Mapping & Monitoring

Pan-tropical Forest Cover Mapped with Cloud-Free Radar Imaging

Tropical deforestation and forest degradation account for an estimated 20% of the world's anthropogenic emissions of carbon dioxide, a significant greenhouse gas contributor. Despite the important services that tropical forests provide, there is incomplete data and knowledge of their condition and coverage, and thus no accurate baseline for evaluating and monitoring future changes. As international initiatives develop under the UNFCCC to provide a policy mechanism for slowing tropical deforestation, a baseline for evaluating and monitoring forest cover and associated biomass changes needs to be established across the forested tropics of Central Africa, Latin America and Southeast Asia.

The Woods Hole Research Center has initiated a three-year project focused on pan-tropical mapping of forest cover and associated carbon stocks stored in above-ground biomass. The project encompasses two approaches (See sidebar for link to MODIS approach as well as capacity building component.) The approach detailed below focuses on the production of a pan-tropical database of high-resolution ALOS/PALSAR data and their use for pan-tropical forest cover mapping as baseline data for subsequent deforestation and forest degradation monitoring.

Radar images from the Japanese ALOS satellite-borne PALSAR sensor are collected since its successful launch by the Japan Aerospace Exploration Agency (JAXA) in 2006. The sensor is cloud penetrating due to the use of long wavelength (23 cm, L-Band) for imaging of Earth's surfaces. As part of a systematic observation strategy for global mapping, cloud-free, pan-tropical datasets of PALSAR radar data are now acquired within a couple of months every year. The first near-complete collection of pan-tropical data in a dual-polarimetric mode, which proves very useful for forest mapping, was achieved in June-September 2007, with some minor acquisition gaps filled during 2008 and 2009 observations cycles.

Click here to load Google Earth Pan-Tropical KMZ File. For ALOS data to appear, some zooming in may be necessary.

With the map below, you can view pan-tropical, cloud-free ALOS radar data within the Google Earth Plugin. (Some browsers are not compatible with the plug-in yet.)

Image Data © by JAXA/METI, Image Processing by WHRC/ASF

(Data delivery and mosaic production is ongoing.)

Image Data © by JAXA/METI, Image Processing by WHRC/ASF


South America



How is the Image Mosaic generated?

The image mosaics are based on a false-color combination of the L-Band radar backscatter values using two distinct information channels: a) Image data derived from microwave energy that was both transmitted and received by the sensors radar antenna in the horizontal direction, i.e. parallel to Earth’s surface, and b) image data derived from microwave energy transmitted in the horizontal direction, but received in the vertical direction. The former case is referred to as HH-polarization while the latter case is HV-polarization.

In the image mosaics, the HH information channel was assigned to red, HV was assigned to green, and the ratio between the two (HH/HV) was assigned to blue. With the applied color assignment, green and yellow tones correspond to instances where both HH and HV information channels have high energy returns, e.g., over forested and urban areas. Blue and magenta colors are generally found in non-forested areas, where the HH polarized energy often exhibits a higher return from the surface than the HV polarized energy.

Ca. 16,000 image frames (coverage 70x70 km per frame) were radiometrically adjusted (radar speckle filtering, terrain illumination correction) and orthorectified with digital elevation models from the Shuttle Radar Topography Mission. The geocoded frames where then assembled to image mosaic tiles in resolutions of 15 m, 50 m, and 100 m.

ALOS Based Pan-Tropical Forest-Cover

Work is ongoing to classify the pan-tropical ALOS image mosaic data into forest cover information. In a first, simple step, orthorectified image mosaic data were classified unsupervised to clusters for assignment to various forest types. At this stage of the analysis, the clusters were coded to distinguish dense forest (light green colors), open forest (greenish-brown), sparse vegetation (brown), non-vegetated surfaces (blue/black and dark magenta), and flooded forests (greenish/yellow). More sophisticated supervised classification algorithms with the use of training data are currently developed.

Image Data © by JAXA/METI, Image Processing by WHRC/ASF

South America





For further information on the ALOS/PALSAR mission:

JAXA’s website on ALOS

Kellndorfer et al., WHRC COP13 Bali report on ALOS/PALSAR

This work contributes to the Group on earth Observation Forest Carbon Tracking Task ( and JAXA’s Kyoto and Carbon Initiative (

Funding and support:

Gordon and Betty Moore Foundation,, the David & Lucile Packard Foundation, and NASA.

Key Project Partners:

Japan Aerospace Exploration Agency (JAXA), JAXA Kyoto and Carbon Inititiative, Alaska Satellite Facility (ASF), NASA, SARMAP, Boston University.

Pantropical Mapping Initiative

MODIS Mapping
Pantropical Capacity Building