Yingbin Deng

Orcid: 0000-0002-0015-147X

According to our database1, Yingbin Deng authored at least 15 papers between 2012 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
A Comparison of Machine Learning and Empirical Approaches for Deriving Bathymetry from Multispectral Imagery.
Remote. Sens., January, 2023

2022
Sub-Block Urban Function Recognition with the Integration of Multi-Source Data.
Sensors, 2022

Exploring the Applicability of Self-Organizing Maps for Ecosystem Service Zoning of the Guangdong-Hong Kong-Macao Greater Bay Area.
ISPRS Int. J. Geo Inf., 2022

Identify urban building functions with multisource data: a case study in Guangzhou, China.
Int. J. Geogr. Inf. Sci., 2022

2021
Extraction and Analysis of Finer Impervious Surface Classes in Urban Area.
Remote. Sens., 2021

Exploring the Impacts and Temporal Variations of Different Building Roof Types on Surface Urban Heat Island.
Remote. Sens., 2021

2020
Extraction and Analysis of Blue Steel Roofs Information Based on CNN Using Gaofen-2 Imageries.
Sensors, 2020

Developing Shopping and Dining Walking Indices Using POIs and Remote Sensing Data.
ISPRS Int. J. Geo Inf., 2020

2019
Examining the Deep Belief Network for Subpixel Unmixing with Medium Spatial Resolution Multispectral Imagery in Urban Environments.
Remote. Sens., 2019

2016
Development of a Class-Based Multiple Endmember Spectral Mixture Analysis (C-MESMA) Approach for Analyzing Urban Environments.
Remote. Sens., 2016

2015
Corrigendum to "Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters" [Int. J. Appl. Earth Observ. Geoinf. 33(2014) 290-301].
Int. J. Appl. Earth Obs. Geoinformation, 2015

RNDSI: A ratio normalized difference soil index for remote sensing of urban/suburban environments.
Int. J. Appl. Earth Obs. Geoinformation, 2015

2014
Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters.
Int. J. Appl. Earth Obs. Geoinformation, 2014

2013
Estimating Composite Curve Number Using an Improved SCS-CN Method with Remotely Sensed Variables in Guangzhou, China.
Remote. Sens., 2013

2012
Extraction and Analysis of Impervious Surfaces Based on a Spectral Un-Mixing Method Using Pearl River Delta of China Landsat TM/ETM+ Imagery from 1998 to 2008.
Sensors, 2012


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