Sentinel-2 NDVI (Iowa Farmland, Summer 2023)

# Platform Comparison: Sentinel-2 NDVI — Gold Spec
#
# Compute NDVI from a cloud-masked Sentinel-2 summer 2023 composite
# over Iowa farmland.  Ground truth: mean NDVI ~0.73.
#
# This spec is designed to run through both the Python backend and
# browser-wasm executor (folia bench exec -b browser-wasm).

name: sentinel2-ndvi
version: "1.0"
description: >
  Compute mean NDVI from Sentinel-2 L2A Surface Reflectance over
  central Iowa farmland during summer 2023 (Jun-Aug).  Cloud-mask
  using the SCL band, create a temporal median composite, then
  compute NDVI = (B08 - B04) / (B08 + B04).
  Ground truth: ~0.73 (calibrated from GEE 2026-03-29).

settings:
  default_bbox: [-93.5, 41.5, -93.2, 41.7]
  default_crs: EPSG:4326

layers:

  # ============================================================
  # SOURCE LAYERS
  # ============================================================

  source/s2-collection:
    uri: "@sentinel-2-l2a"
    type: raster
    description: >
      Sentinel-2 L2A Surface Reflectance (Harmonized).
      Summer 2023 over central Iowa.
    params:
      bbox: [-93.5, 41.5, -93.2, 41.7]
      datetime: "2023-06-01/2023-09-01"
      assets: [B04, B08, SCL]
      query: { "eo:cloud_cover": { "lt": 20 } }

  # ============================================================
  # COMPUTE: CLOUD MASK + COMPOSITE + NDVI
  # ============================================================

  compute/cloud-masked:
    type: raster
    description: >
      Cloud-masked Sentinel-2 using SCL band.
      Keep vegetation (4), bare soil (5), water (6).
    compute:
      op: cloud_mask_sentinel2
      inputs:
        data: { layer: source/s2-collection }
      params:
        scl_classes: [4, 5, 6]

  compute/composite:
    type: raster
    description: >
      Temporal median composite of cloud-masked imagery.
    compute:
      op: temporal_reduce
      inputs:
        data: { layer: compute/cloud-masked }
      params:
        method: median

  compute/ndvi:
    type: raster
    description: >
      NDVI = (B08 - B04) / (B08 + B04).
    compute:
      op: raster_ndvi
      inputs:
        data: { layer: compute/composite }
      params:
        nir_band: B08
        red_band: B04

  # ============================================================
  # RESULT: MEAN NDVI
  # ============================================================

  result/mean-ndvi:
    type: table
    description: >
      Mean NDVI across the Iowa farmland AOI.
      Ground truth: ~0.73.
    compute:
      op: analysis_zonal_stats
      params:
        stats: [mean]
      inputs:
        raster: { layer: compute/ndvi }