Doria · Field Intelligence Module 05

Forest
Monitoring

Doria fuses five satellite datasets — Hansen Global Forest Change, the JRC Tropical Moist Forest record, Google Dynamic World, MODIS tree cover and JAXA PALSAR radar — into one canopy layer. Reserve managers see where forest is being lost, where it is quietly degrading, and where it is recovering — without waiting a year for a national inventory.

© Doria 2026 royalesirandula@gmail.com Hansen · JRC TMF · Dynamic World · MODIS · PALSAR Scroll for data ↓
Intro Loss Detection Impact Approach 05
Introduction
3.9M
hectares of African forest lost every year to clearing, fire and degradation over the last decade
1yr+
typical lag before annual national forest maps reveal where clearing actually happened on the ground
~30%
of tropical forest disturbance is degradation — canopy thinning that loss-only maps miss entirely

Forest loss rarely announces itself. A charcoal operation thins the canopy for months before a single tree "disappears" from a satellite map; a boundary farm expands one field at a time. By the time a clearing is large enough to register on an annual product — or a ground patrol happens to walk past it — the intervention window has closed and the accountability trail has gone cold.

Doria's Forest Monitoring module triangulates five independent datasets so no single blind spot hides a change. Hansen Global Forest Change and MODIS tree cover set the baseline; JAXA PALSAR radar sees through cloud and season; the JRC Tropical Moist Forest record separates outright deforestation from slow degradation; and Google Dynamic World surfaces near-real-time land-cover conversion between annual updates. Managers get canopy intelligence they can act on this month — not next year.

* Loss and degradation figures derived from Hansen/GFC v1.11, the JRC Tropical Moist Forest record, and FAO Forest Resources Assessment 2020; canopy baselines from MODIS VCF & JAXA PALSAR FNF.
• How Doria Sees the Forest

Four layers of canopy intelligence
from five satellite datasets

←
→
🌳
Multi-Dataset Canopy Baseline
Hansen Global Forest Change, MODIS percent-tree-cover, and JAXA PALSAR forest/non-forest radar are combined into a single baseline. Because radar sees through cloud and the optical layers cross-check each other, the baseline holds up in the wet season when single-sensor maps go blind.
Canopy Baseline
🪓
Deforestation vs Degradation
The JRC Tropical Moist Forest record splits disturbance into deforestation-year and degradation-year layers. Doria surfaces both — so a manager can tell outright clearing (send enforcement) apart from canopy thinning (engage the community) instead of treating every pixel the same.
Loss vs Thinning
🛰️
Near-Real-Time Change
Google Dynamic World produces 10-metre land-cover probabilities from every cloud-free Sentinel-2 pass. Doria watches the forest class between annual products — flagging conversion to bare ground or cropland within days of the overpass, not at the end of the year.
Real-Time Change
🌱
Regrowth & Restoration Tracking
Recovery is as important as loss. TMF regrowth classes and tree-cover trend let managers prove that a restored block is actually greening up over time — turning monitoring into the evidence base for restoration reporting, carbon claims, and donor accountability.
Regrowth
The Crisis

Blind to
the Loss

Swipe to explore the four blind spots →

Detection Comes Too Late
Annual maps, real-time clearing
Degradation Goes Unseen
Slow thinning below the radar
01
Annual Maps, Real-Time Loss
Most protected areas still rely on national forest inventories or annual global products that publish a year or more after the fact. By the time a clearing shows up in the data, the trees are gone, the actors have moved on, and the only option left is to document a loss rather than prevent one.
02
Degradation Is Invisible
Selective logging, charcoal production, and fuelwood harvesting thin a canopy without ever creating a clean "loss" pixel. Loss-only maps score these forests as intact — right up until they collapse — so a huge share of real ecological damage never enters the reporting at all.
03
Boundary Clearing & Charcoal
A large share of forest loss around African reserves creeps in along the boundary — farm expansion and charcoal burning that advances field by field. Without spatial attribution tied to a fixed baseline, engaging the responsible communities or holding a concession accountable is guesswork.
04
No Baseline, No Accountability
Donors, carbon buyers, and regulators increasingly demand verifiable proof of forest condition and change. A reserve with no consistent, dataset-backed baseline cannot demonstrate what it protected — or prove that a restoration project delivered — no matter how good the work on the ground actually was.
01
Annual Maps, Real-Time Loss
Most protected areas still rely on national forest inventories or annual global products that publish a year or more after the fact. By the time a clearing shows up in the data, the trees are gone, the actors have moved on, and the only option left is to document a loss rather than prevent one.
02
Degradation Is Invisible
Selective logging, charcoal production, and fuelwood harvesting thin a canopy without ever creating a clean "loss" pixel. Loss-only maps score these forests as intact — right up until they collapse — so a huge share of real ecological damage never enters the reporting at all.
↗
03
Boundary Clearing & Charcoal
A large share of forest loss around African reserves creeps in along the boundary — farm expansion and charcoal burning that advances field by field. Without spatial attribution tied to a fixed baseline, engaging the responsible communities or holding a concession accountable is guesswork.
04
No Baseline, No Accountability
Donors, carbon buyers, and regulators increasingly demand verifiable proof of forest condition and change. A reserve with no consistent, dataset-backed baseline cannot demonstrate what it protected — or prove that a restoration project delivered — no matter how good the work on the ground actually was.
How it Works

The Forest
Watch

Swipe to explore the monitoring lifecycle →

Baseline & Detection
Five datasets into one canopy layer
Verify & Report
Ground truth and restoration proof
01
Multi-Dataset Baseline
A manager selects a protected area — a custom boundary or a WDPA polygon — and Doria computes its canopy baseline across Hansen, MODIS, PALSAR and TMF. This becomes the fixed reference every future observation is measured against, on the exact tenant boundary that matters to that reserve.
02
Change Detection & Alert
Dynamic World and the TMF disturbance layers are checked against the baseline. New deforestation or degradation inside the boundary is highlighted on the map, classified as clearing or thinning, and quantified in hectares — so the response is matched to the threat rather than a raw pixel count.
03
Field Verification Tasking
Flagged change becomes a field task. Rangers navigate to the coordinates, confirm the cause on the ground, and file a geo-tagged report — closing the loop between what the satellite saw and what is actually happening, and building an evidence trail for enforcement or community engagement.
04
Trend Audit & Restoration Proof
Every observation feeds a canopy trend for the reserve. Loss is tracked over time, and regrowth in restored blocks is measured against the baseline — turning monitoring into the auditable record that donors, carbon programmes, and regulators require.
1
Multi-Dataset Baseline
A manager selects a protected area — a custom boundary or a WDPA polygon — and Doria computes its canopy baseline across Hansen, MODIS, PALSAR and TMF. This becomes the fixed reference every future observation is measured against, on the exact tenant boundary that matters to that reserve.
2
Change Detection & Alert
Dynamic World and the TMF disturbance layers are checked against the baseline. New deforestation or degradation inside the boundary is highlighted on the map, classified as clearing or thinning, and quantified in hectares — so the response is matched to the threat rather than a raw pixel count.
↗
3
Field Verification Tasking
Flagged change becomes a field task. Rangers navigate to the coordinates, confirm the cause on the ground, and file a geo-tagged report — closing the loop between what the satellite saw and what is actually happening, and building an evidence trail for enforcement or community engagement.
4
Trend Audit & Restoration Proof
Every observation feeds a canopy trend for the reserve. Loss is tracked over time, and regrowth in restored blocks is measured against the baseline — turning monitoring into the auditable record that donors, carbon programmes, and regulators require.