Научная статья на тему 'Community Open media data portal to disseminate Geospatial knowledge and skills'

Community Open media data portal to disseminate Geospatial knowledge and skills Текст научной статьи по специальности «СМИ (медиа) и массовые коммуникации»

CC BY
86
33
i Надоели баннеры? Вы всегда можете отключить рекламу.

Аннотация научной статьи по СМИ (медиа) и массовым коммуникациям, автор научной работы — Govorov M., Gienko G., Gienko A., Khmelevsky Y., Maguire B.

Many professionals use aerial and satellite imagery analysis interpretation in different GIS projects. The best practical way to acquire such knowledge and skill is for observers to go to the field, locate themselves in an overhead image, observe the landscape and find corresponding features in the image. In reality, the users often work with time and budget constraints and need quick, practical and reliable reference information to assist with the interpretation of particular images. Based on the assumption that natural observations could be substituted by terrestrial photographs, we propose to develop a Web-based participatory mechanism for professional collaboration in Remote Sensing and Image Interpretation. The more users share their annotated geo-referenced terrestrial photographs of different land covers, terrain features and geographical phenomena, the more users can use them to interpret remotely-sensed images in their own projects.

i Надоели баннеры? Вы всегда можете отключить рекламу.
iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.
i Надоели баннеры? Вы всегда можете отключить рекламу.

Текст научной работы на тему «Community Open media data portal to disseminate Geospatial knowledge and skills»

УДК 528.926:004

M. Govorova, G. Gienkob, A. Gienkoc, Y. Khmelevskyd, B. Maguirea

a Malaspina University-College, Advanced Diploma Program in GIS, 900 Fifth Street, Nanaimo, British Columbia, V9R 5S5, Canada

b University of the South Pacific, School of Geography, Suva, Fiji Islands c Russian Academy of Science, Krasnoyarsk Scientific Center, PO Box 2557, Krasnoyarsk,

Russia

d Okanagan College, Computer Science Department, 1000 KLO Road, Kelowna, British Columbia, V1Y 4X8, Canada

МЕДИА-ПОРТАЛ ГЕОПРОСТРАНСТВЕННЫХ ДАННЫХ

COMMUNITY OPEN MEDIA DATA PORTAL TO DISSEMINATE GEOSPATIAL KNOWLEDGE AND SKILLS

Many professionals use aerial and satellite imagery analysis interpretation in different GIS projects. The best practical way to acquire such knowledge and skill is for observers to go to the field, locate themselves in an overhead image, observe the landscape and find corresponding features in the image. In reality, the users often work with time and budget constraints and need quick, practical and reliable reference information to assist with the interpretation of particular images. Based on the assumption that natural observations could be substituted by terrestrial photographs, we propose to develop a Web-based participatory mechanism for professional collaboration in Remote Sensing and Image Interpretation. The more users share their annotated geo-referenced terrestrial photographs of different land covers, terrain features and geographical phenomena, the more users can use them to interpret remotely-sensed images in their own projects.

Во многих ГИС-проектах используются разные виды аэро и космических изображений, однако интерпретация таких снимков требует определенных навыков и опыта. Знание определенной территории, типа ландшафта, разных видов растительности, объектов антропогенной деятельности человека - все эти факторы определяют степень адекватности распознавания изображения, и, как следствие, качество выполнения ГИС-проекта. Во многих случаях полевые наблюдения, часто требуемые при дешифрировании снимков, могут быть заменены аннотированными наземными фотографиями местности, координаты которых известны из GPS наблюдений. В статье описываются основные принципы построения WEB-портала, предназначенного для сбора, хранения и распространения геопривязанных наземных фотографий. Архитектура системы и открытая копирайт политика позволяют организовать свободный доступ к такой геопространственной информации для дальнейшего использования в ГИС-проектах.

Introduction

Emerging innovations in optics, electronics and computers have led to the launch of a number of Earth-observation systems that provide vast amounts of data. Terabits of visual data are transmitted from satellites to the Earth every day. Some of the data are free, and the price of the rest is falling due to competition between image providers. This provides great opportunities for institutions,

research groups and organizations worldwide to use remotely-sensed imagery in their projects, both in social and natural sciences. Users often encounter difficulties working with aerial or satellite images, because these images differ from conventional photos in at least three important ways: objects are portrayed from an overhead (and unfamiliar) position, images are taken at scales most people are unaccustomed to seeing, and images are recorded over a range of wavelengths in multiple channels, often beyond the visible spectral zone.

While Remote Sensing specialists and cartographers in many universities study the basics of image interpretation, other professionals (e.g. biologists and environmental specialists) are generally not aware of image interpretation techniques until they become involved in a project that requires such skills. The best practical way to acquire such knowledge and skill is for observers to go to the field, locate themselves in an overhead image, observe the landscape and find corresponding features in the image. Visual links between the natural view of a particular object and its representation in an overhead image create an association between the two in the user’s brain. The wider the variety of such mental images, the more experienced the image interpreter. These mental images, along with analytical abilities for establishing associations between objects and sites are the essence of visual image interpretation. In reality, the users often work with time and budget constraints and need quick, practical and reliable reference information to assist with the interpretation of particular images. At the same time, there are individuals around the globe with relevant expertise and skills that could be shared. The only question is how to accumulate and deliver this knowledge to the community at large.

Based on the assumption that natural observations could be substituted by terrestrial photographs, we propose the following approach. The coordinates of a terrestrial photograph are used to locate the position of a photographer in a satellite image, and the bearing and vertical angle of the photo are used to determine a cone that covers the area shown in the photograph. Thus, the user is simultaneously provided with two views - from on the ground and from above it. Looking at the terrestrial photograph, the user could imagine standing on the spot and observing the landscape. Looking at the “overhead” image at the same time, the use r can associate the “natural” view of the landscape in a terrestrial photo with features in an aerial or satellite “footprint” of the same area (see Fig. 1). In other words, the user can use conventional terrestrial photographs to establish the visual link between an object and its representation in an overhead image, which, as said above, is the principal component in the process of acquiring image interpretation skills.

Fig. 1. Geo-linked terrestrial photo and satellite “footprint” of the same area, showing positions of all available terrestrial images (blue circles) and visibility

cone for the current photo (green circle)

Such abilities could be provided by establishing a Web-based participatory mechanism for professional collaboration in Remote Sensing and Image Interpretation. The more annotated terrestrial photos of different land covers, terrain features and geographical phenomena available from different locations around the globe, the more knowledge can be acquired by a particular user. Furthermore, the more users share their geo-referenced terrestrial photographs, the more users can use them to interpret remotely-sensed images in their own projects.

Methodology

Fundamentals of participatory mechanisms. A survey of the recent literature pertaining to participation and collaboration in GIS communities reveals that research has tended to fall into two categories: Participatory GIS (PGIS) and Public Participation GIS (PPGIS) on one hand, and perspectives on professional collaboration in GIS on the other. The first category provides valuable background information related to the community-based management of spatial information (PPGIS) - usually in a form of acquisition, geo-referencing and visualizing Indigenous Spatial Knowledge [Public Participation GIS ...]. The second category discusses in great detail the issues of open data and software in the professional geospatial community (the OGC - Open Geospatial Consortium [The Open Geospatial Consortium.]). As opposed to well-established and time-proven policies, specifications and practices in PPGIS and OGC, there is no systematic approach to principles of organization and functioning of Web-based participatory mechanisms for professional collaboration in Remote Sensing and Image Interpretation.

Visual interpretation of remotely-sensed imagery. Visual interpretation was the backbone of remote sensing when aerial photographs were the only remotely-sensed images available. Using visual cues, such as size, tone, texture, shape, pattern, and the relationship to other objects, an experienced image interpreter was able to identify many features in an image [Campbell, 2002; Lillesand and Kiefer, 2004]. To avoid misinterpretation, the visual interpreter uses feature identification keys - sample objects that are identified in selected overhead image by other experts. These feature identification keys greatly help the user; however, because they are defined for a particular image, acquired by a

particular sensor under particular conditions of the object and environment, they usually have little value for images acquired by another sensor or at another time. In some rare cases, feature identification keys might have a ground truth, e.g. sample objects identified in an overhead image and recognized in the field [Lillesand and Kiefer, 2004; Zion National Park]. These ground truth feature identification keys are the most accurate and valued tools for image interpretation. Of course, the user can go to the field and identify objects, but most projects make use of remotely-sensed imagery to avoid field mapping in the first place.

Web-GIS and database management. There is also a well-established literature in the field of Web-based information systems, information portals, and database management related to the work proposed here. The following publications provide information on different aspects of Web-information systems [Taniar, 2004; Vidgen, 2002; The Open Geospatial Consortium] and spatial data portals [System Design Strategies, 2005; Peng, 2003].

Implementation

The Web-based participatory mechanism for professional collaboration in Remote Sensing and Image Interpretation has scientific, procedural, and technical components. The following technical aspects are discussed in this paper:

- Applicability of the approach to a variety of remotely sensed data (remotely sensed imagery with different spatial, spectral and temporal resolutions);

- Approaches to prove the concept (feasibility, interpretation with and without terrestrial photos);

- Data and metadata (terrestrial photos, overhead images, GPS data, verbal descriptions, maps, spectral signatures, etc.);

- Implementation scheme: field work including geo-referencing

(coordinates, direction, and vertical angle), user-portal interaction, and the use of ground truth photos for in-office image interpretation.

Software implementation of the GeoTruth system is based on Web Map Server (WMS) solutions [The Open Geospatial Consortium], which uses a webbrowser as a thin client and does not require client site installation (Fig.2). The system reads common GIS raster data without conversion and is able to present user-defined grid objects.

Fig. 2. The GeoTruth WMS Architecture

The components of GeoTruth WMS provide the following functionalities:

- Geographical data can be stored in a relational database or an OS file

system.

- The core of GeoTruth WMS is the Spatial Server, which is responsible for cartographic visualisation of raster and vector data; radiometric, spatial and spectral data corrections and transformations; visibility modeling; data search; custom object uploading and extraction.

- The Metadata Server uses XML to describe the meta-information about terrestrial objects, provides a means to explore metadata and search the feature identification keys for terrestrial objects.

- The Application Server (AS) is a middle tier, and provides an interface between the Web-server and the GeoTruth Spatial and Metadata Servers. The AS enables Web-server, Servlet Engine to intercommunicate with GeoTruth Servers.

- The Web Server provides the access to the GeoTruth information from the Internet.

- WMS Client is just a light Web browser client.

Conclusions

There have been few attempts to create repositories of sample objects but they either represent images acquired by a particular sensor without ground truth [Remote Sensing Guides], or provide ground truth photographs representing very specific objects in limited areas (i.e. specific types of plants in a reserve area) [Zion National Park]. Any repository of this type will always have certain limits, because the compilation of feature identification keys and ground truth data for diverse geographic objects worldwide is an extraordinary task for any single project or organization; but it is quite possible for users to compile such a repository by themselves. The only way is to develop a Web-based mechanism, allowing users to share their geo-referenced terrestrial photographs with others, and promote this service within the Remote Sensing community. Geo-referenced annotated terrestrial images provide the “natural”, terrestrial view of objects, that

are also depicted in aerial or satellite images, and will greatly help users to identify and interpret features in remotely sensed images, either by visual interpretation or with computer-assisted automatic image analysis.

References

1. Campbell, J.B., 2002, Introduction to remote sensing, 3rd ed., Guilford, New York

2. Lillesand, T.M. and Kiefer, R.W., 2004, Remote sensing and image interpretation, 5th ed., John Wiley & Sons, New York, 766 p.

3. Peng, Z., Tsou, M., 2003, Internet GIS: Distributed Geographic Information Services for the Internet and Wireless Network, John Wiley & Sons, Inc., 720 p.

4. Public Participation GIS Home Page,

http://www.ncgia.maine.edu/ppgis/ppgishom.html .

5. Remote Sensing Guides by American Museum of Natural History, http://cbc.rs-gis.amnh. org/remote_sensing/gui des

6. System Design Strategies, 2005, An ESRI, Technical Reference Document.

7. Taniar, R., 2004, Advanced Web Technologies and Applications, Computers, 936 p.

8. The Open Geospatial Consortium, Inc. (OGC), http://www.opengeospatial.org/ .

9. Vidgen, R., 2002, Developing Web Information Systems: From Strategy to Implementation, 274 p.

10. Zion National Park: USGS - NPS Vegetation Mapping Program, Zion National Park, http://biology.usgs.gov/npsveg/zion/ .

© M. Govorov, G. Gienko, A. Gienko, Y. Khmelevsky, B. Maguire, 2008

i Надоели баннеры? Вы всегда можете отключить рекламу.