Soil moisture map construction using microwave remote sensors and sequential data assimilation Article Swipe
Bernard T. Agyeman
,
Bo Song
,
Soumya Ranjan Sahoo
,
Xunyuan Yin
,
Jinfeng Liu
,
Sirish L. Shah
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2010.07037
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2010.07037
Microwave remote sensors mounted on center pivot irrigation systems provide a feasible approach to obtain soil moisture information, in the form of water content maps, for the implementation of closed-loop irrigation. Major challenges such as significant time delays in the soil moisture measurements, the inability of the sensors to provide soil moisture information in instances where the center pivot is stationary, and the inability of the sensors to provide soil moisture information in the root zone reduce the usability of the water content maps in the effective implementation of closed-loop irrigation. In this paper, we seek to address the aforementioned challenges and consequently describe a water content map construction procedure that is suitable for the implementation of closed-loop irrigation. Firstly, we propose the cylindrical coordinates version of the Richards equation (field model) which naturally models fields equipped with a center pivot irrigation system. Secondly, measurements obtained from the microwave sensors are assimilated into the field model using the extended Kalman filter to form an information fusion system, which will provide frequent soil moisture estimates and predictions in the form of moisture content maps. The utility of the proposed information fusion system is first investigated with simulated microwave sensor measurements. The information fusion system is then applied to a real large-scale agriculture field where we demonstrate the its ability to address the challenges. Three performance evaluation criteria are used to validate the soil moisture estimates and predictions provided by the proposed information fusion system.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2010.07037
- https://arxiv.org/pdf/2010.07037
- OA Status
- green
- Cited By
- 2
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3092896522
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3092896522Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2010.07037Digital Object Identifier
- Title
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Soil moisture map construction using microwave remote sensors and sequential data assimilationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-09-28Full publication date if available
- Authors
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Bernard T. Agyeman, Bo Song, Soumya Ranjan Sahoo, Xunyuan Yin, Jinfeng Liu, Sirish L. ShahList of authors in order
- Landing page
-
https://arxiv.org/abs/2010.07037Publisher landing page
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https://arxiv.org/pdf/2010.07037Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2010.07037Direct OA link when available
- Concepts
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Data assimilation, Remote sensing, Assimilation (phonology), Environmental science, Water content, Microwave, Soil science, Meteorology, Computer science, Geography, Geology, Geotechnical engineering, Telecommunications, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2022: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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27Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.pivot | 6, 58, 140 |
| abstract_inverted_index.using | 156 |
| abstract_inverted_index.water | 22, 81, 105 |
| abstract_inverted_index.where | 55, 212 |
| abstract_inverted_index.which | 132, 167 |
| abstract_inverted_index.(field | 130 |
| abstract_inverted_index.Kalman | 159 |
| abstract_inverted_index.center | 5, 57, 139 |
| abstract_inverted_index.delays | 37 |
| abstract_inverted_index.fields | 135 |
| abstract_inverted_index.filter | 160 |
| abstract_inverted_index.fusion | 165, 189, 201, 241 |
| abstract_inverted_index.model) | 131 |
| abstract_inverted_index.models | 134 |
| abstract_inverted_index.obtain | 14 |
| abstract_inverted_index.paper, | 93 |
| abstract_inverted_index.reduce | 76 |
| abstract_inverted_index.remote | 1 |
| abstract_inverted_index.sensor | 197 |
| abstract_inverted_index.system | 190, 202 |
| abstract_inverted_index.ability | 217 |
| abstract_inverted_index.address | 97, 219 |
| abstract_inverted_index.applied | 205 |
| abstract_inverted_index.content | 23, 82, 106, 181 |
| abstract_inverted_index.mounted | 3 |
| abstract_inverted_index.propose | 121 |
| abstract_inverted_index.provide | 9, 49, 68, 169 |
| abstract_inverted_index.sensors | 2, 47, 66, 149 |
| abstract_inverted_index.system, | 166 |
| abstract_inverted_index.system. | 142, 242 |
| abstract_inverted_index.systems | 8 |
| abstract_inverted_index.utility | 184 |
| abstract_inverted_index.version | 125 |
| abstract_inverted_index.Firstly, | 119 |
| abstract_inverted_index.Richards | 128 |
| abstract_inverted_index.approach | 12 |
| abstract_inverted_index.criteria | 225 |
| abstract_inverted_index.describe | 103 |
| abstract_inverted_index.equation | 129 |
| abstract_inverted_index.equipped | 136 |
| abstract_inverted_index.extended | 158 |
| abstract_inverted_index.feasible | 11 |
| abstract_inverted_index.frequent | 170 |
| abstract_inverted_index.moisture | 16, 41, 51, 70, 172, 180, 232 |
| abstract_inverted_index.obtained | 145 |
| abstract_inverted_index.proposed | 187, 239 |
| abstract_inverted_index.provided | 236 |
| abstract_inverted_index.suitable | 112 |
| abstract_inverted_index.validate | 229 |
| abstract_inverted_index.Microwave | 0 |
| abstract_inverted_index.Secondly, | 143 |
| abstract_inverted_index.effective | 86 |
| abstract_inverted_index.estimates | 173, 233 |
| abstract_inverted_index.inability | 44, 63 |
| abstract_inverted_index.instances | 54 |
| abstract_inverted_index.microwave | 148, 196 |
| abstract_inverted_index.naturally | 133 |
| abstract_inverted_index.procedure | 109 |
| abstract_inverted_index.simulated | 195 |
| abstract_inverted_index.usability | 78 |
| abstract_inverted_index.challenges | 32, 100 |
| abstract_inverted_index.evaluation | 224 |
| abstract_inverted_index.irrigation | 7, 141 |
| abstract_inverted_index.agriculture | 210 |
| abstract_inverted_index.assimilated | 151 |
| abstract_inverted_index.challenges. | 221 |
| abstract_inverted_index.closed-loop | 29, 89, 117 |
| abstract_inverted_index.coordinates | 124 |
| abstract_inverted_index.cylindrical | 123 |
| abstract_inverted_index.demonstrate | 214 |
| abstract_inverted_index.information | 52, 71, 164, 188, 200, 240 |
| abstract_inverted_index.irrigation. | 30, 90, 118 |
| abstract_inverted_index.large-scale | 209 |
| abstract_inverted_index.performance | 223 |
| abstract_inverted_index.predictions | 175, 235 |
| abstract_inverted_index.significant | 35 |
| abstract_inverted_index.stationary, | 60 |
| abstract_inverted_index.consequently | 102 |
| abstract_inverted_index.construction | 108 |
| abstract_inverted_index.information, | 17 |
| abstract_inverted_index.investigated | 193 |
| abstract_inverted_index.measurements | 144 |
| abstract_inverted_index.measurements, | 42 |
| abstract_inverted_index.measurements. | 198 |
| abstract_inverted_index.aforementioned | 99 |
| abstract_inverted_index.implementation | 27, 87, 115 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |