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Abstract
Delineating accurate nutrient fluxes and distributions in multimedia environments requires the integration of vast amounts of information. Such nutrient flows may be related to atmospheric deposition, agricultural runoff, and urbanization effect on surface and groundwater systems. Two types of significant undertakings for nutrient management have been in place for sustainable development. While many environmental engineering technologies for nutrient removal have been developed to secure tap water sources and improve the drinking water quality, various watershed management strategies for eutrophication control are moving to highlight the acute need for monitoring the dynamics and complexities that arise from nutrient impacts on water quality status and ecosystem state, both spatially and temporally. These monitoring methods and data are associated with local point measurements, air-borne remote sensing, and space-borne satellite images of spatiotemporal nutrient distributions leading to the generation of accurate environmental patterns. Within this context, several key water quality constituents, including total nitrogen, total phosphorus, chlorophyll-a concentration, colored dissolved organic matter (dissolved organic carbon or total organic carbon), harmful algal blooms (e.g., cyanobacterial toxins or microcystin concentrations), and descriptors of ecosystem states, such as total suspended sediment (or turbidity), transparency (e.g., Secchi disk depth), and temperature, will be of major concern. Considering the advancements, challenges, and accomplishments related to remote sensing technologies in the past four decades, we present a thorough literature review of contemporary state-of-the-art technologies of remote sensing platforms and sensors that may be employed to support essential scientific missions, and provide an in-depth discussion and new insight into various inversion methods (or models) to improve the estimation accuracy. In this study, the spectrum of these remote sensing technologies and models is first divided into groups based on chronological order associated with different platforms and sensors, although some of them may be subject to mission-oriented arrangements. Case-based and location-based studies were cited, organized, and summarized to further elucidate tracks of application potential that support future, forward-looking, cost-effective, and risk-informed nutrient management plans. The comprehensive reviews presented here should echo real-world observational evidence by using integrated sensing, monitoring, and modeling techniques to improve environmental management, policy analysis, and decision making.
NOMENCLATURE
Abbreviations
| Acronym | = | Meaning |
| AISA | = | Airborne Imaging Spectrometer for different Applications |
| ALOS | = | Advanced Land Observation Satellite |
| ANN | = | Artificial Neural Network |
| ASTER | = | Advanced Spaceborne Thermal Emission and Reflection Radiometer |
| AVHRR | = | Advanced Very High Resolution Radiometer |
| AVIRIS | = | Airborne Visible/Infrared Imaging Spectrometer |
| CASI | = | Compact Airborne Spectrographic Imager |
| CBERS | = | China-Brazil Earth Resources Satellite |
| CDOM | = | Colored Dissolved Organic Matter |
| CERP | = | Comprehensive Everglades Restoration Plan |
| CZCS | = | Coastal Zone Color Scanner |
| DO | = | Dissolved Oxygen |
| DOC | = | Dissolved Organic Carbon |
| ENVISAT | = | Environmental Satellite |
| EO-1 | = | Earth Observing-1 |
| EOS | = | Earth Observing System |
| EROS | = | Earth Resources Observation Satellite |
| ERS | = | European Remote-Sensing Satellite |
| ERTS | = | Earth Resources Technology Satellite |
| ETM+ | = | Enhanced Thematic Mapper Plus |
| GA-PLS | = | Genetic Algorithms with Partial Least Squares |
| GEGA | = | Grammatical Evolution - Genetic Algorithm |
| GIS | = | Geographical Information System |
| GP | = | Genetic Programming |
| HABs | = | Harmful Algal Blooms |
| HRG | = | High Resolution Geometric |
| HRV | = | High Resolution Visible |
| HRVIR | = | High Resolution Visible and Infrared |
| IDFM | = | Integrated Data Fusion and Machine-learning |
| IoT | = | Internet of Things |
| IR | = | Infrared |
| IRIS | = | Internet Routing in Space |
| IRS | = | Indian Remote Sensing |
| JPL | = | Jet Propulsion Laboratory |
| JERS-1 | = | Japanese Earth Resources Satellite 1 |
| KITSAT | = | Korea Institute of Technology Satellite |
| LMR | = | Linear Multiple Regression |
| MERIS | = | Medium Resolution Imaging Spectrometer |
| MIR | = | Mid-band Infrared |
| MODIS | = | Moderate-Resolution Imaging Spectroradiometer |
| MAE | = | Mean Absolute Error |
| MSS | = | Multispectral Scanner System |
| MW | = | Microwave |
| N | = | Nitrogen |
| NH3 | = | Ammonia |
| NIR | = | Near Infrared |
| NOx | = | Nitrogen Oxides |
| NOAA | = | National Oceanic and Atmospheric Administration |
| NRC | = | National Research Council |
| OSA | = | Optical Sensor Assembly |
| P | = | Phosphorous |
| Pan | = | Panchromatic |
| PALSAR | = | Phased Array type L-band Synthetic Aperture Radar |
| PSO | = | Particle swarm Optimization |
| RADAR | = | Radio Detection and Ranging |
| RBFN | = | Radial Basis Function Network |
| RBV | = | Return Beam Vidicon |
| RMSE | = | Root Mean Square Error |
| SAR | = | Synthetic Aperture Radar |
| SDD | = | Secchi Disk Depth |
| SE | = | Standard Error |
| SeaWiFS | = | Sea-viewing Wide Field-of-view Sensor SeaWiFS |
| SMMR | = | Scanning Multi-channel Microwave Radiometer |
| SMAP | = | Soil Moisture Active Passive satellite |
| SMOS | = | Soil Moisture and Ocean Salinity satellite |
| SPOT | = | Système Pour l’Observation de la Terre |
| SR | = | Scanning Radiometer |
| SST | = | Sea Surface Temperature |
| SVM | = | Support Vector Machine |
| TIR | = | Thermal Infrared |
| TM | = | Thematic Mapper |
| TN | = | Total Nitrogen |
| TNDVI | = | Transformed Normalized Difference Vegetation index |
| TOC | = | Total Organic Carbon |
| TP | = | Total Phosphorous |
| TSI | = | Trophic State Index |
| TSM | = | Total Suspended Matter |
| TSS | = | Total Suspended Solids |
| USEPA | = | United States Environmental Protection Agency |
| USGS | = | United States Geological Survey |
| VHRR | = | Very High Resolution Radiometer |
| VIS | = | Visible |
| WHO | = | World Health Organization |