Introduction
1.2. Need for Crop Monitoring
Remote sensing offers an efficient and reliable means of collecting the information required, in order to map tea type and acreage. Remote sensing provides the structure information on the health of the vegetation. The spectral reflectance of a tea field always varies with respect to the phenology, stage type and crop health and these could be well monitored and measured using the multispectral sensors. Information from remotely sensed data can be inputted to a Geographic Information System (GIS) and other cropping system which can then be combined with ancillary data to provide information of ownership and management practices, etc.
Assessment of tea health, as well as early detection of the crop infestations, is critical in ensuring good tea productivity. Stress associated with, for example, moisture deficiencies, insects, fungal and weed infestations, must be detected early enough to provide an opportunity for the planters to mitigate. This process requires that remote sensing imagery be provided on a frequent basis (at a minimum, weekly) and be delivered to the farmer quickly, usually within 2 days. There are also instances where the tea growth varies from one spot to another. These growth differences may be due to soil nutrient deficiencies and other stress conditions. Remote sensing allows the farmer to identify areas within a field which are experiencing difficulties, so that he can apply, for instance, the correct type and amount of fertilizer, pesticide or herbicide. Using this approach, the farmer not only improves the productivity from his land, but also reduces his farm input costs and minimizes environmental impacts.
Remote sensing has a number of attributes that lend themselves to monitoring the health of tea plants. One advantage of optical (VIR) sensing is that it can see beyond the visible wavelengths into the infrared, where wavelengths are highly sensitive to crop vigour as well as crop stress and crop damage. Remote sensing imagery also gives the required spatial overview of the land. Recent advances in communication and technology allow a planter to observe images of his fields and make timely decisions about managing the crops. Remote sensing can aid in identifying the tea crops affected by conditions that are too dry or wet, affected by insect, weed or fungal infestations or weather related damage. Images can be obtained throughout the growing season to not only detect problems, but also to monitor the success of the treatment.
Healthy vegetation contains large quantities of chlorophyll, the substance that gives most vegetation its distinctive green colour. In referring to healthy tea crops, reflectance in the blue and red parts of the spectrum is low since chlorophyll absorbs this energy. In contrast, reflectance in the green and near-infrared spectral regions is high. Stressed or damaged crops experience a decrease in chlorophyll content and changes to the internal leaf structure. The reduction in chlorophyll content results in a decrease in reflectance in the green region and internal leaf damage results in a decrease in near-infrared reflectance. These reductions in green and infrared reflectance provide early detection of crop stress. Examining the ratio of reflected infrared to red wavelengths is an excellent measure of vegetation health. This is the premise behind some vegetation indices, such as the normalized differential vegetation index (NDVI). Healthy plants have a high NDVI value because of their high reflectance of infrared light, and relatively low reflectance of red light. Phenology and vigour are the main factors in affecting NDVI. Examining variations in tea crop growth within one field is possible. Areas of consistently healthy and vigorous crop would appear uniformly bright. Stressed vegetation would appear dark amongst the brighter, healthier crop areas. If the data is georeferenced, and if the planter has a GPS (Global Positioning System) unit, he can find the exact area of the problem very quickly, by matching the coordinates of his location to that on the image.
Detecting damage and monitoring tea crop health requires high-resolution imagery and multispectral imaging capabilities. One of the most critical factors in making imagery useful to planters is a quick turnaround time from data acquisition to distribution of crop information. Receiving an image that reflects crop conditions of two weeks earlier neither help real time management nor damage mitigation. Images are also required at specific times during the growing season, and on a frequent basis.