Application of MODIS NDVI for Monitoring Kenyan Rangelands Through a Web Based Decision Support Tool - Ndungu, Lilian; Oware, Maungu; Omondi, Steve; Wahome, Anastasia; Mugo, Robinson; Adams, Emily (Frontiers in Environmental Science, 2019)
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 (RDST) 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 datasets (roads, water sources, invasive species, protected areas, place names, conflict areas, migration routes), 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 and maps generated by this tool are being used decision making tool by rangeland managers in the counties and in other management units (conservancies and ranches). Specifically, 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.