Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction
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TLDR
In this article, the authors developed a data assimilation-crop modeling framework that incorporates remotely sensed soil moisture and leaf area index (LAI) into a crop model using sequential data assimation, which is used to control crop model runs, assimilate remote sensing (RS) data and update model state variables.About:
This article is published in Remote Sensing of Environment.The article was published on 2013-11-01 and is currently open access. It has received 298 citations till now. The article focuses on the topics: Crop simulation model & Soil water.read more
Citations
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The Ensemble Kalman Filter: Theoretical formulation and practical implementation
TL;DR: The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it as mentioned in this paper, and also presents new ideas and alternative interpretations which further explain the success of the EnkF.
Journal ArticleDOI
Remote sensing for agricultural applications: A meta-review
TL;DR: In this paper, the authors present the agronomical variables and plant traits that can be estimated by remote sensing, and describe the empirical and deterministic approaches to retrieve them, and provide a synthesis of the emerging opportunities that should strengthen the role of remote sensing in providing operational, efficient and long-term services for agricultural applications.
Journal ArticleDOI
A review of data assimilation of remote sensing and crop models
TL;DR: In this article, a detailed overview of the latest developments and applications of crop models, remote sensing techniques, and data assimilation methods in the growth status monitoring and yield estimation of crops is presented.
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The Evaporative Stress Index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts
Martha C. Anderson,Cornélio Alberto Zolin,Paulo Cesar Sentelhas,Christopher Hain,K. A. Semmens,M. Tugrul Yilmaz,Feng Gao,Jason A. Otkin,Robert Tetrault +8 more
TL;DR: In this paper, the authors study correlations for the period 2003-2013 between yield estimates for major crops grown in Brazil and the Evaporative Stress Index (ESI) -an indicator of agricultural drought that describes anomalies in the actual/reference evapotranspiration (ET) ratio, retrieved using remotely sensed inputs of land surface temperature (LST) and leaf area index (LAI).
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Assimilation of remote sensing into crop growth models: Current status and perspectives
Jianxi Huang,Jose Gomez-Dans,Hai Huang,Hongyuan Ma,Qingling Wu,Philip Lewis,Shunlin Liang,Shunlin Liang,Zhongxin Chen,Jing-Hao Xue,Yantong Wu,Feng Zhao,Jing Wang,Xianhong Xie +13 more
TL;DR: A critique of both the advantages and disadvantages of both EO data and crop growth models is provided, and a solid and robust framework for DA is introduced, where different DA methods are shown to be derived from taking different assumptions in solving for the a posteriori probability density function using Bayes’ rule.
References
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Journal ArticleDOI
The Ensemble Kalman Filter: theoretical formulation and practical implementation
TL;DR: A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias, and an ensemble based optimal interpolation scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications.
Journal ArticleDOI
The DSSAT cropping system model
James W. Jones,Gerrit Hoogenboom,Cheryl H. Porter,Kenneth J. Boote,William D. Batchelor,L. A. Hunt,Paul W. Wilkens,Upendra Singh,Arjan J. Gijsman,Joe T. Ritchie +9 more
TL;DR: The benefits of the new, re-designed DSSAT-CSM will provide considerable opportunities to its developers and others in the scientific community for greater cooperation in interdisciplinary research and in the application of knowledge to solve problems at field, farm, and higher levels.
The Ensemble Kalman Filter: Theoretical formulation and practical implementation
TL;DR: The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it as mentioned in this paper, and also presents new ideas and alternative interpretations which further explain the success of the EnkF.
Journal ArticleDOI
The Soil Moisture Active Passive (SMAP) Mission
Dara Entekhabi,Eni G. Njoku,Peggy O'Neill,Kent Kellogg,Wade T. Crow,W. Edelstein,Jared Entin,Shawn D Goodman,Thomas J. Jackson,Joel T. Johnson,John S. Kimball,Jeffrey R. Piepmeier,Randal D. Koster,Neil R.W. Martin,Kyle C. McDonald,Mahta Moghaddam,Susan Moran,Rolf H. Reichle,Jiancheng Shi,Michael W. Spencer,Samuel W Thurman,Leung Tsang,Jakob van Zyl +22 more
TL;DR: The Soil Moisture Active Passive mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey to make global measurements of the soil moisture present at the Earth's land surface.
Journal ArticleDOI
Data Assimilation Using an Ensemble Kalman Filter Technique
TL;DR: In this article, the authors proposed an ensemble Kalman filter for data assimilation using the flow-dependent statistics calculated from an ensemble of short-range forecasts (a technique referred to as Ensemble Kalman filtering) in an idealized environment.
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