Mung used to collect remotely sensed data which

Mung bean pulses are the most important parts of our diet
due their nutrition factors.
It is cultivated twice in Pakistan during year, first in Feb. and second in
June. Proper planning and growth monitoring is required to have the required
yield to fulfill the demand of mung beans because growth assessment is the
basic factor to estimate the yield. The traditional method of growth assessment
are either very difficult are unreliable. As these methods are mainly based on
physical parameters like: number of leafs, shapes of leafs, height of plant,
color of plants etc. All these parameters are subjective in nature, due which
standard results cannot be achieved. Number of remote sensing techniques are
being employed for the growth monitoring now a day’s. Since Mung plant have
their unique spectral features (reflectance or emission regions), they will be identified from
remote sensing imagery according to their unique spectral characteristics. Steps involve in Mung plant growth
mapping include image preprocessing and image classification. A number of
methods are being used to collect remotely sensed data which are satellite
imagery, photographic data etc. MSR-5 CROP      SCAN
device will be used to have remotely sensed data of mung beans field time to
time. This device facilitates to provide data compatible to LANDSAT (a
satellite which provide data regarding to agriculture field). Acquired data
will be manipulated by using some protocols defined by vender of the MSR-5
device. This work will be a milestone to develop a modern technique, based on
quantitative analysis, for the growth assessments of other crops also.

1.    
Introduction

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Pulses
are very important in balanced diet due to their nutritional values. They have
critical role with their high fabric source of protein, and essential
nutrients, plus low-fat contents. The dry pluses contain no cholesterol. They
are recommended to be included in diets of people suffering from the diabetics and
heart diseases. Mung beans are a high source of nutrients: including magnesium,
potassium, manganese, zinc, copper and various B vitamins. This is also a very
filling food, high in resistant starch and dietary fiber. These are being used
in dried powder form, as uncooked beans as bean noodles split-peeled, and also
sprouted seeds. The dried seed may be eaten raw, fermented, cooked or milled.
Due to their high nutrient density mung bean are also considered useful in
defending against several chronic, age related diseases, including heart
disease, obesity, diabetes and cancer.

 In Chinese cuisine the mung beans are used to
make sugar water. Also in China, the boiled and shelled beans are used as filling
in glutinous rice dumplings eaten during the dragon boat festival. The beans
may also be cooked until soft, blended into liquid, sweetened, and served as a
beverage, popular in many parts of China. In Indonesia, they are
made into popular dessert snack. In Hong Kong, mung beans and mung paste are
made into ice cream or frozen ice pop.

Mung
crop is widely cultivated in a large number of countries. In Pakistan it is
cultivated twice in a year; first
time during the month of February and second time in June and July, due to that
it is economically valuable for the formers.

There are different verities of mung
beans some of them are NM-121-25, NM-20-21, NM-51, NM-54, NM-92, AEM-96,
NM-98, Chakwal Mung-97, Karak Mung-1, Ramzan-2005, NM-2006,
Chakwal
Mung-2006, AZRI Mung-06 and Dera Mung.

All
the verities are not equally suitable to be caltivated in different areas to
have proper yeild. For this purpose selection of proper seed and growth
monitering are essential.    

After
the selecting the appropriate veritie of mung beans for better production
following steps should be taken carefully, selection of land, preparation of
land, fertilizer application, sowing method, seed treatment, weed control,
insect pests and proper growth monitoring of plants. In this research we will
discuses how a large field of mung plant can be monitored remotely by using
MSR-5 SCANCROP device.

2.    
Literature Review

J.G.P Clever and H.J.C van Leeuwen use optical and microwave
remote sensing data in combination for crop growth monitoring. They use simple
reflectance model to estimate leaf area index(LAI) from optical data, and
simple backscatter model use for estimating LAI from radar data. Subsequently,
the synergistic effect of using both optical and radar data for estimating LAI
was analyzed by studying different data acquisition scenarios. Finally, the
remote sensing models were inverted to obtain LAI estimates during the growing
season for use in calibrating the crop growth model to actual growing
conditions1. The National Agricultural
Statistical Service (NASS) of the U.S. Department of Agriculture conducts field
interviews with sampled farm operators and obtains crop cuttings to make crop
yield estimates at regional and state levels. NASS needs supplemental spatial
data that provides timely information on crop condition and potential yields.
In this research, the crop model EPIC (Erosion Productivity Impact Calculator)
was adapted for simulations at regional scales. Satellite remotely sensed data
provide a real-time assessment of the magnitude and variation of crop condition
parameters, and this study investigates the use of these parameters as an input
to a crop growth model2Hans-Eric Nilsson reviews various applications of remote
sensing and image analysis in plant pathology. He describes technical methods
and their possibilities, but also emphasize the biological prerequisites and
restrictions of practical  applications 3. Yichun Xie. et al, use remote sensing imagery in
vegetation mapping. They  focus on the
comparisons of popular remote sensing sensors, commonly adopted image
processing methods and prevailing classification accuracy assessment. Mapping vegetation through remotely sens
images involve various consideration processes and techniques. They developed
vegetation classification at first to classify and mapping vegetation cover by
remotely sensed images either at community level or species level 4. Harini Nagendra. et al, GIS and remote
sensing application in invasive plant monitoring. They discussed different
applications in this field. GIS and remote sensing used for analyzing the
spatial distribution of certain feature throughout a large landscape. They use
both tools for the understanding of invasive plant movement 5. Rajesh K Dhumal at el work on
identification / differentiation of crops of same types. They use multispectral
and hyper spectral images that contain spectral information about crops. They
use supervise and unsupervised classification techniques to map geographic
distribution of crops optical data and characterize cropping practices 6. Kyle W. Freeman use remote sensing by-plant
prediction of corn forage biomass and nitrogen uptake at various growth stages.
His research demonstrates that by-plant information can be collected and used
to direct used high resolution N applications 7. Crop growth simulation models and remote
sensing method have high potential in crop growth monitoring and yield
prediction. However crop model have limitations in regional application and
remote sensing in describing growth process. Ma Yuping use the WOFOST model
adjusted and regionalize for winter wheat in north china and coupled through
the LAI to the SAIL-PROSPECT model in order to simulate soil adjusted
vegetation index(SAVI)8. The crop model EPIC (Erosion Productivity
Impact Calculator) was adopted for simulation at regional scales. Satellite remotely
sense data provides a real time assessment of the magnitude and variation of
crops condition and parameters, to investigate the use of these parameter an
input to crop growth model (Doraiswamy at el) 2. PCM (precision crop management) is an
agricultural management, designed to target crop and soil inputs according to
within, field requirement to optimize profitability and protect the
environment. Progress in PCM has been hampered by lack of timely, distributed
information on crop and soil conditions (M.S. Moran et al) 9. RM Johnston and MM Barson developed simple
remote sensing techniques for mapping and monitoring wetland, using landsat TM
imagery of inland wetland sites in Victoria and New South Wales. A range of
classification methods are examined in attempt to map the location and extent
of wetlands and their vegetation types 10. C.S.T Daughtry et al evaluate several
spectral indices for measuring crop residue cover using satellite multispectral
and hyper spectral data and to categorize soil tillage intensity in agricultural
fields. Landsat Thematic Mapper (TM) and EO-1 Hyperion imaging spectrometer
data were acquired over agricultural fields in central Iowa in May and June
2004 11. 
Thomas G. Van Niel and Tim R McVicar determine the temporal windows for
highest overall and individual crop discrimination; and compare simple methods
for combining best single-date results to increase overall accuracy12.                     

3.     
Problem Statement

Different methodologies have been
used to monitor the crops growth, but still different issues are there, like
manually monitoring each plant in a large landscape field is not possible. We
cannot get accurate results. In this research we shall try to solve these
issues by  remotely monitoring the mung
plant field by remotely scanned digital data

3.1       Research
Questions

How the growth of the mung
plants may be monitored remote sensing?

3.2         
Research Objectives

It is
very hard job to monitor the mung plant growth daily basis manually so  we will use advance method for this purpose
with the implementation of remote sensing approach. In this approach numerical
data acquired by MSR-5 will be used. In this way it will be select out
parameters which are helpful in this regard.

4.       Methodology

4.1 Data Acquision:

A device MSRS-5 scan crop which will be used to achieve the
required spectral digital data. The said device provides the spectral data in
the range of images from 390 nm to 750 nm in the blue, green, red, infrared and
farinfrared.  The data of mung field will
acquired time to time approximately after two week. The physical parameters
like watering the field, use of fertilizer and pesticide along with plant
condition will be manually recorded. The effect of above said procedures values
will also be analyzed. Different predefined protocols by the vender of this device
will be employed to import the data in the environment of different software’s
for further statistical analysis to have useful information regarding to the
said plant condition. 

4.2. Data Analysis

Data acquired from the said device has form of numerical format.
The variation of above mentioned spectral bands blue, green, red, infrared and
farinfrared with the plant growth watering of fields and fertilizer will be
analyzed by applying different statiscal and mathematical  approaches.