Cenk Donmez

Mapping regional forest fire probability using artificial neural network model in a Mediterranean forest ecosystem

ABSTRACT Forest fires are one of the most important factors in environmental risk assessment and it is the main cause of forest destruction in the Mediterranean region. Forestlands have a number of known benefits such as decreasing soil erosion, containing wild life habitats, etc. Additionally, forests are also important player in carbon cycle and decreasing the climate change impacts. This paper discusses forest fire probability mapping of a Mediterranean forestland using a multiple data assessment technique. An artificial neural network (ANN) method was used to map forest fire probability in Upper Seyhan Basin (USB) in Turkey. Multi-layer perceptron (MLP) approach based on back propagation algorithm was applied in respect to physical, anthropogenic, climate and fire occurrence datasets. Result was validated using relative operating characteristic (ROC) analysis. Coefficient of accuracy of the MLP was 0.83. Landscape features input to the model were assessed statistically to identify the most descriptive factors on forest fire probability mapping using the Pearson correlation coefficient. Landscape features like elevation (R = −0.43), tree cover (R = 0.93) and temperature (R = 0.42) were strongly correlated with forest fire probability in the USB region.

Modeling Forest Productivity Using Envisat MERIS Data

The aim of this study was to derive land cover products with a 300-m pixel resolution of Envisat MERIS (Medium Resolution Imaging Spectrometer) to quantify net primary productivity (NPP) of conifer forests of Taurus Mountain range along the Eastern Mediterranean coast of Turkey. The Carnegie-Ames-Stanford approach (CASA) was used to predict annual and monthly regional NPP as modified by temperature, precipitation, solar radiation, soil texture, fractional tree cover, land cover type, and normalized difference vegetation index (NDVI). Fractional tree cover was estimated using continuous training data and multi-temporal metrics of 47 Envisat MERIS images of March 2003 to September 2005 and was derived by aggregating tree cover estimates made from high-resolution IKONOS imagery to coarser Landsat ETM imagery. A regression tree algorithm was used to estimate response variables of fractional tree cover based on the multi-temporal metrics. This study showed that Envisat MERIS data yield a greater spatial detail in the quantification of NPP over a topographically complex terrain at the regional scale than those used at the global scale such as AVHRR.

Modelling the current and future spatial distribution of NPP in a Mediterranean watershed

Abstract The aim of this study is to use full spatial resolution Envisat MERIS data to drive an ecosystem productivity model for pine forests along the Mediterranean coast of Turkey. The Carnegie, Ames, Stanford Approach (CASA) terrestrial biogeochemical model, designed to simulate the terrestrial carbon cycle using satellite sensor and meteorological data, was used to estimate annual regional fluxes in terrestrial net primary productivity (NPP). At its core this model is based on light-use efficiency, influenced by temperature, rainfall and solar radiation. Present climate data was generated from 50 climate stations within the watershed using co-kriging. Regional scale pseudo-warming data for year 2070 were derived using a Regional Climate Model (RCM) these data were used to downscale the GCM General Circulation Model for the research area as part of an international research project called Impact of Climate Changes on Agricultural Production Systems in Arid Areas (ICCAP). Outputs of climate data can be moderated using the four variables of percent tree cover, land cover, soil texture and NDVI. This study employed 47 MERIS images recorded between March 2003 and September 2005 to derive percent tree cover, land cover and NDVI. Envisat MERIS data hold great potential for estimating NPP with the CASA model because of the appropriateness of both its spatial and its spectral resolution.

The Anthroscape Approach in Sustainable Land Use

The final outcomes of the approach of the anthroscape, seeking to develop a powerful tool for use by the local communities/administrations and relevant bodies for a bottom to top approach, as a quantified entity, means to direct the future land and water use decisions to be taken at lower levels – as farm domains etc. – leading to the development of an “Anthroscape Land Quality Class” map and the relevant “Ideal Land Use Patterns” of the Seyhan Anthroscape. These two final products of quantification are sought to be capable in revealing the magnitude and the distribution of the degradation of the selected area, as well as allocating the ideal land use types given for the percentages of the distributions of land except their specific location. In this context, the downstream part of the map will show the abundant degradation arising via the intensive cultivation practices where the class stated in the map reveals the urgent need of an integrated SLWM Programme to revert the lower class C and D ALQCs to higher ALQCs to meet the requirements of the sustainable use of the land. Whereas, the higher ALQC land in the transition or upstream zone stands for higher resilience and lower input requirements to meet the ideal use of the land. The Net Primary Production (NPP) – The remainder of photosynthesis and respiration – which has significance in the global and regional carbon budgets and is a function of the standing biomass (an important component of the carbon cycle and a key indicator of ecosystem performance) was utilized via land cover and management to serve as a supplementary indicator of the Anthroscape and the Anthroscape Land Quality.

A comparative assessment of catchment runoff generation and forest productivity in a semi-arid environment

ABSTRACT Understanding the dynamic interactions between forest ecosystems and water in the Mediterranean region is essential for increasing ecosystem services. Even if many studies were implemented to analyse the variations of water and net primary productivity (NPP) in the last decade, this is still an important research question especially for the Eastern Mediterranean, where the research attempts are limited. The main objective of this study was to carry out a comparative analysis of catchment runoff generation and forest NPP and to reveal their temporal dynamics at basin scale in a semi-arid Mediterranean environment. The methodology consisted three steps: (i) estimating catchment runoff generation by implementing process-based J2000 modelling suite, (ii) modelling NPP of the land cover/use types by adapting an ecosystem-process model (BIOME-Biogeochemical cycles) and (iii) assessing the spatio-temporal variability of NPP and runoff dynamics by incorporating the modelling results with multiple regression analysis. Model simulations showed that temperature highly contributed to NPP variations of needle-leaf forests and grasslands. The multiple regression analysis also indicated that runoff was influenced by elevation, precipitation and forest cover. This relationship showed that the inter-annual variability in forest NPP would relate to the variations in runoff distribution across a small Mediterranean subcatchment.

Doğu Akdeniz’de Web-Tabanlı Turunçgil Bilgi Sistemi Oluşturulması

Ulkemizde tarim ve tarima dayali sektorlerin daha etkin ve kârli olabilmesi guncel tarimsal tekniklerin disinda enformatik, konumsal bilgi sistemleri gibi bilisim teknolojileri yardimiyla planlanmasini ve yonetimini gerektirmektedir. Ozellikle turuncgil sektoru, sektorun surdurulebilirligini saglamak icin teknolojik sistemleri kullanilarak kaynak yonetimini saglayacak bir modele ihtiyac duyulmaktadir. Bu calismada, UA verileri ve CBS yontemleri kullanilarak, Icel ve Adana Il sinirlari icerisinde turuncgil uretim alanlari haritasinin uretilmesi, agac sayisi, turu, yasi ve verimliligi gibi uretim bilgilerin yani sira toprak, hidroloji ve iklim gibi cevresel kosullari iceren dinamik bir turuncgil yonetim modeli olusturulmasi amaclanmistir. Bu kapsamda yuksek yersel cozunure sahip uydu goruntuleri kullanilarak, turuncgil alanlarinin siniflamasi gerceklestirilmistir. Bu surecte turuncgil parselleri sayisallastirilmis ve parsellere ait bilgiler arazi calismalari ile elde edilerek CBS ortamina aktarilarak modele dahil edilmistir. Olusturulan veri tabani moduler sunucu uzerine kurulan ArcGIS Server Manager ortaminda harita ve ozellik servisleri olarak iki farkli temelde ele alinmistir. Harita servisleri veri tabaninin mevcut durumun ortaya konmasi asamasinda, ozellik servisler ise veri tabanina kullanicilar tarafindan yeni bilgi girisi/guncellemesi asamasinda kullanilmistir. ArcSDE servis yardimi ile kurumsal cografi veri tabani, SQL Server ile de ArcGIS Server Manager kullanilarak veri tabani yayinlanmaya baslanmistir. Bu veri tabani her iki servisler ile iliskilendirilerek ArcGIS API Silverlight teknolojisi ile sorgulama, istatistik, veri girisi ve web ara yuzu olusturulmustur. Ayrica, alana ait toprak, hidroloji ve iklim verilerinin de veri tabanina aktarilmasiyla, turuncgil alanlarinin konumsal olarak dagiliminin, cesitliliginin ve verimliliginin belirlenmesi, izlenmesi ve bunlarin birbirleriyle ve cevresel diger faktorlerle iliskilerinin analiz edilmesi ve cevresel risk (don olaylari) planlarinin olusturulmasi mumkun olmustur.