Scientific Papers - Earth Sciences

Browse by year:
2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999

2006

AKKARTAL, A., B. GÖRAL, Z. UÇA AVCI and F. SUNAR: The Need of an Operational Flood Monitoring System in Turkey: A Case Study - The Maritsa River In: Proceedings of the RSPSoc Annual Conference 2006, Newcastle, UK. September 12 – 14, 2006.

ARGIALAS, D. and A. TZOTSOS (2006): Automatic Extraction of Physiographic Features and Alluvial Fans in Nevada, USA from Digital Elevation Models and Satellite Imagery through Multiresolution Segmentation and Object-oriented Classification In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

BARLOW, J., S. FRANKLIN and Y. MARTIN (2006): High Spatial Resolution Imagery, DEM Derivates, and Image Segmentation for the Detection of Mass Wasting Processes. Photogrammetric Engineering & Remote Sensing. Vol. 72, No. 6, June 2006, pp. 687-692.

BROOKS, C.N., D.L. SCHAUB, R.B. POWELL, N.H. FRENCH and R. SHUCHMAN (2006): Multi-temporal and multi-platform agricultural land cover classification in Southeastern Michigan  In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

BROWN, S., D. VANDERZANDEN, J. BARBER and G. BASSETTE (2006): Mapping Non-Forest Vegetation Using Fuzzy Logic with High Resolution Aerial Imagery, SPOT 5, and Landsat 7 ETM+ on the Helena National Forest, Montana. Eleventh Biennial USDA Forest Service Remote Sensing Applications Conference. April 24-28, 2006. Salt Lake City, Utah, USA.

BUEHLER Y. A., KELLENBERGER T. W., SMALL, D., ITTEN K. I. (2006): Rapid mapping with remote sensing data during flooding 2005 in Switzerland by object-based methods – a case study In: Geo-Environment & Landsacape Evolution II, WIT Transactions on Ecology and the Environment Vol 89 pp. 391 - 400

CHAMPAGNE, C., H. MCNAIR an J. SHANG (2006): An Object-Oriented Approach to Land Use Mapping in the Canadian Prairies. Eleventh Biennial USDA Forest Service Remote Sensing Applications Conference. April 24-28, 2006. Salt Lake City, Utah, USA.

CHUBEY, M., S. FRANKLIN and M. WULDER (2006): Object-based Analysis of Ikonos-2 Imagery for Extraction of Forest Inventory Parameters PE & RS, April 2006.

DAMLA UÇA AVCI, BAR GÖRAL, AYDA AKKARTAL and FILIZ SUNAR (2006): Flood Monitoring Using Multi-Temporal Radarsat-1 Images In: Proceedings of the RSPSoc Annual Conference 2006, Newcastle, UK. September 12 – 14, 2006.

DESCLÉE, B., P.BOGAERT and P. DEFOURNY (2006): Forest change detection by statistical object-based method. Remote Sensing of Environment, 102, 1-11

EHLERS, M., U. MICHEL, G. BOHMANN and D. TOMOWSKI (2006): Decision based data fusion techniques for the analysis of settlement areas from multisensor satellite data Despite the population stagnation in many industrialized countries, we experience a steady sprawl of urban/suburban space. This fact is based on the migration out of the inner cities, increasing demands on living space, and set-aside of land for commercial developments. In developing countries, this urban growth occurs at dramatic speeds and costs to the environment. Often, planning offices have no or only outdated information about new settlements and their composition in their jurisdiction. The University of Osnabrueck’s Institute for Geo-informatics and Remote Sensing has developed a hierarchical method for decision based fusion to automate the delineation of new residential and commercial built-up area. The procedure is based on fusion techniques at the decision level using differently weighted parameters for texture, shape, and spectral characteristics. It was applied to multisensor satellite images from sensors such as SPOT-5, Kompsat 1, Landsat ETM, and Aster. Using this method, accuracies exceeding 90% could be achieved. (In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006).

Frohn RC : The use of landscape pattern metrics in remote sensing image classification This letter demonstrates the utility of landscape pattern metrics for increasing classification accuracy of land cover. Three examples are provided for the use of a landscape shape complexity measure in remote sensing segmentation-based classification schemes. The examples include: (1) classification of thaw lakes on the North Slope of Alaska; (2) classification of drained basins in Alaska; and (3) classification of natural vs. anthropogenic pastures in Bolivia. In these examples the Square Pixel Metric (SqP) was applied to objects created from image segmentation to distinguish between categories that had similar spectral properties but different shape complexity values. (In: International Journal of Remote Sensing, Volume 27, Issue May 10, 2006 , pages 2025 – 2032)

FROHN, R.C. (2006): The use of landscape pattern metrics in remote sensing image classification International Journal of Remote Sensing Volume 27, Number 10, 2025 - 2032.

HANSEN, D., C. CURLIS and B. SIMPSON (2006): Techniques for discrimination between agriculture and similar land cover types with fuzzy logic and spectral polygon characteristics  In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

HURD, J.D., D.L. CIVCO, M.S. GILMORE, S. PRISLOE and E.H. WILSON (2006): Tidal wetland classification from Landsat imagery using an integrated pixel-based and object-based classification approach In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

Kellenberger T. W., Schubiger W., Itten K. (2006): Object Oriented Land Cover Mapping of the Kanchenjunga Conservation Area (KCA) in Nepal, for Sustainable Development and Use of Natural Resources In: Proc. IGARSS'06, Denver, Colorado pp. 2369 - 2372

LALIBERTE, A. (2006): Rangeland Mapping. Ease Classification with an Object-Oriented Approach and Satellite Imagery. Earth Imaging Journal, Vol. 3, No. 1, 30-32.

LALIBERTE, A., A. RANGO and E.L. FREDRICKSON (2006): Separating green and senescent vegetation in very high resolution photography using an intensity-hue-saturation transformation and object based classification In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

LATRHOP, R.G., P. MONTESANO and S. HAAG (2006): A Multi-Scale Segmentation Approach to Mapping Seagrass Habitats Using Airborne Digital Camera Imagery. Photogrammetric Engineering & Remote Sensing. Vol. 72, No. 6, June 2006, pp. 665-675.

LEWINSKI, S. (2006): Applying fused multispectral and panchromatic data of Landsat ETM+ to object oriented classification  In: Proccedings of the 26th EARSeL Symposium, New Developments and Challenges in Remote SensingMay 29-June 2, 2006, Warsaw, Poland.

LEWINSKI, S. (2006): Applying Fused Multispectral and Panchromatic Data of Landsat ETM+ to Object-Oriented Classification Poster at the 26th EARSeL Symposium, New Developments and Challenges in Remote SensingMay 29-June 2, 2006, Warsaw, Poland.

LIE, Z., C. RAMIREZ, L. FISHER and J. DONNEGAN (2006): Mapping Tropical Vegetation Using Very High Resolution Satellite Imagery. Eleventh Biennial USDA Forest Service Remote Sensing Applications Conference. April 24-28, 2006. Salt Lake City, Utah, USA.

MATIKAINEN, L., J. HYYPPÄ and M.E. ENGDAHL (2006): Mapping Built-up Areas from Multitemporal Interferometric SAR Images - A Segment-based Approach. Photogrammetric Engineering & Remote Sensing. Vol. 72, No. 6, June 2006, pp. 701-714.

MCGANN, M., S. GOODMAN, R. KOKALY and A. MCADAMDS (2006):  Advanced Remote Sensing Technologies for Monitoring Postburn Vegetation Trends and Conditions. Eleventh Biennial USDA Forest Service Remote Sensing Applications Conference. April 24-28, 2006. Salt Lake City, Utah, USA.

McGlynn I, Okin G: Characterization of shrub distribution using high spatial resolution remote sensing: Ecosystem implications for a former Chihuahuan Desert grassland Patchiness is often considered a defining quality of ecosystems in and and semiarid regions. The spatial distribution of vegetation patches and soil nutrients coupled with wind and water erosion as well as biotic processes are believed to have an influence on land degradation. A geostatistical measure of spatial "connectivity" is presented to directly measure the size of patches in the landscape from a raster data set. Connectivity is defined as the probability that adjacent pixels belong to the same type of patch. Connectivity allows the size distribution of erodible patches to be quantified from a remote sensing image or field measurement, or specified for the purposes of modeling. Applied to high-resolution remote sensing imagery in the Jornada del Muerto Basin in New Mexico, the spatial distribution of plants indicates the current state of grassland-to-shrubland transition in addition to processes of degradation in this former grassland. Shrub encroachment is clearly evident from decreased intershrub patch size in coppice dunes of 27.8 m relative to shrublands of 65.2 in and grassland spacing of 118.9 in. Shrub patches remain a consistent 2-4m diameter regardless of the development of bush encroachment. A strong SW-NE duneland orientation correlates with the prevailing wind direction and suggests a strong aeolian control of surface geomorphology. With appropriate data sets and classification, potential applications of the connectivity method extend beyond vegetation dynamics, including mineralogy mapping, preserve planning, habitat fragmentation, pore spacing in surface hydrology, and microbial community dynamics. (In: Remote Sensing of Environment 101, 2006, pp 554–566)

MELLIN, T. (2006): Classification and Data Analysis Methods for Mapping Existing Vegetation at the Midscale in the Forest Service Southwestern Region. Eleventh Biennial USDA Forest Service Remote Sensing Applications Conference. April 24-28, 2006. Salt Lake City, Utah, USA.

MITRI, G.H. and I.Z. GITAS (200&): Fire type mapping using object-based classification of Ikonos imagery In: International Journal ofWildland Fire, 2006, 15, 457–462

MOELLER, M.S. and T. BLASCHKE (2006): A new index for the differentiation of vegetation fractions in urban neighbourhoods based on satellite imagery  In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

NOBREGA, R., C. O'HARA, V. VIJAYARAJ, G. OLSON, S. KIM, J. A. QUINTANILHA and M. BARROS (2006): Extracting and classifying bare soil erosion risk areas in a urban basin using object-oriented technologies, high resolution imagery and elevation data. GIS and Water Resources IV AWRA Spring Specialty Conference. Houston , Texas . May 8 - 10. 2006

PATENAUDE, G., I. WOODHOUSE, D. KNOX, D. MCINERNEY and J. SUAREZ-MINGUEZ (2006): Remote Sensing for UK Public Forests Management. Eleventh Biennial USDA Forest Service Remote Sensing Applications Conference. April 24-28, 2006. Salt Lake City, Utah, USA.

Quartel S, Addink EA, Ruessink BG: Object-oriented extraction of beach morphology from video images The ARGUS system is a shore-based, optical video system offering a suitable remote sensing technique for the purpose of longterm, high-resolution monitoring of coastal morphodynamics. Ten-minute time-exposure (timex) images obtained by the ARGUS cameras during low tide show the intertidal morphology (bars, troughs and rips) by the differences between water, wet sand and dry sand, where dry sand represents bars, and wet sand and water represent troughs and rips. A semi-automatic object-oriented algorithm was developed for classification of intertidal beach in low-tide video images and was tested on 13 low-tide ARGUS images collected at Noordwijk aan Zee, The Netherlands. Because of the strong relation between the visual observations and objectoriented image analysis, the ARGUS images are subdivided in small homogeneous areas (i.e. objects) by segmentation. Maximum likelihood classification creates a model for each day using a random selection of the objects, which are manually labelled, and their accompanying variables. Of the three classes, class wet sand had a classification fit of 43.4% when compared to an in situ classification; class water was correctly classified for 90.1% and dry sand could be classified best (92.8%). By combining their cross-shore position and their classification, objects can be directly linked with the respective morphological features. (In: International Journal of Applied Earth Observation and Geoinformation, volume 8, issue 4, December 2006, pp: 256-269)

SHIBA, M. and A. ITAYA: Using eCognition for improved forest management and monitoring systems in precision forestry.  In: Ackerman PA, Längin DW & Antonides MC (Editors) 2006: Precision Forestry in plantations, semi-natural and natural forests. Proceedings of the International Precision Forestry Symposium, Stellenbosch University, South Africa, March 2006. Stellenbosch University, Stellenbosch.

STEFANACCI, J. (2006): Automated stand delineation and fire fuels mapping  In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

Troy A, Zhou W: Creating a parcel level database from high resolution imagery State and local planning agencies are increasingly acquiring high resolution, multi-spectral aerial or satellite imagery. While these images make a good backdrop and are interesting to look at, to be of real use in planning something needs to be done with them. Specifically, images need to be processed in order to be used in a Geographic Information System (GIS), allowing for queries, searches, overlay analysis, or database creation. In this article we discuss a new approach that allows planners to get the most out of high resolution imagery. In this article, we show how new technologies can be used to automate the process of “extracting” information from imagery and, based on that, map out a city’s resources and liabilities at a very fine scale. We show how this approach was used to automate the process of mapping: 1) building footprints; 2) roads, sidewalks, parking lots and other impervious surfaces; 3) vegetation, down to the level of individual trees and lawns, and 4)”multi-layer phenomena,” which are, for instance, areas where trees overhang roads. We also show how this information can then be summarized at a number of levels, from a planning district on to an individual parcel. (In: American Planning Association InfoText (the quarterly newsletter of the Information Technology Division of the APA), fall 2006, issue 87).

TZOTSOS, A. and D. ARGIALAS (2006): MSEG: A generic region-based multi-scale image segmentation algorithm for remote sensing imagery. In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

VAN AARDT, J. and R.H. WYNNE (2006): Segment-based forest volume-by-type modelling using small footprint lidar height distributions In: Ackerman PA, Längin DW & Antonides MC (Editors) 2006: Precision Forestry in plantations, semi-natural and natural forests. Proceedings of the International Precision Forestry Symposium, Stellenbosch University, South Africa, March 2006. Stellenbosch University, Stellenbosch.

WARNICK, R. (2006): Texture Metric Comparison of Manual Forest Stand Delineation and Image Segmentation. Eleventh Biennial USDA Forest Service Remote Sensing Applications Conference. April 24-28, 2006. Salt Lake City, Utah, USA.

WOOD, E.C., B.K. WYLIE, J.F. BROWN, D.J. MEYER and S. MAXWELL (2006): Range condition as input to water quality monitoring in the northern plains.  In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

YAN, G., J.F. MAS, B.H.P. MAATHUIS, Z. XIANGMIN, P.M. VAN DIJK (2006): Comparison of pixel-based and object-oriented image classification approaches - a case study in a coal fire area, Wuda, Inner Mongolia, China. International Journal of Remote Sensing. Volume 27, Number 18 / 20 September 2006, 4039 - 4055.

YUAN, F. (2006): Mapping impervious surface area using high resolution imagery: A comparison of object-based and per pixel classification. In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

ZHANG, Q. and I. COULOIGNER (2006): Automated road network extraction from high resolution multi-spectral imagery.  In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

ZHANG, Y. and T. MAXWELL (2006): A fuzzy logic approach to supervised segmentation for object-oriented classification.  In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

ZHOU, Y. and Y.Q. WANG (2006): Extraction of impervious surface area using orthophotos in Rhode Island. In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

ZHU, H. and F.L. SCARPACE (2006): Aerial image matching incorporating object recognition. In: Proceedings of ASPRS 2006 Annual Conference, Reno, Nevada; May 1-5, 2006.

Disclaimer: The materials referred to on this web page are provided by Definiens as a service to our customers and may be used for informational purposes only.No part of these documents may be reproduced by any method whatsoever without the prior written consent of the individual author. Whilst every care is taken to ensure the accuracy of the information contained on this site, the opinions, analysis and facts stated are based on information and sources which, while we believe them to be reliable, are not guaranteed by Definiens. In particular, it should not be relied upon as the sole source of reference in relation to the subject matter.