Using satellite imagery toevaluate the impacts of oilpipeline on vegetation
Başlık çevirisi mevcut değil.
- Tez No: 757442
- Danışmanlar: DR. M.T MARSHALL, DR. T.A GROEN
- Tez Türü: Yüksek Lisans
- Konular: Jeoloji Mühendisliği, Geological Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2021
- Dil: İngilizce
- Üniversite: University of Twente
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 46
Özet
Özet yok.
Özet (Çeviri)
Oil pipelines have various effects on vegetation both during and after construction. Oil pipeline construction activities and their impacts over time pose a threat to the sustainability of plant species and other biodiversity conservation, especially as it passes through protected or adjacent areas (Castell et al., 1994). These impacts from the pipeline vary according to different land cover types and elevations. This study aims to evaluate the magnitude of change and the duration of the recovery process in forest and grass fields, depending on elevation, using the LandTrendr algorithm and Landsat images after pipeline construction. For this study, a part of the Baku Tbilisi Ceyhan (BTC) pipeline remaining in Georgia was selected. After the construction activities covering the years 2003-2005, the change in the vegetation was studied using the Normalized Difference Vegetation Index (NDVI) with the help of remote sensing. The magnitude of the disturbance in the vegetation experienced in this period and the time required for the recovery of the vegetation afterwards were determined. First, preprocessing was performed for data preparation, which included cloud masking, harmonization, and measurement of surface reflectance to ensure continuity over time. In the second phase, LandTrendr segmentation parameters were established to detect changes in which time series algorithm was run, temporal interruptions, abrupt changes and temporal segmentation were performed. After determining the spatial and temporal changes through LandTrendr, the magnitude of the change in our sample areas, forests and grasslands, and the duration of vegetation recovery were evaluated using 500 samples (pixel values). We also created a regression model based on three variables to understand the impact of elevation, distance to pipeline, and different land cover classes on the magnitude of changes and recovery period. Finally, we evaluated our model using K-fold cross validation and interpreting the spatial temporal changes of land cover due to pipeline disturbance. According to the disturbance result, the changes in NDVI increase with altitude, and the regression result shows that forest and grass land cover, distance to pipeline, and elevation can explain 36.8% (RMSE=0.067) of the changes in NDVI. Also, NDVI variation in grass increases while forest decreases with altitude. The regression results in forest and grass were R2=0.374 (RMSE=0.062) and R2=0.403 (RMSE=0.066), respectively. For the duration of recovery period, the change in NDVI increases with elevation, and the regression result shows that forest and grass land covers, distance to pipeline, and elevation can explain 6.5% (RMSE=4.425) of the changes in NDVI. Also, the recovery period in forest is longer than in grass, and the regression results in forest and grass show R2 = 0.0344 (RMSE=4.07), R2 = 0.091 (RMSE=3.39), respectively. As a result, K-fold cross validation was run for the disturbance and recovery period, showing R2=0.415 (RMSE=0.057) for the disturbance and R2=0.286 (RMSE=4.080) for the recovery period. Therefore, this study shows that LandTrendr algorithm is suitable to estimate the magnitude of change and duration of recovery in vegetation greenness after pipeline disturbance.
Benzer Tezler
- Türkiye'deki dağlık havzalarda uygulanan swat modeli ile iklim değişikliğinin incelenmesi
Evaluating climate change impacts using swat in a mountainous region of Turkey
İSMAİL BİLAL PEKER
Yüksek Lisans
Türkçe
2020
İnşaat MühendisliğiEskişehir Teknik Üniversitesiİnşaat Mühendisliği Ana Bilim Dalı
DR. ÖĞR. ÜYESİ ALİ ARDA ŞORMAN
- Determination of the impacts of marine farms on marine ecosystems by using remote sensing: Ildırı Bay
Balık çiftliklerinin denizel ekosisteme etkilerinin uzaktan algılama ile tespiti: Ildırı Körfezi
FETHİ BENGİL
Yüksek Lisans
İngilizce
2011
Deniz BilimleriDokuz Eylül ÜniversitesiDeniz Bilimleri ve Teknolojisi Ana Bilim Dalı
YRD. DOÇ. DR. KEMAL CAN BİZSEL
- Sürdürülebilir peyzaj planlama ve tasarımı için kentsel alanlarda iklim parametrelerinin ve iklim bölgesi temelli morfolojik yaklaşımın iklim senaryoları ile değerlendirilmesi
Assessment of climate indicators and morphological features in urban areas within the framework of climate scenarios: A sustainable landscape planning approach
AMRAGIA H MOSTAFA ELAHSADI
Doktora
Türkçe
2025
MimarlıkKastamonu ÜniversitesiPeyzaj Mimarlığı Ana Bilim Dalı
PROF. DR. MEHMET ÇETİN
- Deprem sonrasında binaların hasar tespitinde kullanılan yapay öğrenme algoritmalarının analizi
Analysis of machine learning algorithms used in post-earthquake building damage assessment
SERHAT MÜRSEL KÖROĞLU
Yüksek Lisans
Türkçe
2025
Jeodezi ve Fotogrametriİstanbul Teknik ÜniversitesiBilişim Uygulamaları Ana Bilim Dalı
DOÇ. DR. CANER GÜNEY
- An improved flood detection and susceptibility mapping using remote sensing and GIS technologies
Uzaktan algılama ve Cbs teknolojilerini kullanarak gelişmiş bir sel algılama ve duyarlılık haritalaması
MAHYAT SHAFAPOURTEHRANY
Doktora
İngilizce
2015
CoğrafyaUniversiti Putra Malaysia UPMİnşaat Mühendisliği Ana Bilim Dalı
PROF. DR. BISWAJEET PRADHAN