Ismail Colkesen

Gebze Technical University | GYTE · Department of Geodetic and Photogrammetric Engineering

Poplars (Populus sp.), a tree that grows rapidly species, are significant as industrial forest products. The delineation and monitoring of poplar cultivated areas are invaluable for decision-making processes. With the remote sensing technology, accurate detection of poplar planted areas could be determined much faster, more economically, and with m...

Ayçiçeği, dünyanın farklı bölgelerinde yaygın olarak yetiştirilen besin, ekonomik ve tıbbi değeri yüksek olan önemli bir tarımsal üründür. Ülkemiz için de önemli yağlı tohum kaynaklarından biri olan ayçiçeğinin tespiti ve izlenmesi yüksek doğrulukta verim tahminlemesi ve sürdürülebilir üretim planlaması açısından büyük önem arz etmektedir. İnsansız...

Unmanned aerial vehicle (UAV) technology is capable of delivering high spatial, spectral, and temporal resolution data that facilitate the monitoring of crops over time and provide crucial timely and quantifiable information about the yield, growth, and health of crops. Accurate identification of sunflower crops from UAV orthomosaics is essential f...

The increasing demand for digital agriculture necessitates agricultural productivity and environmental sustainability advancements. Unmanned Aerial Vehicle (UAV)-based remote sensing technologies offer valuable insights for enhancing crop yields and optimizing resource use compared to traditional ground-based data collection methods. Processing the...

As valued members of forest ecosystems, fast-growing tree species are of great importance for protecting natural forests, fulfilling the demand for raw wood material, and preserving biodiversity and ecosystem services. In this regard, multi-temporal monitoring and evaluation of poplar planted areas are essential for decision makers and planners to...

One of the main threats to freshwater resources is pollution from anthropogenic activities such as rapid urbanization and excessive agricultural nutrient runoff. Remote sensing technologies have been effectively used in monitoring and mapping rapid changes in the marine environment and assessing the overall health of freshwater ecosystems. The main...

Floods are one of the most significant natural disasters, leading to substantial material damage Floods are one of the most significant natural disasters, causing both material damages and loss of life. Scientific studies indicate that the intensification of the hydrological cycle due to the effects of climate change can lead to excessive rainfall...

Modern remote sensing technologies play a critical role in agricultural applications, especially in recent years with the advances in unmanned aerial vehicle (UAV) technologies and artificial intelligence. Remotely sensed imagery is an invaluable data source for sustainable agricultural activities, such as precision agriculture. This study evaluate...

In spring 2021, mucilage, also known as “sea snot” or “sea saliva” has been intensely observed in the Sea of Marmara and has reached a threatening level. Due to the declining water quality, many marine organisms have perished, the fishing industry and tourism have been adversely affected. In this paper, a detailed investigation was carried out to a...

Lately, unmanned aerial vehicle (UAV) become a prominent technology in remote sensing studies with the advantage of high-resolution, low-cost, rapidly and periodically achievable three-dimensional (3D) data. UAV enables data capturing in different flight altitudes, imaging geometries, and viewing angles which make detailed monitoring and modelling...

As one of the most important members of the freshwater ecosystem, lakes have been under pressure in recent years, mainly due to climate change, population growth and anthropogenic activities, which adversely affect water quality and cause several environmental disasters such as harmful algal blooms. Remote sensing technologies have been widely used...

In recent years, detailed monitoring of different vegetation classes by using modern remote sensing technologies has become one of the essential issues for smart agriculture activities. In this study, using three advanced machine learning algorithms, namely canonical correlation forest (CCF), rotation forest (RotFor) and support vector machines (SV...

Ağaç sayımı, ürün gelişim takibi ve verim tahmini gibi birçok tarımsal uygulama için önemli veri kaynağı durumunda olan uzaktan algılama teknolojileri özellikle son yıllarda insansız hava aracı (İHA) teknolojileri ve yapay zeka alanındaki ilerlemeler ile birlikte hassas tarım uygulamalarında önemli bir rol oynamaktadır. Bu çalışmada, yüksek çözünür...

Depremler, insanlığı ve arazi mülkiyetini tehdit eden en yıkıcı doğal afet türlerinden biridir. Bu afet geçen yüzyılda dünya çapında yaklaşık 2 milyon insanın ölümü ve yüz milyarlarca dolarlık ekonomik kayıp ile sonuçlanmıştır. Deprem etkilerinin belirlenmesi ve analizinde uzaktan algılama teknolojisi ve hava ve uzay kaynaklı temel ürünlerin kullan...

The rapid increase in urbanization and industrialization has brought about a boosting effect in environmental pollution, causing a decrease in biological diversity and a deterioration in the ecological balance. As a result, the number of environmental disasters drastically increases every year. One of the most significant of these disasters is rece...

Poplars (Populus sp.), a member of fast-growing and short-lived tree species, have been widely planted since ancient times. Identification and mapping of poplar planted areas on global and local scales, as well as the automatic crown detection and counting of individual poplar trees in a given area provide valuable information to decision-makers in...

Maize is one of the most important staple crops worldwide for the agricultural sector, including animal production, human consumption and other industrial purposes. Due to its vital role in human life and other industrial purposes, it is essential to monitor the phenological development of maize for sustainable agriculture goals at a local and glob...

Kentleşme ve sanayileşmedeki hızlı artış, çevre kirliliğini artırıcı bir etki yaratarak biyolojik çeşitliliğin azalmasına ve ekolojik dengenin bozulmasına neden olmaktadır. Buna bağlı olarak, çevre felaketlerinin sayısı her yıl önemli ölçüde artmaktadır. Bu afetlerin en önemlilerinden biri, Türkiye'nin Marmara Denizi'nde yakın zamanda meydana gelen...

Marine mucilage that threatens marine habitats is one of the natural disasters, mainly resulting from global warming and marine pollution. Monitoring sea surface mucilage formations and mapping their spatial distributions provide valuable information to the local authorities and decision-makers in developing prevention and rehabilitation strategies...

Mısır bitkisi binlerce yıldır pek çok ülkede tarımı yapılan önemli bitkilerden bir tanesidir. Ülkemizde arpa ve buğdaydan sonra yer alan ve tarımı yapılan bir bitkidir. Hayvan yemi ve insan gıdası olarak kullanılmakta ve sanayide ham madde ihtiyacını karşılamaktadır. Ekonomik ve gıda arzı açılarından bakıldığında mısır bitkisinin fenolojik gelişimi...

Bu çalışmada nesne tabanlı sınıflandırma yaklaşımı ile görüntü sınıflandırma işleminde temel sorunlardan birisi olan yetersiz bölütleme (under segmentation) sorununun çözümü noktasında piksel ve nesne tabanlı sınıflandırma tekniklerinin bir arada kullanılmasını esas alan eşik tabanlı hibrit sınıflandırma yaklaşımı önerilmiştir. Belirtilen tekniğin...

Forest resources are the primary components of the ecosystem environment. Poplars (Populus sp.), a member of the fast-growing trees, are one of the most productive forest tree species for industrial production thanks to their desirable traits comprising rapid growth, hybridization ability, and ease of propagation. Determining poplar cultivated area...

The objective determination of real estate values with current technological approaches has an important role in effective and sustainable real estate management plans. Mass appraisal is the process of valuing a large number of real estate simultaneously instead of evaluating the real estate individually for reducing the loss in terms of time and...

Son yıllarda hızlı gelişen türler ve klonların belirli üretim teknik ve sistemlerle yetiştirilmesi, odun hammadde arzının karşılanması noktasında büyük öneme sahiptir. Bu bağlamda, dünyada ve Türkiye’de kavak türleri ve klonları kullanılarak geniş ölçekte endüstriyel plantasyonlar oluşturulmaktadır. Türkiye’de yetiştirilen kavak türlerinin ayrımı,...

The issue of accurate identification of the Earth's surface features from the very high spatial resolution (VHSR) satellite imagery has been a major area of interest within the field of remote sensing. Vegetation indices obtained from the remotely sensed imagery have long been used as a simple but effective tool for quantitative and qualitative ide...

Hızla büyüyen bir ağaç türü olan kavak, Türkiye'de büyük endüstriyel ve ticari öneme sahiptir. Bu nedenle, kavak ağaçlarının diğer bitki türlerinden ayırt edilmesi önemli bir araştırma konusudur. Uzaktan algılama teknolojileri, zaman ve maliyet açısından kavak ekili alanları, geleneksel yaklaşımlardan daha verimli bir şekilde tespit etme yeteneğine...

Recent advances in airborne and space-based remote sensing technologies and a rapid increase in the use of machine learning (ML) techniques in digital image processing applications have led to a renewed interest in the classification of satellite imagery. Decision-tree based ensemble learning (EL) algorithms, one of the popular ML techniques, have...

Climate change and global warming along with human activities have caused abrupt changes in the atmosphere, marine, and terrestrial ecosystems. One of these changes is the rising number of mucilage events in marine ecosystems. During the recent two decades, mucilage blooms have begun to appear more frequently in the Sea of Marmara in Turkey, surrou...

Forest fires cause aerosol emissions and biomass burning that pose major threats to the ozone layer. The precise estimation of burned area with the degree of burn severity plays a critical role to investigate the impacts of fire on forests. Burn severity analysis using remotely sensed data has become popular in the last decade for post-fire detecti...

The production of land use and land cover (LULC) maps using UAV images obtained by RGB cameras offering very high spatial resolution has recently increased. Vegetation indices (VIs) have been widely used as an important ancillary data to increase the limited spectral information of the UAV image in pixel-based classification. The main goal of this...

Unmanned air vehicle (UAV) became an alternative airborne remote sensing technique, due to providing very high resolution and low cost spatial data and short processing time. Particularly, optical UAVs are frequently utilized in various applications such as mapping, agriculture, and forestry. Especially for precise agriculture purposes, the UAVs we...

The aim of the current study was to evaluate the performance of patch-based classification technique in land use/land cover classification and to investigate the effect of patch size in thematic map accuracy. To reach desired goal, recently proposed ensemble learning classifiers (i.e., XGBoost and CatBoost) were utilized to classify produced image...

The aim of this study is to analyze the forest fires, occurred in Manavgat, Bodrum and Marmaris districts in July and August 2021, using remote sensing techniques with multi-temporal optical satellite images and to determine the boundaries of the damaged areas. ESA’s Sentinel-2 images acquired before, during and after fires were obtained for the an...

Having reliable thematic information representing the Earth’s surface objects is one of the main input data required for many applications in agricultural, forestry and environmental sciences. As well as being the lungs of the world and their crucial role in carbon cycle, forests are a one of the valuable natural resources for many daily supply pro...

In the last decades, the unmanned aerial vehicle (UAV) has become one of the most demanded remote sensing techniques with the advantage of very high resolution and accurate data derived from low flight altitudes. Due to increased demand in various applications, the technological level of UAVs is developing day by day. For accurate orientation of th...

Unmanned air vehicle (UAV) has become an indispensable mobile mapping technology of remote sensing thanks to offering low cost and high resolution spatial data. Particularly, camera equipped optical UAVs are large in demand by land-related professions, including mapping, agriculture and forestry. Regarding the requirements, the technological level...

In recent years, there has been a markedly increase in temperatures of the Earth's surface including oceans and seas due to global warming. Mucilage, or sea saliva observed in the inland seas and bays is one of the destructive results of this phenomenon. Mucilage formations have been widely observed in May 2021 in the Marmara Sea, especially in...

Spectral libraries can be used for the analysis of the spectral properties of tree species, as well as for the detection and mapping of tree species through remotely sensed data. This study aims to statistically analyze the performance of atmospheric correction methods in calibrating ground spectral measurements with the Sentinel-2 imagery. In this...

Global warming threatens ecosystems through rising temperatures, increasing sea levels, drought, and extreme weather conditions. The natural balance of seas and oceans is also at stake with recent outbreaks of mucilage events all over the world. The mucilage phenomenon, which has been frequently observed in the Adriatic and Tyrrhenian seas, has tak...

Küresel ısınmanın karasal alanların yanında denizel alanlarda da doğal dengeyi bozan etkileri bulunmaktadır. Bu bozucu etkilerden biri olan müsilaj ya da deniz salyası, iç deniz ve körfezlerde ortaya çıkan doğal felaketlerden biridir. Müsilaj, Marmara Denizi’nde 2021 yılının Mayıs ayından itibaren hızlı bir şekilde yayılarak akıntı ve rüzgâr etkisi...

Global warming has effects that disrupt the natural balance in marine areas as well as terrestrial areas. One of these disruptive effects, mucilage, or sea saliva, is one of the natural disasters in the inland seas and bays. Mucilage has been spreading rapidly in the Sea of Marmara since May 2021 and has been effective in the Gemlik and Izmit bays,...

The production of land use / land cover (LULC) maps using UAV images obtained by RGB cameras that offer high spatial resolution has recently increased. Vegetation indexes (VIs) are one of the important tools used to increase the limited spectral information of the UAV image in pixel-based classification. The aim of this study is to examine the effe...

Son dönemde Marmara Denizi’nde yoğunlukla gözlemlenen; görsel, ekolojik ve ticari yönlerden sebep olduğu olumsuz etkileri nedeniyle kamuoyunun gündemine oturan deniz salyası sadece bugün değil geleceğimizi için de tehlike oluşturuyor. Bu bağlamda Türkiye Bilimler Akademisi Başkanlığı, konusunda uzman bilim insanları bu çevre sorununu değerlendirmel...

The poplar trees used in peeling, packaging, furniture, fiber chip, cellulose industry and construction sector are one of the most significant wood supply sources of the countries. Monitoring the development stage of cultivated poplar trees, determination of their boundaries and mapping their fields in cheaper and more accurate ways plays an import...

In this study, the performances of random forest (RF), rotation forest (RoF), and canonical correlation forest (CCF) algorithms were compared and analyzed for classification of hyperspectral imagery. For this purpose, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Indian Pine (IP), the Reflective Optics System Imaging Spectrometer Univ...

Landslides have been qualified as a one of the most destructive natural disasters in history that cause damage to man-made structures and negatively affect human life in many ways. Due to its great importance for hazard management, producing accurate and up- to-date landslide susceptibility maps is essential for many local- to global-scale studies....

The primary aim of this research paper is to develop an easy-to-use tool package called Landslide Susceptibility Mapping Tool Pack (LSM Tool Pack) for producing landslide susceptibility maps based on integrating R with ArcMap Software. The proposed tool contains 5 main modules namely: (1) Data Preparation (DP), (2) Feature (Factor) Selection (FS),...

The main purpose of this study is to propose an interoperable land valuation data model for residential properties as an extension of the national geographic data infrastructure (GDI) and to make mass valuation process applicable with the use of machine learning approach. As an example, random forest (RF) ensemble algorithm was implemented in Pendi...

The poplar species in the forest ecosystems are one of the most valuable and beneficial species for the society and environment. Conventional methods require high cost, time and labor need, and the results obtained vary and are insu˚cient in terms of achieved accuracy level. Determination of poplar cultivated fields and mapping of their spatial sit...

Forests are of great importance for the sustainability of the ecosystem as well as for the mankind. The poplar species in the forest ecosystems are one of the most valuable and beneficial species for the society and environment. Turkey is a very rich country in terms of cultivated poplar species. The determination of poplar areas in Turkey is usual...

Forest fires give great harms to the ecosystem and wildlife by destroying the forested lands and threaten the lives and properties. Due to climate change and global warming, forest fires have increased significantly in recent years. Therefore, reliable and up-to-date information about the location and extent of the burned area is essential for deci...

Parallel to the rapid technological advances, up-to-date remote sensing platforms and sensors have made it possible to observe the Earth's surface features at a higher spatial and spectral resolution. The WorldView-2 (WV-2) imagery has been effectively used for the detailed mapping of agricultural crop-type types in many studies. The selected area...

Landslide susceptibility mapping (LSM) is a major area of interest within the field of disaster risk management that involves planning and decision-making activities. Therefore, preparation of dataset, construction of predictive model and analysis of results are considered to be important stages for effective and efficient disaster management in LS...

Up to now, numerous classification methods have been developed to increase the classification accuracy of satellite images. In recent years, ensemble learning algorithms have been effectively used due to their success in classifying hyperspectral data having hundreds of spectral bands with similar spectral properties. Ensemble learning also known a...

In recent years, instead of traditional pixel-based classification approach, object-based classification approach is preferred for especially classification of the high spatial resolution satellite imagery. Determination of the optimal scale parameter identifying image object size for segmentation process aiming to combine pixels having similar cha...

Real estate valuation is the process of determining the value of the real property by examining environmental and social factors related to the real property with the quality and benefit information. Real estate valuation is actively used in taxation, expropriation, privatization, insurance and finances applications. In Turkey, legislation about re...

Machine learning techniques have been increasingly employed for solving many scientific and engineering problems. These data driven methods have been lately utilized with great success to produce landslide susceptibility maps. They give promising results particularly for mapping large landslide prone areas with limited geotechnical data. This chapt...

In parallel to the increasing accessibility of high resolution imagery, object-based image analysis (OBIA) has recently become a hot topic in remote sensing. Segmented objects significantly reduce the high-dimensionality and low-training size problems for classification process. On the other hand, Estimation of Scale Parameter (ESP-2) tool, which i...

In recent years, ensemble learning methods have become popular in landslide susceptibility mapping (LSM) with varying degrees of success. Within classifier ensemble concept, decision tree based ensemble learners such as random forest (RF) (i.e. decision forest) and rotation forest (RotFor) have gained a great interest due to their robustness agains...

With the increase in spatial resolution of recent sensors, object-based image analysis (OBIA) has gained importance for producing detailed land use maps. One of the main advantages of OBIA is that a variety of spectral, spatial and textural features can be extracted for the segmented image objects that are later utilized in classification. However,...

Object-based image analysis (OBIA) has attained great importance for the delineation of landscape features, particularly with the accessibility to satellite images with high spatial resolution acquired by recent sensors. Statistical parametric classifiers have become ineffective mainly due to their assumption of normal distribution, vast increase i...

In sustainable land development concept, primary factor is to obtain reliable and accurate information about land and to manage all this information efficiently. Definitive and reliable information about land and real property promote the geographical enablement and efficient information management which leads to achieve a sustainable development....

Classifying spectrally similar crop types in fragmented landscapes is a difficult task due to the low spectral and spatial resolution of satellite imagery. The objective of this study is twofold: (I) to evaluate the performance of a recent ensemble methodology, namely canonical correlation forest (CCF), and (ii) to investigate the potential of rece...

Having accurate and reliable thematic information is essential for many global and local scale studies. Producing thematic maps representing different physical characteristics of the Earth’s surface by means of image classification has been one of the most concentrated issues in remote sensing. Up to now, many classification algorithms have been pr...

OZET: Doğru ve güvenilir tematik bilgiye sahip olmak küresel ve yerel ölçekli birçok çalışma için esastır. Uydu görüntülerinin sınıflandırılmasıyla yeryüzünün farklı fiziksel özelliklerini temsil eden tematik haritaların üretilmesi uzaktan algılamada en yoğun çalışma konularından birisidir. Bu amaçla günümüze kadar birçok sınıflandırma algoritması...

Logistic model tree (LMT), a new method integrating standard decision tree (DT) induction and linear logistic regression algorithm in a single tree, have been recently proposed as an alternative to DT-based learning algorithms. In this study, the LMT was applied in the context of pixel- and object-based classifications using high-resolution WorldVi...

Ozet Son yıllarda, metre altı mekânsal çözünürlük sağlayan yüksek çözünürlüklü uydu görüntülerinin varlığı ile birlikte sınıflandırma işlemi geleneksel piksel-tabanlı görüntü analizinden obje-tabanlı görüntü analizine yönelmiştir. Herhangi bir sınıflandırma probleminde olduğu gibi, uygun bir sınıflandırma algoritmasının seçilmesi obje-tabanlı temat...

Günümüzde, hiperspektral görüntülerin miktarındaki artışa paralel olarak nesne-tabanlı sınıflandırma yaklaşımı arazi kullanımı ve arazi örtüsü sınıflarının belirlenmesinde daha önemli bir hale gelmiştir. Hiperspektral görüntülerin yüksek boyutlu veri içermesi ve genellikle sınırlı sayıda eğitim verisi bulunmasından dolayı, istatistik tabanlı parame...

OZET Günümüzde, hiperspektral görüntülerin miktarındaki artışa paralel olarak nesne-tabanlı sınıflandırma yaklaşımı arazi kullanımı ve arazi örtüsü sınıflarının belirlenmesinde daha önemli bir hale gelmiştir. Hiperspektral görüntülerin yüksek boyutlu veri içermesi ve genellikle sınırlı sayıda eğitim verisi bulunmasından dolayı, istatistik tabanlı p...

With the availability of high resolution satellite image, object-based image analysis has gained considerable importance for producing detailed land use and land cover maps. One of the main advantages of the object-based image analysis is that it allows variety of features to be identified for the segmented image objects. However, the use of a larg...

Hyperspectral images provide important information for addressing complex classification problems required for a detailed characterization of spectral behavior of the target objects. Classification of such datasets into meaningful land use and land cover classes (LULC) has been the most concentrated topic in remote sensing arena. Rotation forest (R...

Machine learning algorithms reported to be robust and superior to the conventional parametric classifiers have been recently employed in object-based classification. Within these algorithms, ensemble learning methods that construct set of individual classifiers and combining their predictions to make final decision about unlabelled data have been s...

Yüksek konumsal çözünürlüğe sahip uydu görüntüleri yardımıyla yeryüzü nesnelerin konumlarına ve dağılımlarına ilişkin detaylı bilgilerin elde edilmesi mümkündür. Buna karşın yüksek çözünürlüklü görüntüler heterojen yapıda ve benzer yansıma değerlerine sahip yoğun görüntü piksellerinden oluşmaktır. Karmaşık yapıdaki pikseller arasındaki spektral ayr...

Many landslide conditioning factors have been considered in the literature for landslide susceptibility mapping, but it is not certain which factors produce the best result for an area under analysis. With the availability of increasing number of landslide conditioning factors, finding the best combination of factors has become an important researc...