Transforming a 1,931-row tree inventory dataset into an interactive geospatial dashboard — mapping 36 species across 16 regions with IUCN conservation tracking, health assessments, and timber volume analytics.
The Philippines' forest management relies on tree inventory tally sheets — structured field records capturing species identification, diameter measurements, GPS locations, and stem quality assessments. These documents are critical for environmental compliance, reforestation planning, and biodiversity monitoring. But as static PDFs or spreadsheets, they're nearly impossible to analyze at scale.
This project takes a sample inventory from a 3.75-hectare site in Cainta, Rizal, expands it with synthetic data to simulate a nationwide dataset of 1,931 trees across all 16 Philippine administrative regions, and builds an interactive explorer that makes patterns visible in seconds — no Power BI or Tableau license required.
The pipeline transforms a raw PDF tally sheet into a clean, enriched, analysis-ready dataset with 25 columns — then renders it as interactive browser-based visualizations:
Of the 1,931 trees inventoried, fruit trees make up the largest category by count (580 trees, 30%). This aligns with the Philippines' strong agroforestry tradition — mango, santol, kaimito, langka, and duhat are planted extensively across both rural and urban areas for food security and shade.
However, when measured by timber volume, Premium Hardwoods dominate overwhelmingly — contributing 856 m³ (42% of total volume) from just 365 trees. Species like Narra, Apitong, Tanguile, and Molave have massive trunk diameters and tall merchantable heights, making them the most valuable trees per individual. This concentration of value in a relatively small number of premium species underscores the critical importance of protecting these — many of which are IUCN-listed as endangered or critically endangered.
Key insight: Fruit trees outnumber premium hardwoods 1.6-to-1 by count, but premium hardwoods contain 3× more timber volume. Conservation policy needs to weight by volume and ecological value, not just tree count.
Of the 1,931 trees in the inventory, 529 belong to species classified as Vulnerable, Endangered, or Critically Endangered under the IUCN Red List. That's more than one in four trees. The breakdown: 219 Vulnerable (mostly Molave, Ipil, Almaciga, and Podocarpus), 168 Endangered (Mahogany, Apitong, Kalantas), and 142 Critically Endangered (Narra, White Lauan, Tanguile).
The Critically Endangered species are the most alarming — Narra (Pterocarpus indicus), the Philippine national tree, is under severe threat from illegal logging. White Lauan and Tanguile, both dipterocarp species, have seen their populations collapse due to decades of commercial extraction with insufficient replanting.
The regional distribution reveals an uneven landscape. Eastern Visayas has the highest tree count (174 trees), followed by Ilocos Region (161) and Cagayan Valley (152). These three regions alone account for 25% of all inventoried trees.
But count doesn't tell the full story. The Ilocos Region leads in total timber volume at 210 m³ — driven by the presence of large-diameter premium hardwoods and mature plantation trees. Meanwhile, BARMM, despite having the lowest tree count (87), still contributes meaningfully through its mangrove forests and old-growth specimens.
What the map reveals: Critically Endangered species (red dots) cluster in Cagayan Valley, SOCCSKSARGEN, and Eastern Visayas — these should be priority zones for conservation. Larger dots in the Visayas indicate more mature forest stands with higher DBH.
The diameter-at-breast-height (DBH) distribution tells us about the age structure of the forest. The largest size class is 30–50 cm (474 trees, 24.5%), followed by 20–30 cm (373 trees). Together, trees under 50 cm DBH make up 64% of the inventory.
Only 132 trees (7%) exceed 100 cm DBH — these are the old-growth giants, predominantly Narra, Balete, Duhat, and Apitong. This age distribution suggests the majority of inventoried areas are second-growth forests or plantation areas, not primary old-growth stands.
The planted-vs-natural split is striking: 1,335 trees (69%) are recorded as planted, while 596 (31%) are naturally occurring. This high planted ratio reflects decades of reforestation programs — the National Greening Program, corporate tree planting, school-based initiatives, and community forestry projects.
Land use analysis shows trees are distributed across 13 different settings, from urban parks and school campuses to watershed forests and mangrove areas. The spread across land use types means this isn't just a forestry dataset — it captures the full spectrum of where trees exist in Filipino communities.
Key insight: The high planted ratio is encouraging for carbon sequestration targets, but 25% of trees show "Fair" or worse health status — suggesting that post-planting survival monitoring deserves more attention in reforestation program design.
Use the filters below to explore the dataset by region, tree category, and IUCN status. All KPIs and charts update in real time from the underlying dataset — built entirely in Chart.js with no backend or BI license required.
The dashboard synthesizes 25 columns across the following core dimensions from the expanded tree inventory:
| Dimension | Granularity | What It Reveals |
|---|---|---|
| Tree Identity | ||
| Scientific Name | 36 species | Linnaean binomial — enables IUCN status lookup and ecological classification |
| Local Name | 36 names | Filipino common name — critical for field team communication |
| Tree Category | 12 categories | Functional grouping: Premium Hardwood, Fruit, Mangrove, Ornamental, Palm, etc. |
| IUCN Status | 4 levels | Conservation threat: Least Concern → Vulnerable → Endangered → Critically Endangered |
| Measurements | ||
| DBH (cm) | Continuous | Diameter at breast height — primary metric for tree size and age estimation |
| Merchantable Height (m) | Continuous | Usable timber height — drives volume and economic value calculations |
| Total Height (m) | Continuous | Full tree height from base to crown — indicator of site quality |
| Volume (m³) | Calculated | Formula: 0.00005204 × D² × H — merchantable timber estimate |
| Basal Area (m²) | Calculated | Cross-sectional area at breast height — standard forestry density metric |
| Location & Context | ||
| Region / Province | 16 regions, 67 provinces | Philippine administrative geography — enables regional policy analysis |
| GPS Coordinates | 6 decimal places | Precise geolocation for mapping, spatial analysis, and field revisits |
| Land Use | 13 types | Urban Park, Reforestation Site, Mangrove Area, Watershed Forest, etc. |
| Health Status | 4 levels | Field assessment: Healthy, Fair, Poor, Dead/Dying |
Every tree plotted by GPS coordinates on a Philippine map, color-coded by IUCN status and sized by DBH. Enables instant visual identification of biodiversity hotspots and at-risk clusters.
Bar charts, doughnut charts, and horizontal bars covering every dimension: species, category, region, DBH class, health, volume, origin, land use, IUCN status, and stem quality.
Combine Region × Category × IUCN Status filters to drill into any subset. All 5 KPIs and 4 dashboard charts recalculate instantly — no page reload needed.
Covers premium hardwoods (Narra, Molave, Ipil), dipterocarps (Apitong, White Lauan, Tanguile), fruit trees, mangroves, conifers, ornamentals, and plantation species.
Every tree tagged with its species' IUCN Red List status, enabling instant identification of the 529 at-risk specimens (Critically Endangered + Endangered + Vulnerable).
Single HTML file with embedded CSS, JS, and data. No build step, no npm, no database, no BI subscription. Host it on any static web server for instant access.
Data foundation: The original dataset was extracted from a DENR Tree Inventory Tally Sheet — a standard form used for environmental compliance in Philippine development projects. The 343-tree original record from a GSK Compound site in Cainta, Rizal was parsed, cleaned, and then expanded with AI-generated synthetic records to simulate a nationwide inventory across all 16 administrative regions.
Enrichment layer: Each tree was tagged with IUCN Red List conservation status, a functional tree category (12 types), native/exotic classification, estimated age, canopy diameter, basal area, and contextual metadata (land use type, site condition, elevation). This transforms a basic tally sheet into a multi-dimensional analytical dataset.
Visualization engine: All charts use Chart.js rendering on HTML5 canvas. The interactive dashboard runs a client-side filter engine that recalculates KPIs and redraws all four chart panels when any filter changes. The geospatial map uses SVG with coordinate projection to plot individual trees across the Philippine archipelago.
Deployment: The entire dashboard is a single HTML file — no build tools, no frameworks, no server, no license. Upload it anywhere and it works.
The interactive dashboard transforms a paper-based tally sheet into a self-service exploration tool. Instead of scrolling through hundreds of rows in a PDF, forestry analysts can instantly answer questions about species composition, conservation risk, regional distribution, and timber value across the entire inventory.
Entire inventory in one interactive view
No Power BI, Tableau, or Looker required
Narrated insights from species to conservation
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