Klasyfikacja terenów zieleni w Lublinie na podstawie zdjęcia satelitarnego IKONOS 2

Krukowski, Mirosław; Cebrykow, Paweł; Płusa, Joanna

doi:10.56583/br.603

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…Krukowski et al [31] used high-resolution IKONOS 2 satellite images with a level of detail allowing for the precise allocation of individual pixels to land cover classes. They decided to distinguish two classes of urban greenery: high and low.…”

Section: Introductionmentioning

confidence: 99%

Determining the Urgency of Greening by Estimating the Amount of Greenery Resources in the Place of Residence

Bielecki,

Będkowski

2024

Preprint

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Areas covered with vegetation play a key role for life on Earth and should be inventoried in a clear and complete manner in order to improve the process of its protection and development. Data showing the amount of greenery in areas most deformed by humans, i.e. urbanized areas, are particularly important. Local governments need to know how to invest theirs limited sources in the quality of life of residents by supplementing the urban fabric with additional vegetation. The article presents a proposal for how to calculate the degree of greenness of cities based on remote sensing data. Additionally, a novel method was proposed to help in planning the development of areas covered with vegetation, taking into account the spatial distribution of the local population. The result was a comprehensive method presenting the actual natural situation in a specific city.

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Section: Introductionmentioning

confidence: 99%

Determining the Urgency of Greening by Estimating the Amount of Greenery Resources in the Place of Residence

Bielecki,

Będkowski

2024

Preprint

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Generative adversarial approach to urban areas NDVI estimation: A case study of Łódź, Poland

Adamiak,

Będkowski,

Bielecki

2023

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Generative adversarial networks (GAN) opened new possibilities for image processing and analysis. In- painting, dataset augmentation using artificial samples, or increasing spatial resolution of aerial imagery are only a few notable examples of utilising GANs in remote sensing (RS). The normalised difference vegetation index (NDVI) ground-truth labels were prepared by combining RGB and NIR orthophotos. The dataset was then utilised as input for a conditional generative adversarial network (cGAN) to perform an image-to-image translation. The main goal of the neural network was to generate an artificial NDVI image for each processed 256 px × 256 px patch using only in- formation available in the panchromatic input. The network achieved a structural similarity index measure (SSIM) of 0.7569 ± 0.1083, a peak signal-to-noise ratio (PSNR) of 26.6459 ± 3.6577 and a root-mean-square error (RSME) of 0.0504 ± 0.0193 on the test set, which should be considered high. The perceptual evaluation was performed to verify the meth- od’s usability when working with a real-life scenario. The research confirms that the structure and texture of the pan- chromatic aerial RS image contain sufficient information for NDVI estimation for various objects of urban space. Even though these results can highlight areas rich in vegetation and distinguish them from the urban background, there is still room for improvement regarding the accuracy of the estimated values. The research aims to explore the possibility of utilising GAN to enhance panchromatic images (PAN) with information related to vegetation. This opens exciting opportunities for historical RS imagery processing and analysis.

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The degree of greenery in Łódź city, Poland – clearing up discrepancies between official statistics and satellite data

Bielecki

Będkowski

2022

ASPAL

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Motives: According to public statistics guidelines, areas officially classified in Lodz city as urban greenery include only forests, parks, lawns, squares and cemeteries. Areas of so-called unsealed greenery are omitted, which, however, have a great positive impact on improving the living conditions of the population. By taking information from satellite images and comparing them with official data, we have received a closer to the reality picture of the city, which is much more better than it would appear from official statistical data. Another dimension which the study addresses is the uneven distribution of greenery of a certain quality in individual units of the city. Aim: Comparing these data with the fact that the distribution of places of residence is also uneven, an attempt was made to assess the accessibility of green areas for the inhabitants of Lodz city. Results: The results show that there are much more green spaces, similar in terms of vegetation abundance to the official green spaces. That means the city is underestimated when talking about the degree of greenery.

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Klasyfikacja terenów zieleni w Lublinie na podstawie zdjęcia satelitarnego IKONOS 2

Cited by 3 publications

References 2 publications

Determining the Urgency of Greening by Estimating the Amount of Greenery Resources in the Place of Residence

Determining the Urgency of Greening by Estimating the Amount of Greenery Resources in the Place of Residence

Generative adversarial approach to urban areas NDVI estimation: A case study of Łódź, Poland

The degree of greenery in Łódź city, Poland – clearing up discrepancies between official statistics and satellite data

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