Rajah Ameer, Salman Siddiqui, Aditya Sood, Herath Manthrithilake, Ranjith Ariyaratne Sri Lanka Geospatial Forum 10 June 2013

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Water for a food-secure world
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Rajah Ameer, Salman Siddiqui, Aditya Sood, Herath
Manthrithilake, Ranjith Ariyaratne
Sri Lanka
Geospatial Forum
10 June 2013
Monitoring Spread
of Agro-wells in
Jaffna using
Hi-resolution
Images

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Water for a food-secure world
IWMI and Geo Informatics
• Rainfall Estimation from
NDVI using Wavelet
Transformation
• Flood analysis using
MODIS time series
images
• Irrigated Area Mapping
for SA, Asia and Africa
• Land use and Land
cover changes in
Cambodia and
Myanmar

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Water for a food-secure world
IWMI and Geo Informatics
• Time series analysis of Boro
paddy area in West Bengal
• Mapping of Snow Cover
and Snow Melt changes in
HKH region
• -----------------------
• Managing and
Dissemination of Spatial
Data
• Development of Water Data
Portal and Sri Lanka Water
Information System
• Development of Specific
Data Portal for Specific
Project

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Spatial Resources
• Both proprietary and open source software
used for RS/GIS
• Database – Open Source
• Web Map Servers – Proprietary & Open
Source
• High-end Workstations for Processing
• Storage space - 50 TB

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Introduction
• Groundwater is the primary
source of fresh water in Jaffna
district
• Rainfall is inadequate or occurs
during one season only.
• Farmers are interested in
cultivating high-value crops which
are in turn high water-demanding
as well.
• Ground water aquifer is shallow
• Agro-wells are large-diameter
which allow larger quantities of
water to be extracted at a time for
irrigation.
• Jaffna already has a salinity
problem, which is exacerbate due
to this over-extraction of water
from agro-wells.

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Introduction
• Hence to preserve the quality
of groundwater in Jaffna, it is
important to properly manage
and monitoring the agro-wells
in the district.
• Immediate requirement for the
management of agro-wells for
the sustainable development
of the Jaffna District.
• For this purpose, identification
and location (geo-referencing)
of agro-wells are very
important to study and manage
the spatial distribution of agro-
wells

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Objectives
– To develop a
methodology to extract
agro-wells using high
resolution images
– To map agro-wells
distribution in the
whole Jaffna district
– Identify agro-well hot
spots

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Data
• WorldView-2 and QuickBird-2
• 12 Different dates images from 2010 and
2011
• Area ~1,200 Sq. km
• Size ~ 250 GB

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Methodology
Shape
Size
Multispectal Image Panchromatic Image
Pansharpening
Agriculture area Wells
Feature Probability
Training Samples
Probability Threshold
Training Sample
Feature Probability
Segmentation
Filtering
Vectorization
Probability Threshold
Multiclass Feature
Extraction
Input Image Mask Agriculture Area
Filtering
Vectorization
Geometry of Object (Well)
Single Feature Extraction
OBJECTBASED
Input Image

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Extracting Agriculture area
a) Original XS image b) probability for a one class c) segmented and filtered image d) segments converted
vector e) extracted vector after applying the probability threshold f) Extracted agriculture lands

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Extracting Agro-well
a) Agriculture masked image from pansharpen image b) Probability layer for wells c) Pixels selected using probability threshold d)
Filtered pixels of wells e) converted vector objects f) agro wells on the agriculture land after performing geometric cleaning and
template matching

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Results

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Results

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Results
No. of Identified Agro-wells : 19,905 (excluding Delft Island)
Agro-wells are not evenly distributed
Some areas have high agro-well density

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Results – Agro-well Density

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Results - Agro-well hot spots

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Validating the Result
• Filed visit for
Validation
• 646 agro-wells
randomly picked
Ground
Image
Agro-well No Agro-
well
Agro-well 581 1
No Agro-
well
64 0

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Validating the Result
• Error of Omission
=9.93%
• Error of
Commission=0.17%
• Overall
Accuracy=90.07%

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Another Application: Counting rooftops in Jaffna to model rainwater
harvesting

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Another Application: Counting rooftops in Jaffna to model rainwater
harvesting

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Discussion
• Tree shadows
confuse with well
• Wells partially or fully
covered by trees are
sometimes difficult to
be identified

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Discussion
• Most of the time
accuracy depends on
the quality of the
image

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Water for a food-secure world
Conclusion
• Hi-resolution image and object based
classification methodology are good
enough to extract Agro-wells
• Policy should be developed to control
digging more wells and over extraction of
water in the indentified agro-well hot spot
areas

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Water for a food-secure world
Recommendation
• To improve the accuracy
– Use LIDAR if possible
– Same date and same sensor images
• Similar method can be applied for different kind of feature
extraction in the island using High resolution images
• Possible Usage
– Number of Wells in the dry zone
– Impact on agriculture yield/production
– Optimum Ground Water Extraction
– GW Quality studies
– Rainwater Harvesting

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Water for a food-secure world
Landsat 8
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