Results 201 to 210 of about 3,000 (242)

Ozone pollution monitoring using a full-time hyperspectral tomography system for multiple air pollutants. [PDF]

Nat Commun
Ma W, Xing C, Wang W, Zhang Q, Wang Z, Yang Y, Liu C.   +6 more
europepmc   +1 more source

Satellite mapping of every building's function in urban China reveals deep built environment disparities. [PDF]

Nat Commun
Li Z, Li L, Hu T, Cheng M, He W, Qiu T, Zhang L, Zhang H.   +7 more
europepmc   +1 more source

City-level carbon emissions data in Southeast Asia from 2000 to 2020. [PDF]

Sci Data
Chen X, Ba Y.
europepmc   +1 more source

Development of an AIoT-Based Early Flash-Flood Warning System for Smart Rural Disaster Resilience. [PDF]

Sensors (Basel)
Wiangnak V, Wiboonrat M, Duangsuwan S.
europepmc   +1 more source

A systematic review of digital and wearable sensor data in the ABCD study: Insights, methods, and emerging opportunities. [PDF]

Dev Cogn Neurosci
Alexander JD, Mills S, Sumpter K, Smith CJ, Das B, Fan R, Hunt ET, Brown SA, Curtis BL, Cummins KM, Mason M, Neale MC, Tapert SF, Baker FC, Fuemmeler BF, Wade NE.   +15 more
europepmc   +1 more source

SSTAR: a user-friendly framework for detecting and monitoring subtle thermal precursors to volcanic eruptions-application to Shishaldin, Alaska. [PDF]

Earth Planets Space
Girona T, Brenot L.
europepmc   +1 more source

Remote sensing of human beings – a perspective from nighttime light [PDF]

Geo-Spatial Information Science, 2016
AbstractCity lights, fishing boats, and oil fields are the major sources of nighttime lights, therefore the nighttime light images provide a unique source to map human beings and their activities from outer space. While most of the scholars focused on application of nighttime light remote sensing in urbanization and regional development, the actual ...
Xia Zhao, Xi Li
exaly   +2 more sources

Nighttime light remote sensing for urban applications: Progress, challenges, and prospects

ISPRS Journal of Photogrammetry and Remote Sensing, 2023
202310 bckw ; Version of Record ; Others ; Hong Kong Polytechnic University; Global STEM Professorship of the Hong Kong SAR Government ; Published ...
Qihao Weng, Karen C. Seto, Qiming Zheng
exaly   +3 more sources

GDP Forecasting Model for China’s Provinces Using Nighttime Light Remote Sensing Data

Remote Sensing, 2022
In order to promote the economic development of China’s provinces and provide references for the provinces to make effective economic decisions, it is urgent to investigate the trend of province-level economic development. In this study, DMSP/OLS data and NPP/VIIRS data were used to predict economic development.
Xiao Huang, Zhenfeng Shao, Bowen Cai
exaly   +3 more sources