Mıhlı çayı havzasında uydu verileri ile veri entegrasyonu kullanarak havza gelişimi ve jeotermal enerji analizi
Using data entegration with satellite images, data manegement and geothermal energy analysis in Mihli creek basin
Yazar: SAKİNE KANDİL
Danışman: PROF. DR. H.GONCA COŞKUN
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / Geomatik Mühendisliği Ana Bilim Dalı
Derece: Yüksek Lisans, 2017
Konu: Jeodezi ve Fotogrametri = Geodesy and Photogrammetry

Özet:
Son yıllarda, akarsu havza yönetimi çalışmalarında uzaktan algılama yöntemleri ve Coğrafi Bilgi Sistemleri (CBS) kullanılmaktadır. Havza yönetimi çalışmalarında su potansiyelinin belirlenmesinin hidrolik açıdan önemi büyüktür.  Havza sınırı, yağış verileri, akım verileri, alan, eğim ve arazi kullanımı parametreleri havzanın su potansiyeli için gerekli parametreleridir. Uzaktan algılama ve CBS kullanımı ile oluşturulan verilerle yapılan hidrolik model, yağış ve akım verileri dışında havza ile ilgili akarsuyun su potansiyelinin elde edilmesine olanak sağlar. 
Çalışmanın ilk aşamasında Harita Genel Komutanlığı (HGK) tarafından 1/25000 ölçekli topografya haritaları kullanarak üretilmiş sayısal arazi modelinden (SAM) yararlanılarak, CBS yazılımı olan ArcGIS ile havzanın sınırı ve drenaj alanları elde edilmiştir. Alt havzalardan akan suyun ana çaya birleştiği noktalar (poor point) belirlenmiştir. Uydu verilerinin yüksek spektral ve yüksek geometrik doğrulukla belirlenebilmesi için mevcut uydu verilerine füzyon teknikleri uygulanmıştır.
Görüntü füzyonu uzaktan algılamanın çeşitli alanlarında kullanılmaktadır. Görüntü füzyonunun amacı, hem yüksek geometrik hem de yüksek spektral çözünürlüklü multispektral görüntüler elde etmektir.
Tez çalışmasında, Edremit Körfezi'nin kuzeyindeki Mıhlı Çayı Havzası'nın Ağustos 2011 tarihli Landsat 5 TM uydusuna ait 30  m çözünürlükte multispetral uydu verisi, Temmuz 2012 tarihli SPOT 4 uydusuna ait 10 m çözünürlükte pankromatik ve 20 m çözünürlükte multispektral uydu verisi kullanılmıştır. 
Bu çalışmada, görüntü füzyon yöntemlerinden IHS (Intensity-Hue-Saturation), Temel Bileşenler Analizi (PCA), Brovey Dönüşümü, Ehlers Füzyonu, Multiplicative Dönüşümü ve Dalgacık Dönüşümü kullanılmıştır. Füzyon tekniklerini uygulamadan önce verilere görüntü zenginleştirme teknikleri uygulanmıştır. Görüntü füzyonu yöntemleri ile elde edilen sonuç görüntülere kontrolsüz ve kontrollü olmak üzere iki aşamada sınıflandırma işlemi uygulanmıştır. Sınıflandırma işlemlerinden sonra sonuç görüntülerin doğruluk analizleri elde edilmiştir. Mıhlı Çayı Havzası için kullanılan yöntemlerin genel doğruluk analiz sonuçları kıyaslanmıştır. Bu sayede havza için yüksek doğruluk elde edilen füzyon teknikleri belirlenmiştir.
Tez çalışmasının uygulamasının ikinci kısmında ise çalışma alanına ait yüzey sıcaklık analizi (YSA) oluşturulmuştur. Havza yönetimi ve potansiyel jeotermal alanların belirlenmesi gibi çalışmalar hızla değişen yeryüzü için önemlidir. YSA için tek pencere algoritması kullanılmıştır. Tek pencere algoritmasının bir aşaması olan NDVI (Normalized Difference Vegatation Index) çalışması için Landsat 5 TM uydu verisinin 4. ve 3. kanalları kullanılmıştır. Tek pencere algoritması için Landsat 5 TM uydu verisinin termal kanalı olan 6.kanal kullanılmıştır. Termal band sayesinde yayınırlık, atmosferik geçirgenlik ve ortalama atmosferik sıcaklık parametreleri elde edilerek tek pencere algoritması gerçekleşmiştir. Havzanın mevcut SAM ile sıcaklık değerleri bir arada ele alınarak irdelenmiştir. Havzanın bazı bölgelerinde ani sıcaklık artışları belirlenmiş ve tahmini potansitel jeotermal alanların varlığına işaret edebilir, yaklaşımı ile havza yönetimi için yeni bir veri girilmiştir.

Abstract:
The extraction of information about the Earth's surface structure and content through the acquisition and interpretation of spectral measurements made by remote sensing image processing techniques. The use of multispectral images is a commonly applied in field researches and high geometric and spectral resolution is required for accurate classification of land cover. 
Nowadays, Remote Sensing and GIS have been used in several areas. In especially data management studies, Remote Sensing and GIS have a vital factor. In data management studies, water potential is mentioned appears in literature frequently. Necessery parameters of main water potantial creek are such as basin boundary, slope, land use, area, flow and rainfall data. Remote sensing and GIS provide to obtain all data of main creek water potential without flow and rainfall data.
Firstly, main basin and sub-basins boundary were determined using ArcGIS software for data management. Digital Terrain Model (DTM) that was produced by General Command of Mapping (HGK) using 1/25000 scale topography maps was utilized and with ArcGIS software, basin boundary and drain basins were obtained. Poor points of basin which are pointed from creek main basin and sub-basin were determined.
In order to provide high spectral and geometric accuracy of satellite data were applied fusion methods. Image fusion can be named as choosing the best characteristics of the input images. The sensors used for image fusion are mostly panchromatic and multispectral sensors. Because the fusion result is a sharpened version of multispectral image by panchromatic image, the fusion is also named as pansharpening. There are lots of fusion methods. In this study, six different image fusion techniques have been applied to high spectral and low spatial resolution satellite images with high spatial and low spectral resolution images to obtain fused images with increased spatial resolution, while preserving spectral information as much as possible. These techniques are Intensity-Hue-Saturation (IHS), Principial Component Analysis (PCA), Brovey Transform, Ehlers Fusion, Multiplicative Transform, and Wavelet Transform were utilized. 
IHS method transforms a color in RGB space from IHS space. HIS space provides information and parameter that are very close to human color perception. The modified IHS transform also improves the resolution of the fused image. It changes the spectral contents of the image.
PCA translates and rotates the data into a new coordinate system to maximize the variance of the original data. Since the new components have perpendicular axes to each other, there is no correlation between them. This method preserves the original spectral contents in all possible combinations. The output fused image has a higher contrast than the input MS image.
Brovey Transform is a simple numerical method to merge different sources of data. This method uses a ratio algorithm to combine the images. Brovey transform is designed for the production of RGB images. The result image contains the combination of the three bands of MS and PAN.
Ehlers Fusion algorithm was created by Prof. Manfred Ehlers, University of Osnabrück. The Ehlers fusion uses the IHS transformation to obtain the optimum color discrimination in the multispectral image. While IHS transformation involves 3 bands (RGB), in this method, using multiple IHS transformations, the number of bands used is increased.
Multiplicative Transform applies a simple multiplicative algorithm which integrates the two raster images. The multiplicative method is the simplest of the PCA and Brovey methods.
Finally, Wavelet Transform technique is an intensive process. This method includes mathematical proceeding and emerges frequency components of image.
In this study, panchromatic image from Spot 4 satellite in July 2012 and multispectral image from Landsat 5 TM satellite in August 2012 of Mıhlı Creek Basin are used. The panchromatic image which has 10 m resolution and multispectral image having 30 m resolution are utilized. Additionally, multispektral image having 20 m resolution from SPOT 4 were used for image fusion The Mıhlı Creek Basin is analysed using pansharpening methods and the result images are compared. 
Image classification and accuracy assesment are realized and the optimal result is obtained. After image fusion, the result images obtained from image fusion methods were applied image classification. Image classification involves unsupervised and supervised classification. In this study, classes of basin were determined as forest area, settlement area, stream branches, roads, vegatation area, and soil area. With classification, percentage of accuracy analysis by general and class of the result images were obtained. 
In Landsat 5 TM MS – SPOT 4 PAN fusion, the best results are roads in the IHS method 93.94%, settlement area in the PCA and Multiplicative Transform 100.00%, vegatation area in the Brovey Transform 91.30%, forest and settlement areas in Ehlers Fusion 100.00%, and forest, vegatation, settlement areas in Wavelet Transform 100.00%. In SPOT 4 MS - PAN fusion, the best results are stream branches in the IHS method 100.00%, settlement and forest areas in the PCA and Multiplicative Transform 100.00%, vegatation, settlement areas and stream branches in the Brovey Transform 100.00%, vegatation and settlement areas in Ehlers Fusion 100.00%, and settlement area in Wavelet Transform 100.00%.
The percentages of general accuracy analysis of Landsat 5 TM MS and SPOT 4 PAN fusion results are as follows: Ehlers Fusion 87.60%, Brovey Transform 86.00%, Dalgacık Transform 81.63%, Multiplicative Transform 80.82%, Principal Component Analysis (PCA) 76.00% ve IHS method 72.00% accuracies were achieved. The percentages for SPOT 4 MS and PAN fusion results are as: Ehlers Fusion 89.58%, Brovey Transform 88.00%, Multiplicative Transform 85.71%, Principal Component Analysis (PCA) 83.67% ve IHS method 80.00%, Dalgacık Transform 74.00% accuracies were achieved. 
The results indicate that the Ehlers Fusion provides the highest performance in both Landsat 5 TM MS – SPOT 4 PAN fusion and SPOT 4 MS – SPOT 4 PAN fusion. Accuracy assesment percentage of SPOT 4 MS – SPOT 4 PAN fusion has higher than Landsat 5 TM MS – SPOT 4 PAN fusion. On the other hand, only Wavelet Transform in Landsat 5 TM MS- SPOT 4 PAN fusion provides higher accuracy.
In data management, depend on temperature, prediction of potential geothermal area is important for potential water since geothermal water is groundwater. In second part of this study, land surface temperature (LST) analysis of the basin was formed. Using ArcGIS software, digital terrain model of the basin and its elevation was obtained for slope parameter of basin. Moreover, sub-watershed of basin was extracted. Elevation of Mıhlı Creek Basin has 0 – 1400 m.
For LST analysis, mono window algorithm was utilized. The mono window algorithm consists of six steps as  convert the digital number (DN) into spectral radiance, the spectral radiance into at-sensor brigtness temperature, calculate land surface emissivity, atmospheric transmittance, mean atmospheric temperature, and LST retrieval.
Thanks to Landsat 5 TM data whose of fourth and third layer, NDVI (Normalized Difference Vegatation Index) that is a stage in mono window algorithm was realized. Additionally, thermal band sixth of Landsat 5 TM was used. Obtained temperature analysis was associated with elevation of basin. In some areas of basin, sudden temperature increase was observed and potential geothermal fields were predicted.
The results indicate that the basin varies between 20 and 35 °C approximately. Between 1000 – 1400 m elevation was seen 21 – 23 °C, 700 – 1000 m elevation was observed 22 – 24 °C, 500 – 700 m elevation is above 30 °C, and  between 0 - 500 m elevation observed that the temperature is always above 30 ° C in these areas.
Particularly, it has been observed that sudden temperature increases occur at the control points selected from the poor points of the stream branches. Some areas have been observed to have temperatures up to 37 °C. These sudden temperature deviations can indicate the presence of potential geothermal fields in study area.