Oil in the Sahara: mapping anthropogenic threats to Saharan biodiversity from space

Clare Duncan, Daniela Kretz, Martin Wegmann, Thomas Rabeil & Nathalie Pettorelli

The Sahara

• Biggest desert on earth

• ~Shared by 14 nations

Stereotypes

• Beautiful, yes, but...

• Austere

• Lifeless

• Barren

• Wasteland

• Desolate

• Infertile

• Sterile

• And lastly insecure

Human and cultural diversity

Land of pastoralism

BIODIVERSITY

Wildlife decline

• Overhunting, firearms, civil unrest

• Vehicles, access to remote areas

• Changing landuse/habitat loss

• Inadequate resources: poor international visibility and support

• New developments…mining industry

Addax Critically

Endangered

Slender-horned Gazelle

Endangered

Dorcas Gazelle Vulnerable

IUCN Red List

Historical range of the Addax

Addax population status from 1960 onwards

Oil industry in Agadem Block, Niger

Oil industry in the last stronghold of the addax

Oil in the Sahara: mapping anthropogenic threats to Saharan biodiversity from the

ground

Oil in the Sahara: mapping anthropogenic threats to Saharan biodiversity from the

ground

Addax distribution in the Termit & Tin Toumma National Nature Reserve, Niger

Future addax distribution

Future addax distribution

Urgent need to assess quickly & efficiently the impact of oil exploration activities

Field ground surveys: 1,000 km within the reserve, cost per mission for fuel, equipment & security 2,000 €

Field surveys are expensive

Use remote sensing data to assess the impact of oil exploration activities in the Sahara

Source of free images: Google Earth, very high resolution images not always available

USGS, Landsat TM & ETM pixel resolution can be to rough for small oil exploration sites and you need field data for validation

Solution develop a model combining field data, Google Earth Imagery & Landsat images

Model to assess oil exploration infrastructure impacts

100% of the oil exploration sites in the

Algerian scene were properly classified by the

model

Supervised landcover classification of the

Landsat ETM scene in Algeria, Oriental Erg

Random Forest Model

40 parameters 8 bands x 5 variables

(min, max, mean, stdv, var)

Valid

ation

of th

e mo

del

with

grou

nd

-truth

ed

geo-referen

ced d

ata

Use of VHR Google Earth Imagery to get training

points for the supervised classification

Model applied to the Landast ETM Nigerien scene with field data

validation sites and false color composition image

Results for Niger: 43% omission error Why?

Oil infrastructure from space in Algeria (Google Earth imagery)

Oil infrastructure from space in Niger (Google Earth imagery)

Small oil exploration site in Niger

Temporary oil exploration site in Niger

CONCLUSION

Other sensors can be tested depending on the availability of free images in the area

Not a magic box! Field data and visual interpretation are still needed but the model is very useful in a cost-effective monitoring framework for large areas (e.g. PA in the Sahara)

A good tool to assess potential threats for endangered migratory species (listed on appendix 1 of the CMS) regarding habitat connectivity

Useful for the management of large PA in the Sahara combination of field ground survey, aerial survey & assessment via remote sensing

Saharan biodiversity conservation approach can play a valuable role in addressing the issues related to pastoralism and its resilience to drought, desertification, climate change and security need to develop further collaborations

Project supported by