Introduction
Since the launch of the LANDSAT 4 and 5 satellites in the early 1980s the use of satellite images in archaeological work has become a realistic possibility and found to be reliable in monitoring grasslands. The Thematic Mapper scanner collects data on seven different bands of the electromagnetic spectrum, and because different ground features have distinctive reflective properties, analysis of these data can identify details of the earth’s surface from distant space. Certain bands have been used to identify cultural features such as roads and buildings, other bands are sensitive to different rock and soil types and yet others to different types of vegetation. Satellite images are large raster images and can be manipulated and enhanced by Image Processing techniques just like any other digital image. Each LANDSAT image covers an area of 34,000 sq km and has a spatial resolution of 30 m; each pixel in the image represents a 30-metre square on the ground. The French SPOT 12 satellite improves on this resolution with 20 m for multi spectral images and 10 m for single-band images covering an area of 48,000 sq km (Lock, 2003).
Because of this rather poor resolution these satellite images have tended not to be used for the prospection and location of individual sites unless the sites are of a considerable size. On a LANDSAT image, for example, unless an archaeological feature fills a considerable proportion of a 30-metre pixel it is not going to influence the numeric value of that pixel. Where satellite images have proved to be very useful, however, is in providing environmental and landscape information in areas where maps are either difficult to acquire or difficult to use such as jungle and desert. An early example of the latter is the UNESCO Libyan Valleys Survey where a LANDSAT image provides essential background information for an archaeological survey placing known, and identifiable, archaeological features within a wider landscape setting. Image Processing also allows for the classification of a landscape into different land types, and land uses, according to the spectral signal, and this information can be used for locational analysis or for survey design. Again, because satellite images are spatial data, their integration with other types of landscape, environmental and archaeological information through GIS software is becoming increasingly common practice (Lock 2003). Satellite images are used by institutions and governments for different purposes. The use of satellite images changes the approaches of a government in dealing with people. The paper will discuss about the use of remote sensing in monitoring grasslands. Such topic is interesting because this study may help in solving the land problems of nations.
Background of the Study
It is readily apparent that in the physical geographic domain, continued rapid developments in remote sensing have dramatically increased the availability of data describing earth surface processes, such as climate, changes in land cover and land use, deforestation, and urbanization. Each of these new sources of physical geographic data are related to aspects of human spatial activity, but none of them can be thought of as materially augmenting more traditional social scientific data that describe the social characteristics of individuals and groups. It is also noteworthy that such data are rarely useful without extensive ground-truthing, a process that remains time-consuming and expensive (Goodchild & Janelle 2004). Allied to the use of a GIS is remote sensing for data gathering. This deals with the detection and measurement of phenomena without being in contact with them. This data gathering method uses devices sensitive to electromagnetic energy such as light, heat, and radio waves. Remote sensing provides a unique perspective from which to observe large regions and global monitoring is possible from nearly any site on earth. In practice, satellite remote sensing has been put to use to estimate atmospheric water vapor, trace gases, aerosol particles, clouds and precipitation, and to monitor and quantify changes in territories that are otherwise not accessible. The use of remote sensing means changes can be observed and merged with the other data layers of a GIS (Mansell & Wehn 1998).
Another type of remote sensing device generating input for a GIS is videography, an advance on aerial photography. Video techniques using portable equipment produce geo referenced aerial video images in analogue or digital format. Airborne videography does not rely on special aircrafts and incorporates visual, infra-red, and thermal imaging. The advantages of this technology lie in its customization flexibility, the possibilities for data integration with other digital data such as scanned or digitized maps and satellite data, and its low cost compared with conventional aerial photography. The combination of these technologies provides important means of analysis and access to environmental information. The United Nations Environment Program (UNEP) contributes to the Global Resource (Mansell & Wehn 1998). Information Database (GRID), compiling and archiving geo referenced data. The GRID centers uses specialized ICT applications, such as remote sensing, and geographic information systems, and are building the expertise to prepare, analyze, and present environmental data. UNEP's Environmental and Natural Resources Information Networking (ENRIN) program is supported by a satellite telecommunication system (Mansell & Wehn 1998).
With full Internet connectivity, the satellite communication system provides a high capacity means of delivering environment data and information for other UNEP initiatives such as GRID. The project is financed by a number of donor countries and implemented in collaboration with UNEP and the European Space Agency (ESA) (Mansell & Wehn 1998). After conducting a remote sensing, researchers use texture analysis to gather the different data they need in analyzing land cover and use. The texture analysis helps in showing an animated display of the different features of a certain area.
Aims/Objectives
The main aim of the study is to discuss about the application of remote sensing with respect to grassland monitoring. Another aim of the study is determine the importance of image texture in analyzing satellite images with regards to land cover/land use.
Summary
The texture analysis helps in showing an animated display of the different features of a certain area. It dissects certain features of an area and found very useful in monitoring grasslands. Apparently, the multi structural analysis helps in of the parts of the figure showed the different circumstances in the image. The multi structural analysis shows a more animated different transformation of the image depending on what the color system stands for. Image texture when used in a multi spectral analysis of satellite image creates an image that can give more data and clearer visualization of the different aspects and properties of the generated image.
Conclusion
Traditionally, data analysts have turned to data mining techniques when the size of their data has become too large for manual or visual analysis. One method use in data mining is remote sensing for data gathering. This deals with the detection and measurement of phenomena without being in contact with them. After conducting a remote sensing, researchers use texture analysis to gather the different data they need in analyzing land cover and use. The texture analysis helps in showing an animated display of the different features of a certain area. If used with multi spectral analysis, texture analysis helps in providing an image that can be highly reliable in providing information on classification of land cover and land use. The combination of the two analysis gives a better chance of having accurate data that are needed by the government and other people involved in such study.
References
Goodchild, M.F. & Janelle, D.G. (eds.) (2004). Spatially integrated social science, Oxford University Press, New York.
Lock, G. (2003). Using computers in archaeology, Routledge, New York.
Mansell, R. & Wehn, U. (eds.) (1998). Knowledge societies: information technology for sustainable development, Oxford University, Oxford.
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