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Author Putrenko, V., & Pashynska, N.
Title Data mining of sustainable development process with using nightlight indicators Type Journal Article
Year 2019 Publication TECHNOLOGY AUDIT AND PRODUCTION RESERVES Abbreviated Journal
Volume 3/2 Issue 47 Pages
Keywords Remote Sensing
Abstract (down) Об’єктом дослідження є процес сталого розвитку територіальних одиниць на прикладі регіонів України. Концепція сталого розвитку стала провідною стратегією розвитку для більшості країн світу. Однією із найбільших проблем залишається отримання повних та верифікованих даних для моделей оцінювання розвитку. В роботі було використано методику розрахунку індексу сталого розвитку, яка розроблена в Світовому центрі даних з геоінформатики та сталого розвитку Національного технічного університету України «Київський політехнічний інститут ім. Ігоря Сікорського». Дана методика ґрунтується на розрахунку метрики індексу сталого розвитку на основі вимірів якості життя населення та безпекової компоненти проживання для окремих країн та регіонів. Для застосування методики на регіональному рівні було запропоновано використання інформації про нічне освітлення території, яка отримується засобами дистанційного зондування Землі із супутникових систем. Досліджено характер та тісноту зв’язку між яскравістю нічного освітлення та індикаторами сталого розвитку. З’ясовано, що найбільш значущий зв’язок наявний між показниками індексу економічного розвитку, індексом впливу на зміну клімату та нічним освітленням території регіонів України. На основі геоінформаційного аналізу програмного забезпечення ArcGIS компанії ESRI було застосовано інструментарій статистичного зонування, який надає можливості для статистичної обробки даних супутникових знімків у межах виокремлених за адміністративним принципом регіонів або інших полігональних областей. На основі математичного апарату інтелектуального аналізу даних було здійснено глобальний та локальний регресійний аналіз зв’язку між виявленими показниками. Розгляд тісноти цього зв’язку в територіальному розрізі дозволив виявити зони з найбільшою та низькою тіснотою впливу, що пояснюється особливостями соціально-економічного розвитку даних територій. Завдяки цьому забезпечується можливість отримання розрахунку аналогічних показників на більш детальних територіальних рівнях, які відповідають окремим районам або містам обласного значення
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Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Ukranian Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ intern @ Serial 2737
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Author Li, X.; Ge, L.; Chen, X.
Title Detecting Zimbabwe's Decadal Economic Decline Using Nighttime Light Imagery Type Journal Article
Year 2013 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 5 Issue 9 Pages 4551-4570
Keywords Zimbabwe; economic decline; nighttime light; DMSP-OLS; remote sensing; light at night
Abstract (down) Zimbabwe’s economy declined between 2000 and 2009. This study detects the economic decline in different regions of Zimbabwe using nighttime light imagery from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). We found a good correlation (coefficient = 0.7361) between Zimbabwe’s total nighttime light (TNL) and Gross Domestic Product (GDP) for the period 1992 to 2009. Therefore, TNL was used as an indicator of regional economic conditions in Zimbabwe. Nighttime light imagery from 2000 and 2008 was compared at both national and regional scales for four types of regions. At the national scale, we found that nighttime light in more than half of the lit area decreased between 2000 and 2008. Moreover, within the four region types (inland mining towns, inland agricultural towns, border towns and cities) we determined that the mining and agricultural sectors experienced the most severe economic decline. Some of these findings were validated by economic survey data, proving that the nighttime light data is a potential data source for detecting the economic decline in Zimbabwe.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number IDA @ john @ Serial 212
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Author Levin, N.; Ali, S.; Crandall, D.; Kark, S.
Title World Heritage in danger: Big data and remote sensing can help protect sites in conflict zones Type Journal Article
Year 2019 Publication Global Environmental Change Abbreviated Journal Global Environmental Change
Volume 55 Issue Pages 97-104
Keywords Remote Sensing
Abstract (down) World Heritage sites provide a key mechanism for protecting areas of universal importance. However, fifty-four UNESCO sites are currently listed as “In Danger”, with 40% of these located in the Middle East. Since 2010 alone, thirty new sites were identified as under risk globally. We combined big-data and remote sensing to examine whether they can effectively be used to identify danger to World Heritage in near real-time. We found that armed-conflicts substantially threaten both natural- and cultural-heritage listed sites. Other major risks include poor management and development (globally), poaching (Africa mostly) and deforestation (tropics), yet conflict is the most prominent threat. We show that news-mining of big-data on conflicts and remote sensing of nights-lights enabled us to identify conflict afflicted areas in near real-time. These findings provide a crucial avenue for developing a global transparent early-warning system before irreversible damage to world heritage takes place.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0959-3780 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2279
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Author Yue, Y.; Tian, L.; Yue, Q.; Wang, Z.
Title Spatiotemporal Variations in Energy Consumption and Their Influencing Factors in China Based on the Integration of the DMSP-OLS and NPP-VIIRS Nighttime Light Datasets Type Journal Article
Year 2020 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 12 Issue 7 Pages 1151
Keywords Remote Sensing
Abstract (down) With the speedy growth of economic development, the imbalance of energy supply and demand pose a critical challenge for the energy security of our country. Meanwhile, the increasing and excessive energy consumption lead to the greenhouse effect and atmospheric pollution, greatly threatening the survival and development of human beings. This study integrated two nighttime light remote sensing datasets, namely Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data, to extend the temporal coverage of the study. Then, the distributions of China’s energy consumption from 1995 to 2016 at a 1-km resolution were estimated using different models and the spatiotemporal variations of energy consumption were explored on the basis of the best estimated results. Next, the factors influencing China’s energy intensity on the provincial level were investigated based on the spatial econometric model. The results show that: (1) The integrated nighttime light datasets can be successfully applied to estimate the dynamic changes of energy consumption. Moreover, the panel data model established in our research performed better than the quadratic polynomial model. (2) During the observation period, the energy consumption in China significantly increased, especially in the Yangtze River Delta, the Pearl River Delta, the Beijing–Tianjin–Hebei region, eastern coastal cities, and provincial capitals. (3) Different from the random spatial distribution pattern of energy consumption on the provincial level, the spatial distribution of energy consumption on the prefectural level has significant clusters, and its spatial agglomeration was strengthened year by year during the research period. (4) The spatial Durbin model (SDM) with a spatial fixed effect has been proved to be more suitable to explore the impact mechanism of China’s energy consumption. Among the four socio-economic factors, industrial structure has the greatest impact on the provincial energy intensity in China. Moreover, the changes in industrial structure and foreign direct investment (FDI) can not only influence the local energy intensity but also affect the energy intensity of the neighboring provinces.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2922
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Author Liu, Y.; Yang, Y.; Jing, W.; Yao, L.; Yue, X.; Zhao, X.
Title A New Urban Index for Expressing Inner-City Patterns Based on MODIS LST and EVI Regulated DMSP/OLS NTL Type Journal Article
Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 9 Issue 8 Pages 777
Keywords Remote Sensing
Abstract (down) With the rapid pace of urban expansion, comprehensively understanding urban spatial patterns, built environments, green-spaces distributions, demographic distributions, and economic activities becomes more meaningful. Night Time Lights (NTL) images acquired through the Operational Linescan System of the US Defense Meteorological Satellite Program (DMSP/OLS NTL) have long been utilized to monitor urban areas and their expansion characteristics since this system detects variation in NTL emissions. However, the pixel saturation phenomenon leads to a serious limitation in mapping luminance variations in urban zones with nighttime illumination levels that approach or exceed the pixel saturation limits of OLS sensors. Consequently, we propose an NTL-based city index that utilizes the Moderate-resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) images to regulate and compensate for desaturation on NTL images acquired from corresponding urban areas. The regulated results achieve good performance in differentiating central business districts (CBDs), airports, and urban green spaces. Consequently, these derived imageries could effectively convey the structural details of urban cores. In addition, compared with the Vegetation Adjusted NTL Urban Index (VANUI), LST-and-EVI-regulated-NTL-city index (LERNCI) reveals superior capability in delineating the spatial structures of selected metropolis areas across the world, especially in the large cities of developing countries. The currently available results indicate that LERNCI corresponds better to city spatial patterns. Moreover, LERNCI displays a remarkably better “goodness-of-fit” correspondence with both the Version 1 Nighttime Visible Infrared Imaging Radiometer Suite Day/Night Band Composite (NPP/VIIRS DNB) data and the WorldPop population-density data compared with the VANUI imageries. Thus, LERNCI can act as a helpful indicator for differentiating and classifying regional economic activities, population aggregations, and energy-consumption and city-expansion patterns. LERNCI can also serve as a valuable auxiliary reference for decision-making processes that concern subjects such as urban planning and easing the central functions of metropolis.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1713
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