Remote Sensing Technology: The Mainstay of Digital Agriculture

Introduction

Remote sensing, the ability to obtain information about an area or object without direct physical contact, in today’s time, acts as one of the biggest inputs for data-driven smart agriculture. “Digital agriculture” which is the use of new and advanced technology to enable smarter and more sustainable food production, depends largely on the availability of reliable external data that can translate to better decision making throughout different stages of cultivation. With growing population and dwindling cultivable land resources as the two main challenges facing food production in the future, it is the intelligence derived from these sources that will guide cultivation and harvesting decisions by providing cultivators with the right information at the right time. 

The Current Agriculture Industry Challenges

The challenges farmers face today include, but aren’t limited to the following:

• Regular Equipment Maintenance

Agriculture as an industry is heavily dependent on machinery. Maintenance operations, even scheduled regularly, consume time and impact the budget; but nevertheless, fail to eliminate the unpredictability factor. Once a piece of equipment accidentally goes out of order, it usually leads to unexpected downtimes.

• Correct water estimates

Growing plants need water, but the amounts of it differ depending on soil humidity levels. To measure these levels, farmers have to go to the field and take regular manual tests – alternatively, they could use smart sensing technology, which is by far, more accurate, convenient, and time efficient.

• Eliminating water waste and overhead expenses

Failing to collect accurate soil humidity information may result in the under watering or overwatering of the plants. Poorly watered plants are dry and frail, but overwatering creates water waste and involves unpredicted water expenses.

• Estimating correct planting times

Each plant has its own optimal planting time depending on a range of environmental factors. However, it is often difficult to correctly estimate this time without accurate data.

• Measuring soil temperature and moisture levels

Soil temperature and moisture levels are key metrics farmers need to collect to estimate the state of crops and take appropriate action. 

• Pest control

Successful pest control involving detecting pests, their location, activity and behavior patterns is another challenge farmers have to face. 

How Remote Sensing is Priceless for Digital Agriculture

• Understand Crop Type and Harvesting Time

With remote sensing, farmers have access to complete information about ideal soil and weather conditions well into the future, helping them to plan their cultivation cycle better. The predictive nature of the technology helps in zeroing in on the perfect time to plant a particular crop under the given weather conditions and also provides valuable information right from sowing till harvesting.

 

• Soil Mapping and Forecasting Irrigation Requirements

It is also an important factor in estimating the soil moisture data in a given plot of land, which can help identify the ideal crop to cultivate and the level of moisture it would require throughout different stages of growth. As a result of this, it also helps in adequately planning the irrigation needs well in advance.

 

• Assessing Crop Health and Accurate Yield Prediction

Remote sensing helps in closely monitoring crop health of a given field on a continuous basis so as to identify crop nutrients deficiencies and make quick actions before any damage being made. It also serves as a reliable method of predicting the yield over a given cultivation cycle and in identifying the right time to harvest based on the climatic conditions.
 

NDVI in its most pure form is simply raw data, a crop-based selfie that tells you how your farm is doing at any particular moment in time.

• Monitoring Drought and Weather-related dependencies

Remote sensing technology  can continuously monitor the weather patterns of a given area. This is especially beneficial in drought or flood-affected areas where the information helps in identifying the time between one rainfall to the next and prepare for any eventuality if it were to occur.

 

• Evaluating Historical Land Quality and Degradation Mapping

Satellite imagery helps in assessing the quality of a particular piece of land over a given period of time in order to calculate the extent of land degradation with cultivation. Knowing the historical performance of land has many uses, not just to farmers but also for determining crop insurance coverage or loan disbursement by banks and other credit providers.

 

• Identifying Pest and Disease Infestation

Since remote sensing ensures that the crop is constantly monitored over the span of its cultivation, it helps protect the crop against a full-blown onslaught of any pest or disease. Any detected pest or hazardous element sparks an alert that gets sent out immediately. These real-time alerts ensure that all possible threats are quickly identified and handled before they impact the entire farm.

 
Conclusion

Agriculture is one of the sectors that remote sensing technologies can maximum benefit. Smarter decision making regarding every aspect of cultivation is the key and remote sensing allow agri-businesses to control, monitor and accurately predict the outcome of each and every crop that is cultivated. The applications of this digital intelligence are numerous and touch various stakeholders throughout the agricultural value chain. The pertinent question for agri-businesses and stakeholders isn’t about deciding whether or not to engage in smart data-driven agricultural practices, it lies in identifying the right solution that combines technology and agricultural know-how in a manner that makes the most sense for them given their current challenges and finding smarter ways of overcoming them.