Results 21 to 30 of about 2,336,597 (324)

Smart Irrigation Controllers: How Do Soil Moisture Sensor (SMS) Irrigation Controllers Work?

EDIS, 2009
Revised! AE437, a 5-page illustrated fact sheet by Michael D. Dukes, Mary Shedd, and Bernard Cardenas-Lailhacar, is part of the Smart Irrigation Controllers series. It describes how soil moisture sensor systems work, rules for installation, setting the sensor threshold, and programming the irrigation timer. Includes references.
Michael D. Dukes, Mary Shedd, Bernard Cardenas-Lailhacar   +2 more
openaire   +6 more sources

A Long-term Consistent Artificial Intelligence and Remote Sensing-based Soil Moisture Dataset

Scientific Data, 2023
The Consistent Artificial Intelligence (AI)-based Soil Moisture (CASM) dataset is a global, consistent, and long-term, remote sensing soil moisture (SM) dataset created using machine learning.
Olya Skulovich, Pierre Gentine
doaj   +1 more source

Estimation and Validation Study of Soil Moisture Using GPS-IR Technique Over a Tropical Region: Variability of SM With Rainfall and Energy Fluxes [PDF]

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Soil Moisture (SM) data play an important role in different fields of research like hydrology, agriculture, climatology, etc. In this article, global positioning system interferometric reflectometry technique was used to estimate SM. Estimated SM data have been validated and compared with collocated in situ probe, Soil Moisture and Ocean Salinity (SMOS)
Gummadipudi Naga Madhavi, P. Sharath Kumar, Radhika A. Chipade, Jyoti Bhate, Tummalapalli Venkata Chandrasekhar Sarma   +4 more
openaire   +3 more sources

Soil Moisture Mapping with Moisture-Related Indices, OPTRAM, and an Integrated Random Forest-OPTRAM Algorithm from Landsat 8 Images

Remote Sensing, 2022
Remote sensing tools have been extensively used for large-scale soil moisture (SM) mapping in recent years, using Landsat satellite images. Rainfall, soil clay percentage, and the standardized precipitation index play key roles in determining the ...
Umesh Acharya, Aaron L. M. Daigh, Peter G. Oduor   +2 more
doaj   +1 more source

Improving Surface Soil Moisture Estimation Through Assimilating Satellite Land Surface Temperature With a Linear SM-LST Relationship

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Soil moisture (SM) plays a vital role in linking the global terrestrial water, energy, and carbon cycles. Land data assimilation (DA) is typically applied for acquiring more accurate SM estimates by incorporating remote sensing (RS) retrievals to constraint model parameters and system states.
Jiaxin Tian, Hui Lu 0003, Kun Yang 0004, Jun Qin, Long Zhao, Yaozhi Jiang, Pengfei Shi, Xiaogang Ma 0004, Jianhong Zhou   +8 more
openaire   +2 more sources

The NAFE'05/CoSMOS Data Set: Toward SMOS Soil Moisture Retrieval, Downscaling, and Assimilation [PDF]

, 2008
The National Airborne Field Experiment 2005 (NAFE'05) and the Campaign for validating the Operation of Soil Moisture and Ocean Salinity (COSMOS) were undertaken in November 2005 in the Goulburn River catchment, which is located in southeastern Australia.
Berger, Michael, Hacker, Joerg .M., Merlin, Olivier, Hacker, Jorg Michael, Walker, Jeffrey P., Skou, Niels, Kim, Edward J., Kim, Edward, Panciera, Rocco, Walker, Jeffrey, Kalma, Jetse D, Kalma, Jetse D.   +11 more
core   +1 more source

Evaluation of Multi-Source Soil Moisture Datasets over Central and Eastern Agricultural Area of China Using In Situ Monitoring Network

Remote Sensing, 2021
Multi-source soil moisture (SM) products provide a vigorous tool for the estimation of soil moisture on a large scale, but it is crucial to carry out the evaluation of those products before further application.
Yanqing Yang, Jianyun Zhang, Zhenxin Bao, Tianqi Ao, Guoqing Wang, Houfa Wu, Jie Wang   +6 more
doaj   +1 more source

Parameter Sensitivity in LSMs: An Analysis Using Stochastic Soil Moisture Models and ELDAS Soil Parameters [PDF]

, 2009
Integration of simulated and observed states through data assimilation as well as model evaluation requires a realistic representation of soil moisture in land surface models (LSMs).
Hurk, B., van den, Seneviratne, S.I., Uijlenhoet, R., Teuling, A.J.   +3 more
core   +1 more source

Temporal stability of soil moisture and radar backscatter observed by the advanced Synthetic Aperture Radar (ASAR) [PDF]

, 2008
The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics.
Annett Bartsch, Doubkova, Marcela, Bartsch, Annett, Pathe, Carsten, Scipal, K., Klaus Scipal, Günter Blöschl, Bloschl, G., Martinez-Fernandez, J., Pathe, C., Wolfgang Wagner, Alexander Löw, Scipal, Klaus, Hasenauer, Stefan, Doubkova, M., Bloschl, Guenter, Bartsch, A., José Martínez-Fernández, Sabel, Daniel, Löw, Alexander, Stefan Hasenauer, Loew, A., Daniel Sabel, Marcela Doubkova, Hasenauer, S., Wagner, W., Carsten Pathe, Martinez-Fernandez, Jose, José Martínez-Fernández, Wagner, Wolfgang, Günter Blöschl, Sabel, D., Alexander Löw   +32 more
core   +1 more source

A proposal for a SAR interferometric model of soil moisture [PDF]

, 2012
Since long it is known that SAR interferometric observables are influenced by soil moisture variations, however there is a lack of scattering models that link interferometric observables and variations of the dielectric properties.
De Zan, Francesco, Alessandro Parizzi, Parizzi, Alessandro, Francesco De Zan, Pau Prats, Prats, Pau   +5 more
core   +1 more source