Method and device for quantitatively estimating the content of surface elements by combining geochemical exploration and remote sensing

The invention discloses a method for quantitatively estimating the content of surface elements by combining geochemical exploration and remote sensing. It includes step 1: Obtain hyperspectral or multispectral remote sensing data in the detection area and adjacent areas; step 2: Obtain analysis data...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Luo, Mozhou, Cheng, Gong, Zhang, Hongrui, Li, Guangqiang, Luo, Dan, Yin, Shenghu, Li, Wei
Format: Patent
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The invention discloses a method for quantitatively estimating the content of surface elements by combining geochemical exploration and remote sensing. It includes step 1: Obtain hyperspectral or multispectral remote sensing data in the detection area and adjacent areas; step 2: Obtain analysis data of geochemical exploration in the detection area or adjacent areas; step 3: Perform atmospheric correction and geometric correction on the remote sensing data through data preprocessing to match the coordinate systems of the remote sensing image with the geochemical data; step 4: Use part of the geochemical exploration data as a modeling sample, and extract the reflectance of each band of the corresponding location from the remote sensing image according to the sample point coordinates; step 5: Calculate the correlation of reflectance of each band between the sample geochemical exploration data and the corresponding remote sensing data, select the characteristic band, and establish a regression model; step 6: Use the regression model to invert the content of each element or compound on the surface of the detection area, and display the abnormality in color. Remote sensing Geochemical data. exploration data. Data preprocessing., Sample selection Regression modeling., Quantitative inversion,) Fig.1