CN114450715B - 预测和修正植被状态 - Google Patents

预测和修正植被状态

Info

Publication number
CN114450715B
CN114450715B CN202080068003.2A CN202080068003A CN114450715B CN 114450715 B CN114450715 B CN 114450715B CN 202080068003 A CN202080068003 A CN 202080068003A CN 114450715 B CN114450715 B CN 114450715B
Authority
CN
China
Prior art keywords
vegetation
model
image
training data
data area
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.)
Active
Application number
CN202080068003.2A
Other languages
English (en)
Chinese (zh)
Other versions
CN114450715A (zh
Inventor
C·阿尔布雷克特
H·哈曼
L·克莱因
陆思渊
P·沙拉斯钱德拉
周旺
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
International Business Machines Corp
Original Assignee
International Business Machines 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 International Business Machines Corp filed Critical International Business Machines Corp
Publication of CN114450715A publication Critical patent/CN114450715A/zh
Application granted granted Critical
Publication of CN114450715B publication Critical patent/CN114450715B/zh
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G06N3/0455—Auto-encoder networks; Encoder-decoder networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0464—Convolutional networks [CNN, ConvNet]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/09—Supervised learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/046—Forward inferencing; Production systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
    • G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
    • G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
    • G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/188—Vegetation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20212—Image combination
    • G06T2207/20224—Image subtraction
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation
    • G06T2207/30188—Vegetation; Agriculture

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Biomedical Technology (AREA)
  • Molecular Biology (AREA)
  • Mathematical Physics (AREA)
  • Multimedia (AREA)
  • Computational Linguistics (AREA)
  • Biophysics (AREA)
  • Medical Informatics (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Databases & Information Systems (AREA)
  • Quality & Reliability (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
CN202080068003.2A 2019-10-21 2020-09-24 预测和修正植被状态 Active CN114450715B (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US16/658,533 2019-10-21
US16/658,533 US11436712B2 (en) 2019-10-21 2019-10-21 Predicting and correcting vegetation state
PCT/IB2020/058917 WO2021079210A1 (en) 2019-10-21 2020-09-24 Predicting and correcting vegetation state

Publications (2)

Publication Number Publication Date
CN114450715A CN114450715A (zh) 2022-05-06
CN114450715B true CN114450715B (zh) 2026-01-13

Family

ID=75492165

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202080068003.2A Active CN114450715B (zh) 2019-10-21 2020-09-24 预测和修正植被状态

Country Status (5)

Country Link
US (1) US11436712B2 (https=)
JP (1) JP7556649B2 (https=)
CN (1) CN114450715B (https=)
GB (1) GB2602929B (https=)
WO (1) WO2021079210A1 (https=)

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021108639A1 (en) * 2019-11-27 2021-06-03 X Development Llc Utility line maintenance and safety
WO2021154891A1 (en) 2020-01-27 2021-08-05 Rahul Saxena System and method of intelligent vegetation management
US11768945B2 (en) * 2020-04-07 2023-09-26 Allstate Insurance Company Machine learning system for determining a security vulnerability in computer software
WO2022036227A1 (en) * 2020-08-13 2022-02-17 Zesty.Ai, Inc. Determining climate risk using artificial intelligence
WO2022125787A1 (en) 2020-12-09 2022-06-16 Zesty.Ai, Inc. Determining 3d structure features from dsm data
US20220327463A1 (en) * 2021-04-07 2022-10-13 International Business Machines Corporation Managing vegetation conditions
JP7641854B2 (ja) 2021-08-19 2025-03-07 ヒタチ・エナジー・リミテッド 植生管理システム及び植生管理方法
US12260464B2 (en) 2021-09-27 2025-03-25 Hexcuity Limited System and method for automated forest inventory mapping
CN113868963B (zh) * 2021-10-20 2022-06-28 中国水利水电科学研究院 基于机器学习的仿自然生态植被构建方法、系统及设备
US20230186623A1 (en) * 2021-12-14 2023-06-15 Ping An Technology (Shenzhen) Co., Ltd. Systems and methods for crop disease diagnosis
US20230316744A1 (en) * 2022-03-31 2023-10-05 Sharper Shape Oy Method and system for remotely analysing trees
US20230347193A1 (en) * 2022-04-27 2023-11-02 X Development Llc Systems and methods for minimizing wildfire ignition risk
US12555373B2 (en) 2022-05-26 2026-02-17 International Business Machines Corporation Automated hazard recognition using multiparameter analysis of aerial imagery
US20230385702A1 (en) * 2022-05-27 2023-11-30 Raytheon Company Data fabric for intelligent weather data selection
US11594015B1 (en) * 2022-07-26 2023-02-28 Finite Carbon Corporation Detecting changes in forest composition
US12529654B2 (en) * 2022-07-26 2026-01-20 Landyield Holdings Llc Detecting changes in forest composition
US12333801B2 (en) * 2022-08-31 2025-06-17 AIDASH Inc. Systems and methods for identifying trees and estimating tree heights and other tree parameters
US12360286B2 (en) 2022-10-14 2025-07-15 Zesty.Ai, Inc. Hail predictions using artificial intelligence
US12360287B2 (en) 2022-10-14 2025-07-15 Zesty.Ai, Inc. Hail frequency predictions using artificial intelligence
US12536594B2 (en) 2022-10-14 2026-01-27 Zesty.Ai, Inc. Hail severity predictions using artificial intelligence

Family Cites Families (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7031927B1 (en) 2000-04-12 2006-04-18 Strategic Weather Services System, method, and computer program product for weather and terrestrial vegetation-based water renovation and management forecasting
US7702597B2 (en) 2004-04-20 2010-04-20 George Mason Intellectual Properties, Inc. Crop yield prediction using piecewise linear regression with a break point and weather and agricultural parameters
US7720605B2 (en) 2007-06-22 2010-05-18 Weyerhaeuser Nr Company Identifying vegetation attributes from LiDAR data
CA2753542A1 (en) 2008-11-13 2010-05-20 Saint Louis University Apparatus and method for providing environmental predictive indicators to emergency response managers
CN103034910B (zh) 2012-12-03 2016-03-09 北京农业信息技术研究中心 基于多源信息的区域尺度病虫害预测方法
US9069104B2 (en) 2012-12-12 2015-06-30 International Business Machines Corporation Pathway management using model analysis and forecasting
US9131644B2 (en) 2014-08-19 2015-09-15 Iteris, Inc. Continual crop development profiling using dynamical extended range weather forecasting with routine remotely-sensed validation imagery
US20160247079A1 (en) 2015-02-20 2016-08-25 Iteris, Inc. Modeling of soil compaction and structural capacity for field trafficability by agricultural equipment from diagnosis and prediction of soil and weather conditions associated with user-provided feedback
US10989838B2 (en) 2015-04-14 2021-04-27 Utopus Insights, Inc. Weather-driven multi-category infrastructure impact forecasting
US10755357B1 (en) * 2015-07-17 2020-08-25 State Farm Mutual Automobile Insurance Company Aerial imaging for insurance purposes
SG10201506012SA (en) * 2015-07-31 2017-02-27 Accenture Global Services Ltd Inventory, growth, and risk prediction using image processing
CN105787457A (zh) 2016-03-08 2016-07-20 浙江工商大学 一种modis卫星集成dem提高植被分类遥感精度的估算方法
US10664750B2 (en) 2016-08-10 2020-05-26 Google Llc Deep machine learning to predict and prevent adverse conditions at structural assets
KR20190046841A (ko) 2016-09-07 2019-05-07 봇슈 가부시키가이샤 정보 처리 장치 및 정보 처리 시스템
US10586105B2 (en) * 2016-12-30 2020-03-10 International Business Machines Corporation Method and system for crop type identification using satellite observation and weather data
GB2561845A (en) 2017-04-24 2018-10-31 Point4Uk Ltd Determining risk posed by vegetation
US20180314994A1 (en) 2017-05-01 2018-11-01 International Business Machines Corporation Directed unmanned aircraft for enhanced power outage recovery
CN109406412A (zh) 2017-08-18 2019-03-01 广州极飞科技有限公司 一种植物健康状态监控方法及装置
CA3084902A1 (en) 2017-12-12 2019-06-20 Oy Arbonaut Ltd. A method to quantify fire risk to structures
CN108681715A (zh) 2018-05-18 2018-10-19 三亚中科遥感研究所 海南热带天然林植被型组分类方法
CN109815914A (zh) * 2019-01-28 2019-05-28 成都蝉远科技有限公司 一种基于植被区域识别的卷积神经网络模型训练方法及系统
AU2019204376B1 (en) * 2019-06-21 2020-07-02 Curvebeam Ai Limited Image Analysis Method and System

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Modeling risk of mangroves to tropical cyclones: A case study of Hurricane Irma;Caiyun Zhang;《Estuarine, Coastal and Shelf Scienc》;20190831;第224卷;108-116 *
Storm outage modeling for an electric distribution network in Northeastern USA;D. W. Wanik等;《Natural Hazards 》;20150716;第79卷;1359-1384 *

Also Published As

Publication number Publication date
JP2022552369A (ja) 2022-12-15
WO2021079210A1 (en) 2021-04-29
GB2602929A (en) 2022-07-20
US20210118117A1 (en) 2021-04-22
CN114450715A (zh) 2022-05-06
GB2602929B (en) 2024-01-03
JP7556649B2 (ja) 2024-09-26
US11436712B2 (en) 2022-09-06
GB202205196D0 (en) 2022-05-25

Similar Documents

Publication Publication Date Title
CN114450715B (zh) 预测和修正植被状态
US11676375B2 (en) System and process for integrative computational soil mapping
CN117808214A (zh) 水利工程数据分析系统
CN117708551B (zh) 基于双精度gdp数据展布的洪涝灾害影响评估方法和系统
CN118628315A (zh) 基于人工智能的生态环境风险预警方法和装置及存储介质
El-Mahdy et al. Flood classification and prediction in South Sudan using artificial intelligence models under a changing climate
CN121053747A (zh) 一种基于大数据的海洋藻华灾害预警系统
CN118966784A (zh) 隧道施工中地质风险预测方法、系统、设备、介质及产品
Phonphan et al. Evaluating spatiotemporal dynamics: A comparative study of predictive efficacy in land use land cover change Models-Markov Chain, CA-ANN, and PLUS
Tillihal et al. River flood monitoring and management: a review
CN117670130A (zh) 基于最大熵的干旱区生态修复方法及装置
CN117152532A (zh) 输电线路区段标注方法、装置、计算机设备和存储介质
CN120181152B (zh) 基于PINNs的洪水预测方法、装置、设备及介质
CN117235581B (zh) 一种基于坡体缓陡程度分类的滑坡风险预测方法
US20240320549A1 (en) Information processing apparatus, information processing method, and recording medium
Ardana et al. Rainfall prediction using adaptive neuro-fuzzy inference system method
CN117689210A (zh) 道路自然灾害风险智能评估方法
Mok et al. Deep learning-enhanced flood damage prediction: A DFNN-based hybrid approach with simplified inputs
Fordjour Development of a Deep Learning-Based Flood Forecasting Tool With Firefly Algorithm for the Blackburn Fork Watershed, Tennessee
Ramlan et al. Rainfall prediction in flood prone area using deep learning approach
CN119090109B (zh) 移动数智巡视路径优化方法、系统和装置
Huynh Hybrid Physics-AI Approaches Integrating Neural Networks into Distributed Hydrological Models for Regional Flood Simulation
Zhou et al. A modelling tool for rainfall-triggered landslide susceptibility mapping and hazard warning based on GIS and machine learning
CN121765688B (zh) 滑坡危险预测系统及方法
Alexandrina et al. Flood Prediction in Jakarta Using Long Short-Term Memory

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
GR01 Patent grant
GR01 Patent grant