Detection of current and potential hazelnut plantation areas in Trabzon, North East Turkey using GIS and RS

Reis, Selçuk ( Aksaray, Yazar )Monitoring agricultural products requires the periodic determination of land cover and the production of land use policies in an optimum way. The hazelnut is one of the important Turkish agricultural exports and Turkey provides 77% of the world's hazelnuts. In Turkey, hazelnut production exceeds the demand; new regulations have been enacted to create new land use policies. By putting into practice regulations restricting hazelnut plantation areas, a more efficient and productive hazelnut harvest policy could be created. Therefore, more information on existing land cover is required to determine optimum (or ideal) potential hazelnut areas (PHA) and to forecast future crop production. The principle aim of this study is to create a methodology for determining existing PHA, using Geographic information system (GIS) and remote sensing (RS) techniques regarding to support hazelnut policy developers and economists. This study was basically carried out in the province of Trabzon, which is one of the most important hazelnut production areas in Turkey. Landsat ETM+ image was used to generate a current land cover classification. Using the supervised classification method, overall accuracy was determined to be 84.7%. Suitable hazelnut areas were determined according to criteria settled by government regulations...

Land cover identification for finding hazelnut fields using WorldView-2 imagery

IEEE International Geoscience and Remote Sensing Symposium (IGARSS) -- JUL 24-29, 2011 -- Vancouver, CANADAWOS: 000297496300039Remote sensing imagery is currently used as an efficient tool for agricultural management. Particularly, very high spatial resolution (less than 1m) enables extraction of permanent crops (including nut orchards) by visual interpretation or automated methods based on mainly textural features representing the regular plantation pattern. For accurate detection of orchards (hazelnuts in particular), this study proposes a rule-based classification utilizing multi-scale Gabor features and spectral values. Thanks to its very high spatial (0.5m) and spectral (8-bands) resolution, WorldView-2 imagery is primarily used. The classification accuracies, obtained with features extracted from WorldView-2 and Quickbird imagery, are compared for a study area in Turkey (major hazelnut producer in the world). In addition, supplementary value of the new 4 bands (coastal, yellow, red edge, and NIR2) in WorldView-2 imagery is discussed.IEEE, Inst Elect & Elect Engineers Geosci & Remote Sensing Soc (IEEE GRSS

Performance analysis of maximum likelihood and artificial neural network classifiers for training sets with mixed pixels

WOS: 000258730900004This study evaluates the performance of an artificial neural network, specifically a multilayer perceptron, and a maximum likelihood algorithm to classify multitemporal Landsat ETM+ remote sensor data. The study area in Turkey is a mountainous region that contains many small scattered fields, usually 5-10 pixels in size. The classifiers were employed to identify eight land cover/use features covering the bulk of the study area using the same training and test datasets in order to avoid any difference resulting from sampling variations. Results show that the neural network approach performed better in extracting land cover information from multi-spectral and multitemporal images with training data sets including a large amount of mixed and atypical pixels. The maximum likelihood classifier was found to be ineffective, particularly in classifying spectrally similar categories and classes having subclasses

Temporal monitoring of water level changes in Seyfe lake using remote sensing

WOS: 000260579000008The Earth's water resources are endangered by inconsiderate use, pollution and lack of conservation measures. Temporal monitoring is necessary for the conservation and usage planning of water resources, and to make informed decisions. Seyfe Lake and its environs in Turkey is one of, the most important water basins in the world because it is a node on bird migration paths between Europe, Asia and Africa. for this reason, the International Council of Bird Preservation (ICBP) has registered 27 of the bird species living, at Seyfe Lake on the conservation list. In this work, the temporal changes in the water surface area of Seyfe Lake and its environs, which are important for ecological, historical and tourism reasons, are investigated. The change of water surface in the lake is examined over a 26 year period using satellite images taken between 1975 and 2001. Landsat images from years 1975, 1987 and 2001 are used. The change is tracked from the images using an unsupervised classification method. A decrease of slightly more than 33% was observed in the water surface area this 26 year period. The temporal change indicated by the images was compared with the related meteorological data between 1975 and 2001. Over this time period, climate conditions (rainfall, temperature and evaporation) in the study area have been changed by approximately 21%. These changes could have affected the Lake surface area, but also could external human interference around the Lake

Designing and developing a province-based spatial database for the analysis of potential environmental issues in Trabzon, Turkey

WOS: 000262495900013Environmental databases generated by automation of the decision-making process for resolving complex environmental problems can be used more efficiently than traditional environmental evaluation. Such databases allow access to and analysis of spatial information at either the local or regional level for purposes including the development and assessment of effect of environmental policies, land use planning, precautions for natural disasters, monitoring of the effects of such disasters, and planning of the responses to them. This requires gathering data about local and regional resources, including data on access to roads and rivers, settlements, soil, land cover, and population. The study reported here highlights some technical problems associated with the collection and integration of data from a data-poor environment, and describes the potential benefits of integrating spatial data in relation to environmental problems. The Black Sea region of Turkey, especially the Trabzon province, in which the study was conducted, is burdened with adverse environmental conditions in terms of climate, topography, and land cover. These adverse conditions often cause landslides and in some areas restrict settlement. The purpose of the study described here was to analyze the spatial change (1990-2000) in population distribution in the Trabzon province and to detect potential landslide areas within the province by using functions incorporated in Geographical Information Systems (GIS). The preliminary results of these analyses showed that 62.4% of the area of the Trabzon province is at risk for landslide and that 283 village settlements are within regions at high risk for landslide.Prime Ministry State Planning Organization (SPO) of Turkey; Karadeniz Technical UniversityThe authors are grateful to the Prime Ministry State Planning Organization (SPO) of Turkey and Karadeniz Technical University Research Funds for financially supporting the study. The authors would also like to thank the GIS Lab research center staff at Karadeniz Technical University for their help in this study

Using landsat data to determine land use/land cover changes in Samsun, Turkey

Reis, Selçuk ( Aksaray, Yazar )The rapid industrialization and urbanization of an area require quick preparation of actual land use/land cover (LU/LC) maps in order to detect and avoid overuse and damage of the landscape beyond sustainable development limits. Remote sensing technology fits well for long-term monitoring and assessment of such effects. The aim of this study was to analyze LU/LC changes between 1980 and 1999 in Samsun, Turkey, using satellite images. Three Landsat images from 1980, 1987 and 1999 were used to determine changes. A post classification technique was used based on a hybrid classification approach (unsupervised and supervised). Images were classified into six LU/LC types; urban, agriculture, dense forest, open forest-hazelnut, barren land and water area. It is found that significant changes in land cover occurred over the study period. The results showed an increase in urban, open forest/hazelnut, barren land and water area and a decrease in agriculture and dense forest in between 1980 and 1999. In this period, urban land increased from 0.77% to 2.47% of the total area, primarily due to conversions from agricultural land and forest to a lesser degree. While the area of dense forest decreased from 41.09% to 29.64% of the total area, the area of open forest and hazelnut increased from 6.73% to 11.88%...

Investigation of availability of remote sensed data in cadastral works

Cadastre, which defines legal status and rights specifying the boundaries of the immovable property on the land and map, is very important in relation to property (Kadastro 1987). In countries like Turkey that require high precision, in cadastral survey data is used in the cadastral work to ensure that precision plays an important role. Less costly and more efficient studies should be used to improve suitability to the original on cadastral maps (NAP 1980). Mainly terrestrial methods in cadastral mapping studies, photogrammetric and remote sensing methods are also used. The uses of these methods appear in differences like necessary equipment, used techniques, accuracy requirements, staff and cost. Surveying of parcel boundaries and other details in cadastral works are performed using terrestrial measurement methods generally called as traditional method