A Thesis on the Changes of Environmental Characteristics Based on Multi-Temporal Remote Sensing Imagery--The Case of Changbaishan Region
Abstract
The multidimensional classification feature dataset produced by using multi-temporal remote sensing data can fully exploit the vegetation information in remote sensing images to improve the classification accuracy of the surface cover information. In this paper, for example, the Songnen Plain in Changbai Mountain Range, which is one of the saline-alkaline soil distribution areas, is utilized to extract 11 types of surface cover information in the experimental area through different classification methods using the multidimensional classification feature dataset produced by multi-temporal Landsat8 remote sensing data, and the accuracy comparison analysis is carried out.
Keywords
Full Text:
PDFReferences
Song ZX. Research on multi-temporal remote sensing image change detection based on deep learning[D]. Jilin University,2023.
Qi WD, Zheng XC, He LM. et al. Remote sensing monitoring of temporal changes of cotton hailstorm based on multi-temporal Sentinel-2 images[J]. Remote Sensing Technology and Application, 2023, 38(03): 566-577.
Yao PL, Wang RJ. Research on environmental characteristics of Shendong region based on multi-temporal remote sensing data[J]. Geological Review, 2023, 69(S1): 439-441.
Lv Y. Research on rock image characterization and classification based on multi-source and multi-temporal remote sensing data[D]. Jilin University, 2023.
Teng XH, Wang L, Yu RP. et al. Height extraction of surface structures based on multi-temporal high-resolution remote sensing images[J]. Building Structure, 2023, 53(02): 155.
DOI: https://doi.org/10.18686/pes.v5i3.1980
Refbacks
- There are currently no refbacks.
