Status quo efforts solve – sensing techniques, vegetation databases, and water techniques

The extremely large scale nature of land degradation and desertification means that over recent decades, remote-sensing techniques have been applied widely as tools for evaluating spatial and temporal trends18,19,20. A diverse range of variables and indices extracted from different sensors or satellites, such as AVHRR (Advanced Very-High-Resolution Radiometer), AVHRR-GIMMS (Global Inventory Monitoring and Modelling System), MODIS (Moderate Resolution Imaging Spectroradiometer), NOAA (National Oceanic and Atmospheric Administration) AVHRR or LANDSAT, amongst others, have been employed for assessing land degradation and desertification11,21,22,23,24. From these sources, large databases have been developed that relate to a plethora of vegetation and climate properties25,26, including the normalized difference vegetation index (NDVI)26,27,28, land cover changes29, leaf area index (LAI)30, land surface temperature (LST)30, multidisciplinary indices comprising LAI, albedo and evapotranspiration (ET)30,31, water use efficiency (WUE), net primary production (NPP)32, enhanced vegetation index (EVI)33, and rainfall and vegetation datasets34. Vegetation indices extracted from remote sensing data have been especially useful for monitoring changes in vegetation cover over time. Recent studies have reported the high efficiency of vegetation indices such as NDVI, NPP, LAI and EVI for evaluating the spatial and temporal changes across different scales35,36. These variables are commonly correlated with other climate parameters such as rainfall, temperature or evapotranspiration, which are useful for assessing and forecasting the potential for land degradation into the future24,34,35,36,37,38. Time-series trends in climate and vegetation indices and the relationships between them have been investigated by many authors26,38,39. For example, images from the Tropical Rainfall Measuring Mission (TRMM) sensor have been used to examine the correspondence of vegetation trends with rainfall, while others have studied relationships between land-use changes and land surface temperature (LST)40. Evaluating relationships between vegetation dynamics and climate parameters is a proven powerful and efficient means to determine whether imminent climate change and unconstrained human activities pose a threat to food security and sustainable societies in rapidly developing regions of the world25,26,37.