Quality of Normalized Difference Vegetation Index (NDVI) and land surface temperature

Three new datasets have been published on the Agro-informatics Platform within the WaPOR channel. While decadal (every 10 days) versions of this data were already available, these new layers provide even more context for users by focusing on the long-term quality of key inputs to the workflow of production of WaPOR data: normalized difference vegetation index (NDVI) and land surface temperature (LST). In fact, when atmospheric conditions are not ideal for the retrieval of quality data by satellites, it can lead to an increase in the uncertainty in the outputs, that is to WaPOR data produced at that time.  These layers allow users to see areas (pixels) where the quality of these inputs tends to be high and low. They can evaluate whether their region of interest has historically received high-quality satellite observations, helping them determine if WaPOR data is suitable for their specific application or if supplementary data sources may be needed in areas with persistent quality limitations. The two long term NDVI quality layers (300 and 100m resolutions) represent the average percentage of decades with at least one valid observation over the five-year period between 2018 and 2023 (2018-2023). They are produced once and are derived from the decadal NDVI quality layers.  Similarly, the long term LST quality layer (300m resolution) provides an indication of the quality of the land surface temperature input data through the average percentage of valid observations over the same five-year period (2018-2023). It was produced once and is derived from the decadal LST quality layers. 

More about the app here: https://data.apps.fao.org/?lang=en&share=f-04a1d02a-6114-4c24-b484-6c09c20e8940