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Unsupervised classification of high resolution satellite imagery by self-organizing neural network
37-44Views:42The current paper discusses the importance of the modern high resolution satellite imagery. The acquired high amount of data must be processed by an efficient way, where the used Kohonen-type self-organizing map has been proven as a suitable tool. The paper gives an introduction to this interesting method. The tests have shown that the multispectral image information can be taken after a resampling step as neural network inputs, and then the derived network weights are able to evaluate the whole image with acceptable thematic accuracy.
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Spatial distribution of vegetation cover in Erbil city districts using high-resolution Pléiades satellite image
10-22Views:243Green 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.
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Monitoring temperature patterns at selected world heritage sites in Egypt using high resolution WorldClim data
42-58Views:531Long term temperature patterns helps in assessing changes in the climatic conditions of an area and climatic changes poses a major challenge to the world heritage sites whether it is natural or cultural. Therefore in this study using maximum and minimum temperature data for the period 1960-2021 downloaded from WorldClim 2.1 calculation of mean temperature is done in QGIS environment for the selected UNESCO world heritage sites of Arab Republic of Egypt. WorldClim 2.1 provides finer resolution gridded data downscaled from Climate Research Unit. Trend analysis using linear regression and Mann-Kendall method and Sen’s Slope estimate is used to understand the patterns of mean temperature at all the selected sites. The study reveals that mean temperature at all the selected sites is increasing but since 1990 the sites which are located geographically in lower Egypt are witnessing rapid increase in mean temperature compared to the sites located in upper Egypt which historically witnessed more temperature due to its geographical milieu. This study can help in stimulating the utility of geospatial data in understanding the changes in climatic parameters in relation to world heritage sites. Moreover it can serve as foundation upon which detailed longitudinal site specific investigation can be done.
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Sentinel-2 satellite-based analysis of bark beetle damage in Sopron Mountains, Hungary
33-40Views:61Sopron mountains were affected by bark beetle (Ips typographus) damage between 2017 and 2020, which was surveyed on high-resolution ESA Sentinel-2 satellite images for the period 2017 and 2020 using Mosaic Hub, Anaconda, and Jupyter Notebook web-based computing environments. Biotic forest damage was detected based on vegetation (NDVI) and moisture (MSI, NDWI) indices derived from satellite images. The spatial and temporal change of damage was observed in the image series, resulting in information about the level of degradation and regeneration. In pursuance of GIS processing, 84 forest compartments were compared, which showed in most of the cases (97%) negative interannual change in the index mean values (MSI = - 0.14, NDWI = - 0.2, NDVI= - 0.19) when years compared to each other. The remote sensing-based survey was marked out and validated based on the forest database of the Hungarian Division of Forest of National Land Centre and forest protection damage reports of the Hungarian National Forest Damage Registration System.
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The developement of red mud flood environmental information system and the methodology for the spatial analysis of the degraded area
1-11Views:216The red mud disaster occurred on 4th October 2010 in Hungary has raised the necessity of rapid intervention and drew attention to the long-term monitoring of such threat. Both the condition assessment and the change monitoring indispensably required the prompt and detailed spatial survey of the impact area. It was conducted by several research groups - independently - with different recent surveying methods. The high spatial resolution multispectral aerial photogrammetry is the spatially detailed (high resolution) and accurate type of remote sensing. The hyperspectral remote sensing provides more information about material quality of pollutants, with less spatial details and lower spatial accuracy, while LIDAR ensures the three-dimensional shape and terrain models. The article focuses on the high spatial resolution, multispectral electrooptical method and the evaluation methodology of the deriving high spatial resolution ortho image map, presenting the derived environmental information database.