Satellite and Fluorescence Remote Sensing for Rice Nitrogen Status Diagnosis in Northeast China

Nitrogen (N), as the most important element of crop growth and development, plays a decisive role in ensuring yield. However, the problems of over-application of N fertilizers have been repeatedly reported in China, which resulted in low N use efficiency and high risk of environmental pollution. The requirements of developing technologies for real-time and site-specific diagnosis of crop N status are the foundation to realize the precision N management, and also benefit to the improvement of the N use efficiency. Remote sensing technology provides a promising non-intrusive solution to monitor rice N status and to realize the precision N management over large areas. This research focuses on proposing N nutrition diagnosis methods and developing N fertilizer management strategies for paddy rice of cold regions in Northeast China. The main contents and results are presented as follows: (1)This study developed a new critical N (Nc) dilution curve for paddy rice of cold regions in Northeast China. The curve could be described by the equation Nc=27.7W^(-0.34) if W≥1 t/ha for dry matter (DM) or Nc=27.7g/kg DM if W<1 t/ha, where W is the aboveground biomass. Results indicated that the new Nc dilution curve was suitable for diagnosing short-season Japonica rice N status in Northeast China. The validation result indicated that it worked well to diagnose plant N status of the 11-leaf variety rice. (2)This study investigated the potential of the satellite remote sensing data for diagnosing rice N status and guiding the topdressing N application at the stem elongation stage in Northeast China. 50 vegetation indices (VIs) were computed based on the FORMOSAT-2 satellite data, and they were correlated with the field-based agronomic variables, i.e., aboveground biomass (AGB), leaf area index (LAI), plant N concentration (PNC), plant N uptake (PNU), chlorophyll meter readings, and N nutrition index (NNI, defined as the ratio of actual PNC and critical PNC according to the new Nc dilution curves). The results presented that 45% of variation in the NNI was obtained by using a direct estimation method based on the best VI according to the FORMOSAT-2 satellite data, while 52% of the variation in the NNI was yielded by an indirect estimation method, which firstly used the VIs to estimate AGB and PNU, respectively, then estimated NNI according to these two variables. Moreover, based on the critical N uptake curve, a N recommendation algorithm was proposed. The algorithm was based on the difference between the estimated PNU and the critical PNU to adjust the topdressing N application rate. The results demonstrated that FORMOSAT-2 images have the potential to estimate rice N status and guide panicle N fertilizer applications in Northeast China. (3)This study also evaluated the potential improvements of the newest satellite sensors with the red edge band for diagnosing rice N status in Northeast China. The canopy-scale hyperspectral data were upscaled to simulate the wavebands of RapidEye, WorldView-2, and FORMOSAT-2, respectively. The VI analysis, stepwise multiple linear regression (SMLR), and partial least squares regression (PLSR) were performed to evaluate the N status indicators. The results indicated that the VIs based on the RE band from RapidEye and WorldView-2 data could explain more variability for N indicators than the VIs from FORMOSAT-2 data having no RE band. Moreover, the SMLR and PLSR results revealed that both the near-infrared and red edge band were important for N status estimation. (4)The proximal fluorescence sensor Multiplex_3 was used to evaluate the potential of fluorescence spectrum for estimating the N status of the cold regional paddy rice at different growth stages. The Multiplex indices and their normalized N sufficient indices (NSI) were used to estimate the five N status indicators, i.e., AGB, leaf N concentration (LNC), PNC, PNU, and NNI. The results indicated that there were strong relationships between the fluorescence indices (i.e., BRR_FRF, FLAV, NBI_G, and NBI_R) and (i.e., LNC, PNC, NNI), with the coefficient of determination between 0.40 and 0.78. In particular, NNI was well estimated by these fluorescence indices. Moreover, the NSI data improved the accuracy of the N diagnosis. These results of this study were useful for N nutrition diagnosis and variable fertilization of the cold regional paddy rice, which were significant for the ecological environment protection and the national food security

Terrestrial laser scanning for crop monitoring. Capturing 3D data of plant height for estimating biomass at field scale

Terrestrial laser scanning (TLS) is a young remote sensing method, but the trustworthiness of such measurements offers great potential for accurate surveying. TLS allows non-experts to rapidly acquire 3D data of high density. Generally, this acquisition of accurate geoinformation is increasingly desired in various fields, however this study focuses on the application of TLS for crop monitoring. The increasing cost and efficiency pressure on agriculture induced the emergence of site specific crop management, which requires a comprehensive knowledge about the plant development. An important parameter to evaluate this development or rather the actual plant status is the amount of plant biomass, which is however directly only determinable with destructive sampling. With the aim of avoiding destructive measurements, interest is increasingly directed towards non-contact remote sensing surveys. Nowadays, different approaches address biomass estimations based on other parameters, such as vegetation indices (VIs) from spectral data or plant height. Since the plants are not taken it is feasible to perform several measurements across a field and across the growing season. Hence, the change of spatial and temporal patterns can be monitored. This study applies TLS for objectively measuring and monitoring plant height as estimator for biomass at field scale. Overall 35 TLS campaigns were carried out at three sites over four growing seasons. In each campaign a 3D point cloud, covering the surface of the field, was obtained and interpolated to a crop surface model (CSM). A CSM represents the crop canopy in a very high spatial resolution on a specific date. By subtracting a digital terrain model (DTM) of the bare ground from each CSM, plant heights were calculated pixel-wise. Manual measurements aligned well with the TLS data and demonstrated the main benefit of CSMs: the highly detailed acquisition of the entire crop surface. The plant height data were used to estimate biomass with empirically developed biomass regression models (BRMs). Validation analyses against destructive measurements were carried out to confirm the results. The spatial and temporal transferability of crop-specific BRMs was shown. In one case study, the estimations from plant height and six VIs were compared and the benefit of fusing both parameters was investigated. The analyses were based on the TLS-derived CSMs and spectral data measured with a field spectrometer. The important role of plant height as a robust estimator was shown in contrast to a varying performance of BRMs based on the VIs. A major benefit through the fusion of both parameters in multivariate BRMs could not be concluded in this study. Nevertheless, further research should address this fusion, with regard to the capability of VIs to assess information about the vegetation cover or biochemical and biophysical parameters

A Global Review of Empirical Models for Estimating Photosynthetically Active Radiation

A good working knowledge of photosynthetically active radiation (PAR) is of vital requirement for determining the terrestrial photosynthesis, primary productivity calculation, ecosystem-atmosphere carbon dioxide, plant physiology, biomass production, natural illumination in greenhouses, radiation climate, remote sensing of vegetation, and radiation regimes of plant canopy, photosynthesis, productivity models of vegetation, etc. However, routine measurement of PAR is not available in most location of interest across the globe. During the past 77 years in order to estimate PAR on hourly, daily and monthly mean basis, several empirical models have been developed for numerous locations globally. As a result, numerous input parameters have been utilized and different functional forms applied. This study was aim at classifying and reviewing the empirical models employed for estimating PAR across the globe. The empirical models so far utilized were classified into ten main categories and presented base on the input parameters applied. The models were further reclassified into numerous main sub-classes (groups) and finally presented according to their developing year. In general, 757 empirical models, 62 functional forms and 32 groups were reported in literature for estimating PAR across the globe. The empirical models utilized were equally compared with models developed using different artificial neural network (ANN); and the result revealed that ANN models are more suitable for estimating PAR across the globe. Thus, this review would provide solar energy researchers with input parameters and functional forms that have been widely used to up to date, and recognizing their importance in estimating PAR globally. Citation: Nwokolo, S. C., and Amadi, S. O. (2018). A Global Review of Empirical Models for Estimating Photosynthetically Active Radiation. Trends in Renewable Energy, 4(2), 236-327. DOI: 10.17737/tre.2018.4.2.007

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017

Remote Sensing for Precision Nitrogen Management

This book focuses on the fundamental and applied research of the non-destructive estimation and diagnosis of crop leaf and plant nitrogen status and in-season nitrogen management strategies based on leaf sensors, proximal canopy sensors, unmanned aerial vehicle remote sensing, manned aerial remote sensing and satellite remote sensing technologies. Statistical and machine learning methods are used to predict plant-nitrogen-related parameters with sensor data or sensor data together with soil, landscape, weather and/or management information. Different sensing technologies or different modelling approaches are compared and evaluated. Strategies are developed to use crop sensing data for in-season nitrogen recommendations to improve nitrogen use efficiency and protect the environment

Evaluating the sustainability of urban agriculture projects

Evaluating the sustainability of urban agriculture projects. 5. International Symposium for Farming Systems Design (AGRO2015

Groundwater Hydrology

The two fields of knowledge “geology” and “hydrology” always go hand in hand, often giving rise to the terms “geohydrology” and “hydrogeology.” The importance of the science of water, commonly called “hydrologic science,” is always complemented by the “science of the interior of the earth.” Whereas hydrology is concerned with the quality and quantity of underground water, its movement, extraction, and recharge, geology talks of the rock matrix and the structure in which this water is contained, stored, and moved around.In recent times, the knowledge of geohydrology or the hydrology of groundwater has gained an impetus many times its original scale; and with that, acquisition, expansion, research, advancement, and dissemination of this knowledge have become more significant. With so many dimensions of geohydrology available for exploration, research, and technological advancement, any work contributing to any dimension of geohydrology and groundwater will find its right place. This compilation of chapters is going to play a very important part in furthering the knowledge of geohydrology and may prove an interesting and useful read for various cross-sections of academia, researchers, engineers, hydrologists, and all categories of water consumers

New Approaches in Social, Environmental Management and Policy to Address SDGs

The book comprises a selection of papers addressing some of the most relevant challenges and opportunities for addressing SDGs from many different perspectives. Papers in this collection cover the most recent lines and approaches of research in addressing SDGs and are all novel propositions that deepen the analysis of environmental, social and governance strategies in the adaptation of the society to meet the 17 SDGs