Vegetation Density (trees)_Alkhala

This metadata document describes the 2023 National Forest Inventory (NFI) conducted in the Al hala region to assess forest density, spatial distribution, and land cover characteristics. The dataset comprises 11 sampled polygons (out of a total 45 grid cells) classified into three density categories (Low, Medium, Dense), with associated geometric and attribute data. Key metrics include polygon area, grid classification codes, and forest density labels. The inventory aims to support sustainable forest management, carbon stock estimation, and biodiversity conservation. Data Collection Sampling Design: Systematic grid-based sampling across 45 predefined cells; only 11 polygons documented in this subset. Remote Sensing: Likely used satellite imagery (e.g., Sentinel-2, Landsat) or LiDAR for canopy cover analysis. Ground Validation: Assumed field surveys to verify remote sensing classifications (methodology unspecified).

Classification Criteria: Dense: High canopy cover/biomass (gridcode 0). Medium: Moderate canopy cover (gridcode 1). Low: Sparse canopy cover (gridcode 2).

Data Processing GIS Tools: Polygon creation and area calculation (e.g., ArcGIS, QGIS). Quality Control: Partial validation implied by "0 of 45 selected" (no polygons flagged for review).

Data and Resources

Additional Info

Field Value
Source FAO KSA
Author NCVC and FAO
Maintainer NCVC and FAO
Last Updated April 9, 2025, 17:24 (UTC)
Created April 9, 2025, 14:42 (UTC)
Areagsm Polygon area in m²
Label Density category (Low/Medium/Dense)
gridcode Density class code