Normalized difference vegetation index (Khongor, Mongolia - Seasonal - 15m)
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✦ Suggested by OrionAIThe Relative Water Deficit dataset represents the water deficit per pixel computed as 1 minus the ratio of ETa over ETx (max crop ET) over MOFALI center pivots in Khongor, Mongolia for the Kharif season (July to October) 2019. **Data publication:** 2020-01-01 **Supplemental Information:** Unit: n.a. **Contact points:** Metadata Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) Resource Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) **Data lineage:** 1 minus the ratio of seasonal ETa over maximum crop seasonal ET **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The Above Ground Biomass Production (AGBP) is computed using vegetation index-based approach in PySEBAL and aggregated over MOFALI center pivots in Khongor, Mongolia for the Kharif season (July to October) 2019. **Data publication:** 2020-01-01 **Supplemental Information:** Unit: Kg/ha **Contact points:** Metadata Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) Resource Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) **Data lineage:** Seasonal data obtained by adding all the monthly AGBP maps from July to October 2019 **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
Actual EvapoTranspiration over MOFALI center pivots study area in the Khongor, Mongolia, for the Kharif season (July to October) 2019. **Data publication:** 2020-01-01 **Supplemental Information:** Unit: mm/season **Contact points:** Metadata Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) Resource Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) **Data lineage:** Seasonal data obtained by adding all the monthly ETa maps from July to October 2019. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The map represents the water flux per pixel computed as precipitation minus ETa over MOFALI center pivots in Khongor, Mongolia for the Kharif season (July to October) 2019. **Data publication:** 2020-01-01 **Supplemental Information:** Unit: mm/season **Contact points:** Metadata Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) Resource Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) **Data lineage:** Seasonal Precipitation minus seasonal ETa. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The Biomass Water Productivity (WPb) is computed by dividing Biomass by ETa and aggregated over MOFALI center pivots in Khongor, Mongolia for the Kharif season (July to October) 2019. **Data publication:** 2020-01-01 **Supplemental Information:** Unit: Kg/m3 **Contact points:** Metadata Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) Resource Contact: [Sajid Pareeth](mailto:S.Pareeth@un-ihe.org) **Data lineage:** Seasonal data obtained by adding all the monthly AGBP maps from July to October 2019 **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The long-term NDVI quality layer is produced as a summary of the quality for the entire time period (2009 to date). Pixel values indicate the percentage of good NDVI observations over the entire time period. The data is provided from January 2009 to 2023. **Data publication:** 2021-01-01 **Supplemental Information:** No data value: 255 Unit: % Map code: L3-ODN-QUAL-NDVI-LT **Citation:** FAO 2018. WaPOR Database Methodology: Level 3. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** The long-term NDVI quality layer is produced as a summary of the quality for the entire time period (2009-2019). Pixel values indicate the percentage of good NDVI observations over the entire time period. While the dekadal NDVI Quality layer shows the quality of the data for a specific time of year, the long-term NDVI quality layer has been added to give users a quick overview of the areas that tend to suffer more cloud cover. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
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