Selected Terrain Correction Methods and Formulas for Landsat 8 in Karst Mountains

An Excel dataset containing formulas and likely quantitative results for evaluating topographic correction methods on Landsat 8 surface reflectance data. The data was authored by Xuanying Shen and last updated on April 30, 2026. It compares the performance of the SCSCTS, SCS+C, and PLC models in a karst mountainous region of Guizhou, China.

Use Cases

• Benchmarking topographic correction algorithms based on the described performance metrics like reflectance dependence and pixel anomalies.
• Improving radiometric consistency for vegetation indices (EVI, NIRv, RDVI) in mountainous regions based on the described correction framework.
• Developing physically-based correction models for strong shadow conditions based on the illumination-stratified approach.
• Assessing seasonal sensitivity of correction methods under different solar elevation conditions as described in the study.

Strengths

• The dataset is associated with a method (SCSCTS) that reduced dependence of near-infrared reflectance on illumination by up to 99.4% under low solar elevation.
• Correction performance is quantitatively described, such as reducing anomalous reflectance pixels by 72.0% in spring and 93.9% in winter.
• The data has a clear open license (CC-BY-4.0) and a specific last update date (2026-04-30).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small (5.5 KB), indicating limited scope, likely containing formulas and summary results rather than extensive raw data.

Provenance

Source

figshare, authored by Xuanying Shen.

Collection Method

Likely contains derived results from applying correction methods to Landsat 8 surface reflectance data.

Time Range

Spring and winter conditions, specific years not stated.

Freshness

Last updated 2026-04-30 17:25:05; freshness should be verified.

Geography

A karst mountainous region in Guizhou, China.