ASAP - Anomaly hot Spots of Agricultural Production, a new early warning decision support system

Felix Rembold, Michele Meroni, Ferdinando Urbano Joint Research Centre of European Commission

Food Security Unit

MultiTemp 2017

• Growing number of online VISUALIZATION tools make available remote sensing and agro-meteo data to analysts

But mostly remain pixel-based and do not provide explicit early warning messages about agricultural problems

Why a new system?

ASAP goal • Provide (to non-remote sensing experts) timely warnings and short narrative

in case of agricultural problems

ASAP 2-steps workflow 1. Automatic warning classification. Global, every 10 days at first sub-national level

2. Analysts assessment of triggered warnings to validate and describe hotspots with short narratives. >80 countries of interest, every month at national level

The final selection of hot spot countries depends on expert judgement, supported by the warning classification system and auxiliary information.

ASAP customers • EC and EU delegations • GEOGLAM CM4EW users • Other multi-agency food security assessments

(IPC, Cadre Harmonisé) • Agricultural experts in general

Goal: automatically apply a standardized analysis of RFE & NDVI to be proposed to the analyst

Globally

Targeting cropland and rangelands (where and when they grow)

Step 1. Warning classification scheme

Warning classification, WHERE Level of aggregation: GAUL1

Targets: cropland and rangeland layers (anomalies occurring elsewhere are neglected)

Focus: drought-related production deficit

Annual Climatic Water Balance (P-ET0)

█ Only NDVI

█ NDVI & RFE

Warning classification, WHEN

Update every 10 days during the average growing season period

We rely on pixel-based Land Surface Phenology, as derived from NDVI time series analysis (SPIRITS)

SOS25%

SEN75%

EOS35%

MAX

“Expansion” “Maturation” “Senescence

Classification is made only when at least 15% of the total crop/rangeland area of the GAUL is in the growing season (SOS<t<EOS)

Anomalies occurring outside this target period are neglected

Cropland Active cropsASAP unit

Warning classification, WHAT

Pixel level

Keep track of three possible anomalies (all standardised):

• Cumulative NDVI from SOS

[Z of NDVIc < -1]

• Rainfall, long period

Critical NDVI Critical SPI3

• Rainfall, short period

Critical SPI1

[Z of NDVIc > +1]

Exceptional NDVI

[3-month SPI < -1] [1-month SPI < -1]

NDVI (METOP @1 km) Precipitation (ECMWF @25 km)

(HRES analysis model & ERA-Interim)

SOS25%

SEN75%

EOS35%

MAX

Warning classification, HOW

Admin level

Look at the Area Fraction classified as “Critical”

𝐶𝐶𝐶𝐶𝐶𝐶𝑥𝑥 = 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑙𝑙𝑎𝑎𝑙𝑙𝑎𝑎𝑙𝑙𝑙𝑙𝑎𝑎𝑙𝑙 𝑎𝑎𝑎𝑎 "𝑐𝑐𝑎𝑎𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑎𝑎𝑙𝑙"𝑐𝑐𝑡𝑡𝑐𝑐𝑎𝑎𝑙𝑙 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑡𝑡𝑜𝑜 𝑎𝑎𝑐𝑐𝑐𝑐𝑐𝑐𝑎𝑎𝑎𝑎 𝑝𝑝𝑐𝑐𝑥𝑥𝑎𝑎𝑙𝑙𝑎𝑎

x = SPI1, SPI3, zNDVIc

Any CAF > 25 % will trigger a warning for that admin level

Two conditions to trigger a warning: the area is subject to a severe negative anomaly & the area concerned is relevant

Retrieve the admin median progress of the season (% and phase)

“Expansion” “Maturation “

“Senescence”

Critical

ASAP unitCroplandActive crops

Warning source

(Indicator with CAF > 25%)

zNDVIc +

none

SPI1 U SPI3 U zNDVIc

zNDVIc

Warning levelby warning source and pheno-

phaseExpansion OR maturation

Senescence

Favourable conditions

Favourable conditions

- -

1- -

SPI1 1 -

SPI3 1+ -

2 4

zNDVIc & SPI1 3 -

SPI3 & SPI1 1++ -

zNDVIc & SPI3 3+ -

zNDVIc & SPI3 & SPI1 3++ -

Ranking of warning levels Admin level

The final warning level builds on: Pheno-stage & type of indicator exceeding CAF

RFE-based - Rainfall deficit possibly evolving into poor growth

NDVI-based - Evidence of poor growth

Both - Poor growth & negative prospects

Output of classification The Warning Explorer

11 June 2017

Warnings are automatically sent to analyst dashboard

Assessment made every month at country level

Only ASAP countries are covered (GEOGLAM + DG DEVCO food security priority countries)

Step 2. Analyst assessment

Analyst evaluation assisted by:

Automatically generated reports showing relevant maps and graphs

Local news by JRC Media Monitor tailored queries

Ad-hoc analysis of HR imagery (Landsat 8, Sentinel 1 and 2) in Google Earth Engine

Temporal profiles (NDVI, RFE)

Anomaly maps

Analyst assessment

Overview of past warning levels

Winter wheat area in Western cape, SA

As a result, the automatic warning at GAUL1 is promoted (or not) as:

Analyst assessment output

Minor or major hotspot at country level

Published on the ASAP main page with a short narrative and main background info

Global overview map and narrative

As a result, the automatic warning at GAUL1 is promoted (or not) as:

Analyst assessment output

Minor or major hotspot at country level

Published on the ASAP main page with a short narrative and main background info

Country reports Situation overview Detailed maps/graphs Land cover and phenology

Summary

Automatic warning classification and underlying data updated globally every 10-day on the Warning Explorer web-page mars.jrc.ec.europa.eu/asap/hsds/

Every warning must be verified by the analysts (monthly) to become visible in the ASAP analyst assessment web-page mars.jrc.ec.europa.eu/asap/

Downloadable summary reports are produced for all countries

Development Status

Pre-operational testing by analysts September 2016 – May 2017

Operational and public since May

Near-future improvements

Update of current crop/rangeland masks

new ASAP-GWRSI replacing SPI1

Use of the advanced NRT filtering of MODIS time-series replacing METOP

Thank you! ASAP https://mars.jrc.ec.europa.eu/asap/

Warning Explorer https://mars.jrc.ec.europa.eu/asap/hsds/