Toward a Smart Tool for Irrigation Systems management Using remote sensing

In agriculture, water and fertilizer are two limiting elements of plant growth. Indeed, the lack or the excess of one of them disturbs the yields in terms of quality and quantity. Optimal irrigation/fertilization and precisely dosed nutrient supply allow fast growing plants to reach their full potential, offering much larger and better quality yields. The use of remote sensing through satellites images becomes necessary in the case of a large area. To manage properly the use of water and fertilizers in a region it is necessary to know the spatial distribution of crops. So first, we have to discriminate crops. Next the control of doses and plant growth rate must be performed.

In this paper we present a tool for smart management of the water irrigation and fertilizer using remote sensing data and mathematical algorithms by considering crops as a dynamical system.

We give some mathematical algorithms to discriminate dynamical systems (crops) and after we consider the problem of detection of the impact of irrigation and fertilization on the crop through spectral signatures. For this, we consider the problem of detecting the effects of nitrogen and irrigation on the mint  by spectroscopy and we compare the obtained results with other obtained measures for rosemary  without fertilizer. For our case study, we choose potted mint as a plant that grows very fast and we apply our spectral measurement protocol to answer the following problem: Can we detect the effect of water and nitrogen by observing the growth of a given crop using the spectrometer? The results will be used for our tool to manage irrigation and fertilizer.

Keywords: irrigation, fertilizer, crop growth, remote sensing, dynamical systems

This work is the result of a research project: Alkhawarizmi/2020/11: Tool for intelligent management of irrigation water and forest heritage, funded by MESRSFC, CNRST and ADD, Morocco