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Defence and Space

Airbus Logo

Defence and Space

Airbus Logo

Defence and Space

Amazon Rainforest, Maraã, Satellite Imagery

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Amazon Rainforest, Maraã, Satellite Imagery thumbnail

Sensor

SPOT

Resolution

1.5m

Location

Maraã, Amazonas, Brazil

Copyright

© Airbus DS 2023

Date

22 September, 2023

Image type

Optical

This image of the Amazon Rainforest in Maraã, Brazil was captured by the Airbus SPOT satellite on 09/22/2023. 

The municipality of Maraã is located deep in the Amazon jungle in the Brazilian state of Amazonas. Maraã spans an area of 16,910 km² and is part of the Brazilian microregion Japurá. 

The Amazon jungle is one of the world’s most important ecological resources. It is home to approximately 10% of known wildlife species and stores an estimated 150 to 200 billion tons of carbon. In this image of Maraã, the viewer can see the denseness of the Amazonian jungle alongside deforested areas with less thick vegetation. 

Tributaries of the Japurá River can be seen crossing the bottom, middle, right, and top of the image. In the very centre of the image, there are two large horseshoe-shaped offshoots of the Japurá which connect via thin streams to the tributaries. Also known as the Caquetá River, the Japurá River stretches for 2,820 kilometres throughout the Amazon basin. 

Zooming in on the image allows the viewer to closely study the routes of the Japurá River through the forest. The banks of the river are visible and provide a contrast to the vivid green of the forest. No man-made structures are easily definable, but the image has captured some sparse cloud cover and the resulting shadows on the forest. 

SPOT provides provide a comprehensive overview of large areas, the perfect complement to detailed imagery captured by Pléiades Neo (30cm resolution) and Pléiades (50cm resolution) products.

With its 60km swath, SPOT can cover three million km² per day with daily revisits making it ideal for country-wide, demanding applications. SPOT’s 1.5m resolution and remarkable swath acquisition products are ideal for applications such as national mapping and forestry monitoring.