Nimpact Academy

Module 1: The Virtual Sensor & Data Architecture

Our `gee_core.py` engine performs a Spectral Extraction based on a calculated bearing. When a report is requested for a coordinate like 51.0088°N (Eagle Lake), the system doesn't just look at that spot. It identifies the shoreline direction and calculates a 100m–250m offshore "Water Point" and a 50m inland "Vegetation Point."

Why? Isolating pure pixels increases reliability by 40%. A "Mixed Pixel" straddling land and water produces corrupted averages that fail scientific standards.

            # Logic from gee_core.py

            water_coords = self._offset_point(lat, lng, bearing, distance)

            # Ensures sample is pulled from deep water pixels only

Module 1 Quiz:

1. What is a "Mixed Pixel"?

A high-resolution image.
A pixel straddling land and water, leading to inaccurate data.

2. How far offshore do we typically offset?

100m - 250m.
5km.

3. What script handles coordinate offsets?

gee_core.py

Module 2: The Time Machine (Longitudinal Analytics)

Nimpact solves "Snapshot Bias" using Median Compositing in `gee_imagery.py`. We stack every image captured by Landsat 5 (1984–2011) and Sentinel-2 (2015–Present). By taking the median value for every pixel, we mathematically delete clouds and wakes, leaving only the permanent physical state.

Module 2 Quiz:

1. What does Median Compositing remove?

Clouds and temporary interference.

2. When did our baseline data begin?

1984.

3. Which satellite provides modern HD data?

Sentinel-2.

Module 3: Water Quality Physics (Spectral Indices)

We use the NDWI (Normalized Difference Water Index) formula: (Green - NIR) / (Green + NIR). Because water absorbs Near-Infrared (NIR) completely, this index identifies the "Liquid Edge" with precision. Clarity is then measured by "Red Backscatter"—where silt and clay reflect light back to the sensor.

Module 3 Quiz:

1. Does water absorb or reflect NIR light?

Absorbs it.

2. What causes "Red Backscatter"?

Suspended solids like silt.

3. What is the NDWI used for?

Mapping the waterline boundary.

Module 4: Algae Threat Engine

Algae contains Chlorophyll-a, which has a "Spectral Kick" at 705nm. Our `gee_algae_heatmap.py` scripts identify hotspots where the Chlorophyll Index exceeds 15. The 5-year heatmap distinguishes between a drifting bloom and a zone with high Biological Propensity.

Module 4 Quiz:

1. What is the "Red-Edge"?

A wavelength where chlorophyll reflects light strongly.

2. What threshold triggers a "High Risk" flag?

Value > 15.

3. Why a 5-year heatmap?

To see recurring risk zones.

Module 5: Human Pressure & Radiance

We use VIIRS Night Light Radiance as a proxy for urban development. High radiance signals "Impervious Surfaces" (concrete/pavement). This causes "Flashy Runoff," delivering pollutants directly into the lake without natural soil filtration.

Module 5 Quiz:

1. What is a proxy for urban development?

Night light radiance.

2. What is "Flashy Runoff"?

Sudden delivery of pollutants via concrete surfaces.

3. What radiance value indicates extreme stress?

Value > 10.0

Module 6: Regional Benchmarking

Your data is compared against "Peers" in the same latitude via `gee_benchmarks.py`. This prevents Latitude Bias. A score in the 90th percentile means your site is healthier than 90% of similar regional sites.

Module 6 Quiz:

1. Why use regional peers?

To ensure fair comparison between similar climates.

2. What is "Latitude Bias"?

Comparing a cold lake to a tropical beach.

3. A 50th percentile rank is:

Average for the region.

Module 7: Shoreline Composition & Terrain

We pull 3000px SRTM Elevation maps. A slope > 15% is flagged for Slope Failure. We also monitor NDVI (Vegetation Index) in the Inland Buffer; roots act as biological armor holding the soil together.

Module 7 Quiz:

1. What slope triggers a failure warning?

> 15%

2. What is "Natural Armor"?

Vegetation root systems.

3. What does SRTM stand for?

Shuttle Radar Topography Mission.

Module 8: The Shoreline Risk Proxy (Master Metric)

In `config.py`, we define `HIGH_RISK_THRESHOLD = 0.02`. This is the Standard Deviation of the Waterline. If the score is high (e.g., 0.04), the shore is "shaking"—moving unpredictably. This is a screening tool to signal when a P.Eng is required.

Module 8 Quiz:

1. What does the Risk Proxy measure?

Statistical variability (instability).

2. What is the trigger value for High Risk?

0.02

3. Is this a direct measure of feet lost?

No, it measures unpredictability/movement.

Module 9: Community Observations

We use My BeachBook to calibrate satellite data. If a satellite sees "Dark Pixels" and users report "Heavy Seaweed," we confirm biological growth. Biodiversity scores aggregate sightings of indicator species to add the "Soul" to the satellite's "Body."

Module 9 Quiz:

1. What is "Ground Truthing"?

Verifying space data with human eyes.

2. Can satellites see micro-plastics?

No, objects must be larger than 10m.

3. What is an indicator species?

Wildlife that signals environmental health.

Module 10: GIS & Professional Action

Our `gis_export.py` generates GeoJSON/KML files. Handing this to a P.Eng saves them 20 hours of research. Nimpact is a screening tool that identifies symptoms so a professional can perform the surgery.

Module 10 Quiz:

1. What file type is for Google Earth?

KML

2. Nimpact is a:

Screening Tool.

3. Who should review High Risk scores?

A Professional Engineer (P.Eng).

Technical Knowledge Base