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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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Phot
o: D
avid
Bra
zier
/IW
MI
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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 dataTeam: Salman Siddiqui, Sajid Pareeth, Kiran M. C., Rajah Ameer,
Darshana Wickeramasinghe, Cai Xueliang, Ajith JayasekareSide Event:Use of Remote Sensing and GIS Tools in the Irrigation Commands to assist planning and management1st. World Irrigation Forum29 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
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
f(x) = 0.98355786470664 x + 0.416053382334002
Province wise Cultivated Area in Pakistan1990-91 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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Water for a food-secure world
Current IWMI Mapping Irrigation Areas Irrigated Area Mapping
• South Asia• Asia • Africa
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Water for a food-secure world
• 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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Water for a food-secure world
Image classification steps
Original Image
Segmented Image
ISOCLASS Classified Image
Recoded Image
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Water for a food-secure world
CountryIrrigated 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 AsiaIrrig. Area Map
Comparison : Past and Current Products
2006 GIAM Product
Nepal Example
2012 SAIAM Product
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Water for a food-secure world
Irrigated Area MappingAsia
Based on MODIS (Terra & Aqua)
Product : MOD13Q1 (16Day NDVI Composite)
Spatial Resolution : 250mTemporal Range : Jan. 2009 to Dec. 2011No. Tiles/Images : 4,140
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Water for a food-secure world
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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Water for a food-secure world
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 AnalysisFourier transformation to analyze the seasonality
Dominant annual cycle indicate single crop areas
Dominant semi-annual cycle indicate irrigated double crop areas
NDVI time seriesFirst harmonicSecond harmonicThird harmonic
Methodology : Asia
Manual Method
stackImagestack
ImagestackImagestack
ImageNDVI 3yearImage 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 SignatureExtraction
Signature textSignature
textSignature textSignature
textSignatures
SignatureAggregation
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 SignatureAnalysis
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Irrigated Area MapAsia
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Water for a food-secure world
Irrigated Area Mapping : Africa
Based on MODIS (Terra & Aqua)
Product : MOD13Q1 (16Day NDVI Composite)
Spatial Resolution : 250mTemporal Range : Sept. 2010 to Sept. 2012No. 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.
Methodology adopted for AfricaAnnual
MODIS – 16 day NDVI
Temporal Fourier Analysis
Mean NDVI Amplitude 1
Amplitude 2 Phase 1 Phase 2TrendStandard
deviation
Training Sites from Google
Earth
Rule based Classification Land Cover
Decision Tree
Analysis
Global Ecoregions
Extract Pixel ValuesEcoregion 1
Agriculture
Amp 2 >
Amp 1
Irrigated + Rainfed
FALSE
Monthly Rainfall
Temporal Fourier Analysis
Rainfall Phase 1
Analyse concurr
ence
RAINFEDIRRIGATED
TRUE
MISMATC
H CONCURRENT
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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 IssueThe 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!!!
