Innovations in Remote Sensing and Photogrammetry

Abstract

This book has its origins in the Australasian Remote Sensing and Photogrammetry conference series. The theme for the book, Innovations in Remote Sensing and Photogrammetry, encompasses a broad range of topics in geoinformation and cartography presented over 36 papers. These are characterised in four sections: data fusion techniques and their applications in environmental monitoring; synoptic monitoring and data processing; terrestrial applications of remote sensing; and marine applications of remote sensing. Color figures are an important contribution to many of these papers. Readers are directed to the eBook version of this publication for access to full color reprints of the relevant papers. The book begins with an introduction to spatial data visualization, with particular focus given to attribute uncertainty, as a critical step in enabling users to assess the suitability of the data for the intended application and to better understand the potential limitations of their data and subsequent outputs. This is important for policy-makers and natural resource managers whose decisions depend on spatial information. Consequences can be severe if data is unknowingly erroneous or misused. This paper provides a setting for the way in which we as spatial data providers and users need to think about, and share information. In addition it provides a linkage between this book and the book series, Lecture Notes in Geoinformation and Cartography, to which it belongs. The first section begins with a series of papers on remote sensing data fusion techniques and their applications in environmental monitoring. Data synthesis and integration is critical to unlocking the full potential of earth observing sensors. In the context of landcover mapping, Ali et al. explore a method of combing both active and passive imagery. They conclude more accurate land cover mapping is attainable using object-level fusion than using the pixel-level supervised process. Bunting et al. present a technique that uses textural information, derived from image filters, to be used alongside hyperspectral data for the classification of broad forest types. Poon et al. discuss the potential for QuickBird as an effective method of extracting 3D information to be used for high accuracy ground feature determination. Lee et al. calibrate the ICESat laser data with airborne Lidar to generate new data products providing information about forest height and structure. Finally Sheffield et al. describe a native woody vegetation ground data collection protocol that attempts to