Will the traditional agriculture pass into oblivion? Adaptive remote sensing approach in support of precision agriculture

Abstract

Is it a time for replacing the traditional agricultural system by adaptive remote sensing (RS) Yes, of course it is. This chapter has focused on developing four adaptive models to predict and monitor soil-plant properties using RS. First, an image and point spectroscopic model to replace the current soil chemical analysis methods, which are slow, complicated, or inaccurat was developed. Spectroscopy has opened a new era in which outdated conventional soil analyses are being left behind. Spectroscopy can be utilized to precisely predict some soil (e.g. salinity, gypsum, heavy metals) properties, making it an important tool in precision farming. Second, adaptive and coactive neuro-fuzzy inference system for estimation of difficult-to-measure soil (phosphorus and soil cation exchange capacity, CEC) properties was proposed. The conventional procedures for CEC measurement demand longer time and it is difficult to maintain their stability during long-term experiments. Third, a real-time adaptive sensor network technology for land degradation prediction was implemented. Advancement in remote sensors and GIS technology has offered an approach to extremely modern early warning systems for observing most environmental hazards. Issuing appropriate warning systems are crucial to alleviate the environmental hazards impact on population, environment, and the economy. Early warning information system (EWIS) can be utilized for the early identification, observing, and prediction of soil salinization, desertification, and water content for farming computerization. Finally, adaptive thermal sensing technique to support precision agriculture was suggested. Thermal imaging has shown potential to assist with many aspects of soil and irrigation management. By such methods, thermal information about a large area can be obtained simultaneously and at times see things that otherwise may be hidden. Thermal infrared remote sensing can be used to soil salinity detection, water resources monitoring, and soil surface temperature mapping. This technology is a non-intrusive, non-contact, and non-destructive method used to predict thermal properties of soils.