GENERAL INFORMATION

1. Title of Dataset: Validation dataset supporting “Extending a Scalable Satellite-Based Vegetation Edge Detection Framework to Diverse Tropical Coasts”

2. Author Information
	A. Principal Investigator Contact Information
		Name: Idham Nugraha
		Institution: University of Glasgow
		Address: School of Geographical and Earth Sciences, University Avenue, Glasgow, G12 8QQ
		Email: i.nugraha.1@research.gla.ac.uk

	B. Associate or Co-investigator Contact Information
		Name: Larissa Naylor
		Institution: University of Glasgow
		Address: School of Geographical and Earth Sciences, University Avenue, Glasgow, G12 8QQ
		Email: Larissa.Naylor@glasgow.ac.uk


		Name: Martin Hurst
		Institution: University of Glasgow
		Address: School of Geographical and Earth Sciences, University Avenue, Glasgow, G12 8QQ
		Email: Martin.Hurst@glasgow.ac.uk


3. Date of data collection (range): 
2024-01-01 to 2024-06-30 (satellite image)
April-Ma 2024 (field survey)

4. Geographic location of data collection: 
Coastal area of Dumai and Padang in Sumatra Island, Indonesia.

5. Information about funding sources that supported the collection of the data: 
This research was funded by an award from the Indonesia Endowment Fund for Education (LPDP) under award number: SKPB-1550/LPDP/LPDP.3/2025, granted to Idham Nugraha


SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: 
This dataset is made available for research and educational purposes. Users are requested to cite the associated publication when using the data.

2. Links to publications that cite or use the data: Nugraha, I., Naylor, L., & Hurst, M. (2026). Extending a Scalable Satellite-Based Vegetation Edge Detection Framework to Diverse Tropical Coasts. Frontiers in Marine Science (in production).

3. Links to other publicly accessible locations of the data: 
N/A

4. Links/relationships to ancillary data sets:
Raw Sentinel-2 imagery is publicly available via the ESA Copernicus Open Access Hub and is not included in this dataset.

5. Was data derived from another source? 
yes
    5A. If yes, list source(s): Satellite imagery: Sentinel-2 (ESA Copernicus Programme)
High-resolution imagery: PlanetScope (for validation digitisation)
Field data: GNSS survey conducted using Arrow GPS receiver (April–May 2024)n


DATA & FILE OVERVIEW

1. File List: 
Nugraha_2026_VedgeSat_Validation_Dataset.zip
Contains all processed validation data supporting the associated publication.
The ZIP file includes:
	Extracted_VE/
	Final vegetation edge shapefiles extracted using the VedgeSat toolkit.

	Validation_line/
	Manually digitised reference lines and GNSS ground-truth validation lines.

	VedgeSat_Validation_Results_Summary.xlsx
	Summary accuracy metrics including RMSE, R², and MPE.

	VedgeSat_Tuning_Results_Summary.xlsx
	NDVI threshold sensitivity analysis results.

	README.txt
	Metadata and documentation describing the dataset contents and methodology.

2. Relationship between files, if important: 
Shapefiles contained within the ZIP archive consist of standard ESRI components (.shp, .shx, .dbf, .prj, .cpg) and must be kept together to ensure proper functionality within GIS software.

3. Additional related data collected that was not included in the current data package: 
Raw Sentinel-2 imagery is publicly available via the ESA Copernicus Open Access Hub and is therefore not included.

4. Are there multiple versions of the dataset? 
no


METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: 
Vegetation edges were extracted from Sentinel-2 satellite imagery using the VedgeSat toolkit, a Python-based automated vegetation edge detection framework. The vegetation edge represents the seaward stable boundary of coastal vegetation.

Validation lines were generated using two approaches:
	(i) Manual digitisation of high-resolution PlanetScope imagery within a GIS environment, and
	(ii) Ground-based GNSS surveys conducted during April–May 2024 using an Arrow GNSS receiver to record the seaward vegetation edge as line features.

2. Methods for processing the data: 
Data processing and validation analyses were conducted using GIS software (ArcGIS Pro) and Python-based workflows associated with the VedgeSat toolkit.

3. Instrument- or software-specific information needed to interpret the data: 
Any Geographical Information System which can read shapefiles (ESRI ArcMap, ESRI ArcGIS Pro, QGIS)

4. Standards and calibration information, if appropriate: 
N/A

5. Environmental/experimental conditions: 
N/A

6. Describe any quality-assurance procedures performed on the data: 
Manual validation lines were cross-checked against multiple image dates to minimise interpretation error. 
GNSS-derived validation lines were visually inspected and compared with satellite imagery to ensure positional consistency.

7. People involved with sample collection, processing, analysis and/or submission: 

Ilham Setiyadi, Aslam Fuadi, M. Faisal Karim, and Owen Syah from Universitas Islam Riau, Indonesia. The Search and Rescue Team from Badan Penanggulangan Bencana Daerah (BPBD) Kota Dumai.