TY - GEN
T1 - Detection and Identification of Surface Cover in Coalbed Methane Enrichment Area Based on Spectral Unmixing
AU - Zhao, Shanshan
AU - Qin, Qiming
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Based on the existing geological data and a large amount of research data in the study area, the article compared and analyzed the difference in hyperspectral reflectance between the potential enrichment area and the reference area. The use of Sentinel-2 multispectral images has been investigated to construct the surface recognition model of coalbed methane enrichment areas from two aspects: vegetation covered area and bare areas. Firstly, semi-automatic endmember extraction is implemented by adopting a more pratical spectral un-mixing method. And the vegetation research area and min-eral research area are separated accordingly. In the vegetation research area, the rich red edge information of Sentinel-2 is used to construct an anomaly recognition model. While in bare soil areas, advanced information processing technology is used to extract weak mineral alteration anomalies. The re-sults are validated with field data.
AB - Based on the existing geological data and a large amount of research data in the study area, the article compared and analyzed the difference in hyperspectral reflectance between the potential enrichment area and the reference area. The use of Sentinel-2 multispectral images has been investigated to construct the surface recognition model of coalbed methane enrichment areas from two aspects: vegetation covered area and bare areas. Firstly, semi-automatic endmember extraction is implemented by adopting a more pratical spectral un-mixing method. And the vegetation research area and min-eral research area are separated accordingly. In the vegetation research area, the rich red edge information of Sentinel-2 is used to construct an anomaly recognition model. While in bare soil areas, advanced information processing technology is used to extract weak mineral alteration anomalies. The re-sults are validated with field data.
KW - Anomaly detection
KW - Endmember Ex-traction
KW - Multi-spectral image
KW - Spectral Un-mixing
UR - http://www.scopus.com/inward/record.url?scp=85140354259&partnerID=8YFLogxK
U2 - 10.1109/IGARSS46834.2022.9883648
DO - 10.1109/IGARSS46834.2022.9883648
M3 - Conference Proceeding
AN - SCOPUS:85140354259
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3732
EP - 3735
BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Y2 - 17 July 2022 through 22 July 2022
ER -