Remote Sensing techniques for Agriculture suvey

S. Balaselvakumar
Research Scholar, Department of Geography,
Bharathidasan University, Tiruchirapalli- 620 024, India

S. Saravanan
Department of Zoology, Annamalai University,
Chidambaram -608 002, India

Introduction
Agriculture resources are among the most important renewable, dynamic natural resources. Comprehensive, reliable and timely information on agricultural resources is very much necessary for a country like India whose mainstay of the economy is agriculture. Agriculture survey are presently conducted throughtout the nation in order to gather information and associated statistics on crops, rangeland, livestock and other related agricultural resources. These information of data are most importance for the implementation of effective management decisions at local, panchayat and district levels. In fact, agricultural survey is a backbone of planning and allocation of the limited resources to different sectors of the economy.

With increasing population pressure throughout the nation and the concomitant need for increased agricultural production (food and fiber crops as well as livestock) there is a definite need for improved management of the nation agricultural resources. In order to accomplish this, it is first necessary to obtain reliable data on not only the types, but also the quality, quantity and location of these resources. The remote sensing techniques has been and it will continue to, a very important factor in the improvement of the present systems of acquiring and generating agricultural data.

Remote sensing and its Importance in Agricultural survey
Remote sensing is nothing but a means to get the reliable information about an object without being in physical contact with the object. It is on the observation of an object by a device separated from it by some distance utilizing the characteristics response of different objects to emissions in the electromagnetic energy is measured in a number of spectral bands for the purpose of identification of the object.

In such study single tabular form of data or map data is not sufficient enough which can provide can be, combined with information’s obtained from existing maps and tabular data.

• Remote Sensing techniques using various plate form has provide its utility in agricultural survey
• Satellite data provides the actual synoptic view of large are at a time, which is not possible from conventional survey methods.
• The process of data acquisition and analysis is very fast through Geographic Information System (GIS) as compared to conventional methods.

Remote Sensing techniques have a unique capability of recording data in visible as well as invisible (i.e. ultraviolet, reflected infrared, thermal infrared and microwave etc.) part of electromagnetic spectrum. Therefore certain phenomenon, which cannot be seen by human eye, can be observed through remote sensing techniques i.e. the trees, which are affected by disease, or insect attack can be detected by remote sensing techniques much before human eyes see them.

Present system of Generating agricultural data and its Problems
The present system of agricultural data is collected throughout the nation. The main responsibility of collection agricultural survey lies on the Director of Land Records, Director of agriculture and District Statistical Office under the Ministry of Agriculture. These data are collected not only on a local but also some extent of district and state level. The associate of agricultural survey on crops (crop production, type of crop and crop yield), range land (condition of range, forest type, water quality, types of irrigation system and soil characteristics) and livestock (livestock population, sex of animal, types of farm and distribution of animals).

The basic problems in this survey are;

• Reliability of data
• Cost and benefits
• Timeless
• Incomplete sample frame and sample size
• Methods of selection
• Measurement of area
• Non sampling errors
• Gap in geographical coverage
• Non availability of statistics at disaggregated level.

Remote Sensing techniques make it use before the remote sensing data may provide solution to these particular problems of agricultural survey.

Remote Sensing techniques for Agricultural survey
The given factors influenced the use of remote sensing in agricultural surveys; via 1. Characteristics of the agricultural landscape 2. Characteristic of EMR on Agricultural survey.

Detection, identification, measurement and monitoring of agricultural phenomena are predicated on the assumption that agricultural landscape features (e.g. crops, livestock, crop infestations and soil anomalies) have consistently identifiable signatures on the type of remote sensing data.

Some of the parameters which may cause these identifiable signatures include crop type, state of maturity, crop density, crop geometry, crop vigor, crop moisture, crop temperature, soil moisture, soil temperature. An image analysis can correlate a certain signature with one of these many characteristics. Remote Sensing techniques in agriculture survey which affect the signature on remote sensing imagery. It is important to consider briefly the significance of choosing the appropriate sensor system, as well as the scale and resolution requirements that will yield optimum benefits for objectives of agricultural survey.

Signature in Remote Sensing
The knowledge of spectral signatures is essential for exploiting the potential of remote sensing techniques. This knowledge enables one to identify and classify the objects of agricultural resources. It is also required for interpretation of all remotely sensed data, especially in agricultural resource data whether the interpretation is carried out visually or using digital techniques. It also helps us in specifying requirements for any remote sensing mission e.g. which optimal wave length bands to be used or which type of sensor will be best suited for a particular task (agricultural survey). All objects of agricultural resource on the surface of the earth have characteristic spectral signatures. For example, the given fig. 1 shows the average spectral reflectance curves (or) spectral signatures for three typical earth’s features; vegetation, soil and water.

The spectral reflectance curves for vigorous vegetation manifests the “Peak-and valley” configuration. The valleys in the visible portion of the spectrum are indicative of pigments in plant leaves. Dips in reflectance that can be sent at wavelengths of 0.65 mm, 1.4 mm and 1.9 mm are attributable to absorption of water by leaves. The soil curves show a more regular variation of reflectance. Factors that evidently affect soil reflectance are moisture content, soil texture, surface roughness and presence of organic matter. The water curves shows that from about 0.5 mm, reduction in reflectance with increasing wavelength, so that in the near infrared range, the reflectance of deep clear water is virtually zero (Mather, 1987) However, the spectral reflectance of water is significantly affected by the presence of dissolved and suspended organic and inorganic material and by the depth of the water body. Determinations of spectral signatures implies basic under standing of interaction of electromagnetic radiation with agricultural resources objects. This is also necessary for analyzing and designing sensor systems for agricultural survey.

Sensor systems in Remote Sensing
In remote sensing the acquisition of data is depending upon the sensor system used. Various remote sensing platforms (Aircraft, Satellite) are equipped with different sensor systems. Sensor is a device that receives electromagnetic radiation, converts it into a signal and presents it in a form suitable of obtaining information about the land or earth resource as used by an information gathering system. Sensor can be grouped, either on the basic of energy source. They are as classified.

Active sensor
An active sensor operates by emitting its own energy, which is needed to detect the various phenomena (e.g. RADAR, camera with a flash gun)

Passive sensor
The operation of passive sensor is dependent of the existing sources of energy, like sun (e.g. photographic systems, multispectral scanners).

The given sensor system of camera are in agricultural survey.

1. Photographic cameras
   The photographic system, having conventional camera with black and white photography, is the oldest and probably, so far, the most widely used sensor for recording information about ground object. Photographic cameras have been successfully used in aircraft platform remote sensing. In this system, the information is limited to size and shape, as the films used are sensitive only to visible region of spectrum. The response of black & white films is about 0.4-0.7 mm for infrared imagery, films with response extending up to 0.9 mm are available.
2. Return Beam Vidicon (RBM)
   This is very similar to a television camera. In such a system, a fixed camera lens on a photosensitive semi-transparent sheet forms the ground image. This image is created on the surface as electrical change or potential.

   The TV cameras are the best example of high resolution, operated in space for resource survey was the RBV used in LAND SAT series. On LAND SAT I, II and III RBV cameras were used, each corresponding to a different wavelength band 0.475-0.585 mm (green), 0.580-0.690 mm (red) and 0.690-0.830 mm (near infrared). The Indian experimental remote sensing satellite, Bhaskara-I and II carried a two-band TV camera system, Multispectral imagery was produced in LAND SAT and Bhaskara by using separate camera tubes of each band and selecting the spectral band with appropriate filters.

3. Optical-mechanical scanners
   This imaging system has the advantage that any set of desired spectral bands can be selected with appropriate filter and detector combinations. The mostly widely used sensor in this category is the MSS on LAND SAT series. MSS has four spectral bands, covering form 0.5-to 1.1 mm region. MSS operates on the principle of scanning successive lines at right angles to the flight path by means of a rotation or oscillating optical system. The radiation levels along the lines are recorded by appropriate sensor elements. When used in the visible band, the collected light can be split by the optics and separately filtered and recorded, giving simultaneous multispectral recording from the one instrument. MSS can record in any part of ultraviolet to near IR window. They are use also in the thermal IR windows
4. Radar and Microwave sensors
   The acquisition of data in microwave region has been possible since 1950s but its application to natural resources is considerably less developed, as compared to the visible and IR image interpretations. Microwave sensors have distinct advantages because they are unaffected by atmospheric conditions and are thus able to penetrated smoke, clouds, haze and snow. Under this system, Plan Position Indicator (PPI), Side Looking Air borne Radar (SLAR) and Synthetic Aperture Radar (SAR) can be grouped. These systems offer day and night as well as all weather capability and ability to penetrate a cover of vegetation.
5. Advance remote sensors
   Linear Imaging and Self Scanning Sensors (LISS) are the advanced imaging systems. This type of scanning sensor are used an array of solid-state devices. The array may be made of photo-diodes, phototransistors or Charge-Coupled Devices (CCDs). In the LISS, the optics focuses a strip of terrain in the cross-track into the sensor array. The image from each detector is stored and shifted out sequentially to receive a video signal. The SPOT (Satellite Probatorie d’ Observation de la Terra) and IRS (Indian Remote Sensing Satellite) series carry such solid-state sensor systems, which are also known as push-broom scanners.

   The IRS IC most advanced satellite, carries an improved sensor system. Besides carrying a sophisticated LISS-III camera, it has a Panchromatic camera (PAN) and a Wide Field Sensor (WiFS). The PAN has been designed to provide data with a spatial resolution of 5.8m in stereo mode, with a ground swath of 70km, whereas WiFS provides data in two spectral bands, with a spectral resolution of 188m and a ground swath of 180km.

   The given wavelengths are employed in agricultural survey through Electromagnetic radiation by using remote sensor system.

Use of wavelength region for Agricultural survey

Generally the remote sensing devices operate in the green, red and near infrared regions of the electromagnetic spectrum for agriculture and other allied phenomena. Agricultural resources can be obtained by measuring spectral, spatial and temporal variations of electromagnetic radiation emanating from points of interest and then analyzing these measurements to relate them to specific classes of agricultural phenomena purpose. Spectral variations are changes in the intensity of radiation at a given wavelength i.e. difference in colour. Spatial variations are changes in radiation from one location to another i.e. difference in shape and position. Temporal variations are changes in radiation from one time to another i.e. difference over time. One of the most successful applications of multispectral space imagery (sensor) is monitoring the state of the world’s agricultural production. This application includes and differentiation of the agricultural phenomena.

Electromagnetic Remote Sensing Process
Agricultural resources data are collected y aircraft and satellite-mounted instruments, which receive reflected energy from target in some frequency of the electromagnetic spectrum. The process involved in electromagnetic remote sensing system namely, data acquisition and data analysis are outlined below and a schematic diagram of electromagnetic remote sensing process in shown in the Fig. 2

Data acquisition
The data acquisition process comprises of the following distinct elements, which are necessary in agricultural survey

• Energy sources
• Propagation of energy through the atmosphere
• Energy interactions with earth’s surface features
• Air borne/Space borne sensors to record the reflected energy
• Generation of sensor data in the form of pictures or digital information

Data analysis
The data analysis process involves examining the data using various viewing instrument to analyze pictorial data, which is called the visual interpretation technique and computer to analyse digital data, a process known as digital analysis.

Reference Data
Reference data also called ground truth area an essential part of remote sensing data processing. It is used to analyse and interpret remotely sensed data, to calibrate a sensor, and to verify information extracted from remote sensing data.

The above given figure-3 shows the part of the spectrum relevant to remote sensing. The most common form of remote sensing was Aerial photography, in which used the visible light section of the electromagnetic spectrum. Newer sensors can acquire data in this and other sections of the electromagnetic spectrum, such as the non-visible infrared and near infrared wavelength, as will as microwaves used for radar. Many of these sensors can acquire several section of the spectrum concurrently and may be termed multispectral scanners. The electromagnetic wavelength bands with their bands with their utility in remote sensing are described in the given table -1

Table 1 Electromagnetic spectral region
Advantages of Remote Sensing techniques in Agricultural survey
With the primary aim of improving the present means of generating agricultural data, a number of specific advantages may result form the use of remote sensing techniques.

1. Vantage point
   Because the agricultural landscape depends upon the sun as a source of energy, it is exposed to the aerial view and, consequently, is ideally suited or remote sensing techniques.
2. Coverage
   With the use of high-altitude sensor platforms, it is now possible to record extensive areas on a single image. The advent of high-flying aircraft and satellites, single high quality images covering thousand of square miles
3. Permanent record
   After an image is obtained, it serves as a permanent record of a landscape at a point in time which agriculture changes can be monitored and evaluated.
4. Mapping Base
   Certain types of remote sensing imagery are, in essence, pictorial maps of the landscape and after rectification (if needed), allow for precise measurement (such as field acreages) to be made on the imagery, obviating time-consuming on the ground surveys. These images may also aid ground data sampling by serving as a base map for location agriculture features while in the field, and also as a base for the selection of ground sampling point or areas.
5. Cost savings
   The costs are relatively small when compared with the benefits, which can be obtained form interpretation of satellite imagery.
6. Real-time capability
   The rapidly with which imagery can be obtained and interpreted may help to eliminate the lock of timeliness which plagues, so many agricultural survey.

Other advantages of Remote Sensing

• Easy data acquisition over inaccessible area.
• Data acquisition at different scales and resolutions
• The images are analyzed in the laboratory, thus reducing the amount of fieldwork.
• Colour composites can be produced from three individual band images, which provide better details of the area then a single band image or aerial photograph.
• Stereo-satellite data may be used for three-dimensional studies. At present, all advantages listed above have been demonstrated either operationally or experimentally:

Application of Remote sensing techniques for Agricultural survey
The specific application of remote sensing techniques can be used for i) detection ii) identification iii) measurement iv) monitoring of agricultural phenomena.

Area of specific applications
a) Applicable to crop survey 1. Crop identification
2. Crop acreage
3. Crop vigor
4. Crop density
5. Crop maturity
6. Growth rates
7. Yield forecasting
8. Actual yield
9. Soil fertility 10. Effects of fertilizes
11. Soil toxicity
12. Soil moisture
13. Water quality
14. Irrigation requirement
15. Insect infestations
16. Disease infestations
17. Water availability
18. Location of canals b) Applicable to range survey 1. Delineation of forest types
2. Condition of range
3. Carrying capacity
4. Forage
5. Time of seasonal change
6. Location of water
7. Water quality
8. Soil fertility
9. Soil moisture
10. Insect infestations
11. Wildlife inventory
c) Applicable to livestock survey 1. Cattle population
2. Sheep population
3. Pig population
4. Poultry Population
5. Age sex distribution 6. Distribution of animals
7. Animal behavior
8. Disease identification
9. Types of farm buildings

Conclusion
The use of remote sensing technology has been rapidly expanded for the development of key sectors. This paper highlights the fact that the remote sensing techniques will continue to be very important factor in the improvement of present system of acquiring agricultural data. The remote sensing provides various platforms for agricultural survey. Satellite imagery has unique ability to provide the actual synoptic vies of large area at a time, which is not possible for conventional survey methods and also the process of data acquisition and analysis are very fast through GIS (Geographic Information System) as compared to the conventional methods. The different features of agriculture are acquired by characteristic, spectral reflectance, spectral signature of agriculture and associated phenomena through EMR. In General the research paper emphasizes the utmost need of timeliness and accuracy of the output generated by remote sensing techniques and its calibration with ground-truth and other information systems like aerial photography and satellite imagery etc. Further, the importance of remote sensing with special reference to agricultural sector involving crop acreage, crop production, rangeland and livestock has been discussed in detail. For the further improvement in the use of remote sensing technology in various fields, we can have interaction with the Dep. of Space that is specialized in this field.

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