Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів
When assessing the level of development of territories, the problem of finding objective qualitative data that will characterize it arises. One of the possible sources of such data is the remote sensing of the Earth (RSE). The article is devoted to the analysis of the possibility of using the produc...
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| author | Zgurovsky, Michael Yefremov, Kostiantyn Gapon, Sergii Pyshnograiev, Ivan |
| author_facet | Zgurovsky, Michael Yefremov, Kostiantyn Gapon, Sergii Pyshnograiev, Ivan |
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| description | When assessing the level of development of territories, the problem of finding objective qualitative data that will characterize it arises. One of the possible sources of such data is the remote sensing of the Earth (RSE). The article is devoted to the analysis of the possibility of using the product of RSE – the map of night lights, for modeling the economical dimension of the sustainable development of the regions of Ukraine. Using the regression and correlation analysis and neural networks, appropriate models for assessing the level of economic development of the Kherson region, Donetsk region, and the AR of Crimea were obtained. The study was carried out by the team of the World Data Center for Geoinformatics and Sustainable Development of the Igor Sikorsky Kyiv Polytechnic Institute. It was part of research on the analysis of the behavior of complex socio-economic systems and processes of sustainable development in the context of the quality and safety of people’s lives. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2023.2.04 |
| first_indexed | 2025-07-17T10:28:17Z |
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M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev, 2023
Системні дослідження та інформаційні технології, 2023, № 2 49
TIДC
ПРОБЛЕМИ ПРИЙНЯТТЯ РІШЕНЬ ТА
УПРАВЛІННЯ В ЕКОНОМІЧНИХ, ТЕХНІЧНИХ,
ЕКОЛОГІЧНИХ І СОЦІАЛЬНИХ СИСТЕМАХ
UDC 338.27:311.16
DOI: 10.20535/SRIT.2308-8893.2023.2.04
ASSESSMENT OF THE ECONOMICAL DIMENSION OF
SUSTAINABLE DEVELOPMENT OF THE UKRAINE’S REGIONS
BASED ON THE BRIGHTNESS OF NIGHT LIGHTS
M. ZGUROVSKY, K. YEFREMOV, S. GAPON, I. PYSHNOGRAIEV
Abstract. When assessing the level of development of territories, the problem of
finding objective qualitative data that will characterize it arises. One of the possible
sources of such data is the remote sensing of the Earth (RSE). The article is devoted
to the analysis of the possibility of using the product of RSE – the map of night
lights, for modeling the economical dimension of the sustainable development of the
regions of Ukraine. Using the regression and correlation analysis and neural net-
works, appropriate models for assessing the level of economic development of the
Kherson region, Donetsk region, and the AR of Crimea were obtained. The study
was carried out by the team of the World Data Center for Geoinformatics and Sus-
tainable Development of the Igor Sikorsky Kyiv Polytechnic Institute. It was part of
research on the analysis of the behavior of complex socio-economic systems and
processes of sustainable development in the context of the quality and safety
of people’s lives.
Keywords: sustainable development, spatial data analysis, economical
development, night lights, mathematical modeling.
INTRODUCTION
The effectiveness and quality of management decisions regarding the behavior of
complex socio-economic and security systems depends on the completeness and
adequacy of the assessment of the management situation. For the construction of
such an estimate, an important factor is the quality of the data used during the
study.
In this study, a system is understood as a territory that is either an object of
management or an environment for a certain management situation. During the
assessment of the level of development of territories, the problem of finding ob-
jective qualitative data that will characterize it arises. One of the possible sources
of such data is the application of remote sensing of the Earth (RSE).
The study is devoted to the analysis of the possibility of using one of the
products of the RSE — the map of night lights, for modeling the economical di-
mension of sustainable development of the regions of Ukraine and other adminis-
trative-territorial entities.
M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev
ISSN 1681–6048 System Research & Information Technologies, 2023, № 2 50
The possibilities of using the map of night lights were considered by various
scientists. In particular, at the global level, Jiansheng Wu et al. [1] investigated
the relationship between GDP and night lights using 15 years of observations. In
[2], the authors reviewed the indicators determining Human Well-Being for 2006
and showed the existing relationship with night lights. At the regional level, there
were similar studies for the population of Japan [3] and Ukraine [4], the level of
urbanization and GRP of the regions of China [5; 6], etc.
In a previous study [7], the spatial correlation of indicators of sustainable
development and the brightness of night lights according to the data of 2011 was
considered. The preservation of zonal trends with the components of the quality
and safety of people’s lives, the Index of the economical dimension, the Competi-
tiveness Index and the Sustainable Development Index of Ukraine’s regions was
confirmed.
This study, in contrast to the results of foreign scientists, investigates the
possibility of an integral assessment of the level of economic development based
on maps of night lights at the regional level in dynamics, and also presents models
for determining the level of economic development of the regions of Ukraine for
the first time.
The study was carried out by the team of the World Data Center for Geoin-
formatics and Sustainable Development of the Igor Sikorsky Kyiv Polytechnic
Institute and was part of research on the analysis of the behavior of complex
socio-economic systems [8] and sustainable development processes in the context
of the quality and safety of people’s lives [9; 10; 11].
METHODOLOGY FOR CALCULATING THE INDEX OF BRIGHTNESS OF
NIGHT LIGHTS OF THE UKRAINE’S REGIONS
The maps of night lights (Fig. 1) used in the study are the result of data processing
by the Department of Geological and Atmospheric Sciences, Iowa State Univer-
sity [12] on artificial illumination of the Earth’s surface at night from the sources
of the Earth Observation Group, Colorado School of Mines [13].
Fig. 1. Map of night lights (raster image (composite) of artificial night luminosity of the
Earth’s surface) for 2013
Assessment of the economical dimension of sustainable development of the Ukraine’s regions …
Системні дослідження та інформаційні технології, 2023, № 2 51
The Night Light Brightness Index was calculated for the territory of Ukraine
and each of its regions for the period 2004 — September 2022 (monthly available
data is presented for 2022). For this, a vector mask of the borders of countries and
regions and their urbanized territories was created on the night luminance maps.
Geospatial calculation functions averaged indicators within each urbanized area
of each region. The Night Light Brightness Index of an administrative-territorial
formation is the sum of the values for the illumination of each cell of the map
within the urbanized territories reduced to the area of the administrative-territorial
formation:
,, 1
i
j
ki
K
kj
i S
L
I
i
where i — number of the administrative-territorial formation; j — year of calcula-
tion; i
jI — the value of the Night Lights Brightness Index; iS — the area of the
administrative-territorial formation in km2; iK — the number of cells, the bright-
ness of which is counted to the i-th administrative-territorial formation; j
kiL , —
the brightness of the k-th cell of the i-th administrative-territorial entity for the j-th
year, which is measured in the range from 0 to 63.
Thus, the regions with the highest values of luminosity in their urbanized ter-
ritories received the highest values of the Night Lights Brightness Index, and vice
versa, the regions with the lowest values of luminosity in their urbanized territo-
ries — the lowest. The method of zonal statistics was used to calculate the sum of
the values of the raster cells within the vector masks.
The result of calculations of the Night Lights Brightness Index for regions of
Ukraine is presented in the Table 1 and in Fig. 2.
THE NIGHT LIGHTS BRIGHTNESS INDEX ANALYSIS
The Night Lights Brightness Index had a decreasing trend several times:
– global economic crises (2006–2009);
– annexation of territories of Ukraine in 2014;
– the pandemic of COVID-19;
– the Russia’s invasion on the territory of Ukraine in 2022.
Fig. 2. Evaluation of the brightness of the urbanized territories of the regions of Ukraine
from 2004 to September 2022 (monthly available data is presented for 2022)
M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev
ISSN 1681–6048 System Research & Information Technologies, 2023, № 2 52
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Assessment of the economical dimension of sustainable development of the Ukraine’s regions …
Системні дослідження та інформаційні технології, 2023, № 2 53
The Night Lights Brightness Index for the territory of Ukraine in 2018
(Fig. 3) grew by 64% compared to 2015 and amounted to 9.225 and 5.599, re-
spectively. In 2021, the historical maximum of the index for the studied period
was observed and amounted to 10.083. The minimum is 2.577 in August 2022
which was reached due to consequences of the Russia’s military actions.
Only in four regions (Kyiv city, Sevastopol city, Kherson and Kyiv regions)
the brightness of night lights was the lowest in 2009 as a result of the global eco-
nomic crisis, and in all other regions — in 2015 (if we excluded 2022).
In Kyiv city, unlike other regions, had a growing trend till January 2022. The
dynamics of the brightness index is shown in Fig. 4, 5.
Let’s consider Donetsk and Luhansk regions. In 2015, the value of the Night
Lights Brightness Index was affected greatly (Fig. 2). Fig. 6 shows the change in
the intensity of night lights between 2013 and 2015 in the territory of these re-
gions. Places of decrease in intensity are marked in dark grey on the map, and
places of increase are marked in light grey. As can be seen from the figure, a de-
crease in the indicator is observed in most of the territories of the regions, which
also indicates a decrease in economic activity.
Fig. 3. Map of night lights (raster image (composite) of artificial night luminosity of the
Earth’s surface) of the regions of Ukraine for 2015
Fig. 4. Evaluation of the brightness of the territory of the Kyiv city from 2005 to 2018
M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev
ISSN 1681–6048 System Research & Information Technologies, 2023, № 2 54
As for August 2022, the most affected regions are Kharkiv, Sumy, Ivano-
Frankivsk, Dnipropetrovsk. The decreasing was 78–80%. The less one is Sevas-
topol city (33%). It should be noted here that along with the unconditional impact
of Russian aggression, this month is accompanied by a seasonal decrease in eco-
nomic activity.
In order to verify the possibility of using night lights maps to assess the level
of economic development of territories, a correlation-regression analysis of the
Index of the economical dimension of sustainable development — an integral in-
dicator calculated according to the methodology [9], and the Night Lights Bright-
ness Index for the regions of Ukraine was conducted.
In the Table 2 the results of calculating the correlation coefficient of the
studied indicators for each region are shown. The obtained results indicate that the
relationship between economic development and the brightness of night lights is
uneven for different regions of the country. The value of the correlation coeffi-
cient for the Kyiv city stands out from a number of data due to the specifics of the
functioning of the capital. If we consider the entire data set (except for the Kyiv
city), the correlation coefficient for the Index of the economical dimension of sus-
tainable development and the Night Lights Brightness Index is 0.716 (Fig. 7),
which indicates the presence of a connection.
Fig. 5. Comparison of the brightness of the territory of the Kyiv city in 2005 and 2018.
2005 2018
Fig. 6. Changes in the intensity of night lights between 2013 and 2015 in Donetsk and
Luhansk regions
Assessment of the economical dimension of sustainable development of the Ukraine’s regions …
Системні дослідження та інформаційні технології, 2023, № 2 55
T a b l e 2 . Correlation coefficients of the Index of the economical dimension of sus-
tainable development of the regions of Ukraine and the level of brightness of night lights
Region Correlation coefficient
AR of Crimea 0.744
city Sevastopol 0.732
Donetsk 0.721
Odesa 0.689
Poltava 0.660
Luhansk 0.636
Ivano-Frankivsk 0.616
Zhytomyr 0.605
Dnipropetrovsk 0.590
Kherson 0.563
Khmelnytskiy 0.530
Cherkasy 0.519
Rivne 0.478
Kharkiv 0.476
Ternopyl 0.464
Kirovohrad 0.457
Vinnytsya 0.432
Mykolayiv 0.397
Chernihiv 0.390
Chernivtsi 0.355
Volyn 0.279
Zaporizhzhya 0.267
Zakarpattya 0.252
Sumy 0.235
Kyiv 0.000
Lviv -0.028
Kyiv city -0.227
The presence of such a connection allows building models for assessing the
level of the economic component of sustainable development based on satellite
data for territories in the absence of the necessary statistical information.
Fig. 7. Dependence of the Index of the economical dimension of sustainable development
of the regions of Ukraine and the level of brightness of night lights
M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev
ISSN 1681–6048 System Research & Information Technologies, 2023, № 2 56
ASSESSMENT OF THE LEVEL OF ECONOMIC DEVELOPMENT OF THE
KHERSON REGION AND THE AUTONOMOUS REPUBLIC OF CRIMEA
BASED ON THE NIGHT LIGHTS BRIGHTNESS INDEX
Three regions were selected for modeling:
– Kherson region (to check the methodology of building models);
– Autonomous Republic of Crimea (due to the absence of the objective sta-
tistical information since 2014);
– Donetsk region (due to the absence of the objective statistical information
since 2014).
After the analysis of the relevant time series, the presence of a lag in 1 pe-
riod was determined. The models are built in the form of nonlinear regression
[14] and neural network [15] and have the following form:
1. Regressions:
a. Kherson region
00551,0))1((*0763,0)( tIlntI nlec ,
where )(tIec . — Index of the economical dimension of sustainable development
at a moment in time t, )1( tInl . — the Night Lights Brightness Index at a mo-
ment in time 1t ;
b. AR of Crimea
2856,0))1((*30658,0)( tILNtII nlnlec ,
where )(tIec — Index of the economical dimension of sustainable development at a mo-
ment in time t, )1( tInl — the Night Lights Brightness Index at a moment in time 1t .
c. Donetsk region
0489917756,2)1(*0019647232,0)( tItI nlec ,
c
Fig. 8. Weights and structure of CNN for the: a — Kherson region; b — AR of Crimea; c —
Donetsk region (Iec — Index of the economical dimension of sustainable development at
a moment in time t, Lights — the Night Lights Brightness Index at a moment in time (t–1)
ba
Assessment of the economical dimension of sustainable development of the Ukraine’s regions …
Системні дослідження та інформаційні технології, 2023, № 2 57
where )(tIec — Index of the economical dimension of sustainable development at a mo-
ment in time t, )1( tInl — the Night Lights Brightness Index at a moment in time 1t .
2. Convolutional Neural Network (CNN):
a. The weights and structure of the CNN for the Kherson region are pre-
sented in Fig. 8, a;
b. The weights and structure of the CNN for AR of Crimea are presented in Fig. 8, b;
c. The weights and structure of the CNN for the Donetsk region are pre-
sented in Fig. 8, c;
The model for the Kherson region has an average relative error of 7,6% for
nonlinear regression and 6.4% for convolutional neural network. The results are
presented in Fig. 9 and in Table 3. According to the built model, in 2021 the re-
gion showed growth and fall in 2022.
T a b l e 3 . Calculation of the Index of the economical dimension based on
the brightness of night lights for the Kherson region
Year
The Index of
the economical
dimension
The Night
Lights
Brightness
Index
The values of the Index
of the economical
dimension are
modeled using
non-linear regression
The values of the Index
of the economical
dimension are
modeled using CNN
2009 0.162 6.487 0.157 0.164
2010 0.164 7.966 0.148 0.144
2011 0.178 8.455 0.164 0.168
2012 0.163 8.950 0.168 0.168
2013 0.155 7.570 0.173 0.167
2014 0.190 6.338 0.160 0.167
2015 0.136 5.447 0.146 0.141
2016 0.131 5.832 0.135 0.133
2017 0.133 6.490 0.140 0.137
2018 0.137 8.109 0.148 0.144
2019 6.883 0.165 0.168
2020 6.549 0.153 0.154
2021 8.930 0.149 0.145
01.2022 8.991 0.173 0.167
02.2022 5.542 0.173 0.167
03.2022 2.535 0.136 0.134
08.2022 2.094 0.076 0.124
09.2022 2.893 0.062 0.126
10.2022 0.087 0.122
Fig. 9. Calculation of the Index of the economical dimension based on the brightness of
night lights for the Kherson region
M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev
ISSN 1681–6048 System Research & Information Technologies, 2023, № 2 58
The model for the Autonomous Republic of Crimea can be used to assess the
level of economic development of the region after 2013. The average relative er-
ror of the obtained models is no more than 10.2%. The results are presented in
Fig. 10 and in Table 4.
T a b l e 4 . Calculation of the Index of the economical dimension based on the
brightness of night lights for AR of Crimea
Year
The Index
of the
economical
dimension
The Night
Lights
Brightness
Index
The values of the Index
of the economical
dimension are
modeled using
non-linear regression
The values of the Index
of the economical
dimension are
modeled using CNN
2009 0.216 4.778 0.194 0.192
2010 0.223 5.994 0.263 0.266
2011 0.301 6.161 0.272 0.273
2012 0.282 6.879 0.306 0.296
2013 0.320 5.739 0.250 0.254
2014 4.600 0.182 0.178
2015 3.872 0.129 0.124
2016 4.224 0.156 0.150
2017 4.900 0.202 0.201
2018 6.011 0.264 0.267
2019 5.461 0.235 0.238
2020 5.216 0.221 0.222
2021 7.398 0.328 0.305
01.2022 7.439 0.330 0.305
02.2022 5.731 0.250 0.253
03.2022 4.311 0.162 0.157
08.2022 3.335 0.084 0.089
09.2022 4.139 0.150 0.144
10.2022 4.778 0.194 0.192
According to the simulation results, after a certain economic growth in
2011–2013, the Autonomous Republic of Crimea fell in 2014–2016. In 2016–2021,
there is an upward trend in the Index of the economical dimension of sustainable
development.
Fig. 10. Calculation of the Index of the economical dimension based on the brightness
of night lights for AR of Crimea
Assessment of the economical dimension of sustainable development of the Ukraine’s regions …
Системні дослідження та інформаційні технології, 2023, № 2 59
The model for the Donetsk region has an average relative error of 19.4% for
nonlinear regression and 18.2% for convolutional neural network. This is due to
increased uncertainty in partial annexation and hostilities. The results are pre-
sented in Fig. 11 and in Table 5. According to the built model, the region has de-
creasing economic dimension trend after 2013 and after 2018. The models show
even greater level of falling during 2022.
T a b l e 5 . Calculation of the Index of the economical dimension based on the
brightness of night lights for the Donetsk region
Year
The Index
of the
economical
dimension
The Night
Lights
Brightness
Index
The values of
the Index of the
economical dimension
are modeled using
non-linear regression
The values
of the Index
of the economical
dimension are
modeled using CNN
2009 0.503 12.762 0.432 0.495
2010 0.468 15.090 0.363 0.375
2011 0.517 15.862 0.511 0.558
2012 0.554 17.416 0.566 0.561
2013 0.482 14.255 0.685 0.520
2014 12.071 0.455 0.522
2015 9.425 0.323 0.305
2016 10.390 0.195 0.214
2017 11.977 0.238 0.222
2018 14.864 0.318 0.297
2019 12.337 0.495 0.552
2020 11.736 0.338 0.330
2021 15.934 0.305 0.279
01.2022 16.338 0.571 0.560
02.2022 9.257 0.601 0.553
03.2022 5.683 0.188 0.214
08.2022 4.510 0.069 0.238
09.2022 5.639 0.043 0.247
10.2022 0.068 0.239
Fig. 11. Calculation of the Index of the economical dimension based on the brightness
of night lights for the Donetsk region
M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev
ISSN 1681–6048 System Research & Information Technologies, 2023, № 2 60
CONCLUSIONS
In the course of the research, data on the luminosity of night lights on the territory
of Ukraine was collected and processed. Based on the processed data, the Night
Lights Brightness Index for the regions of Ukraine was formed and analyzed. The
conducted correlation-regression analysis confirmed the possibility of using the
specified index to determine the economic component of sustainable development
on the territory of Ukraine.
Built for the Kherson region, the Autonomous Republic of Crimea and the
Donetsk region, the assessment models of Index of the economical dimension of
sustainable development showed an error of no more than 7.6%, 10.2% and
19.4%, which, among other things, allowed us to assess the level of economic
development for the territory of the Autonomous Republic of Crimea and the Do-
netsk region for 2014–2022.
Using developed approach, we showed that the annexation of territories sig-
nificantly affected the level of economic development of the territories of Crimea
and Donbas. So, the Crimea fell by 0.174 points (57.8%), and the Donetsk region
lost almost twice as much – 0.398 points (66.1%). At the same time, the pandemic
period affected these regions in different ways. Crimea, after the restoration of its
economic processes, lost only 0.044 points (16.6%), while the Donetsk region lost
0.232 points (44.3%).
And without having time to strengthen the trend towards economic recovery
from the consequences of Covid-19, due to the full-scale invasion, these regions
also suffered significantly. Not being a highly developed region, by the third dec-
ade of 2022 Crimea lowered its level of economic development by 0.230 points,
when the Donetsk region lost much more – 0.432 points.
Thus, according to the results of the study, it was established that the degree
of brightness of night lights can be used to assess the economic component of sus-
tainable development of the regions of Ukraine, and in particular, the level of
economic activity of the territories. This will help to make an assessment in the
absence of ready-made qualitative statistical information, for example, for newly
formed administrative units, or for regions for which, for various reasons, it is
impossible to obtain sets of economic indicators.
Generally, with the application of the proposed approach, it was possible to
identify and confirm the decrease in the economic activity of the regions of
Ukraine during the pandemic and a full-scale invasion of Russia.
Further research is planned to be directed to the creation of a set of models
for assessing the level of economic development of any territory within Ukraine
with the aim of creating appropriate applications within the Information and Ana-
lytical Situational Center of the Igor Sikorsky Kyiv Polytechnic Institute.
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Received 12.02.2023
M. Zgurovsky, K. Yefremov, S. Gapon, I. Pyshnograiev
ISSN 1681–6048 System Research & Information Technologies, 2023, № 2 62
INFORMATION ON THE ARTICLE
Michael Z. Zgurovsky, ORCID: 0000-0001-5896-7466, National Technical University
of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail: zgu-
rovsm@hotmail.com
Kostiantyn V. Yefremov, ORCID: 0000-0003-3495-6417, National Technical University
of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail:
k.yefremov@wdc.org.ua
Sergii V. Gapon, ORCID: 0000-0002-8834-5825, National Technical University of
Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail: gapon@wdc.org.ua
Ivan O. Pyshnograiev, ORCID: 0000-0002-3346-8318, National Technical University of
Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine, e-mail: pyshno-
graiev@gmail.com
ОЦІНЮВАННЯ ЕКОНОМІЧНОГО ВИМІРЮВАННЯ СТАЛОГО РОЗВИТКУ
РЕГІОНІВ УКРАЇНИ НА ОСНОВІ ЯСКРАВОСТІ НІЧНИХ ВОГНІВ /
М.З. Згуровський, К.В. Єфремов, С.В. Гапон, І.О. Пишнограєв
Анотація. Під час оцінювання рівня розвитку територій виникає проблема
пошуку об’єктивних якісних даних, що будуть її характеризувати. Одним з
можливих джерел таких даних є застосування методів дистанційного зонду-
вання Землі (ДЗЗ). Проаналізовано можливості використання одного з
продуктів ДЗЗ – карти нічних вогнів, для моделювання економічного
вимірювання сталого розвитку регіонів України. У результаті за допомогою
регресійно-кореляційного аналізу та нейронних мереж отримано відповідні
моделі оцінювання рівня економічного розвитку Херсонської області,
Донецької області та АР Крим. Наведене дослідження виконано командою
Світового центру даних «Геоінформатика та сталий розвиток» КПІ ім. Ігоря
Сікорського і є частиною досліджень з аналізу поведінки складних соціально-
економічних систем та процесів сталого розвитку в контексті якості та безпеки
життя людей.
Ключові слова: сталий розвиток, просторовий аналіз даних, економічний роз-
виток, нічні вогні, математичне моделювання.
|
| id | journaliasakpiua-article-285440 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T10:28:17Z |
| publishDate | 2023 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/ce/24bd4e91da4a6f6ec47100561795dbce.pdf |
| spelling | journaliasakpiua-article-2854402023-08-07T15:49:29Z Assessment of the economical dimension of sustainable development of the ukraine’s regions based on the brightness of night lights Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів Zgurovsky, Michael Yefremov, Kostiantyn Gapon, Sergii Pyshnograiev, Ivan sustainable development spatial data analysis economical development night lights mathematical modeling сталий розвиток просторовий аналіз даних економічний розвиток нічні вогні математичне моделювання When assessing the level of development of territories, the problem of finding objective qualitative data that will characterize it arises. One of the possible sources of such data is the remote sensing of the Earth (RSE). The article is devoted to the analysis of the possibility of using the product of RSE – the map of night lights, for modeling the economical dimension of the sustainable development of the regions of Ukraine. Using the regression and correlation analysis and neural networks, appropriate models for assessing the level of economic development of the Kherson region, Donetsk region, and the AR of Crimea were obtained. The study was carried out by the team of the World Data Center for Geoinformatics and Sustainable Development of the Igor Sikorsky Kyiv Polytechnic Institute. It was part of research on the analysis of the behavior of complex socio-economic systems and processes of sustainable development in the context of the quality and safety of people’s lives. Під час оцінювання рівня розвитку територій виникає проблема пошуку об’єктивних якісних даних, що будуть її характеризувати. Одним з можливих джерел таких даних є застосування методів дистанційного зондування Землі (ДЗЗ). Проаналізовано можливості використання одного з продуктів ДЗЗ – карти нічних вогнів, для моделювання економічного вимірювання сталого розвитку регіонів України. У результаті за допомогою регресійно-кореляційного аналізу та нейронних мереж отримано відповідні моделі оцінювання рівня економічного розвитку Херсонської області, Донецької області та АР Крим. Наведене дослідження виконано командою Світового центру даних "Геоінформатика та сталий розвиток" КПІ ім. Ігоря Сікорського і є частиною досліджень з аналізу поведінки складних соціально-економічних систем та процесів сталого розвитку в контексті якості та безпеки життя людей. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2023-06-30 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/285440 10.20535/SRIT.2308-8893.2023.2.04 System research and information technologies; No. 2 (2023); 49-62 Системные исследования и информационные технологии; № 2 (2023); 49-62 Системні дослідження та інформаційні технології; № 2 (2023); 49-62 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/285440/279550 |
| spellingShingle | сталий розвиток просторовий аналіз даних економічний розвиток нічні вогні математичне моделювання Zgurovsky, Michael Yefremov, Kostiantyn Gapon, Sergii Pyshnograiev, Ivan Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів |
| title | Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів |
| title_alt | Assessment of the economical dimension of sustainable development of the ukraine’s regions based on the brightness of night lights |
| title_full | Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів |
| title_fullStr | Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів |
| title_full_unstemmed | Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів |
| title_short | Оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів |
| title_sort | оцінювання економічного вимірювання сталого розвитку регіонів україни на основі яскравості нічних вогнів |
| topic | сталий розвиток просторовий аналіз даних економічний розвиток нічні вогні математичне моделювання |
| topic_facet | sustainable development spatial data analysis economical development night lights mathematical modeling сталий розвиток просторовий аналіз даних економічний розвиток нічні вогні математичне моделювання |
| url | https://journal.iasa.kpi.ua/article/view/285440 |
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