IRJET- Use Geotechnical to Analyze Agricultural use Changes to Support Urban Planning Policies

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 7638
Use Geotechnical to Analyze Agricultural Use Changes to Support
Urban Planning Policies
Shadi Z. M. Kuhail
skouhail@ucas.edu.ps
Master of Geography and GIS
Coordinator of GIS Specialization
Lecturer in Information Technology Department
University College of Applied Sciences - Gaza. Palestine
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Abstract:The study aimed at analyzing satellite data to
track the change in agricultural use in Gaza governorates by
using geographic information systems and remote sensing
techniques, in addition to determining the land plots that are
considered the most appropriate in directing urbanization
away from the waste of agricultural lands. The study also
showed an overview of information systems Geographic and
Remote Sensing As an optimal technical technique used in
analysis, the study showed that the use of remote sensing
technology cannot be dispensedthroughtheanalysisofspatial
visualization to calculate the area of agricultural land in
ancient times Recently, the study showed that the use of
cartographic modeling to arrive at the identification of
appropriate vouchers for agricultural activities is more
efficient than the methods used in local institutions.
Key Words: Geotechnical-Agricultural-GIS-Remote Sensing-
Farmland- Model Builder.
1.INTRODUCTION
Urban growth is one of the most important human
phenomena, and the rapid growth of urban populations has
become a major danger. The population of cities with more
than 10,000 people jumped from 700 million in 1950 to 2.3
billion in 1990. According to UN estimates, Cities of this
category to about 5.5 billion people in 2025.(1)
This rapid increase of the population will inevitablyleadtoa
rapid expansion of the urban mass and may be at the
expense of agricultural land. The study of land use is one of
the subjects that require high accuracyandgreatpotential in
producing detailed maps and detailed databases to include
the development of chronological analysis of maps. Of the
use of remote sensing techniques because it is capable of
handling a huge amount of space images and conducting
many computerized statistics and processes.
1.1 Subject of study
The governorates of Gaza witnessed a significant urban
expansion at the expense of agriculturallandanddidnotstop
the urban growth as long as there are needsofthepopulation
of the urban cluster so the subject of the study in answer to
the following questions:
1. Is the expansion of the urban block has a negative impact
on agricultural land?
2. Can maps be provided showing the distribution of current
and future agricultural land?
3. How geotechnical techniques are used to analyze satellite
data?
1.2 Objectives
1. The use of GIS technology and remote sensing in the
analysis of satellite data
2. Study of the change in the area of agricultural land from
1975 to 2018 using remote sensing.
3. Expected calculation of agricultural land in 2030.
2. Method of analysis
Remotesensingprogramsvaryamongthemselvesintermsof
accuracy in the analysis of satellite images, but there are
software gaps vary from one program to another, but Eardas
Imagingthemostaccurateandcomprehensiveprograms,and
the process of building the database in the programs of the
sensor pass through many stages, combining,merging,initial
processing and interpretation.
The spatial data collection for the periods 1975-1985-1995,
2005-2015-2018, according toUTM-WGS84ZONE36N, was
done by four readings per period to meet the need of the
sequential analysis of the average seasons of the year
because there are plants grown in the summer and another
in the winter, A visual rating of each period was completed
and then collected and a network map of the analytical
medium was produced.
Fig -1: Stages of data analysis and satellite images

The reflected radiation from agricultural land is influenced
by several factors, the most important of which is the
roughness and softness of the vegetation cover and the
materials it contains. The radiation reflected from the green
trees is different from the radiation reflection of dry trees.
Therefore, it is possible to estimate the area of agricultural
land and tree density (2).
Analysis of chlorophyll in the water, which reflectsthecycle
of amphibian plants that affect the nature of the reflected
radiation. Water containing large quantities of suspended
sediments reflects visible wave radiation more than pure
water. Here in the Gaza Strip, In satellite images accurately
when applying the average analytical approach to
classifications by seasons of the year.
Table-1: Results of analysis of satellite images of Farmland
Governorate Gaza km2
year
RafahKhanYounesMiddleGazaNorth
12.0133.3622.3829.4130.161975
11.1830.6723.0826.0320.721985
11.1528.4121.7624.1615.381995
9.3223.8418.2219.1811.222005
17.5728.0819.2013.379.512015
17.3129.1313.3713.109.662018
The table shows that there is a decline in the area of
agricultural land from 1975 to 2018 for urban use. It is also
evident that there is an increase in agricultural land in Khan
Younis and Rafah from 2005 to 2015 due to the withdrawal
of the Israeli occupation from the settlements in the Gaza
Strip. A slight increase in the agricultural area from 2015 to
2018 at the level of most governorates in view of the
encouragement of the Ministry of Agriculture on agriculture
and the identification of crops for self-sufficiency.(3).
Chart -1: Development of the agricultural land area
3. data analysis
The results of the analysis are used for theyears 1975-1985-
1995-2005-2015 using the output data produced by the
Markov chain analysis within the IDRISI environment. An
application model was implemented for the first half of
2015. This model uses the results of the years precedingthis
model. Which shows the expectation and change in the
expansion of the urban mass, the standard KAPA model is
used to test the validity of this data. If the reliability ratio is
more than 70% here we acknowledge its validity. If the
KAPA model is a measurement of less than 70% correct.(4)
Fig -2: classification and analysis of satellite images
In terms of the data of this research, the measurement of the
Kappa IDRISI model using a validated tool was given a kaba
level of 0.9314, a kappa for the information used 0.8229, a
kappa for the cell level of 0.8325 and a kappa for the class
accuracy of 0.8951, all above 0.7. This gives a high analytical
index. Forecasts for 2030.(5)
Table-2: Classification of agricultural use by seasons / km2
Year January April July October average
1975 144.25 137.56 122.32 105.26 127.35
1985 118.85 116.56 112.21 98.99 111.66
1995 113.86 110.97 98.59 79.99 100.87
2005 91.26 89.19 82.69 63.99 81.79
2018 101.86 100.19 80.26 68.71 87.75

4. Predict
Table-3: Expected results 2030 / km2
Governorate Gaza 2030
RafahKhanYounesMiddleGazaNorthType
26.1743.4937.8134.5036.60Urban
9.1513.471.455.462.68agricultural
The above table shows that there are expectations of a
further decline in agricultural land according to the
projections of 2030. It is also noted that there are provinces
where agricultural lands may be exposed to extinction, such
as the
northern and central governorates.(6)
5. Use cartographic modeling to reduce waste of
agricultural land.
One of the basic requirements for building the cartographic
model is the formulation of criteria or the conditions
necessary to evaluate the land for the future development
process, which ensures the fulfillment of the needs and the
maintenance of the standard of land ownership. The use of
GIS technology here in determining the areas that can be
employed as new residential areas and according to special
criteria in the region.(7)
In this study, criteria were carefully formulated after
reviewing previous studies, field visits, comparison with
international standards, conducting a series of personal
interviews and working with correspondents.(8)
Fig -3: Results of applying the study criteria
5.1: Building Model Builder.
After building the hierarchical model and defining the
criteria, types, levels and degree of weight, the cartographic
model was built in the ArcGIS and through the structural
model, which is based on the simplification of complex
problems and the overlap of the data and their spatial and
descriptive relationships. Therefore, this model is
formulated to simplify the problem and formulate the
method of solving it through So-calledgraphical layoutofthe
stages of work.(9)
Fig -4: Modeling and charting
5.2: Analysis proposed sites
After setting the criteria for deliberate guidance for the
agricultural and urban growth of the Gaza governorates and
after applying the weights, the process concluded to devise
the appropriate sites as follows.(10)
Fig -5: Map relevance 2030

6. CONCLUSIONS
6.1.Gaza Strip is a rapidly growing population, one of the
highest in the world, and this is the main reasonfortherapid
decline of agricultural land.
6.2.The study showed that thereisa verystrongrelationship
between the expansion of the urban mass and the steady
increase in the number of population in the Gaza
Governorates. This is the main determinant of the planned
agricultural planning.
6.3.The study succeeded in preparing a detailed study to
show the evolution and change in the spatial distribution of
land use maps since 1975.
6.4.The study showed the ability of GIS and remote sensing
technology to study the evolution of agricultural and urban
land area through the production of accurate maps.
6.5.The use of analysis according to the Markov Applied
Mathematical Chain and the confirmation of results
according to this Kaba accuracy index gives accurate results
for relying on the results of the research in government
decision making.
6.6.The use of cartographic modeling to determine the
future agricultural and urban growth areas is more efficient
than the methods used in local institutions, optimizing the
use of resources, achieving the highest returns and
minimizing land losses.
6.7.The process of relying on the distribution of the
questionnaire to the planning and GIS specialists is one of
the best ways to obtain the weights of the planning
standards accurately.
7. Recommendations study
7.1. Adopt a strategy to increase the absorptive capacity of
existing urban centers by encouraging the vertical
expansion of buildings.
7.2. Focus on public awareness to realize the importance
of commitment to urban planning and conservation of
agricultural land according to the provisions of the
structural plans and interest in popular participation in
the preparation of future plans.
7.3. Use of geographic information systems and remote
sensing in all local institutions because it has proved
successful in the preparation of spatial databases
REFERENCES:
1. United Nations (World Urbanization Prospects) New
York 2014.
2. Ir Yannick Curnel (Basic principles of remote sensing)
Dec 2014 - Walloon Agricultural Research Centre (CRA-W)-
Agriculture and natural environment Department-p21.
3. Palestinian Sector Plan (Urban Development Sector)
2010-2020 -p11
4. Canada Centre for Remote Sensing(Fundamentals
of Remote Sensing)2016
5..Werle D (Radar Remote Sensing - A Training Manual) .
(1988 and 1992), 193p, 75 35mm slides, Dendron Resource
Surveys Ltd, Ottawa, Ontario, Canada, ISBN 0- 9693733-0-9
6. Oliver, C. & S. Quegan (Understandingsyntheticaperture
radar images) 1998, 479 p., Artech House, Norwood, MA,
USA, ISBN 089006850X
7. Sohaib abu jaeab (Future Urban Development in Khan
Yunis Governorate in light of the conservation of
environmental resources using GIS.RS)2012. Master of
Islamic University in Gaza Palestine .p199.
8. Ministry of Works and Human Settlement(Spatial
Planning Standards)June 2017.p9.
9. Isri Company (ModelBuilder - Creating Tools Tutorial)
Copyright © 1995-2010 Esri. All rights reserved.
10. Shadi Kuhail (Impact of the Urban Growth On The
Land Ownership In Gaza Governorates, Using GIS and
Remote Sensing Technology)2013. Master of Islamic
University in Gaza Palestine .p190.

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