniques and Platforms Edited by Boris Escalante-Ramírez Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2012 InTech All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. As for readers, this license allows users to download, copy and build upon published chapters even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Dragana Manestar Technical Editor Miroslav Tadic Cover Designer InTech Design Team First published June, 2012 Printed in Croatia A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechopen.com Remote Sensing – Advanced Techniques and Platforms, Edited by Boris Escalante-Ramírez p. cm. ISBN 978-953-51-0652-4 Contents Preface IX Section 1 Analysis Techniques 1 Chapter 1 Characterizing Forest Structure by Means of Remote Sensing: A Review 3 Hooman Latifi Chapter 2 Fusion of Optical and Thermal Imagery and LiDAR Data for Application to 3-D Urban Environment and Structure Monitoring 29 Anna Brook, Marijke Vandewal and Eyal Ben-Dor Chapter 3 Statistical Properties of Surface Slopes via Remote Sensing 51 Josué Álvarez-Borrego and Beatriz Martín-Atienza Chapter 4 Classification of Pre-Filtered Multichannel Remote Sensing Images 75 Vladimir Lukin, Nikolay Ponomarenko, Dmitriy Fevralev, Benoit Vozel, Kacem Chehdi and Andriy Kurekin Chapter 5 Estimation of the Separable MGMRF Parameters for Thematic Classification 99 Rolando D. Navarro, Jr., Joselito C. Magadia and Enrico C. Paringit Chapter 6 Low Rate High Frequency Data Transmission from Very Remote Sensors 123 Pau Bergada, RosaMa Alsina-Pages, Carles Vilella and Joan Ramon Regué Chapter 7 A Contribution to the Reduction of Radiometric Miscalibration of Pushbroom Sensors 151 Christian Rogaß, Daniel Spengler, Mathias Bochow, Karl Segl, Angela Lausch, Daniel Doktor, Sigrid Roessner, Robert Behling, Hans-Ulrich Wetzel, Katia Urata, Andreas Hueni and Hermann Kaufmann VI Contents Chapter 8 Differential Absorption Microwave Radar Measurements for Remote Sensing of Barometric Pressure 171 Roland Lawrence, Bin Lin, Steve Harrah and Qilong Min Chapter 9 Energy Efficient Data Acquistion in Wireless Sensor Network 197 Ken C.K. Lee, Mao Ye and Wang-Chien Lee Chapter 10 Three-Dimensional Lineament Visualization Using Fuzzy B-Spline Algorithm from Multispectral Satellite Data 213 Maged Marghany Section 2 Sensors and Platforms 233 Chapter 11 COMS, the New Eyes in the Sky for Geostationary Remote Sensing 235 Han-Dol Kim, Gm-Sil Kang, Do-Kyung Lee, Kyoung-Wook Jin, Seok-Bae Seo, Hyun-Jong Oh, Joo-Hyung Ryu, Herve Lambert, Ivan Laine, Philippe Meyer, Pierre Coste and Jean-Louis Duquesne Chapter 12 Hyperspectral Remote Sensing – Using Low Flying Aircraft and Small Vessels in Coastal Littoral Areas 269 Charles R. Bostater, Jr., Gaelle Coppin and Florian Levaux Chapter 13 CSIR – NLC Mobile LIDAR for Atmospheric Remote Sensing 289 Sivakumar Venkataraman Chapter 14 Active Remote Sensing: Lidar SNR Improvements 313 Yasser Hassebo Chapter 15 Smart Station for Data Reception of the Earth Remote Sensing 341 Mykhaylo Palamar Chapter 16 Atmospheric Propagation of Terahertz Radiation 371 Jianquan Yao, Ran Wang, Haixia Cui and Jingli Wang Chapter 17 Road Feature Extraction from High Resolution Aerial Images Upon Rural Regions Based on Multi-Resolution Image Analysis and Gabor Filters 387 Hang Jin, Marc Miska, Edward Chung, Maoxun Li and Yanming Feng Chapter 18 Hardware Implementation of a Real-Time Image Data Compression for Satellite Remote Sensing 415 Albert Lin Contents VII Chapter 19 Progress Research on Wireless Communication Systems for Underground Mine Sensors 429 Larbi Talbi, Ismail Ben Mabrouk and Mourad Nedil Chapter 20 Cold Gas Propulsion System – An Ideal Choice for Remote Sensing Small Satellites 447 Assad Anis Preface Nowadays it is hard to find areas of human activity and development that have not profited from or contributed to remote sensing. Natural, physical and social activities find in remote sensing a common ground for interaction and development. From the end-user point of view, Earth science, geography, planning, resource management, public policy design, environmental studies, and health, are some of the areas whose recent development has been triggered and motivated by remote sensing. From the technological point of view, remote sensing would not be possible without the advancement of basic as well as applied research in areas like physics, space technology, telecommunications, computer science and engineering. This dual conception of remote sensing brought us to the idea of preparing two different books. The present one is devoted to new techniques for data processing, sensors and platforms, while the accompanying book is meant to display recent advances in remote sensing applications. From a strict perspective, remote sensing consists of collecting data from an object or phenomenon without making physical contact. In practice, most of the time we refer to satellite or aircraft-mounted sensors that use some sort of electromagnetic radiation to gather geospatial information from land, oceans and atmosphere. The growing diversity of human activity has motivated the design of new sensors and platforms as well as the development of new methodologies that can process the enormous amount of information that is being generated daily. Collected information, however, represents only a footprint of the object or the phenomenon we are interested in. In order for the end-user to be able to interpret and use this information, the data has to be processed so that it does not longer represent a digital number, but a physical- related value. Among the tasks that usually must be carried out on this data, we find several numerical corrections and calibrations: geometrical, digital elevation, atmospheric, radiometric, etc. Moreover, depending on the end-user application, data may need to be filtered, compressed, transmitted, fused, classified, interpolated, etc. The problem is even more complex when we think of the variety of sensors and satellites that have been designed and launched. We are talking about a large diversity that includes passive or active sensors; panchromatic, multispectral or hyperspectral sensors; all of them with spatial resolutions that range from a couple of centimeters to several kilometers, to mention a few examples. In summary, different methodologies and techniques for data processing must be designed and customized according, not only to the specific application, but also to the sensor and satellite characteristics. X Preface We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas. The first part of the book is devoted to new methodologies and techniques for data processing in remote sensing. The reader will find interesting contributions in forest characterization, data fusion, surface slopes statistical properties, multichannel and Markovian classification, road feature extraction, miscalibration correction, barometric pressure measurements, wireless sensors networks and lineament visualization. The second part of the book gathers chapters related to new sensors and platforms for remote sensing, including the new COMS satellite, hyperspectral remote sensing, mobile LIDAR for atmospheric remote sensing, SNR improvements in LIDAR, a smart station for data reception, terahertz radiation propagation, HF data transmission for very remote sensing, hardware image compression, wireless communications for underground sensors, and cold gas propulsion for remote sensing satellites. I wish to express my deepest gratitude to all authors who have contributed to this book. Without their strong commitment this book would not have become such a valuable piece of information. I am also thankful to InTech editorial team who has provided the opportunity to publish this book. Boris Escalante-Ramírez National Autonomous University of México, Faculty of Engineering, Mexico City, Mexico [...]... site in Karlsruhe, Germany Characterizing Forest Structure by Means of Remote Sensing: A Review 7 Characterizing Forest Structure by Means of Remote Sensing: A Review 8 6 Remote Sensing – Advanced TechniquesWill-be-set-by-IN-TECH and Platforms 1.3 Modelling issues When the aim is to assess the forest attributes by means of remote sensing data, one may note, again, the importance of estimating forest... intermediate silvicultural practices), and modelling rare and ecologically-valuable populations 22 20 Remote Sensing – Advanced TechniquesWill-be-set-by-IN-TECH and Platforms 4 References Acker, S., Sabin, T., Ganio, L & McKee, W (1998) Development of old-growth structure and timber volume growth trends in maturing douglas-fir stands, Forest Ecology and Management 104: 26 5– 280 BMU (2009) National biomass... application of 3D topographic remote sensing for forest monitoring 2.3 Combining LiDAR and optical data for modelling As explained earlier, the application of ALS-extracted metrics (height and intensity features) has been validated as a being helpful and thus required for most practices regarding forest 18 16 Remote Sensing – Advanced TechniquesWill-be-set-by-IN-TECH and Platforms inventory This is because... Geoscience and Remote Sensing Symposium, 2002 IGARSS ’02 Vol 6,, pp 310 8–3 110 Franco-Lopez, H., Ek, A R & Bauer, M E (2001) Estimation and mapping of forest stand density, volume, and cover type using the k-nearest neighbours method, Remote Sensing of Environment 77: 251?274 Franklin, J (1986) Thematic mapper analysis of coniferous forest structure and composition, International Journal of Remote Sensing. .. monitoring processes, where the assessment of environmental processes has been enabled to be carried out by means of advanced methods such as intensive modelling and simulations 6 4 Remote Sensing – Advanced TechniquesWill-be-set-by-IN-TECH and Platforms (Guo, 2005) As described above, assessment and mapping of forest attributes have followed a similar progress as an essential prerequisite for forest management... Non-parametric and semiparametric models, Springer, New York 24 22 Remote Sensing – Advanced TechniquesWill-be-set-by-IN-TECH and Platforms Hudak, A., Crookston, N., Evans, J., Hall, D & Falkowski, M (2008) Nearest neighbour imputation of species-level, plot-scale forest structure attributes from lidar data, Remote Sensing of Environment 112: 223 2–2 245 Hudak, A T., Crookston, N L., Evans, J S., Falkowski,... Journal of Remote Sensing 29(5): 133 9–1 336 Imhoff, M (1995) Radar backscatter and biomass saturation: ramifications for global biomass inventory, IEEE Transactions on Geoscience and Remote Sensing 33(2): 51 0–5 18 Iverson, L R., Cook, E A & Graham, R L (1994) Regional forest cover estimation via remote sensing: the calibration center concept, Landscape Ecology 9(3): 15 9–1 74 Jochem, A., Hollaus, M., Rutzinger,... 1986, Hyytiälä, Finland Research Notes No 19 Department of Forest Mensuration and Management, University of Helsinki Kimmins, J (1996) Forest ecology, Macmillan Inc., New York Koch, B (2010) Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment, ISPRS Journal of Photogrammetry and Remote Sensing 65: 58 1–5 90 Koch, B., Straub,... Proceedings of the fifth Annual Forest Inventory and Analysis Symposium, pp 6 1–6 8 Finley, A O & McRoberts, R E (2008) Efficient k-nearest neighbour searches for multi-source forest attribute mapping, Remote Sensing of Environment 112: 220 3–2 211 Characterizing Forest Structure Sensing: A Reviewof Remote Sensing: A Review Characterizing Forest Structure by Means of Remote by Means 23 21 Foster, J., Kingdon,... the remote sensing society was carried out by (Tomppo et al., 2009), in which TM-derived spectral features were used to predict site fertility, species dominance and coniferous/deciduous dominance as categorical responses across Characterizing Forest Structure Sensing: A Reviewof Remote Sensing: A Review Characterizing Forest Structure by Means of Remote by Means 15 13 selected test sites in Finland and . REMOTE SENSING – ADVANCED TECHNIQUES AND PLATFORMS Edited by Boris Escalante-Ramírez Remote Sensing – Advanced Techniques and Platforms Edited by. descriptor of stand structure, as it can mainly characterize the older and 4 Remote Sensing – Advanced Techniques and Platforms Characterizing Forest Structure by Means of Remote Sensing: A Review. waveform LiDAR system (Lim et al., 2003). 6 Remote Sensing – Advanced Techniques and Platforms Characterizing Forest Structure by Means of Remote Sensing: A Review Fig. 1. An example of false