Vegetation
Sentinel-2 observations and NDVI, with acquisition dates, quality masks and coverage diagnostics.
Terra by HumanitasIn developmentUnderstand the land
Understand the land
behind the risk.
Explore satellite observations, vegetation trends and climate anomalies to support more informed agricultural lending assessments.
EARTH OBSERVATION & AGRICULTURETerra by Humanitas
For agricultural credit & risk analysts
A financial statement only tells part of the story.
The conditions surrounding an agricultural asset can change between reviews. Terra is being developed to bring field-level environmental observations and historical context into the questions a lending analyst already asks.
Supporting professional judgment with transparent environmental evidence.
From observation to a better question
See the signal. Understand the context.
Walk through a schematic example. Every value and parcel below is synthetic; this is an explanation of the intended experience, not a live assessment.
SCHEMATIC DEMO · SYNTHETIC DATA
Anomaly overlaySchematic land cover
Choose Compare, Interpret or Review to enable the divider. Use the arrow keys to adjust the revealed layer.
LowerSimilarVegetation difference from a synthetic baseline
Terra / Observe
Start with an area.
An area boundary defines where evidence is examined. Coverage, acquisition date and data quality matter before any signal is interpreted.
- Observed NDVI
- 0.54NDVI units
- Baseline median
- 0.67NDVI units
- Difference
- −0.13NDVI units
Method context
The real MVP uses Sentinel-2 vegetation observations and ERA5-Land climate evidence. This illustration is not connected to those data sources.
Environmental signals
Different evidence. A connected perspective.
Precipitation
ERA5-Land-derived precipitation evidence, examined over a defined target window and available historical context.
Temperature
ERA5-Land-derived temperature evidence and historical comparisons, with completeness and baseline diagnostics.
Context changes interpretation
An observation is a starting point. History gives it perspective.
The MVP compares vegetation with seasonal observations from prior calendar years and examines climate over a defined window. Available baseline years, missing observations and diagnostic limits are part of the evidence.
A historical anomaly does not, by itself, establish its cause or predict a borrower’s ability to repay.
Transparent by design
Keep the chain of evidence visible.
- Area geometry and acquisition date
- Source provenance and processing context
- Historical baselines and anomaly diagnostics
- Data completeness and quality notices
- Explainable, rule-based environmental indicators
An example credit-review workflow
Built around the analyst’s questions.
Define the review
Agree on the agricultural area, relevant period and the decision the evidence could inform.
Examine the evidence
Review vegetation and climate observations together with baseline coverage and quality diagnostics.
Investigate the context
Discuss unusual conditions with the borrower and cross-check management, crop and financial records.
Document the judgment
Record the evidence, uncertainty and follow-up questions. The lending decision remains with the institution.
Where Terra stands today
A developing product. An invitation to shape it.
The technical MVP brings together satellite vegetation observations, historical comparisons, climate evidence and geospatial analysis. The next step is to explore a focused pilot with agricultural lending professionals and assess usefulness in their workflow.
Terra by Humanitas
Discuss a pilotWhat would make environmental evidence useful in your next review?
Let’s define a small pilot around a real analytical question, an agreed area and clear evaluation criteria.