RCUK-CIAT Newton Fund Advancing sustainable forage-based livestock production systems using multi-source remote sensing and social science approaches

农业和畜牧业生产历来是哥伦比亚经济发展的主要组成部分之一，它是世界上最大的农业用地扩张潜力的国家之一。大约34%的土地面积（约40万公顷）用于畜牧活动，大部分牧场用于广泛的放牧系统。农业是哥伦比亚农村就业的重要来源，也是受气候和气候变化影响最大的部门之一，需要解决影响牧场和畜牧业生产力和可持续性的关键挑战。格拉斯哥大学（UofG）、布里斯托大学（UofB）和CIAT之间的这一合作项目将汇集跨学科的观点和方法，以制定在地方和区域一级进行饲料监测和管理的RS方法。具体目标是：1）为CIAT总部的试验地点开发共同设计的多维多光谱和雷达数据的获取、处理和分析工作流程; 2）调查从机载/星载/现场数据集中提取草生长和质量指标的业务功能，并开发饲料管理决策支持系统框架;调查与小农接触的方法，并确定对将这些技术及其产出纳入实践的态度和潜在障碍。该项目将提供新的数据，以建立对多源遥感和预测分析工具能力的基本认识，从而提供关于牧草数量和质量以及小农采用此类技术的能力和意愿的可靠和一致的信息。该项目的产出将直接为饲料生产管理活动提供信息，并将通过项目网站、项目结束讲习班以及通过支持过渡委员会举办的进一步宣传活动向利益攸关方传达。

Agriculture and livestock production have historically been one of the major components of Colombian economic development and it is one of the top countries in the world in terms of greatest agricultural land expansion potential. Approximately 34% of the land area (~40m Ha) is used for livestock activities, with most pastures dedicated to extensive grazing systems. Agriculture is a critical source of employment in rural Colombia and is one of the sectors most affected by climate and climate change and where solutions to key challenges affecting the productivity and sustainability of pastures and the livestock sector are required. This collaborative project between University of Glasgow (UofG) University of Bristol (UofB) and CIAT will bring together cross-disciplinary perspectives and methodologies to develop RS-based approaches for forage monitoring and management at local and regional levels. The specific objectives are to: 1) develop co-designed work-flows for acquiring, processing and analysis of multi-dimensional multispectral and radar data for trial sites at CIAT headquarters; 2) investigate operational functions for extraction of grass growth and quality metrics from combined airborne/spaceborne/in situ datasets and develop a framework for a forage management decision support system; and 3) investigate methodologies for engagement with smallholders and determine attitudes to and potential barriers of incorporation of such technologies and their outputs into practice. The project will deliver new data to establish a baseline understanding of the capabilities of multi-source remote sensing and predictive analysis tools to provide reliable and consistent information on forage quantity and quality and smallholder capability and willingness to adopt such technologies. Outputs from the project will directly inform forage production management activities and will be communicated to stakeholders via a project website, an end-of-project workshop, and through promotion at further dissemination events run by CIAT.