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Remote Sensing techniques for Agriculture suvey
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).
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