Yazar "Eker, Remzi" seçeneğine göre listele
Listeleniyor 1 - 20 / 25
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe 3D MODELLING OF A HISTORIC WINDMILL: PPK-AIDED TERRESTRIAL PHOTOGRAMMETRY vs SMARTPHONE APP(Copernicus Gesellschaft Mbh, 2022) Eker, Remzi; Elvanoglu, N.; Uçar, Z.; Bilici, E.; Aydın, A.Cultural heritage (CH), what we inherited from the past generations, is a precious asset connecting the past to the present. It has many demonstrable benefits to nations around the world. For many countries, it has been a part of national identity as well as a key driver of the economy. However, CH is under constant threat of demolition due to wars, natural and human-induced hazards, and negligence. Therefore, documentation of CH has become very essential. Recent advancements in remote sensing technology have improved upon approaches for the surveying and structural modelling of the CH. This paper examines two close-range photogrammetry approaches in modelling a historic windmill. In the first approach, to generate a 3D model of the windmill, the images were obtained with a PPK-aided system and then processed through the Structure-from-Motion (SfM) method in Agisoft Metashape software. The second approach utilized a smartphone app both to capture the images and then generate the 3D model of the windmill with SfM. The 3D models of windmills, generated with two different methods, were compared in CloudCompare software using the cloud-to-mesh distance (C2M) tool. Two models were aligned with point pairs-picking for registration and the result showed that the models are quite similar and distance between the two models ranged from -5cm to +5cm.Öğe ASSESSING URBAN FOREST CANOPY COVER in GREAT PLAIN CONSERVATION AREA (DÜZCE CITY, TURKEY) between 1984 and 2015(International Society for Photogrammetry and Remote Sensing, 2021) Uçar, Zennure; Eker, Remzi; Aydın, A.Urban trees and forests are essential components of the urban environment. They can provide numerous ecosystem services and goods, including but not limited to recreational opportunities and aesthetic values, removal of air pollutants, improving air and water quality, providing shade and cooling effect, reducing energy use, and storage of atmospheric CO2. However, urban trees and forests have been in danger of being lost by dense housing resulting from population growth in the cities since the 1950s, leading to increased local temperature, pollution level, and flooding risk. Thus, determining the status of urban trees and forests is necessary for comprehensive understanding and quantifying the ecosystem services and goods. Tree canopy cover is a relatively quick, easy to obtain, and cost-effective urban forestry metric broadly used to estimate ecosystem services and goods of the urban forest. This study aimed to determine urban forest canopy cover areas and monitor the changes between 1984-2015 for the Great Plain Conservation area (GPCA) that has been declared as a conservation Area (GPCA) in 2017, located on the border of Düzce City (Western Black Sea Region of Turkey). Although GPCA is a conservation area for agricultural purposes, it consists of the city center with 250,000 population and most settlement areas. A random point sampling approach, the most common sampling approach, was applied to estimate urban tree canopy cover and their changes over time from historical aerial imageries. Tree canopy cover ranged from 16.0% to 27.4% within the study period. The changes in urban canopy cover between 1984-1999 and 1999-2015 were statistically significant, while there was no statistical difference compared to the changes in tree canopy cover between 1984-2015. The result of the study suggested that an accurate estimate of urban tree canopy cover and monitoring long-Term canopy cover changes are essential to determine the current situation and the trends for the future. It will help city planners and policymakers in decision-making processes for the future of urban areas. © Author(s) 2021. CC BY 4.0 License.Öğe Assessment of forest road conditions in terms of landslide susceptibility: a case study in Yigilca Forest Directorate (Turkey)(Tubitak Scientific & Technical Research Council Turkey, 2014) Eker, Remzi; Aydın, AbdurrahimForest roads are one of the biggest investments in forest management. Their possible adverse effect on the environment is becoming an important issue for administrators due to a recent increase in public awareness. Especially in the Black Sea Region of Turkey, road-related landslides are common in forested areas because the roads are located in hilly regions with steep slopes. In addition to their impact on forests, landslides can cause damage to roadbeds which requires immediate maintenance. Landslide-susceptibility maps are widely used for different purposes such as reducing the effects of landslides, decision making, and planning. These maps can easily be generated by utilizing the advanced features of Geographical Information Systems (GIS) and computer technologies. Logistic regression (LR) is a widely used technique for mapping landslide susceptibility; landslide conditioning parameters such as topography, lithology, land use, distance to streams and roads, and curvature can be mapped by GIS tools. In this study a fieldwork-generated inventory of 288 landslides was used to produce a landslide-susceptibility map for the Yigilca Forest Directorate (Turkey). This map was generated by applying a GIS-based LR method. Land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature were considered as the landslide conditioning parameters. After the landslide-susceptibility map was divided into 5 classes of susceptibility (very low, low, moderate, high, and very high), it was overlapped with a road network map in order to evaluate forest road conditions in terms of landslide susceptibility. For a quantitative analysis of forest road-landslide interaction, 2 new parameters were determined: a landslide frequency index (divided into general and real) and a road-landslide index (divided into general and real). Real landslide frequency and general landslide frequency on the roads were found to be 0.42 and 0.18, respectively. The results showed that the real road-landslide index and the general road-landslide index in the area were 0.10 and 0.04, respectively.Öğe Assessment of forest road conditions in terms of landslide susceptibility: a case study in Yığılca Forest Directorate (Turkey)(2014) Eker, Remzi; Aydın, AbdurrahimForest roads are one of the biggest investments in forest management. Teir possible adverse efect on the environment is becoming an important issue for administrators due to a recent increase in public awareness. Especially in the Black Sea Region of Turkey, road-related landslides are common in forested areas because the roads are located in hilly regions with steep slopes. In addition to their impact on forests, landslides can cause damage to roadbeds which requires immediate maintenance. Landslide-susceptibility maps are widely used for diferent purposes such as reducing the efects of landslides, decision making, and planning. Tese maps can easily be generated by utilizing the advanced features of Geographical Information Systems (GIS) and computer technologies. Logistic regression (LR) is a widely used technique for mapping landslide susceptibility; landslide conditioning parameters such as topography, lithology, land use, distance to streams and roads, and curvature can be mapped by GIS tools. In this study a feldwork- generated inventory of 288 landslides was used to produce a landslide-susceptibility map for the Yığılca Forest Directorate (Turkey). Tis map was generated by applying a GIS-based LR method. Land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature were considered as the landslide conditioning parameters. Afer the landslide-susceptibility map was divided into 5 classes of susceptibility (very low, low, moderate, high, and very high), it was overlapped with a road network map in order to evaluate forest road conditions in terms of landslide susceptibility. For a quantitative analysis of forest road-landslide interaction, 2 new parameters were determined: a landslide frequency index (divided into general and real) and a road-landslide index (divided into general and real). Real landslide frequency and general landslide frequency on the roads were found to be 0.42 and 0.18, respectively. Te results showed that the real road-landslide index and the general road-landslide index in the area were 0.10 and 0.04, respectively.Öğe Assessment of large-scale multiple forest disturbance susceptibilities with AutoML framework: an Izmir Regional Forest Directorate case(Northeast Forestry Univ, 2024) Eker, Remzi; Alkis, Kamber Can; Aydin, AbdurrahimDisturbances such as forest fires, intense winds, and insect damage exert strong impacts on forest ecosystems by shaping their structure and growth dynamics, with contributions from climate change. Consequently, there is a need for reliable and operational methods to monitor and map these disturbances for the development of suitable management strategies. While susceptibility assessment using machine learning methods has increased, most studies have focused on a single disturbance. Moreover, there has been limited exploration of the use of Automated Machine Learning (AutoML) in the literature. In this study, susceptibility assessment for multiple forest disturbances (fires, insect damage, and wind damage) was conducted using the PyCaret AutoML framework in the Izmir Regional Forest Directorate (RFD) in Turkey. The AutoML framework compared 14 machine learning algorithms and ranked the best models based on AUC (area under the curve) values. The extra tree classifier (ET) algorithm was selected for modeling the susceptibility of each disturbance due to its good performance (AUC values > 0.98). The study evaluated susceptibilities for both individual and multiple disturbances, creating a total of four susceptibility maps using fifteen driving factors in the assessment. According to the results, 82.5% of forested areas in the Izmir RFD are susceptible to multiple disturbances at high and very high levels. Additionally, a potential forest disturbances map was created, revealing that 15.6% of forested areas in the Izmir RFD may experience no damage from the disturbances considered, while 54.2% could face damage from all three disturbances. The SHAP (Shapley Additive exPlanations) methodology was applied to evaluate the importance of features on prediction and the nonlinear relationship between explanatory features and susceptibility to disturbance.Öğe A Comparative Analysis of UAV-RTK and UAV-PPK Methods in Mapping Different Surface Types(2021) Eker, Remzi; Alkan, Ece; Aydın, AbdurrahimThis study aimed to compare unmanned aerial vehicle (UAV) based real-time kinematic (RTK) and post-processing kinematic (PPK) methods via five approaches: an RTK-CORS method (M1), a short-baseline PPK method obtaining corrections from a GNSS base station (M2), and three long-baseline PPK methods that obtained corrections from the three Turkish RTK-CORS network TUSAGA-Aktif reference stations (M3: IZMI, M4: CESM, and M5: KIKA). The comparison was based on the accuracy of the corrected camera positions, the average error of the camera locations computed in the photo-alignment and optimization process, georeferencing errors of the models via nine GCPs based on four scenarios, and Root Mean Square (RMS) errors in the Z-direction for different surface types (i.e. roads, shadows, shrubs, boulders, trees, and ground). For the surface types of “ground”, “roads”, and “shrubs”, RMS error rates were obtained 10 cm lower than that of other surface types in all methods except M4. The greatest differences were obtained over trees and shadowed areas. The conclusion of these comparisons was that the lowest RMS error rate was determined on a solid textured surface. The consideration of mean RMS error regardless of surface type in such model comparisons is misleading.Öğe Comparison of Autonomous and Manual UAV Flights in Determining Forest Road Surface Deformations(2022) Eker, Remzi; Türk, Yılmaz; Aydın, AbdurrahimThe deterioration of the surface of forest roads is an important factor affecting the safe navigation of vehicles and traffic safety. In addition to traditional methods, automated methods are also used to determine the deterioration of the road surface. UAV systems, which are among the automated methods, are widely used to determine surface deformations with high accuracy. This study aimed to evaluate the advantages and disadvantages of two different flight modes of UAV, including autonomous flight and manual flight, in mapping road surface deformations. Within the scope of this study, the 50-meter section of the Type B forest road located in Kardüz Forest Management Chief (Düzce/Türkiye), was selected. For this study, first the pros and cons of the autonomous and manual flight data acquisition process were evaluated. Then, the photogrammetric data processing results were compared in terms of data size, with precision and accuracy. In addition, the deformation status on the surface within the selected road was determined using the average Z value differences obtained with two flight methods. The result of the study showed that, the number of images obtained from manual flights was 5.5 times higher than from autonomous flights and the flight time was taken four times longer. The average ground sampling distance of the orthophotos generated from two different light modes indicated that the manual flight mode provided seven times higher resolution than autonomous flight. Moreover, the results from the statistical tests for the two flight modes showed differences. When manual flights and autonomous flights are evaluated in terms of reducing the shadow effect, manual flights can be considered more advantageous. Furthermore, it was found that the dynamic mobility of erosion and accumulation on the road surface continued in time series in both flight methods.Öğe Forest mapping against rockfalls on a regional scale in Inebolu of Turkey(Istanbul Univ, Fac Forestry, 2017) Aydın, Abdurrahim; Eker, RemziDetermining areas where forest plantations provide protection against rockfall is significant in the prevention of disasters. In this paper, a case study is conducted in the Ozluce Forest District of Inebolu, Turkey. Potential rockfall source areas are firstly calculated and mapped via RollFree, which uses a digital elevation model as the only input. The rockfall travel distance is then identified using an empirical energy line angle to create propagation maps for different scenarios (using a set of four angles: 28 degrees, 32 degrees, 35 degrees, and 38 degrees). By marking the lower boundaries of propagation, the maximum run-out zone of a fallen block is determined as having a very low, low, medium, or high probability of occurrence (marking the lower boundaries of propagation). These propagation maps are then overlapped with a forest stand map to define areas where the forest provides a protective function against rockfall. According to propagation maps that indicate a high probability of occurrence, only 9% of the total forest area is found to be capable of playing a protective role, whereas for those determined as having a low probability of occurrence, 17% of the forest area provides a protective function.Öğe Future land use/land cover scenarios considering natural hazards using Dyna-CLUE in Uzungol Nature Conservation Area (Trabzon-NE Turkiye)(Springer, 2022) Aydın, Abdurrahim; Eker, RemziThis study aimed to determine past and potential future temporal and spatial changes in land use/land cover (LULC) and to evaluate its interactions with natural hazards (especially snow avalanches and rockfalls) in Uzungol Nature Conservation Area (Trabzon-NE Turkiye). The objectives were (1) to assess past LULC change over the last 60 years (1955-2015), (2) to simulate future LULC with Dyna-CLUE by 2035 and 2050 considering two different scenarios, and (3) to evaluate interactions of past and future LULC change with natural hazards. The analysis of past LULC change showed that over the last 60 years settlement areas increased to 51.03 ha converting fully from agricultural areas. According to the future LULC simulations, scenario 1 showed that settlements will expand from 68 ha in 2015 to 97.5 ha in 2035, and up to 126.5 ha in 2050 towards areas that are exposed to snow avalanches. Scenario 2 showed that these settlement areas will increase to 119.75 ha in 2035 and 137.75 ha in 2050. In addition, according to scenario 1 settlements that are exposed to rockfall hazard will change from 28 ha in 2015 to 24 ha in 2035 and 28.25 ha in 2050, whereas according to scenario 2 these areas will change to 26.25 ha in 2035 and 28.75 ha in 2050. This study showed how LULC dramatically changed since 1955 due to population growth and changes in consumption patterns in society, and it further showed potential changes in the future. It was concluded that an obligatory increase in settlements towards dangerous areas will be observed in the future.Öğe Fuzzy rule-based landslide susceptibility mapping in Yigilca Forest District (Northwest of Turkey)(Istanbul Univ, Fac Forestry, 2016) Aydın, Abdurrahim; Eker, RemziLandslide susceptibility map of Yigilca Forest District was formed based on developed fuzzy rules using GIS-based FuzzyCell software. An inventory of 315 landslides was updated through fieldworks after inventory map previously generated by the authors. Based on the landslide susceptibility mapping study previously made in the same area, for the comparison of two maps, same 8 landslide conditioning parameters were selected and then fuzzified for the landslide susceptibility mapping: land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature. Mamdani model was selected as fuzzy inference system. After fuzzy rules definition, Center of Area (COA) was selected as defuzzification method in model. The output of developed model was normalized between 0 and 1, and then divided five classes such as very low, low, moderate, high, and very high. According to developed model based 8 conditioning parameters, landslide susceptibility in Yigilca Forest District varies between 32 and 67 (in range of 0-100) with 0.703 Area Under the Curve (AUC) value. According to classified landslide susceptibility map, in Yigilca Forest District, 32.89% of the total area has high and very high susceptibility while 29.59% of the area has low and very low susceptibility and the rest located in moderate susceptibility. The result of developed fuzzy rule based model compared with previously generated landslide map with logistic regression (LR). According to comparison of the results of two studies, higher differences exist in terms of AUC value and dispersion of susceptibility classes. This is because fuzzy rule based model completely depends on how parameters are classified and fuzzified and also depends on how truly the expert composed the rules. Even so, GIS-based fuzzy applications provide very valuable facilities for reasoning, which makes it possible to take into account inaccuracies and uncertainties.Öğe Generating Avalanche Hazard Indication Map and Determining Snow Avalanche Protection Forests in Caykara-Trabzon (NE-Turkey)(Istanbul Univ-Cerrahpasa, 2022) Aydın, Abdurrahim; Eker, Remzi; Odabaşı, Yunus BarışIn this study, a GIS-based large-scale hazard indication map was generated for Caykara District (Trabzon, NE Turkey) by taking the forest into account in the determination of potential release zones. In addition, the forest stands with potential protection function (FS-PPF) were determined and mapped in terms of defined degrees of protection (high, moderate, moderate-low, low, and very low). In total, 5525 release zones covering 8446 ha were determined in Caykara District, whereas the areas exposed to avalanche hazards covered 22088 ha. In addition, 6629 ha of FS-PPF were mapped, 72% of which fell into the high FS-PPF protection class and included pure or mixed coniferous forest stands. Moreover, 22% of the entire FS-PPF mapped in the study area fell within the very low protection class. In terms of forest stand types, it was revealed that 54% of the FS-PPF against snow avalanches consisted of pure coniferous or coniferous mixed with other tree species, 24% were mixed coniferous and broad-leaved tree species (coniferous tree species being predominant), 11% were mixed broad-leaved and coniferous tree species (broad-leaved tree species being predominant), and 11% were pure broadleaved tree species or broad-leaved species mixed with others. In this study, we have proposed a procedure to depict the different degrees of protection provided by the FS-PPF against snow avalanches in order to facilitate functional planning goals in Turkish forestry. The results showed that the FS-PPF map could be integrated within forest management plans and could be used as a base in the planning of silvicultural operations.Öğe Heyelan ve kar kaynaklı doğal afetlerin izlenmesi ve haritalanmasında modern uzaktan algılama tekniklerinin kullanılması(Düzce Üniversitesi, 2018) Eker, Remzi; Aydın, AbdurrahimUzaktan algılama tekniklerinin doğal afetlerde kullanımı teknolojik ve bilimsel gelişmelere bağlı olarak artmaktadır. Bu nedenle bu çalışmada insansız hava aracı (İHA) sistemleri, lazer tarama sistemleri (hava ve yersel), Sentetik Açıklıklı Radar (SAR) interferometri (InSAR) ve optik sayısal fotogrametri modern uzaktan algılama tekniklerinin üç ayrı ülkede (Türkiye, Avusturya ve İsviçre) yer alan beş ayrı çalışma alanında heyelan ve kar/çığ çalışmalarına yönelik uygulamaları yapılmıştır. Avusturya (Gallenzerkogel ve Gschliefgraben heyelanları) ve Türkiye'de (Himmetoğlu ve Devrek heyelanları) ikişer adet alanda heyelan çalışması ve İsviçre'de (Dischma vadisi) kar derinlik haritalama ve kar erimesinin izlenmesi çalışması yapılmıştır. Avusturya'daki heyelan sahalarında İHA ve hava lazer tarama verileri ile heyelan izleme, Türkiye'deki heyelan sahalarında InSAR zaman serileri (Persistent Scatterers Interferometry, PSI ve Small Baseline Subset, SBAS analizleri), İHA ve optik sayısal fotogrametri teknikleri ile heyelan deformasyon haritalama, İsviçre'de ise İHA ve yersel lazer tarama verileri ile kar derinlik haritalama ve kar örtüsü erimesinin izlenmesi çalışması yapılmıştır. Gschliefgraben heyelan alanında sadece hava lazer tarama verisi ile nokta bulutu karşılaştırma teknikleri ve sayısal görüntü korelasyon teknikleri ile heyelan deformasyonlarının ve yerdeğiştirme alanlarının belirlenmesi çalışması yapılmıştır. Gallenzerkogel heyelan alanında yaklaşık bir yıllık dönem için üç ayrı İHA verisi ve heyelan öncesi hava lazer tarama verisi kullanılarak hem Sayısal Yükseklik Modeli (DEM) farkları hem de modern nokta bulutu karşılaştırma algoritması olan M3C2 yöntemi kullanılarak heyelan izleme çalışması yapılmıştır. Dischma vadisinde ise yaklaşık bir aylık dönemde temin edilen beş ayrı İHA ve yersel lazer tarama (TLS) verisi ile kar erimesinin izlenmesi çalışması yapılmıştır. İHA ve TLS verileri zaman serileri kullanılarak kar erimesine ilişkin ilk örnek bir çalışma yapılmıştır. Zonguldak ili Devrek ilçesi Karşıyaka mahallesi heyelan alanında eski tarihli hava fotoğrafları ve İHA verileri ile birlikte ERS-1/2, Envisat ASAR ve Sentinel-1 C band SAR görüntüleri ile uzun dönemli (1992-2015) deformasyon haritalama için PSI analizi yapılmıştır. Bolu ili Göynük ilçesi Himmetoğlu köyü heyelan alanında ise İHA verisi ile birlikte, Sentinel-1 C band SAR görüntüleri ile PSI ve SBAS analizleri yapılarak yüzey deformasyonlarını izleme çalışması yapılmıştır. Gerçekleştirilen örnek uygulamalar ile doğal afetlerde gelişmiş uzaktan algılama tekniklerinin kullanım imkânları değerlendirilmiştir.Öğe İnsansız hava aracı ile orman yolu kazı ve dolgu hacimlerinin belirlenmesi: Bolu-Taşlıyayla örneği(2022) Türk, Yılmaz; Aydın, Abdurrahim; Canyurt, Harun; Eker, RemziOrmancılıkta üretim aktivitelerinin planlanmasında ve orman yollarının tasarlanmasında, konumsal verilere dayalı karar destek sistemleri bazı ülkelerde yaygın olarak kullanılmaktadır. Son yıllarda, ormanlık alanların yüksek çözünürlükte ve doğrulukta sayısal yükseklik modellerinin (SYM) üretilmesinde İnsansız Hava Araçları (İHA) kullanılmaktadır. İHA ile iş yükü azaltılmakta, zaman kazanımı ve daha hassas veriler elde edilmektedir. Orman yolu yaklaşık maliyet ve hakediş cetvellerinin hazırlanmasında iş yükü fazla olmaktadır. Ayrıca yol yapımı bittikten sonra yüklenici firmaya ödenecek ücret hakediş (olur) cetvellerinde bulunan kesin maliyete göre belirlenmektedir. Bu çalışmanın amacı İHA teknolojisi ile hakediş orman yolu kazı ile dolgu hacimleri belirlenmiş ve zemin klasları da incelenmiştir. Seben Orman İşletme Müdürlüğü sınırları içerisinde yer alan Taşlıyayla Orman İşletme Şefliği 001 kodlu orman yolunun 100 metrelik kısmı çalışamaya konu edilmiştir. Çalışmaya konu yolun yapımından önce ve sonra İHA (drone) ile uçuşlar otonom olarak gerçekleşmiştir. Çalışma sonucunda, hakediş 384,23 m3 kazı ile 188,30 m3 dolgu hacmi ve 893,84 m2 kazı alanı ile 447,85 m2 dolgu alanı bulunmuştur. Ayrıca alanda toprak ve küskülük zemin klasları tespit edilmiştir.Öğe Long-term retrospective investigation of a large, deep-seated, and slow-moving landslide using InSAR time series, historical aerial photographs, and UAV data: The case of Devrek landslide (NW Turkey)(Elsevier, 2021) Eker, Remzi; Aydin, AbdurrahimThis study presents a successful combination of different remote sensing data used in a long-term retrospective investigation of a large and destructive deep-seated, slow-moving landslide reactivated on 16 July 2015 in Devrek District (Zonguldak, Turkey). To this aim, Synthetic Aperture Radar (SAR) data were used for Interferometric SAR (InSAR) time-series analysis together with unmanned aerial vehicle (UAV) images and aerial photographs for digital photogrammetric analysis. The SAR dataset was divided into three sub-periods: 1) 1992-2001 for ERS-1 and ERS-2 satellites; 2) 2003-2010 for Envisat ASAR; and 3) 2014-2015 for Sentinel-1. Persistent Scatterers Interferometry (PSI) was applied for each sub-period. In total, 20 aerial photographs, dating from as early as 1944, were obtained, along with data from a UAV flight mission conducted on 23 June 2018. The historical aerial photographs revealed that the region has had a landslide problem since the 1940s. Between 1944 and 2018, a noticeable expansion of the settlement area towards the toe of the landslide was also observed. Aerial photographs (1984 and 2011) and UAV images (2018) were used to map landslide deformations using the M3C2 algorithm. Due to the high number of modelling errors, the 1984 and 2011 aerial photographs did not allow mapping of the landslide deformations. However, it was possible to determine them for the periods of 2011 and 2018. The M3C2 results between 2011 and 2018 were also compared to the PSI results, which were quite compatible with those obtained via photogrammetric methods. Moreover, two orthophotos belonging to 2011 and 2018 were used to reveal the horizontal displacement of buildings caused by the landslide. As a result, the complete investigation of the landslide performed in this study may serve to facilitate additional plans and strategies for prevention and mitigation of potential reactivations in the future.Öğe Monitoring of Snow Cover Ablation Using Very High Spatial Resolution Remote Sensing Datasets(Mdpi, 2019) Eker, Remzi; Bühler, Yves; Schlögl, Sebastian; Stoffel, Andreas; Aydın, AbdurrahimThis study tested the potential of a short time series of very high spatial resolution (cm to dm) remote sensing datasets obtained from unmanned aerial system (UAS)-based photogrammetry and terrestrial laser scanning (TLS) to monitor snow cover ablation in the upper Dischma valley (Davos, Switzerland). Five flight missions (for UAS) and five scans (for TLS) were carried out simultaneously: Four during the snow-covered period (9, 10, 11, and 27 May 2016) and one during the snow-free period (24 June 2016 for UAS and 31 May 2016 for TLS). The changes in both the areal extent of the snow cover and the snow depth (HS) were assessed together in the same case study. The areal extent of the snow cover was estimated from both UAS- and TLS-based orthophotos by classifying pixels as snow-covered and snow-free based on a threshold value applied to the blue band information of the orthophotos. Also, the usage possibility of TLS-based orthophotos for mapping snow cover was investigated in this study. The UAS-based orthophotos provided higher overall classification accuracy (97%) than the TLS-based orthophotos (86%) and allowed for mapping snow cover in larger areas than the ones from TLS scans by preventing the occurrence of gaps in the orthophotos. The UAS-based HS were evaluated and compared to TLS-based HS. Initially, the CANUPO (CAracterisation de NUages de POints) binary classification method, a proposed approach for improving the quality of models to obtain more accurate HS values, was applied to the TLS 3D raw point clouds. In this study, the use of additional artificial ground control points (GCPs) was also proposed to improve the quality of UAS-based digital elevation models (DEMs). The UAS-based HS values were mapped with an error of around 0.1 m during the time series. Most pixels representing change in the HS derived from the UAS data were consistent with the TLS data. The time series used in this study allowed for testing of the significance of the data acquisition interval in the monitoring of snow ablation. Accordingly, this study concluded that both the UAS- and TLS-based high-resolution DSMs were biased in detecting change in HS, particularly for short time spans, such as a few days, where only a few centimeters in HS change occur. On the other hand, UAS proved to be a valuable tool for monitoring snow ablation if longer time intervals are chosen.Öğe Ormanların heyelan oluşumu üzerindeki etkileri(2014) Eker, Remzi; Aydın, AbdurrahimÖzellikle dağlık bölgelerde ortaya çıkan stabilite problemlerinin olumsuz sonuçlarından dolayı, heyelanlar üzerindeki etkileri bakımından ormanların ve ormancılık faaliyetlerinin önemi ormanların koruma fonksiyonu ile birlikte giderek artmaktadır. Ormanlar ve ormancılık faaliyetleri (ağaç kesimi, yol inşası gibi) heyelan kaynaklı stabilite problemleri açısından literatürde çeşitli yönleriyle çalışılmıştır. Ancak orman örtüsünün mevcudiyetinin etkileri ile ormancılık faaliyetlerinin heyelanlar üzerindeki etkilerinin nasıl ve ne yönde olduğuna dair yapılan çalışmaların temel alınarak tartışıldığı bir derleme çalışmaya ihtiyaç olduğu dikkat çekmektedir. Bu makalede bu ihtiyaç göz önüne alınarak orman-heyelan ve ormancılık-heyelan konularında uluslararası düzeyde yapılan çalışmalar incelenerek tartışılmıştır.Öğe PREDICTION OF DAILY STREAMFLOW USING JORDAN-ELMAN NETWORKS(Parlar Scientific Publications (P S P), 2012) Aydın, Abdurrahim; Eker, RemziThe prediction of daily streamflow is required for future planning in water resource activities. This study presents the application of the Jordan-Elman network with the Levenberg-Marquardt algorithm. Prediction was made by using flow data of gauging station no. 2122 on Birs River, Switzerland between 2000 and 2010. The data, 4018 days in total, were used as calibration and validation sets for the chosen Jordan-Elman Neural Network architecture. Of the data obtained, 2922 days (1st January 2000 - 31st December 2007) were reserved for calibration, and remaining data were used for validation. In total, six different models were developed, based on the prediction of current flow from up to six-days-ahead flows. Mean square error (MSE), Nash-Sutcliffe Sufficiency Score (NSSS) and coefficient of correlation (R-value) were used as performance criteria. Model M-6 (six-days- ahead flows) gave the best results, with respect to all prediction performance criteria.Öğe A PRIMARY TEST RESULTS OF A HANDHELD MOBILE LASER SCANNER IN EXTRACTION OF TREE PARAMETERS(Copernicus Gesellschaft Mbh, 2022) Eker, Remzi; Uçar, Z.; Aydın, A.Sustainable forest planning and management require accurate and precise information about the estimation of forest resources. In particular, two tree parameters are very important among the others: diameter-at-breast height (DBH) and height that are used to estimate the volume and biomass of the tree. With the development of Remote Sensing (RS), information about the tree parameters can be acquired in more accurately and precisely with laser scanning technology. In this study, a Handheld Mobile Laser Scanner (HMLS), called TORCH, was tested for extracting tree parameters with 3D Forest software. The TORCH uses the SLAM (Simultaneous Localization and Mapping) algorithm to locate the scanner in an unknown environment and register the obtained 3D point clouds. Estimated DBH and height parameters from HMLS data extracted using 3D Forest software were compared with the field measurements (i.e., reference data). The preliminary results of the study showed that estimated DBH from HMLS data were relatively higher than ground measurement, while estimated height from point clouds data was slightly lower than the reference data. The continuous improvement in mobile laser scanners will improve the success of the devices while acquiring 3D structural information of tree parameters and reducing the cost and time spent in forest inventory.Öğe Remote sensing and GIS-based inventory and analysis of the unprecedented 2021 forest fires in Türkiye's history(Springer, 2024) Eker, Remzi; Cinar, Tunahan; Baysal, Ismail; Aydin, AbdurrahimIn the summer of 2021, T & uuml;rkiye experienced unprecedented forest fire events. Throughout that fire season, a total of 291 fire incidents, covering an area of 202,361 hectares, dominated the public agenda. This study aimed to document and analyze the 30 large fires (affecting over 100 hectares) of 2021 using remote sensing and GIS techniques. A comprehensive fire database was established, encompassing information on burned areas, fire severity, and fuel types, determined from forest-stand types and topographical properties including slope, elevation, and aspect (in eight directions). Sentinel-2 satellite images were utilized to calculate dNBR values for assessing fire severity, analyzed in the Google Earth Engine platform. Three GIS-integrated Python scripts were developed to construct the fire database. In total, 164,658 hectares were affected by these large fires, occurring solely in three regions of T & uuml;rkiye: the Mediterranean, Aegean, and Eastern Anatolian. The majority of the burned area was situated in the Mediterranean region (59%), with only 3% in Eastern Anatolia. The burned areas ranged from a minimum of 150 hectares to a maximum of 58,798 hectares. Additionally, 679 hectares of residential areas and 22,601 hectares of agricultural land were impacted by the fire events. For each fire, 21 fuel types and their distribution were determined. The most prevalent fire-prone class, Pure Turkish pine species (Pr-& Ccedil;z), accounted for 59.56% of the total affected area (99,516 hectares). Another significant fire-prone pine species, the Pure Black pine species (Pr-& Ccedil;k), covered 7.67% (12,811 hectares) of the affected area. Fuel types were evaluated by considering both forest-stand development stages and canopy closure. Regarding forest-stand development stages, the largest area percentage burned belonged to the Mature class (26.48%).Öğe Tracking deformation velocity via PSI and SBAS as a sign of landslide failure: an open-pit mine-induced landslide in Himmetoğlu (Bolu, NW Turkey)(Springer, 2024) Eker, Remzi; Aydin, Abdurrahim; Gorum, TolgaA destructive landslide occurred in Himmetoglu village in Goynuk District (Bolu, NW Turkey) caused by open-pit coal mining activities. Field observations after the landslide failure and interviews with villagers motivated us to question the possibility of using satellite SAR data to detect precursory signs of failure with regard to deformation velocity. In this study, first, landslide deformations were mapped by applying the digital elevation model (DEM) of Difference (DoD) method using DEMs from aerial photography and UAV data. However, the primary aim was to track deformation velocity as a sign of landslide failure with persistent scatterers interferometry (PSI) and small baseline subset (SBAS) methods from Sentinel-1A data. For the SBAS, the deformation velocity for ascending and descending orbits varied between - 12 and 39 mm year-1 and between - 24 and 6 mm year-1, respectively. For the PSI, the deformation velocity for ascending and descending orbits varied between - 16 and 31 mm year-1 and between - 18 and 20 mm year-1, respectively. PSI and SBAS resulted in sharply changing line-of-sight displacement rates, which were interpreted as slope failure signs, from three months prior to the landslide. In addition, higher deformation velocities were observed in locations closer to landslide crack as expected. Based on our findings, we concluded that SAR interferometric time-series analysis have the makings of being used as a suitable approach in early discerning and avoiding potential slope failures in open-pit mining areas, when it is made carefully by observing the progress in mining activities by considering the other factors such as rainfall and earthquakes.
