Higher resolutions and new data processing capacity are greatly improving our ability to map irrigated areas in Asia and Africa. But areas estimated are higher than national statistics. These differences can be attributed to factors such as inadequate accounting of informal irrigation.

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Water for a food-secure world
Mapping irrigated area:
Development of an automated approach
based on crop phenology through earth
observation data
Team: Salman Siddiqui, Sajid Pareeth, Kiran M. C., Rajah Ameer,
Darshana Wickeramasinghe, Cai Xueliang, Ajith Jayasekare
Side Event:
Use of Remote Sensing and GIS Tools in the Irrigation Commands to assist
planning and management
1st. World Irrigation Forum
29 September to 5 October, Mardin, Turkey

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Water for a food-secure world
Why use RS for Irrigated Area?
• Location of irrigated areas
• Seasonality of irrigation
• Map informal irrigation (GW,
small reservoirs, tanks etc.)
• Overcome limitations of
conventional methods
• Provide operational irrigation
mapping services
An entire state can have one
irrigated area %
Precise location of
irrigation mapped
Single crop Continuous crop
Double crop
y = 0.983x + 0.416
0
10
20
30
40
50
60
70
0 10 20 30 40 50 60 70
Province wise Cultivated Area in Pakistan
1990-91 vs 99-2000
Irrigated areas between 1990-
91 vs. 99-2000 for the 4
provinces is almost the same
as per the Agricultural Census
reports

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Water for a food-secure world
Opportunity to update (G)IAM
• Data available at higher spatial resolution
• Good temporal coverage
• Availability of better hardware and software for
processing large data sets.
• New algorithms in image classification – ‘object based
image analysis’
• Impact of climate change and rapid urbanization is more
visible during last decade

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Current IWMI Mapping Irrigation Areas Irrigated
Area Mapping
• South Asia
• Asia
• Africa

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• MODIS NDVI data set
– 250m resolution
– Available for every 16 days from 2000
onwards
– Global coverage
– Pre-processed standard data product
– The only data set available free of
cost, consistently, with a global
coverage
• IRS – AWiFS
– Spatial Resolution – 56 m
– Large swath – 740 km
– Spectral resolution suitable for
vegetation study
Level 1
Level 2
Data and Method : South Asia

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Image classification steps
Original Image
Segmented Image
ISOCLASS Classified
Image
Recoded Image

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Water for a food-secure world
Country
Irrigated area
(million ha)
Rainfed Area
(million ha)
Total Area
(Irrigated + Rainfed)
Nepal 4.3 0.5 4.8
Pakistan 21 6.7 27.7
Sri Lanka 0.7 0.4 1.1
India 169 31 200
Bhutan 0.2 0.06 0.26
Bangladesh 11 0 11
Total cropped area 206.2 38.66 244.86
South Asia
Irrig. Area Map

8. Comparison : Past and Current Products
2006 GIAM
Product
Nepal Example
2012 SAIAM
Product

9. www.iwmi.org
Water for a food-secure world
Irrigated Area Mapping
Asia
Based on MODIS (Terra & Aqua)
Product : MOD13Q1
(16Day NDVI Composite)
Spatial Resolution : 250m
Temporal Range : Jan. 2009 to Dec. 2011
No. Tiles/Images : 4,140

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Identifying Croplands using Satellite Images
• Diverse reflectance properties according to the crop and
growth stages
• Conventional mapping techniques have limited success
using coarse resolution images
• Need generic methods to separate croplands from natural
vegetation
• Natural vegetation and croplands exhibit different
seasonal characteristics

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Water for a food-secure world
Identifying Irrigated Areas
• Analyze the intra-annual vegetation changes
• Much of Asia has one significant rainfall season
• Natural vegetation undergo one annual cycle of growth
and drying up
• Irrigated, double crop areas likely to have two cycles
• Single crop areas would have one annual cycle
• Fourier transformation of the annual NDVI curve to
identify the cyclic characteristics

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Fourier Analysis
• Used to analyze the harmonic nature
of time-series data
• decompose the complex curve into
individual component curves
• identify the harmonic nature of the
dominant signal
• estimate the time of the wave peak

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Water for a food-secure world
Fourier Analysis
Fourier transformation to analyze the seasonality
Dominant
annual cycle
indicate single
crop areas
Dominant
semi-annual
cycle indicate
irrigated
double crop
areas
NDVI time series
First harmonic
Second harmonic
Third harmonic

14. Methodology : Asia
Manual Method
stack
Imagestack
Imagestack
Imagestack
ImageNDVI 3year
Image Stack
ISO-Data
Classification
(100-1000
class)(100-1000
class)(100-1000
class)(100-1000
class)(100-1000
class)
Classified
Image
(100-1000
classes)
Temporal
Signature
Extraction
Signature
textSignature
textSignature
textSignature
textSignatures
Signature
Aggregation
K mean
Classification
Class
Assignment
Fourier
Smoothing
Filter
Smooth
Temporal
Signature No of peaks
Peak Duration
Mean NDVI
Peak Starting
date(s)
Peak date(s)
NDVI slope
STD NDVI
Peak NDVI
value(s)
Visual
Signature
Analysis

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Irrigated Area Map
Asia

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Irrigated Area Mapping : Africa
Based on MODIS (Terra & Aqua)
Product : MOD13Q1
(16Day NDVI Composite)
Spatial Resolution : 250m
Temporal Range : Sept. 2010 to Sept. 2012
No. Tiles/Images : 1,840
Work in Progress!!!!

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Water for a food-secure world
Mapping Agriculture in Africa - Challenges
• Poor performance of the rapid mapping
techniques used for Asia
• Cropland – Savanna/ Open forest mosaic
• Sparse natural vegetation – low contrast
between agriculture and adjacent open
landscape
• Small farm size – interspersed with natural
vegetation
• Many farms are < 2 ha – MODIS pixel size is
~6.25 ha

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Water for a food-secure world
Approach
• Modified the methods adopted for Asia
• Developing a rule-based, pixelwise mapping technique to
characterize the annual vegetation dynamics
• Derived NDVI based parameters to capture various
aspects of the magnitude and change of seasonal
changes of vegetation
• Rules developed for each eco-region.

19. Methodology adopted for Africa
Annual
MODIS – 16
day NDVI
Temporal
Fourier
Analysis
Mean NDVI
Amplitude
1
Amplitude
2
Phase 1 Phase 2Trend
Standard
deviation
Training Sites
from Google
Earth
Rule based
Classification
Land Cover
Decision
Tree
Analysis
Global
Ecoregions
Extract Pixel
Values
Ecoregion 1
Agriculture
Amp 2
>
Amp 1
Irrigated +
Rainfed
FALSE
Monthly
Rainfall
Temporal
Fourier
Analysis
Rainfall
Phase 1
Analyse
concurr
ence
RAINFEDIRRIGATED

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Water for a food-secure world
Characterizing the seasonality
• Measure of green biomass
• Harmonic / cyclic characteristics on vegetation change
• Measure of intra-annual variability of green biomass
• Trend

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Water for a food-secure world
• Ecoregion wise
classification
• Training sites for various
land cover types
• Classification rules
developed through
Classification Tree
Analysis
Rule-based classification

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Water for a food-secure world
Mapping irrigated areas - Africa
• Identify areas with a significant semi-
annual cycle of vegetation change
• Use the components resulted from
Fourier analysis
• Areas with two growing seasons are
identified with dominance of the second
harmonic term
• Demarcate as irrigated areas

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Water for a food-secure world
Mapping irrigated areas - Africa
• Areas where annual cycle is prominent may consist
of both irrigated and rainfed areas.
• Compare the correspondence of maximum
vegetation growth in a year with the rainfall season.
• A mismatch between these two indicate higher
chance for presence of irrigation.

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Water for a food-secure world
Mapping irrigated
areas - Africa

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Water for a food-secure world
Critical Issue
The areas estimated are higher than the national statistics.
These differences have been attributed to factors such as:
• Inadequate accounting of informal irrigation (e.g., tanks, minor
reservoirs, and ground water) statistics in the National
statistics;
• Better understanding of the issue of resolution in influencing
area;
• Misrepresentation of the minimum mapping unit areas; and
• Better understanding of definitions of irrigation (e.g.,
supplemental irrigation).

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Water for a food-secure world
Thank you!!!