Dr. Nataliya Stankova Profile

Dr. Nataliya Stankova

at Space Research and Technology Institute

SPIE Involvement:

Author

Publications (11)

Proceedings Article | 28 May 2024 Poster + Paper

Postfire forest disturbances and initial regrowth using direction angle

Nataliya Stankova, Temenuzhka Spasova

Proceedings Volume 13083, 130831H (2024) https://doi.org/10.1117/12.3023275

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

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Wildfires considerably disturb the structure and forest ecosystem functioning. The disturbances estimation as well as the extent of damage to the soil and vegetation soon after the fire is crucial information for planning of restoration efforts. Because of the financial resources needed for field work and the involvement of experts, remote aerospace methods and data are extensively employed in monitoring ecological research. The aim of this paper is to assess postfire forest disturbances and initial regrowth processes using the tasseled cap derived Direction Angle (DA). DA is an index introduced by the authors in previous research – the angle between the Greenness component from the TCT (tasseled cap transformation) and VIC (Vector of Instantaneous Condition). The proposed method is based on linear orthogonal transformation of multispectral satellite images and is characterized with higher accuracy compared to standard methodologies using vegetation indices. The higher accuracy of the methodology is based on the linear orthogonal transformation of multispectral satellite images (TCT), which increases the degree of identification of the three main components changing during fire – soil, vegetation, and moisture/water. The methodology proposed in this paper is characterized by high accuracy in assessing the recovery of undergrowth, that is difficult to differentiate using standard monitoring methodologies based on vegetation indices. The DA raster images show the direction of change of the green tasseled cap component (TCG) relative to the VIC, which allows to estimate the degree of recovery of the vegetation component for different moments of the study period. The variations observed in DA values illustrate the pattern of the green component at various points during the investigation period, enabling the assessment of disturbances and the monitoring of regrowth processes. The test area is located in the Middle Rhodopes, near the village of Hvoyna (Smolyan region), Bulgaria, where on 28/08/2023 a wildfire broke out. 1,500 decares have been burnt by the fire, including deciduous and coniferous forest. The wildfire affected 100-130 years old black pine (Pinus nigra) forests.

Proceedings Article | 19 October 2023 Paper

Modeling post-fire forest regrowth using tasseled cap-derived indicators

Nataliya Stankova, Daniela Avetisyan

Proceedings Volume 12734, 1273419 (2023) https://doi.org/10.1117/12.2679783

KEYWORDS: Forest fires, Vegetation, Satellites, Ecosystems, Satellite imaging, Landsat, Earth observing sensors, Climatology, Modeling

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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

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 | 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 | 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 | 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.