Delineating the Trace and Kinematics of the Long Point Fault in Houston, Texas using LiDAR Data and Continuous GPS Data
type: CreativeWork
description: The Houston metropolitan area, and more broadly the Gulf Coast in general, has numerous normal faults that have caused damage to anthropogenic structures on or near the Earth's surface. These faults offset soft sediments, and as a result very little seismic energy is accumulated to produce destructive earthquakes. However, creeping along these faults causes moderate to severe damage to hundreds of residential, commercial, and industrial structures that are part of the infrastructure in the Houston area. The damages require constant repairs that burden private citizens, businesses, and government agencies. Precise surface traces of these faults are notoriously difficult to map due to the easily eroded lithology and constant reworking of the surface by human activities. In this case study, LiDAR data collected from the 2001 Tropical Storm Allison Recovery Project was used to distinguish the precise trace of the Long Point Fault, which is a well-known active fault that spans much of the northwest and west part of the Houston metropolitan area. To determine the kinematics of the Long Point Fault, 11 Continuous GPS (CGPS) stations were installed along most of the fault. All of these CGPS stations were mounted on concrete or masonry buildings. The CGPS stations are within close proximity to each other. The average distance between them is 4.8 km. The sites are on both the footwall (6) and the hanging wall (5). All sites are within 1 km of the fault surface trace. The average distance from the fault is 0.33 km. GPS data were processed using both Precise Point Positioning (PPP) and Double Difference (DD) methods; the PPP solutions were converted to the Stable Houston Reference Frame (SHRF) from the original IGS08 reference frame. The double difference solutions show a slight relative movement between the UTEX site and HCC2 site in the north-south direction. The PPP results imply a slight common displacement trend in the east-west direction in the study area since 2013, whic…
abstract: The Houston metropolitan area, and more broadly the Gulf Coast in general, has numerous normal faults that have caused damage to anthropogenic structures on or near the Earth's surface. These faults offset soft sediments, and as a result very little seismic energy is accumulated to produce destructive earthquakes. However, creeping along these faults causes moderate to severe damage to hundreds of residential, commercial, and industrial structures that are part of the infrastructure in the Houston area. The damages require constant repairs that burden private citizens, businesses, and government agencies. Precise surface traces of these faults are notoriously difficult to map due to the easily eroded lithology and constant reworking of the surface by human activities. In this case study, LiDAR data collected from the 2001 Tropical Storm Allison Recovery Project was used to distinguish the precise trace of the Long Point Fault, which is a well-known active fault that spans much of the northwest and west part of the Houston metropolitan area. To determine the kinematics of the Long Point Fault, 11 Continuous GPS (CGPS) stations were installed along most of the fault. All of these CGPS stations were mounted on concrete or masonry buildings. The CGPS stations are within close proximity to each other. The average distance between them is 4.8 km. The sites are on both the footwall (6) and the hanging wall (5). All sites are within 1 km of the fault surface trace. The average distance from the fault is 0.33 km. GPS data were processed using both Precise Point Positioning (PPP) and Double Difference (DD) methods; the PPP solutions were converted to the Stable Houston Reference Frame (SHRF) from the original IGS08 reference frame. The double difference solutions show a slight relative movement between the UTEX site and HCC2 site in the north-south direction. The PPP results imply a slight common displacement trend in the east-west direction in the study area since 2013, whic…
author: Saenz, Gabriel J. 1983-
language: eng
keywords: GPS, LiDAR, Long Point Fault
date published: 2013-08
date modified: 2026-07-24T02:33:06Z
provider: University of Houston
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Houston

PropertyValue
property ID: Handle
value: http://hdl.handle.net/10657/490