東南テキサスの舗装状態と気候データ:舗装性能に対する洪水影響を評価するためのデータセット

Hossein Hariri Asli¹, Nicholas Brake¹, Mahdi Feizbahr¹

¹Department of Civil and Environmental Engineering, Lamar University, Beaumont, TX 77710, United States.

Data in brief

|September 2, 2025

まとめ

この研究は,南東テキサスの舗装性能予測のための包括的なデータセットを紹介しています. 道路の環境への影響を理解し,整備戦略を改善するのに役立ちます.

科学分野:

土木工学
データサイエンス
環境科学

背景:

効率的な舗装整備は経済的な安定性,ネットワークの性能,安全性にとって不可欠です.
正確な舗装状態の評価は,メンテナンスとリハビリテーション (M&R) 戦略を最適化するために不可欠です.
データ駆動型モデリングには標準化された高品質のデータセットが必要です

研究の目的:

東南テキサスを中心に歩道性能予測のための包括的なデータセットを提示します.
負荷に関連したおよび負荷に関係のない舗装の劣化メカニズムを調査できるようにする.
洪水の影響を受けた地域の維持需要と回復力を予測するツールの開発を支援する.

主な方法:

舗装,交通,気象,洪水シミュレーション,地形変形,地形データを含むデータセットを集めました.
ArcGIS Pro,Microsoft Excel,およびPythonを使用して,データの事前処理を行い,機械学習の可用性を確保しています.
気候/環境要因の分析,予測特性の特定,および相関分析を容易にした.

主要な成果:

このデータセットは,様々な要因による舗装の劣化の詳細な調査を可能にします.
様々な変数における重要な予測特性と相関性を特定した.
舗装性能モデリングの入力変数選択のギャップを埋めました.

結論:

標準化されたデータセットは舗装管理の改善に不可欠です
このデータセットは,インフラストラクチャのパフォーマンスモデリングと舗装の回復力を高めるための堅固な基盤を提供します.
正確な状態の評価を通じて改善された資源配分とM&R戦略をサポートします.

キーワード:

データ駆動モデリング洪水の危険性のあるインフラ舗装障害舗装性能について東南テキサス州

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