Browsing by Subject "remote sensing"

Now showing 1 - 20 of 55

Access status: Open Access ,
A brief review of recent developments in the integration of deep learning with GIS
(Wydawnictwa AGH, 2022) Mohan, Shyama; Giridhar, M.V.S.S.
The interaction of Deep Learning (DL) methods with Geographical Information System (GIS) provides the opportunity to obtain new insights into environmental processes through the spatial, temporal and spectral resolutions as well as data integration. The two technologies may be connected to form a dynamic system that is incredibly well adapted to the evaluation of environmental conditions through the interrelationships of texture, size, pattern, and process. This perspective has acquired popularity in multiple disciplines. GIS is significantly dependant on processors, particularly for 3D calculations, map rendering, and route calculation whereas DL can process huge amounts of data. DL has received a lot of attention recently as a technology with a plethora of promising results. Furthermore, the growing use of DL methods in a variety of disciplines, including GIS, is evident. This study tries to provide a brief overview of the use of DL methods in GIS. This paper introduces the essential DL concepts relevant to GIS, the majority of which have been published in recent years. This research explores remote sensing applications and technologies in areas such as mapping, hydrological modelling, disaster management, and transportation route planning. Finally, conclusions on contemporary framework methodologies and suggestions for further studies are provided.
Access status: Open Access ,
A machine learning model for improving building detection in informal areas - a case study of Greater Cairo
(Wydawnictwa AGH, 2022) Taha, Lamyaa Gamal El-deen; Ibrahim, Rania Elsayed
Building detection in Ashwa'iyyat is a fundamental yet challenging problem, mainly because it requires the correct recovery of building footprints from images with high-object density and scene complexity. A classification model was proposed to integrate spectral, height and textural features. It was developed for the automatic detection of the rectangular, irregular structure and quite small size buildings or buildings which are close to each other but not adjoined. It is intended to improve the precision with which buildings are classified using scikit learn Python libraries and QGIS. WorldView-2 and Spot-5 imagery were combined using three image fusion techniques. The Grey-Level Co-occurrence Matrix was applied to determine which attributes are important in detecting and extracting buildings. The Normalized Digital Surface Model was also generated with 0.5-m resolution. The results demonstrated that when textural features of colour images were introduced as classifier input, the overall accuracy was improved in most cases. The results show that the proposed model was more accurate and efficient than the state-of-the-art methods and can be used effectively to extract the boundaries of small size buildings. The use of a classifier ensample is recommended for the extraction of buildings.
Access status: Open Access ,
An analysis of the spatial and temporal changes on the Jakobshavn Glacier (Greenland) using remote sensing data
(Wydawnictwa AGH, 2021) Olszewska, Katarzyna; Borowiec, Natalia
This article presents the problem of climate warming and the effect of melting ice caps. The problem of climate warming is discussed in two stages. In the first stage, the factors affecting global warming are discussed in detail and the effects and risks of ablation extensively described. Analyses were conducted on data available online from NASA and Carbon Dioxide Information Analysis Center. The Greenland area (Jakobshavn Glacier) was selected to visualize glacier calving front changes. The analysis of changes was performed on the selected satellite images covering the summer period (June to September) provided by the Landsat program. Then, the changes in the position of the calving front of the Jakobshavn Glacier were visualized for the period 1985–2020, with a repeatability of every 5 years. Thus, our results addressed the challenges of environmental changes to remote sensing data processing. In addition to the visualization, a surface summary of these changes was presented in the study. The results were discussed in the context of climate change data processed by means of the GIS method. Furthermore, an analysis of the effects of greenhouse gases on glacier surface changes was performed. In summary, the results reveal that satellite imagery is an excellent source of data on which to visualize glacier calving rates, comparing individual layers showing the position of the glacier calving front and calculating the area of calved ice.
Access status: Open Access ,
An empirical analysis of changes in the Błędów Desert using machine learning methods
(Wydawnictwa AGH, 2025) Czernik, Anna; Borowiec, Natalia; Marmol, Urszula
The aim of the study was to determine changes in the land cover of the Błędów Desert, which is a habitat for rare flora and fauna species protected under the Natura 2000 program. Invasive plants, which pose a threat to protected species, are present in this area. Additionally, human activities can have negative impacts on the desert ecosystem. Therefore, the land manager is obligated to carry out actions aimed at maintaining the appropriate size and character of the desert. The analysis was conducted using satellite imagery from the Sentinel-2 mission, which provides images with high temporal and spatial resolution. The study covered the years 2015–2022 and took into account seasonal variability due to the presence of green vegetation. Change detection methods based on data integration, including photointerpretation and machine learning classification, were used for land cover analysis. Five representative land cover classes were defined, enabling a quantitative presentation of changes in the Błędów Desert and a qualitative assessment of the classification performed. The results of the study indicate variability in land cover depending on the season, with an increasing number of protected plant species, including grasslands. Simultaneously, a slight increase in the desert area was noted, manifesting as an increase in sand in forested areas. The results obtained demonstrate the effective implementation of the Natura 2000 program objectives.
Access status: Open Access ,
Analysis of spatial‑temporal changes of agricultural land use during the last three decades in the Araban district of Turkey using remote sensing
(Wydawnictwa AGH, 2021) Tunç, Erdihan; Tsegai, Awet Tekeste; Çelik, Sevil
Agricultural land use and land cover dynamics were investigated in the Araban district of Turkey during the periods 1984-2019 by the use of Remote Sensing and Geographic Information Systems (GIS). Landsat‑TM andLandsat‑TIRS/OLI satellite imageries were used to determine land use and land cover changes. Using unsupervised classification method of ERDAS 8.3 software, three main ag‑ ricultural activities were identified namely irrigated farming, dry farming, and horticultural/garden farming. The analysis has revealed that during the last three decades dry farming has decreased significantly by 14.69% (3802.14 ha) whereas horticultural/garden crops and irrigated farming lands have increased by 11.32% (667.19 ha) and 2.51% (2929.41 ha) respectively. Araban has been under intensive agricultural use due to its fertile soil and preference for horticultural crops such as pistachio, grapes and olives that provide more profit over dry farming crops such as wheat and barley has changed land use. Decrease in dry farming in a semi‑arid climate where Araban is located, has a potential ecological consequence, including a rapid drop of groundwater level, drying of wetlands and the disappearance of the biodiversity, thus, a necessary measures should be taken to implement an environmentally friendly, sustainable agriculture and settlement plan.
Access status: Open Access ,
Application of satellite monitoring data for winter cereals growing in the Lviv region
(Wydawnictwa AGH, 2020) Stupen', Mihajlo Grigorovič; Stupenʹ, Nazar Mihajlovič; Rižok, Zorâna Ruslanìvna; Stupenʹ, Oksana Ìvanìvna
The authors applied satellite monitoring data of agricultural lands of the geographic information system of International Production Assessment Division of the United States Department of Agriculture on the example of winter cereal cultivation. The authors did so according to the indices of vegetation index NDVI, information on atmospheric precipitation, soil moisture, and air temperature compared to Earth observations to estimate the condition of their sowing area. According to the research results, one can use remote sensing data of the IPAD USDA geographic information system to monitor agricultural land, yield capacity prediction and the estimation of gross agricultural products.
Access status: Open Access ,
Assessing the shallow water habitat mapping extracted from high-resolution satellite image with multi classification algorithms
(Wydawnictwa AGH, 2023) Nandika, Muhammad Rizki; Ulfa, Azura; Ibrahim, Andi; Purwanto, Anang Dwi
Remote sensing technology is reliable in identifying the distribution of seabed cover yet there are still challenges in retrieving the data collection of shallow water habitats than with other objects on land. Classification algorithms based on remote sensing technology have been developed for application to map benthic habitats, such as Maximum Likelihood, Minimum Distance, and Support Vector Machine. This study focuses on examining those three classification algorithms to retrieve information on the benthic habitat in Pari Island, Jakarta using visual interpretation data for classification, and data field measurements for accuracy testing. This study used five classes of benthic objects, namely sand, sand-seagrass, rubble, seagrass, and coral. The results show how the proposed approach in this study provides an overall good classification of marine habitat with an accuracy produced 63.89-81.95%. The Support Vector Machine algorithm produced the highest accuracy rate of about 81.95%. The Support Vector Machine algorithm at a very high spatial resolution is considered to be capable of identifying, monitoring, and performing the rapid assessment of benthic habitat objects.
Access status: Open Access ,
Assessment of the 2010 Kura river flood using remote sensing data and GIS tools
(Wydawnictwa AGH, 2017) Aghayev, Amil T.
In the Kura River basin fl oods occur frequently and pose a major threat for the local population. This research aims to test if freely available remotely sensed data may provide valuable information on flood extent in this region. Flood in 2010 was analysed as a flood event example. Various maps illustrating this event were collected and compared to satellite Landsat data. A map of the fl ooded areas was developed with ArcGIS 10.2.1 software. Attention was paid to the identifi cation of inundated areas. It was found that there were serious faults in the map prepared by the responsible government agencies. On the basis of satellite image interpretation, districts completely and partly damaged by the flood were determined and mapped.
Access status: Open Access ,
Bibliografia prac na temat teledetekcyjnych metod kontroli środowiska opublikowanych przez autorów w latach 1977-2005
(Wydawnictwa AGH, 2005) Dworak, Tadeusz Zbigniew; Hejmanowska, Beata ; Pyka, Krystian
The article contains the list of 93 papers published by us in the years 1977-2005. The aim of this bibliography is to present whole our knowledge within remote sensing methods for the investigation and control of the environment - natural and anthropogenic.
Access status: Open Access ,
Delineation of Groundwater Storage and Recharge Potential Zones Using Multi-Influencing Factors (MIF) Method: Application in Synclinal Coastal Basin of Essaouira (Western High Atlas of Morocco)
(Wydawnictwa AGH, 2024) Agli, Saloua; Ahmed, Algouti; Abdellah, Algouti; Abdelouahed, Farah; Moujane, Said; Salma, Kabili; Maryam, Errami
Unpredictable rainfall caused by climate change and pollution directly impacts groundwater demand, making the exploitation of groundwater reserves necessary. To achieve this, a study in the synclinal basin of Essaouira (Western High Atlas) used GIS, remote sensing, and the Multi-Influencing Factors (MIF) method, to identify areas ideal for the installation of productive wells. An overlay analysis created a groundwater potential zone (GWPZ) map, showing 30% of the basin with high potential, 51% with moderate potential, and 19% with low to very low potential. The groundwater potential zone map was validated using geophysical surveys, piezometric data, and well water levels, showing a 69.3% prediction accuracy with the ROC curve.
Access status: Open Access ,
Department of Geoinformatics and Applied Computer Science
(Wydawnictwa AGH, 2016) Chuchro, Monika; Leśniak, Andrzej
Access status: Open Access ,
Designation of flood risk zones using the Geographic Information System Technique and remote sensing data in Wasit, Iraq
(Wydawnictwa AGH, 2021) Rasn, Kouther Hasheem; Nsaif, Qutaiba Abdulwahhab; Al-Obaidi, Mudhar; John, Yakubu Mandafiya
Floods are a great concern for people and infrastructure, and this is an is‑sue which has increased in several regions around the globe in recent years. This study aims to evaluate flood risk areas and create a flood risk map using in‑tegrated remote sensing data and a geographic information system (GIS) in the Wasit governorate - eastern Iraq. Specifically, GIS‑based multi‑criteria analy‑sis (MCA) was used to map flood hazard areas using a four‑criteria layer which is as follows: flow accumulation, slope, rainfall, and elevation. These four layers are standardized and combined using the overlay approach in ArcGIS software and a final map was produced. The study area was divided into five zones based on the results map, namely: very low, low, medium, high, and very high, according to the flood risk area. The resulting map indicates that over 60% of the study area is likely to experience a high and very high level of propensity of flooding. This study could be useful for government planners and decision‑makers to predict potential flooding areas and enhance flood management plans.
Access status: Open Access ,
Development of flood-hazard-mapping model using random forest and frequency ratio in Sumedang Regency, West Java, Indonesia
(Wydawnictwa AGH, 2023) Ismanto, Rido Dwi; Fitriana, Hana Listi; Manalu, Johanes; Purboyo, Alvian Aji; Prasasti, Indah
Flooding, often triggered by heavy rainfall, is a common natural disaster in Indonesia, and is the third most common type of disaster in Sumedang Regency. Hence, flood-susceptibility mapping is essential for flood management. The primary challenge in this lies in the complex, non-linear relationships between indices and risk levels. To address this, the application of random forest (RF) and frequency ratio (FR) methods has been explored. Ten flood-conditioning factors were determined from the references: the distance from a river, elevation, geology, geomorphology, lithology, land use/land cover, rainfall, slope, soil type, and topographic wetness index (TWI). The 35 flood locations from the flood-inventory map were selected, and the remaining 18 flood locations were used for justifying the outcomes. The flooded areas from the RF model were 28.39%, the rest (71.61%) were non-flooded areas. Also, the flooded areas from the FR method were 8.02%, and the non-flooded areas were 91.98%. The AUC for both methods was a similar value – 83.0%. This result is quite accurate and can be used by policymakers to prevent and manage future flooding in the Sumedang area. These results can also be used as materials for updating existing flood-susceptibility maps.
Access status: Open Access ,
Fotogrametria i teledetekcja w europejskich programach geinformacyjnych
(Wydawnictwa AGH, 2006) Linsenbarth, Adam
The policy of the European Union must be based on condense and up-to date spatial information, necessary both to create the policy of the European Union as well as to implement and monitor the resolutions resulting from the directives of the Union. Two programmes of the European Union meet these expectations. These are INSPIRE and GMES programme. This article presents these programmes, focussing of the role of photogrammetry and remote sensing. The work on the project of the INSPIRE programme, referring to the European Infrastructure of Spatial Data started at the end of 1990s. As the result of the activities of the Group of Experts of programme INSPIRE and several Working Groups, preliminary premises for the INSPIRE programme were made. The result of this work was making the project of the Directive INSPIRE, which, on 23rd July 2004 was submitted to the Parliament and Council of the European Union for the legislation process. As the result of the work done in both these bodies, a document was issued. The title of the document was: Common Statement of the Council. The term of voting is June 2006, at the plenary session of the European Parliament. According to this document, the basic source of terrain information should be satellite or airborne orthophotomaps. Programme GMES (Global Monitoring of Environment and Security) realized by the European Commission and European Space Agency refers to permanent monitoring of our continent and mainly the use of Earth and large city agglomerations. Main source of information in this programme will be medium and high resolution satellite images.
Access status: Restricted ,
Geological mapping of North Wazirstan, Pakistan using remotely sensed images
(Data obrony: 2017-10-06) Nawaz, Adil
Wydział Geologii, Geofizyki i Ochrony Środowiska
Digitally enhanced OLI Landsat 8 images were applied for mapping of North Waziristan Pakistan. The territory is rough and without rich vegetation; the exposure of the Waziristan ophiolite, related sedimentary lithologies and inaccessibility to the area made the utilization of Landsat information helpful in this investigation. In the remote sensing investigation, Landsat 8 OLI data were used to make band ratios, band combinations, principal component and image classification methods. Multispectral images were prepared and investigated for this study. On the basis of the image classification techniques; unsupervised classification, five principle lithological units are marked which are giving satisfactory results (about 63.07 %.) when compared with referenced geological map using confusion matrix analysis. The outcomes are very satisfied and need to examine about the utility and confinements of remote sensing strategy on the investigation zone. Further to confirm the results of unsupervised classification, extra investigations might be helpful. As a results, issues confronted during the classification must be considered into all general accuracy.
Access status: Restricted ,
Geological mapping of the Altiplano (SW Bolivia) based on remotely sensed images
(Data obrony: 2017-10-06) Rędziak, Jakub
Wydział Geologii, Geofizyki i Ochrony Środowiska
Tematem niniejszej pracy magisterskiej jest tworzenie mapy litologicznej skał i osadów wyeksponowanych na powierzchni za pomocą wielospektralnych zdjęć teledetekcyjnych. Korzystne warunki panujące w Altiplano (Boliwia) zachęcają do wykonywania badań teledetekcyjnych właśnie tutaj. Obszar ten charakteryzuje się suchym klimatem, brakiem szaty roślinnej oraz doskonale widocznymi ekspozycjami skał. Mapa powstała na podstawie zdjęć teledetekcyjnych pobranych ze strony https://earthexplorer.usgs.gov/. Za pomocą tego zestawu danych, stworzone zostały odpowiednie kompozyty, indeksy międzykanałowe oraz obie klasyfikacje - ISO oraz nadzorowana.
Access status: Restricted ,
Geological mapping of the area of Kielce (south-central Poland) based on remotely sensed images
(Data obrony: 2017-10-06) Misiak, Radosław
Wydział Geologii, Geofizyki i Ochrony Środowiska
Celem pracy jest stworzenie mapy litologicznej utworów i wychodni skalnych odsłaniających się w kopalniach odkrywkowych, na podstawie przetwarzania i analizy wielospektralnych zdjęć teledetekcyjnych. Wynikowa mapa zostanie stworzona dzięki takim narzędziom i metodom teledetekcyjnym jak stworzenie odmiennych kompozycji kolorów w celu inspekcji i stworzenia maski; indeksów spektralnych w celu analizy ilościowej oraz klasyfikacji (zarówno ISO, jak i klasyfikacji nadzorowanej). Otrzymana mapa zostanie następnie zweryfikowana i, jeśli to konieczne, zrewidowana i poprawiona poprzez weryfikację z danymi referencyjnymi. Ostatecznie, do mapy zostaną dodane kolory i nazwy poszczególnych klas, siatka współrzędnych oraz odpowiednie mapy jako podkład.
Access status: Restricted ,
Geological mapping of the area of Lawra Gold Belt (Ghana) based on remotely sensed images
(Data obrony: 2017-06-29) Kadey, Godsway
Wydział Geologii, Geofizyki i Ochrony Środowiska
Remote sensing techniques and spatial data analysis through Geographic Information Systems (GIS) have been jointly applied in lithological discrimination in the Lawra gold belt. Spectral signatures of the study area recorded by the Landsat 8 were studied to aid geological unit identification. As expected the savannah vegetation coupled with tropical geomorphic events (weathering, erosion and deposition), spectral inseparability and positional errors have the tendency to affect significantly the accuracy of the classification. Final detection of lithologies was based on correlation between classes generated in the thematic map and the reference geological map with a moderate overall accuracy of 20.192%. Results show that for unsupervised classification using Iterative Self-Organizing Data Analysis Technique (ISODATA) small number of classes produces more accurate results. The results once more show the limitations of spectral based approaches to geological mapping in vegetated terrains. The development of this data will provide a baseline on which to base future studies of the area. Integrated approach (geology, textural and spectral features) could be used to improve overall accuracy.
Access status: Open Access ,
Geomatics-enabled Interdisciplinary Approach Based on Geospatial Data Processing for Hydrogeological Risk-analysis
(Wydawnictwa AGH, 2024) Di Stefano, Francesco; Chiappini, Stefano; Sanità, Marsia; Pierdicca, Roberto; Malinverni, Eva Savina
Hydrogeological risks that are associated with rivers have emerged as a significant concern worldwide, impacting both natural ecosystems and human settlements. This contribution presents an interdisciplinary project that leverages many technologies for data-acquisition and modeling to comprehensively analyze and manage risks in riverine environments. The project integrates geomatics, geological, and hydrological techniques to provide a holistic understanding of river dynamics and their associated hazards. As a central component of this project, geomatics plays a pivotal role in instrumental field surveying through the deployment of photogrammetry and LiDAR instruments. Remote-sensing data from satellite imagery further enriches the project’s temporal analysis capabilities. By analyzing this data over time, researchers can monitor changes in river patterns, land use, and climate-related variables, this helps identify trends and potential triggers for hydrological events. To manage and integrate the vast amount of geospatial information that is generated, a geodatabase within a geographic information system (GIS) has been established. It enables efficient data storage, retrieval, and analysis, fostering collaboration among multidisciplinary researcher teams. This system offers tools for risk-assessment, modeling, and scenario planning, these allow for proactive measures for mitigating hydrological risks.
Access status: Open Access ,
Green space assessment and management in Biscay Province, Spain using remote sensing technology
(Wydawnictwa AGH, 2021) Makinde, Esther O.; Andonegui, Cristina M.; Vicario, Ainhoa A.
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 (R 2 = 0.1826), NDMI (R2 = 0.0117), for 2009 EVI (R 2 = 0.2192), NDMI (R2 = 0.3322), for 2019 EVI (R2 = 0.1258), NDMI (R 2 = 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 beena reduction in the amount of carbon which the Biscay Forest can sequester.