NPP-VIIRS Nighttime Lights Illustrate the Post-Earthquake Damage and Subsequent Economic Recovery in Hatay Province, Turkey
Abstract
:1. Introduction
2. Study Area and Data Sources
2.1. Study Area
2.2. Data Sources
3. Methodology
3.1. Methods of Assessing Earthquake Damage
- We extracted radiance, solar zenith angle, QF cloud mask, and moon illumination fraction from the VNP46A1 data for each pixel within the study area.
- To minimise the impact of solar illumination, pixels with a solar zenith angle of less than 108 degrees were excluded. On 12 February 2023, most pixels affected by clouds were concentrated over the Nur Mountains and the Mediterranean Sea, where their impact on urban illumination was minimal. Consequently, we could effectively eliminate these cloud-contaminated pixels using the QF cloud mask.
- To accurately identify cloud-contaminated pixels, we excluded all pixels with moon illumination levels exceeding 60% [36].
- The image was processed using two-dimensional linear interpolation techniques to fill in the vacant pixels left by the masking manipulation.
- Subsequently, the average value of the VNP46A1 image from the ocean, mountain, and desert regions was calculated to determine an NTL threshold. This threshold was used to eliminate background noise from the VNP46A1 image, as demonstrated in the following equation:
3.2. Method of Assessing Economic Recovery of Affected Regions
4. Results
4.1. Earthquake Damage Map from NTLs
4.2. Assessment of the Post-Earthquake Economic Recovery
5. Discussion
5.1. Relationships Between Reduced NTLs and Damaged Buildings
5.2. Reliability Analysis of NTL Data Reflecting the Level of Regional Economic Development
5.3. Validation of the Effectiveness of the Post-Earthquake Economic Recovery
5.3.1. Validation of the Effectiveness of the Post-Earthquake Economic Recovery Framework
5.3.2. Verification of Economic Recovery Across Various Districts Post-Earthquake
5.4. Strengths, Weaknesses, and Prospects of the Study
- The 500 m resolution of the data presents challenges in identifying earthquake damage within residential areas smaller than 0.25 km2. The mixed-pixel nature of the data generates composite signals that encompass various land covers, including structures with differing levels of damage. This blending diminishes the accuracy of assessing the specific damage status of individual structures. Moreover, illumination from interfering light sources—such as highway landscape lights, emergency rescue lights, and temporary warming fires—further compromises the accuracy of damage assessments. Notably, variations in NTL illumination exhibit a strong linear relationship (R2 > 0.7) with moderate to severe structural damage, yet only a weak linear correlation (R2 < 0.3) with slight structural damage. This disparity highlights the dual nature of NPP-VIIRS NTL data in seismic evaluations: while it excels in macro-level monitoring of significant building damage across large areas after major seismic events, its ability to detect minor damage—such as cracks or localised collapses—is limited by its low spatial resolution and the mixed-pixel effect, reducing its effectiveness in identifying low-intensity seismic damage scenarios.
- NTL data serve as a crucial proxy for gauging the intensity of human socioeconomic activities. However, its application in assessing economic recovery after an earthquake faces significant challenges due to its multidimensional complexity. Certain post-disaster economic behaviours can heavily interfere with NTL signals. For instance, the increased brightness from temporary settlement relief facilities and nighttime construction efforts can easily be misinterpreted as indications of short-term economic recovery. On the other hand, factors such as population migration and workforce loss can suppress NTL signals, reflecting a more profound decline in economic activity in the affected regions. Informal economic activities that emerge after disasters—such as unlit temporary markets and mobile vendors—are often excluded from NTL data analysis, potentially leading to a systemic underestimation of the resilience and recovery capacity of the post-disaster economy. Furthermore, data collected over the 22 months following the earthquake may primarily represent trends from the initial stages of economic recovery, thereby limiting the reliability of the findings.
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix A.1
Point | Latitude | Longitude | City | Structure | Field Assessment | NTL Assessment |
---|---|---|---|---|---|---|
33 | 36.229135 | 36.165190 | Antakya | Residential buildings | Severely damaged | Moderately damaged |
34 | 36.231058 | 36.165816 | Antakya | Residential buildings | Severely damaged | Moderately damaged |
35 | 36.230311 | 36.169230 | Antakya | Residential buildings | Severely damaged | Severely damaged |
36 | 36.229718 | 36.168989 | Antakya | Residential buildings | Severely damaged | Severely damaged |
37 | 36.229971 | 36.167919 | Antakya | Residential buildings | Severely damaged | Severely damaged |
38 | 36.229917 | 36.164761 | Antakya | Residential buildings | Severely damaged | Moderately damaged |
39 | 36.231030 | 36.166230 | Antakya | Residential buildings | Severely damaged | Moderately damaged |
40 | 36.227029 | 36.163210 | Antakya | Residential buildings | Severely damaged | No damage |
41 | 36.238769 | 36.175664 | Antakya | Residential buildings | Severely damaged | Severely damaged |
44 | 36.239264 | 36.175192 | Antakya | Residential buildings | Severely damaged | Severely damaged |
45 | 36.239587 | 36.174556 | Antakya | Residential buildings | Severely damaged | Severely damaged |
46 | 36.239842 | 36.174091 | Antakya | Residential buildings | Severely damaged | Severely damaged |
47 | 36.240405 | 36.173694 | Antakya | Residential buildings | Severely damaged | Severely damaged |
48 | 36.240463 | 36.173423 | Antakya | Residential buildings | Severely damaged | Severely damaged |
49 | 36.240688 | 36.173581 | Antakya | Residential buildings | Severely damaged | Severely damaged |
50 | 36.240839 | 36.173702 | Antakya | Residential buildings | Severely damaged | Severely damaged |
51 | 36.239997 | 36.173350 | Antakya | Residential buildings | Severely damaged | Severely damaged |
52 | 36.240112 | 36.173131 | Antakya | Residential buildings | Severely damaged | Severely damaged |
53 | 36.240274 | 36.173241 | Antakya | Residential buildings | Severely damaged | Severely damaged |
54 | 36.240429 | 36.172994 | Antakya | Residential buildings | Severely damaged | Severely damaged |
55 | 36.240267 | 36.172886 | Antakya | Residential buildings | Severely damaged | Severely damaged |
56 | 36.240550 | 36.172784 | Antakya | Residential buildings | Severely damaged | Severely damaged |
57 | 36.240416 | 36.172655 | Antakya | Residential buildings | Severely damaged | Severely damaged |
58 | 36.240745 | 36.172505 | Antakya | Residential buildings | Severely damaged | Severely damaged |
59 | 36.241039 | 36.172805 | Antakya | Residential buildings | Severely damaged | Severely damaged |
60 | 36.241110 | 36.172623 | Antakya | Residential buildings | Severely damaged | Severely damaged |
61 | 36.240215 | 36.172083 | Antakya | Residential buildings | Severely damaged | Severely damaged |
62 | 36.240042 | 36.172413 | Antakya | Residential buildings | Severely damaged | Severely damaged |
63 | 36.239851 | 36.172581 | Antakya | Residential buildings | Severely damaged | Severely damaged |
64 | 36.239735 | 36.172734 | Antakya | Residential buildings | Severely damaged | Severely damaged |
65 | 36.241418 | 36.172778 | Antakya | Residential buildings | Severely damaged | Severely damaged |
66 | 36.241354 | 36.172972 | Antakya | Residential buildings | Severely damaged | Severely damaged |
83 | 36.241648 | 36.173339 | Antakya | Residential buildings | Severely damaged | Severely damaged |
77 | 36.582782 | 36.169085 | Iskenderun | Residential buildings | Severely damaged | Severely damaged |
78 | 36.206695 | 36.152426 | Antakya | Residential buildings | Severely damaged | Severely damaged |
79 | 36.230528 | 36.150281 | Antakya | Residential buildings | Severely damaged | Slightly damaged |
80 | 36.241316 | 36.174080 | Antakya | Residential buildings | Severely damaged | Severely damaged |
81 | 36.241375 | 36.174252 | Antakya | Residential buildings | Severely damaged | Severely damaged |
82 | 36.240990 | 36.173876 | Antakya | Residential buildings | Severely damaged | Severely damaged |
67 | 36.241648 | 36.173339 | Antakya | Residential buildings | Severely damaged | Severely damaged |
84 | 36.241127 | 36.175161 | Antakya | Residential buildings | Severely damaged | Severely damaged |
85 | 36.239203 | 36.174925 | Antakya | Residential buildings | Severely damaged | Severely damaged |
86 | 36.239916 | 36.177123 | Antakya | Residential buildings | Severely damaged | Severely damaged |
111 | 36.185111 | 36.121000 | Antakya | School buildings | Severely damaged | Severely damaged |
0 | 36.569031 | 36.166170 | Iskenderun | Medical buildings | Severely damaged | Severely damaged |
116 | 36.270309 | 36.223331 | Antakya | Medical buildings | Slightly damaged | Slightly damaged |
124 | 36.240469 | 36.174834 | Antakya | Critical buildings | Severely damaged | Severely damaged |
130 | 36.591100 | 36.168200 | Iskenderun | Religious buildings | Severely damaged | Severely damaged |
148 | 36.361587 | 36.286585 | Antakya | Airports | Severely damaged | Severely damaged |
150 | 36.231208 | 36.166476 | Antakya | Roads and bridges | Severely damaged | Moderately damaged |
26 | 36.195933 | 36.158567 | Antakya | Residential buildings | Severely damaged | Severely damaged |
87 | 36.589400 | 36.178200 | Iskenderun | Residential buildings | Severely damaged | Moderately damaged |
104 | 36.245400 | 36.569900 | Reyhanli | Residential buildings | Severely damaged | Moderately damaged |
119 | 36.235400 | 36.169500 | Antakya | Medical buildings | Severely damaged | Severely damaged |
126 | 36.201500 | 36.165500 | Antakya | Religious buildings | Severely damaged | Severely damaged |
133 | 36.201500 | 36.165500 | Antakya | Historic buildings | Severely damaged | Severely damaged |
135 | 36.531637 | 36.364843 | Kirikhan | Historic buildings | Severely damaged | No damage |
136 | 36.201900 | 36.162100 | Antakya | Historic buildings | Severely damaged | Severely damaged |
158 | 36.200000 | 36.159000 | Antakya | Roads and bridges | Slightly damaged | Severely damaged |
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Data Type | Data Description | Time Range | Source | Purpose |
---|---|---|---|---|
NPP-VIIRS VNP46A1 DNB NTLs | Post-earthquake daily NTLs under less cloudy conditions | 12 February 2023 | LAADS DAAC | Assessment of potential damage from the earthquake disaster |
NPP-VIIRS VNP46A3 monthly NTLs | Pre-earthquake monthly NTLs | January 2023 | LAADS DAAC | Assessment of potential damage from the earthquake disaster |
Time series monthly NTLs | April 2020–November 2024 | LAADS DAAC | Assessment of the post-earthquake economic recovery | |
Landsat 8 OLI image | Post-earthquake multispectral image | 16 July 2023 | EarthExplorer | Extraction of vegetation extent |
Earthquake damage reference data | Reference map of building damage | Last updated on 9 May 2023 | EOS | Validation of NTL-identified building damage |
Reference map of earthquake-damaged buildings | February 2023 | Earth Engine Apps | Validation of NTL-identified building damage | |
Field photographs of structural damage | 3 April 2023 | EERI | Validation of NTL-identified building damage | |
Provincial GDP statistics | Provincial GDP statistics in Turkey | 2012–2023 | TURKSTAT | Analysis of the regression relationship between NTLs and economic activity in Turkey |
Administrative divisions | Administrative boundaries for 12 districts in Hatay Province, Turkey | 2022 | GADM | Assessment of the post-earthquake economic recovery across the districts |
Reference Source | Category | CE | OE | OA | KC |
---|---|---|---|---|---|
EOS | Damage | 26.66% | 18.43% | 77.28% | 0.55 |
No damage | 18.35% | 26.56% | |||
Earth Engine Apps | Damage | 29.30% | 25.88% | 71.55% | 0.43 |
No damage | 27.49% | 31.04% |
District | Pre-Earthquake | District | Post-Earthquake | ||||
---|---|---|---|---|---|---|---|
R2 | F | p | R2 | F | p | ||
Hatay | 0.94 | 522.86 | 0.00 | Hatay | 0.85 | 117.34 | 0.00 |
Altinozu | 0.93 | 455.05 | 0.00 | Altinozu | 0.95 | 114.41 | 0.00 |
Belen | 0.91 | 341.40 | 0.00 | Belen | 0.86 | 36.56 | 0.00 |
Dortyol | 0.92 | 375.68 | 0.00 | Dortyol | 0.76 | 18.73 | 0.00 |
Erzin | 0.74 | 91.19 | 0.00 | Erzin | 0.70 | 13.72 | 0.00 |
Hassa | 0.98 | 1633.23 | 0.00 | Hassa | 0.96 | 128.72 | 0.00 |
Iskenderun | 0.97 | 957.90 | 0.00 | Iskenderun | 0.81 | 26.17 | 0.00 |
Kirikhan | 0.98 | 1923.83 | 0.00 | Kirikhan | 0.91 | 60.62 | 0.00 |
Kumlu | 0.89 | 271.01 | 0.00 | Kumlu | 0.91 | 60.38 | 0.00 |
Antakya | 0.87 | 209.03 | 0.00 | Antakya | 0.94 | 318.92 | 0.00 |
Reyhanli | 0.95 | 559.58 | 0.00 | Reyhanli | 0.94 | 94.06 | 0.00 |
Samandag | 0.97 | 930.72 | 0.00 | Samandag | 0.55 | 11.50 | 0.00 |
Yayladagi | 0.95 | 631.81 | 0.00 | Yayladagi | 0.94 | 89.17 | 0.00 |
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Li, F.; Liao, S.; Fu, X.; Liu, T. NPP-VIIRS Nighttime Lights Illustrate the Post-Earthquake Damage and Subsequent Economic Recovery in Hatay Province, Turkey. ISPRS Int. J. Geo-Inf. 2025, 14, 149. https://doi.org/10.3390/ijgi14040149
Li F, Liao S, Fu X, Liu T. NPP-VIIRS Nighttime Lights Illustrate the Post-Earthquake Damage and Subsequent Economic Recovery in Hatay Province, Turkey. ISPRS International Journal of Geo-Information. 2025; 14(4):149. https://doi.org/10.3390/ijgi14040149
Chicago/Turabian StyleLi, Feng, Shunbao Liao, Xingjian Fu, and Tianxuan Liu. 2025. "NPP-VIIRS Nighttime Lights Illustrate the Post-Earthquake Damage and Subsequent Economic Recovery in Hatay Province, Turkey" ISPRS International Journal of Geo-Information 14, no. 4: 149. https://doi.org/10.3390/ijgi14040149
APA StyleLi, F., Liao, S., Fu, X., & Liu, T. (2025). NPP-VIIRS Nighttime Lights Illustrate the Post-Earthquake Damage and Subsequent Economic Recovery in Hatay Province, Turkey. ISPRS International Journal of Geo-Information, 14(4), 149. https://doi.org/10.3390/ijgi14040149