Attachments
Agricultural Stress Index (ASI)
The Agriculture Stress Index (ASI) helps show how ‘stressed’ crop areas are by combining vegetation condition and temperature variables. The compiled results are then analysed over time, by comparing current values to the long-term minimum and maximum, and spatially, by aggregating agriculture areas by administrative area. The ASI can also be analysed together with individual variables that make up the ASI, such as Rainfall and Vegetation condition. These are available as separate RFSAN products.
NDVI Difference
The NDVI provides a measure of the amount and vigour (greenness) of vegetation at the land surface. The magnitude of NDVI is related to the level of photosynthetic activity in the observed vegetation. In general, higher values of NDVI indicate greater vigour and amounts of vegetation. Anomalies represent a subtraction of the mean Normalised Difference Vegetation Index (NDVI values) for a 10-day period from current-year values for the same period, rendering an image where negative values (brown) portray less vigorous vegetation than average, and positive values (green) represent areas that are more vigorous in the current year. Mean Anomaly- The long term mean anomaly is a subtraction of the mean NDVI values (2001-2015) for a 10-day period from current-year values for the same period. Previous Year Difference –The difference image is a subtraction of the current year NDVI values from those of the previous year for the same 10-day time period. Anomaly/ Difference Classification: The absolute difference and anomaly images are stretched from -0.3 (brown or less vegetation activity) to 0.3 (green/more vegetation activity) NDVI. The area of relatively no difference is approximately -0.05 – 0.05.
Rainfall Anomaly
The information presented here uses the Rainfall Estimator (RFE) version 2.0 by National Oceanic and Atmospheric Administration’s (NOAAs) Climate Prediction Center (CPC). RFE 2.0 uses techniques to estimate precipitation using cloud top temperature and station rainfall data from approx. 1,000 stations of World Meteorological Organization (WMO) Global Telecommunication System (GTS) to provide accurate rainfall totals. RFE 2.0 obtains the final daily rainfall estimation using a two part merging process, and is then processed into monthly datasets by the RFSAN team. More information can be found at the NOAA CPC website, or email maps@rfsan.org.
Analysis
The results of the rainfall, NDVI and temperatures analysis – all considered in FAO’s Agricultural Stress Index – show that May has been used for harvesting winter crops inside Syria. This is evidenced by the increased use of the colour blue (see legend) in the areas where agriculture plays a significant role. There are still a few areas in the north-west of Syria (e.g. Aleppo and Idleb) that have been badly affected. These areas have typically seen stress over a number of months, so their harvests are expected to have been negatively impacted. Agriculture in the areas of Lattakia and Tartous is expected to have done better, as less than 10 per cent of the areas has been classified as stressed. Note that since the ASI is based on Remotely Sensed data only, and there is no confirmation on what crops have been planted. Precipitation has been below the long term average over Syria for the months of March, April and May (2016). Also, higher temperatures have been observed across the region for the same time period. Together, these have seen vegetation growth to be below average over much of Syria. 2015 saw a higher than expected precipitation and therefore shows a greater NDVI difference for 2016 than compared to the Long Term Average for Syria. Vegetation conditions look good over the northern and central Iraq when compared to the long term average, while north-eastern Syria also shows above average vegetation activity. As we are now in the dry season for the region, any impact on summer crops development (e.g. vegetables, fruit and fodder crops) depends largely on availability and access to irrigation.