CN114264672A - Deep soil humidity inversion method based on microwave remote sensing - Google Patents
Deep soil humidity inversion method based on microwave remote sensing Download PDFInfo
- Publication number
- CN114264672A CN114264672A CN202111580975.2A CN202111580975A CN114264672A CN 114264672 A CN114264672 A CN 114264672A CN 202111580975 A CN202111580975 A CN 202111580975A CN 114264672 A CN114264672 A CN 114264672A
- Authority
- CN
- China
- Prior art keywords
- soil
- remote sensing
- deep soil
- microwave remote
- deep
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
- Radiation Pyrometers (AREA)
Abstract
The invention discloses a deep soil humidity inversion method based on microwave remote sensing, which comprises the steps of obtaining deep soil data, calculating the emissivity and the reflectivity of the deep soil, constructing an inversion model and inverting the deep soil humidity; the method comprises the steps of obtaining the brightness temperature of deep soil to be measured based on microwave remote sensing, obtaining the physical temperature of the deep soil to be measured through a soil measuring instrument, calculating the emissivity and the reflectivity of the deep soil according to obtained data, and inverting the emissivity, the reflectivity and the equivalent dielectric constant of the soil through a constructed inversion model, so that the deep soil humidity is obtained.
Description
Technical Field
The invention relates to the technical field of soil moisture content inversion, in particular to a deep soil humidity inversion method based on microwave remote sensing.
Background
The soil water is unsaturated water in soil layer, which is widely distributed on land surface layer and is necessary water source for plant growth, so the soil water resource is important resource related to agricultural production quality, meanwhile, the soil water resource is a link for mutual conversion of surface water and underground water, which can enter into atmosphere in a steaming mode and be supplemented in the soil surface layer in a precipitation mode, so the soil water resource is a core factor in surface energy exchange and is also an important carrier composition of global surface substance energy circulation, the water content in soil is also called soil humidity and is a physical quantity representing the dryness and wetness degree of soil, which is a relative variable of the soil water content, usually expressed by the percentage of the soil water content in dry soil, also called soil moisture, and the soil moisture is an important input parameter thereof in various hydrological models, climate models and ecological models, and in drought, In natural disasters such as flood, debris flow landslide and the like, corresponding models can be established according to the distribution and the space-time change of soil moisture, and better help and support are provided.
At present, a plurality of methods for measuring the moisture in soil exist, but the existing method has a complex mechanism for inverting the moisture of deep soil and complex processing steps, improves the application cost of the method to a certain extent, is inconvenient to popularize, cannot meet the requirement of obtaining large-range spatial distribution information of the moisture of the deep soil within a specified time, cannot ensure the measurement precision, so that the application range is limited, cannot be suitable for different application scenes, and has low applicability, therefore, the invention provides the deep soil moisture inversion method based on microwave remote sensing to solve the problems in the prior art.
Disclosure of Invention
Aiming at the problems, the invention aims to provide a deep soil humidity inversion method based on microwave remote sensing, the method comprises the steps of obtaining the brightness temperature of deep soil to be measured based on microwave remote sensing, obtaining the physical temperature of the deep soil to be measured through a soil measuring instrument, calculating the emissivity and the reflectivity of the deep soil according to the obtained data, and inverting the emissivity, the reflectivity and the equivalent dielectric constant of the soil through a constructed inversion model to obtain the deep soil humidity.
In order to achieve the purpose of the invention, the invention is realized by the following technical scheme: a deep soil humidity inversion method based on microwave remote sensing comprises the following steps:
the method comprises the following steps: firstly, transmitting a radio frequency signal to a deep soil target at a high altitude through a microwave remote sensing transmitter, receiving an echo signal of the deep soil target through a microwave remote sensing receiver, measuring the brightness temperature of the deep soil, then drilling a hole in the monitoring area, wherein the drilling depth is 5-10 m, then extending a probe of a soil measuring instrument into the drilling hole, and measuring the physical temperature of the deep soil;
step two: firstly, preprocessing acquired soil brightness temperature data and soil physical temperature data, including filtering noise reduction, geometric correction and radiation correction, constructing a bispectrum scattering model, calculating soil emissivity according to the preprocessed soil brightness temperature data and the preprocessed soil physical temperature data, and then calculating soil reflectivity according to the soil emissivity;
step three: constructing a soil humidity inversion model comprising an input module, a feature mining module, a numerical simulation module and an output module by taking a full connection layer as a basic unit based on a depth confidence network structure model;
step four: the equivalent dielectric constant of the deep soil in the monitoring area is obtained, then the equivalent dielectric constant of the soil, the emissivity of the soil and the reflectivity of the soil are input into a soil humidity inversion model for inversion, and finally the humidity inversion value of the deep soil is obtained.
The further improvement lies in that: in the first step, the frequency of the radio frequency signal transmitted by the microwave remote sensing transmitter is 4GHz-6GHz, the microwave remote sensing transmitter is provided with a polarized antenna, the polarized antenna adopts vertical receiving polarization and horizontal receiving polarization, and the incident angle of the antenna is 30-45 degrees.
The further improvement lies in that: in the first step, the soil measuring instrument is realized by adopting a mode of heating a temperature sensor by a single chip microcomputer, the temperature sensor is arranged in a probe of the soil measuring instrument, the temperature sensor is a digital temperature sensor or a thermistor temperature sensor, the temperature range is-30-50 ℃, and the probe of the soil measuring instrument is subjected to anti-corrosion and waterproof treatment.
The further improvement lies in that: in the second step, the emissivity of the soil is equal to the ratio of the brightness temperature of the soil to the physical temperature of the soil, and the sum of the reflectivity of the soil and the emissivity of the soil is equal to 1.
The further improvement lies in that: in the second step, the specific step of constructing the double-spectrum scattering model is to construct a random rough surface in a spectrum domain, decompose a related spectrum into the sum of two independent random rough surfaces by dividing, construct a double-spectrum surface by adopting a surface spectrum domain theory on the basis of a kirchhoff model and a small disturbance model, and select a corresponding surface spectrum filter to obtain the random rough surface double-spectrum scattering model.
The further improvement lies in that: in the third step, each neuron in the fully connected layer is fully connected with all neurons in the previous layer, and the features extracted by the fully connected layer in front of the neuron are integrated.
The further improvement lies in that: in the third step, the input module is used for inputting parameter data, the feature mining module is used for extracting features in the input parameter data, the numerical simulation module is used for expressing the mined features, and the output module is used for outputting the soil humidity value.
The further improvement lies in that: in the fourth step, the specific steps of obtaining the equivalent dielectric constant of the deep soil of the monitored area are as follows: and collecting a sample of deep soil in the monitored area, performing component analysis to obtain soil component composition, and calculating the equivalent dielectric constant of the soil by using the soil component composition.
The invention has the beneficial effects that: the method comprises the steps of obtaining the brightness temperature of deep soil to be measured based on microwave remote sensing, obtaining the physical temperature of the deep soil to be measured through a soil measuring instrument, calculating the emissivity and the reflectivity of the deep soil according to obtained data, and inverting the emissivity, the reflectivity and the equivalent dielectric constant of the soil through a constructed inversion model, so that the deep soil humidity is obtained.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method according to a first embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, the present embodiment provides a deep soil moisture inversion method based on microwave remote sensing, including the following steps:
the method comprises the following steps: firstly, a microwave remote sensing transmitter transmits a radio frequency signal to a deep soil target at high altitude to a monitoring area, then a microwave remote sensing receiver receives an echo signal of the deep soil target to measure the brightness temperature of the deep soil, then the monitoring area is drilled, the depth of the drilled hole is 5 meters, then a probe of a soil measuring instrument is extended into the drilled hole to measure the physical temperature of the deep soil, the frequency of the radio frequency signal transmitted by the microwave remote sensing transmitter is 4GHz, the microwave remote sensing transmitter is provided with a polarized antenna, the polarized antenna adopts vertical receiving polarization and horizontal receiving polarization, the incident angle of the antenna is 30 degrees, the soil measuring instrument is realized by adopting a mode of a single chip microcomputer and a temperature sensor, the temperature sensor is arranged in the probe of the soil measuring instrument, the temperature sensor adopts a digital temperature sensor or a thermistor temperature sensor, and the temperature range is between-30 ℃ and 50 ℃, carrying out anti-corrosion and waterproof treatment on a probe of the soil measuring instrument;
step two: firstly, preprocessing acquired soil brightness temperature data and soil physical temperature data including filtering noise reduction, geometric correction and radiation correction, ensuring the measurement precision to a certain extent by preprocessing the acquired data, then constructing a dual-spectrum scattering model, calculating the soil emissivity according to the preprocessed soil brightness temperature data and the soil physical temperature data, then calculating the soil reflectivity according to the soil emissivity, wherein the soil emissivity is equal to the ratio of the soil brightness temperature to the soil physical temperature, the sum of the soil reflectivity and the soil emissivity is equal to 1, constructing the dual-spectrum scattering model by specifically constructing a random rough surface in a spectrum domain, dividing a related spectrum to decompose the random rough surface into the sum of two independent random rough surfaces, and constructing a dual-spectrum surface by adopting a surface spectrum domain theory on the basis of a kirchhoff model and a small disturbance model, selecting a corresponding surface spectrum filter to obtain a random rough surface double-spectrum scattering model;
step three: constructing a soil humidity inversion model comprising an input module, a feature mining module, a numerical simulation module and an output module by taking a full connection layer as a basic unit based on a depth confidence network structure model;
step four: the method comprises the following steps of firstly obtaining the equivalent dielectric constant of deep soil of a monitoring area, inputting the equivalent dielectric constant of the soil, the emissivity of the soil and the reflectivity of the soil into a soil humidity inversion model for inversion, finally obtaining a humidity inversion value of the deep soil, fully connecting each neuron in a full connection layer with all neurons in the previous layer, and integrating the characteristics extracted by the full connection layer in front of the neuron, wherein an input module is used for inputting parameter data, a characteristic mining module is used for extracting the characteristics in the input parameter data, a numerical simulation module is used for expressing the excavated characteristics, an output module is used for outputting a soil humidity value, and the concrete steps of obtaining the equivalent dielectric constant of the deep soil of the monitoring area are as follows: and collecting a sample of deep soil in the monitored area, performing component analysis to obtain soil component composition, and calculating the equivalent dielectric constant of the soil by using the soil component composition.
Example two
Referring to fig. 1, the present embodiment provides a deep soil moisture inversion method based on microwave remote sensing, including the following steps:
the method comprises the following steps: firstly, a microwave remote sensing transmitter transmits a radio frequency signal to a deep soil target at high altitude to a monitoring area, then a microwave remote sensing receiver receives an echo signal of the deep soil target to measure the brightness temperature of the deep soil, then the monitoring area is drilled, the depth of the drilled hole is 10 meters, then a probe of a soil measuring instrument is extended into the drilled hole to measure the physical temperature of the deep soil, the frequency of the radio frequency signal transmitted by the microwave remote sensing transmitter is 6GHz, the microwave remote sensing transmitter is provided with a polarized antenna, the polarized antenna adopts vertical receiving polarization and horizontal receiving polarization, the incident angle of the antenna is 45 degrees, the soil measuring instrument is realized by adopting a mode of a single chip microcomputer and a temperature sensor, the temperature sensor is arranged in the probe of the soil measuring instrument, the temperature sensor adopts a digital temperature sensor or a thermistor temperature sensor, and the temperature range is between-30 ℃ and 50 ℃, carrying out anti-corrosion and waterproof treatment on a probe of the soil measuring instrument;
step two: firstly, preprocessing the acquired soil brightness temperature data and soil physical temperature data, including filtering noise reduction, geometric correction and radiation correction, then constructing a bispectrum scattering model, calculating the emissivity of the soil according to the brightness temperature data of the pretreated soil and the physical temperature data of the soil, then calculating the reflectivity of the soil according to the emissivity of the soil, wherein the emissivity of the soil is equal to the ratio of the brightness temperature of the soil to the physical temperature of the soil, the sum of the reflectivity of the soil and the emissivity of the soil is equal to 1, constructing a dual-spectrum scattering model by constructing a random rough surface in a spectrum domain, dividing a related spectrum to decompose the random rough surface into the sum of two independent random rough surfaces, on the basis of a kirchhoff model and a small disturbance model, a dual-spectrum surface is constructed by adopting a surface spectrum domain theory, and a corresponding surface spectrum filter is selected to obtain a random rough surface dual-spectrum scattering model;
step three: constructing a soil humidity inversion model comprising an input module, a feature mining module, a numerical simulation module and an output module by taking a full connection layer as a basic unit based on a depth confidence network structure model;
step four: the method comprises the following steps of firstly obtaining the equivalent dielectric constant of deep soil of a monitoring area, inputting the equivalent dielectric constant of the soil, the emissivity of the soil and the reflectivity of the soil into a soil humidity inversion model for inversion, finally obtaining a humidity inversion value of the deep soil, fully connecting each neuron in a full connection layer with all neurons in the previous layer, and integrating the characteristics extracted by the full connection layer in front of the neuron, wherein an input module is used for inputting parameter data, a characteristic mining module is used for extracting the characteristics in the input parameter data, a numerical simulation module is used for expressing the excavated characteristics, an output module is used for outputting a soil humidity value, and the concrete steps of obtaining the equivalent dielectric constant of the deep soil of the monitoring area are as follows: and collecting a sample of deep soil in the monitored area, performing component analysis to obtain soil component composition, and calculating the equivalent dielectric constant of the soil by using the soil component composition.
The method comprises the steps of obtaining the brightness temperature of deep soil to be detected based on microwave remote sensing, obtaining the physical temperature of the deep soil to be detected through a soil measuring instrument, calculating the emissivity and the reflectivity of the deep soil according to obtained data, and inverting the emissivity, the reflectivity and the equivalent dielectric constant of the soil through a constructed inversion model, so that the more accurate humidity of the deep soil in a monitoring area is obtained.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A deep soil humidity inversion method based on microwave remote sensing is characterized by comprising the following steps:
the method comprises the following steps: firstly, transmitting a radio frequency signal to a deep soil target at a high altitude through a microwave remote sensing transmitter, receiving an echo signal of the deep soil target through a microwave remote sensing receiver, measuring the brightness temperature of the deep soil, then drilling a hole in the monitoring area, wherein the drilling depth is 5-10 m, then extending a probe of a soil measuring instrument into the drilling hole, and measuring the physical temperature of the deep soil;
step two: firstly, preprocessing acquired soil brightness temperature data and soil physical temperature data, including filtering noise reduction, geometric correction and radiation correction, constructing a bispectrum scattering model, calculating soil emissivity according to the preprocessed soil brightness temperature data and the preprocessed soil physical temperature data, and then calculating soil reflectivity according to the soil emissivity;
step three: constructing a soil humidity inversion model comprising an input module, a feature mining module, a numerical simulation module and an output module by taking a full connection layer as a basic unit based on a depth confidence network structure model;
step four: the equivalent dielectric constant of the deep soil in the monitoring area is obtained, then the equivalent dielectric constant of the soil, the emissivity of the soil and the reflectivity of the soil are input into a soil humidity inversion model for inversion, and finally the humidity inversion value of the deep soil is obtained.
2. The deep soil humidity inversion method based on microwave remote sensing according to claim 1, characterized in that: in the first step, the frequency of the radio frequency signal transmitted by the microwave remote sensing transmitter is 4GHz-6GHz, the microwave remote sensing transmitter is provided with a polarized antenna, the polarized antenna adopts vertical receiving polarization and horizontal receiving polarization, and the incident angle of the antenna is 30-45 degrees.
3. The deep soil humidity inversion method based on microwave remote sensing according to claim 1, characterized in that: in the first step, the soil measuring instrument is realized by adopting a mode of heating a temperature sensor by a single chip microcomputer, the temperature sensor is arranged in a probe of the soil measuring instrument, the temperature sensor is a digital temperature sensor or a thermistor temperature sensor, the temperature range is-30-50 ℃, and the probe of the soil measuring instrument is subjected to anti-corrosion and waterproof treatment.
4. The deep soil humidity inversion method based on microwave remote sensing according to claim 1, characterized in that: in the second step, the emissivity of the soil is equal to the ratio of the brightness temperature of the soil to the physical temperature of the soil, and the sum of the reflectivity of the soil and the emissivity of the soil is equal to 1.
5. The deep soil humidity inversion method based on microwave remote sensing according to claim 1, characterized in that: in the second step, the specific step of constructing the double-spectrum scattering model is to construct a random rough surface in a spectrum domain, decompose a related spectrum into the sum of two independent random rough surfaces by dividing, construct a double-spectrum surface by adopting a surface spectrum domain theory on the basis of a kirchhoff model and a small disturbance model, and select a corresponding surface spectrum filter to obtain the random rough surface double-spectrum scattering model.
6. The deep soil humidity inversion method based on microwave remote sensing according to claim 1, characterized in that: in the third step, each neuron in the fully connected layer is fully connected with all neurons in the previous layer, and the features extracted by the fully connected layer in front of the neuron are integrated.
7. The deep soil humidity inversion method based on microwave remote sensing according to claim 1, characterized in that: in the third step, the input module is used for inputting parameter data, the feature mining module is used for extracting features in the input parameter data, the numerical simulation module is used for expressing the mined features, and the output module is used for outputting the soil humidity value.
8. The deep soil humidity inversion method based on microwave remote sensing according to claim 1, characterized in that: in the fourth step, the specific steps of obtaining the equivalent dielectric constant of the deep soil of the monitored area are as follows: and collecting a sample of deep soil in the monitored area, performing component analysis to obtain soil component composition, and calculating the equivalent dielectric constant of the soil by using the soil component composition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111580975.2A CN114264672A (en) | 2021-12-22 | 2021-12-22 | Deep soil humidity inversion method based on microwave remote sensing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111580975.2A CN114264672A (en) | 2021-12-22 | 2021-12-22 | Deep soil humidity inversion method based on microwave remote sensing |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114264672A true CN114264672A (en) | 2022-04-01 |
Family
ID=80828869
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111580975.2A Pending CN114264672A (en) | 2021-12-22 | 2021-12-22 | Deep soil humidity inversion method based on microwave remote sensing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114264672A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116229285A (en) * | 2023-05-06 | 2023-06-06 | 深圳大学 | Soil water content monitoring method integrating Internet of things data and space scene |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104155007A (en) * | 2014-09-01 | 2014-11-19 | 中国科学院地理科学与资源研究所 | Multi-angle full-automatic earth surface fine emissivity spectrum collecting system device |
| CN106018439A (en) * | 2016-07-05 | 2016-10-12 | 吉林大学 | Microwave remote sensing soil moisture monitoring system and monitoring method thereof |
| CN108761034A (en) * | 2018-05-16 | 2018-11-06 | 河海大学 | A kind of multi-source satellite soil moisture retrieval method |
| CN111597751A (en) * | 2020-03-24 | 2020-08-28 | 自然资源部第一海洋研究所 | Crude oil film absolute thickness inversion method based on self-expansion depth confidence network |
-
2021
- 2021-12-22 CN CN202111580975.2A patent/CN114264672A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104155007A (en) * | 2014-09-01 | 2014-11-19 | 中国科学院地理科学与资源研究所 | Multi-angle full-automatic earth surface fine emissivity spectrum collecting system device |
| CN106018439A (en) * | 2016-07-05 | 2016-10-12 | 吉林大学 | Microwave remote sensing soil moisture monitoring system and monitoring method thereof |
| CN108761034A (en) * | 2018-05-16 | 2018-11-06 | 河海大学 | A kind of multi-source satellite soil moisture retrieval method |
| CN111597751A (en) * | 2020-03-24 | 2020-08-28 | 自然资源部第一海洋研究所 | Crude oil film absolute thickness inversion method based on self-expansion depth confidence network |
Non-Patent Citations (4)
| Title |
|---|
| 焦李成 等: "《人工智能、类脑计算与图像解译前沿》", 30 November 2019, 西安电子科技大学出版社 * |
| 袁苇等: "不同微波遥感模态和不同数据组合的等湿度区域分布与土壤湿度的反演", 《中国工程科学》 * |
| 陈堃 等: "基于深度置信网络的 GNSS-IR土壤湿度反演", 《测绘通报》 * |
| 韩念龙等: "被动微波反演裸露区土壤水分综述", 《吉林大学学报(地球科学版)》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116229285A (en) * | 2023-05-06 | 2023-06-06 | 深圳大学 | Soil water content monitoring method integrating Internet of things data and space scene |
| CN116229285B (en) * | 2023-05-06 | 2023-08-04 | 深圳大学 | Soil water content monitoring method integrating Internet of things data and space scene |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | Interpolated or satellite-based precipitation? Implications for hydrological modeling in a meso-scale mountainous watershed on the Qinghai-Tibet Plateau | |
| Guo et al. | Impact of root water content on root biomass estimation using ground penetrating radar: evidence from forward simulations and field controlled experiments | |
| Jensen et al. | HOBE: The Danish hydrological observatory | |
| CN106767687A (en) | A kind of method of utilization remote sensing moisture measurement beach elevation | |
| CN109343125B (en) | Red soil key zone underground structure space prediction method based on ground penetrating radar | |
| Myeni et al. | Present status of soil moisture estimation over the African continent | |
| CN109871637B (en) | Near-ground air temperature estimation method under cloud-sky condition | |
| Brauer et al. | The effect of differences between rainfall measurement techniques on groundwater and discharge simulations in a lowland catchment | |
| Bian et al. | Integrated method of RS and GPR for monitoring the changes in the soil moisture and groundwater environment due to underground coal mining | |
| Bocchiola et al. | Spatial estimation of Snow Water Equivalent at different dates within the Adamello Park of Italy | |
| Wang et al. | Assessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data | |
| Cao et al. | Mapping the response of volumetric soil water content to an intense rainfall event at the field scale using GPR | |
| CN109490920A (en) | A kind of method for building up of wetland DDM waveform and multipath simulation model | |
| Liu et al. | Noninvasive 2D and 3D mapping of root zone soil moisture through the detection of coarse roots with ground‐penetrating radar | |
| CN201724913U (en) | Non-contact soil humidity measurement instrument | |
| Rawat et al. | An integrated approach to estimate surface soil moisture in agricultural lands | |
| CN114264672A (en) | Deep soil humidity inversion method based on microwave remote sensing | |
| Choi et al. | Remote sensing observatory validation of surface soil moisture using Advanced Microwave Scanning Radiometer E, Common Land Model, and ground based data: Case study in SMEX03 Little River Region, Georgia, US | |
| Balenzano et al. | A ground network for SAR-derived soil moisture product calibration, validation and exploitation in Southern Italy | |
| Payero et al. | Development and application of cell-phone-based internet of things (IoT) systems for soil moisture monitoring | |
| Shi et al. | Improving soil moisture retrieval from GNSS-interferometric reflectometry: Parameters optimization and data fusion via neural network | |
| Pang et al. | The review of soil moisture multi-scale verification methods | |
| CN107451348A (en) | A kind of optimization evaluation method of L-band forest microwave radiation transmission characteristic | |
| Fontaine et al. | Application of electromagnetic induction to develop a precision irrigation framework to facilitate smallholder dry season farming in the Nasia-Kparigu area of northern Ghana | |
| Nwogwu et al. | Development of a Solar-Powered Integrated Wireless Soil Moisture Meter |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |