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Doctoral seminar on
Pest surveillance, Remote sensing and GIS- role in IPM
Course-in-chargeDr. N. C. VenkateswarluProfessor and HeadDept of Entomology
Presented byV, ShilpakalaTAD/2014-12
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1. • Introduction
2. • Pest surveillance
3. • Remote sensing
4. • GIS
5. • Conclusion3
Pest surveillance
Monitoring pests and their natural enemies is a fundamental tool
in IPM - for taking management decision
Remote sensing
Collection of remotely sensed data.
GIS
Collection of both hardware and software for dealing with spatial
information.
1. Introduction
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2. Pest Surveillance
O Refers to the constant watch on the population dynamics
of pests, its incidence and damage on each crop at fixed
intervals to forewarn the farmers to take up timely crop
protection measures.
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Three basic components of pest surveillance are
O Determination of
a. the level of incidence of the pest species
b. the loss caused by the incidence
c. the economic benefits, the control will provide.
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Objectives of Pest Surveillance
O to know existing and new pest species
O to assess pest population and damage at different
growth stage of crop
O to study the influence of weather parameters on
pest
O to study changing pest status (minor to major)
O to assess natural enemies and their influence on
pests
O effect of new cropping pattern and varieties on pest
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SurveyAn official procedure conducted over a
defined period of time to determine thecharacteristics of a pest population or todetermine which pest species occur in an area(ISPM No. 5)
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Roving survey
O Assessment of pest population/damage from randomly selected spots representing larger area.
O Provides information on pest level over large area.
O Large area surveyed in short period
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Fixed plot survey
O Assessment of pest population/damage from a fixed plot selected in a
field.
O The data on pest population/damage recorded periodic from sowing
till harvest. e.g. plots randomly selected from in
of crop area in case of
From each plot 10 plant selected at random.
O Total tillers and tillers affected - in these 10 plants counted.
O Total leaves and number affected - ( % damaged leaves).
O Population of - number/tiller.
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Other types of survey
O Qualitative survey - Useful for detection of pest
O Quantitative survey - Useful for enumeration of pest
According to ISPM definitions, O detection,O monitoring O delimiting surveys.
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Pest Survey Sites
O Reported presence and distribution of the pest.
O Biology of the pest. O Distribution of host plants of the pest and
especially of their areas of commercial production.
O Climatic suitability of sites for the pest.
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Timing of survey procedures may be determined by:
• Life cycle • Phenology of the pest and its hosts • Pest management programmes • Whether the pest is best detected on crops in
active growth or in the harvested crop.
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Sampling Techniques
O Absolute sampling - To count all the pests
occurring in a plot
O Relative sampling - To measure pest in terms
of some values which can be compared over
time and space e.g. Light trap catch,
Pheromone trap
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O Methods of sampling
a. In situ counts - Visual observation on number of insects
on plant canopy (either entire plot or randomly selected plot)
b. Knock down - Collecting insects from an area by
removing from crop and (Sudden trap) counting (Jarring)
c. Netting - Use of sweep net for hoppers, odonates,
grasshoppers.
d. Norcotised collection - Quick moving insects
anaesthesised and counted
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e. Trapping - Light trap - Phototropic insects
O Pheromone trap - Species specific
O Sticky trap - Sucking insects
O Bait trap - Sorghum shootfly - Fishmeal trap
O Emergence trap - For soil insects
f. Crop samples
Plant parts removed and pest counted
e.g. Bollworms
O Stage of SamplingO Sample Size
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Pest Negligible% Low Moderate Severe Very severe
Leaf miner < 1 % 1-5 % 6-15 % 16-30 % > 30 %
Butterfly < 1 % 1-5 % 6-10 % 11-15 % > 15 %
Survey and surveillance of insect pests and their natural enemies in
acid lime ecosystems of south coastal Andhra Pradesh
Sreedevi (2010)
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Scoring of population/damage levels of major acid lime insect pests
Pest Management in Horticultural Ecosystems, 16(2): 131-135
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Pest management in horticultural ecosystems, 16(2): 131-135
Pest Management in Horticultural Ecosystems, 16(2): 131-13519
DRR Annual progress report 2013, vol.2-Entomology
O BPH- 24 centers with maximum 54528 insects/week- during 47th week at Raipur.
O WBPH- 21 centers (5683 insects/week)-during 42nd week at Gangavathi.
O Planthoppers continue to be second major pests.
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The art and science of obtaining information
about an object, area or phenomenon through the analysis
of data acquired by a device that is not in contact with
the object under investigation (Lillesand et al., 2004)
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History of Remote Sensing
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History of Remote Sensing
O first meteorological satellite was launched by US on 1st
April, 1960 for weather forecast, movement of hurricanes
and other associated uses. It was named as earth resources
technology satellite (ERTS) – well suited for agricultural
responses.
O These satellites are now referred to as LAND SAT.
O First remote sensing satellite in India was launched in 1988,
named as IRS(Indian Remote Sensing).
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Areas ofAPPLICATION
OGeologyOHydrologyO Sea IceO Land Cover & Land UseOMappingOOceans & Coastal MonitoringOAgricultureOForestry
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Agriculture
• Crop acreage estimation
• Crop modeling for yield & production
forecast / estimation
• Crop & Orchard monitoring
Scope
• Timely availability of crop statistics
for decision making & planning
• Crop growth monitoring
• Soil status monitoring
• Regular reports regarding total area
under cultivation
Benefits
Banana Plantation – Muhammad Pur (Ghotki)
Mar 05, 2006, RecoveryJan 12, 2006, DamageDec 16, 2005, Pre-Frost
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Forestry
• Satellite image based forest
resource mapping and updation
• Forest change detection
• Forest resource inventory
• GIS database development
Scope
• Availability of baseline information
• Planning for afforestation strategies
• Futuristic resource planning
• Sustainability of environment
• Wild life conservation & development.
Benefits
Sarhad Reserve Forest (Ghotki)
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Types of REMOTE SENSINGActive Remote Sensing
Passive Remote Sensing
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Types of Remote Sensing Platforms
O field-based (ground based),
O mounted on aircraft(airborne)
O satellites (space borne).
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Ground based
O Spectroradiometry is the technique of measuring the
spectrum of radiation emitted by a source.
O In order to do this the radiation must be separated
into its component wavebands and each band
measured separately.
O It is achieved by diffraction grating technique
within the spectroradiometers to split the radiation
entering the system into its constituent wavebands.
O A suitable detector is then used to quantify the
radiation of each wavelength (ASD 1999 ) .
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Concept
Stresses interferes with photosynthesis
and physical structure of the plant (Hatfield and
Pinter, 1993).
O causes changes in pigment, chemical
concentrations, cell structure, nutrient, water
uptake, and gas exchange. (Raikes and Burpee
1998).
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Spectral response
REMOTE SENSING DATA
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REFLECTANCE IN
VEGETATION
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Typical spectral reflectance curve of healthy vegetation depicting
different absorption peaks
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• Downward or sideward looking sensors are mounted on an
aircraft to obtain images of the earth's surface.
• It has the capability of offering very high spatial resolution
images.
• But low coverage area and high cost per unit area of ground
coverage.
• It is not cost-effective to map a large area using an airborne
remote sensing system.
• Airborne remote sensing missions are often carried out as
one-time operations, whereas earth observation satellites offer
the possibility of continuous monitoring of the earth.
AIRBORNE REMOTE SENSING
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AIRBORNE REMOTE SENSING
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Spaceborne remote sensingO In spaceborne remote sensing, sensors are
mounted on-board a spacecraft (space shuttle
or satellite) orbiting the earth.
O The geostationary orbits are commonly used
by meterological satellites.
O Located at a high altitude of 36,000 km.
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Spaceborne remote sensing provides the
following advantages:O Large area coverage.
O Frequent and repetitive coverage of an area of
interest.
O Quantitative measurement of ground features using
radiometrically calibrated sensors.
O Semiautomated computerised processing and
analysis.
O Relatively lower cost per unit area of coverage.
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Optical/thermal imaging systems can be classified
according to the number of spectral bands used:
O Monospectral or panchromatic (single wavelength
band, "black-and-white", grey-scale image) systems
O Multispectral (several spectral bands) systems
O Superspectral (tens of spectral bands) systems
O Hyperspectral (hundreds of spectral bands) systems
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• A hyperspectral image consists of about a hundred or
more contiguous spectral bands.
• Applications in fields such as precision agriculture
(e.g. monitoring the types, health, moisture status
and maturity of crops), coastal management (e.g.
monitoring of phytoplanktons, pollution).
• Currently, hyperspectral imagery is not commercially
available from satellites.
• There are experimental satellite-sensors that acquire
hyperspectral imagery for scientific investigation
(e.g. NASA's Hyperion sensor on-board the EO1
satellite, CHRIS sensor on board ESA's PRABO
satellite).
HYPERSPECTRAL IMAGE
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Multispectral Images
• A multispectral imagery consists of several bands of
data. For visual display, each band of the image may be
displayed one band at a time as a grey scale image, or in
combination of three bands at a time as a colour
composite image.
• Interpretation of a multispectral colour composite image
will require the knowledge of the spectral reflectance of
the targets in the scene.
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BOTTOM VIEW OF MS4100 MULTI-SPECTRAL CAMERA (A) AND
REGULAR DIGITAL RGB CAMERA (B) ON CESSNA 206.
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DISADVANTAGES OF REMOTE SENSING
Expensive to build and operate!!!!
Measurement uncertainty can be large
Data interpretation can be difficult
need to understand theoretically how the instrument is
making the measurements
need to understand measurement uncertainties
need to have some knowledge of the phenomena you
are sampling
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GEOGRAPHIC implies that locations of the data items are known, or can be calculated, in terms of Geographic
coordinates (Latitude, Longitude)
INFORMATION implies that the data in a GIS are organized to yield useful knowledge, often as coloured maps
and images, but also as statistical graphics, tables, and various on-screen responses to interactive queries.
SYSTEM implies that a GIS is made up from several inter-related and linked components with different functions.
Thus, GIS have functional capabilities for data capture, input, manipulation, transformation, visualization, combinations,
query, analysis, modelling and output.
WHAT IS A GIS ?
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3. GIS
O Geographic Information System
O A GIS is a computer system capable of capturing,
storing, analyzing, and displaying geographically
referenced information; that is, data identified according
to location.
O Practitioners also define a GIS as including the
procedures, operating personnel, and spatial data that go
into the system.
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The History
• First developed in North America, particularly the
U.S. and Canada in the mid-1960s
• Previously been used in natural resources and
environmental research.
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GIS: OLD AND NEW
Traditional GIS
MAP TYPEWRITERMANUAL DRAFTINGTOOLS
New GIS
COMPUTER PLOTTER CD-ROM
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GPS device
It is a device which uses 24 satellites orbiting at 24,200 km above earth to find latitudes, longitudes and altitude of any location on the earth.
• For a forest manager to optimize timber production
• For a geologist to identify the best site to construct dam
• For a geoinformatics engineer to establish a relay station
Unlimited applications…• Site suitability• Erosion modeling• Civil engineering • Urban planning• Forestry• Environmental management• Natural disaster management• Biology• Geology • Mining• Hydrology….
GIS APLLICATIONS
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•Data Acquisition and processing
•Database Management and Retrieval
•Spatial Measurement and Analysis
•Graphic output and Visualization
Basic functions of GIS
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SPATIAL DATARaster
Vecto
rDATA MODEL AND STRUCTURE
RASTER MODEL VECTOR MODEL53
PROCESS OF IMAGE
INTERPRETATION
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Hyperspectral radiometry for the detection and discrimination of damage caused by sucking pests of cotton
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Sensitivity curves of damaged and undamaged cotton plants
Thrips damaged Leaf hopper damaged Aphids damaged
Ranjitha and Srinivasan, 2014
Current biotica 8(1): 5-12.
Spectral and spatial properties of rice brown
plant hopper and groundnut late leaf spot
disease infestation under field conditions
Prabhakar et al., 2013
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Multispectral reflectance of rice plants with different levels of BPH severity
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Journal of Agrometeorology 15 (Special Issue-I) : 57-62(March 2013)
Classified satellite image depicting BPH damage in east
godavari district, A.P. During 2007
64Journal of Agrometeorology 15 (Special Issue-I) : 57-62(March 2013)
DIFFERENTIATING STRESS INDUCED BY GREENBUGS ANDRUSSIAN WHEAT APHIDS IN WHEAT USING REMOTE SENSING
Green bug Russian wheat aphid
Older leaves Younger leaves
Less visible More visible
Chlorophyll a reduced than b Both a and b reduced
No impact on carotenoids Sig. loss of carotenoids
Decreased
Reflectance in NIR(cellular lysis)
Increased in NIR (low water
content)
Computers and Electronics in Agriculture 67 :64–70
Yang et al. (2009)
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Use of ground based hyperspectral remote
sensing for detection of stress in cotton caused
by leafhopper (Hemiptera: Cicadellidae)
Prabhakar et al., 2011
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Reflectance spectra of cotton plants infested by leafhopper at different levels of
infestation (Grade 0, healthy; Grade 1, lowest; Grade 4, highest
Computers and Electronics in Agriculture 79 :189–19867
Using ground-based multispectral radiometry to detect
stress in wheat caused by greenbug (Homoptera:
Aphididae) infestation
Computers and Electronics in Agriculture 47 (2005) 121–135
Yang et al.,2005
• Out breaks appear every year• Early detection – critical part of IPM • Hand held Cropscan Radiometer MSR 16R• Band centered at 694 nm and vegetative
index from bands centered at 800 to 694-identified as sensitive to damage.
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Computers and Electronics in Agriculture 97 : 61–7069
Prabhakar et al., 2013
MEAN REFLECTANCE SPECTRA OF COTTON PLANTS UNDER DIFFERENT GRADES
OF MEALYBUG INFESTATION70
Hyperspectral detection of rice damaged by rice leaf folder (Cnaphalocrocis medinalis)
Computers and Electronics in Agriculture 82 : 100–107
Jianrong Huang et al. (2012)
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Automatic identification and counting of small size pests in
greenhouse conditions with low computational cost
Ecological Informatics 72
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A new invasive insect in Sweden – Physokermes inopinatus: Tracing
forest damage with satellite based remote sensing
• MODIS data• SPOT data• Associated black encrustation absorbs light in
the red band and cancels out the increased reflectance of the damaged needles.
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Forest Ecology and Management 285: 29–37
Olsson et al., 2012
A and B shows spruce forest infested by P. inopinatusand sooty mold
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Coupling historical prospection data and a remotely-sensed vegetation
index for the preventative control of desert locusts
Basic and Applied Ecology 14 : 593–604
Cyril Piou et al., 2013
. Black pixels represent NDVI values = 0, lighter pixels indicate NDVI-values >0
the Akjoujt area between 2001 and 2009the Aioun area between 2001 and 2009
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• Monitoring is backbone of IPM. Farmer must keep continuous vigilance on pest activity on crops.
• Monitoring helps in issuing forewarning and facilitates proper timing of plant protection measures thereby preventing avoidable losses and environmental contamination, and ensuring favourable benefit-cost.
• Remote sensing technique is very useful, less time consuming and cost effective tool for suggesting action plans /management strategies for agricultural sustainability of any region.
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• Remotely sensed images can be used to identify nutrient deficiencies, diseases, water deficiency or surplus, weed infestations, insect damage, hail damage, wind damage, herbicide damage, and plant populations
• GIS is considered one of the important tools for decision making in problem solving environment dealing with geo-information.
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