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    Wyświetlanie 1-9 z 9
    Tytuł:
    Crop production intensity and haNDVI indicator – amplitude of NDVI related to harvest
    Autorzy:
    Łopatka, Artur
    Koza, Piotr
    Powiązania:
    https://bibliotekanauki.pl/articles/2147933.pdf
    Data publikacji:
    2020-11-30
    Wydawca:
    Instytut Uprawy Nawożenia i Gleboznawstwa – Państwowy Instytut Badawczy
    Tematy:
    remote sensing
    NDVI
    nitrogen fertilizers
    Sentinel
    MODIS
    Opis:
    In response to the growing needs of spatial recognition of the intensity of agricultural crop production, a new haNDVI indicator was developed, that measures the amplitude of the NDVI indicator related to the harvest. The proposed way of calculating haNDVI is to use the minimum and maximum functions for the raster layers set from the growing season. This avoids the need for preliminary classification of crops, including to determine the moment of harvest. It has been shown that the haNDVI indicator calculated on aggregated NDVI layers with a resolution of 1 km is correlated with soil quality indexes, NPK fertilization intensity (r = 0.69) and the share of crops in the total area (r = 0.86) for municipalities. The properties of the haNDVI indicator make it particularly useful for the initial, rapid scanning of environmental quality in terms of the intensity of plant production and indicating the hazards locations associated with the use of fertilizers and plant protection products.
    Źródło:
    Polish Journal of Agronomy; 2020, 42; 24-33
    2081-2787
    Pojawia się w:
    Polish Journal of Agronomy
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Application of Remote Sensing Techniques and Spectral Analyzes to Assess the Content of Heavy Metals in Soil – A Case Study of Barania Góra Reserve, Poland
    Autorzy:
    Sobura, Szymon
    Widłak, Małgorzata
    Hejmanowska, Beata
    Muszyńska, Joanna
    Powiązania:
    https://bibliotekanauki.pl/articles/2174645.pdf
    Data publikacji:
    2022
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    remote sensing
    heavy metals
    Sentinel-2
    soil
    spectral indices
    Opis:
    The understanding of the spatial and temporal dynamics of farmland processes is essential to ensure the proper crop monitoring and early decision making needed to support efficient resource management in agriculture. By creating appropriate crop management strategies, one can increase harvest efficiency while reducing costs, waste, chemical spraying, and inhibiting the impact of biotic and abiotic factors on crop stress. Only reliable spatial information makes it possible to comprehend the influence of various factors on the environment. The main objective of the research presented in the paper was to assess the possibility of using maps of vegetation and soil indices, such as NDVI, SAVI, IRECI, CIred-edge, PSRI and HMSSI, calculated on the basis of images from the Sentinel-2 satellite, to qualitatively determine the increased amount of heavy metals in the soil in the areas of small agricultural plots around the Barania Góra nature reserve in Poland. The conducted pilot project shows that the spectral indices: NDVI, SAVI, IRECI, CIred-edge, PSRI, and HMSSI, calculated on the basis of images from Sentinel-2, have the potential to assess the content of nickel zinc, chromium and cobalt in the soil on agricultural plots. However, the confirmation of the obtained results requires continuation of the research.
    Źródło:
    Geomatics and Environmental Engineering; 2022, 16, 4; 187--213
    1898-1135
    Pojawia się w:
    Geomatics and Environmental Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Spatial and Temporal Variability of Moisture Condition in Soil-Plant Environment using Spectral Data and Gis Tools
    Autorzy:
    Grzywna, H.
    Dąbek, P. B.
    Olszewska, B.
    Powiązania:
    https://bibliotekanauki.pl/articles/123280.pdf
    Data publikacji:
    2018
    Wydawca:
    Polskie Towarzystwo Inżynierii Ekologicznej
    Tematy:
    drought
    soil moisture
    NDVI
    Sentinel-2
    satellite data
    remote sensing
    Opis:
    The studies on agricultural droughts require long-term atmospheric, hydrological and meteorological data. On the other hand, today, the possibilities of using spectral data in environmental studies are indicated. The development of remote sensing techniques, increasing the spectral and spatial resolution of data allows using remote sensing data in the study of water content in the environment. The paper presents the results of the analysis of moisture content of soil-plant environment in the lowland areas of river valley using the spectral data from Sentinel-2. The analyses were conducted between February and November 2016. The spectral data were used to calculate the Normalize Differential Vegetation Index (NDVI) which provided the information about the moisture content of the soil-plant environment. The analyses were performed only on grasslands, on 22 objects located in the research area in the Oder river valley between Malczyce and Brzeg Dolny, Poland. The NDVI values were correlated with the hydrological and meteorological parameters. The analyses showed spatial and temporal variability of the moisture conditions in the soil-plant environment showed by the NDVI variability and existence some relationships between the climatic and spectral indices characterizing the moisture content in the environment.
    Źródło:
    Journal of Ecological Engineering; 2018, 19, 6; 56-64
    2299-8993
    Pojawia się w:
    Journal of Ecological Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Zastosowanie satelitarnych wskaźników teledetekcyjnych do monitorowania uwilgocenia biomasy w uprawach miskanta olbrzymiego (Miscanthus x giganteus)
    Application of satellite remote sensing indicators to monitor the moisture of biomass in giant miscanthus crops (Miscanthus x giganteus)
    Autorzy:
    Kubiak, Katarzyna
    Kotlarz, Jan
    Powiązania:
    https://bibliotekanauki.pl/articles/883159.pdf
    Data publikacji:
    2019-09-05
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Maszyn Rolniczych
    Tematy:
    trawy
    Poaceae
    miskant olbrzymi
    Miscanthus x giganteus
    warunki meteorologiczne
    fotosynteza C4
    biomasa
    wilgotnosc
    zawartosc wody
    teledetekcja
    pomiary satelitarne
    satelita Sentinel-2
    C4 carbon fixation
    Sentinel 2 satellite
    weather conditions
    water index
    remote sensing
    Opis:
    Miskant olbrzymi (Miscanthus x giganteus) z powodu jego fizjologicznej adaptacji do ścieżki fotosyntezy C4 jest uważany za istotny gatunek upraw na cele energetyczne. Dostępność wody silnie wpływa na jego plony, a wysoki plon biomasy z jednostki powierzchni jest związany z miejscami, w których opady wynoszą co najmniej 762 mm rocznie. Celem pracy było wyznaczenie wskaźników teledetekcyjnych obrazujących zawartość wody w uprawach miskanta olbrzymiego za pomocą zobrazowań satelitarnych Sentinel 2 oraz określenie korelacji tych wskaźników z najpowszechniejszym wskaźnikiem teledetekcyjnym biomasy NDVI oraz z warunkami pogodowymi na wybranym terenie w latach 2016-2018. Analiza zależności warunków pogodowych i wartości teledetekcyjnych wskaźników wodnych w badanych uprawach wykazała dość silną ko-relację (ok +0,80) pomiędzy wskaźnikami wodnymi (m.in. NDWI, MSI, NDII, Water Index) a opadami oraz umiarkowaną ujemną korelację (ok -0,40) z temperaturą.
    Miscanthus x giganteus due to its physiological adaptation to the C4 photosynthesis pathway is considered as an important species of the crop for energy purposes. The availability of water strongly affects its yield, and the high biomass yield per unit area is associated with places where rainfall is at least 762 mm per year. The work aimed to determine re-mote sensing indicators showing the water content in Miscanthus x giganteus cultivars using Sentinel 2 satellite imagery and to determine the correlation of these indicators with the most common remote-sensing NDVI biomass and weather conditions in a selected area in 2016-2018. Analysis of the relationship between weather conditions and remote sensing values of water indicators in the studied crops showed quite strong correlation (about +0.80) between water indicators (including NDWI, MSI, NDII, Water Index) and precipitation and moderate negative correlation (about -0.40) with tem-perature.
    Źródło:
    Technika Rolnicza Ogrodnicza Leśna; 2019, 3; 16-18
    1732-1719
    2719-4221
    Pojawia się w:
    Technika Rolnicza Ogrodnicza Leśna
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Application of Sentinel-2 Data for Automatic Forest Cover Changes Assessment – Białowieża Primeval Forest Case Study
    Autorzy:
    Pelc-Mieczkowska, Renata
    Powiązania:
    https://bibliotekanauki.pl/articles/2051560.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    Białowieża Primeval
    forest cover
    remote sensing
    radiometric indices
    Sentinel-2
    Puszcza Białowieska
    lesistość
    teledetekcja
    wskaźniki radiometryczne
    Opis:
    Sentinel-2 mission, as a part of European Space Agency Earth Observation Program Copernicus, designed specifically for Earth surface observations provides images in 13 bands. That imaging is used to analyse many subject areas as Land monitoring, Emergency management, Security and Climate change. In the presented paper the application of Sentinel-2 data for automatic forest cover changes detection has been analysed. As input data, B02, B03, B04 and B08 bands have been used to compute Normalized Difference Vegetation Index (NDVI) and Enhanced Normalized Difference Vegetation Index (ENDVI). To track changes in the forest cover over the years, for each pixel the difference in the value of vegetation indices between consecutive years have been calculated. Then the threshold was set at the level of 0.15. The values of differences above the threshold mean a significant decrease in the quality of vegetation and may be considered areas of deforestation.
    Źródło:
    Civil and Environmental Engineering Reports; 2021, 31, 4; 148-166
    2080-5187
    2450-8594
    Pojawia się w:
    Civil and Environmental Engineering Reports
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Zastosowanie danych z satelity Sentinel-2 do szacowania rozmiaru szkód spowodowanych w lasach huraganowym wiatrem w sierpniu 2017 roku
    Assessment of forest damage caused by the August 2017 hurricane using Sentiel-2 satellite data
    Autorzy:
    Hościło, A.
    Lewandowska, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/986595.pdf
    Data publikacji:
    2018
    Wydawca:
    Polskie Towarzystwo Leśne
    Tematy:
    lesnictwo
    lasy
    huragany
    szkody w lesie
    drzewostany pohuraganowe
    metody badan
    teledetekcja satelitarna
    satelita Sentinel-2
    forest damage
    windthrow
    remote sensing
    Opis:
    Extreme weather events such as hurricanes, floods or fires become more and more common phenomena in Europe. In August 2017, strong wind accompanied by heavy thunderstorms caused severe damage over the large area in central and western Poland. According to rapid damage assessment prepared by the State Forests authorities a few days after the windthrow, ca 79.7 thousand hectares of forest was damaged and 9.8 million of cubic meters of wood was lost. Assessment of such a large−scale forest damage is difficult without using the remote sensed data. In this study, we examined the potential of the European satellite Sentinel−2 data for assessment of the forest damage caused by the windthrow. The assessment was performed using a difference between a normalized difference moisture index (NDMI) calculated based on the pre− and post−damage Sentinel−2 images. NDMI was calculated based on NIR (824 nm) and SWIR (1610 nm) bands. The result of this study showed the total damage area in forest is equal to 35.8 thousand hectares, of which 27.7 thousand hectares was damaged within the State Forests and 8.1 thousand hectares outside the State Forests administration. These figures are much lower than the estimates by the State Forests, regarding the forest damage within the State Forests and higher comparing to estimations in the non−state forest. In fact, these figures are comparable with the heavily damage areas assigned to clearance by the State Forests. The accurate comparison of the results was not possible due to the lack of up−to−date information on forest damage. Sentinel−2 data revealed to be perfect data for large scale damage assessment and post−damage forest monitoring mainly due to the wide swath up to 290 km. The limitation of the optical sensors is the cloudiness. Unfortunately, in the case of this analysis, the first cloud free image was acquired 6 weeks after the windthrow. It reduces the potential of the single−source data for rapid assessment of damages.
    Źródło:
    Sylwan; 2018, 162, 08; 619-627
    0039-7660
    Pojawia się w:
    Sylwan
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Klasyfikacja pokrycia terenu z wykorzystaniem obrazów Sentinel-2A przetworzonych za pomocą metody głównych składowych (PCA)
    Land cover classification using Sentinel-2A images processed by the principal components method (PCA)
    Autorzy:
    Kałużna, Urszula
    Będkowski, Krzysztof
    Powiązania:
    https://bibliotekanauki.pl/articles/2058371.pdf
    Data publikacji:
    2020
    Wydawca:
    Polskie Towarzystwo Geograficzne
    Tematy:
    teledetekcja
    pokrycie terenu
    EGiB
    Sentinel-2A
    PCA
    nadzorowana klasyfikacja obrazu
    remote sensing
    land cover
    Land and Buildings Register
    supervised image classification
    Opis:
    Celem badań jest ocena możliwości realizacji klasyfikacji nadzorowanej z wykorzystaniem obrazów (komponentów) uzyskiwanych w wyniku przetworzenia oryginalnych obrazów Sentinel-2A za pomocą metody głównych składowych (PCA). Klasyfikację wykonano w ośmiu wariantach, z wykorzystaniem algorytmów najmniejszej odległości (MD, Minimum Distance) oraz największego prawdopodobieństwa (ML, Maximum Likelihood), przy czym zastosowano oryginalne kanały 2, 3, 4, 8 Sentinel-2A oraz różną liczbę komponentów. Wyniki klasyfikacji oceniono poprzez porównanie z danymi o pokryciu terenu według Ewidencji Gruntów i Budynków (EGiB). Przeprowadzenie klasyfikacji na ograniczonej do dwóch liczbie komponentów uzyskanych w procedurze PCA tylko nieznacznie zmieniło wyniki w porównaniu do klasyfikacji na oryginalnych, nieprzetworzonych kanałach Sentinel-2A. Najbardziej zbliżone do danych EGiB rezultaty uzyskano stosując klasyfikację ML kanałów oryginalnych, nieprzetworzonych lub używając wszystkich komponentów PCA. Podjęta próba porównania pokrycia terenu ustalonego za pomocą klasyfikacji obrazów satelitarnych z klasami pokrycia, które zostały wyodrębnione z mapy EGiB wykazała, że przetworzenie mapy z postaci wektorowej na rastrową wpływa istotnie na uzyskiwane wyniki.
    The aim of the research is to assess the feasibility of supervised classification using images (components) obtained through processing the original Sentinel-2A images by means of the principal component method (PCA). The classification was performed in eight variants, using the algorithms of the minimum distance (MD) and the maximum likelihood (ML), with the original channels 2, 3, 4, 8 of Sentinel-2A and a various number of components. The results of the classification were assessed by comparing them to the land coverage data of Land and Buildings Register (Ewidencja Gruntów i Budynków – EGiB). Performing the classification on a number of PCA components limited to two only slightly altered the results compared to the classification on the original, raw Sentinel-2A channels. The results most similar to the EGiB data were obtained using the ML classification of the original channels, i.e. raw channels or using all PCA components. The attempt to compare the land coverage established by the classification of satellite images to the coverage classes that were extracted from the EGiB map revealed that processing the map from vector to raster form significantly influences the obtained results.
    Źródło:
    Teledetekcja Środowiska; 2020, 61; 19-37
    1644-6380
    Pojawia się w:
    Teledetekcja Środowiska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Flooded wetlands mapping from Sentinel-2 imagery with spectral water index : a case study of Kampinos National Park in central Poland
    Autorzy:
    Solovey, Tatiana
    Powiązania:
    https://bibliotekanauki.pl/articles/2059679.pdf
    Data publikacji:
    2020
    Wydawca:
    Państwowy Instytut Geologiczny – Państwowy Instytut Badawczy
    Tematy:
    remote sensing
    Sentinel-2
    flooded wetlands mapping
    Modified Normalised Difference Water Index
    MNDWI
    Normalised Difference Pond Index
    NDPI
    Normalised Difference Turbidity Index
    NDTI
    Opis:
    Flood monitoring of wetlands and floodplains is a new issue in remote sensing, as compared to the mapping of open water bodies. The method based on spectral water indices, calculated on the basis of green, red and shortwave infrared bands, is one of the most popular methods for the recognition of a water body in multispectral images. The recently introduced Sentinel-2 satellite can provide multispectral images with high spatial resolution. This new data set is potentially of great importance for flood mapping, due to its free access and the frequent revisit capabilities. In this study, three popular water indices (Modified Normalized Difference Water Index, Normalized Difference Pond Index and Normalized Difference Turbidity Index) were used. The efficiency of the proposed method was tested experimentally using the Sentinel-2 image for the Kampinos National Park in Poland. The experiment compared four extraction algorithms including three based on individual water indicators and one on a combination of them. The results showed that the 10-metre false colour composite produced significantly improved the recognition of flooding in wetland areas by comparison with single spectral water indices. In this way, flooded wetlands were mapped based on the Sentinel-2 data set for the years 2017-2018.
    Źródło:
    Geological Quarterly; 2020, 64, 2; 492--505
    1641-7291
    Pojawia się w:
    Geological Quarterly
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Program Copernicus źródłem informacji o dominującym typie drzewostanu w Polsce – ocena dokładności krajowej warstwy wysokorozdzielczej
    Copernicus Program as a source of information on the dominant leaf type in Poland – assessment of the accuracy of the national high resolution layer
    Autorzy:
    Mirończuk, A.
    Leszczyńska, A.
    Hościło, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/979243.pdf
    Data publikacji:
    2020
    Wydawca:
    Polskie Towarzystwo Leśne
    Tematy:
    program Copernicus
    dane satelitarne
    warstwa wysokorozdzielcza
    lasy
    stopien zmieszania
    Polska
    leśnictwo
    źrodła informacji
    typy lasów
    copernicus
    high resolution layers
    forest type
    remote sensing
    Sentinel-2
    Opis:
    Information on the spatial distribution and variability of forests is important in monitoring of forest resources, biodiversity assessment, threat prevention, estimation of carbon content and forest management. The Pan−European High Resolution Layers (HRLs) produced as part of the European Earth Monitoring Programme – Copernicus provide detailed information on the land cover characteristics in Europe. The HRLs are produced using satellite imagery based on an interactive rule−based classification. There are the following HRL themes: imperviousness, forest, water and wetness and grasslands. The HRLs are available for the reference year 2012 and 2015, at the spatial resolution of 20 m. The forest related HRL consists of tree cover density, dominant tree type and forest type products. In this study, we performed a) the qualitative and quantitative analysis of the accuracy of the dominant leaf type (DLT) layer for the 2015 year at the national scale, and b) detailed analysis of the data quality at the forest stand level over the selected forest districts. The DLT layer was compared with the national orthophotos. The detailed analysis was carried out using Sentinel−2 images and forest inventory data obtained from the Forest Data Bank over the selected forest districts. The accuracy analysis of the national DLT layer revealed the high omission error equal to 18.8%, and lower commission error of 5.4%. The omission error is mostly related to the omitted orchards and young forest plantations, which are included in the DLT layer. The commission error of the broadleaved forest is related mostly to the small patches of coniferous forest that was misclassified as broadleaved. In general, commission errors were identified more frequently in broadleaved forest than in the coniferous forest. In many locations the patches of coniferous forest were misclassified as broadleaved forest. In general, the area of the broadleaved forest is overestimated.
    Źródło:
    Sylwan; 2020, 164, 02; 151-160
    0039-7660
    Pojawia się w:
    Sylwan
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
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