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

Can remote sensing enable a Biomass Climate Adaptation Index for agricultural systems?

“…Remote sensing is also being investigated as a method to monitor the resilience of ecosystems (Ndungu et al, 2019;Jones et al, 2021). For example, NDVI has been used to measure the resilience of ecosystems following exposure to shocks such as a drought (Washington- Allen et al, 2008;Ndungu et al, 2019;Von Keyserlingk et al, 2021). However, limited research has to date been conducted to assess the use of NDVI to track climate change adaptations in the agriculture sector.…”

“…However, limited research has to date been conducted to assess the use of NDVI to track climate change adaptations in the agriculture sector. Recently, the potential of MODIS satellite derived NDVI as a tool for monitoring adaptations has been demonstrated focusing on sites in Burkina Faso (Nyamekye et al, 2021) and Kenya (Ndungu et al, 2019). Using the RESTREND method (Evans and Geerken, 2004;Ibrahim et al, 2015), it is possible to monitor adaptation interventions compared to a counterfactual (Nyamekye et al, 2021).…”

“…For ricebased systems, techniques such as Synthetic Aperture Radar (SAR) have been used to monitor and map rice productivity (Nelson et al, 2014;Setiyono et al, 2018), an option that TAPAS is exploring. Even where appropriate satellites and data sources are used, one of the major limitations of remote sensing as a means of data collection is that data needs to be processed into a format that can be understood and analyzed by end-users (Jacobs and Al-Azar, 2019;Ndungu et al, 2019). End-users must also be enabled to routinely use the Biomass CAI for their geo-locations of interest, requiring user friendly interfaces (Jacobs and Al-Azar, 2019;Ndungu et al, 2019), training manuals to guide use and interpretation (FAO and UNDP, 2019) and/or collaboration with the TAPAS program to facilitate knowledge transfer, adoption and scaling (FAO, 2013;Ndungu et al, 2019).…”

“…Even where appropriate satellites and data sources are used, one of the major limitations of remote sensing as a means of data collection is that data needs to be processed into a format that can be understood and analyzed by end-users (Jacobs and Al-Azar, 2019;Ndungu et al, 2019). End-users must also be enabled to routinely use the Biomass CAI for their geo-locations of interest, requiring user friendly interfaces (Jacobs and Al-Azar, 2019;Ndungu et al, 2019), training manuals to guide use and interpretation (FAO and UNDP, 2019) and/or collaboration with the TAPAS program to facilitate knowledge transfer, adoption and scaling (FAO, 2013;Ndungu et al, 2019). The TAPAS Biomass CAI platform is being developed with a graphical user interface (GUI) via mobile phone and low-bandwidth internet access, essential to bridging the "digital divide" represented by lack of access to bandwidth (Hilbert, 2016).…”

Assessing the Health of Akamkpa Forest Reserves in Southeastern Part of Nigeria Using Remote Sensing Techniques

“…e MODIS-derived vegetation indices (NDVI and EVI) have been severally used to analyze the spatiotemporal trends over Southern Asia [8]; extract and understand the phenological information about evergreen, semievergreen, moist deciduous, and dry deciduous vegetation in India [9]; forecast the seasonal crop yield in Canada [15]; identify the corn growth in Western Mexico [16]; estimate the forest productivity and dieback in a Mediterranean holm oak forest [10]; assess the seasonal and potential canopy photosynthesis in relation to seasonal changes in Leaf Area Index (LAI), chlorophyll concentration, and air temperatures of NE Argentina subtropical forests [11]; quantify the drought intensity and its geographical effects in order to support the drought monitoring applications [17]; investigate the biomass of forest reserve and the periods of vegetation [12]; depict the quality and relative health of a forest reserve [13]; determine the onset of phenophases in spring and autumn and also to assess forest growth and health condition [18]; evaluate the sensitivity of MODIS-based vegetation index to heat and drought stress in temperate forests [19]; and monitor the trends and changes in vegetation and evaluate the proxies for drought conditions [20].…”