Monthly 30-m Surface Water Dataset of the Tibetan Plateau from 2000 to 2021

File name

Detailed definition

Description

TP MWH Dataset Output Files:

TP2000_2021_MonthlyWater

History_afterSGF.zip

File composition

The core dataset comprises 264 standardized monthly surface water distribution maps covering the entire Tibetan Plateau from January 2000 to December 2021.

File format

GeoTIFF raster format, compatible with mainstream remote sensing and GIS software platforms.

Spatial reference

WGS84 geographic coordinate system (EPSG:4326), with a spatial resolution of 30 m, consistent with the original Landsat observation data.

Pixel classification rules

Binary classification system, where pixel value = 3 represents surface water body, and pixel value = 1 represents not-water; no invalid gap pixels exist in the final reconstructed dataset.

Naming convention

TP_YYYY_MMafterSGF.tif, where YYYY denotes the 4-digit year and MM denotes the 2-digit month, enabling straightforward temporal indexing and batch processing.

Validation Auxiliary File: TP_validation_samples.csv

This CSV file records complete attribute information for all 12,141 stratified random validation samples used in this study, supporting reproducible quantitative accuracy evaluation and cross-dataset comparison. All geographic coordinates are recorded to 8 decimal places to eliminate spatial matching errors.

samples

Unique numbering sequence identifier for each validation sample point. Continuous integer from 1 to 12141.

longitude

Longitude coordinate of the sample point in the WGS84 geographic coordinate system. Numeric value recorded to 8 decimal places.

latitude

Latitude coordinate of the sample point in the WGS84 geographic coordinate system. Numeric value recorded to 8 decimal places.

GE_observation_date

Acquisition date of the high-resolution historical imagery from Google Earth Pro for the sample point, retrieved via the built-in time-slider function to match the dataset’s temporal coverage.

Date format: YYYY/MM/DD

actual_classification

Ground truth classification of the sample point, determined through manual visual interpretation of Google Earth Pro high-resolution historical imagery.

1 = not-water; 3 = water.

land_cover_type

Refined 9-category land cover classification of the sample point, supporting stratified accuracy evaluation for typical plateau surface features.

9 = visualization plotting placeholder; 8 = Frozen Water Surface; 7 = Snow-Covered Water Surface; 6 = Cloud and Terrain Shadow Occlusion; 5 = River Water; 4 = Saline Shallow Water and Saline Land; 3 = Natural Open Water; 2 = Vegetation; 1 = Terrestrial Land

TPMWH_classification

Classification result of the sample point extracted from the corresponding year-month TP MWH dataset image.

1 = not-water; 3 = water.

TPMWH_validation_results

Binary validation result indicating the matching status between TP MWH classification and ground truth actual_classification.

1 = correct prediction; 0 = incorrect prediction.

JRC_classification

Classification result of the sample point extracted from the corresponding year-month original JRC MWH dataset image.

1 = not-water; 3 = water; 0 = invalid gap pixel.

JRC_validation_results

Binary validation result indicating the matching status between JRC MWH classification and ground truth actual_classification

1 = correct prediction; 0 = incorrect prediction.

GLAD_classification

Classification result of the sample point extracted from the corresponding year-month GLAD Global Surface Water Dynamics dataset image.

1 = not-water; 3 = water; 255 = invalid gap pixel.

GLAD_validation_results

Binary validation result indicating the matching status between GLAD dataset classification and ground truth actual_classification.

1 = correct prediction; 0 = incorrect prediction.