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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:
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:
Wykrywanie wody na zdjęciach optycznych Sentinel-2 na podstawie wskaźników wodnych
The detection of water on Sentinel-2 imagery based on water indices
Autorzy:
Robak, A.
Gadawska, A.
Milczarek, M.
Lewiński, S.
Powiązania:
https://bibliotekanauki.pl/articles/132357.pdf
Data publikacji:
2016
Wydawca:
Polskie Towarzystwo Geograficzne
Tematy:
Sentinel-2
obrazowanie optyczne
wskaźniki wodne
detekcja wody
korekcja atmosferyczna
optical satellite images
water indices
water detection
atmospheric correction
Opis:
Copernicus Programme managed by the European Commission and implemented in partnership with i.a. the European Space Agency (ESA) provides free access to satellite data from Sentinel mission including Sentinel-2 high resolution optical satellite data. The aim of the research was to recognize opportunities of water detection on Sentinel-2 imagery. Satellite data was analyzed before and after atmospheric correction. A number of tests were carried out using indices selected from the literature. Based on the gained experience, a new index for water detection has been proposed, Sentinel Water Mask (SWM), specially adapted for Sentinel-2 images. Its construction is based on the highest difference between spectral values of water surface and other land cover forms. SWM provides quick and effective detection of water which is especially important in flood assessment for crisis management. Research was performed on unprocessed images of Sentinel-2 Level-1C and images after atmospheric correction (Level-2A). Water was detected with the use of threshold values determined by the visual interpretation method. The accuracy of the obtained water masks was assessed on the basis of validation points. The performed analysis allowed to indicate indices, which enable estimation of areas covered by water on Sentinel-2 images with high classification accuracy, this is: AWEInsh (Automated Water Extraction Index), MNDWI (Modified Normalized Difference Water Index), NDWIMcFeeters (Normalized Difference Water Index). Their application allowed for achievement of overall accuracy of water detection oscillating around 95% and high Kappa coefficient. The usage of the proposed SWM index leads to slightly better results (more than 96%). The sensitivity to the selection of threshold values of analyzed indices was assessed and then the optimal threshold ranges were determined. The optimal threshold value for NDWIMcFeeters should be included in the value range (0.1, 0.2), for MNDWI (0.2, 0.3) and for SWM (1.4, 1.6). The unambiguous threshold range for AWEInsh index was impossible to indicate due to the large range of values.
Źródło:
Teledetekcja Środowiska; 2016, 55; 59-72
1644-6380
Pojawia się w:
Teledetekcja Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wpływ susz na wskaźniki teledetekcyjne grądu wysokiego i boru mieszanego w Lesie Młochowskim - analiza zobrazowań satelitarnych Sentinel-2 lasów objętych ochroną ścisłą oraz gospodarczych w latach 2017-2021
The influence of drought on remote sensing indicators of hornbeam and mixed coniferous forest in the Mlochowski Forest - analysis of Sentinel-2 satellite images of protected and economic forests in 2017-2021
Autorzy:
Kotlarz, J.
Powiązania:
https://bibliotekanauki.pl/articles/2136480.pdf
Data publikacji:
2021
Wydawca:
Instytut Badawczy Leśnictwa
Tematy:
susza
grad wysoki
bor mieszany
teledetekcja
Znormalizowany Wskaznik Wegetacji
znormalizowany roznicowy wskaznik wody
wskaznik NDWI zob.znormalizowany roznicowy wskaznik wody
wskaznik wilgotnosci MSI
satelita Sentinel-2
drought
NDVI
NDWI
MSI
Sentinel-2
oak-hornbeam forest
mixed coniferous forest
Opis:
The purpose of this paper was to describe processes that took place in the Łowicz-Błonia plain during the long-term drought of 2018 and the series of short-term droughts in 2019. For our analysis we used multispectral satellite images of high- ground hornbeam and mixed coniferous forest in the Młochowski Forest from 2017–2021. Sentinel-2 images provided the means to investigate the impact of mild droughts on the values of the NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), and MSI (Moisture Stress Index) as well as their monthly variability and differences between forest divisions. During periods without drought, the variability of all three indices was typical for each phase of the vegetation cycle: in the spring months the value of NDVI and MSI increased, NDWI decreased. During the autumn months, the behavior of the indicators reversed. In the period of long-term drought in 2018, the NDWI was higher in forest divisions with aspecies composition characteristic of a mixed coniferous forest compared to divisions with a higher share of deciduous trees such as oaks and hornbeams, including the rigorously protected area of high–hornbeam forest. NDWI was the only index to show a downward trend during mild droughts, while during moderate droughts, also a decrease in NDVI and MSI was observed. This was most clearly seen in deciduous forests. We did not observed any correlation of NDVI, NDWI, or MSI with the protection status of the forest or the absence thereof
Źródło:
Leśne Prace Badawcze; 2021, 82, 3; 87-100
1732-9442
2082-8926
Pojawia się w:
Leśne Prace Badawcze
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using Sentinel-2A to identify the change in dry marginal agricultural land occupation
Autorzy:
Indarto, Indarto
Putra, Bayu T. W.
Mandala, Marga
Powiązania:
https://bibliotekanauki.pl/articles/1844401.pdf
Data publikacji:
2020
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
agricultural
change
land
mapping
marginal
Sentinel-2A
Opis:
Dry marginal agricultural land (DryMAL) potentially use as an alternative resource for crop production. DryMAL defined as land having low natural fertility due to its intrinsic properties and forming environmental factors. This study uses Sentinel-2A imagery to map the spatial extent, compare the result of the classification, and identify the change in DryMAL occupation. The area of study (461.9 km2) is part of Situbondo Regency and is located at the eastern part of East Java, Indonesia. Sentinel-2A image captured in dry-season of 2018 use for this study. Then, supervised image classification using a maximum likelihood algorithm use for image treatment and processing. Furthermore, 450 ground control points for training areas collected during the field surveys. Five bands use in the classification process. The maps produced from the classification process were then compared to the land-use map from the year 2000. The change in DryMAL occupation from 2000 to 2018 was calculated by comparing the classified and land-use map. Supervised classification yielded an overall accuracy of 95.8% and a kappa accuracy of 93.2%. The classification produced six (6) classes of land use: (1) forest, (2) pavement or built-up area, (3) irrigated paddy field, (4) non-irrigated rural area, (5) dry marginal land and (6) water body. Globally, during the last two decades, regional development led by the Regency occupied more DryMAL area for developing plantation. The effort reduces the amount of non-irrigated and converting to the plantation, pavement areas, and irrigated paddy-field.
Źródło:
Journal of Water and Land Development; 2020, 47; 89-95
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using a GEOBIA framework for integrating different data sources and classification methods in context of land use/land cover mapping
Autorzy:
Osmólska, A.
Hawryło, P.
Powiązania:
https://bibliotekanauki.pl/articles/145304.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
mapa użytkowanych gruntów
mapa pokrycia terenu
mapa leśna
data fusion
random forest
supervised classification
Sentinel-2
Opis:
Land use/land cover (LULC) maps are important datasets in various environmental projects. Our aim was to demonstrate how GEOBIA framework can be used for integrating different data sources and classification methods in context of LULC mapping.We presented multi-stage semi-automated GEOBIA classification workflow created for LULC mapping of Tuszyma Forestry Management area based on multi-source, multi-temporal and multi-resolution input data, such as 4 bands- aerial orthophoto, LiDAR-derived nDSM, Sentinel-2 multispectral satellite images and ancillary vector data. Various classification methods were applied, i.e. rule-based and Random Forest supervised classification. This approach allowed us to focus on classification of each class ‘individually’ by taking advantage from all useful information from various input data, expert knowledge, and advanced machine-learning tools. In the first step, twelve classes were assigned in two-steps rule-based classification approach either vector-based, ortho- and vector-based or orthoand Lidar-based. Then, supervised classification was performed with use of Random Forest algorithm. Three agriculture-related LULC classes with vegetation alternating conditions were assigned based on aerial orthophoto and Sentinel-2 information. For classification of 15 LULC classes we obtained 81.3% overall accuracy and kappa coefficient of 0.78. The visual evaluation and class coverage comparison showed that the generated LULC layer differs from the existing land cover maps especially in relative cover of agriculture-related classes. Generally, the created map can be considered as superior to the existing data in terms of the level of details and correspondence to actual environmental and vegetation conditions that can be observed in RS images.
Źródło:
Geodesy and Cartography; 2018, 67, 1; 99-116
2080-6736
2300-2581
Pojawia się w:
Geodesy and Cartography
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:
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:
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
Tytuł:
Processing of satellite data in the cloud
Autorzy:
Proficz, J.
Drypczewski, K.
Powiązania:
https://bibliotekanauki.pl/articles/1940555.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska
Tematy:
Apache Spark
satellite data
Sentinel-2
ESA
big data
cloud
OpenStack
dane satelitarne
duże zbiory danych
chmura
Opis:
The dynamic development of digital technologies, especially those dedicated to devices generating large data streams, such as all kinds of measurement equipment (temperature and humidity sensors, cameras, radio-telescopes and satellites – Internet of Things) enables more in-depth analysis of the surrounding reality, including better understanding of various natural phenomenon, starting from atomic level reactions, through macroscopic processes (e.g. meteorology) to observation of the Earth and the outer space. On the other hand such a large quantitative improvement requires a great number of processing and storage resources, resulting in the recent rapid development of Big Data technologies. Since 2015, the European Space Agency (ESA) has been providing a great amount of data gathered by exploratory equipment: a collection of Sentinel satellites – which perform Earth observation using various measurement techniques. For example Sentinel-2 provides a stream of digital photos, including images of the Baltic Sea and the whole territory of Poland. This data is used in an experimental installation of a Big Data processing system based on the open source software at the Academic Computer Center in Gdansk. The center has one of the most powerful supercomputers in Poland – the Tryton computing cluster, consisting of 1600 nodes interconnected by a fast Infiniband network (56 Gbps) and over 6 PB of storage. Some of these nodes are used as a computational cloud supervised by an OpenStack platform, where the Sentinel-2 data is processed. A subsystem of the automatic, perpetual data download to object storage (based on Swift) is deployed, the required software libraries for the image processing are configured and the Apache Spark cluster has been set up. The above system enables gathering and analysis of the recorded satellite images and the associated metadata, benefiting from the parallel computation mechanisms. This paper describes the above solution including its technical aspects.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2017, 21, 4; 365-377
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ocena obrazowych danych teledetekcyjnych do identyfikacji obiektów w zielonej i błękitnej infrastrukturze
Assessment of remote sensing image data to identify objects in green and blue infrastructure
Autorzy:
Pluto-Kossakowska, Joanna
Władyka, Monika
Tulkowska, Weronika
Powiązania:
https://bibliotekanauki.pl/articles/132389.pdf
Data publikacji:
2018
Wydawca:
Polskie Towarzystwo Geograficzne
Tematy:
ortofotomapa lotnicza
Sentinel-2
NDVI
BDOT10k
aerial orthophotomap
Opis:
W ostatnich latach koncepcja zielonej i błękitnej infrastruktury zdobywa coraz większe uznanie i coraz częściej jest wdrażana również w polskich miastach i gminach. Pełni wiele ważnych funkcji, począwszy od aspektu rekreacyjnego, ekologicznego i ekonomicznego aż po gospodarczy. Koncepcja ta przywiązuje szczególną wagę do elementów środowiska przyrodniczego przy podejmowaniu decyzji dotyczących głównie zagospodarowania przestrzennego, ale też do aspektów jego monitorowania i zarządzania. Aby sprostać temu zadaniu niezbędne jest odwołanie się do aktualnych danych przestrzennych. Można z powodzeniem wykorzystać istniejące bazy danych przestrzennych, jak np. BDOT10k, Natura 2000 czy inne tematyczne powstające w urzędach miast, np. w biurach ochrony środowiska. Wymagają one jednak ustawicznej aktualizacji i tu w sukurs przychodzą zdjęcia wielospektralne, które mogą znacznie przyspieszyć i zautomatyzować proces aktualizacji bazy danych przestrzennych. W zależności od potrzeb i szczegółowości bazy danych można do tego celu wykorzystać dane optyczne z pułapu lotniczego lub satelitarnego. Celem przeprowadzonych badań jest analiza możliwości wykorzystania ortofotomapy lotniczej oraz zdjęcia satelitarnego Sentinel-2 pozyskanych dla dwóch różnych obszarów badawczych. Do eksperymentów zostały wybrane obszary testowe odmienne pod względem charakterystyki pokrycia terenu, stopnia zainwestowania i krajobrazu. Była to gmina miejsko-wiejska o krajobrazie rolniczym oraz centralna dzielnica miasta wojewódzkiego o wysokim wskaźniku zurbanizowania. Opracowano i przetestowano metodykę przetwarzania ortofotomapy i zdjęcia satelitarnego w celu ekstrakcji informacji o obiektach topograficznych reprezentujących roślinność oraz wody będącymi integralną częścią bazy danych „błękitnej i zielonej infrastruktury”. Przeprowadzone badania i analizy porównawcze wskazały na potencjał i ograniczenia obu źródeł danych teledetekcyjnych.
In recent years, the concept of green and blue infrastructure has been earning recognition and is increasingly being implemented in Polish cities and municipalities. It serves many important functions, ranging from recreational, ecological aspects to economic ones. This concept attaches particular attention to elements of the natural environment when making decisions regarding mainly spatial development, but also to aspects of its monitoring and management. To meet this task, it is necessary to refer to current spatial data. It is possible to successfully use existing spatial databases such as BDOT10k, Natura 2000 or other thematic created in city offices, e.g. in environmental protection offices. However, they require constant updating and here remote sensing data comes in, which speeds up the database update process. Depending on the needs and detail of the database, you can obtain data for this purpose from both the air and satellite altitude. The purpose of the research was to analyze the possibilities of using an aerial orthophotomap and a Sentinel-2 satellite image obtained for two different research areas. Test areas that were different in terms of land cover and local government units were selected for the experiments. It was an urban-rural commune with an agricultural landscape and the central district of a selected provincial city with a high urban index. The methodology of orthophotomap and satellite image processing and extraction of information about topographic objects related to vegetation and waters being an integral part of the „blue and green infrastructure” database was developed and tested. The conducted research and comparative analyzes indicated the potential and limitations of both sources of remote sensing data.
Źródło:
Teledetekcja Środowiska; 2018, 59; 13-27
1644-6380
Pojawia się w:
Teledetekcja Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Monitorowanie zasięgu roślinności o charakterze leśnym w obszarach rekultywowanych z zastosowaniem zobrazowań satelitarnych Sentinel-2
Monitoring the spatial range of forested areas in the reclaimed sites using Sentinel-2 images
Autorzy:
Szostak, M.
Knapik, K.
Likus-Cieślik, J.
Wężyk, P.
Pietrzykowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/980307.pdf
Data publikacji:
2019
Wydawca:
Polskie Towarzystwo Leśne
Tematy:
tereny rekultywowane
zadrzewienia
zasieg wystepowania
pokrycie terenu
monitoring
satelita Sentinel-2
obrazowanie
przetwarzanie obrazow
wektoryzacja
analiza przestrzenna
image processing
manual vectorization
spatial analyses
reclamation
Opis:
Presented research investigates the possibility of applying the newest, free available satellite images Sentinel−2 for the automation of land use/cover (LULC) mapping in reclaimed areas, mainly in the aspect of monitoring forested areas. The study was performed for the former sulphur mines: ‘Machów’ (871.7 ha of the dump area after the opencast strip mine) and ‘Jeziórko’ (216.5 ha of the afforested area after the borehole exploitation). These areas are characterized by a diverse terrain structure and vegetation cover as the result of reclamation. The applied directions of reclamation were agro−forestry for the Sulphur Mine ‘Machów’ and forestry for the Sulphur Mine ‘Jeziórko’. We verified whether processing of Sentinel−2 data allows for reliable LULC classification – mainly identification forested areas in relation to the LULC mapping prepared by manual vectorization of orthophotomaps. Obtained classification results for Sentinel−2 data were also compared to the results of Landsat 8 images processing. The results of Sentinel−2 images classification showed correct graphical representation of the LULC classes, especially forested areas, in the relation to the results of applied on−screen vectorization of aerial orthophotomaps – better than results of the Landsat 8 images processing. The area of the mail class ‘Forests’ as a result of classification Sentinel−2 and Landsat 8 images compared to the results of manual on−screen vectorization of the orthophomaps shows differences: 5.4% – Sentinel−2, 12.8% – Landsat 8 for Sulphur Mine ‘Machów’ and 1.8% – Sentinel−2, 8.8% – Landsat 8 for Sulphur Mine ‘Jeziórko’. Research indicates the possibility of automation of LULC classification using Sentinel−2 images. It could be very useful for LULC changes monitoring in reclaimed areas, mainly in the aspect of forested areas mapping as a result of way of reclamation.
Źródło:
Sylwan; 2019, 163, 01; 55-61
0039-7660
Pojawia się w:
Sylwan
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Metastatic and non-metastatic sentinel inguinofemoral lymph nodes in vulvar cancer show an increased lymphangiogenesis
Autorzy:
Piechowicz, M.
Mikos, M.
Banas, T.
Okon, K.
Pietrus, M.
Balajewicz-Nowak, M.
Szczudlik, L.
Kojs, Z.
Czerw, A.
Juszczyk, G.
Pityński, K.
Powiązania:
https://bibliotekanauki.pl/articles/2085422.pdf
Data publikacji:
2020
Wydawca:
Instytut Medycyny Wsi
Tematy:
anti-D2–40 antibody
lymphatic vessel density
immunohistochemistry
sentinel lymph node
vulvar cancer
Opis:
Introduction and objective. Lymph node involvement is a strong predictor of disease recurrence and patient survival in vulvar cancer. The aim of the study was to evaluate the feasibility of sentinel lymph node (SLN) screening, the incidence of skip metastases, and lymph node lymphangiogenesis. Materials and method. Fifty-five patients participated in this prospective, single centre study. A double SLN screening method was employed using radiocolloid (technetium-99 sulfur colloid) and 1.0% Isosulfan Blue. Immunohistochemistry, using a mouse monoclonal antibody against D2–40, was used to evaluate lymphatic vessel density (LVD). All calculations were performed using STATISTICA software v. 10 (StatSoft, USA, 2011); p<0.05 was considered significant. Results. Using both methods of SLN detection, 100% accuracy was achieved, and skip metastases were diagnosed in only one woman (1.82%). Peri-tumour median LVD was significantly increased compared with matched intra-tumour samples (p<0.001), while median LVD was significantly lower in negative, compared with positive SLN, regardless of whether matched non-SLN were negative (p<0.001) or positive (p=0.005). Metastatic SLN exhibited significantly higher median LVD compared with matched negative non-SLN (p=0.015), while no significant difference in median LVD was detected between positive SLN and matched positive non-SLN. However, negative SLN had a significantly higher median LVD compared with matched negative non-SLN (p = 0.012). Conclusions. SLN detection is a safe and feasible procedure in vulvar cancer. In patients without nodular involvement, SLN, compared with non-SLN, exhibited significantly higher median LVD, which may be an indication of its preparation to host metastases, and thus requires further investigation.
Źródło:
Annals of Agricultural and Environmental Medicine; 2020, 27, 1; 123-128
1232-1966
Pojawia się w:
Annals of Agricultural and Environmental Medicine
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Mapping of windstorm damage occurring in the forest stands of Czerniejewo forest district (Polish State Forests National Holding) using aerial photographs and sentinel-2 satellite imagery
Wykorzystanie ortofotomap lotniczych oraz zobrazowań satelitarnych Sentinel-2 w procesie określania uszkodzeń drzewostanów w Nadleśnictwie Czerniejewo (RDLP Poznań) spowodowanych przez huragan
Autorzy:
Krawczyk, Wojciech
Wężyk, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/28407807.pdf
Data publikacji:
2020
Wydawca:
Stowarzyszenie Geodetów Polskich
Tematy:
hurricane
forest stands damage assessment
aerial orthophoto
Sentinel-2
nawałnica
określanie zasięgu uszkodzeń drzewostanów
ortofotomapa lotnicza
Opis:
On the night of 11 and 12.08.2017 a severe hurricane passed over Poland, in a belt of almost 300 km, causing damage in forest stands of area exceeding 100 000 ha. The study aimed to demonstrate the implementation of remote sensing technologies in the process of determining the extent of forest stand damages in the Czerniejewo Forest District (RDLP Poznań) caused by wind and monitoring the progress of clean-up work. In this study were used digital aerial orthophotos commissioned by the State Forests National Forest Holding (PGL LP) and Sentinel-2 (ESA) satellite images as well. The area of damaged stands was determined with the use of two approaches, i.e.: supervised classification (approach A) and thresholding of values of Normalised Difference Vegetation Index - NDVI (approach B). The obtained results were compared to reference data obtained by visual interpretation of high resolution RGB aerial orthophotos by RDLP Poznań experts. Monitoring of the progress of the clean-up works in damaged stands was carried out in 9-time intervals. The conducted image classification and spatial GIS analyses showed that the area of stands damaged by the wind was for methods A and B: 579.16 ha and 516.01 ha, respectively, with 631.00 ha as the reference. The results obtained in the study indicate errors in underestimating the area of forest stand damage based on Sentinel-2, i.e.: 51.84 ha (8.2%) in the case of method A and by 114.99 ha (18.2%) for method B. In the whole analysed time, clean-up operations were carried out on the total area of 762.33 ha of damaged forest stands, and their highest intensity was observed in the first 4 months after the storm. The work showed the applicability of free of charge Sentinel-2 (ESA) satellite imagery in the process of determining the extent of forest stand damages, pointing to the supervised classification method (Maximum Likelihood algorithm; ML) as more accurate than using the threshold of NDVI.
W nocy 11/12.08.2017 nad Polską, w pasie o długości niemal 300 km, przeszła bardzo silna nawałnica powodując zniszczenia drzewostanów na obszarze 100 000 ha. Celem prezentowanej pracy było zademonstrowanie implementacji technologii teledetekcyjnych w procesie określania zasięgu uszkodzeń drzewostanów w Nadleśnictwie Czerniejewo (RDLP Poznań) spowodowanych przez wiatr oraz monitorowania postępu prac uprzątających. W pracy wykorzystano wykonane na zlecenie PGL Lasy Państwowe cyfrowe ortofotomapy lotnicze, a także zobrazowania satelitarne z misji Sentinel-2 (ESA). Powierzchnię uszkodzonych drzewostanów określano dwoma metodami, tj.: klasyfikacji nadzorowanej - metoda A oraz progowania wartości znormalizowanego wskaźnika roślinności (NDVI) - metoda B. Otrzymane wyniki porównano do danych referencyjnych uzyskanych na drodze interpretacji wzrokowej wysokorozdzielczych ortofotomap lotniczych RGB dokonanych przez ekspertów RDLP Poznań. Monitorowania postępu prac uprzątających prowadzonych w zniszczonych drzewostanach dokonano w 9 przedziałach czasowych. Analizy przestrzenne GIS wykazały, iż powierzchnia uszkodzonych przez wiatr drzewostanów wyniosła dla metody A oraz B, odpowiednio: 579.16 ha oraz 516.01 ha, przy czym za referencję przyjęto 631.00 ha. Uzyskane w pracy wyniki wskazują na błędy niedoszacowania obszaru zniszczeń drzewostanów, tj.: 51.84 ha (8.2%) dla metody A oraz o 114.99 ha (18.2 %) dla metody B. W ciągu całego analizowanego okresu prace uprzątające wykonano na łącznej powierzchni 762.33 ha uszkodzonych drzewostanów, przy czym największą ich intensywność stwierdzono w pierwszym okresie 4 miesięcy po wystąpieniu nawałnicy. Praca wykazała przydatność nieodpłatnych zobrazowań satelitarnych Sentinel-2 (ESA) w procesie określania zasięgu uszkodzeń drzewostanów, wskazując na metodę klasyfikacji nadzorowanej (algorytm maksymalnego prawdopodobieństwa) jako dokładniejszą, niż korzystanie z wartości wskaźnika roślinnego NDVI.
Źródło:
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2020, 32; 13--35
2083-2214
2391-9477
Pojawia się w:
Archiwum Fotogrametrii, Kartografii i Teledetekcji
Dostawca treści:
Biblioteka Nauki
Artykuł
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