| Project Detail |
Project Name Big Data Analytics in Agriculture and Seaports
Project Number 57319-001
Country / Economy Regional
Bangladesh
Indonesia
Project Status Active
Project Type / Modality of Assistance Technical Assistance
This SSTA aims to understand the effects of climate change on agricultural production and food security, as well as the influence of human activities, particularly seaport development, on coastal environments. Through data analysis and modeling, the SSTA will develop adaptation strategies for agriculture and investigate potential environmental indicators for coastal water quality monitoring. By leveraging big data or non-traditional data sources, this research will provide valuable insights for policymakers and stakeholders to make informed decisions regarding climate change and ocean health. This SSTA aligns with ADBs commitment to climate action and aims to contribute to the long-term sustainability and well-being of participating DMCs.
Project Rationale and Linkage to Country/Regional Strategy
Climate change is a significant contributor to extreme weather events, causing widespread damage to both the environment and communities worldwide. The Asia-Pacific region is particularly vulnerable to these impacts primarily due to the regions heavy reliance on agriculture and densely populated coastal areas. Unfortunately, human activities play a crucial role in making these events more frequent and severe. This TA explores climate change from these two perspectives. Firstly, it acknowledges the impact of climate change on agriculture production and food security, and explores effective adaptation strategies. Secondly, it recognizes the influence of human activities on the environment and the need to understand and minimize this. The complex relationship between climate change and human activities in diverse local contexts necessitates further research to inform effective mitigation and adaptation strategies.
From the first perspective, this TA explores the impact of climate change on agricultural production and food security, and effective adaptation strategies to mitigate climate risks. According to estimates by the United Nations Food and Agriculture Organization (UN FAO), between 2008 and 2018, Asia alone suffered disaster-related crop and livestock production losses worth approximately USD 207 billion, accounting for about 74 percent of the global loss. Most of these losses occurred in China, which accounted for 55 percent of the global total, amounting to USD 153 billion. With climate change expected to intensify extreme weather events, this situation is likely to worsen without timely adaptation actions. The majority of farmers in the region are smallholders who rely on their produce for both food and income. Therefore, agricultural losses could directly lead to increased hunger and malnutrition, as well as reduced income and well-being for the poorest populations. Additionally, large-scale production reductions could trigger food price volatility and create food crises at national and regional levels.
To tackle these challenges, the initial step involves data analysis of the impact of climate change on agricultural production and food security. By utilizing historical data on climate and crop production, we will develop models to analyze the relationship between climate variables and crop yield, as well as to estimate crop losses due to extreme weather events. With advancements in meteorology and climatology, we now have access to future climate projections with higher spatial and temporal resolution, enabling more precise and geospatially granular forecasting of the potential impacts of climate change on agricultural production. Furthermore, our research may include adaptation strategies, such as agricultural insurance, climate-resilient seeds, improved irrigation systems, if data are available.
From the second perspective of human impact on climate change, the TA will focus on human activities at coastal waters, specifically, at seaports. In facilitating the delivery of goods and services across global supply chains, seaports play a crucial role. It serves as a hub for international trade and provides temporary storage and handling facilities. As such, Asian Development Bank (ADB) has a number of projects focusing on the development of seaports . Numerous studies have explored seaport performance indicators, highlighting their significant impacts for economic growth, and this economic impact has shown to be increasing in developing member countries (DMCs), e.g., Indonesia. Nevertheless, it is equally important to recognize that seaport development has environmental consequences.
Multiple organizations, such as OECD and US EPA, have emphasized the role of seaports in the aquatic ecosystem. The discharge of wastewater, containing organic waste, nutrients, and heavy metals from various onboard activities, introduces a new set of challenges. Pollutants like nitrogen and phosphorus from human waste and detergents can trigger eutrophication in coastal waters, fostering excessive algal growth and oxygen depletion. At seaports, where ships linger for extended periods, uncontrolled activities could potentially lead to habitat degradation, poor water quality, public health hazards, and loss of biodiversity. In this SSTA, depending on data availability, key seaports of select DMCs will be identified and analyzed using non-traditional, satellite data with high spatial and temporal resolution to explore potential environmental indicators that could provide more granular and timely information.
ADBs transition into the climate bank for Asia and the Pacific, along with its strong commitment to enabling and stimulating climate-smart investment, underscores the need for comprehensive research and knowledge products in addressing the pressing environmental challenges posed by climate change. Therefore, rigorous impact assessments of climate change in the case studies proposed in this SSTA can provide more informed knowledge to guide resources and policy interventions. Given the significant impact of human activities on the environment and the reciprocal impact of climate change on human society and ecosystems, extensive and relevant data are crucial for conducting effective impact assessments. While traditional data sources may not fully satisfy this need due to their lack of timeliness, frequency and geospatial granularity, non-traditional data sources or big data offer promising avenues for gathering the necessary information.
Big datas volume, velocity and variation create new opportunities for undertaking rigorous impact assessments. Predictive analytics, real-time monitoring and evaluation, and deeper insights can be obtained from non-traditional data sources like sensors and satellite data. For example, satellite data can monitor agricultural production timely at a large scale and detect the concentration of chlorophyll-a for quality of coastal water monitoring. Big data analysis allows the study to delve deeper into the potential interrelation of human activities and climate change across a wider geographical area over an extended period. Using such data and viable data mining and analysis schemes, governments and organizations can see trends and insights that allow them to perform data-driven decision-making.
Thus, this knowledge and support TA will generate knowledge to: (i) estimate the impact of climate change on agriculture production and investigate effective climate change adaptation strategies, and (ii) estimate the impact of seaport activities to coastal water quality. The insights from this TA will enable DMCs and ADB to take proactive steps in tackling climate change challenges, make well-informed decisions, and strive to establish economies and ecosystems that are resilient to climate change impacts, thereby promoting the long-term sustainability and welfare of these countries. By understanding the impact of seaport activities on coastal water quality, this TA will contribute to the protection of marine ecosystems and ocean health. The TA will also generate novel datasets derived from non-traditional sources, offering high spatial and temporal resolution insights into the target area, while concurrently building related capacity in targeted DMCs to effectively utilize the dataset and generated knowledge. These datasets and algorithms -- together with capacity building activities -- can be provided to identified DMCs to equip them in developing data-driven climate policies. This TA is well aligned with Strategy 2030, particularly tackling climate change (OP3), promoting food security (OP5) and strengthening institutional capacity in DMCs (OP6), particularly in big data capabilities.
For the study of the impacts of climate change on agricultural production and food security, possible DMCs include PRC, India, and Vietnam, contingent on the availability of data. For the study of seaport activities on coastal water quality, possible DMCs include Bangladesh and Indonesia, depending on data availability. Regional departments will be consulted as part of a collaborative approach to finalize the DMCs. This approach ensures that the SSTA is closely aligned with the operational priorities of ADB as outlined in the corporate results framework. |
