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    Wyświetlanie 1-9 z 9
    Tytuł:
    A Comparison of Land Use Classifications in Urbanized Areas in Selected European Countries
    Autorzy:
    Matuk, Olga
    Powiązania:
    https://bibliotekanauki.pl/articles/1838016.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    land use
    land cover
    cadastre
    urban areas
    land cover registration
    Opis:
    The real estate cadastre is the primary source of information on land use. It re cords information related to the division of land into types based on the actual way of land use or development. The distinguished types of land use depend on many geographical factors, as well as historical and economic conditions. The study presents a comparison of the detail of land use classification registered in the real estate cadastre in areas functionally related to the urban areas of 9 European countries: Austria, Bulgaria, the Czech Republic, Estonia, Spain, Lithuania, Luxembourg, Germany and Poland. The research concerned the determination of the degree to which the classification of land use in urbanized areas is detailed, whether the studied European countries are characterized by the same number of distinguished classes of ob jects at different levels of detail, and what percentage are the distinguished classes of land use objects in urbanized areas in relation to all of the distinguished classes of objects land use at different levels of detail of classification. The study used legal acts regulating land use issues which have been made available in national languages by government institutions.
    Źródło:
    Geomatics and Environmental Engineering; 2021, 15, 2; 59-66
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Quantitative Analysis of Land Use Classification in Agricultural and Forest Areas
    Autorzy:
    Matuk, Olga
    Powiązania:
    https://bibliotekanauki.pl/articles/2174642.pdf
    Data publikacji:
    2022
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    land use
    land cover
    cadastre
    land cover registration
    agricultural areas
    forest areas
    Opis:
    The article deals with the research on the quantitative classification of land use, which directly affects the amount of land use data collected in the real estate cadastre. For the purpose of this article, the cadastral systems of seven European countries – Austria, Bulgaria, Estonia, Spain, Lithuania, Germany and Poland – have been examined, taking into account how detailed is the classification in agricultural and forest areas. The research covered the provisions of legal acts applicable in the researched seven European countries and made available in national languages by the government bodies. The article asks the following three questions: 1) whether the researched countries adopted the same approach to isolating classes of items related to agricultural and forest areas; 2) whether the researched countries feature the same number of classes of items recorded at various levels of detail; 3) what is the percentage of the distinguished item classes of land uses in the agricultural and forest areas in relation to all of the distinguished item classes at all the levels of detail. The conducted research can be used as a material supporting works consisting of the modernization of the functioning of land registration in the real estate cadastre in Poland.
    Źródło:
    Geomatics and Environmental Engineering; 2022, 16, 4; 59--77
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Green Space Assessment and Management in Biscay Province, Spain using Remote Sensing Technology
    Autorzy:
    Makinde, Esther O.
    Andonegui, Cristina M.
    Vicario, Ainhoa A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1838002.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    biomass computation
    carbon stock
    land use land cover
    Landsat
    remote sensing
    Opis:
    Our ecosystem, particularly forest lands, contains huge amounts of carbon storage in the world today. This study estimated the above ground biomass and carbon stock in the green space of Bilbao Spain using remote sensing technology. Landsat ETM+ and OLI satellite images for year 1999, 2009 and 2019 were used to assess its land use land cover (LULC), change detection, spectral indices and model biomass based on linear regression. The result of the LULC showed that there was an increase in forest vegetation by 12.5% from 1999 to 2009 and a further increase by 2.3% in 2019. However, plantation cover had decreased by 3.5% from 1999–2009; while wetlands had also decreased by 9% within the same period. There was, however, an increase in plantation cover from 2009 to 2019 by 2.1% but a further decrease in wetlands of 4.3%. Further results revealed a positive correlation across the three decades between the widely used Normalized Differential Vegetation Index (NDVI) with other spectral indices such as Enhance Vegetation Index (EVI) and Normalized Differential Moisture Index (NDMI) for biomass were: for 1999 EVI (R2 = 0.1826), NDMI (R2 = 0.0117), for 2009 EVI (R2 = 0.2192), NDMI (R2 = 0.3322), for 2019 EVI (R2 = 0.1258), NDMI (R2 = 0.8148). A reduction in the total carbon stock from 14,221.94 megatons in 1999 to 10,342.44 megatons 2019 was observed. This study concluded that there has been a reduction in the amount of carbon which the Biscay Forest can sequester.
    Źródło:
    Geomatics and Environmental Engineering; 2021, 15, 4; 21-43
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Monitoring of Land Surface Temperature from Landsat Imagery: A Case Study of Al-Anbar Governorate in Iraq
    Autorzy:
    Morsy, Salem
    Ahmed, Shaker
    Powiązania:
    https://bibliotekanauki.pl/articles/2203961.pdf
    Data publikacji:
    2023
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    land surface temperature
    Landsat
    single channel algorithm
    NDVI
    land use
    land cover
    classification
    regression
    Opis:
    Land surface temperature (LST) estimation is a crucial topic for many applications related to climate, land cover, and hydrology. In this research, LST estimation and monitoring of the main part of Al-Anbar Governorate in Iraq is presented using Landsat imagery from five years (2005, 2010, 2015, 2016 and 2020). Images of the years 2005 and 2010 were captured by Landsat 5 (TM) and the others were captured by Landsat 8 (OLI/TIRS). The Single Channel Algorithm was applied to retrieve the LST from Landsat 5 and Landsat 8 images. Moreover, the land use/land cover (LULC) maps were developed for the five years using the maximum likelihood classifier. The difference in the LST and normalized difference vegetation index (NDVI) values over this period was observed due to the changes in LULC. Finally, a regression analysis was conducted to model the relationship between the LST and NDVI. The results showed that the highest LST of the study area was recorded in 2016 (min = 21.1°C, max = 53.2°C and mean = 40.8°C). This was attributed to the fact that many people were displaced and had left their agricultural fields. Therefore, thousands of hectares of land which had previously been green land became desertified. This conclusion was supported by comparing the agricultural land areas registered throughout the presented years. The polynomial regression analysis of LST and NDVI revealed a better coefficient of determination (R2) than the linear regression analysis with an average R2 of 0.423.
    Źródło:
    Geomatics and Environmental Engineering; 2023, 17, 3; 61--81
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Geospatial Applicationsin Land Use/Land Cover Change Detection for Sustainable Regional Development:The Case of Central Haryana, India
    Autorzy:
    Kumar, Surender
    Singh, Ripudaman
    Powiązania:
    https://bibliotekanauki.pl/articles/1838027.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    geospatial
    India
    land use
    land cover
    RS-GIS
    sustainable regional development
    thematic change
    Opis:
    Timely and accurate detection of land use/land cover (LULC) change is important for the macro and micro level sustainable development of any region. For this purpose, geospatial techniques are the best tool for change analysis as they supply timely, cheaper, precise and up to date information. This paper examines the spatial temporal change trend in LULC in the case of Central Haryana. Landsat 2, 3, 5, 7 and 8 images for the years 1975–2020 for pre and post monsoon periods were analyzed for the study. Radiometric correction was performed to derive better information. ArcGIS 10.2 and ENVI 5.3 are used for thematic layout and thematic change preparation. An unsupervised classification using ERDAS IMAGINE 2015 has also been done to classify study area in eight classes. The year 1975 is considered as the base year for change detection analysis. Results showed an increasing trend for the land use classes of built up, water body, and agricultural land without waterlogging in the pre and post monsoon periods between 1975 and 2020. Remaining land use classes of agriculture with waterlogging, open waterlogged area, vegetation and fallow land/sand dunes decreased during the same period. Increased human activities have changed the LULC in the region and have had a great impact on its sustainable regional development.
    Źródło:
    Geomatics and Environmental Engineering; 2021, 15, 3; 81-98
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Unmanned Aerial Vehicles for Three‑dimensional Mapping and Change Detection Analysis
    Autorzy:
    Gbopa, Adetola Olufunmilayo
    Ayodele, Emmanuel Gbenga
    Okolie, Chukwuma John
    Ajayi, Akinwumi Olaitan
    Iheaturu, Chima Jude
    Powiązania:
    https://bibliotekanauki.pl/articles/1838008.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    UAV technology
    3D mapping
    orthophoto
    land cover
    change detection analysis
    Opis:
    Unmanned Aerial Vehicles (UAVs), commonly known as drones are increasingly being used for three dimensional (3D) mapping of the environment. This study utilised UAV technology to produce a revised 3D map of the University of Lagos as well as land cover change detection analysis. A DJI Phantom 4 UAV was used to collect digital images at a flying height of 90 m, and 75% fore and 65% side overlaps. Ground control points (GCPs) for orthophoto rectification were coordinated with a Trimble R8 Global Navigation Satellite System. Pix4D Mapper was used to produce a digital terrain model and an orthophoto at a ground sampling distance of 4.36 cm. The change detection analysis, using the 2015 base map as reference, revealed a significant change in the land cover such as an increase of 16,306.7 m2 in buildings between 2015 and 2019. The root mean square error analysis performed using 7 GCPs showed a horizontal and vertical accuracy of 0.183 m and 0.157 m respectively. This suggests a high level of accuracy, which is adequate for 3D mapping and change detection analysis at a sustainable cost.
    Źródło:
    Geomatics and Environmental Engineering; 2021, 15, 1; 41-61
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An Accuracy Analysis Comparison of Supervised Classification Methods for Mapping Land Cover Using Sentinel 2 Images in the Al‑Hawizeh Marsh Area, Southern Iraq
    Autorzy:
    Alwan, Imzahim A.
    Aziz, Nadia A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1838006.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    land cover mapping
    Sentinel 2
    supervised classification
    maximum likelihood
    Support Vector Machine (SVM)
    confusion matrix
    Opis:
    Land cover mapping of marshland areas from satellite images data is not a simple process, due to the similarity of the spectral characteristics of the land cover. This leads to challenges being encountered with some land covers classes, especially in wetlands classes. In this study, satellite images from the Sentinel 2B by ESA (European Space Agency) were used to classify the land cover of Al Hawizeh marsh/Iraq Iran border. Three classification methods were used aimed at comparing their accuracy, using multispectral satellite images with a spatial resolution of 10 m. The classification process was performed using three different algorithms, namely: Maximum Likelihood Classification (MLC), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). The classification algorithms were carried out using ENVI 5.1 software to detect six land cover classes: deep water marsh, shallow water marsh, marsh vegetation (aquatic vegetation), urban area (built up area), agriculture area, and barren soil. The results showed that the MLC method applied to Sentinel 2B images provides a higher overall accuracy and the kappa coefficient compared to the ANN and SVM methods. Overall accuracy values for MLC, ANN, and SVM methods were 85.32%, 70.64%, and 77.01% respectively.
    Źródło:
    Geomatics and Environmental Engineering; 2021, 15, 1; 5-21
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Sub-pixel classification of middle-resolution satellite images – evaluation of regression trees applicability to monitor impervious surfaces coverage
    Podpikselowa klasyfikacja średniorozdzielczych obrazów satelitarnych – ocena możliwości zastosowania drzew regresji w monitoringu pokrycia terenu powierzchniami nieprzepuszczalnymi
    Autorzy:
    Drzewiecki, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/385386.pdf
    Data publikacji:
    2010
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    wskaźnik nieprzepuszczalności
    mapy pokrycia terenu
    drzewa regresji
    teledetekcja satelitarna
    Landsat TM
    imperviousness index
    land cover mapping
    regression trees
    satellite remote sensing
    Opis:
    The aim of the presented research was to test the method of assessing the imperviousness index on the basis of middle-resolution satellite images with the use of regression trees. The task also included evaluation of the applicability of the method to monitor the changes of impervious surfaces coverage. The research has been done in the catchments of Prądnik and Dłubnia rivers (Malopolska region, Poland). The imperviousness index has been assessed for two time periods – current state (2007) and the mid-1990s. The training and verification data for both time periods have been obtained from aerial orthophotomaps for urban, suburban, rural, industrial and commercial areas. In both time states the best assessment of imperviousness index have been achieved for the variants where the regression trees were built on the basis of all satellite data accessible for the time period. However, it is worth notifying that the variant with the input data limited to three images from spring, summer and autumn provided comparable accuracy of the results. These models have the systematic error between 1.3–2.2%, the mean error between 15.8–16.4% and correlation coefficient between 0.85-0.86 for the mid-1990s. For the year 2009 these values are respectively: 1.4–1.7%, 15.7–16.0% and 0.86. The accuracy of the imperviousness index obtained in the present research is comparable with the accuracy obtained with the use of regression trees in research reported in the literature. The comparison has shown high accuracy of imperviousness index change assessment for the whole population of pixels in verification dataset. The systematic error is 0.1%. However, the obtained assessment accuracy for a single pixel (š14.5%) can be too low for some applications.
    Celem prezentowanych badań było sprawdzenie możliwości zastosowania drzew regresji do szacowania wskaźnika nieprzepuszczalności powierzchni terenu na podstawie średniorozdzielczych obrazów satelitarnych. W ramach badań przeprowadzona została również ocena stosowalności tej metody jako narzędzia monitoringu pokrycia terenu powierzchniami nieprzepuszczalnymi. Badania przeprowadzono na obszarze obejmującym zlewnie rzek Prądnik i Dłubnia. Wskaźnik nieprzepuszczalności oszacowano dla dwóch stanów czasowych – roku 2007 i połowy lat 90. XX wieku. W obu przypadkach dane treningowe i weryfikacyjne pozyskano z ortofotomap lotniczych dla obszarów o zróżnicowanym użytkowaniu (terenów zabudowy miejskiej, podmiejskiej, wiejskiej, przemysłowej oraz handlowej). W przypadku obu stanów czasowych najlepsze oszacowanie wskaźnika nieprzepuszczalności uzyskano w wariantach, w których do budowy drzew regresji użyto wszystkich dostępnych obrazów satelitarnych z poszczególnych okresów. Na uwagę zasługuje jednak fakt, iż porównywalną dokładność oszacowania uzyskano także w wariantach, w których dane wejściowe ograniczone były jedynie do trzech obrazów pozyskanych w okresie wiosennym, letnim i jesiennym. Zbudowane modele pozwalały na oszacowanie wskaźnika nieprzepuszczalności dla stanu z połowy lat 90. z błędem przeciętnym wynoszącym 1.3–2.2%, błędem średnim pomiędzy 15.8% a 16.4% oraz współczynnikiem korelacji w granicach 0.85–0.86. Dla roku 2007 wartości te wyniosły odpowiednio: 1.4–1.7%, 15.7–16.0% i 0.86. Uzyskany w prezentowanych badaniach poziom dokładności oszacowania wartości wskaźnika nieprzepuszczalności jest porównywalny z wynikami uzyskiwanymi z zastosowaniem drzew regresji przez innych autorów. Ocena dokładności oszacowania zmian wskaźnika nieprzepuszczalności wykazała bardzo wysoką dokładność ich określenia w odniesieniu do całości populacji pikseli w próbce weryfikacyjnej. Błąd systematyczny wyniósł w tym przypadku 0.1%. Należy jednak zauważyć, iż uzyskany dla pojedynczego piksela błąd średni na poziomie š14.5% może być zbyt duży dla niektórych zastosowań takiego podejścia jako narzędzia monitoringu zmian pokrycia powierzchni terenu.
    Źródło:
    Geomatics and Environmental Engineering; 2010, 4, 4; 61-75
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of Landsat imagery based vegetation indices to imperviousness index mapping
    Zastosowanie indeksów wegetacji do opracowywania map współczynnika nieprzepuszczalności na podstawie obrazów z satelity Landsat
    Autorzy:
    Drzewiecki, W.
    Osak, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/385630.pdf
    Data publikacji:
    2009
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    wskaźnik nieprzepuszczalności
    mapy pokrycia terenu
    indeksy wegetacji
    teledetekcja satelitarna
    Landsat TM
    imperviousness index
    land cover mapping
    vegetation indices
    satellite remote sensing
    Opis:
    The paper focuses on imperviousness index mapping with satellite remote sensing approach based on vegetation indices. Imperviousness factor can be defined as a percent of the total considered area covered by impervious surfaces (any materials that are impervious to water, such as rooftops, streets, driveways, parking lots, etc). With Landsat TM images comparable maps can be obtained for the time period from mid-80s to present. The imperviousness factor map of City of Cracow was prepared for 1996. Imperviousness factor accuracy was estimated for 20 percent.
    W publikacji przedstawiono zastosowanie teledetekcyjnej metody opartej na wskaźnikach wegetacji do sporządzania map współczynnika nieprzepuszczalności. Mapy te przedstawiają w odniesieniu do każdego piksela obrazu satelitarnego procentowy udział powierzchni o charakterze nieprzepuszczalnym, takich jak np. dachy budynków, drogi asfaltowe, parkingi itp. Wykorzystanie obrazów satelitarnych Landsat TM pozwala na uzyskanie porównywalnych map dla okresu od połowy lat 80. XX. wieku do chwili obecnej. Opracowanie wykonano dla obszaru Krakowa w roku 1996. Uzyskana dokładność oszacowania współczynnika nieprzepuszczalności wyniosła 20 procent.
    Źródło:
    Geomatics and Environmental Engineering; 2009, 3, 4; 43-52
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

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