The potential of nighttime light remote sensing data to evaluate the development of digital economy: A case study of China at the city level

Computers Environment and Urban Systems ◽

10.1016/j.compenvurbsys.2021.101749 ◽

2022 ◽

Vol 92 ◽

pp. 101749

Author(s):

Zuoqi Chen ◽

Ye Wei ◽

Kaifang Shi ◽

Zhiyuan Zhao ◽

Congxiao Wang ◽

...

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Digital Economy ◽

Sensing Data ◽

Nighttime Light ◽

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Comparison of selected impervious surface products derived from remote sensing data — A case study for the city of Munich

2011 Joint Urban Remote Sensing Event ◽

10.1109/jurse.2011.5764761 ◽

2011 ◽

Author(s):

Christian Geiss ◽

Michael Wurm ◽

Hannes Taubenbock ◽

Wieke Heldens ◽

Thomas Esch

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Impervious Surface ◽

Sensing Data ◽

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Estimating urban greenness index using remote sensing data: A case study of an affluent vs poor suburbs in the city of Johannesburg

The Egyptian Journal of Remote Sensing and Space Science ◽

10.1016/j.ejrs.2020.07.002 ◽

2020 ◽

Author(s):

Khaled Abutaleb ◽

Marko Freddy Mudede ◽

Nsalambi Nkongolo ◽

Solomon W. Newete

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Sensing Data ◽

The City ◽

Greenness Index

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Improving canopy variables estimation from remote sensing data by exploiting ancillary information. Case study on sugar beet canopies

Agronomie ◽

10.1051/agro:2002008 ◽

2002 ◽

Vol 22 (2) ◽

pp. 205-215 ◽

Author(s):

Bruno Combal ◽

Fr�d�ric Baret ◽

Marie Weiss

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Sensing Data ◽

Ancillary Information

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Water extend estimation over vegetated terrains in coastal area using multitemporal remote sensing data: a case study in Tumpat, Malaysia

7th Brunei International Conference on Engineering and Technology 2018 (BICET 2018) ◽

10.1049/cp.2018.1553 ◽

2018 ◽

Author(s):

Z. Rahimi ◽

F. Othman

Keyword(s):

Remote Sensing ◽

Coastal Area ◽

Remote Sensing Data ◽

Sensing Data ◽

Multitemporal Remote Sensing

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Evaluating change detection techniques using remote sensing data: Case study New Administrative Capital Egypt

The Egyptian Journal of Remote Sensing and Space Science ◽

10.1016/j.ejrs.2021.03.001 ◽

2021 ◽

Author(s):

Ahmed Saber ◽

Ibrahim El-Sayed ◽

Mustafa Rabah ◽

Mohamed Selim

Keyword(s):

Remote Sensing ◽

Change Detection ◽

Remote Sensing Data ◽

Detection Techniques ◽

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Research on the Development of Urbanization in Yangtze River Economic Belt Based on Nighttime Light Remote Sensing Data

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss39084.2020.9324574 ◽

2020 ◽

Author(s):

Wei Zhang ◽

Jianwei Qi ◽

Guanghui Wang ◽

Tao Zhang ◽

Haoran Zhai

Keyword(s):

Remote Sensing ◽

Yangtze River ◽

Remote Sensing Data ◽

Sensing Data ◽

Nighttime Light

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A suitalbe solution for extraction of alteration anomalies from the remote sensing data: A case study of the Baogutu porphyry copper deposit intrusion, Xinjiang, China using Aster data

2009 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2009.5418086 ◽

2009 ◽

Author(s):

Yu Chen ◽

Qizhong Lin ◽

Huadong Guo ◽

Yongmin Wei ◽

Qinjun Wang

Keyword(s):

Remote Sensing ◽

Porphyry Copper ◽

Remote Sensing Data ◽

Copper Deposit ◽

Porphyry Copper Deposit ◽

Sensing Data ◽

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The Evaluation of GPM Precipitation Remote Sensing Data with Observed Data (Case Study: Mid-West of Iran)

Journal of Remote Sensing and Gis ◽

10.52547/gisj.11.2.115 ◽

2019 ◽

Vol 11 (2) ◽

pp. 115-124

Author(s):

hamid reza sadeghi ◽

jafar masoompour ◽

Morteza miri

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

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Hydrological modelling and evapotranspiration estimation based on remote sensing data : a case study in the Doñana region and surrounding irrigated areas

10.20868/upm.thesis.52678 ◽

2018 ◽

Author(s):

María del Carmen Moyano Pérez

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Hydrological Modelling ◽

Sensing Data ◽

Evapotranspiration Estimation

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Developing a Comprehensive Spectral-Biogeochemical Database of Midwestern Rivers for Water Quality Retrieval Using Remote Sensing Data: A Case Study of the Wabash River and Its Tributary, Indiana

Remote Sensing ◽

10.3390/rs8060517 ◽

2016 ◽

Vol 8 (6) ◽

pp. 517 ◽

Author(s):

Jing Tan ◽

Keith Cherkauer ◽

Indrajeet Chaubey

Keyword(s):

Remote Sensing ◽

Water Quality ◽

Remote Sensing Data ◽

Sensing Data ◽

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