Multi-Sensors Remote Sensing Applications for Assessing, Monitoring, and Mapping NPK Content in Soil and Crops in African Agricultural Land

Abstract

Demand for agricultural products is increasing as population continues to grow in Africa. To attain a higher crop yield while preserving the environment, appropriate management of macronutrients (i.e., nitrogen (N), phosphorus (P) and potassium (K)) and crops are of critical prominence. This paper aims to review the state of art of the use of remote sensing in soil agricultural applications, especially in monitoring NPK availability for widely grown crops in Africa. In this study, we conducted a substantial literature review of the use of airborne imaging technology (e.g., different platforms and sensors), methods available for processing and analyzing spectral information, and advances of these applications in farming practices by the African scientific community. Here we aimed to identify knowledge gaps in this field and challenges related to the acquisition, processing, and analysis of hyperspectral imagery for soil agriculture investigations. To do so, publications over the past 10 years (i.e., 2008–2021) in hyperspectral imaging technology and applications in monitoring macronutrients status for crops were reviewed. In this study, the imaging platforms and sensors, as well as the different methods of processing encountered across the literature, were investigated and their benefit for NPK assessment were highlighted. Furthermore, we identified and selected particular spectral regions, bands, or features that are most sensitive to describe NPK content (both in crop and soil) that allowed to characterize NPK. In this review, we proposed a hyperspectral data-based research protocol to quantify variability of NPK in soil and crop at the field scale for the sake of optimizing fertilizers application. We believe that this review will contribute promoting the adoption of hyperspectral technology (i.e., imaging and spectroscopy) for the optimization of soil NPK investigation, mapping, and monitoring in many African countries.

Use of Optical and Radar Imagery for Crop Type Classification in Africa: A Review

“…As technology advances, the introduction of next-generation satellites equipped with radar, LiDAR, and hyperspectral capabilities is anticipated to further enhance available information. With this range of satellite imagery, more techniques are required to combine different image and auxiliary data for mapping homogeneous land units [ 105 ] in Africa in order to (i) help the understanding of agricultural methods and cropping systems in terms of their spatial variability, (ii) contribute to the long-term management of these systems [ 106 ], and identify gaps in knowledge and obstacles concerning the processing and analysis of imagery for agricultural investigations in the majority of African nations [ 107 , 108 ].…”

QoS Performance Evaluation for Wireless Sensor Networks: The AQUASENSE Approach

“…The NPK sensor [9] setup includes four 10K resistors to detect the nutrients present in the soil while guarding against LED current overload. To determine the nutritional level of the soil solution, LEDs first transmit light into it.…”

Hyperspectral Imaging of Adaxial and Abaxial Leaf Surfaces as a Predictor of Macadamia Crop Nutrition

“…Hyperspectral imaging sensors mounted on platforms such as satellites, aircraft and unmanned aerial vehicles (UAV) have been used to estimate N, P and K levels in the leaves of many crops [ 30 , 31 , 32 ]. Satellite and airborne remote-sensing techniques may not always provide high-accuracy predictions of crop nutrition, as atmospheric conditions can affect prediction accuracy [ 33 , 34 ]. Laboratory-based hyperspectral imaging, on the other hand, has been used to predict foliar nutrient concentrations with high accuracy in apple ( Malus domestica ) (e.g., N: R 2 = 0.77) and cacao ( Theobroma cacao ) (e.g., N: R 2 = 0.75; P: R 2 = 0.71) [ 28 , 35 ].…”