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Uydu görüntü verileri kullanılarak orman yangın analizi

Forest fire analysis using satellite images

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  1. Tez No: 520096
  2. Yazar: ÇİĞDEM İNAN
  3. Danışmanlar: PROF. DR. SEDEF KENT PINAR
  4. Tez Türü: Yüksek Lisans
  5. Konular: Mühendislik Bilimleri, Engineering Sciences
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2018
  8. Dil: Türkçe
  9. Üniversite: İstanbul Teknik Üniversitesi
  10. Enstitü: Bilişim Enstitüsü
  11. Ana Bilim Dalı: İletişim Sistemleri Ana Bilim Dalı
  12. Bilim Dalı: Uydu Haberleşmesi ve Uzaktan Algılama Bilim Dalı
  13. Sayfa Sayısı: 89

Özet

Doğal dengenin tesisinde kritik öneme haiz nitelikteki ormanların, çevresel ve ekolojik faydaları itibariyle ciddi biçimde korunması gerekmektedir. Orman yangınları etkileri ve ortaya çıkardığı sonuçları bakımından tüm dünyada en vahim doğal afetlerin başını çekmektedir. Dünya genelinde orman yangınlarından bahsedildiğinde, öncelikli olarak Akdeniz ülkeleri, Avustralya, Kanada ve Amerika Birleşik Devletleri hatıra gelmektedir. Söz konusu ülkeler yangınlarla mücadele açısından başarılı sayılabilir. Bu başarıda, yangın tehlikesinin gerçekçi tahmini, doğru bir şekilde oluşturulmuş planlama sistemleri ve tehlikenin olduğu yerlere acil müdahale imkânların da rolü büyüktür. Türkiye'de, orman yangınlarının oluşumunda en elverişli şartlara haiz olan Akdeniz ikliminin etkisinde yer almaktadır. Büyük ölçüde kuru-yarı nemli, yarı nemli ve yarı kurak iklim şartlarının hakim olan Türkiye için, orman yangını bütün bölgedeki orman alanları için yüksek risk ve ciddi tehlike barındırmaktadır. Bütün Dünya'da ve benzer şekilde ülkemizde de ormanlara yapılan tahribatın başını orman yangınları çekmektedir. İstatistiki bilgiler irdelendiğinde ülkemizde orman yangınlarının değişik yapıya sahip olduğu ancak ilerleyen senelerde nüfus sayısındaki artışa bağlı olarak yangınlar da da fark edilir bir artışın yaşandığı göze çarpmaktadır. Bu durum; doğal orman yangınına ait yangın öncesi ve yangın sonrası Landsat 8 OLI / TIRS görüntüleri kullanılarak, yanan alan belirlenmiştir. Çalışma kapsamında söz konusu yangında, OGM verilerine göre 540 ha ormanlık alanın yok olduğu tespit edilmiştir. Ancak yapılan analizler sonucu, yanan alan (NDVI) değeri 1372 ha , yanan alan (BAI) değeri 1403 ha ve yanan alan (NIR) değeri 1588 ha olarak hesaplanmıştır. Buna göre, en doğru ve kapsamlı sonucun NIR bandının maskesinin filtrelenmesinden elde edildiği görülmüştür.

Özet (Çeviri)

The ecosystem consisting of the interaction between microorganisms which are living beings, animals, plants including trees, and physical environmental factors like light, air, soil and temperature is called a forest. The infinite number of substances and events that bring the forest to existence are in a two-way relationship and interaction with each other. For this reason, the forest is an ecosystem that manifests itself through the population of many plants and animals. The forests which are playing a critical role in the establishment of natural equilibrium have to be devoutly protected due to their environmental and ecologic benefits. Forest fires are the leading cause of destruction to the forests worldwide as well as in our country. When referring to forest fires all over the world, primarily Mediterranean countries, Australia, Canada and the United States come to mind. These countries can be considered successful in the fight against fires. This success is due to the realistic prediction of the danger of fire, the right planning systems and the opportunities for immediate intervention in places where there is danger. Turkey is situated under the influence of the Mediterranean climate which provides the most favorable conditions for the occurrence of forest fires. In Turkey, which is mainly dominated by dry and semi-humid, semi-humid and semi-arid climatic conditions, forest fires constitute a great risk and a serious danger for all forest areas in the region. In areas where forest fires have occurred, fires are classified as areas to obtain extensive information on the damage caused by fires. The main purpose of the classification is to demonstrate the effectiveness of the activities carried out in combat with fires and to contribute to the measures to be taken against this fight. To achieve success in combating forest fires, it is not enough to use resources economically and effectively by the timely and on-the-spot recruitment of the necessary measures. In addition, advanced technologies must be used in every phase of the firefighting process. For this reason, due to the possibilities they offer, Remote Sensing methods have been used for the mapping of fire areas, fire management, determination of the severity of the combustion and the burnt area for a long period of time. Fire characteristics and plant canopy can be determined in connection with the temperature differences between the fire surface and the fire surface using the fire algorithms used in Remote Sensing methods. The severity of combustion is defined as the determination of the ecosystem specific effect of the physical, chemical and biological structure that undergoes a change in the fire. In this context, spectral changes occurring in the infrared bands of the vegetation are taken into consideration in the determination of burning intensity and burned area, and some analyzes are made by the determined indices. Combustion intensity can be calculated by grading difference images generated by taking advantage of satellite image indices before and after fire. In the post-fire period, many activities are carried out by taking advantage of the satellite image indexes for examining forest foliation. In this context, the responsible institutions in our country are carrying out activities for the re-foresting of areas where forest fire is happening, and forests have been damaged by fire. xviii On the other hand, in the literature review, it has been determined that various studies have been carried out to determine the forest fire characteristics (burning area and intensity of burning) and to determine the rehabilitation of the area in question. For example, the intensity of burning in forest fires in southern Spain has been determined by processing LANDSAT TM / ETM satellite imagery. In the satellite images obtained before and after the fire, the middle (M) and near (N) infrared (IR) bands were analyzed and the locations of the burned and unburned pixels could be determined. The middle (M) and near (N) bands were found to be the most appropriate bands to determine the fire character. Currently, when the fire effects of large-scale fires in various parts of the world are examined, the dimensions of damage inflicted on vegetation can be categorized by using the method of Differenced Normalized Burn Ratio (dNBR) which is widely used in determining the forest burning intensity map. As a result of the analysis based on the fire which took place in the Extremadura region of Spain in 2009 and had an impact on 3000 hectares (ha) forest area, 15 satellite images obtained through LANDSAT TM for forest foliation during the 27 months after the fire were examined. The normalized difference for each image was examined by calculating the NDVI for the aforementioned forest foliage survey. Like all over the world, forest fires cause serious loss also in our country. For this reason, one of the main tasks of forest fire fighting organizations is to reduce forest fires to the minimum. Prediction of fire development and fire behavior characteristics (burning substance consumption, burning intensity and spreading rate) is critical in terms of firefighting activities. The inadequacy of forest monitoring stations in our country and the spatial size of the forests make it difficult to systematically detect forest fires. Remote Sensing methods stand out as a vital data source for the operational activities to be carried out in large scale with the possibilities that they have brought. In terms of the effects of forest fires and their consequences, the worst natural disasters in the world are leading. When statistics are analyzed, forest fires in our country have different structures, but in the following years, there is a noticeable increase in fires due to the increase in the number of the population. This situation; natural decay, erosion, desertification, landslides and mass loss. However, renewal of forests and vegetation damaged by fires is also important for land management. Estimation of forest fires and their behavior is very important in terms of fire fighting methods. In this context, using satellite imagery greatly facilitates the detection of fireaffected areas and intensity of burning in large areas. Temperatures reaching extremely high levels in July and August, particularly in the Mediterranean region, pose a threat to forest areas when they reach low humidity. Disaster struggle has an important position among remote sensing practices and forest fires, one of the most frequent natural disasters today, can be critically evaluated through satellite imagery. In this study, we investigated the Antalya Kumluca fires, one of the forest fires in the Mediterranean region in our country. Pre-and post-fire satellite images were used to determine the burning area. In this sense, it is observed that the work put forward in our country is not in the desired place. The aim of this work is to detect rapidly the burning area in forest fires that may occur in the future and to contribute to forest rehabilitation applications to be realized through satellite images. For this purpose, forest fire, remote sensing analysis techniques and Landsat 8 OLI / TIRS satellite images which were effective in Kumluca district of Antalya province between 24.06.2016 - 29.06.2016 were evaluated. Using the Landsat 8 OLI / TIRS images before and after the fire of Antalya-Kumluca forest fire, the burning area was determined. Within the scope of the study, it has been determined that there is no forest area of 540 ha according to GGM data. However, the results of the analyzes were calculated as 1372 hectares for burning area (NDVI), 1403 ha for burning area (BAI) and 1588 ha for burning area (NIR). Accordingly, it has been shown that the most accurate and comprehensive result is obtained by filtering the mask of the NIR band.

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