Harnessing Innovation: Collaborative Project Empowers Namibia’s Agricultural Sector For Food Security

By:Staff Writer
The United Nations’ Food and Agriculture Organisation (FAO) and the University of Maryland (UMD)/NASA Harvest, will collaborate on an agricultural project in Namibia.
With funding from the United States Agency for International Development (USAID) Bureau of Humanitarian Assistance, the organisations aim to harness advanced technologies and methodologies to enhance yield estimates, ultimately informing and strengthening interventions related to agricultural productivity and food security.
The project is titled,”Improved Yield Estimates to Inform Agricultural and Food Security Interventions.”
The main goal of the collaborative project is to leverage remote sensing yield forecast models to improve the accuracy, accessibility, and timeliness of crop production data. By achieving this, the project aims to enhance the effectiveness of agricultural and food security interventions in Namibia.
Key objectives include generating more reliable yield estimates, strengthening the analytical capabilities of stakeholders involved, and providing early warning information for targeted agricultural interventions.
Through the utilisation of advanced technologies and methodologies, the project strives to foster a more resilient and informed agricultural sector, ultimately contributing to improved food security in Namibia.
In a collaborative effort, the Ministry of Agriculture, Water and Land Reform (MAWLR) in Namibia, in partnership with the Food and Agriculture Organisation (FAO) and UMD/NASA Harvest, has embarked on an extensive field data collection initiative since November 2022.
This data collection project encompasses seven key northern regions of Namibia, including Oshikoto, Oshana, Ohangwena, Omusati, Kavango West, Kavango East, and Zambezi.
The objective of the data collection phases is to gather comprehensive information on various aspects of agricultural activities in these regions.
This includes assessing the availability of agricultural inputs crucial for farming, conducting preliminary crop estimates to gauge production potential, and carrying out post-harvest assessments to accurately determine the actual harvest yield
Smallholder farming and subsistence agriculture are prevalent in these regions, making them vulnerable to climate change and other environmental factors.
The FAO and UMD/NASA Harvest project aims to collect accurate data on crop yields and other relevant information to provide tailored interventions that address the specific needs of farmers in these regions.
Gift Kamupingene, FAO National Project Coordinator says the accurate data on crop yields and other relevant information collected through the project will enable FAO, UMD/NASA Harvest, and MAWLR to provide tailored interventions that address the specific needs of farmers in the regions.
The partnership benefits from advanced technologies such as remote sensing, machine learning, and artificial intelligence. These technologies allow for the collection of accurate and timely data on a large scale, providing a comprehensive understanding of the challenges faced by farmers in Namibia.
“The sample size has significantly increased, allowing us to achieve broader coverage of farmers and obtain reliable responses,” said Johanna Shapwa, Agro Business Analyst in MAWLR’s Division of Statistics and Business Information.
Shapwa said the use of remote sensing technology has facilitated the collection of extensive and timely data thereby enhancing the capacity of government to analyse and consider potential interventions.
“The project’s use of advanced technologies and data collection efforts will contribute to addressing the challenges faced by farmers in Namibia,” she noted.
The improved yield estimates provided by FAO and UMD/NASA Harvest aim to equip decision-makers with the necessary tools to plan and implement effective agricultural interventions, enhance food security, and support sustainable development in the country.
The data collected will also contribute to the development and enhancement of robust remote sensing-based yield forecast models.
Namibia, along with Malawi and Kazakhstan, is one of the three countries selected for the pilot project due to its capacity and availability of recent crop statistics essential for the yield forecast model.