2015
DOI: 10.3390/rs70506296
|View full text |Cite
|
Sign up to set email alerts
|

An Improved Physics-Based Model for Topographic Correction of Landsat TM Images

Abstract: Abstract:Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications. Based on Li model and Sandmeier model, this paper proposed an improved physics-based model for the topographic correction of Landsat Thematic Mapper (TM) images. The model employed Normalized Difference Vegetation Index (NDVI) thresholds to approximately divide land targets into eleven groups, due to NDVI's lower sensiti… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
18
0

Year Published

2015
2015
2024
2024

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 34 publications
(18 citation statements)
references
References 60 publications
(89 reference statements)
0
18
0
Order By: Relevance
“…Optical remotely-sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications [37]. As shown in Table 2 and DEM data, the sun elevation angle is higher than most of the terrain slopes, and does not vary greatly over the study period.…”
Section: Cloud Detection and Atmosphere Correctionmentioning
confidence: 99%
“…Optical remotely-sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications [37]. As shown in Table 2 and DEM data, the sun elevation angle is higher than most of the terrain slopes, and does not vary greatly over the study period.…”
Section: Cloud Detection and Atmosphere Correctionmentioning
confidence: 99%
“…Furthermore, land cover stratification based on NDVI has been successfully used to consider the land cover dependency of c (Hantson and Chuvieco, 2011;Li et al, 2015;Reese and Olsson, 2011), and such stratification was also applied in this study. Each image was divided into three NDVI classes: <0.4, 0.4-0.6, >0.6 (Fig.…”
Section: Topographic Normalization Using C-correctionmentioning
confidence: 99%
“…For example, there are large estimation errors over the eastern regions of Jilin province because of the mountainous areas. Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications [47]. In addition, the moisture condition substantially changes with the topography and slope aspect, and precipitation is not the only factor which determines the moisture condition of croplands and the adjacent forests [48].…”
Section: Discussionmentioning
confidence: 99%