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Application of MODIS NDVI for Monitoring Kenyan Rangelands through a Web Based Decision Support Tool

机译:通过基于Web的决策支持工具,MODIS NDVI在肯尼亚肯亚兰地区监测中的应用

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The Kenyan rangelands contribute significantly to the country’s GDP through livestock production and tourism. With dependence on rain-fed pastures, climate variability coupled with human induced factors such as overgrazing have adversely affected the rangeland ecosystems. And while indigenous communities and conservation experts already use their knowledge of the landscape to make decisions, this information is usually localized. Earth observation imagery provides a bigger picture that can complement indigenous knowledge and improve decision making. This research leverages on data from the MODIS receiver located at the Regional Centre for Mapping of Resources for Development(RCMRD) to develop the indices for the web-based Rangelands Decision Support Tool(RDST) . The tool automates data processing and provides an easy to use interface for accessing indices for rangeland monitoring. MODIS Normalized Difference Vegetation Index (NDVI), anomalies and deviation indices are provided on the tool at decadal, monthly and seasonal time steps .Users begin their assessments by selecting their monitoring units and an NDVI index that responds to their specific questions. These questions respond to assessing current conditions, monitoring trends and changes in vegetation, and evaluating proxies for drought conditions . The information can then be overlaid with other ancillary data sets (roads, water sources, invasive species, protected areas, conflict areas), for context. At the click of a button, the information can be downloaded as a map for further analysis or application in sub regional decision making. Information generated by the tool are being used decision making tool by rangeland managers and county officers. Specifically, to inform adjustments to existing grazing plans, managing movement of livestock from designated grazing areas in wet and dry season, monitoring the success of rehabilitation efforts and resilience of the rangeland ecosystems, monitoring drought, managing scarce water resources and monitoring the spread of invasive species. Successful implementation and application for decision making has relied heavily on local indigenous knowledge and capacity building on use of the earth observation indices. The SERVIR project service planning engagement approach was used in engagements with stakeholders. This improved their participation in co-development of the tool and indices; and in adoption of the tools for decision making.
机译:肯尼亚的牧场通过畜牧生产和旅游业为该国的GDP做出了重大贡献。由于依赖雨养牧场,气候多变性和人为因素(例如过度放牧)对牧场生态系统产生了不利影响。虽然土著社区和保护专家已经利用他们对景观的知识来做出决定,但这些信息通常是本地化的。地球观测图像提供了更大的图景,可以补充本地知识并改善决策。这项研究利用位于开发资源区域地图中心(RCMRD)的MODIS接收器的数据来开发基于Web的Rangelands决策支持工具(RDST)的索引。该工具可自动执行数据处理,并提供易于使用的界面来访问牧场监测的索引。该工具会在年代,月度和季节时间步长上提供MODIS归一化植被指数(NDVI),异常和偏差指数。用户可以通过选择监测单位和可以回答其特定问题的NDVI指数来开始评估。这些问题响应于评估当前状况,监测植被趋势和变化以及评估干旱状况的代理。然后,可以将这些信息与其他辅助数据集(道路,水源,入侵物种,保护区,冲突区)相结合。只需单击一个按钮,就可以将信息下载为地图,以供进一步分析或应用于次区域决策。该工具生成的信息已被牧场经理和县官员用作决策工具。具体而言,为调整现有的放牧计划提供信息,管理在干燥和干旱季节从指定的放牧区转移牲畜,监测恢复工作的成功和牧场生态系统的复原力,监测干旱,管理稀缺的水资源并监测入侵性疾病的扩散种类。成功地执行和应用决策在很大程度上依赖于当地土著知识和利用地球观测指数的能力建设。 SERVIR项目服务规划参与方法用于与利益相关者的参与。这增加了他们参与共同开发工具和索引的参与;并采用决策工具。

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