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  • Spatial distribution of vegetation cover in Erbil city districts using high-resolution Pléiades satellite image
    10-22
    Views:
    185

    Green spaces are playing an essential role for ecological balance and for human health in the city as well.
    They play a fundamental role in providing opportunities for relaxation and enjoying the beauty of nature
    for the urban population. Therefore, it is important to produce detailed vegetation maps to assist planners
    in designing strategies for the optimisation of urban ecosystem services and to provide a suitable plan
    for climate change adaptation in one fast growing city. Hence, this research is an investigation using 0.5
    m high-resolution multispectral Pléiades data integrated with GIS data and techniques to detect and
    evaluate the spatial distribution of vegetation cover in Erbil City. A supervised classification was used
    to classify different land cover types, and a normalised difference vegetation index (NDVI) was used
    to retrieve it for the city districts. Moreover, to evaluate the accessibility of green space based on their
    distance and size, a buffer zone criterion was used. The results indicate that the built-up land coverage
    is 69% and vegetation land cover is 14%. Regarding NDVI results, the spatial distribution of vegetation
    cover was various and, in general, the lowest NDVI values were found in the districts located in the city
    centre. On the other hand, the spatial distribution of vegetation land cover regarding the city districts was
    non-equal and non-concentric. The newly built districts and the districts far from the Central Business
    District (CBD) recorded the lowest vegetation cover compared with the older constructed districts.
    Furthermore, most of the districts have a lack of access to green spaces based on their distance and size.
    Distance and accessibility of green areas throughout the city are not equally distributed. The majority of
    the city districts have access to green areas within radius buffer of two kilometres, whereas the lowest
    accessibility observed for those districts located in the northeast of the city in particular (Xanzad,
    Brayate, Setaqan and Raperin). Our study is one of the first investigations of decision-making support
    of the spatial planning in a fast-growing city in Iraq and will have a utilitarian impact on development
    processes and local and regional planning for Erbil City in the future.

  • Heavy metal loads in the soil of Debrecen
    57-67
    Views:
    39

    Results of examinations on the amount, and spatial distribution of heavy metal compounds in the soil
    of Debrecen, their geographic, pedologic and ecologic aspects are presented in this study. The effects
    of the differences in traffic conditions, build-up/land use and the density of vegetation on the heavy
    metal content of the soils have been examined in city of Debrecen and its closer environment.
    Cadmium-, cobalt-, nickel-, lead-, and copper-contents of the soil samples taken from 88 sites of the
    sample area have been studied after acidic extraction, using atomic absorption spectrometer with the
    flame technique. Close-to-background concentrations of heavy metals in unpolluted soils of the
    forested area of the Nagyerdő were determined. Spatial differences in the heavy metal content of the
    soils for the whole area of Debrecen have been studied. Influence of soil properties (humus, CalciumCarbonate content, pH and grain-size distribution) on the binding and mobility of heavy metals in the
    soil has been examined. Vertical distribution and mobility of heavy metal compounds in acid sandy
    soils was determined. Heavy metal content of soil in the most sensitive areas, playgrounds,
    recreational areas, urban gardens and grazing fields along busy roads has been surveyed.

  • Urban vegetation classification with high-resolution PlanetScope and SkySat multispectral imagery
    66-75
    Views:
    523

    In this study two high-resolution satellite imagery, the PlanetScope, and SkySat were compared based on their classification capabilities of urban vegetation. During the research, we applied Random Forest and Support Vector Machine classification methods at a study area, center of Rome, Italy. We performed the classifications based on the spectral bands, then we involved the NDVI index, too. We evaluated the classification performance of the classifiers using different sets of input data with ROC curves and AUC values. Additional statistical analyses were applied to reveal the correlation structure of the satellite bands and the NDVI and General Linear Modeling to evaluate the AUC of different models. Although different classification methods did not result in significantly differing outcomes (AUC values between 0.96 and 0.99), SVM’s performance was better. The contribution of NDVI resulted in significantly higher AUC values. SkySat’s bands provided slightly better input data related to PlanetScope but the difference was minimal (~3%); accordingly, both satellites ensured excellent classification results.