Q1: Remote sensing can be used for crop status study. Discuss three possible outcomes of remote sensing can be used in precision crop management and benefit to farmers.

Nutrient deficiency analysis

Lack of certain nutrients stops the plant from growing normally. Certain nutrients which are directly or indirectly related with the production of chlorophyll, have a distinctive effect on the colour of the leaves. Nitrogen deficiency for example, first causes the yellowing of the leaf area around the veins and progressively the yellow area extends to the rest of the leaf, slowly turning into red and then brown colour. Manganese deficiency first affects the newer leaves, which grow near the top of the plant canopy. On the other hand, nitrogen deficiency tends to affect the older leaves which are found at the lower part of the plant, near the soil.

Plants have a particular way to reflect the electromagnetic radiation. This unique characteristic is known as the vegetation's spectral signature. Reflectance of vegetation is very low in the blue band and red band of the electromagnetic spectrum, are also call as wavelength. The reflectance of electromagnetic spectrum slightly higher in the green band and very high in the near infra-red band. With remote sensing data, we can directly estimate how much chlorophyll there is in a plant. By combining more than one bands of the recorded remote sensing data, we can create vegetation indices and use them to estimate crop status. Depending on the visible and near-infrared reflectance, the produced vegetation indices give us an indication on the amount of chlorophyll present in the plants. The amount of chlorophyll has strong correlation with amount of nutrient. The healthy leave with green colour have enough nitrogen and high reflectance from near infra-red band compare to other band. We can use the NDVI method to map the crop field and identify the lack nutrient area in the field. So, the farmer can use the output of NDVI analysis to supply the nutrient for the needed area. As a result, it can help the farmer to reduce the cost and amount of fertilizer to apply in the field.

Water stress analysis in the crop field

Like many organisms, plants require water to survive. In addition to the water being used in essential biochemical processes, water is the "means of transportation" for nutrients from the soil to every part of the plant. Water enters the plant through the roots, travels through the main stalk and the branches, eventually reaching the leaves. All the biological processes taking place within a plant, produce heat. The transpiring water, captures that heat and removes it from the plant when it transpires through the leaves. When there is not enough water and the plant is under stress, it cannot lose heat through transpiration fast enough and as a result, the plant's temperature increases. In general, this increase in temperature can be detected with thermal sensor of remote sensing, by using parts of the spectrum that are sensitive to heat.  By using thermal data, we can map out the heat produce by the crop in the field. As a result, the farmer can start to manage their irrigation to the specific region that are lack of water. Situation in Malaysia, not all farmer really aware about the water stress since Malaysia have enough rainfall annually in average. However, there is a dry period in every year and can cause the water stress on the crop especially for on the hilly area.

Identify plants disease and pest

In addition to identifying plants under stress from lack of nutrients or water, remote sensing can also assist in protecting the plants from potential attacks of pests, fungi or bacteria. By combining agricultural knowledge with remotely sensed data, it is possible to have early warning and prevent a pest or a disease from affecting the crops, by taking appropriate action at an early stage. In general, healthy plants will reflect high amount of electromagnetic spectrum in near infra-red band due to chlorophyll content in the leaves. As we know, chlorophyll is use for photosynthesis process for plant to grow. Using remote sensing data, we can measure and identify the chlorophyll content and leave area index (LAI) based on multispectral satellite imagery. The green leave will reflect 60% of the near infra-red electromagnetic spectrum compare to visible light spectrum. By using the ratio between near infra-red spectrum and visible light (Red) spectrum, we can measure the measure the vegetation indices. By using the normalize differences vegetation index (NDVI), we can identify and distinguish between the healthy crop and problematic crop. Healthy crop will reflect very well in near infra-red part of spectrum.

The NDVI value is ranges from 0 to 1. The healthy crop will have higher NDVI value, (0.7 to 0.9) and near to 1 subject to crop type and leave structure. Meanwhile, the lower NDVI value ranges from 0.3 to 0.5 is consider as non-healthy leave or low leaf area index (LAI). Base on the agriculture experience, if the NDVI value is low on the curtain corner of the crop field or near to boundary, it may be due to pest attack. If the NDVI value is low that shows the non-healthy leave in the middle or spotted inside the crop field, it may be cause by disease or fungi infection. Take into consideration as the soil profile and water irrigation for the crop field is in the same condition. Than we can assume the lower NDVI value area is subject to disease or pest attack to the crop. The farmer can only focus to the lower NDVI value area and do the ground verification. It will benefit the farmer in term of time to check the whole crop area, and also help the farmer to combating the disease or pest base on the problematic area.