The Annual Cycling of Nighttime Lights in India
India is known to have unstable power supply, and many locations show an annual cycle in VIIRS Nighttime Light (VNL). In this study, autocorrelation function (ACF) analysis is used to identify the annual cycling in VNL. Two fundamentally different classification techniques are proposed to classify t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/6/1199 |
| _version_ | 1827697149974937600 |
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| author | Fengchi Hsu Mikhail Zhizhin Tilottama Ghosh Christopher Elvidge Jay Taneja |
| author_facet | Fengchi Hsu Mikhail Zhizhin Tilottama Ghosh Christopher Elvidge Jay Taneja |
| author_sort | Fengchi Hsu |
| collection | DOAJ |
| description | India is known to have unstable power supply, and many locations show an annual cycle in VIIRS Nighttime Light (VNL). In this study, autocorrelation function (ACF) analysis is used to identify the annual cycling in VNL. Two fundamentally different classification techniques are proposed to classify the ACF profile into one of the three arch types, i.e., acyclic, single peak, and dual peak. The results from the two classification techniques are closely compared to verify their output. This analysis is carried out for the entire territory of India in 15 arc second grid cells. The power stability data acquired from the India Human Development Survey (IHDS) and the Electricity Supply Monitoring Initiative (ESMI) are used to verify their relationship to the annual cycling of VNL. To further aide the analysis, land use/land class are accounted for by data from the India National Remote Sensing Center (NRSC). As a result, the contribution of power stability to VNL annual cycling in India is inconclusive due to the limitation of power stability data. Furthermore, other potential factors should be further examined. |
| first_indexed | 2024-03-10T13:02:16Z |
| format | Article |
| id | doaj.art-b145cdab92d545cea6b3d087e81f542a |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T13:02:16Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-b145cdab92d545cea6b3d087e81f542a2023-11-21T11:25:21ZengMDPI AGRemote Sensing2072-42922021-03-01136119910.3390/rs13061199The Annual Cycling of Nighttime Lights in IndiaFengchi Hsu0Mikhail Zhizhin1Tilottama Ghosh2Christopher Elvidge3Jay Taneja4Earth Observation Group, Payne Institute for Public Policy, Colorado School of Mines, Golden, CO 80401, USAEarth Observation Group, Payne Institute for Public Policy, Colorado School of Mines, Golden, CO 80401, USAEarth Observation Group, Payne Institute for Public Policy, Colorado School of Mines, Golden, CO 80401, USAEarth Observation Group, Payne Institute for Public Policy, Colorado School of Mines, Golden, CO 80401, USAElectrical and Computer Engineering, University of Massachusetts, Amherst, MA 01003, USAIndia is known to have unstable power supply, and many locations show an annual cycle in VIIRS Nighttime Light (VNL). In this study, autocorrelation function (ACF) analysis is used to identify the annual cycling in VNL. Two fundamentally different classification techniques are proposed to classify the ACF profile into one of the three arch types, i.e., acyclic, single peak, and dual peak. The results from the two classification techniques are closely compared to verify their output. This analysis is carried out for the entire territory of India in 15 arc second grid cells. The power stability data acquired from the India Human Development Survey (IHDS) and the Electricity Supply Monitoring Initiative (ESMI) are used to verify their relationship to the annual cycling of VNL. To further aide the analysis, land use/land class are accounted for by data from the India National Remote Sensing Center (NRSC). As a result, the contribution of power stability to VNL annual cycling in India is inconclusive due to the limitation of power stability data. Furthermore, other potential factors should be further examined.https://www.mdpi.com/2072-4292/13/6/1199nighttime lightremote sensingVIIRSday-night bandtime series analysisIndia |
| spellingShingle | Fengchi Hsu Mikhail Zhizhin Tilottama Ghosh Christopher Elvidge Jay Taneja The Annual Cycling of Nighttime Lights in India Remote Sensing nighttime light remote sensing VIIRS day-night band time series analysis India |
| title | The Annual Cycling of Nighttime Lights in India |
| title_full | The Annual Cycling of Nighttime Lights in India |
| title_fullStr | The Annual Cycling of Nighttime Lights in India |
| title_full_unstemmed | The Annual Cycling of Nighttime Lights in India |
| title_short | The Annual Cycling of Nighttime Lights in India |
| title_sort | annual cycling of nighttime lights in india |
| topic | nighttime light remote sensing VIIRS day-night band time series analysis India |
| url | https://www.mdpi.com/2072-4292/13/6/1199 |
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