Temat: Sentinel-2 - Katalog OPAC zbiorów

Skocz do pozycji: 1.

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

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Skocz do pozycji: 2.

Tytuł:: Application of geomatic tools for the diachronic monitoring of landscape metrics in the northeastern algerian highlands, case of the city of Setif
Autorzy:: Kraria, Hocine
Zighmi, Karim
Chibani, Abdelmouhcene
Powiązania:: https://bibliotekanauki.pl/articles/2201671.pdf
Data publikacji:: 2022
Wydawca:: Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie
Tematy:: LAUP
GIS
RS
PCA
Sentinel 2A
Landsat
Opis:: Geomatic tools could be used efficiently for urban development planning. The problem of the study lies in the extensive land use of terrains that are now suitable for heavy construction which slows down the development of new facilities. Furthermore, the authorities are forced to plan future settlements around Setif, at a distance of 8 to 12 kilometers from the city limits, threatening the long-term viability of construction and the ring of farmland that connects them to the core city. This must be done during the planning stage based on a diachronic analysis of all the natural and physical factors/parameters. The main objective of this research is to explore the application of landscape metrics to the analysis and monitoring of urban growth in the city of Setif, north-east of Algeria. For this purpose, our research paper uses Geographic Information System (GIS) and Remote Sensing (RS) techniques based on Principal Component Analysis (PCA) and the Angle Mapper Algorithm (SAM) target method for the analysis of urban land planning and sustainable urban planning of Setif. In the result of these analyses we propose suitability/buildability maps with more suitable construction sites. The research method is based on a 17-year time series dataset compiled from the Sentinel 2A and Landsat imagery between 2004 and 2021. Additionally, we used a cadastral Vs geotechnical overlay to estimate soil capacity. This work proves again that the integration of RS and GIS techniques allows for scientific identification of the lands suitable for urban development (LAUP).
Źródło:: Geomatics, Landmanagement and Landscape; 2022, 4; 67--79
2300-1496
Pojawia się w:: Geomatics, Landmanagement and Landscape
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Application of Sentinel-2 and EnMAP new satellite data to the mapping of alpine vegetation of the Karkonosze Mountains
Autorzy:: Jędrych, M.
Zagajewski, B.
Marcinkowska-Ochtyra, A.
Powiązania:: https://bibliotekanauki.pl/articles/92448.pdf
Data publikacji:: 2017
Wydawca:: Oddział Kartograficzny Polskiego Towarzystwa Geograficznego
Tematy:: Sentinel-2
EnMAP
classification
alpine vegetation
satellite systems
Opis:: Effective assessment of environmental changes requires an update of vegetation maps as it is an indicator of both local and global development. It is therefore important to formulate methods which would ensure constant monitoring. It can be achieved with the use of satellite data which makes the analysis of hard-to-reach areas such as alpine ecosystems easier. Every year, more new satellite data is available. Its spatial, spectral, time, and radiometric resolution is improving as well. Despite significant achievements in terms of the methodology of image classification, there is still the need to improve it. It results from the changing needs of spatial data users, availability of new kinds of satellite sensors, and development of classification algorithms. The article focuses on the application of Sentinel-2 and hyperspectral EnMAP images to the classification of alpine plants of the Karkonosze (Giant) Mountains according to the: Support Vector Machine (SVM), Random Forest (RF), and Maximum Likelihood (ML) algorithms. The effects of their work is a set of maps of alpine and subalpine vegetation as well as classification error matrices. The achieved results are satisfactory as the overall accuracy of classification with the SVM method has reached 82% for Sentinel-2 data and 83% for EnMAP data, which confirms the applicability of image data to the monitoring of alpine plants.
Źródło:: Polish Cartographical Review; 2017, 49, 3; 107-119
2450-6974
Pojawia się w:: Polish Cartographical Review
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Free water table area monitoring on wetlands using satellite and UAV orthophotomaps - Kampinos National Park case study
Autorzy:: Góraj, Maciej
Wróblewski, Cezary
Ciężkowski, Wojciech
Jóźwiak, Jacek
Chormański, Jarosław
Powiązania:: https://bibliotekanauki.pl/articles/1203882.pdf
Data publikacji:: 2019
Wydawca:: Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy
Tematy:: UAV
Sentinel-2
machine learning
surface water
inundation
wetlands
Opis:: The surface water table level is a crucial factor for the existence of wetland habitats, and valuable from the point of view of environmental protection. In particular, surface water table in a hydrological year play an important role, affecting the seasonal changes in conditions of the development of species inhabiting a given patch of vegetation. The occurrence of floods often determines the possibility of survival of a given plant community. Information on the seasonal variability of surface waters, and above all the range of seasonal floods, is very important from the point of view of planning protection activities in National Parks in order to preserve wetland habitats. Nowadays, remote sensing data is an important source of spatial information, particularly those characterized by low cost data acquisition and processing. One such source is imagery collected from satellites, along with products freely distributed by the European Space Agency. Satellites of the Sentinel constellation provide multi-spectral optical remote sensing images recorded at visible and infrared wavelengths. Due to the short satellite revisit time of the Sentinel, the images from this satellite constitute a potential source of information for the monitoring of moisture on wetlands with a high temporal resolution. In this study, the authors aim to demonstrate the possibilities associated with the use of satellite images to monitor the range of a free surface water table in the pilot area located within the basin of the Łasica Channel, located in the Kampinos National Park (Poland). The accuracy of the results of the remote sensing transformations will be assessed using high resolution RGB images obtained with the use of unmanned aerial vehicles (UAV) and control points measurements. The maps of free water table has been acquired as an result of ensemble regressors (Random Forest, Extra Trees, Bagging). Regressors has been learned and applied for two sessions. Promising results were obtained indicating the possibility of using the proposed method on a similar scale.
Źródło:: Meteorology Hydrology and Water Management. Research and Operational Applications; 2019, 7, 1; 23-30
2299-3835
2353-5652
Pojawia się w:: Meteorology Hydrology and Water Management. Research and Operational Applications
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

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

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Skocz do pozycji: 6.

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

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Skocz do pozycji: 7.

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

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Skocz do pozycji: 8.

Tytuł:: Forest Community Mapping Using Hyperspectral (CHRIS/PROBA) and Sentinel-2 Multispectral Images
Autorzy:: Głowienka, Ewa
Zembol, Nicole
Powiązania:: https://bibliotekanauki.pl/articles/2174650.pdf
Data publikacji:: 2022
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: hyperspectral
pre-processing
multispectral
Sentinel-2
CHRIS/PROBA
machine learning
Opis:: The possibility to use hyperspectral images (CHRIS/PROBA) and multispectral images (Sentinel-2) in the classification of forest communities is assessed in this article. The pre-processing of CHRIS/PROBA image included: noise reduction, radiometric correction, atmospheric correction, geometric correction. Due to MNF transformation the number of the hyperspectral image channels was reduced (to 10 channels) and smiling errors were removed. Sentinel-2 image (level 2A) did not require pre-processing. Three tree genera occurring in the study area were selected for the classification: pine (Pinus), alder (Alnus) and birch (Betula). Image classification was carried out with three methods: SAM (Spectral Angle Mapper ), MTMF (Mixture Tuned Matched Filtering), SVM (Support Vector Machine). For the CHRIS/PROBA image, the algorithm SVM turned out to be the best. Its overall accuracy (OA) was 72%. The poorest result (OA = 52%) was for the MTMF classifier. In the classification of Sentinel-2 multispectral image the best result was for the MTMF method: OA = 82%, kappa coefficient 0.7. For other methods, the overall accuracy exceeded 65%. Among the classified genera, the highest producer’s accuracy was obtained for pine (PA = 96%), and the broad-leaf genera: alder and birch had PA ranging from 42% to 85%.
Źródło:: Geomatics and Environmental Engineering; 2022, 16, 4; 103--117
1898-1135
Pojawia się w:: Geomatics and Environmental Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Agricultural Droughts Monitoring of Aceh Besar Regency Rice Production Center, Aceh, Indonesia – Application Vegetation Conditions Index using Sentinel-2 Image Data
Autorzy:: Sugianto
Rusdi, Muhammad
Budi, Muhammad
Farhan, Ahmad
Akhyar
Powiązania:: https://bibliotekanauki.pl/articles/2202332.pdf
Data publikacji:: 2023
Wydawca:: Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:: drought monitoring
VCI
vegetation condition index
sentinel-2A
vegetation health index
Opis:: Monitoring the agricultural drought of paddy rice fields is a crucial aspect of preparing for proper action in maintaining food security in Indonesia. The Aceh Province is one of Indonesia’s national rice production centers, especially Aceh Besar Regency; it includes three central districts; Indrapuri, Kuta Cot Glie, and Seulimeum. Satellite-Sentinel 2A data have been tested to monitor the drought levels of around 2,803 Ha in the three districts in this study. This study aimed to determine the drought level in Indrapuri, Kuta Cot Glie, and Seulimeum districts, Aceh Besar Regency’s paddy rice fields using Sentinel-2A data imagery. The vegetation conditions index (VCI) of Sentinel-2 data was utilized to identify a vegetative drought level in the area for the 2018, 2019, 2020, 2021, and 2022 growing seasons. The vegetation inertia index is derived from the Normalized Difference Vegetation Index (NDVI). The results show that the VCI looked volatile, but the trendline increased by four percent, from 92.56 in July 2019 to 96.08 in July 2021. Most areas on the dates investigated found that the no drought category was still dominant. The designated data analyzed found that the June 2022 data tend to be distributed to the drought in extreme, severe, moderate, and mild increases compared to the previous data investigated. This figure shows an increasing drought in the study area, and the average drought index is in the category of mild drought. In addition, there has been a trendline decline in the value of NDVI in recent years, causing agricultural land for paddy rice fields to be slightly vulnerable to drought.
Źródło:: Journal of Ecological Engineering; 2023, 24, 1; 159--171
2299-8993
Pojawia się w:: Journal of Ecological Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: An analysis of flooding coverage using remote sensing within the context of risk assessment
Autorzy:: Solovey, Tatiana
Powiązania:: https://bibliotekanauki.pl/articles/94266.pdf
Data publikacji:: 2019
Wydawca:: Uniwersytet im. Adama Mickiewicza w Poznaniu
Tematy:: Sentinel-2
Remote Sensing
flood mapping
Water Indexes
teledetekcja
mapowanie powodzi
wskaźnik wody
Opis:: Results of research of the identification of flooding as a result of groundwater table fluctuations on the example of the valley of the River Vistula, with the use of multi-spectral Sentinel-2 images from the years 2017-2018 are presented. An analysis of indexes of water use, calculated on the basis of green, red and shortwave infrared (SWIR) bands, for extraction of water objects and flooded areas was carried out. Based on the analyses conducted, a mapping method was developed, using three water indexes (MNDWI Modified Normalised Difference Water Index, NDTI Normalised Difference Index and NDPI Normalised Difference Pond Index). Results show that the 10 metre false colour composite R_NDTIG_NDPIB_MNDWI obtained significantly improved submerged extractions more than did individual water indexes. Moreover, the 10-m-images of MNDWI and NDPI, obtained by the sharpening High Pass Filter (HPF), may represent more detailed spatial information on floods than the 20-m-MNDWI and NDPI, obtained from original images.
Źródło:: Geologos; 2019, 25, 3; 241-248
1426-8981
2080-6574
Pojawia się w:: Geologos
Dostawca treści:: Biblioteka Nauki

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