Use of AI in Desertification Prevention

Context

As global temperatures continue to rise and human populations expand, large parts of the Earth are becoming vulnerable to desertification, or the permanent loss of once-cultivable land. Artificial intelligence (AI) is a valuable ally in combating desertification, but we must be aware of the challenges that must be addressed to make new AI solutions effective.

Using artificial intelligence to combat desertification

• Saudi Arabia's effort: In August 2023, Saudi Arabia launched a large-scale anti-desertification program. Under this, satellite images are being analyzed to monitor changes in land use, vegetation cover and soil moisture levels through AI algorithms.
• Effective in decision making: Artificial intelligence is helping to detect and assess desertification trends in vulnerable areas. It is helping in making decisions about actions such as improving water management, planting trees and promoting sustainable agriculture.
• Helps in formulating strategies: Drones equipped with AI-powered sensors help in capturing high-resolution data from remote or inaccessible areas, providing information about soil and vegetation conditions and helping us develop customized mitigation strategies.
• Aerial Drone Seeding: AI-guided drones are being used in the United Kingdom, the US and Australia to enable tree planting or reforestation projects in barren or sparsely populated areas.
• Predicting climate patterns: AI has been widely used in areas such as predictive modeling. These AI models predict future climate patterns and extreme weather events that may lead to desertification.
• AI for Earth Initiative: AI also analyzes data, land use patterns and environmental factors to predict areas that are potentially at high risk from erosion.
  • Microsoft's 'AI for Earth' initiative encourages a wide range of uses of AI to accelerate environmental protection, including efforts to combat desertification.
• ‘AI for Earth’ is being used by integrating machine learning tools with geospatial data analytics and machine vision techniques to create predictive models of water demand and contribution in local agricultural areas in south-east Spain.

Challenges in deployment of AI

• Barriers to implementation: Desertification often affects relatively remote or underdeveloped areas where data collection practices are rudimentary and data are lacking or non-existent.
• Data Divide: The widespread data divide between countries in the Global South and North is also a major challenge, with some countries in the Global South lacking access to basic digital infrastructure, making data capture difficult.
• Aerial Surveys and Skills Lack: The lack of aerial imagery datasets is a key issue when it comes to data scarcity, and the skills gap often makes it more complex to build AI solutions.
• Shortage of financing: long term AI projects Of For Wealth and investment get to do difficult yes Can Having more AI solutions To advanced to do and them Applicable related to doing High Cost Economic Form From Deprived areas In One Big Obstacle become can Is.
• Complexity of factors: Environmental variability can sometimes be an obstacle itself. Desertification is influenced by a complex interaction of different factors that can sometimes be difficult to model accurately with AI. Climate instability can change conditions unpredictably, complicating AI predictions and interventions.
• Regulation problems: The regulatory landscape for implementing AI technologies can be difficult to navigate, especially in countries that take a strict approach to the use of AI.

Status of desertification in India and mitigation responses

• In 2015, India joined the voluntary Bonn Challenge and pledged to restore 13 million hectares of degraded land by 2020 and an additional 8 million hectares by 2030.
• In 2019, this pledge was further expanded to restore 26 million hectares of degraded and deforested land by 2030. Of this, India has already restored 9.8 million hectares between 2011-17.
• The Indian government has launched various schemes and programmes to combat desertification including afforestation.
  • green India Mission
  • city ​​forest scheme
  • Compensatory Afforestation Fund Management 
  • The planning authority includes afforestation and land restoration works under Mahatma Gandhi National Rural Employment Guarantee Scheme.
  • India has also launched an updated National Action Plan to combat desertification and land degradation through forestry interventions
• However, about 32% of the land is subject to degradation and 25% of the land is heading towards desertification. India still faces a major challenge.
• According to the Desertification and Land Degradation Atlas of India, 2021, about 29.77% of India’s total geographical area (TGA) was undergoing land degradation and desertification during the year 2018-19. 
• Land degradation and desertification has increased by 1.18 million hectares from 96.2 million hectares in 2011-13 to 97.85 million hectares at present.

Way forward or suggestions

• North America, China, Israel are using AI-powered tools and analytics to monitor land degradation in real-time, execute targeted reforestation projects and create sustainable land management practices. India can follow their experiences.
• Despite challenges ranging from lack of data and inadequate capacity to funding constraints and regulatory hurdles, AI is set to play a growing role in combating desertification, so special efforts are needed to make available large amounts of relevant environmental data..
• Open, public datasets such as the Aerial Image Dataset (AID) bring together a diverse array of images from different countries and regions and are an asset to AI developers and more such datasets should be created collaboratively.
• Cross-border data-sharing also remains a thorny issue that needs to be resolved. There have been calls within groupings such as the G20 to facilitate the sharing of certain classes of development data that have an impact on regional policy-making or developing technology-based solutions to international challenges.
• AI is capable of boosting the ability to understand, predict, and mitigate the effects of desertification with unprecedented accuracy and efficiency, so special policies are needed for its use.