Impact of roads on deforestation levels across Latin America

ROAD IMPACT ASSESSMENT
ON HABITAT LOSS
IN LATIN AMERICA
Karolina Argote, Louis Reymondin, Carolina Navarrete, Denny
Grossman, Jerry Touval, Andy Jarvis
Decision and Policy Analysis Research Area (DAPA)
International Center for Tropical Agriculture (CIAT)
Conservation Biology Institute (CBI)
The Nature Conservancy (TNC)

Project outcomes

This project presents a habitat change monitoring methodology
that can be used to identify environmental impacts of road
construction, and support improved design of future projects
that would minimize negative environmental impacts.

The project has also helped understand the nature of
environmental impacts of road infrastructure projects in distinct
contexts across Latin America, demonstrating the importance of
policy and ecosystem specific safeguards.

Objectives of the project
• Evaluate the environmental impacts of road
infrastructure in the past through monitoring
of natural habitat loss pre- and post-
construction for 5 road projects across Latin
America
• Demonstrate how this can be integrated into a
decision support tool – DATABASIN
• Identify entry points by which ex ante
assessment can provide improved safeguards

Content
1. Methodologies
1.1. Terra-I – Habitat Change Monitoring

2. Road Impact Results
2.1. The BR-364 highway in Brazil.

2.2. The IIRSA projects in Peru.

2.3. The Pan-American Highway in Panama.

2.4. The Santa Cruz – Puerto Suarez corridor in Bolivia.

2.5. The Trans-Chaco Highway in Paraguay.

3. Methodology of the Future Deforestation
Scenarios and Results

4. Carbon-Conservation Interface

5. Conclusions and Recommendations

Photo by Alvaro Gaviria in Cartagena del Chaira
Parques Nacionales Naturales de Colombia

1.1. Methodologies: Terra-i Methodology

Terra-i is a system that monitoring the habitat change in Latin America
using Neural Network and satellite data

We therefore try to learn how each pixel (site) responds to climate, and any anomoly corresponds to human impact.
Neural-network, is a bio-inspired technology which emulates the basic mechanism of a brain.

It allows …
To find a pattern in noisy dataset 9000

To apply these patterns to new dataset 8500

8000

7500

7000
NDVI

INPUTS: Past NDVI (MODIS MOD13Q1)
6500
Previous Rainfall (TRMM) Measurments
6000
Predictions
5500 Interval max
OUTPUT: 16 day predicted NDVI Interval min
5000

4500
1 2 3 4 5 6 7 8 9
Time

1.1. Methodologies: Terra-i

The Bottom-Line
• 250m resolution
• Latin American coverage (currently)
• Satellite data to monitorithe habitat every 16 days
• Identification of habitat change events
• Habitat loss data online to visualize and download.

www.terra-i.org

1.1. Methodologies: Interpreting the maps

1.1. Methodologies: Interpreting the graphs

When did the habitat
loss happen within each
buffer?

Area of
habitat
lost

Geographic
footprint of Buffer distance
the road from the road (km)

BR-364 Highway, Brazil
Date
Acre Segment: Construction 2002 to 2010
Rondonia Segment: Construction 1985 to 1997

2.1. Road Impact Results: BR-364 Highway, Brazil

Study Area
Section 2: a corridor of 515km which connects the town of Rio Branco in the state of Acre and Porto Velho in the
state of Rondônia.


Study Area
The road Cruzeiro do Sul – Porto Velho was analyzed into two different sections. Section 1: a corridor of 623km
Cruzeiro do Sul - Rio Branco in the state of Acre, Brazil.

This section passes through a large biological corridor of the state of Acre which has been regulated by 39 protected
areas connected to each other.


Road impact
Comparing the two segments one can see a
huge difference in the deforestation rates and
in how it is the spatially distributed.

Much higher deforestation
rates, and much BIGGER
footprint >50km due to
secondary roads etc.

More localised footprint, and
and lower overall deforestation
levels. Nevertheless, increase
in last 2 years.


Protected Areas
Protected Area 2004 2005 2006 2007 2008 2009 2010 2011 Accum. Rate
Bom Futuro 3,906 9,531 18,325 11,381 13,675 2,619 14,738 2,231 76,406 10,188
Rio Jaciparana 3,838 5,594 12,288 7,300 3,563 2,494 10,925 1,525 47,525 6,337
Uru-Eu-Wau-Wau 219 450 1,238 656 1,125 575 7,000 1,494 12,756 1,701
Rio Ouro Preto 263 744 1,613 550 206 100 3,006 131 6,613 882
Corumbiara 1,313 1,894 956 1,081 531 94 550 75 6,494 866
Pacaas Novas 0 75 275 2,488 194 225 2,306 663 6,225 830
Mutum 50 100 1,231 656 525 288 2,331 369 5,550 740

Bom Futuro and Jaciparaná are the two protected
areas most affected by deforestation in Rondônia
and are located next to the analyzed road, within a
buffer area of 20km.

Actually, the deforestation rate in Bom Futuro has
been of 10,188 hectares per year (adding up to
76,406 hectares converted in 7.5 years) whereas it
has been of 6,337 hectares per year in Rio Jaciparaná
(adding up to 47525 hectares converted in 7.5 years).


Conclusions
• Section 1: Acre. Habitat loss of 19,542 hectares was recorded per year in average in a buffer area
of 50km of the Cruzeiro do Sul -Rio Branco Segment
• Section 2: Rondonia. Habitat loss of 79,783 hectares per year within a same buffer size around
the Rio Branco -Porto Velho Segment.
• Much higher in the segment Rio Branco-Porto Velho (in Rondonia) than in Cruzeiro do Sul-Rio
Branco (In Acre) likely due to the conservation policies implemented in Acre state. Note fewer
secondary roads, and greater protection from National Parks in segment 1.

Road: Rondonio Acre
Project Period: 2002-2010 2002-2010
Average pre-road deforestation rate: 79,000 18,700
Average post-road deforestation rate: 113,000 (+43%) 32,400 (+72%)
Year of peak deforestation: 2006 2008
Footprint (modal deforestation distance): 20-30km 20-30km

IIRSA Project, Peru
Date
Construction: 1998 to 2007

2.2. Road Impact Results: IIRSA Projects, Peru

Study Area
The analyzed roads have a total length of 1584km and go through all Peru from the Pacific coast to the
Acre state in Brazil. The road was split into three different sections for the analysis:

 Section 1: 752km.
Paita on the Pacific coast
Section 1 (Piura) to Tarapoto.
Andean

Tarapoto - Huanuco (where
it passes 2km away from
Tingo Maria National Park).

Section 2
Piedemonte Tingo Maria (Huanuco) -
Cruzeiro do Sul (Acre, Brazil).
Section 3
Amazon


Road Impact

Section 1 (Paita-Tarapoto) : accumulated loss of 40,794 hectares (5,439 Ha/yr).

IIRSA Road Impact Significant
Habitat loss Section 1: Patia-Tarapoto increase in
6,000 deforestation in
5,000 past 3-4 years
4,000
Hectares

3,000 Most habitat
2,000 loss in first
1,000
10km (45%)
0
Road to 10 10 to 20 20 to 30 30 to 40 40 to 50


Road Impact

Section 2 (Tarapoto-Tingo Maria) : accumulated loss of 30,763 Ha (4,102 Ha/yr). Most impacted areas are
located in a buffer of 30km from the road.

Significant
IIRSA Road Impact increase in
Habitat loss Section 2: Tarapoto-TingoMaria
3,000
deforestation in
past 3-4 years
2,500

2,000
Hectares

Most habitat
1,500
loss in first
1,000
30km (88%)
500

0
Road to 10 10 to 20 20 to 30 30 to 40 40 to 50


Road Impact

Section 3 (Tingo Maria-Cruzeiro): accumulated loss of 58,900 hectares (7,853
Ha/year). Most impacted areas are located in a buffer of 30km from the road.

No apparent
IIRSA Road Impact increase in
Habitat loss Section 3: TingoMaria-Cruzeiro
deforestation
7,000
during or after
6,000
road
5,000
construction
Hectares

4,000
3,000
Most habitat
2,000
loss in first
1,000
30km (81%)
0
Road to 10 10 to 20 20 to 30 30 to 40 40 to 50


Conclusions

Section 1: Andes. Footprint more localised (<10km), 25% increase in habitat loss post-
project versus pre-project.
Section 2: Piedemonte. Larger footprint (10-20km), and > doubling of deforestation after
road finalization.
Section 3: Tingo Mario-Cruzeiro. High baseline levels of deforestation in the region, but
no increase since road project (major sections of road still not complete).

Road: IIRSA, Peru, Section 1 IIRSA, Peru, Section 2 IIRSA, Peru, Section 3
Project period: 1998-2007 1998-2007 1998-2007
Average pre-road deforestation rate: 4,900 2,300 7,600
Average post-road deforestation rate: 6,100 (+25%) 5,200 (+125%) 7,500 (-1%)
Year of peak deforestation: 2010 2010 2005
Footprint (modal deforestation distance): 0-10km 10-20km 10-20km

Pan-American Highway, Panama
Date

2.3. Road Impact Results: Pan-American Highway, Panamá

Study Area
The Pan-American Highway is located in the Darien province in Panama at the eastern end of the country and its
length is approximately 262km, in a 30km of buffer around the road are located more than 10 protected areas with
important ecological functions.


Habitat Change Monitoring

MAIN INPUTS
 For generated deforestation maps before 2000:
A dataset of land cover produced by the Forest Information System
Project, the National Environmental Authority (ANAM) for 1992
and 2000.
 For generated deforestation maps between 2004 and 2010:
Terra-I dataset.

Methodology
i. Reclassify the Land Cover Maps of 1992 and 2000 using ArcGIS software in Vegetation and non
vegetation maps.
ii. Generated the deforestation map of 1992-2000.
iii.Applied the Terra-I Methodology to monitoring the habitat change between 2004 to 2010.
iv.Analyze the road impact in buffers areas in 10, 20, 30, 40 and 50km of the road.


Road impact

The habitat loss is greater the
closest it’s to the road.

Vast majority of habitat change
occurred in the 1990’s directly Buffers Area 1992-2000 2004-2010 Total loss %Loss
after road construction. Road to 10km 253,546 77,930 3,675 81,605 32%
10km to 20km 260,711 37,391 1,606 38,997 15%
Deforestation 2004-2011 < 10% 20km to 30km 539,159 39,849 4,700 44,549 8%
30km to 40km 497,927 16,051 2,531 18,583 4%
of 1990’s levels. 40km to 50km 380,294 7,466 1,844 9,310 2%
Road to 50km 2,450,696 272,150 18,231 290,381 12%


Conclusions

• Between 1992 and 2000 there was an alarming loss of 7% of the total
national forest cover in Panama which is equivalent to 497,306 hectares.
This deforestation is localized mostly in the provinces of Panama and Darien
and close to the road.
• The impact occurs mainly in the direct influence area of the road (0 to
10km).
• The Darien province lost 24% of its forests, and Panama 23%. Most of this
deforestation occurred in Mixed Cative forest in order to create new
cropland areas.

Santa Cruz-Puerto Suarez, Bolivia
Date

2.4. Road Impact Results: Santa Cruz-Puerto Suarez Corridor, Bolivia

Study Area
The corridor Santa Cruz-Puerto Suarez is located in the South East of Bolivia. Its length is approximately 636km and
connects the towns of Santa Cruz de la Sierra and Puerto Suarez located on the border with the state of Mato Grosso
do Sul in Brazil. In the area one can see four easily distinguishable types of ecoregions: Pantanal, Dry Chaco,
Chiquitano Dry Forest and Cerrado


Road Impact

• Road still under construction. Some direct impacts especially close to Santa
Cruz.
• Major indirect impacts of fires originating from “slash and burn” practices,
especially in 2010.

Santa Cruz Road Impact
Habitat loss Section: Santa Cruz-Puerto Suarez
14,000
12,000
10,000
Hectares

8,000
6,000
4,000
2,000
0
Road to 10 10 to 20 20 to 30 30 to 40 40 to 50


Conclusions

• Too early to say what direct impacts are until road fully connects Bolivia with Brazil
• Nevertheless, clear indirect impact through fires originating from slash and burn
activity, especially in the region of Santa Cruz

Road: Santa Cruz-Puerto Suarez
Project period: 2000-2011
Average pre-road deforestation rate: 11,392
Average post-road deforestation rate: N/A
Year of peak deforestation: 2010
Footprint (modal deforestation distance): 20-30km

Trans-Chaco Highway, Paraguay
Date

2.5. Road Impact Results: The Trans-Chaco Highway, Paraguay

Study Area
The trans-Chaco highway length approximately 736km, extending from the boundaries between Bolivia and
Paraguay near the military post Mayor Infante Rivarola in the department of Boqueron until it intersects with the
9th Road which runs through the Dry Chaco in Boqueron continuing through the department of Presidente Hayes
across the humid Chaco region up to the Asuncion metropolitan area in the Central Department.


Habitat Change Monitoring

MAIN INPUTS
Dataset from the high spatial resolution satellite Landsat 4
Thematic Mapper in the Dry Chaco ecoregion.
Terra-I dataset.

Methodology
i. Classify the Landsat-4 satellite images using the k-Means Algorithm .
ii. Generated the deforestation map of 2000-2004.
iii.Applied the Terra-I Methodology to monitoring the habitat change between 2004 to 2011.
iv.Analyze the road impact in buffers areas in 10, 20, 30, 40 and 50km of the road.


Road Impact
• Total of 650,000 Hectares lost in 50km buffer since 2004
• Massive increase since 2007 (project completion)
• Large footprint, covering >50km from road


Conclusions

• Very high levels of deforestation pre- and post- road construction
• But > 300% increase in deforestation rates since road finished, with a footprint that
likely goes beyond 50km buffer

Road: Trans-Chaco Highway
Project period: 2002-2006
Average pre-road deforestation rate: 23,000
Average post-road deforestation rate: 97,000 (+319%)
Year of peak deforestation: 2010
Footprint (modal deforestation distance): 30-40km

Methodologies: Future Deforestation Scenarios

INPUTS
 The distance to the nearest road, to the nearest river,
This methodology is still
to the nearest city (> 1000 people)
under development, nevertheless its
implementation as proof of concept  The elevation
in Brazil generated good results in  The base map (what was already deforested before the
areas with clear patterns of analysis with terra-I (from human classification of the
deforestation. terra-i clusters))
 The detection from the terra-I model.

Steps…
1) Train neural network to recognize pixels that are likely to be deforested

2) Create maps of potential deforestation

3) Select random pixels from the potential maps

4) Repeat 2 and 3

Currently, the tool only takes into account topographic variables, but the idea is in the future is
to include others inputs such as administrative information (protected areas, country…), social
information (small farmers, industrial exploitation, community managed forest…) and
ecosystems in order to improve the estimation.

3. Future Deforestation Scenarios: Applied in BR-364 Road, Brasil

Applied INPUTS
 The distance to the nearest road, to the nearest river,
 The study area was the area around the road Rio to the nearest city (> 1000 people)
Branco-Porto Velho, in Brazil from the 1st of
 The elevation
January 2004 to the 10th of June 2011.
 The base map (what was already deforested before the
Constant rate to 10’000 hectares per 16 days analysis with terra-I (from human classification of the
period (the average rate recorded by Terra-i in this terra-i clusters))
area)
 The detection from the terra-I model.
Sampled 10’000 pixels to train the neural
network. (7000 unchanged and 3000 deforested)

This first implementation of this methodology gave encouraging results as by
comparing this result with the actual detected deforestation one can see that the
general patterns resulting from the simulation are convincing and quite similar to the
real events. However, various improvements could be instigated.

3. Future Deforestation Scenarios: Applied in BR-364 Road, Brasil
PROOF OF CONCEPT

Base map Potential deforestation at T=0 Potential deforestation at T=150

Predicted deforestation Actual deforestation (Terra-i)

A synthesis of findings
Road: Rondonio Acre IIRSA, Peru, Sect. 1 IIRSA, Peru, Sect. 2 IIRSA, Peru, Sect. 3 Trans-Chaco Highway
Project Period: 2002-2010 2002-2010 1998-2007 1998-2007 1998-2007 2002-2006
Average pre-road deforestation rate: 79,000 18,700 4,900 2,300 7,600 23,000
Average post-road deforestation rate: 113,000 (+43%) 32,400 (+72%) 6,100 (+25%) 5,200 (+125%) 7,500 (-1%) 97,000 (+319%)
Year of peak deforestation: 2006 2008 2010 2010 2005 2010
Footprint (modal deforestation distance): 20-30km 20-30km 0-10km 10-20km 10-20km 30-40km

• Roads clearly a significant driver of deforestation
and land-use change, demonstrated in all 5
projects studies. Impacts are both direct and
indirect.
• A road makes a different “footprint” depending
on the ecosystem (Andes <10km, Amazon ~50km,
Chaco >50km).

Lessons learned
• Other factors such as secondary roads and rivers are
important drivers of habitat change and roads open access to
them.
• As a Monitoring Tool Terra-I is only useful to analyze projects
after 2004. In the cases of Acre-Rondonia, Peru and Paraguay
we had three cases where the full power of Terra-I could be
shown.
• Local, national and international policies are clearly important
contexts that should be taken into account during and after
road construction as they have a clear link to land-use change
and can contribute to mitigation or exacerbation of the road
project encironmental impact.

Policy Recommendations
• Regional and national environmental policies in place can significantly
reduce the number of hectares deforested during and after the road
construction project. The most outstanding case can be found in Brazil
where Rondonia has higher deforestation rates compared to Acre.
• Most of the protected areas affected directly or indirectly by the road
construction, were established after the roads where built. In cases were
critical ecosystems are endangered, policy makers and development
planners should consider for the future, well in advance, critical natural
habitats for conservation and biodiversity hotspots.
• It’s expected that infrastructure allows the expansion of economic
activities. In this sense, national and regional policies and incentives to
promote sustainable and environmentally friendly agricultural practices
are also important. In the case of the slash and burn method in Bolivia and
Peru causing multiple forest fires, more national policies and programs to
promote more sustainable practices should be in place, such as the Slash
and Mulch Agroforestry Systems. It’s also key to have increased
productivity. Land policy and law enforcement are also relevant in terms
of reducing the negative environmental impact of road infrastructure.

Project Components by
Conservation Biology Institute

- New Datasets in IDB-DSS
- Carbon
- Deforestation
- New Analyses
- Carbon CNH relationship
- IIRSA road impact on CNH in
Amazon and Gran Chaco
- IDB road impact on CNH related to
deforestation

New Data: Roads and Deforestation

Carbon and Biodiversity Analysis

Carbon-Conservation Interface: CNH Protected Areas

Carbon-Conservation Interface: CNH Species

Carbon-Conservation Interface: CNH Terrestrial Ecosystems

Carbon-Conservation Interface: All Critical Natural Habitat

Carbon-Conservation Interface: Above Ground Carbon

Interface between High Carbon and Critical Natural Habitat

IIRSA Road Impacts to Biodiversity

Cruziero do Sul – Rio Branco Road (BR364)
An exploration of Road Development, Deforestation, Above
Ground Carbon and Critical Natural Habitat

Acknowledgements
This Consultancy Project was conducted by the International Center for Tropical Agriculture (CIAT), the Nature
Conservancy (TNC), and the Conservation Biology Institute (CBI) for the Environmental and Social Safeguards Unit of
the Inter-American Development Bank. This project was supported with funds from the German Federal
Bundesministerium fuer wirtschaftliche Zusammenarbeit und Entwicklung (BMZ) in the framework of a cooperation
program between the Inter-American Development Bank (IDB) and the Deutsche Gesellschaft fuer Internationale
Zusammenarbeit (GIZ).

Thank you!

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