Correcting the nighttime lighting data underestimation effect based on light source detection and luminance reconstruction DOI Creative Commons
Peng Gao, Tianjun Wu, Yong Ge

и другие.

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2023, Номер 121, С. 103380 - 103380

Опубликована: Июнь 7, 2023

Nighttime light remote sensing provides a unique perspective on monitoring human activities and socioeconomic conditions. However, early studies nighttime lighting usually neglected the evaluation of source detection luminance conditions in underdeveloped areas. Recent have identified significant underestimation effect areas, which makes it difficult to use as valid proxy for other variables. To address this problem, paper proposes method based reconstruction. Missing luminous pixels will be using rich information provided by daily-scale data blooming patterns, diverse ancillary utilized regression reconstruction values supplement annual correct effect. The effectiveness was verified from 7,776 townships areas China. results demonstrated that proposed corrected NPP/VIIRS improved accuracy 23.23% 17.71% at village township scales, respectively. correlations between night variables were also improved. Spearman's rank correlation coefficients population, GDP, electricity consumption county scale increased 0.045, 0.020, 0.018, agriculture-related different degrees both scales. can contribute improving modeling correcting This provide better support sustainable development studies.

Язык: Английский

Exploring the relationship between urban residents' emotional changes and built environment before and during the COVID-19 pandemic from the perspective of resilience DOI
Donghui Dai, Wen Dong, Yaowu Wang

и другие.

Cities, Год журнала: 2023, Номер 141, С. 104510 - 104510

Опубликована: Авг. 10, 2023

Язык: Английский

Процитировано

10

Urban flood risk evaluation using social media data and Bayesian network approach: a spatial-temporal dynamic analysis in Wuhan city, China DOI
Yihan Zhang, Jian Fang, Dingtao Shen

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106388 - 106388

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Unveiling the impact of intelligent transformation on economic resilience toward sustainable solutions: a spatio–temporal heterogeneity perspective DOI

Jingwen Lyu,

Wei Xiao, Wei He

и другие.

Asia-Pacific Journal of Regional Science, Год журнала: 2025, Номер unknown

Опубликована: Апрель 28, 2025

Язык: Английский

Процитировано

0

Towards resilience effectiveness: Assessing its patterns and determinants to identify optimal geographic zones DOI
Tong Cheng,

Yonghua Zhao,

Yongze Song

и другие.

Journal of Cleaner Production, Год журнала: 2023, Номер 429, С. 139596 - 139596

Опубликована: Ноя. 1, 2023

Язык: Английский

Процитировано

9

Correcting the nighttime lighting data underestimation effect based on light source detection and luminance reconstruction DOI Creative Commons
Peng Gao, Tianjun Wu, Yong Ge

и другие.

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2023, Номер 121, С. 103380 - 103380

Опубликована: Июнь 7, 2023

Nighttime light remote sensing provides a unique perspective on monitoring human activities and socioeconomic conditions. However, early studies nighttime lighting usually neglected the evaluation of source detection luminance conditions in underdeveloped areas. Recent have identified significant underestimation effect areas, which makes it difficult to use as valid proxy for other variables. To address this problem, paper proposes method based reconstruction. Missing luminous pixels will be using rich information provided by daily-scale data blooming patterns, diverse ancillary utilized regression reconstruction values supplement annual correct effect. The effectiveness was verified from 7,776 townships areas China. results demonstrated that proposed corrected NPP/VIIRS improved accuracy 23.23% 17.71% at village township scales, respectively. correlations between night variables were also improved. Spearman's rank correlation coefficients population, GDP, electricity consumption county scale increased 0.045, 0.020, 0.018, agriculture-related different degrees both scales. can contribute improving modeling correcting This provide better support sustainable development studies.

Язык: Английский

Процитировано

8