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IEEE Joint International Geoscience and Remote Sensing Symposium (IGARSS) / 35th Canadian Symposium on Remote Sensing

作者： Li, Wei Wang, Shiqian Li, Jonathan Univ Waterloo Dept Geog & Environm Management Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781479957750

This paper used QuickBird high resolution image to estimate the population of the city of Waterloo, ON, Canada. Two approaches of object based classification were compared to extract buildings from the original image. One is rule based classification and the other is example based classification. We chose two districts which are Lakeshore and Columbia as our testing areas. Rule based result is better than example based. The overall accuracy of rule based classification in Lakeshore District and Columbia District are 92.5% and 85.5%. With census data, the average area per person is about 38.8 m(2) and the estimated population of the city of Waterloo is about 109589.

关键词： Keywords high resolution object-based classification population estimation QuickBird

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Utility of landsat Image in the Study of Land Cover and Land Surface Temperature Change

Utility of landsat Image in the Study of Land Cover and Land...

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3rd International Conference on Environmental Science and Information Application Technology (ESIAT)

作者： Lv, Zhi-qiang Zhou, Qi-gang Chongqing Technol & Business Univ Tourism & Land Dept Chongqing Peoples R China

Scientists have aimed at exploring land use and land cover (LULC) and their environmental influence in order to improve our understanding of the causes and consequences of these phenomena. This study addresses and use and land cover change (LUCC) in the upper reaches of Pearl River Delta, China, from 1990 to 2008. based on remotely sensed images of Landsat. LUCC and land surface temperature were assessed. Results showed that land surface temperature was highly influenced by the LUCC from 1990 to 2008. An examination of the relationship between the LULC and LST maps was finally conducted to comprehension their interactions. Results indicated that Landsat image was effective for quantifying the heat environment and providing reliable measurements of land use change. LST was found to be positively correlated with impervious surface but negatively correlated with vegetated land. Each temperature zone was associated with a dominant LULC category. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Conference ESIAT2011 Organization Committee.

关键词： Land use land surface temperature object-based classification TM/ETM Fast developing region

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ENSEMBLE CLASSIFIERS FOR BUILDING DAMAGE DETECTION

ENSEMBLE CLASSIFIERS FOR BUILDING DAMAGE DETECTION

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Dubois, David Lepage, Richard Ecole Technol Super Montreal PQ Canada

ISBN: (纸本)9781479979295

Each year, numerous disasters cause high amount of human and material losses. With the presence of both technological and social means like very high spatial resolution (VHR) satellite images and the International Charter "Space and Major Disasters" respectively, decision makers can obtain the needed information to make fast life-saving decisions. The automation of parts of the image analysis process is thus of great interest. This is why we propose to apply an ensemble classification method to provide better building damage evaluation using optical images acquired before and after the event. We base this work on our previous framework for fast building detection and damage evaluation by supervised classification. The results show the positive impact of ensemble classifiers in damage mapping.

关键词： Damage evaluation disaster response ensemble classifier object-based classification remote sensing

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SEMANTIC LABELING OF AERIAL IMAGES BY LEARNING CLASS-SPECIFIC object PROPOSALS 36

SEMANTIC LABELING OF AERIAL IMAGES BY LEARNING CLASS-SPECIFI...

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36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Volpi, Michele Tuia, Devis Univ Zurich Dept Geog MultiModal Remote Sensing CH-8006 Zurich Switzerland

ISBN: (纸本)9781509033324

Land-cover and land-use semantic labeling in centimeter resolution imagery (ultra-high resolution) is mostly performed by supervised classification of informative descriptors extracted from spatially coherent but small objects (e.g. superpixels or patches). In this paper, we propose an extension of this reasoning by proposing a class-specific, multi-scale and bottom-up object proposal strategy to perform semantic labeling. Specifically, we rely on a fully trainable boundary (edge) detector, allowing us to extract class-specific objectproposals. Such proposals enable training rich appearance and object models as well as enhanced spatial reasoning. We evaluate the proposed strategy on the Vaihingen dataset with promising results.

关键词： object proposals object-based classification Semantic labeling Random forests Aerial imagery

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DELINEATION OF INDIVIDUAL TREE CROWNS IN WORLDVIEW-3 SATELLITE IMAGERY WITH MULTISCALE FITTING METHOD

DELINEATION OF INDIVIDUAL TREE CROWNS IN WORLDVIEW-3 SATELLI...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Tong, Fei Zhang, Yun Univ New Brunswick Dept Geodesy & Geomat Engn Fredericton NB Canada

ISBN: (纸本)9781728163741

Currently, most individual tree crowns delineation methods are proposed for aerial images and Lidar data. In this paper, a scheme is proposed to delineate tree crowns from the high spatial resolution WorldView-3 satellite imagery. We select a multiscale fitting scheme for the delineation and propose two modifications to optimize the result generated from this scheme. First, the object-based classification is applied to detect the shadows between tree crowns. Second, we modified the multiscale fitting process to make the selection of optimal scale fairer. The experiment results of a subset in a WorldView-3 satellite image demonstrate that the proposed modifications can improve the delineation accuracy.

关键词： Individual tree crown delineation WorldView-3 object-based classification multiscale fitting

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Adaptation of building extraction rule sets derived from MFC3 and UltraCamD aerial image data sets

Adaptation of building extraction rule sets derived from MFC...

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SPIE Conference on Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX

作者： Trosset, A. M. Bucher, T. Lehmann, F. German Aerosp Ctr DLR Inst Robot & Mechatron Rutherfordstr 2 D-12489 Berlin Germany

ISBN: (纸本)9780819477835

In the context of rapid expansion of many cities to enormous agglomerations with high population density and a worldwide urbanization process serious impacts on environment in urban areas evolve. There is a high demand for the development and application of efficient methods to analyze and monitor changes in urban areas, to support the planning decisions in these regions and for security and risk assessment. Efficient, accurate and reliable extraction of buildings and roof surfaces and their inventory in geographic information systems plays a major role in this context. Previous analyses of digital airborne data sets show up that the inventory mapping and assessment of building changes is only possible on the basis of multi-temporal data sets and digital surface models with high resolution. These analyses confirm explicitly that both high heterogeneity and diversification of urban regions as well as the availability of data sets from different camera systems increase the need for automated and transferable extraction methods. In this context two data sets from different high resolution sensors are used for the development of transferable extraction rule sets within the object-based classification method in Definiens Developer. The Multifunctional Camera (MFC3) and the UltraCamD (UCD) data sets not only have diverse geometric but also different radiometric characteristics. As a study area the centre of Berlin, Germany was selected. Two approaches to generate comparable results from different data sources are tested. The first step deals with the generation of statistical parameters and the normalization of the two data sets. The second step addresses the development and adaptation of the rule set for a robust and universal segmentation and classification process.

关键词： Automated building extraction object-based classification MFC3 UltraCamD aerial image data

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Measuring detailed urban vegetation with multisource high-resolution remote sensing imagery for environmental design and planning

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ENVIRONMENT AND PLANNING B-PLANNING & DESIGN 2012年第3期39卷 566-585页

作者： Li, Weiman Radke, John Liu, Desheng Gong, Peng Calif State Polytech Univ Pomona Dept Landscape Architecture Pomona CA 91768 USA Univ Calif Berkeley Dept Landscape Architecture & Environm Planning Berkeley CA 94720 USA Ohio State Univ Dept Geog Columbus OH 43210 USA Ohio State Univ Dept Stat Columbus OH 43210 USA Tsinghua Univ Ctr Earth Syst Sci Beijing 100084 Peoples R China

The availability of high-resolution remote sensing imagery brings both opportunity and challenge to environmental designers and planners in obtaining high-quality landscape information for better design and planning decision making. To meet the challenge, in this paper we introduce a comprehensive approach to measuring urban vegetation data detailed to single patches of trees or shrubs and single patches of lawn or grass with multisource remote sensing imageries. Methodologically, the approach integrates advanced geospatial technologies to achieve the research objective. First, an automatic registration algorithm is applied to align an unorthorectified QuickBird satellite multispectral imagery to a high-resolution United States Geographical Survey orthoimage. Next, an image segmentation process extracts landscape objects from such multisource data for further object-based image classification. Third, the approach takes advantage of the strong power of a group of prioritized spectral, geometric, topological, and thematic image object features to produce satisfactory classification results. The approach was tested in the Oakland Metropolitan Area in California, USA and was assessed with both groundtruthing and imagetruthing data. The paper concludes with a discussion on the potential applications of both the approach and the generated data in environmental design and planning.

关键词： detailed vegetation setting imagery integration object-based classification remote sensing application in environmental design

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Development of transferable rule-sets for urban areas using QuickBird satellite imagery

Development of transferable rule-sets for urban areas using ...

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IEEE INTERNATIONAL CONFERENCE ON AEROSPACE ELECTRONICS AND REMOTE SENSING (ICARES)

作者： Tathiri, Anahita Shafri, Helmi Zulhaidi Mohd Hamedianfar, Alireza Univ Putra Malaysia Fac Engn Dept Civil Engn Serdang 43400 Selangor Malaysia Univ Putra Malaysia Fac Engn GISRC Serdang 43400 Selangor Malaysia

ISBN: (纸本)9781479961887

Although rule-based object-based classification can often perform better than the supervised approaches, its attribute selection is very time consuming and hardly transferable between different urban areas. The purpose of this study is to identify transferable rule-sets for different areas from QuickBird satellite imagery for urban areas consisting heterogeneous man-made and natural features. object-based classification was used in this research, and a mathematical method was proposed for rule transferability for different urban areas.

关键词： object-based classification transferability rule-based classification urban areas

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Plastic covered vineyard extraction from airborne sensor data with an object-oriented approach

Plastic covered vineyard extraction from airborne sensor dat...

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Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII/18th International Symposium on Remote Sensing

作者： Tarantino, E. Aiello, A. Politecn Bari I-70125 Bari Italy

ISBN: (纸本)9780819488015

In recent years, the wide-spreading of vineyard cultivation in the Apulia Region (Italy) has showed negative consequences on the hydrogeological balance of soils as well as on the visual quality of rural landscape which has been significantly altered by the heavy diffusion of artificial plastic coverings. In order to monitor and manage this phenomenon, a detailed site mapping has become essential. With the increase of spatial resolution, pixel based approaches no longer capture the characteristics of classification targets. Consequently, classification accuracy is poor. object-based image classification techniques overcome this issue by first segmenting the image into meaningful multipixel objects of various sizes and then assigning segments to classes using fuzzy methods and hierarchical decision keys. In this study an object-based classification procedure from Very High Spatial Resolution (VHSR) true color aerial data was developed on a test area located between the Apulian municipalities of Ginosa and Palagiano in order to support the update of the existing land use database aimed at plastic covered vineyard monitoring.

关键词： plastic covered vineyard object-based classification true color aerial data

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ESTIMATING WOOD VOLUME FOR PINUS BRUTIA TREES IN FOREST STANDS FROM QUICKBIRD-2 IMAGERY 23

ESTIMATING WOOD VOLUME FOR <i>PINUS BRUTIA</i> TREES IN FORE...

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23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)

作者： Patias, Petros Stournara, Panagiota AUTH Dept Cadastre Photogrammetry & Cartog Lab Photogrammetry & Remote Sensing Thessaloniki Greece

Knowledge of forest parameters, such as wood volume, is required for a sustainable forest management. Collecting such information in the field is laborious and even not feasible in inaccessible areas. In this study, tree wood volume is estimated utilizing remote sensing techniques, which can facilitate the extraction of relevant information. The study area is the University Forest of Taxiarchis, which is located in central Chalkidiki, Northern Greece and covers an area of 58km(2). The tree species under study is the conifer evergreen species P. brutia (Calabrian pine). Three plot surfaces of 10m radius were used. VHR Quickbird-2 images are used in combination with an allometric relationship connecting the Tree Crown with the Diameter at breast height (Dbh), and a volume table developed for Greece. The overall methodology is based on individual tree crown delineation, based on (a) the marker-controlled watershed segmentation approach and (b) the GEographic object-based Image Analysis approach. The aim of the first approach is to extract separate segments each of them including a single tree and eventual lower vegetation, shadows, etc. The aim of the second approach is to detect and remove the "noisy" background. In the application of the first approach, the Blue, Green, Red, Infrared and PCA-1 bands are tested separately. In the application of the second approach, NDVI and image brightness thresholds are utilized. The achieved results are evaluated against field plot data. Their observed difference are between -5% to +10%.

关键词： Quickbird-2 Marker-controlled watershed segmentation object-based classification Tree wood volume Individual tree crown delineation

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