**1. Introduction**

The effective guarantee of national food security is a key objective for China. Therefore, it has become a need of green agriculture to reduce the amount and increase the efficiency of chemical fertilizers, which could improve the effective supply of agriculture [1–3]. Rice and wheat are the main crops in the world, with a wide distribution and highly suitability. How to achieve high quality and yield is currently a major challenge for agricultural production [4–6]. N made up more than 40% of the mineral elements needed for the growth of rice and wheat [7]. Its content would impact the physiological traits, photosynthesis, and enzyme activities, leading to variations in protein content and grain production [8–10]. Healthy plants have a total N content that ranges from 0.3% to 5% of their dry matter, which directly affects crop production. N deficiency can hinder chlorophyll (Chl) synthesis

**Citation:** Zheng, J.; Song, X.; Yang, G.; Du, X.; Mei, X.; Yang, X. Remote Sensing Monitoring of Rice and Wheat Canopy Nitrogen: A Review. *Remote Sens.* **2022**, *14*, 5712. https://doi.org/10.3390/rs14225712

Academic Editors: Kenji Omasa, Shan Lu and Jie Wang

Received: 30 September 2022 Accepted: 6 November 2022 Published: 11 November 2022

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and reduce the effective number of spikes, thus reducing yields. A surplus of N prevents photosynthetic products from reaching the seeds, delaying maturation [7,11]. Therefore, N content during crop growth has become one of the most important indicators in agricultural production management. Currently it is common to use base fertilizer, or top dressing through experience. It will result in too much or not enough N, which not only inhibits crop growth but also pollutes the environment. How to monitor rice and wheat canopy N timely and accurately, so as to guide variable rate fertilization has become a core research issue [12–15].

Currently the experts in plant protection and agronomy test N manually by observing crop symptoms, plant growth and leaf color. They also use chemical diagnostics, such as plant total N diagnostics and rapid nitrate diagnostics, to detect the N content of each organ. The former has variances in results due to subjective judgments. The latter has good accuracy but destroys the plant and has a time lag, making large-scale application difficult [16]. Therefore, traditional N assessment methods do not facilitate variable rate fertilization, because the information on the timing and extent of crop N abundance and deficiency is not efficiently provided. Remote sensing has enabled the rapid development of multiple scales of application, including satellite, unmanned aerial vehicles (UAVs) and ground. It is the current technology for rapidly acquiring spatial and temporal continuum information on a large range. The spectrum is sensitive to the N response in the Visible–Near Infrared (VIS–NIR). This spectral information can show subtle changes in N content, allowing for more accurate N retrieval [17,18]. Remote sensing monitoring of N in rice and wheat can be non-destructive, effective, and real-time for large-scale studies. It offers significant potential for crop nutrient diagnosis and as a basis of subsequent guidance on fertilizer application [19–21].

Both rice and wheat belong to the gramineous cereal crop in the botanical classification, and both are C3 crops with similar photosynthetic systems [22]. Thus, the absorption of colored light by Chl in both canopies is consistent and the response to the spectrum is similar. N is mainly found in the Chl of the photosynthetic systems and the process of N accumulation in rice and wheat has a high degree of similarity [23,24]. They are both transformed into nutrient bodies at the vegetative growth stages and into reproductive organs at the reproductive growth stages, and there are anisotropic changes in N accumulation in each organ at the growth stage [23,25]. Although the cropping patterns differ, one being dryland and the other paddy, this effect can be attenuated when pre-processing the remote sensing data [26]. Therefore, in remote sensing-based studies, the N transformation processes in rice and wheat are highly consistent, making their remote sensing monitoring systems relatively similar [14,27,28]. In this study, the remote sensing monitoring techniques for both crops are explored in an integrated manner.

To analyze and summarize the current research hotspots and trends in the field of remote sensing of canopy N in rice and wheat, this paper traces the related literature in the Web of Science ™ Core Collection Database. The literature is retrieved and filtered by the topics "nitrogen concentration" or "nitrogen content", "rice" or "wheat" and "remote sensing". An initial collection of 572 apparently relevant records covered the period 2003– 2021. An initial screening progress is conducted to exclude literature that is not relevant to the review, such as conference proceedings, patents, etc. However, it still contains some irrelevant literature, and a further screening is necessary. This is followed by a more detailed screening on titles and abstracts to exclude the following: (1) non-targeted research topics (e.g., corn, cotton, grassland, etc.); (2) not directly estimated N (e.g., Chl, protein, etc.); (3) estimated other indicators (e.g., leaf area, plant height, yield, etc.); (4) measured soil N or other trace elements in agricultural fields; and (5) review articles. By carefully reading the titles and abstracts, off-topic papers are obviously manually excluded. Eventually, a total of 174 articles were identified and analyzed in depth. Figure 1 shows the number of studies retrieved from 2003 to 2021 that used remotely sensed data to assess the canopy N status of rice and wheat, reflecting the general trend in research on the application of remote sensing monitoring of canopy N.

**Figure 1.** Number of rice and wheat N retrieval research studies per year from 2003 to 2021.

Remote sensing technology has shown great potential for crop N monitoring, providing research ideas from various perspectives. This paper based on the mechanism of remote sensing monitoring of canopy N, respectively summarizes the current techniques and methods from three aspects: remote sensing platforms for canopy N monitoring; correlation between remotely sensed data and N status; and the retrieval methods of N status. Then it discusses the factors affecting the accuracy in remote sensing of canopy N and sketches future areas for research.

#### **2. Mechanisms for Remote Sensing Monitoring of Canopy N**
