Yazar "Bostanci, Y. B." seçeneğine göre listele

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    Assessment of the effect of salinity on the early growth stage of the common sunflower (Sanay cultivar) using spectral discrimination techniques
    (Academic Journals, 2008) Turhan, H.; Genc, L.; Smith, S. E.; Bostanci, Y. B.; Turkmen, O. S.
    Salinity is one of the main limiting factors for agricultural production. This is especially true in arid and semi-arid regions of the world like Turkey. The objective of this study was to determine if the effect of salt concentration on the physiological and physiological features of the sunflower (Helianthus annuus L) could be measured using remote sensing techniques. Sunflower seedlings were grown under controlled conditions and irrigated with Hoagland Solution containing three different concentrations of NaCl (salt) (0.0, 0.5, 1.0 and 1.5%). The results showed that plant growth decreased proportionally with increasing levels of NaCl. Chlorophyll concentration and a Normalized Difference Vegetation Index (NDVI) were derived for the plants using a spectroradiometer. There was found to be a significant (r(2) = 0.76) correlation between chlorophyll and NDVI values. Therefore, factors that can be derived through remote sensing such as NDVI and chlorophyll can be used to indirectly demonstrate the impact salinity has on sunflower plants. Therefore, agriculturalists can assess growth rate changes caused by salinity using remote sensing techniques.
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    Öğe
    Determination of Agriculture Land Use and Land Cover Change Using Remote Sensing and GIS in TROIA National Park
    (Univ Namik Kemal, 2007) Genc, L.; Bostanci, Y. B.
    The area selected for land use land cover (LULC) dynamics, TROIA national park, is located in the city of Canakkale, TURKEY. The national park covers an area of about 13600 ha. Remote sensing studies especially multi-temporal analysis of changes provides sufficient information about the dynamics of historic landscape. Tasseled Cap Indexes and Normalized Difference Vegetation Index (NDVI) were used to create the new images from Landsat TM 1987 and Landsat TM 2006 images for classification. Supervised classification was applied with ground truth data and auxiliary data collected from different sources such as air photo, cadastral information and others. Four classes of changed and unchanged multi-temporal raster were discriminated from created new images as followed: Active Agriculture, Grassland, Forestry, and Water. Classification accuracy was determined for 1987 image and 2006 image as 81% and 87% respectively. It was found that LULC change was dynamic between classes because of the land consolidation in the region. Grassland was changed to active agriculture area by 75% and to forestry class by 5%. Forested area also converted to active agriculture by 46% and to grassland by 9%. It was concluded that land consolidation project in the study area was the main force to change land cover.