This is the 24th post in a blog series to be published in 2023 by the APET Secretariat on behalf of the AU High-Level Panel on Emerging Technologies (APET)

The African continent boasts a rich tapestry of diverse forest ecosystems, bestowing numerous benefits upon its inhabitants. Africa is, notably, home to the world's second-largest rainforest, the Congo Basin, which encompasses 17% of the world's forests and 31% of the wooded areas found in the Sahel and other regions.[1]  These landscapes serve as vital sources of various essential products and services, including sustenance, energy resources, shelter, and freshwater. Furthermore, they offer crucial protection against various threats and serve as habitat for a wide array of species.  Frameworks such as the African Union's Agenda 2063 and the African Convention on the Conservation of Nature and Natural Resources provide guidance towards the preservation and safeguarding of these invaluable forest ecosystems.[2] 

Regrettably, the foremost environmental challenge faced by the African continent revolves around the relentless depletion of its forest ecosystems, commonly referred to as deforestation. The gravity of this issue is underpinned by the forests’ substantial economic and ecological value and the unmistakable adverse effects deforestation imposes on both human populations and wildlife.[3] The repercussions include the alarming loss of biodiversity, the release of greenhouse gases into the atmosphere, disturbances in water cycles, heightened soil erosion rates, and the profound disruption of livelihoods.[4]

Deforestation rates are particularly higher in tropical African Union (AU) Member States experiencing population growth and widespread poverty, and Tanzania is no exception to this trend. The United Nations has reported that approximately 37.7% or about 33 million hectares of Tanzania’s land area is covered by forests, with woodlands accounting for approximately 90% of this forested land. Additional types of forests in Tanzania encompass coastal woodlands, mangroves, and acacia forests. [5]

Disturbingly, Tanzania is grappling with a severe crisis of forest loss. Over the two decades spanning from 1990 to 2010, the country experienced an average annual loss of slightly over 4 hundred thousand hectares, which is the equivalent to 0.97% of its forest area. The cumulative loss during this period amounted to a staggering 19.4%, encompassing roughly 8 million hectares of forest cover. Recent assessments paint an even bleaker picture, indicating that Tanzania has already lost 38% of its forested regions. Should the current trajectory persist, Tanzania’s entire forested area could be depleted within the next 50 to 80 years.[6]

The depletion of the forest cover in Tanzania has had a profound and adverse impact on its rich biodiversity. A considerable number of indigenous plant and animal species are unique to Tanzania, yet their survival is gravely threatened due to the habitat destruction caused by deforestation. Historically, Tanzania's forestry sector has been a vital source of employment and income, but these opportunities have dwindled in tandem with the reduction in forested areas. Additionally, the diminishing tree population has played a role in exacerbating climate change, resulting in various detrimental economic consequences, including reduced agricultural yields, heightened health-related risks and infrastructure degradation.[7]

Deforestation in Tanzania primarily stems from several key factors such as the requirement of land for the expansion of agriculture, logging, timber extraction, mining activities and infrastructure development. Additionally, the situation has been exacerbated by an increase in wildfires, a trend observed worldwide, including in Tanzania. Over the period from 2001 to 2022, Tanzania experienced a loss of approximately 3.01 million hectares due to various factors, with wildfires contributing to the loss of 8.81 thousand hectares of tree cover.[8] Furthermore, the surge in wildfires within Tanzania can be attributed to a range of causes, such as the quest for improved pasture quality, the control of parasites, facilitation of wildlife hunting, honey collection, charcoal production, mining activities, pit sawing, grazing practices, farm expansion, arson, with wildfires often attributed to human activities such as pedestrian movements or internal migration.[9]

The AU High-Level Panel on Emerging Technologies (APET) is advocating for AU Member States, including Tanzania, to embrace artificial intelligence (AI) such as satellite imagery and surveillance of forest canopies, machine learning, spatial modeling software and an artificial neural network architecture to map the links between past forest loss and drivers as a means of safeguarding their ecosystems. AI can substantively aid the preservation of African forests through the provision of advanced tools and technologies for their monitoring, administration, and protection. AI is a field of science and engineering that focuses on creating intelligent machines, particularly intelligent computer programmes[10]. APET argues that AI can play a significant role in protecting forests from wildfires by offering early detection, continuous monitoring, and effective management solutions.[11]

The utilisation of aerial and satellite imagery analysis through remote sensing technology allows for the rapid identification of potential wildfire outbreaks by detecting indicators such as smoke, heat, or abnormal patterns within forested regions. Employing image analysis for early detection can also help in identifying fires at their inception. AI systems are capable of scanning images and videos captured by cameras situated in various locations to discern signs such as smoke or flames. Furthermore, they can harness data from Internet of Things (IoT) sensors placed in forested areas, including temperature, humidity, and wind speed, to identify any unusual conditions that may signify the onset of a fire. Part of the problem is a lack of adequate forest monitoring, and the challenge of “obtaining accurate and consistent spatial data on deforestation”. Even with the use of satellite imagery and surveillance of forest canopies, ‘filtering large amounts of data can be slow, labour intensive, and expensive”.

AI's application in enhancing wildfire detection, monitoring, and management across African nations introduces innovative solutions.  Hharnessing AI serves as a promising innovation for enhancing the accuracy of forest monitoring, with the potential to be adapted to other AU Member States through adequate government support, robust policy frameworks, and international cooperation. In Tanzania, the Tanzania Forest Service (TFS) utilizes AI to construct a predictive model for wildfire risk by considering factors such as weather, topography, and vegetation, effectively identifying high-risk areas.[12] This insightful data informs resource allocation and the establishment of early warning systems. Additionally, TFS employs satellite imagery analysis to develop this predictive model, aiding in resource allocation and early warning system implementation. Complementing this effort, TFS has installed a network of cameras in its parks, equipped with AI software, capable of automatically detecting wildfire indicators such as smoke, and transmitting immediate alerts to firefighters.[13] Collaborating with Conservation International, TFS utilizes an AI-powered system for real-time wildfire movement tracking via satellite imagery. This information enhances coordination among firefighters, ensuring the protection of both wildlife and communities.

In South Africa, on the other hand, the South African National Parks (SANParks) employs AI for early wildfire detection. A network of AI-equipped cameras is strategically deployed across SANParks' territories. These cameras autonomously detect smoke and other wildfire indicators in promptly alerting firefighting teams.[14] In Kenya, the Kenya Wildlife Service (KWS) partners with Conservation International to employ AI in monitoring wildfire propagation. The collaboration has yielded an AI-driven system that analyses satellite imagery in real-time to track wildfire movements. This information enhances the coordination of firefighting efforts while safeguarding wildlife and communities.[15]

APET asserts that integrating AI ethically and responsibly is of utmost importance in addressing deforestation in Tanzania and other AU Member States. Key ethical and responsible principles for the implementation of AI in wildfire management for example, could encompass designing AI-powered firefighting robots with a strong focus on minimising environmental impact. Additionally, governments and relevant stakeholders have a responsibility in ensuring that AI-driven early warning systems are accessible to all communities, irrespective of their socio-economic status.  APET, therefore, urges African governments to develop AI-powered resource allocation systems that uphold the principles of equity, fairness, and non-discrimination.  APET, posits, therefore, that by embracing AI with a commitment to ethical and responsible practices, AU Member States can strengthen their capacity to combat the escalating deforestation, wildfire threats, protect communities and preserve the environment for future generations.

 

Featured Bloggers – APET Secretariat

Aggrey Ambali

Justina Dugbazah

Barbara Glover

Bhekani Mbuli

Chifundo Kungade

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[1] https://au.int/en/treaties/african-convention-conservation-nature-and-natural-resources

[2] https://au.int/en/treaties/african-convention-conservation-nature-and-natural-resources

[3] https://earth.org/deforestation-in-africa/

[4] https://www.intechopen.com/chapters/48904

[5]https://rainforests.mongabay.com/deforestation/2000/Tanzania.htm

[6] https://www.intechopen.com/chapters/48904

[7] F. Nzunda, E., & S. Yusuph, A. (2023). Forest Degradation in Tanzania: A Systematic Literature Review. IntechOpen. doi: 10.5772/intechopen.107157

[8] https://www.globalforestwatch.org/dashboards/country/TZA/?category=undefined

[9] https://www.scirp.org/journal/paperinformation.aspx?paperid=75691

[10] https://www.ibm.com/topics/artificial-intelligence

[11] Carta, F.; Zidda, C.; Putzu, M.; Loru, D.; Anedda, M.; Giusto, D. Advancements in Forest Fire Prevention: A Comprehensive Survey. Sensors 2023, 23, 6635. https://doi.org/10.3390/s23146635

[12] https://ts2.space/en/ai-in-wildfire-management-the-rise-of-forest-fire-prediction-technologies/

[13] James, G.L.; Ansaf, R.B.; Al Samahi, S.S.; Parker, R.D.; Cutler, J.M.; Gachette, R.V.; Ansaf, B.I. An Efficient Wildfire Detection System for AI-Embedded Applications Using Satellite Imagery. Fire 2023, 6, 169. https://doi.org/10.3390/fire6040169

[14] https://www.designboom.com/technology/pano-ai-artificial-intelligence-cameras-wildfire-prevention-08-02-2023/

[15] https://www.downtoearth.org.in/news/africa/artificial-intelligence-satellite-driven-crop-monitoring-to-help-kenya-farmers-boost-yield-88187