Elmalı ve Alibey su havzalarının uydu görüntü verileriyle izlenmesi ve bilgi sistemi oluşturma olanakları

Abstract

Bu çalışmanın bir bütün olarak amacı, kentsel planlama çerçevesinde havza arazi kullanım planlarının hazırlanmasında bir bilgi kaynağı olarak uydu görüntülerinin coğrafi bilgi sistemleri ile birlikte kullanılma potansiyellerini incelemede bir temel oluşturmakdır. Birinci bölümde İstanbul Su Havzalarının mevcut durumu ve çalışmanın amacı ortaya konmuştur. İkinci bölümde, Uzaktan Algılamanın temel esasları ve uygulamada kullanılan bazı sınıflandırma Algoritmaları ve Uydu verilerinin konum ve tematik doğruluk derecesini belirten yaklaşımlar açıklanmıştır. Üçüncü bölümde, Coğrafi Bilgi Sistemlerine ilişkin veri yapısı ve Uzaktan Algılama verileri ile Coğrafi Bilgi Sistemlerinin özellikle kırsal ve kentsel planlamada etkin bir şekilde kulllanımının gerekliliği vurgulanmıştır. Dördüncü bölümde, uygulamaların, gerçekleştirildiği İTÜ İnşaat Fakültesi Fotogrametri ve Uzaktan Algılama Laboratuvarı ve işlem Şirketler grubu laboratuvarının yazılım ve donanımları incelenmiştir. Ayrıca çalışmada kullanılan Uydu Sistemleri ve Uydu görüntüleri hakkında bilgi verilmiştir. Çalışmanın uygulama bölümü olan beşinci bölümde, istanbul'un içme ve kullanma suyunu temin eden barajların kent merkezine en yakın olan Elmalı ve Alibey Baraj Havzalarının iki zamanlı Landsat TM görüntüleri kullanılarak havza arazi kullanım karakteristikleri ortaya konulmuş ve görüntüler için hem konum, hem de tematik doğruluk derecesi değerlendirmeleri yapılmıştır. Yüksek tematik doğruluklu raster yapıdaki arazi kullanım verileri vektör veriye dönüştürülmüş ve Coğrafi Bilgi Sistemlerinde grafik veriler olarak değerlendirilmiştir. Arazi kullanımları ile istatistik bilgilere dayalı olarak belirlenen nüfus, yüzeysel su potansiyeli ve niteliği, topoğrafik konum, sanayi tesisleri, iş gücü, sosyo ekonomik yapı v.b. gibi havza planlamaya alt yapı olacak ilgili veriler derlenerek havza planlama ve yönetimi için bir veri tabanı hazırlanmış ve analizler yapılmıştır. Son olarak 1984 yılı ve 1992 yılı CBS katmanları üst üste konularak karşılaştırmalar havza koruma bazında gerçekleştirilmiştir. Son bölümde hızla gelişen ve bu gelişmesini planlı bir sisteme oturtamayan İstanbul'un, su üretim havzalarının, üzerindeki bitki örtüsünün kaçak ve plansız yapılaşma ile çevre kirliliğinin etkisi altında olduğu belirtilmiş, uydu görüntüsü tabanlı bir havza bilgi sistemi örneğinde Elmalı Havzası koruma kuşakları değişimleri yorumlanmıştır. Çalışmadaki yaklaşım şekli yerel ve bölgesel planlama, yönetim birimlerine gelecekteki havza arazi kullanım planlaması ve yönetimi için yüksek doğruluklu bir model olarak değerlendirilmelidir.

Remote Sensing is defined as the art and science of obtained information from a distance, about objects or phenomena without being in physical contact with them. The science of remote sensing provides the instruments and theory to understand how objects and phonemena can be detected. The art of remote sensing is in the development and use of analysis techniques to generate useful information (Aranoff, 1989). The sun is the source of radiations and electromagnetic radiation from the sun is reflected by the Earth and detected by the satellite. The set of all electromagnetic waves is described as the electromagnetic spectrum, which includes the range from the long radio waves, to the microwave, the short-wave X- and gamma rays. Electromagnetic energy reaching the Earth's surface may be reflected, transmitted or absorbed. Earth-surface elements are distinguished on the basis of their spectral reflection characteristics. The major characteristics of an imaging remote sensing instrument operating spectral bands are described in terms of its spatial, spectral, radiometric and temporal resolution. Spatial resolution is a measure of the smallest object that can be resolved by the sensor, or the area on the surface represented by each pixel. This term described as the instantaneous field of view (IFOV). The IFOV is a measure of the area viewed by a single detector in a given instant in time. The second important property of an optical imaging system is its spectral resolution. Digital images collected by satellite sensors have been multi-band or multispectral, that is individual images have been separately recorded in discrete spectral bands. The term spectral resolution refers to the width of these spectral bands. Radiometric resolution refers to the number of digital levels used to express the data collected by the sensor. The number of levels is generally expressed in terms of binary digits (bits) needed to store the value of the maximum level. For instance, in 8 bit data, the data values range from 0 to 255 for each pixel. Temporal resolution refers to how often a sensor obtains imagery of a particular area. Especially for the change detection studies, temporal resolution is very important factor (Erdas, F.G., 1991) (Mather, 1989). Modem satellite sensors such as LANDSAT, SPOT, AVHRR, ERSİ are providing image data for monitoring the earth's resources. In this study LANDSAT and SPOT multitemporal images have been used. The Earth Resources Technology Satellite (ERTS) was the first unmanned satellite designed to provide systematic global coverage of earth resources. In 1975, the ERTS program and satellites were renamed LANDSAT. The first three LANDSAT Satellites carried a multispectral scanner (MSS) and a return beam vidicon (RBV) camera. More importantly, the MSS system for the first time provided digital images suitable for computer analysis. The MSS on LANDSAT 1,2,3 imaged a 185 km wide swath in four bands. Each pixel in an MSS image represents a ground area of approximately 79 m by 56 m. The LANDSAT 4 and 5 satellites were launched into lower sun-synchronous earth orbits of about 700 km. and have a return period of 16 days. LANDSAT 4 and 5 carries two multispectral scanner system, the MSS and TM sensors. Thematic Mapper (TM) provides 7 bands from the visible to the thermal infrared. Each pixel represents a 30m by 30m ground area (except in the case of band 6 which uses a larger pixel 120m by 120m ). The SPOT program was begun by France in 1978. SPOT 1 was launched in 1986. It carries two HRV scanners (High Resolution Visible). Each sensor can operate in both (P and XS). In the Panchromatic mode, a single visible band is detected and an image 10m by 10m pixels is produced. In multispectral mode, three images with 20m by 20m pixels are produced. LANDSAT and more recently SPOT imagery are now routinely used for a wide range of applications these particular images current land cover, the detection of changes in land use. Digital Image Processing Techniques have been applied to comment on satellite images. This techniques involves the manipulation and interpretation of digital images. Image process analysis can be performed in four general steps. XVI Methods of preprocessing remotely-sensed imagery are designed to compensate for one or more of cosmetic defects, geometric distortions, atmospheric interference and variations in illumination geometry. The level of preprocessing required will depend on the problem to which the processed images are to be applied. Therefore, there is no fixed schedule of preprocessing operations which are carried out automatically prior to the use of remotely sensed data. The user must be aware of the geometrical properties the image data and of the effects of external factors (such as the level of, and variations in, atmosheric haze) and must be capable of selecting the appropriate technique to corrrect the defect or to estimate the external effect, if necessary. Image enhancement techniques include, but are not limited to, those of contrast improvement and monochrome to colour transformations. Other image- processing methods can justifiably be called enhancements. These include methods for detecting and emphasizing edges or discontinuities in an image noise reduction techniques ranging from removal of banding to filtering and colour transforms such as principal components analysis. All of these methods alter the visual appearance of the image that is of interest to a user. The development of multi-sensor packages such as that proposed for the Polar Platform of the 1990's and of sensors capable of operating in a large number of narrow spectral bands will present a considerable challenge to the capabilities of digital image-processing systems which in the main, are based on the pixel -by- pixel ("per pixel") analysis of low-dimensional image data. The computational requirements which would result from the application of such techniques to high- dimensional, high-resolution data sets would be immense. Possible new developments in hardware (parallel processing and the hardware implementation of pattern-recognition algorithms) will do much to get more satisfactory solutions to these problems. The other main area in which research and development is needed in the identification of suitable measures of texture and the specification of algorithms capable of employing contextual information into the pattern recognition procedure. With a computer system, pattern recognition can be more scientific. Statistics are derived from the spectral characteristics of all pixels in an image. Then, the pixels are sorted based on mathematical criteria. Data Merging procedures are used to combine image data for a given geographic area with other geographically referenced data sets for the same area. These other data sets might simply consist of image data generated on other dates by the same sensor or by other remote sensing systems. Frequently, the intent of XVII data merging is to combine remotely sensed data with other sources of information in the context of a geographic information system ( Lillesand and Kiefer, 1987). This research illustrate the integration of remote sensing data in a GIS. Regional and Municipal Planners require up-to-date-information to effectively manage land development and plan for change. In urban areas, particularly at the rural-urban fringe, this change is very rapid. As a result, it is difficult to maintain up- to-date information on new housing and industrial/commercial developments. This is particularly true for regional municipalities whose jurisdictions cover large areas. The land-use map, as a source of thematic information, has been an important component of urban and regional planning for many years. In areas where change is very slow, land-use maps which are considered relatively old (i.e., 10 to 20 years) may continue to portray current conditions, adequately and thus provide useful information. However, this is not the case in areas of rapid change, such as the rural-urban fringe, where the entire landscape can change over a short period of time. Here, fields and open areas are converted to residential subdivisions and commercial/industrial plazas. In such areas, the most recent map may be of little value to the person requiring up-to-date information. Even with the availability of satellite imagery and computer storage of information, the stage has not yet been reached where up-to-date information can rapidly and easily be provided. Current information on land use and cover is essential for many planning activities. Remote sensing methods are becoming increasingly important for mapping land use and land cover for following reasons. 1- Image of large areas can be acquired rapidly. 2- Images can be acquired with a spatial resolution that matches the degree of detail required for the survey. 3- Remote sensing images eliminate the problems of surface access that often hamper ground surveys. 4- Images provide a complementary perspective for ground surveys. 5- Image interpretation is faster and less expensive than conducting ground surveys. XVI M 6- Images provide an unbiased, permanent data set that may be interpreted for a wide range of spesific land use and land cover, such as forestry and urban growth like this study. The integration of remote sensing and geographic information systems (GIS) is essential for effective resource management. The volume of remote sensing imagery for managing a provincial resource is such that one must use digital image analysis systems. By combining remote sensing image analysis and geographic information systems, resource managers can have timely and accurate knowledge of a renewable resource. Satellite imagery with higher resolution can be used to update land use information in a GIS for water basin areas. Today's geographic information systems and today's remote sensing image analysis systems are both aspects of single data collection and analysis systems containing data at different levels of representation. The objective of this study is to integrate to GIS and remote sensing techniques create to information resources for water basin land use. In the first chapter Istanbul's current water resources have been given and the study's objectives have been explained. In second chapter basic principles of remote sensing and approaches to evaluate positional and thematic accuracy levels of classifying algorithms and remote sensing data have been explained. In third chapter, data structures regarding GIS and Remote Sensing data have been examined and the necessity of the use of such data in rural and urban planning has been emphasized. In fourth chapter information about the study environment (ITU Civil Engineering-Photogrammetry and Remote Sensing Lab. and software and hardware which are represented by Group of Componies in Turkey) satellite systems and remote sensing data have been given. In chapter five using multitemporal LANDSAT TM images (1984-1992) land- use/cover characteristics in Elmalı and Alibey Water Basin Area have been analyzed and evaluation of thematic and positional accuracy of images have been performed. High accuracy raster data is converted to vectorial data and used in Geographic Information System. A Data Base to be used for water basin planning I XX and managing utilizing statistical attribute data covering population, water potential, topographic position, industry and labour force etc. has been prepared and overlay analysis has been performed. Finally in this chapter comparison between water basin protected areas in 1984 and 1992 using GIS techniques has been made and results have been received in a three dimensional surface model. In final chapter the results of this study have been evaluated and suggestions have been given to avoid further destruction of water basin areas.