Interactive Web GIS & Agricultural Analytics with the Rwapor Shiny Dashboard • Rwapor

Introduction

The Rwapor package includes a full-featured, reactive Shiny Web GIS dashboard designed for point-and-click satellite data retrieval, FAO-56 crop water productivity modeling, seasonal comparisons, and high-throughput farm monitoring.

1. Launching the Dashboard

Launch the dashboard directly from your R console:

library(Rwapor)

# Launch default dashboard
run_wapor()

# Or specify a custom data directory
run_wapor(data_folder = "C:/WaPOR_Projects")

The application automatically opens in your default web browser.

2. Dashboard Architecture & Modules

┌────────────────────────────────────────────────────────────────────────┐
│                        Rwapor Shiny Dashboard                          │
├──────────────┬──────────────┬──────────────────────────┬───────────────┤
│ 📥 Download  │ 🌾 Seasonal  │ 📊 Visualisation         │ 🛰️ Field     │
│  & Extraction│   Analysis   │  & Time Series Analysis  │   Monitoring  │
└──────────────┴──────────────┴──────────────────────────┴───────────────┘

3. Module Walkthroughs

📥 3.1 Download & Spatial Extraction Tab

Project Folder: Select or browse for your project workspace. All downloaded rasters and metadata are organized hierarchically by variable and period.
Interactive Area of Interest (AOI):
- Draw on Map: Draw rectangles or arbitrary polygons directly on the Leaflet map.
- Upload Spatial File: Ingest Shapefiles (.shp in .zip), GeoJSON, KML, GeoPackage (.gpkg), or GeoTIFF templates.
- Smart L3 Region Auto-Detection: When Level 3 variables are selected, the app intersects your AOI geometry with all 30+ sub-national WaPOR Level 3 irrigation schemes in Africa and the Near East, filtering and auto-selecting the appropriate scheme.
Variable Selection & Date Ranges:
- Choose from 100+ WaPOR v3 and AgERA5 variables across Level 1 (~300m), Level 2 (~100m), and Level 3 (~20m).
- Set custom start and end dates.
Execution:
- Stream raster data directly into local GeoTIFFs or extract polygon zonal time series in parallel.

🌾 3.2 Seasonal Analysis & Crop Water Productivity Hub

The Seasonal Analysis module provides a structured 4-step wizard for configuring, parameterizing, and computing agricultural water performance metrics:

Step 1: Seasonal Calendar & Batch Mode:
- Single Season vs. Batch Mode: Toggle between single-season dates or a multi-season schedule (Label, Start, End).
- Smart Folder Detection (Detect): Auto-scans downloaded dekadal rasters in your project directory to deduce available time ranges.
- Download Sync (Copy DL): Instantly imports the temporal periods configured in the Download tab.
- Interactive Batch Guide ([?] Batch Guide): Built-in modal explaining batch syntax, directory layouts, and auto-linking naming conventions.
Step 2: Spatial Masks & Timing:
- Crop Masking: Support for single-crop AOIs or multi-crop categorical masks (1 = Wheat, 2 = Maize, etc.).
- Phenological Timing (SOS/EOS): Supply pixel-wise Day of Year (DOY) planting and harvesting rasters. Cross-year seasons ( $\text{EOS} < \text{SOS}$ ) are automatically shifted by 365/366 days.
- Custom Vector & CSV Generation: Collapsible panel to build all required seasonal rasters from parcel polygons (.geojson/.shp) and survey planting spreadsheets (.csv) via wapor_vector_to_season_rasters().
- Latitude-Aware Area Weighting: Exact ellipsoidal pixel surface area weighting (cos(lat)) for distortion-free volumetric aggregations.
Step 3: Crop Parameterization:
- FAO-56 Presets: Choose from 12 pre-configured crops (Winter Wheat, Sorghum, Sugarbeet, Maize, Rice, Cotton, Potato, Soybean, Sunflower, Barley, Alfalfa, Sugarcane).
- Multi-Crop Table Editor: Customize crop coefficients ( $K_{c,\text{ini}}, K_{c,\text{mid}}, K_{c,\text{end}}$ ), stage lengths, Harvest Index ( $HI$ ), and Moisture Content ( $MC$ ) per crop class.
Step 4: Thematic Indicator Selection: Indicators are organized into four logical thematic fieldsets with quick-select controls ([Core], [All], [Clear]):
- Evapotranspiration & Consumptive Use: Seasonal $AETI$ , Reference $RET$ , Transpiration $T$ , and Crop Evapotranspiration ( $ET_c$ , including class-level rasters).
- Agricultural Water Adequacy: Water Adequacy vs. RET ( $AETI/RET$ ), Adequacy vs. ETc ( $AETI/ET_c$ ), and Relative Water Deficit ( $1 - AETI/ET_c$ ).
- Water Accounting & Precipitation: Seasonal Precipitation ( $PCP$ ), Effective Precipitation ( $P_{eff}$ via USDA SCS or FAO methods), and Net Irrigation Requirement ( $NIR = \max(0, ET_c - P_{eff})$ ).
- Biomass Productivity & Uniformity: Seasonal $NPP$ , Crop Water Productivity ( $CWP$ ), Biomass Water Productivity ( $BWP$ ), Beneficial Transpiration Fraction ( $T/AETI$ ), and Uniformity ( $CV$ , Theil Disparity Index).
- Dynamic L3 Coverage Policy: Conditionally rendered only when sub-national Level 3 datasets are selected.
Execution & Export:
- Real-time progress bar tracking multi-season execution.
- Unified summary metrics table and one-click export of GeoTIFF rasters and CSV tables.

[!TIP] For advanced scripting and multi-crop batch workflows, see the dedicated Batch Seasonal Analysis Tutorial.

📊 3.3 Visualisation & Time Series Hub

The unified Visualisation tab combines spatial raster exploration, side-by-side comparison, and field-level time series diagnostics:

Single Map Visualizer: Interactive Leaflet map with real-time cursor hover values, coordinate readouts, and perceptually uniform color palettes (Viridis, Turbo, Spectral, Plasma).
Dual Map Split-Screen Swipe Slider: Compare two rasters side-by-side (e.g. $AETI$ vs. $ET_c$ , or 2021 vs. 2022) with a draggable swipe bar to pinpoint localized water stress hotspots.
Zonal Time Series & Phenology: Extract and plot multi-field time series trajectories, compute running means, and decompose seasonal cycles using interactive Plotly graphics.
Seasonal Comparison & Anomaly Distribution: Multi-year violin and box plots comparing water productivity across cropping seasons and field parcels.

🛰️ 3.4 High-Throughput Field Monitoring (DuckDB)

Parcels Ingestion: Import agricultural field polygons and crop rotation records.
Embedded DuckDB Engine: Synchronize WaPOR satellite data with a local embedded analytical database.
Field Diagnostics: Run interactive SQL queries, temporal water stress anomaly checks, and border pixel filtering to ensure pure crop canopy signals.