This document discusses the application of Geographic Information Systems (GIS) in horticulture. It begins with definitions of GIS and describes its key components including hardware, software, data, people, and methods. It then outlines various data models and related technologies. The document focuses on applications of GIS and remote sensing in horticulture such as precision farming, production prediction, spatial distribution mapping, site suitability analysis, and habitat identification. It provides examples of GIS analyses including land suitability modeling and risk mapping for crops. The challenges and future scope of using GIS in horticulture are also mentioned.

1. APARNA VELURU,
ROLL NO:5003,
MSC,HORTICULTURE
GIS AND ITS APPLICATIONS
IN HORTICULTURE

2. Geographic Information Systems
Describing Our WorldDescribing Our World
• We can describe any
element of our world
in two ways:
Attribute Information:
What is it?
Species: Oak
Height: 15m
Age: 75 Yrs
Location Information:
Where is it?
51°N, 112°W

3. Definition:
• A GIS is a computer based tool for mapping ,analyzing
things that exist and events that happen on earth.
(OR)
• A database system in which most of the data are
spatially indexed, and upon a set of procedures
operated in order to answer queries about spatial
entities in the database.
Smith et al,1987
Burrough,1986

4. Components of GIS:
A working GIS integrates five key components:
 Hardware
 Software
 Data
 People
 Methods
 General purpose GISs essentially perform five processes or tasks:
Input Manipulation Management Query and Analysis
Visualization
1. Simple questions
2. Analytical questions
3. Proximity analysis
4. Overlay analysis

5. Points
Lines
Areas
Data Models: Raster vs. VectorData Models: Raster vs. Vector
Vector GIS is composed of points, lines, and polygons (areas) Raster GIS
is composed of raster's, or cells

6.  Desktop mapping
 CAD
 DBMS
Remote sensing
 GPS
Related technologies:

7. Special features
On-line Digitization
Map Coordinate Systems Conversion
Spatial Interpolation
3D Display
Mapping Where and What Things Are

8. GIS and its uses

9. Application of these technologies in Horticulture :
 Precision Farming
 Production prediction
 Spatial distribution map
 Site suitability for cultivation of crops
 Soil classification land use planning
 Habitat identification and biodiversity conservation
 Monitoring stress

10. Rain fall
suitability
Altitude
suitability
Ground
truth
observation
Habitat
identification
based on
existing data
Model for crop suitability and habitat identification (Ecological niche
modelling)
Input
 sample record data,point vector
layer
 background (environmental
data), raster data (usualy in ASCII
format)
If environmental layers come from
different sources:
 the same spatial resolution,
 same coordinates of each pixel
(initial pixel),
 each layer must contain equal
number of pixels.
Predictive distribution models
Eg: BIOCLIM, MAXENT, GARP etc

11. GIS-Prediction of Risk maps

12. Data inputData input Rain fall/temperature
Soil type/topography
Rain fall/temperature
Soil type/topography
Paper mapsPaper maps Rain fall
Temperature
Soil type
topography
Rain fall
Temperature
Soil type
topography
Vector layersVector layers
Prepare soil pH
map by soil type map
Prepare slope map by topography map
Prepare soil pH
map by soil type map
Prepare slope map by topography map
Conversion
to raster
format
Conversion
to raster
format
Highly suitable-4
Moderately suitable-3
Marginally suitable-2
Not suitable-1
Highly suitable-4
Moderately suitable-3
Marginally suitable-2
Not suitable-1
Reclassification of thematic
layers
Reclassification of thematic
layers data processingdata processing
Weighting and GIS
overlay analysis
Weighting and GIS
overlay analysis
Suitability maps were created according to the given
criteria with 4 suitability categories
Suitability maps were created according to the given
criteria with 4 suitability categories
Land suitability classification for tomato and cabbage by using GIS technique
Jayasinghe et al.,2010

13. According to the suitability map, 50,400 hectare 25,
68,900 hectare of land area of land area in Sri
Lanka could be identified as not suitable for
growing Tomato and cabbage crops which might
be due to the high rain fall and high temperature
,low elevation.
Cont…
Jayasinghe et al.,2010
Cropland suitability classification can be considered as
Prerequisite for optimum utilization of available land
resources for sustainable agricultural production

14. Site suitability for turmeric production in India-A GIS interpretation
Site suitability map of turmeric drawn with the
help of Eco-crop model DIVA - GIS
Significance: environmental suitability is an important aspect which has direct impact
on the productivity of the crop
Parthasarathy et al.,2007
Optimum climatic
conditions for
cultivation collected
from literature
DIVA - GIS
Prediction of
suitability map
Collection of data on
area, production and
preparation of graphs,
Maps

15. Area map of zinger
Productivity map of
zinger
Suitability map of zinger by DIVA-GIS Parthasaradhy et al.,2007
Site suitability map for Zinger by using GIS

16. Site:kanolibara river basin of sub
humid tropical ecosystem of
central India
Data: Images from remote
sensing + field surveys
multi criteria overlay analysis
Final layer reclassification-
based on index values
17-Biophysical land units
Recommendation of crops
L.F-25%
S.D-10%
L.C-15%
SL-20%
HG-10%
EL_10%
Obi Reddy et al.,2004

17. Cont…
RS and GIS approach helps to characterize biophysical units more effectively to
understand their biophysical potentials, problems and stress environment. also
helps to prepare and execute site specification plans for optimum utilization of
available resources to maximize the productivity as well as maintain ecological
balance.
Obi Reddy et al.,2004

18. parameter slope azimuth soil vegD temp elevation
Criteria 10-20% E,S-E silt-loam 2standsm2 1.5C 1500-1800mStudy
area
Lilium ledibourii in Ardabil province of Iran
Software-GIS
Makhdum model
Data collection in study area
Modelling
Predicted habitat of
L.ledebourii
Fataei et al.,2011

19. Fig: Geographical distribution of Lilium ledebourii
The identified potential new
habitats In Ardabil province
near by its original habitat
Cont….
Fataei et al.,2011
Significance:
They were identified potential habitats for protection of natural monument as well
as increasing the cultivation scope of L.ledebourii .

20. Estimating the global severity of potato late blight with
GIS-linked disease forecast models
LB forecast models- Blitecast,
Simcast
Climate data& its
interpolation
Determination of
growing seasons
Modelling &
Analysis by
using GIS
Global
zonation
Hijmans et al.,(2000)
Blitecast

21. Simcast
Hijmans et al.,(2000)
No of sprays(Observed leaf
wetness)
Noofsprays(Predictedleaf
wetness)
No of sprays (Observed)
Noofsprays(Blitecast)
Conclusion:
Global zonation of LB results in the decision
making about resource allocation for
research, Safe and optimal use of
Fungicides

22. NRSA facilitates several remote sensing & GIS application projects for
natural resources and environmental management catering to food
security, water security, energy security and sustainable development.
SAC has been engaged in the development and dissemination of remote
sensing and GIS technologies for national development.
IRS data is being used for a diverse range of applications such as crop
acreage and production
Supporting institutions and data providers

23. Automation of land evaluation procedures for a variety of
applications using GIS techniques.
Extending precision farming database to smaller farm size and /
or diverse crops/cropping systems.
 More accurate yield models, maps
 Identifying ways and means of reducing the cost of RS, GIS and
precision farming technologies
Errors in GIS
Challenges

24.  GIS along with spatial technologies like GPS and
Remote sensing will be a key to improving farm
practices in the coming decades.
 It plays a potential role decision making and monitor,
analysis, control the production parameters with the
aim to optimize the expanse and ecological effects
and to increase the income.
Conclusion

25. THANK YOU