U.S. Department of the Interior

U.S. Geological Survey

Terrestrial Lidar Data of the 

February 14, 2019, Sausalito Boulevard 

Landslide, Sausalito, California

Data Series 1112
COVER

Photograph of the February 14, 2019, Sausalito Boulevard landslide looking northeastward towards 

the city of Sausalito. The length of the landslide visible in this photo is approximately 60 meters, as 

measured between the headscarp (foreground) and Sausalito Boulevard (middle-ground). Date of 

image is February 15, 2019.
Terrestrial Lidar Data of the 

February 14, 2019, Sausalito Boulevard 

Landslide, Sausalito, California

U.S. Department of the Interior

U.S. Geological Survey

By Brian D. Collins and Skye C. Corbett

Data Series 1112
U.S. Department of the Interior

DAVID BERNHARDT, Acting Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2019

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment—visit https://www.usgs.gov or call 1–888–ASK–USGS.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Collins, B.D. and Corbett, S.C., 2019, Terrestrial lidar data of the February 14, 2019, 

Sausalito Boulevard landslide, Sausalito, California: U.S. Geological Survey Data Series 1112, 12 p., 

https://doi.org/10.3133/ds1112.

ISSN 2327-638X (online)
iii

Contents

Introduction.....................................................................................................................................................1

Topographic and Geomorphologic Setting................................................................................................4

Methods...........................................................................................................................................................4

Data Collection, Registration, and Georeferencing ........................................................................4

Data Filtering..........................................................................................................................................8

Surface Generation ..............................................................................................................................9

Results .............................................................................................................................................................9

Survey Control.......................................................................................................................................9

Point Data...............................................................................................................................................9

Surface Data..........................................................................................................................................9

Summary........................................................................................................................................................11

Acknowledgments.......................................................................................................................................11

References Cited..........................................................................................................................................11

Figures

1. Site map of the February 14, 2019, Sausalito Boulevard landslide.......................................1

2. Photograph showing partial landslide source area and region of one destroyed residential structure............................................................................................................................2

3. Photographs showing damage from the landslide that involved several homes and 

vehicles ..........................................................................................................................................3

4. Photographs showing landslide source area..........................................................................5

5. Photographs of a terrestrial lidar survey in progress.............................................................6

6. Images showing point-cloud-based site map and Sausalito Boulevard looking eastward ................................................................................................................................................6

7. Photograph showing GPS base station set up over Sausalito Boulevard..........................7

8. Images of unfiltered and filtered, bare-earth point cloud data of part of the landslide 

source area..................................................................................................................................10

 9. Images of bare-earth terrain model of the source area from two different 

 perspectives ................................................................................................................................11

Tables

1. Table of processed georeferenced coordinates for base station, laser scan and control 

point locations.............................................................................................................................10
iv

Conversion Factors

U.S. customary units to International System of Units

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

Datum 

Horizontal coordinate information is referenced to the North American Datum of 1983–National 

Adjustment of 2011 (NAD83(2011)) and projected to Universal Transverse Mercator (UTM) Zone 

10N coordinates in metric units.

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88) in metric units. Elevation, as used in this report, refers to distance above the vertical 

datum.

Abbreviations

ASCII American Standard Code for Information Interchange

NAD27 North American Datum of 1927

NAD83 North American Datum of 1983

NAVD88 North American Vertical Datum of 1988

NPS National Park Service

OPUS online positioning user service

RTK real-time-kinematic

TIN triangulated irregular network

USGS U.S. Geological Survey

UTM Universal Transverse Mercator
Terrestrial Lidar Data of the February 14, 2019, Sausalito 

Boulevard Landslide, Sausalito, California

By Brian D. Collins and Skye C. Corbett

Introduction

On February 14, 2019, just before 2:56 am local time 

(Pacific Standard Time), a landslide initiated from the hillslopes above the Hurricane Gulch section of the City of Sausalito, Marin County, California (fig. 1). The landslide, specifically classified as a debris flow, overran a road (Sausalito 

Boulevard) immediately below the landslide source area 

(fig. 2) and impacted a residential structure that subsequently 

toppled downslope and collided with another residential structure. The second structure then crossed a lower road (Crescent 

Avenue) that runs along the base of the slope before the mixture of soil and structural debris came to rest in and near the 

valley axis that drains the lower area of Hurricane Gulch.

Figure 1. Site map of the February 14, 2019, Sausalito Boulevard landslide in Sausalito, 

Marin County, California. Red star shows approximate location of the landslide. Latitude and 

longitude tick marks (in World Geodetic Datum of 1984 coordinates, WGS84) are for general 

reference.

Highway

Robin

Williams

Tunnels

(Waldo

Grade)

Wolfback

SAN FRANCISCO BAY

Ridge

HECHT 

Hurricane Gulch

CRESCENT AVE.

AVE.

SAUSALITO

BLVD.

MAIN ST.

101

0 0.25 0.5 KILOMETERS

 Marin County

CALIFORNIA

-122.490° -122.485° -122.480°

37.850°

37.845°
2 Terrestrial Lidar Data of the February 14, 2019, Sausalito Boulevard Landslide, Sausalito, California

Figure 2. Photograph showing partial landslide source area and region of one destroyed residential structure. The landslide traveled 

from the upper right side of the image, crossed the road (flat area in middle ground), and impacted one residential structure before 

subsequently carrying debris and vehicles from several partially impacted homes farther down the slope (towards the bottom left of the 

image). Date of image is February 14, 2019.

A resident was located in the upper level of the first 

impacted structure (fig. 3A) and survived the disaster. No 

residents were located in the second impacted structure. 

Several other residential structures were damaged as a result 

of passage of the debris flow below Sausalito Boulevard, and 

emergency officials evacuated several residents from neighboring partially damaged structures. Overall, 50 residences 

were evacuated due to the threat posed by potential ongoing 

instability of the slope and natural gas leaks from broken 

pipes leading to residential structures. At least seven vehicles 

were entrained in the debris (fig. 3B), due to the destruction of 

elevated carports attached to structures impacted just below 

Sausalito Boulevard.

The U.S. Geological Survey (USGS) responded to this 

event (herein referred to as the February 14, 2019, Sausalito Boulevard landslide) within hours of the landslide and 

provided situational awareness of possible secondary landslide hazards associated with the unstable slope. The USGS 

also rapidly mobilized its topographic surveying capabilities 

(specifically, GPS and terrestrial lidar devices) and collected 

a three-dimensional point cloud model of the landslide source 

area and surrounding terrain to capture the as-failed condition of the slope for use in potential future studies. This report 

summarizes the methods and available data collected during 

this response.
Introduction 

3

AB

Figure 3.

Photographs showing 

damage from the 

landslide that involved 

several homes and 

vehicles. A, View 

looking to the northeast 

towards Angel Island in 

San Francisco Bay. The 

area of one destroyed 

residential structure is 

in the foreground. The 

other destroyed home is 

located near the center 

of the image, which is 

out of site behind trees. B, Several vehicles 

were entrained within 

the debris amidst soil, 

trees, and structural 

debris. Area shown 

in (B) is located in 

the center left of (A). 

Date of both images is 

February 14, 2019.
4 Terrestrial Lidar Data of the February 14, 2019, Sausalito Boulevard Landslide, Sausalito, California

Topographic and Geomorphologic 

Setting

The February 14, 2019, Sausalito Boulevard landslide 

occurred on an approximately 32°, heavily vegetated slope that 

is part of the National Park Service (NPS) Golden Gate National 

Recreation Area. The slope is located within a section of relief 

that descends to the northeast to less steep areas of the City of 

Sausalito (approximate elevation 55 meters (m) at the location 

of the lower destroyed residence) and upwards to the ridgeline 

(approximate elevation 270 m) above U.S. Highway 101 (fig. 

1). The highway extends northwest to southeast and forms an 

anthropogenic bench in the topography (also called the Waldo 

Grade). The highway also runs parallel to a prominent ridge 

(Wolfback Ridge) in the hills forming the Marin Headlands 

west and above the City of Sausalito. Approximately 180 m 

southwest of the landslide headscarp, the highway enters the 

twin-bore Robin Williams Tunnels. Highway 101 is located 

approximately 60 m (ground distance) above the landslide 

source area at an approximate elevation of 160 m. An unpaved, 

one-lane, and limited access road (Hecht Avenue) is located just 

above (25 m ground distance) the landslide source area at an 

approximate elevation of 145 m.

The landslide source area begins at an elevation of 126 

m and extends for a ground distance of approximately 50 m 

downslope (as measured from the headscarp to just above 

Sausalito Boulevard) to an elevation of approximately 102 m. 

The source area is approximately 12 m wide and 2 to 6 meters 

in thickness (fig. 4A). The landslide occurred on the northwestfacing sideslope of a small (100-m-wide) valley flanked by 

two small (100-m-wide, 200-m-long) ridges that extend to the 

northeast from Wolfback Ridge. The northwest-facing slope of 

the ridge encompassing the landslide source area is composed 

of several slightly convergent swales (characterized as colluvialfilled hollows; for example, see Dietrich and others, 1986). 

The landslide initiated from one of these hollows. Following 

initiation, the landslide dropped over a steep (approximately 

49°) 6-m-tall slope, overran Sausalito Boulevard, impacted 

a residential structure (duplex), and continued downslope. 

Very little deposition of debris above Sausalito Boulevard was 

observed (that is, the source area encompasses almost the entire 

landslide zone above the road and exhibits near complete evacuation of all debris). The landslide deposit zone extends from 

Sausalito Boulevard (approximate elevation 93 m) 30 m down 

an approximately 36° slope to the less steep valley floor. The 

deposit then flowed onto the lower angle (~20°) valley floor and 

eventually stopped just past Crescent Avenue, where the debris 

collided with another residential structure. Total ground length 

of the source and runout zone (as measured from the headscarp 

to the distal end of the deposit) is approximately 220 m. Total 

elevation difference over this distance is approximately 75 m.

Methods

Data Collection, Registration, and 

Georeferencing

We collected terrestrial lidar of the Sausalito landslide 

source area on Sunday, February 24, 2019, 10 days following 

the landslide. Terrestrial lidar is a survey technique that uses 

a pulsed laser to measure the distance to any reflective object 

by measuring the time of travel of the projected and received 

laser return. Combined with integrated precision devices that 

measure the orientation of the laser about the instruments origin, terrestrial lidar is capable of capturing millions of threedimensional points of virtually any landscape in a matter of 

minutes. The resultant data—often termed a “point cloud”—

allows for the geometric reconstruction of complex terrain. It 

also offers a way to survey hazardous topography. The resulting oversteepened surfaces of the landslide headscarp above 

Sausalito Boulevard (fig. 4B) may have been unstable, and 

we used terrestrial lidar to capture these data from positions 

distant from these areas.

We focused our efforts on the landslide source area to 

capture the as-failed geometry of the landslide. Although 

some of our data captures the landslide deposit area below 

Sausalito Boulevard, most of this area was not directly visible 

from our laser setup locations on and above the road. Using a 

Riegl Z420i terrestrial lidar instrument (fig. 5), we collected 

data from six independent laser scan (LS) positions—three 

on Sausalito Boulevard and three from the margins of the 

landslide source area (fig. 6). Scanning at a resolution of 0.08 

to 0.1 degrees in both horizontal and vertical directions, each 

scan position provided approximately 3 million data points 

of the surrounding terrain. At a mean scan distance of 30 m 

from laser to point of reflectance, the mean spot size (area of 

sampling) is approximately 0.4 cm2 for each point measurement. The error associated with laser return positions (Elaser) is 

approximately 1.0 cm (based on the manufacturer’s reported 

accuracy of the laser instrument for 1σ (~68%) standard deviation at 50 m range).

To combine data from independent scan positions, we 

used five control points (CP) (10 cm tall, 10 cm diameter 

cylindrical reflectors, fig. 7) distributed along Sausalito 

Boulevard and the margins of the landslide source area (fig. 

6). Using the default registration algorithm in our processing 

software (Riegl RiScan Pro), we obtained a mean registration 

error (Ereg) of 0.3 cm for all scans combined with one another.

We used a pair of Topcon Hyper+ GPS devices (base + 

rover) operating in real-time-kinematic (RTK) mode to collect 

dual band (L1+L2) differentially corrected positions of all 

laser scan and control point locations. 
Methods 

5

AB

Figure 4. A, Photographs showing 

landslide source area 

as viewed from the 

headscarp. A prominent 

stream of water exited 

the headscarp and 

flowed along the 

landslide axis in the days 

following the landslide. 

Sausalito Boulevard is 

located at the bottom 

of the slope (middle 

ground of image). 

Width of landslide 

is approximately 12 

meters. B, The landslide 

headscarp forms a 

near-vertical slope 

approximately 6 meters 

tall. Photograph (B) 

by Bryant Ho (City of 

Sausalito)
6 Terrestrial Lidar Data of the February 14, 2019, Sausalito Boulevard Landslide, Sausalito, California

Figure 5. Photographs of a terrestrial 

lidar survey in progress from (A), Sausalito 

Boulevard, and (B), the left (west) margin 

of the landslide source area. The laser is 

mounted on a leveled tripod and a camera 

with fish-eye lens is mounted on top to 

capture imagery for post-processing the 

color of the point cloud. In (A), the RTK GPS 

rover is mounted above the camera for 

collection of precision survey data of the 

instrument location.

Figure 6. Image of A, Point-cloud-based site map and B, image of Sausalito Boulevard looking eastward, showing location of laser 

scan positions (LS#), control point reflector locations (CP#), and the horizontal control point (M-163) used for positioning our GPS base 

station relative to the landslide source area. Laser scan position LS6 is not visible in (A) under the trees on the west upper margin of the 

landslide.

A B

Laser scan position

Control point reflector

City of Sausalito horizontal control point

EXPLANATION

B

CP3

CP5

CP2

CP1

CP4 LS5

LS1

LS2

LS4 LS6

LS3

SAUSALITO BOULEVARD

6.5 meters

M-163

A

Landslide 

 source area

Residential

 structure

LS5

LS4

LS2

LS1

LS3

N

CP4

CP1

CP2

CP3

CP5 M-163
Methods 7

Figure 7. Photograph showing GPS base station (neon yellow tripod) with radio mast antenna (yellow and orange tripod) set 

up over control point M-163 on Sausalito Boulevard. Terrestrial lidar data collection from position LS1 is taking place and several 

control points (white cylinders on black and silver tripods) are visible in the background.
8 Terrestrial Lidar Data of the February 14, 2019, Sausalito Boulevard Landslide, Sausalito, California

We located our base station over a City of Sausalito horizontal 

control point (M-163, fig. 7; NAD27 (North American Datum 

of 1927) California State Plane Zone 3 horizontal coordinates 

E1426810.90 ft, N496963.32 ft), but performed a 6-hour static 

GPS collection to obtain an independent coordinate solution 

in NAD83(2011) (North American Datum of 1983–National 

Adjustment of 2011), UTM (Universal Transverse Mercator) 

Zone 10N coordinates (in meters). The static solution was 

processed by the National Geodetic Survey’s online positioning user service (OPUS) processing algorithms (https://

www.ngs.noaa.gov/OPUS/). We used the GEOID12B geoid 

(https://www.ngs.noaa.gov/GEOID/GEOID12B/) output from 

OPUS to transform the ellipsoid solution for the base station 

control point to an orthometric height in NAVD88 (North 

American Vertical Datum of 1988) coordinates (in meters). All 

laser and control points are thereby referenced to this set of 

coordinates (NAD83(2011)-UTM Zone 10N and NAVD88). 

Overall accuracy of the static OPUS solution (that is, the error 

associated with the global control network, Econtrol) is 2.0 cm. 

Overall three-dimensional accuracy of our internal network 

RTK solutions (that is, the error associated with the measurement of positions between the base station and rover locations, 

Esurvey) is 0.8 cm (ignoring one laser scan position, LS4 that 

we were not able to obtain a fixed GPS solution for). We were 

able to obtain subcentimeter solutions for all but three points 

(LS4 – 3.4 cm, LS6 – 1.5 cm, and CP3 – 1.6 cm)—these were 

located under heavy vegetation on the left lateral margin of the 

landslide source area with poor visibility to the sky. Applying the georeferenced coordinates from the laser scan (5 of 6 

points, excluding LS4) and control points (5 of 5 points) to the 

point cloud data resulted in a final georeferencing error (Egeoref) 

of 2.3 cm.

To calculate the overall accuracy of the final data 

products, we use error analysis protocols by Collins and 

others (2014). These protocols outline how errors from the 

laser instrument, registration process, georeferencing procedures, survey network, and global control network should be 

combined to estimate the overall accuracy of terrestrial lidar 

data. The methodology uses a root mean square error formula, 

shown in equations 1 and 2, as an estimate of either local 

(Elocal, internal to the data set; that is, Elaser and Ereg only) or 

global (Eglobal, between the data set and other georeferenced 

data; that is, Elaser, Egeoref, Esurvey, and Econtrol) measurements 

made using the point cloud data. The registration error (Ereg) is 

ignored for the external accuracy calculation because it only 

represents how close the points are within the dataset itself—

the georeferencing error captures this error when comparing 

the data to external data sources such as airborne point cloud 

models. 

 (1)

(2)

For 

laser error (Elaser) of 1.0 cm;

registration error (Ereg) of 0.3 cm;

georeferencing error (Egeoref) of 2.3 cm;

survey error (Esurvey) of 0.8 cm;

and control network error (Econtrol) of 2.0 cm, 

the resultant local error is 1.0 cm and the resultant global error 

is 3.3 cm.

We note that these error assessments are based on possible errors in the data sets. It is highly unlikely that all errors 

are independent, or that they are always additive in the same 

direction. Thus, we find this error analysis more reasonable 

than adding all maximum errors together (that is, 6.4 cm). We 

further note that these accuracies are based on data registration procedures performed locally to the landslide. Far-field 

data contained in the point clouds of the surrounding Hurricane Gulch neighborhood may not be accurate to these 

specifications.

Data Filtering

Point cloud data are subject to extraneous data from a 

number of sources that must be filtered (that is, removed) to 

obtain a reliable and user-friendly data product. Depending 

on the type of data that needs to be filtered, both manual and 

automated algorithms are available. To achieve a final “all 

points” data product (that is, a product that includes all objects 

in the scene, such as the ground, trees, and structures), we 

used manual filtering techniques within a point cloud software 

program (Maptek I-Site Studio version 5.1) to remove points 

from airborne water vapor and dust, birds, and people in the 

scene. We also manually deleted points representing tarps, 

ropes, and sand bags that were being installed on the headscarp of the landslide at the time of the survey. These objects 

were only visible from a few scan positions, and since they 

did not reflect the underlying ground data, they were deemed 

unnecessary to include in the final data product.

To obtain a bare-earth point cloud (that is, a point cloud 

with all vegetation and structures removed), we applied a more 

complicated methodology that utilizes a series of semiautomated filtering steps to remove points representing objects 

other than the ground surface. Using the same point cloud 

software program as previously described, we performed the 

following steps:

1. Beginning with the “all points” data, we applied a 

lowest point (topography) filter on a 1m grid and 

removed all other higher elevation points.

2. We created a triangulated irregular network (TIN) 

surface of the points from step 1 using a maximum 

boundary triangle length of 3 m. We subsequently 

Elocal = (Elaser )

2 + (Ereg )2

Eglobal = (Elaser )

2 + (Egeoref )2 + (Esurvey )2 + (Econtrol

)

2
Results 9

despiked (removed anomalous high or low points 

from) this surface.

3. Starting with the “all points” data again, we selected 

only points that were within 0.3 m of the TIN surface 

from Step 2 (surface proximity filter).

4. Using the point data set from Step 3, we applied a lowest point filter on a 0.5 m grid and removed all other 

higher elevation points.

5. We then created a TIN surface of the points from step 

4 using a maximum boundary triangle length of 2 m. 

We subsequently despiked (removed anomalous high 

points from) this surface.

6. Starting with the “all points” data a third time, we 

selected only points that were within 0.1 m of the 

TIN surface from Step 5.

7. Finally, using the point cloud data from step 6, we 

applied a lowest point filter on a 0.1 m grid to achieve 

a set of points that are representative of only the 

points on the ground surface within the scene.

Because the filtering algorithms utilized on the data work 

by removing the highest points within a given area, it is normal for points describing areas of vertical terrain (for example, 

landslide scarps) to be removed from the data. We mitigated 

this issue by manually adding the deleted vertical points back 

to the filtered model following the last step (step 7). This consequently added more depth and helped create a model that is 

more truthful to the actual ground surface.

Surface Generation

We created a bare-earth ground surface digital terrain 

model using the topographic surface model construction 

algorithm in our point cloud software program (Maptek I-Site 

Studio version 5.1). Here, we constructed a TIN surface, 

despiked the surface to remove any anomalously high or low 

surface points, and filled in any remaining holes in the surface 

with automated TIN-filling methods offered in our software.

Results

Survey Control

We present the survey point coordinates for all laser scan 

(LS#) and control point (CP#) locations, as well as the GPS 

base station bench mark (City of Sausalito point M-163) for 

completeness (table 1) and transparency of our surveying protocols. Note that the coordinate for which all points are based 

is the static GPS solution collected at M-163 on February 24, 

2019, which does not coincide exactly with the City of Sausalito’s NAD27 survey point that is referenced to NAD27 and 

California State Plane (Zone 3) coordinates. After performing 

a coordinate transformation for the City’s coordinate locations, 

our calculations indicate a −12.6 cm difference in easting and 

a −16.0 cm difference in northing between our GPS solution 

and the City’s surveyed benchmark solution (with our GPS 

solution having a smaller value in both cases). These differences are expected given the different surveying techniques 

with which the point was measured, and are highlighted here 

only for aid in any future use of the data in a different coordinate system than presented here (NAD83 and UTM).

Point Data

We present two point cloud data sets for the post-failure 

topography of the February 14, 2019, Sausalito Boulevard 

landslide—one each for the all points data set and the bareearth data set (fig. 8). The all points data set consists of six 

individual files that coincide with each of the six scan positions from which we collected data. Data includes points for 

the landslide and its surroundings, as well as for the vegetation, roads, and residential and other structures visible from 

the scan positions within the Hurricane Gulch neighborhood. 

The scan distance for these data extends to approximately 700 

m from the area of the landslide in some cases. The bare-earth 

data set consists of one combined file of the bare-earth data for 

the landslide source area and its immediate surroundings. Data 

includes only ground surface points as defined by the point 

filtering methodology outlined in the Methods section of this 

report. The scan distance for these data extends away from the 

landslide scarps by about 10 to 14 m.

All point cloud data files (all point and bare-earth data 

sets) are in ASCII (American Standard Code for Information 

Interchange) .txt format. Data files are available for public 

download from the USGS’ Science Base catalog, an opensourced collaborative scientific database. Data for the Sausalito Boulevard landslide can be found in Corbett and Collins 

(2019) accessible through Science Base.

Surface Data

The surface model data presented herein and included in 

the linked data files are but one possible reconstructed digital 

terrain model output using the point cloud data. We processed 

the data to generate a TIN surface model with approximate 

facet length of 10 cm and limited the model boundaries to just 

the landslide source area and surrounding terrain behind the 

landslide scarps (fig. 9). This model can be utilized for a variety of purposes including examining cross-sections through 

the landslide or to obtain the volume of the failed debris (with 

either a prelandslide lidar data set or a manually formed surface reconstruction).
10 Terrestrial Lidar Data of the February 14, 2019, Sausalito Boulevard Landslide, Sausalito, California

B

6.5 meters

SAUSALITO BOULEVARD

N

A

Control

point

GPS base 

station

Vegetation

Landslide 

source area

N

6.5 meters

Figure 8. Images of (A) unfiltered and (B) filtered, bare-earth point cloud data of part of the landslide source area. In (A), 

data includes all points of the scene including trees, survey tripods, and road barricades. In (B), data only includes points 

representing the ground surface.

Table 1. Table of processed georeferenced coordinates for base station, laser scan and control point locations.

Survey point name Easting1

X (meters)

Northing1

Y (meters)

Elevation2

Z (meters)

M-163 (base station) 545189.796 4189089.901 92.452

LS1 545183.327 4189090.155 95.661

LS2 545174.992 4189090.444 96.416

LS3 545195.706 4189095.806 94.238

LS4 545170.352 4189073.930 105.539

LS5 545187.977 4189067.145 110.146

LS6 545164.370 4189059.067 116.214

CP1 545180.830 4189089.082 96.081

CP2 545171.731 4189090.299 96.894

CP3 545172.804 4189079.789 101.530

CP4 545182.048 4189073.714 105.897

CP5 545194.185 4189094.776 94.528

1

Easting and northing referenced to NAD83(2011) horizontal datum and UTM Zone 10N projection.

2

Elevation referenced to NAVD88 vertical datum using the GEOID12B geoid applied to NAD83(2011) ellipsoid solutions. Elevation for the base station represents the indentation on the inset brass disk approximately 

10 cm below the pavement surface of Sausalito Boulevard. Elevation for laser scan locations represents the 

base of the instrument. Elevation for control points represents the center of the cylinders.
References Cited 11

The presented surface model is in .dxf format (drawing 

exchange format; see https://www.loc.gov/preservation/digital/formats/fdd/fdd000446.shtml) and is available for public 

download from the USGS’ Science Base catalog. Data for the 

Sausalito Boulevard landslide can be found in Corbett and 

Collins (2019) accessible through Science Base.

Summary

The February 14, 2019, Sausalito Boulevard landslide 

in Sausalito, California caused significant destruction and 

damage to several residences located in the Hurricane Gulch 

neighborhood of the city. The landslide, composed of a debris 

flow from a colluvial filled hollow, completely evacuated the 

source area and impacted several structures before coming 

to rest in the lower area of the neighborhood. The USGS 

assisted with the emergency response to the event by providing situational awareness of secondary landslide hazards, and 

collecting high-resolution topographic data of the landslide 

source area and surrounding terrain. The data collected from 

this work are available in Corbett and Collins (2019) for the 

purposes of future investigation of the landslide.

B

Landslide 

 source area

12 meters

SAUSALITO BOULEVARD

E

Z

N

A

Landslide 

 source area

SAUSALITOBOULEVARD

12 meters

E

Z

N

Figure 9. Images of bare-earth terrain model of the source area from two different perspectives: (A) looking oblique to the 

southwest, and (B) looking to the south. The model is constructed by joining points via a TIN (triangulated irregular network). Other 

types of surface models can also be generated using either the point data, or resampling of the TIN model.

Acknowledgments

We thank Katherine Arrow and Sean Reynolds (NPS), 

and Loren Umbertis (City of Sausalito) for assistance with site 

access. Funding for this project was provided by the USGS 

Landslide Hazards Program (https://www.usgs.gov/naturalhazards/landslide-hazards). Corina Cerovski-Darriau (USGS) 

and Francis Rengers (USGS) provided helpful reviews of this 

report.

References Cited

Collins, B.D., Corbett, S., Sankey, J.B., and Fairley, H.F., 

2014, High resolution topography and geomorphology at 

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Menlo Park Publishing Service Center, California

Manuscript approval March 29, 2019

Edited by Phil Frederick

Design and layout by Kimber Petersen
ISSN 2327-638X (online)

https://doi.org/10.3133/ds1112

Collins—Terrestrial Lidar Data of the February 14, 2019, Sausalito Boulevard Landslide, Sausalito, California—Data Series , March 2019