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Forestry monitoring software powered by satellite data analytics

Gain full control over your stands by using EOSDA LandViewer to detect deforestation early, track canopy conditions, ensure EUDR compliance, and manage resources efficiently

Access optical multispectral satellite images of forests, stereo (3D) views, and SAR data data
Browse satellite imagery archive dating back to 1982 with complete global coverage
Choose from over 20 pre-set forestry-focused indices or create your own custom band combinations

Start forest monitoring

What you can do with EOSDA LandViewer

Detection of Deforestation and Illegal Logging

EOSDA LandViewer software uses optical satellite imagery from Sentinel-2, Landsat, and other sources, combined with pixel-based change detection, to identify areas of canopy loss. Applying the NDVI index or specialized forest coverage bands supports precise forest cover monitoring, enabling the detection of zones affected by illegal logging or deforestation.

Deforestation detected in Chaco, Bolivia

Forest Fire Detection and Burned Area Assessment

EOSDA LandViewer helps map fire damage by calculating NBR to pinpoint burned areas and assess fire severity. With Change Detection feature, users can quickly compare forest satellite images from before and after the fire. Tracking NDVI change with Time-series analysis reveals how the landscape is recovering, offering valuable insights for creating severity maps and guiding response efforts.

Forest burned area detected in Evros, Greece

Forest Health Monitoring

EOSDA LandViewer provides in-browser Time-series analysis and vegetation stress mapping using NDVI, EVI, SAVI, and other indices. The Clustering tool allows for grouping areas based on shared characteristics, making it easier to analyze canopy condition and detect patterns in plant health.

Amazon forest satellite view on NDVI map

Analyze forest stands

How to analyze forest satellite images on EOSDA LandViewer

1. Set your AOI (area of interest)

Define the area you want to monitor by using the location search, drawing it on the map, or uploading it from your device.

2. Use filters to search for and choose the scene you need

Filter scenes by acquisition date, cloud cover, sensor type, and the extent of AOI coverage to quickly identify relevant options. Once filtered, review the results and select the scene that best meets the requirements of your analysis.

3. Apply indices or band combinations

Use vegetation indices or custom band combinations on your selected scene to detect deforestation, assess stand health, and identify signs of illegal logging or wildfire damage. EOSDA LandViewer provides a variety of forestry-specific indices and presets to help you perform precise, AOI-focused analysis.

4. Use advanced analytical tools

Use advanced analytical tools like Time Series Analysis, Clustering, and Change Detection to reveal vegetation patterns, group similar areas, and detect significant changes over time. This information helps you monitor stands dynamics, identify illegal logging, and assess post-fire recovery for effective management.

Choosing a scene in forestry mapping software

Time series analysis in forestry software

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Analytical tools

Indices and Band Combinations

Instantly visualize stress zones, detect deforestation, monitor wildfire damage, and evaluate forest health by using advanced indices in forest monitoring software, among which are:

NDVI: a versatile index for detecting deforestation, burned zones, and vegetation degradation.
NBR: used to identify burned areas after fires.
Fire Detection Index: effective for spotting active fires, best applied with change detection.
Deforestation Index: highlights recent deforestation by comparing current images to the last cloud-free reference.
EVI: ideal for assessing dense forest vegetation and overall health.
SAVI: effective for monitoring young or newly planted forests.

index applied to a forest satellite image

Change Detection

Change Detection tool on EOSDA LandViewer makes it easy to track forest disturbances over time by comparing satellite images of forests from different dates. Within a few clicks you can pinpoint areas affected by deforestation, wildfires, or illegal logging. The tool automatically highlights changes in vegetation, helping forestry experts monitor risks, evaluate damage, and take swift, informed action.

Time Series Analysis

Time Series Analysis helps uncover how forests change over time by tracking vegetation patterns across a series of satellite images. It reveals trends like deforestation, seasonal cycles, and ecosystem decline, while also identifying early stress signals or signs of recovery after wildfires. This insight supports smarter decision-making in forest management and conservation.

changes uncovered with forest satellite imagery

Clusterization

Clusterization uses satellite imagery to divide forests into zones with similar features, such as vegetation type, health, or disturbance intensity. This technique helps identify patterns like degraded areas or changes in forest composition, supporting more focused actions and efficient resource planning.