Dr. Iva Ivanova Profile

Dr. Iva Ivanova

at Space Research and Technology Institute

SPIE Involvement:

Author

Publications (18)

Proceedings Article | 20 November 2024 Poster + Paper

Assessment of mosses in Antarctica based on remote sensing and chlorophyll fluorescence

Temenuzhka Spasova, Daniela Avetisyan, Iva Ivanova, Nataliya Stankova

Proceedings Volume 13191, 131910V (2024) https://doi.org/10.1117/12.3031486

KEYWORDS: Chlorophyll, Vegetation, Fluorescence, Satellites, Ultraviolet radiation, Moisture, Analytical research, Remote sensing, Ice, Spectroscopy

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Chlorophyll fluorescence refers to the emission of light by chlorophyll molecules when they are excited by absorbed light. Chlorophyll is the pigment responsible for photosynthesis – the process through which plants and other photosynthetic organisms convert light energy into chemical energy. The intensity of chlorophyll fluorescence can vary based on geographical latitude as well as other environmental factors. In Antarctica, where the extreme climatic conditions define the ecosystem, mosses are one of the few land-based organisms that can survive and thrive. The Antarctic Peninsula is especially known for its sparse but resistant vegetation, including several moss species that have adapted to extreme conditions like low temperatures, intense ultraviolet (UV) radiation, and repeated freeze-thaw cycles. These mosses are essential for maintaining the ecological balance in the region and offer important insights into how extreme environments affect plant physiology. This research aims to compare the spectral properties of mosses and lichens, with a focus on differences in their fluorescence intensity on Livingston Island, Antarctica, during the summer season. Field research in Antarctica was carried out in order to validate data obtained from Sentinel 2 MSI satellite images, drone photography, and photogrammetry. A spectrometer was used to analyze the visible spectrum ranging from 380nm to 780nm, corresponding to the spectral ranges utilized by the Sentinel 2 MSI and Sentinel 3 SLSTR satellites. The main research methods involve evaluating chlorophyll fluorescence response and applying various optical indices for remote sensing, including Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Moisture Stress Index (MSI). A radar index generated from processing Sentinel 1 data is utilized as well. These methods enable a thorough analysis of photosynthetic activity and plant health in extreme conditions, providing insights into the adaptive mechanisms of mosses in polar environments.

Proceedings Article | 13 September 2024 Open Access

Spectral analysis and mapping of unregulated landfills in Varna, North-Еast planning region of Bulgaria

Temenuzhka Spasova, Daniela Avetisyan, Adlin Dancheva, Iva Ivanova, Miroslav Tsvetkov

Proceedings Volume 13212, 132121L (2024) https://doi.org/10.1117/12.3038624

KEYWORDS: Satellites, Vegetation, Plastics, Landsat, Earth observing sensors, Environmental monitoring, Satellite imaging, Spectroscopy, Orthophoto maps, Land cover

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The Research, Innovation and Digitalisation Programme for Economic Transformation in Bulgaria is one of the tools to respond to the country’s strategic needs and priorities for the implementation of a common research and innovation development policy in favour of the country’s accelerated economic development. It also responds to the need to speed up the processes of public sector digitalisation and to build an enabling digital environment that ensures high-quality and secure exchange of information between different spheres of life and enhance the effects of their interaction1 . Developing a useful hybrid spectral analysis model to track climate change is the aim of this research. The subject of research is the dynamics tracked by the hybrid model for spectral analysis of unregulated landfills. For this purpose, a database of several identical climatic seasons (10 years) was created and processed to verify and validate the research based on satellite and in situ data. The study covers an example from NUTS2, the North East (BG33) planning region (under the Regional Development and Improvement Act). The generated data is of high value according to the European Commission. They are for a period of at least five years. The study of the unregulated landfills is of national importance and the selected events from the territory of Bulgaria have been studied and monitored through a complex approach based on satellite data and ground-based innovative spectrometric equipment through a mobile spectrometer and a thermal camera. Indices such as Normalized Difference Vegetation Index (NDVI), Normalized Differential Greenness Index (NDGI) and Tasseled cap transformation (TCT) are also applied. Data from Orthophoto, Landsat-9 OLI-2/TIRS-2, Sentinel 2MSI and Sentinel-3 SLTRS satellites were used. Data from Corine Land Cover 2018 Copernicus and Open data were also used in the study. Through this research, the data being generated for unregulated landfills can be supplemented and will be used to create of register and their use by various stakeholders.

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Proceedings Article | 13 September 2024 Open Access

Spectral analysis and mapping of unregulated and regulated landfills in Bulgaria

Temenuzhka Spasova, Iva Ivanova, Daniela Avetisyan, Adlin Dancheva

Proceedings Volume 13212, 132121M (2024) https://doi.org/10.1117/12.3038626

KEYWORDS: Satellites, Vegetation, Plastics, Landsat, Satellite imaging, Earth observing sensors, Data modeling, Thermal imaging cameras, Color, Spectroscopy

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Proceedings Article | 14 June 2024 Poster

Spectral analysis and mapping of unregulated and regulated landfills by planning areas (NUTS 2) in Bulgaria

Temenuzhka Spasova, Iva Ivanova, Daniela Avetisyan, Adlin Dancheva

Proceedings Volume 13083, 130831F (2024) https://doi.org/10.1117/12.3023038

KEYWORDS: Analytical research, Data modeling, Spectral models, Satellites, Unmanned aerial vehicles, Spectroscopy, Optical spheres, Information security, Databases, Climatology

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Proceedings Article | 28 May 2024 Poster + Paper

Assessment of heat islands and renewable energy sources in the north-east planning region of Bulgaria by remote sensing

Temenuzhka Spasova, Iva Ivanova, Daniela Avetisyan, Adlin Dancheva

Proceedings Volume 13083, 1308314 (2024) https://doi.org/10.1117/12.3012240

KEYWORDS: Vegetation, Renewable energy, Satellites, Satellite imaging, Solar energy, Reflectivity, Landsat, Earth observing sensors, Wind energy, Environmental monitoring

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Surface and ground air temperatures are one of the variables that best distinguish and characterize the specific climate in urbanized spaces. Over the years, research has shown that urbanized spaces have experienced persistently higher temperatures, which is defined as the urban heat island effect (Urban Heat Island-UHI). Wind turbines and solar panels are two of the main types of renewable energy sources used in Bulgaria. The presence of too many different facilities related to renewable energy sources often has an impact, but sometimes this impact can be negative for specific territories even if they are not highly urbanized, such as the selected territory in Western Pontic steppes, North-Еast Planning Region (BG33). The study covers examples from the planning region defined in the Law on Regional Development of the Republic of Bulgaria under Art. 11, which will support the Integrated Territorial Strategy for the Development of NUTS 2 planning district. These are territories whose selection is determined by the fact that they have extremely high economic and ecological importance for monitoring the normal course of natural processes, disasters and consequences of sudden changes. The aim of the research is to create a methodology for monitoring through a complex approach, to be used by experts and non-experts, in order to make decisions for the management of the territories occupied with renewable energy sources. Different indicators and indices from the optical range, such as Normalized Differential Greenness Index (NDGI), Tasseled Cap Transformation (TCT), Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), were used for the different groups of objects. The spectral reflectance characteristics of natural and anthropogenic objects have been used to classify temperatures. Open data, data from the National Spatial Data Portal (Inspire). Orthophoto and aircraft images from 100 years ago were used for the needs of the methodology.

Proceedings Article | 19 October 2023 Poster + Paper

Monitoring of renewable energy sources with remote sensing, open data, and field data in Bulgaria

Temenuzhka Spasova, Adlin Dancheva, Daniela Avetisyan, Iva Ivanova, Iliyan Popov, Boris Shirov

Proceedings Volume 12733, 1273311 (2023) https://doi.org/10.1117/12.2680495

KEYWORDS: Vegetation, Satellites, Renewable energy, Color, Thermal imaging cameras, Solar radiation, Temperature metrology, Synthetic aperture radar, Solar energy, Spectroscopy

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Proceedings Article | 21 September 2023 Open Access

Monitoring post-fire forest regrowth using differenced disturbance index classification

Nataliya Stankova, Temenuzhka Spasova, Iva Ivanova

Proceedings Volume 12786, 127861V (2023) https://doi.org/10.1117/12.2681787

KEYWORDS: Forest fires, Landsat, Ecosystems, Vegetation, Satellites, Raster graphics, Satellite imaging, Aerospace engineering, Earth observing sensors, Sensors

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Proceedings Article | 21 September 2023 Open Access

Using Sentinel-2 data for efficient monitoring and modeling of wetland protected areas

Iva Ivanova, Temenuzhka Spasova, Nataliya Stankova

Proceedings Volume 12786, 127861U (2023) https://doi.org/10.1117/12.2681790

KEYWORDS: Vegetation, Satellites, Water content, Reflectivity, Near infrared, Satellite imaging, Earth observing sensors, Short wave infrared radiation, Ecosystems, Data modeling

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Wetlands are ecologically vital habitats that play a crucial role in supporting biodiversity and providing essential ecosystem services. They are considered to be among the most productive ecosystems on the planet that provide numerous benefits. For the purposes of this study, Straldzha Complex Protected Area, Bulgaria was chosen as the object of investigation. Straldzha Complex Protected Area includes a reservoir and surrounding wetlands and meadows, the remains of the eastern part of the former Straldzha Plateau (the largest plateau ever in Bulgaria). The wetland is sensitive to human activities, related to the water management and unsustainable use of the former plateau as agricultural land. For the purposes of this study, data from Sentinel-2 satellite of the European Space Agency were used. The monitoring was carried out during the study period 2017 – 2022. An index-based classification was used in the study, utilizing NDVI, NDWI and MSAVI2 indices for classifying the contents within the wetland's boundaries. NDGI model was applied as well, evaluating the vegetation dynamics in the marsh. The obtained results showed successful mapping and monitoring of wetlands. The wetlands are of high importance and should be protected and conserved to maintain the benefits they provide to the environment and society. The data and results of this research will be able to serve Destination Earth (DestinE), which is an ambitious initiative of the European Union to create a digital model of the Earth that will be used for monitoring the effects of natural and human activities on our planet, prediction of extreme events and adapting policies to the climate challenges. The data and models will serve the Bulgarian initiative for the construction of the Digital Twins, which is being pilot developed in the department of Aerospace Information, Space Research and Technology Institute – Bulgarian Academy of Sciences. Open Data were used in this study, with the aim of promoting the Open science policy and FAIR principles as much as possible.

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Proceedings Article | 12 September 2021 Poster + Paper

Monitoring of surface water bodies by Sentinel and open data

Temenuzhka Spasova, Adlin Dancheva, Iva Ivanova, Denitsa Borisova, Nataliya Stankova

Proceedings Volume 11863, 118631B (2021) https://doi.org/10.1117/12.2600282

KEYWORDS: Data modeling, Satellites, Synthetic aperture radar, Aerospace engineering, Statistical analysis, Remote sensing, Polarization

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Proceedings Article | 12 September 2021 Poster + Paper

Dynamics and development of Alepu marsh for the period 2013-2020 based on satellite data

Iva Ivanova, Nataliya Stankova, Denitsa Borisova, Temenuzhka Spasova, Adlin Dancheva

Proceedings Volume 11863, 1186315 (2021) https://doi.org/10.1117/12.2597726

KEYWORDS: Vegetation, Satellites, Earth observing sensors, Satellite imaging, Data modeling, Visualization, Landsat, Sensors, Image processing, Composites

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Proceedings Article | 26 August 2020 Paper

Seasonal assessment of the dynamics of sea ice based on aerospace data on Livingston Island, New Shetland Islands in Antarctica and Longyearbyen in the Arctic

Теmenuzhka Spasova, Roumen Nedkov, Adlin Dancheva, Andrey Stoyanov, Iva Ivanova, Nikolay Georgiev

Proceedings Volume 11524, 115240J (2020) https://doi.org/10.1117/12.2570829

KEYWORDS: Synthetic aperture radar, Aerospace engineering, Ocean optics, RGB color model, Composites, Polarization, Climatology, Climate change, Remote sensing, Image processing

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Proceedings Article | 9 October 2018 Presentation + Paper

Using SAR and optical data from Sentinel satellites for precise modeling of seasonal floating reed islands dynamics in Srebarna Lake

Iva Ivanova, Roumen Nedkov, Denitsa Borisova, Nataliya Stankova

Proceedings Volume 10790, 107900E (2018) https://doi.org/10.1117/12.2325703

KEYWORDS: Data modeling, Vegetation, Satellites, Synthetic aperture radar, Data acquisition, Ecosystems, Satellite imaging, Image processing

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Proceedings Article | 9 October 2018 Paper

Modeling of forest ecosystems recovery after fire based on orthogonalization of multispectral satellite data

Nataliya Stankova, Roumen Nedkov, Iva Ivanova, Daniela Avetisyan

Proceedings Volume 10790, 107901R (2018) https://doi.org/10.1117/12.2325643

KEYWORDS: Vegetation, Ecosystems, Data modeling, Satellites, Satellite imaging, Earth observing sensors, Multispectral imaging

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Proceedings Article | 6 August 2018 Paper

Application of remote sensing for ecosystems monitoring and risk assessment

Kameliya Radeva, Iva Ivanova, Denitsa Borisova

Proceedings Volume 10773, 107731Q (2018) https://doi.org/10.1117/12.2325854

KEYWORDS: Ecosystems, Satellites, Remote sensing, Earth observing sensors, Satellite imaging

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Proceedings Article | 10 October 2017 Paper

Research of generalized wavelet transformations of Haar correctness in remote sensing of the Earth

Maretta Kazaryan, Mihail Shakhramanyan, Roumen Nedkov, Andrey Richter, Denitsa Borisova, Nataliya Stankova, Iva Ivanova, Mariana Zaharinova

Proceedings Volume 10427, 104271U (2017) https://doi.org/10.1117/12.2278572

KEYWORDS: Wavelets, Remote sensing, Satellite imaging, Earth observing sensors, Satellites, Image processing, Space operations, Transform theory, Wavelet transforms, Image filtering

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In this paper, Haar's generalized wavelet functions are applied to the problem of ecological monitoring by the method of remote sensing of the Earth. We study generalized Haar wavelet series and suggest the use of Tikhonov's regularization method for investigating them for correctness. In the solution of this problem, an important role is played by classes of functions that were introduced and described in detail by I.M. Sobol for studying multidimensional quadrature formulas and it contains functions with rapidly convergent series of wavelet Haar. A theorem on the stability and uniform convergence of the regularized summation function of the generalized wavelet-Haar series of a function from this class with approximate coefficients is proved. The article also examines the problem of using orthogonal transformations in Earth remote sensing technologies for environmental monitoring. Remote sensing of the Earth allows to receive from spacecrafts information of medium, high spatial resolution and to conduct hyperspectral measurements. Spacecrafts have tens or hundreds of spectral channels. To process the images, the device of discrete orthogonal transforms, and namely, wavelet transforms, was used. The aim of the work is to apply the regularization method in one of the problems associated with remote sensing of the Earth and subsequently to process the satellite images through discrete orthogonal transformations, in particular, generalized Haar wavelet transforms. General methods of research. In this paper, Tikhonov's regularization method, the elements of mathematical analysis, the theory of discrete orthogonal transformations, and methods for decoding of satellite images are used. Scientific novelty. The task of processing of archival satellite snapshots (images), in particular, signal filtering, was investigated from the point of view of an incorrectly posed problem. The regularization parameters for discrete orthogonal transformations were determined.

Proceedings Article | 5 October 2017 Paper

Application of SAR data for seasonal monitoring of floating reed islands dynamic in Srebarna Lake

Iva Ivanova, Roumen Nedkov, Denitsa Borisova

Proceedings Volume 10428, 104280M (2017) https://doi.org/10.1117/12.2278542

KEYWORDS: Synthetic aperture radar, Sensors, Remote sensing, Image registration, Satellites, Multispectral imaging, Snow cover, Environmental monitoring

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