Haifeng Ding

Orcid: 0000-0002-2031-1725

According to our database1, Haifeng Ding authored at least 11 papers between 2014 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
A Comprehensive Assessment of the Pansharpening of the Nighttime Light Imagery of the Glimmer Imager of the Sustainable Development Science Satellite 1.
Remote. Sens., January, 2024

2023
Research on Scale Improvement of Geochemical Exploration Based on Remote Sensing Image Fusion.
Remote. Sens., April, 2023

2020
Assessment of the Capability of Sentinel-2 Imagery for Iron-Bearing Minerals Mapping: A Case Study in the Cuprite Area, Nevada.
Remote. Sens., 2020

2018
An Improved Pansharpening Method for Misaligned Panchromatic and Multispectral Data.
Sensors, 2018

2017
A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images.
Sensors, 2017

2016
Study on the extraction of iron mineralized alteration information in vegetation covered areas based on remote sensing ASTER data: A case study of Fenghuangshan iron deposit located in Lanling County, Shandong Province, China.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

Research on automatic detection of seismic landslides information.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

2015
Assessment of pan-sharpening methods applied to WorldView-2 image fusion.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

A new region growing-based segmentation method for high resolution remote sensing imagery.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2014
A multiple-point geostatistical method for digital elevation models conflation.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

A novel multi-resolution segmentation algorithm for highresolution remote sensing imagery based on minimum spanning tree and minimum heterogeneity criterion.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014


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