Handbook of Geospatial Artificial Intelligence

14GeoAI for Disaster Response

Lei Zou

Department of Geography, Texas A&M University

Ali Mostafavi

Department of Civil & Environmental Engineering, Texas A&M University

Bing Zhou, Binbin Lin, and Debayan Mandal

Department of Geography, Texas A&M University

Mingzheng Yang, Joynal Abedin, and Heng Cai

Department of Geography, Texas A&M University

DOI: 10.1201/9781003308423-14

CONTENTS

• 14.1 Introduction

• 14.2 The Paradigm of GeoAI for Disaster Response

  1. 14.2.1 Remote Sensing Data

  2. 14.2.2 Human Mobility Data

  3. 14.2.3 Social Media Data

  4. 14.2.4 Sensor Data

• 14.3 Case Study: Analyzing Twitter Data with NLP for Disaster Response

  1. 14.3.1 Data Collection and Cleaning

  2. 14.3.2 Intelligent Classification Model

  3. 14.3.3 Intelligent Toponym Recognition Model

  4. 14.3.4 Spatial ...