Joint Submission to the First Global Stocktake
A satellite-based deforestation monitoring system for tropical forests,“JICA-JAXA Forest Early Warning System in the Tropics (JJ-FAST)”The Japan Aerospace Exploration Agency (JAXA), Japan International Cooperation Agency (JICA),
Institute for Global Environmental Strategies (IGES) and Brazilian Institute of Environment andRenewable Natural Resources (IBAMA) are pleased to submit this paper to the Global Stocktake of theParis Agreement in response to the mandate of Decision 19/CMA.1, paragraph 19, 36 and 37. Thissubmission provides information to a crosscutting guiding question 23 1.
Summary

A satellite-based deforestation monitoring system has been developed through enhanced
international cooperation among JICA, JAXA, and countries with tropical forests: the JICA-JAXA
Forest Early Warning System in the Tropics (JJ-FAST). This system can help countries to locate
illegal deforestation, so that it can be combatted more efficiently. Reduced deforestation contributes
to reduction of greenhouse gas emissions.



JJ-FAST uses PALSAR-2, a synthetic aperture radar onboard JAXA’s ALOS-2 satellite, to provide
periodic deforestation information even for frequently cloud-covered areas and during the rainyseason.



JJ-FAST has detected about 3 million potential deforested plots in 78 tropical-forest countries
between 2016 and 2021 (Figure 1), including more than 1 million deforested plots in Brazil.
IBAMA uses JJ-FAST and other optical satellite systems to monitor and control illegal
deforestation throughout the year, including rainy and cloudy periods. Practices of JJ-FAST
application in Brazil should provide useful information on how tropical countries can enhance
climate action by using JJ-FAST to detect and control illegal deforestation.



To promote JJ-FAST to combat illegal deforestation, JICA and JAXA provide technical training toa number of countries and held an international conference in Tokyo and regional/country seminars
in seven countries.

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What are good practices, experience and potential opportunities to enhance climate action, including international

cooperation, on mitigation and adaptation and to increase support under Article 13.5 of the Paris Agreement(para36(g)? Which of these can be transferable or replicated by others? How effective was sharing good practices
and experiences on climate action and support, including on enhancing the implementation of adaptation action(Article 7.14(b))?

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Figure 1. Number of deforested plots detected by JJ-FAST per country (as of November 2021).
Table 1. Key points about the JJ-FAST system.
System name

JICA-JAXA Forest Early Warning System in the Tropics (JJ-FAST)

Objectives

To provide information for detecting deforestation in the tropics to combat illegal
activities and promote sustainable forest management

PeriodSince November 2016 (still in operation)

Data

Synthetic Aperture Radar PALSAR-2 onboard ALOS-2 (resolution: 50m)

TargetDeforested areas of more than 2 ha (at present) in 78 tropical countries

Frequency

Every 1.5 months

Features

Reliable monitoring not affected by cloud cover

Results

Provided information on about 3 million deforested areas in 5.5 years

1. Method
1.1 Overview
JJ-FAST is a system that can detect deforestation of areas of more than two hectares in tropical forests.
It relies on PALSAR-2, a synthetic aperture radar mounted on JAXA’s ALOS-2 satellite, to provide
deforestation information. JJ-FAST aims to make the information available to the public every 1.5
months. It is expected that the system will be utilized for forest monitoring by countries with tropicalforests and will act as a deterrent against illegal deforestation. Governmental forest administrators are
the primary target users. Since this system provides data on deforested areas that can be downloaded asa polygon shapefile, criminal activity can be identified by GIS analysis of superimposed land-use andconcession maps available to users. Optical sensors cannot observe cloud-covered areas effectively, but
the microwave sensors of the PALSAR-2 can acquire images of the ground surface through clouds,
allowing deforestation information to be transmitted regularly for all regions.
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1.2 Data used
The ALOS/2/PALSAR-2 used for JJ-FAST is the successor to the ALOS/PALSAR (2006–2011) sensor
and has been operated by JAXA since 2014. PALSAR-2 is a synthetic aperture radar that transmits andreceives microwaves reflected from the ground to acquire forest information. The microwave band waschosen because these wavelengths are less affected by clouds and rain than visible light. This all-weather
observing capability is suitable for monitoring forest cover without clouds also. PALSAR-2 has threeobservation modes (Figure 2), of which JJ-FAST uses the ScanSAR mode for wide-area observations.
The observation swath is 350 km wide and has a resolution of 50 m. It observes the targeted tropicalregions nine times a year.

Figure 2. PALSAR-2 observation mode.
The target regions of JJ-FAST are 78 countries shown in Table 2, covering almost all the tropical forests
globally.
Table 2. Seventy-eight countries covered by JJ-FAST.
Area
Latin
America

AfricaCountrySouth America

Bolivia, Brazil, Colombia, Ecuador, Guyana, Paraguay, Peru,
Suriname, and Venezuela

Central America
and the Caribbean

Belize, Costa Rica, El Salvador, Guatemala, Honduras, Mexico,
Nicaragua, Panama, and Trinidad and Tobago

West Africa

Benin, Burkina Faso, Cote d’Ivoire, Ghana, Guinea, GuineaBissau, Liberia, Mali, Nigeria, Senegal, Sierra Leone, and Togo

East Africa

Burundi, Djibouti, Ethiopia, Kenya, Madagascar, Rwanda,
Seychelles, Somalia, Sudan, South Sudan, Tanzania, and Uganda

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Central Africa

Cameroon, Central African Republic, Chad, Republic of Congo,
Democratic Republic of Congo, Equatorial Guinea, Gabon, and
Sao Tome and Principe

South Africa

Angola, Botswana, Eswatini, Lesotho, Malawi, Mauritius,
Mozambique, Namibia, Republic of South Africa, Zambia, andZimbabwe

Asia

Bangladesh, Bhutan, Brunei, Cambodia, India, Indonesia, Laos,
Malaysia, Myanmar, Nepal, Philippines, Sri Lanka, Thailand,
Timor-Leste, and Viet Nam

Oceania

Papua New Guinea, and Solomon Islands

1.3 Algorithm
Six versions of the detection algorithm have been developed (Table 3). Because the PALSAR-2 image
can distinguish between forest and non-forest cover, deforested areas can be detected by image analysis(Figure 3). Versions 0.0 and 1.0 detected changes in images between only two time periods. As
mentioned above, the resolution of the PALSAR-2 image is 50 m, but the PALSAR-2 image contains
noise called speckle, so it cannot detect changes of a size near the sensor resolution. Therefore, theseearly algorithms could detect deforestation of areas of 5 hectares or more. Since then, the JJ-FAST
development team has improved the algorithms to use multiple polarimetric images provided by
PLASRA-2 and time-series images of up to 21 time periods instead of just two. This now allows us todetect deforestation areas as small as 2 hectares.
In addition, satellite image-based deforestation information usually contains errors. Therefore, the JJFAST development team compares and interprets the automatically processed information with opticalsatellite images and releases information that is recognized as valid. This is called the Quality Check
product. However, there were requests to release the information after automatic processing without thequality check, so from Ver. 2.1, the team has also released a Quick Look product to share the automatic
processing results as quickly as possible.
Table 3. Revision history of the deforestation detection algorithm.
Version

PeriodAlgorithm

0.0

2016.11–2017.07

Changed detection between two images of PALSAR-2 HV

1.0

2017.07–2018.04

Changed detection between two images of PALSAR-2 HV

2.0

2018.04–2018.07

Analysis using a reference from ten scenes of PALSAR-2
HV, HH2018.07–2019.06

Analysis using a reference from 15 scenes of PALSAR-2
HV, HH

2.1

2019.07–2020.05

Analysis using a reference from 20 scenes of PALSAR-2
HV, HH with updated thresholds

3.0

2020.06–

Data processing changed from polygon- to pixel-based.
Applied temporal normalization and introduced thresholdlevel depending on the site
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Figure 3. PALSAR-2 image changes between two periods in a deforested plot.
1.4 Webpage
JJ-FAST

deforestation

informationisavailabletothepublicthrough

a

web

page

(https://www.eorc.jaxa.jp/jjfast/jj_index.html). As shown in Figure 4(a), the top page of JJ-FAST has
drop-down menus. When the Map menu is selected, the distribution of deforestation is shown in a 1°
grid of latitude and longitude (Figure 4(b)). By clicking on the grid, the user can display an enlarged
map and its deforestation information (Figure 4(c)). Users can download the data as a polygon shapefile
to their forest management system for analysis.
(a)

(b)

Figure 3. JJ-FAST web page (continued on next page).

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(c)

(d)

Figure 3. JJ-FAST web page (continued).
1.5 User promotion
JICA and JAXA conducted field surveys in seven countries to validate JJ-FAST’s accuracy and improve
the algorithm (Table 4). In five of these countries, they also held seminars for government officials andother stakeholders. Surveys with local forestry officials and discussions at seminars have promoted JJFAST use. In response to requests from users, the algorithm has been improved to detect deforestationin smaller areas. Further, JICA and JAXA held an international conference on JJ-FAST in Tokyo in 2017,inviting government officials from many developing countries and other international and domestic
stakeholders. In addition to a series of seminars held in developing countries, they have conductedtraining courses in Japan and online (due to COVID-19 restrictions) since 2016. The purpose of the
training course is to promote sustainable forest management using remote sensing/GIS technologies,
including JJ-FAST; 47 government officials from 17 countries have participated so far.
Table 4. JJ-FAST field surveys and regional seminars.
RegionSouth America

AfricaAsia

CountryYear

SurveySeminar

Peru

2016

✓

✓

Brazil2017✓

Botswana

2017

✓

✓

Gabon

2017

✓

✓

Mozambique

2018

✓

Cameroon

2019

✓

✓

Indonesia

2018

✓

✓

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2. Results
2.1 Provision of deforestation information
JJ-FAST has detected many deforested areas in the tropics since the start of operation in November 2016.
Figure 4 shows the number of deforested areas for each PALSAR-2 observation cycle (14 days). When
JJ-FAST started its operation, it released deforestation information for six months, so the information isavailable sincethe 48th cycle in May 2016. Then, starting from the 130th cycle (July 2019), the Quick
Look product (i.e., the automatic processing results) has been released, and the number of detected
deforested areas has rapidly increased. In total, the Quick Look and Quality Check products havereleased information on 2,893,049 deforested plots by November 2021.

Accumulated number of
deforestations

3,000,000
2,500,000
2,000,000
1,500,000
1,000,000

Quick Look
Product
release500,000
0

Algorithm
ver.3.0
release

48

77

99

113

128

142

156

171

185

Observation cycle

Figure 4. The accumulated number of deforested plots detected by JJ-FAST (including Quick Look
and Quality Check products by November 2021).
Examining the results for each country, many deforestations were detected in Brazil, Indonesia, andBolivia (Figures 1 and 5), with these three countries alone accounting for more than half (55%) of thetotal.
Number of plots0

200,000

400,000

Brazil

800,000 1,000,000
1,022,887

Indonesia

316,967

Bolivia
Democratic Republic of Congo

600,000

245,104
171,009

Venezuela

77,079Laos63,456

Colombia

58,341

Mozambique

54,573Mexico52,746

Angola52,264

Figure 5. Top 10 countries with the most deforestation detected by JJ-FAST (as of November 2021).
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2.2 Application in Brazil
Brazilian authorities use JJ-FAST to monitor deforestation and control illegal deforestation in rainy andcloudy periods.
Their control of illegal deforestation starts with detecting deforestation by the National Institute forSpace Research (INPE) using multiple optical satellites under the Near Real-Time Deforestation
Detection System (DETER). Because detecting deforestation optically during the rainy season presents
technical difficulties, the Brazilian government uses multiple deforestation early warning systems(EWSs) to solve technical issues such as cloud effects and interrupted satellite observation intervals to
make constant deforestation detection possible throughout the year. Suspected deforestation data (forwhich illegality is unknown at this stage) are sent from INPE to the Brazilian Institute of Environment
and Renewable Natural Resources (IBAMA), the regulatory agency dealing with illegal deforestation.
IBAMA and its branches then compare deforestation data from DETER, JJ-FAST, and other EWS data
against satellite imagery, a database of legal land use, and additional sources. When there is a highprobability of illegal deforestation, the authority moves to law enforcement, sometimes with the supportof the federal police and other institutions.
Figure 6 compares the deforested areas detected in the Brazilian Legal Amazon 2 in 2019 by JJ-FAST
and the Global Land Analysis and Discovery (GLAD), a global deforestation monitoring system using
optical satellite Landsat imaging 3 . GLAD detects more deforestation than JJ-FAST from April to
October, when there is less cloud cover due to the GLAD’s resolution to detect deforested areas of 0.1
ha or more, surpassing JJ-FAST (2 ha). Meanwhile, from November to March, the area detected by JJFAST is more significant than by GLAD. This period is the rainy season, indicating that radar sensors
are more effective in detecting deforestation than optical sensors, which are vulnerable to cloud cover.
In addition, IBAMA's fieldwork with JJ-FAST information has found that JJ-FAST can detect earlystage deforestation. These features have allowed JJ-FAST to be used in IBAMA’s monitoring operations
extensively.
Thus, in Brazil, forest conservation efforts are made possible by the integrated use of information fromseveral EWSs and land-use planning, the governance system to dispatch enforcement officials to areas
where there is a high possibility of illegal deforestation and to allow them to enforce the law, andcollaborative work among multiple agencies.

2

the largest socio-geographic division designated by the Brazilian government

3

covering the entire tropical region, operated by the University of Maryland with support from

Global Forest Watch8

3,000JJ-FAST
GLAD

Deforestation area (km2)

2,500
2,000
1,500
1,000
500
0

Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.

Figure 6. Monthly deforestation area comparison between JJ-FAST and GLAD in the Brazilian Legal
Amazon 4.
2.3 Potential use in tropical countries
As summarized in Table 2, JJ-FAST covers almost all tropical forests in the world; thus, tropicalcountries can benefit from using JJ-FAST to detect and control illegal deforestation. There are somedesirable technical conditions to optimize the use of JJ-FAST:
1. An environment where data from multiple EWSs, including JJ-FAST, can be obtained and integrated
to identify deforested areas.
2. Cases where optical satellites are not sufficient for complete ground observation.
3. A relatively large area of deforestation (plots of more than 2 ha are frequent).
We have also identified the following conditions for the effective use of JJ-FAST to control illegal
deforestation, taken from the experience of Brazil:
4. A government-based system exists, including the deployment of law-enforcement officials to control
illegal deforestation.
5. Mechanisms exist to share information on deforestation at the central and regional levels.
6. Mechanisms exist for collaboration among relevant agencies and central and local governments tocombat illegal deforestation.

4

Okonogi H., Yamada E., and Morita T. (2022) Eyes on the Planet: Toward Zero Deforestation. in Breakthrough:

The Promise of Frontier Technologies for Sustainable Development. Brookings Institution Press. (Figure 6 is basedon Table 8-1 of this book)93. Contact person
Masato Hayashi, Japan Aerospace Exploration Agency (JAXA): hayashi.masato2@jaxa.jp
Mari Miura, Japan International Cooperation Agency (JICA): Miura.Mari@jica.go.jp
Chisa Umemiya, Institute for Global Environmental Strategies (IGES): umemiya@iges.or.jp
Nara Pantoja, Brazilian Institute of Environment and Renewable Natural Resources (IBAMA):
nara.pantoja@ibama.gov.br

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