ClimAgro uses AI and machine learning to analyze crop-climate interactions. We provide short-, medium-, and long-term risk assessments. Our insight empowers agricultural stakeholders to anticipate climate risks, optimize resources, and enhance climate resilience.
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AgRI is a comprehensive solution combining precise crop-specific risk assessments and both current and medium-term projections. Whether you’re a financial institution seeking risk intelligence for crop loans and insurance or an agribusiness optimizing operational strategies, AgRI AI delivers the critical insights you need for informed deci...
Read MoreClimAgro Analytics excels in converting raw climate, agricultural, and socio-demographic data into actionable insights. We provide data at multiple spatial scales, from local administrative units such as blocks and districts to state and national levels, as well as various temporal scales, including historical records. Our tailored datasets serv...
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In the realm od agricultural finance, knowledge is power. climagro Analytics equips banking and financial Institutions with accurate cropspecific yield predictions and current to medium-term risk projections. By providing invaluable insights, we enable informed decisions on crop loans and insurance, fostering financial resilience in the agricultutral sector.
Efficiency is paramount in the supply chain. For traders and logistics professionals, our analytics provide advance knowledge of crop yields. This strategic insight enables supply chain optimization, from planning harvest logistics to distribution. Stay ahead in the competitive supply chain industry with ClimAgro Analytics.
Agribusinesses demand precision and foresight. Our analytics, grounded in historical climate data, crop yield insights, and farm management data, deliver personalized solutions. From optimizing planting schedules to fine-tuning cultivation practices, CLIMAgro ANALYTICS enhances agribusiness operations, ensuring sustainable and efficient practices.
Governments play a pivotal role in shaping agricultural policies and planning. ClimAgro Analytics supports governmental entities with project-specific climate risk projections. These insights aid in strategic planning, risk mitigation, and sustainable agricultural development. Transform your approach to agricultural governance with our data-driven solutions.
By 2050, India is expected to witness an approximately 50 % increase in food demand, with an increasing climate risk (IPCC, 2021). The scientific community identifies weather-induced losses as a significant contributing factor to low-yields observed in India. According to scientific literature, a 2°C increase in global mean temperature is associated with significant crop yield reductions: corn by 31%, rice by 19%, and wheat by 46%. It is noteworthy that agriculture, being the second-largest contributor to global emissions, plays a crucial role in shaping climate change impacts on food production. In India, 55 of the cropped area is rain-fed. In addition to that, in the vulnerability analysis conducted by the ministry of agriculture & Farmer welfare, Govt of India in 2021, 109 districts out of 573 rural districts 19 of total districts are very high-risk districts, while 201 districts are risk districts.
World Economic Forum survey of 1490 leaders: Extreme weather affects yields and economy. India ranks 7th in climate risk. By 2050, population hits 1.73bn, demanding 70% more food. 61% of farmers rely on rain for ~55% of crops, which will lead to ~70% increase in food demand.
A. Climate Financial Scenario Analysis
Scenario planning and stress testing; Economic impact assessment; Revenue forecasting
B. Identify and Evaluate Climate Risks and Opportunities
Risk mapping and profiling; Vulnerability assessment; Opportunity identification
C. Implement Climate Risk Management Strategies
Risk mitigation strategies; Climate-resilient lending criteria; Monitoring and reporting mechanisms
D. Investment in Climate-Resilient and Sustainable Projects
Sustainable investments; Green bonds and climate funds; Technology adoption
E. Engage and Educate Stakeholders
Client education and support; Policy advocacy; Stakeholder collaboration
F. Enhance Data Integration and Analytical Capabilities
Data integration; Advanced analytics utilization; Collaborative data platforms
ClimAgro Analytics presents a research-intensive hybrid model that combines a data-driven machine learning ML model with a physics-driven crop model. This integration empowers various stakeholders to make well-informed decisions at different time scales. The proposed model leverages historical weather data, agricultural data, and farm management data to train and calibrate both the ML and crop models.
The global market for climate risk digital solutions will grow from around $880 million in 2021 (baseline year) to more than $4 billion in 2027 with a CAGR of 30%, according to Vedantix and S&P Global report.
Historical climate data can be used to analyze past climate trends and patterns, understand the frequency and intensity of weather events, and assess the impact of historical climate conditions on agriculture and other sectors. This information is crucial for making informed decisions in planning and risk management, as well as for academic and scientific research.
Climate impact metrics are processed data that estimate various types of climate-related risks. These metrics help clients understand potential climate impacts on different sectors, such as agriculture, infrastructure, and public health. By using climate impact metrics, clients can develop strategies to mitigate risks and adapt to changing climate conditions.
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