AR108142A1 - Estimación de valores ajustados de precipitación pluvial - Google Patents

Estimación de valores ajustados de precipitación pluvial

Info

Publication number
AR108142A1
AR108142A1 ARP170100956A ARP170100956A AR108142A1 AR 108142 A1 AR108142 A1 AR 108142A1 AR P170100956 A ARP170100956 A AR P170100956A AR P170100956 A ARP170100956 A AR P170100956A AR 108142 A1 AR108142 A1 AR 108142A1
Authority
AR
Argentina
Prior art keywords
precipitation
values
agricultural
data records
digital
Prior art date
Application number
ARP170100956A
Other languages
English (en)
Inventor
Valliappa Lakshmanan
Bill Leeds
Original Assignee
Climate Corp
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Climate Corp filed Critical Climate Corp
Publication of AR108142A1 publication Critical patent/AR108142A1/es

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01W—METEOROLOGY
    • G01W1/00—Meteorology
    • G01W1/14—Rainfall or precipitation gauges
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Environmental & Geological Engineering (AREA)
  • Engineering & Computer Science (AREA)
  • Hydrology & Water Resources (AREA)
  • Atmospheric Sciences (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Ecology (AREA)
  • Environmental Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Mathematics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Operations Research (AREA)
  • Probability & Statistics with Applications (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Computing Systems (AREA)
  • Image Processing (AREA)

Abstract

Un método para estimar los valores ajustados de precipitación pluvial para un conjunto de puntos geográficos usando datos agrícolas comprende usar un sistema servidor de computación que recibe, a través de una red, registros de datos agrícolas que se usan para estimar los valores de precipitación para el conjunto de puntos geográficos. En el sistema servidor de computación las instrucciones de cálculo de precipitación reciben datos digitales que incluyen los registros de datos observados de radar y de pluviómetros agrícolas. El sistema de computación luego reúne los registros de datos agrícolas y crea y almacena conjuntos de datos agrícolas. Los registros de datos agrícolas luego se transforman en uno o más conjuntos de distribución. Los conjuntos de distribución luego se usan para determinar los parámetros de regresión para un modelo digital de regresión de precipitación pluvial. El modelo digital de regresión de precipitación se usa para estimar los valores ajustados de precipitación para un nuevo conjunto de puntos geográficos. El sistema servidor de computación genera entonces una imagen digital que incluye los puntos geográficos y los valores ajustados de precipitación pluvial.
ARP170100956A 2016-04-13 2017-04-12 Estimación de valores ajustados de precipitación pluvial AR108142A1 (es)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US15/097,604 US10371863B2 (en) 2016-04-13 2016-04-13 Estimating rainfall adjustment values

Publications (1)

Publication Number Publication Date
AR108142A1 true AR108142A1 (es) 2018-07-18

Family

ID=60038891

Family Applications (1)

Application Number Title Priority Date Filing Date
ARP170100956A AR108142A1 (es) 2016-04-13 2017-04-12 Estimación de valores ajustados de precipitación pluvial

Country Status (6)

Country Link
US (1) US10371863B2 (es)
EP (1) EP3443393B1 (es)
AR (1) AR108142A1 (es)
BR (1) BR112018070806B1 (es)
CA (1) CA3020852C (es)
WO (1) WO2017180692A1 (es)

Families Citing this family (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10371863B2 (en) * 2016-04-13 2019-08-06 The Climate Corporation Estimating rainfall adjustment values
EP3236209B1 (en) * 2016-04-19 2021-06-09 Honda Research Institute Europe GmbH Navigation system and method for error correction
US10467540B2 (en) * 2016-06-02 2019-11-05 The Climate Corporation Estimating confidence bounds for rainfall adjustment values
US10754063B2 (en) * 2016-06-14 2020-08-25 The Climate Corporation Supervised neural network to predict unlabeled rain rates
WO2018049289A1 (en) 2016-09-09 2018-03-15 Cibo Technologies, Inc. Systems for adjusting agronomic inputs using remote sensing, and related apparatus and methods
US10477756B1 (en) 2018-01-17 2019-11-19 Cibo Technologies, Inc. Correcting agronomic data from multiple passes through a farmable region
CN113168577A (zh) * 2018-09-21 2021-07-23 克莱米特公司 用于执行机器学习算法的方法和系统
CN109871584B (zh) * 2019-01-16 2022-12-06 中山大学 一种基于log-sinh变换的区域月降水统计频率分析方法
WO2020157582A2 (en) * 2019-01-30 2020-08-06 Aeroqual Ltd. Method for calibrating networks of environmental sensors
CN111983730A (zh) * 2019-05-22 2020-11-24 衢州学院 一种基于计算机视觉的智能雨量检测设备
WO2021204913A1 (en) * 2020-04-08 2021-10-14 Basf Se Method for estimating precipitation distribution for a geographical region
CN115685398A (zh) * 2022-10-09 2023-02-03 中国长江三峡集团有限公司 降雨倾角测量方法、装置、计算机设备及介质

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8594936B1 (en) * 2008-12-31 2013-11-26 The Weather Channel, Llc Providing current estimates of precipitation accumulations
KR20130098072A (ko) 2012-02-27 2013-09-04 한국전자통신연구원 강우 감쇠 예측 장치 및 방법과 강우 감쇠 보상 장치
KR101352568B1 (ko) * 2012-12-28 2014-01-24 경북대학교 산학협력단 강우강도 측정 장치 및 그 방법
US20140278339A1 (en) * 2013-03-15 2014-09-18 Konstantinos (Constantin) F. Aliferis Computer System and Method That Determines Sample Size and Power Required For Complex Predictive and Causal Data Analysis
US10564316B2 (en) 2014-09-12 2020-02-18 The Climate Corporation Forecasting national crop yield during the growing season
US20170083823A1 (en) * 2015-09-22 2017-03-23 San Diego State University Research Foundation Spectral Optimal Gridding: An Improved Multivariate Regression Analyses and Sampling Error Estimation
WO2017100220A1 (en) * 2015-12-07 2017-06-15 Rapidsos, Inc. Systems and methods for predicting emergency situations
US10371863B2 (en) * 2016-04-13 2019-08-06 The Climate Corporation Estimating rainfall adjustment values
US10467540B2 (en) * 2016-06-02 2019-11-05 The Climate Corporation Estimating confidence bounds for rainfall adjustment values

Also Published As

Publication number Publication date
EP3443393B1 (en) 2021-12-08
CA3020852C (en) 2023-04-11
US20170300602A1 (en) 2017-10-19
EP3443393A4 (en) 2020-01-15
BR112018070806B1 (pt) 2023-10-17
BR112018070806A2 (pt) 2019-02-05
WO2017180692A1 (en) 2017-10-19
US10371863B2 (en) 2019-08-06
CA3020852A1 (en) 2017-10-19
EP3443393A1 (en) 2019-02-20

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