Monitoring the progress of restoration can often be a challenge but dynamics have brought about innovations to improve resilience and improve reporting for accountability to the different actors and stakeholders. For a long time, Jumuisha engaged in restoration of landscapes through soil control, and regreening. These were done at different landscapes with almost no monitoring and accountability. In 2022, the organization selected a forest landscape in efforts to concentrate to more impactful and more controlled area of restoration. This was very successful since the landscape has since been improving with more natural regeneration happening as a result.

[KWA KAMBA PHOTO taken in June 2024 Visit]

The restoration of this landscape has been possible through collaborative efforts with Time and Life Youth group who are residents and locals living around Kwa Kamba community forest. Also, depicting that community driven development works best when key stakeholders are incorporated in planning and implementation of projects.

Restoration in continuous landscapes is more impactful and easier to monitor progress, however, we cannot ignore the fact that other landscapes need restoration and monitoring for holistic realization of climate adaptation and mitigation in the community.

Green steps restoration project was developed to take into consideration the restoration of continuous landscapes and scattered landscapes. This project is done in partnership with TerraFund for AFR100 who provide an array of resources including monitoring tools that assist in effectively improving restoration practices and accountability for sustainability.

Restoration in continuous landscapes is more impactful and easier to monitor progress, however, we cannot ignore the fact that other landscapes need restoration and monitoring for holistic realization of climate adaptation and mitigation in the community.

Green steps restoration project was developed to take into consideration the restoration of continuous landscapes and scattered landscapes. This project is done in partnership with TerraFund for AFR100 who provide an array of resources including monitoring tools that assist in effectively improving restoration practices and accountability for sustainability.

The intersection of artificial intelligence (AI) and landscape restoration marks a significant advancement in environmental conservation. AI, with its capacity for data analysis, pattern recognition, and predictive modeling, offers a powerful tool for monitoring and optimizing restoration efforts. AI’s ability to process vast amounts of data is particularly valuable in landscape restoration. Remote sensing technologies, such as satellite imagery and drones, collect data on vegetation cover, soil health, and these inform relevant interventions in implementation.

AI algorithms can analyze this data to identify changes in land cover, and assess the effectiveness of restoration interventions. For instance, deep learning models can be trained to recognize specific plant species, enabling accurate monitoring of biodiversity restoration. AI-powered image analysis can accurately measure vegetation cover and detect subtle changes in land health that may be missed by human observers.

One of the key benefits of AI in landscape restoration is its potential to improve efficiency and reduce costs. Traditional monitoring methods often rely on labor-intensive field visits, which can be time-consuming and expensive. AI-powered systems can automate data collection and analysis, freeing up resources for other critical tasks. Additionally, AI can help identify areas that require immediate attention, allowing for targeted restoration efforts and optimizing resource allocation.

Each advanced resource comes with its own concerns. Such concerns include accuracy needs large data sets to train effectively. This also calls for consistency which is also a complex task. Another con is data protection and security since location information needed is sensitive but very critical. For rural landscapes where GIS is not stable, inaccurate data can be projected hence providing inaccurate bias results. It is essential to carefully consider the diversity and quality of training data to ensure that AI systems are fair and equitable.

Despite these challenges, the potential advantages of using AI as a monitoring tool to restoration are based on its capability to make work easy, while improving accuracy and better understanding complex dynamics of ecosystems, and help address the emerging threats to restoration.

Jumuisha Initiative is therefore happy to adapt efficient monitoring tools in its restoration efforts in the community for sustainability and climate resilience.

Climate action in indeed local and we are the champions!