Monterey County Baseline Products and Pre Event Data …faculty.nps.edu/.../NPS-DHS_Playbook_RSC-02_Baseline_Products.pdfMonterey Baseline Products and Pre-Event Data Playbook # RSC-02

Monterey Baseline Products and Pre-Event Data Playbook # RSC-02

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Naval Postgraduate School Earthquake Response Project

Playbook #: RSC-02

Revised – 10/15/2013

Approved for public release; distribution is unlimited

Monterey County Baseline Products and Pre-Event Data Playbook


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Playbook Table of Contents

Executive Summary……………….……………………………………… iii Overview……………….…………………………………………………… 1 Purpose/Objectives……………….……………………………………… 1 Hardware Required……………….……………………………………… 1 Software Required……………….………………………………………. 1 Data Overview……………….……………………………………………. 2 Data Descriptions……………….…………………………………………. 4 Instructions (for viewing selected Datasets)……..………………… 6 Selected Sample Product Descriptions and Instructions…………… 16 Playbook Directory……….…………………………………………….. 20 Scientific Background and Additional Notes……..…………………. 21 References……….………………………………………………………… 31


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Executive Summary This Playbook provides a description of remote sensing imagery and other datasets prepared by the NPS/DHS Earthquake Response Project to provide baseline geographic information about Monterey County and City. These data are provided on a USB disk drive compatible with MS Windows systems for use by first responders and emergency managers as part of Emergency Operations Center resources. The playbook describes the directory structure of the disk; the individual datasets, their nature and characteristics; instructions for general use of the data; and some sample products that can be generated from the data. Selected data preparation steps are also summarized. The Playbook Directory near the end of this document shows the NPS Earthquake Response Playbook sequence to help put this Playbook into perspective and give an overview of products resulting from this research and some aspects of practical implementation. The content of each Playbook is briefly described; however, users are referred to the specific named and numbered Playbooks for full product descriptions. These provide additional detailed product information, instructions on how to separately utilize the individual products, and how to combine them into an integrated system for improved earthquake response.


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Overview Sponsored by the Department of Homeland Security (DHS) Science & Technology Directorate, the Remote Sensing Center (RSC) at the Naval Postgraduate School (NPS) has developed a series of instructional playbooks designed to assist first responders and emergency managers with the use of remote sensing technology for improving earthquake response.

This playbook (Playbook #RSC-02) describes remote sensing datasets and derived products designed to be a valuable source of geographic information in support of emergency planning, change detection, and post-disaster event assessment, response, and management. The Playbook outlines the data structure, specific dataset characteristics, and products developed by NPS/RSC from the data. It describes the steps used to produce the products and provides instructions for their use.

Purpose/Objectives

The objective and purpose of this playbook is to provide details about remote sensing and other geographic data specific to Monterey County and City. This Playbook can be used to develop an understanding of these data and derived products. The intent is that these data, maintained in a centralized archive will act as the starting point for establishing pre-event conditions and conducting emergency planning. Products and data can then be used with post-event data to determine areas of change, to perform damage assessment, and for evaluation of critical infrastructure.

Hardware Required

These data are provided on a USB external disk drive compatible with MS-Windows (XP, VISTA, Windows-7) operating system. Users should be able to plug this device directly into an USB port, have the drive recognized by the system, and be able to see the directory structure as described below. Data can then be used directly on the drive, or copied to another EOC resource. They can also be supplemented by existing imagery and geographic information developed by the EOC.

Software Required

While these data can be viewed and analyzed using any image processing software, ArcGIS is the common software supported by this project for display and viewing of these data and products. This playbook is written with the assumption that your organization is using ArcMAP version 10.0 or higher with 3D Analyst and Spatial Analyst extensions installed and licensed. Both of these extensions must first be activated and enabled under Customize – Extensions.


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For LiDAR data analysis, we also suggest downloading the free software QT Reader, which can display the GeoTIFF format elevation products, and QTT format point cloud data. If you have upgraded to ArcMAP 10.1, native LiDAR files (LAS format) can be added to a LiDAR dataset to exploit the data. Prior to version 10.1, to use the LiDAR in native LAS format, an additional toolbox can be added.

Additional processing and analysis can be achieved using any image processing software.

Data Overview Figure 1 shows the main data directory structure for the data and other information provided for the project on the USB drive. The “Monterey_Earthquake_Project_Page” is the starting point for an internal project website that provides further explanation and access to the data. The Playbooks developed by the project are also on the drive in the “Archived_Monterey_Playbooks” directory. The digital remote sensing data for the project (discussed in this playbook) are in the “Monterey_Baseline_Image_Data” directory. There are subdirectories under these main directories that contain variants or subsets of the data. The data directory names are indicative of types of data for provided. Details of individual datasets are described in separate sections below. Table 1 is a list of the datasets used for this project and provided on the USB drive. Additional information about how the data were acquired and how they have been processed are contained in the Scientific Background section of this Playbook. Some datasets are described further in the other playbooks of this series where they have been used to develop and illustrate specific products.

Figure 1: Monterey County/City Data Directory Structure


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Table 1: NPS/RSC Monterey Remote Sensing Datasets Dataset Location Product Resolution Dates

NAIP Aerial Photos

Monterey County MrSid Compressed RGB True color Mosaics

1m 2004,2005, 2006,2009, 2010, 2012

Worldview-2 North and West Monterey County

8-Band Reflectance Mosaic

2.25m April 2011

Worldview-2 North and West Monterey County

Panchromatic Mosaic

0.50m April 2011

USGS Ortho Quads

Monterey County MrSid Compressed Panchromatic Ortho Mosaic

1m

National Elevation Dataset (NED)

Part of Monterey County

DEM Mosaic 3m

National Elevation Dataset (NED)

Monterey County DEM Mosaics 10, 30m

ASTER GDEM Monterey County ASTER DEM 30m 2008

SRTM DEM Monterey County Shuttle Imaging Radar-C DEM

30m 2000

GTOPO30 Monterey County Regional Low Resolution DEM

1KM

GIS Data: Monterey County Boundary

Monterey County County Boundary Shape File

Vector

GIS Data Monterey City Infrastructure

City of Monterey Boundaries, Streets, etc

Shape Files Vector

GIS Data Monterey City Critical Infrastructure

City of Monterey Defined CIKR

Shape Files Vector 2012

Digital Raster Graphics

Monterey County DRG Mosaic 1m

AMBAG LiDAR Selected Monterey County Locations

Archived Block Data

2010

AMBAG LiDAR Monterey Peninsula

DEM Mosaic 0.65m 2010

AMBAG LiDAR Monterey Peninsula

DSM Mosaic 0.65m 2010

Aerial Photography (SDSU)

Monterey City True color Mosaic

0.14m Aug-12


Monterey City Frame Data 0.14m Aug-12

Orthophotography (NPS/WSI Contract)

Monterey Peninsula

True color Mosaic

0.15m Oct-12


Camp Roberts Frame Data 0.1m Aug-12


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Data Descriptions The following describes the general characteristics of the data provided. More detailed information is available in the Scientific Background section. Worldview-2 (WV-2) Data (in Montery_County_Data_01_DigitalGlobe_Worldview-2_Data) Coverage of northern and western Monterey County acquired 15 April 2011 is provided with 0.5m spatial resolution Panchromatic WV-2 data and 2.25m spatial resolution Multispectral (8-band) WV-2 Data. The final WV-2 imagery have been orthorectified, and projected to map coordinates in UTM Zone 10 North, with the datum set to WGS-84. The multispectral data have also been atmospherically corrected to apparent surface reflectance. There are a total of 14 multispectral scenes and 14 panchromatic scenes that have been mosaicked into a single file for each mode. Detailed information about the datasets and how they were processed is contained in the Scientific Background section of this playbook. National Agricultural Imagery Program (NAIP) Data (in Monterey_County_Data-02_Aerial_NAIP_Orthophoto_Mosaics) Selected Monterey County coverage is provided by high spatial resolution (1m) true color aerial photography for multiple dates. National Agricultural Imagery Project (NAIP) data are collected by the U.S. Department of Agriculture on a periodic basis (yearly in some areas) to provide high spatial resolution aerial photography for agricultural assessment purposes. The NPS Baseline dataset provides coverage for Monterey County in the years 2004, 2005, 2006, 2009, 2010, and 2012 in MrSid (compressed) format. This format can be read by ArcGIS and many other software. The NAIP data are useful for a variety of purposes and provide a good baseline and timeline of imagery data. USGS Orthoquad Mosaic Data (in Monterey_County_Data-03_USGS_Orthoquad_Mosaic)

This is a mosaic of orthorectified panchromatic imagery at 1m spatial resolution produced by the U.S. Geological Survey. Full coverage of Monterey County is provided. Elevation Datasets (in Monterey_County_Data-04_Elevation_Data_(DEM))

These datasets cover a range of spatial resolution digital elevation models (DEMs) produced using a variety of methods. 3, 10, and 30m spatial resolution DEMs produced by the USGS using photogrammetric methods are included. The 10m and 30m DEMs cover the full extent of Monterey County. The 3m DEM only covers the Monterey Peninsula and nearby areas. Alternate DEMs products include the ASTER GDEM (30m), compiled using stereo images from the ASTER satellite, the SRTM DEM (30m) produced through radar interferometry from the Shuttle Imaging Radar Topography Mission (NASA), and the GTOPO30 low resolution (1km) DEM. Selection of which DEM to use depends on coverage, application, and resolution.


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GIS Datasets (in Monterey_County_Data-05_GIS)

These datasets include the Monterey County boundary; general infrastructure for the City of Monterey such as roads, hydrography, and boundary; and Monterey City critical infrastructure. Critical infrastructure data are discussed further in Playbook #: RSC-03 A digital raster graphics (1m-resolution scanned topographic map) of Monterey County is also included. Light Detection and Ranging (LiDAR) Data (in Monterey_County_Data-06_LiDAR_Data)

Captured with advanced measurement techniques, LiDAR produces accurate elevation data that can be used in the preparation, response, and recovery of a large disaster event. LiDAR provides a highly accurate and high resolution representation of the earth as individual points, collectively known as a point cloud. Unfortunately, much of the software in use today does not natively support the point data in the original LAS format. To make the data more useful for the planners, responders, and recovery personnel in Monterey, a variety of the most common formats derived from the point cloud data have been provided. Data contained in this directory are comprised of AMBAG LiDAR data collected during 2010. The Archived Block (Raw) data are included for completeness, however, the principal datasets provided as baseline data and for general use are Monterey Peninsula DEM and Digital Surface Model (DSM) mosaics. Additional details about the datasets and how they were processed is contained in the Scientific Background section of this playbook. Selected sample products are described later in this playbook. High Resolution Orthophotography (NPS Contract to WSI) (in Monterey_Peninsula_Data-07_Orthophotography (2012-NPS-Contract))

High spatial resolution (15cm) 4-band orthophotography data were acquired by WSI under contract to NPS during October 2012. Data for most of the Monterey Peninsula are mosaicked together at full resolution to form one file covering most of the Monterey Peninsula. These represent the most recent and highest resolution coverage currently available. High Resolution Aerial Data (SDSU) (in Monterey_Peninsula_Data-08_Aerial_Photography(SDSU)

These data are high spatial resolution aerial photography coverage of Monterey City critical infrastructure acquired from a light aircraft during August 2012. There is also a high resolution mosaic image of most of the City of Monterey. Mosaics are uncontrolled and may have some spatial offsets.

High Resolution Aerial Data (Camp Roberts)(SDSU) (in Opisbo_Monterey_Counties_Data-09_NPS_Camp_Roberts_Data)

These data are high spatial resolution aerial photography coverage of selected portions and targets at Camp Roberts, California, acquired from a light aircraft during August 2012.


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Instructions (for viewing selected Datasets) This section provides detailed instructions on how to access and view the baseline datasets. It also describes how they can be used to assess pre-event conditions, and generally how they would be used with post-event data to determine change, provide damage assessment, and assist with critical infrastructure evaluation. Details of post-event data and processing requirements and selected examples/case histories are shown in other Playbooks in the NPS/RSC sequence. See the Playbook Directory and individual Playbooks for additional details.

1.0 Viewing WorldView-2 Data in ArcGIS (in Monterey_County_Data-01_DigitalGlobe_Worldview-2_Data) Worldview-2 (WV-2) data are satellite remote sensing imagery collected by the company “Digital Globe” and are constantly being updated. Both Panchromatic (grayscale) data at approximately 0.6m spatial resolution and Multispectral (“color”) data at approximately 2.24m spatial resolution are provided. The following steps can be used to visualize the WorldView-2 data in ArcMap (ArcGIS). Data have been orthocorrected (corrected to map coordinates) and processed to be used as baseline imagery. Further data descriptions and processing information are included in the Scientific Background section of this Playbook. WV-2 Panchromatic Imagery

-> Start ArcMap by double clicking the program icon or selecting from the Start menu

-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the WorldView-2 panchromatic data directory (Monterey_County_Data-01_DigitalGlobe_Worldview-2_Data/Monterey_County_WV-2_Pan_Mosaic)

-> Select the image (Monterey_County_Pan_Ortho_Mosaic.dat), and click Add (Figure 2).

Figure 2: Panchromatic imagery in ArcMap, Border (0) values being displayed.

To Remove Borders:

-> Right click the image name in the Layers list within the Table of Contents frame at the left side of the main window, and click Properties.


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-> Click on the Symbology tab, check the box for Display Background Value, and leave the defaults.

-> Click Apply, then Okay (Figure 3)

Figure 3: Panchromatic image displayed correctly in ArcMap

WV-2 Multispectral Imagery


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the WorldView-2, 8-band data directory (Montery_County_Data_01_DigitalGlobe_Worldview-2_Data/Monterey_County_WV-2_8-

Band_Reflectance_Mosaic). -> Select the image (Monterey_County_Mosaic_8-Band_CorrectedFLAASH.dat), and click Add. -> Once the image has loaded, ArcMap automatically chooses the first three bands

to display (Figure 4).

Figure 4: ArcMap displaying the falsely colored final WorldView 2 image.


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NOTE: This image is “False Color”. To display it in ‘True Color” the bands that we want to display are Band 5 (Red, 0.6588 nm), Band 3 (Green, 0.5457 nm), Band 2 (Blue, 0.4783 nm) – see below.

-> In the Table of Contents frame, right click the WorldView-2 image in the Layers list, and click Properties.

-> Click the Symbology tab, then choose the new band for the Red Channel by clicking on the arrow to the right of the currently selected band name and choosing Band 5 (Figure 5). Repeat for green and blue, choosing Band 3 for the Green Channel and Band 2 for the Blue Channel.

-> Check the box for Display Background Value (R, G, B), and leave the defaults. Refer to Figure 3.

-> Click Apply, and then click OK. The correctly displayed imagery should look similar to Figure 6 (a subset is shown here).

Figure 5: Layer Properties for correctly displaying WorldView 2 data.


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Figure 6: WorldView 2 Image correctly displayed.

2.0 Viewing National Agricultural Imagery Project (NAIP) Data in ArcGIS (in Monterey_County_Data-02_Aerial_NAIP_Orthophoto_Mosaics)

The following steps can be used to visualize the NAIP data in ArcMap (ArcGIS).


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the one of the NAIP data directories (for example, Monterey_County_1m_NAIP_2012 for the 2012 NAIP data.

-> Select the image ending with the extension “.sid” (something like ortho_1-

1_1n_s_ca053_2012_1.sid) and click Add. The image will be displayed similar to Figure 7.

Figure 7: NAIP displayed with borders


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To Remove Borders: -> Right click the image name in the Layers list within the Table of Contents frame

at the left side of the main window, and click Properties. -> Click on the Symbology tab, check the box for Display Background Value, and

leave the defaults. -> Click Apply, then Okay (Figure 8)

Figure 8: NAIP correctly displayed

3.0 Viewing USGS Orthophotography Quad Mosaic Data in ArcGIS (in Monterey_County_Data-03_USGS_Orthoquad_Mosaic)

These are panchromatic aerial photography data collected by the U.S. Geological Survey for mapping purposes. Originally assembled on USGS Topoquad boundaries, they are now provided as orthorectified County mosaics. These data make a useful orthorectified (high precision map geometry) baseline imagery dataset. The following steps can be used to visualize the USGS Orthoquad Mosaic data in ArcMap (ArcGIS).


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to USGS Orthophography data directory (Monterey_County_Data-03_USGS_Orthoquad_Mosaic)

-> Select the image (ortho1-1_s_ca053.sid), and click Add (Figure 9) To Remove Borders:

-> Right click the image name in the Layers list within the Table of Contents frame at the left side of the main window, and click Properties.


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-> Click on the Symbology tab, check the box for Display Background Value, and leave the defaults.

-> Click Apply, then Okay

Figure 9: Orthoquad mosaic displayed in ArcMap with borders.

Figure 10: Orthomosaic displayed without borders.


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4.0 Viewing Digital Elevation Model (DEM) Data in ArcGIS (in Monterey_County_Data-04_Elevation_Data_(DEM))

These are spatial elevation models from a several sources at a variety of spatial resolutions, giving x, y (latitude and longitude) and z (elevation) information. Originally assembled on USGS Topographic quadrangle boundaries, they are now provided as orthorectified County mosaics. These data make a useful orthorectified (high precision map geometry) baseline imagery dataset. The following steps can be used to visualize the DEM data in ArcMap (ArcGIS).


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to one of the DEM data directories, for example (Monterey_County_Data-05_GIS /Monterey_County_10m_DEM)

-> Select the image with the extension “.dat” or “.tif”, for example (Monterey_County_NED10m_DEM_Mosaic.dat), and click Add

-> ArcMap will correctly display the elevation model without any further steps.

5.0 Viewing GIS Shape Files (Baseline and Critical Infrastructure) in ArcGIS Geographic Information System (vector) files of selected information for Monterey City and County are provided on the data disk. These include baseline infrastructure such as road centerlines, hydrography, and county and city boundaries as well as critical infrastructure for the City of Monterey defined by the Monterey OES. These data are provided in ArcGIS “shape file” vector format and can be used as overlays on the raster baseline image data. One example of loading a shape file is given below – the rest of the shape GIS shape files are loaded in similar fashion.

-> Start ArcMap by double clicking the program icon or selecting from the Start

menu -> Display a raster image dataset (for example one of the DEMs) by clicking the Add

Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to one of the DEM data directories, for example (Monterey_County_Data-05_GIS /Monterey_County_10m_DEM)

-> Select the image with the extension “.dat” or “.tif”, for example (Monterey_County_NED10m_DEM_Mosaic.dat), and click Add

-> ArcMap will correctly display the elevation model without any further steps. -> To display the GIS data (Monterey County Boundary) as an overlay to the

displayed image, click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the GIS data directory for the boundary (Monterey_County_Boundary)

-> Select the subdirectory of interest within this directory. For this example we use the Monterey_City_Baseline_Infrastructure directory.

-> Choose the file Monterey_County_Project.shp and click Add. A dialog will ask about the data transformation – click close on this dialog, then an opaque, filled version of the county boundaries will be overlain.


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-> Right click on the colored box underneath the Layer name in the Table of Contents at the left of the data frame and choose “No Color”. The boundary will be displayed as a solid line overlain on the image

6.0 Viewing USGS Digital Raster Graphics (DRG) Data in ArcGIS

(in Monterey_County_Data-05_GIS)

Digital Raster Graphics (DRG) are made by scanning published paper maps on high-resolution scanners. The raster image is georeferenced and fit to the Universal Transverse Mercator (UTM) projection. Colors are usually standardized to duplicate the line-drawing character of the published map. Originally assembled on USGS Topographic quadrangle boundaries, they are now provided as County mosaics. These data provide useful information about infrastructure such as roads and buildings, city boundaries, etc. They are only as current, however, as the map that was scanned and thus don’t include many recent changes. They are best used as a means to visualize general cultural features with respect to other imagery and maps. The following steps can be used to visualize the USGS DRG data in ArcMap (ArcGIS).


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the DRG data directory (Monterey_County_Data-05_GIS / Monterey_County_Digital_Raster_Graphics)

-> Select the image with the extension “.sid”, (drg_s_ca053.sid), and click Add -> No further steps are needed. ArcMap will correctly display the data.

7.0 Viewing AMBAG LiDAR Data in ArcGIS (in Monterey_County_Data-06_LiDAR_Data)

Light Detection and Ranging (LiDAR) is a form of remote sensing based on very accurate elevation measurements using active light sources. They can be used to develop digital elevation models (DEM) as well as digital surface models (DSM). DSM can include information about vegetation, buildings, and other vertical structures. The LiDAR data provided for this project were collected during 2010 for the Association of Monterey Bay Area Governments (AMBAG) under USGS funding. “Raw” (Block) data are provided for archive purposes, however, the processed Digital Elevation Model (DEM) and Digital Surface Model (DSM) data should be used as baseline imagery. Further data descriptions and processing information are included in the Scientific Background section of this Playbook.


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the LiDAR data directory (Monterey_County_Data-06_LiDAR_Data/ Monterey_Peninsula_AMBAG_LiDAR_Mosaics)

(note: another subdirectory provides “raw” LiDAR block data, but this is really only for use by GIS professionals interested in generating their own products)


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-> Select either the “_DEM.dat” (digital elevation model) or the “_DSM.dat” (digital surface model) image and click Add. The DEM is the earth surface topography. The DSM is a 3D model that includes buildings, trees, and other above-ground objects (see Playbook#RSC-07 for details on these products)

-> No Further steps are needed to correctly display the data. (See the Selected Products section and Playbook#RSC-07 for some details on products that can be generated/viewed).

8.0 Viewing High Resolution Orthophotography (NPS Contract with WSI)

in ArcGIS (in Monterey_Peninsula_Data-08_Orthophotography (NPS-Contract))

High spatial resolution aerial orthophotography was acquired of the Monterey Peninsula as part of a survey of the NPS campus during October 2012. These data provide a good current (October 2012) high-resolution photographic baseline for Monterey. Further data descriptions and processing information are included in the Scientific Background section of this Playbook.


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the NPS orthophotography data directory (Monterey_Peninsula_Data-07_Orthophotography/2012-NPS-Contract/Monterey_WSI_Orthophoto_Mosaic)

(Note: another subdirectory provides archived individual photo frame data, but this is really only for use by GIS professionals interested in generating their own products)

-> Select the image (Monterey_Peninsula_WSI_4-Band_Ortho_Mosiac.dat) and click Add. -> Right click the image in the Table of Contents, and click Properties. -> No Further steps are needed to correctly display the data.

9.0 Viewing High Resolution Aerial Data (SDSU) in ArcGIS (in Monterey_Peninsula_Data-07_Aerial_Photography(SDSU))

High spatial resolution color aerial photography coverage of Monterey City critical infrastructure was acquired by San Diego State University from a light aircraft during August 2012. These data, which cover specific identified Monterey City critical infrastructure, are provided as “Frame” data (individual photographs) and as a mosaic. The Frame data are designed to act as baseline data for reacquisition of specific Monterey City infrastructure after an earthquake event. A high-resolution true-color mosaic of high spatial resolution aerial photography for most of the Monterey Peninsula is also provided. This provides a good current (August 2012) high-resolution photographic baseline for Monterey; however, this is an uncontrolled mosaic, so there may be some spatial offsets. Further data descriptions and processing information are included in Playbook#RSC-04A.


-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to the SDSU orthophotography data directory


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(Monterey_Peninsula_Data-08_Aerial_Photography(SDSU)/ Monterey_image_mosaics_courtesy_of_NEOS)

(note: other subdirectories provide frame data for critical infrastructure. These are discussed further in Playbook#RSC-04A.

-> Select the image file neos_ortho_monterey_12aug12_sdsu_modified.tif and click Add. -> Right click the image name in the Layers list within the Table of Contents frame

at the left side of the main window, and click Properties. -> Click on the Symbology tab, check the box for Display Background Value, and

leave the defaults. -> Click Apply, then Okay

10.0 Viewing High Resolution Aerial Data (Camp Roberts) (SDSU) in ArcGIS (in Opisbo-Monterey_Counties_Data-09_NPS_Camp_Roberts_Data)

High spatial resolution color aerial photography coverage of portions of Monterey and San Obispo Counties, California, covering the vicinity of Camp Roberts was also acquired by San Diego State University from a light aircraft during August 2012 in support of the NPS RELIEF exercise. These data, which cover specific identified areas at Camp Roberts are provided as “Frame” data (individual photographs) for change detection. These are designed to provide examples of pre- and post-disaster-event time series. Further data descriptions and processing information are included in Playbook #RSC-4A.


menu -> Click the Add Data (+) button or select File->Add Data->Add Data from the main

menu, and navigate to the Camp Roberts orthophotography data directory (Obispo-Monterey_Counties_Data-09_NPS_Camp_Roberts_Data/RELIEF_image_frames_raw_not_georeferenced/RELIEF_Aug_15th_high_quali

ty_JPEGs) directory Note: other subdirectories provide image collection information and sample change detection products. These are discussed further in Playbook#RSC-04A.

-> As an example, select the image file “IMG_4786.JPG” and click Add. -> You may be asked if you would like to build pyramids. Click No. There may also

be a question regarding Unknown Spatial Reference. Click OK. If you have previously displayed georeferenced data, you may need to exit and restart ArcMap for proper display


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Selected Sample Product Descriptions and Instructions The following is a description of selected products that can be generated from the archive data.

Shaded Relief from LiDAR DSM Data in ArcGIS The shaded relief of the digital surface model allows even the most inexperienced person to identify built structures, trees, and other features above the ground. This layer (Figure 11) can be interactively defined by clicking on a few buttons on the Image Analysis window of ArcMAP (see below) and can provide a backdrop for planning emergency evacuation routes, search and rescue maps, and longer term for resource allocation during recovery after a disaster.

Figure 11: Sample Shaded Relief Image (subset of the full image)



menu, and navigate to the LiDAR data directory (Monterey_County_Data-06_LiDAR_Data/ Monterey_Peninsula_AMBAG_LiDAR_Mosaics)

-> Select the “Monterey_Peninsula_LiDAR_Mosaic_DSM.dat” (digital surface model) image and click Add. The DSM is a 3D model that includes buildings, trees, and other above-ground objects (see Playbook#RSC-07 for details on these products)

-> Click Windows->Image Analysis to start the image analysis tool. This will appear as a docked window on the right edge of the ArcMAP display.


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-> Click on the icon just below the Image Analysis label on the window to select the Image Analysis Options

-> Within the options click on the “Hillshade” tab, use the default values; then click OK

-> In the Image Analysis Window, click on the DSM filename at the top of the window “Monterey_Peninsula_LiDAR_Mosaic_DSM.dat” then in the Processing portion of the dialog near the bottom, choose the arrow next to the color bar and change it to a grayscale bar by choosing that representation at the top of the list

-> Now click on the icon just to the right of the grayscale bar to calculate the hillshade and display as a grayscale image (Figure 12)

An alternate method is to choose the hillshade option under the image properties. -> Start ArcMap by double clicking the program icon or selecting from the Start


menu, and navigate to the LiDAR data directory (Monterey_County_Data-06_LiDAR_Data/ Monterey_Peninsula_AMBAG_LiDAR_Mosaics)


-> Right click on the file name in the Table of Contents window under the Layers selection and choose Properties

-> Click on Use hillshade effect near the middle left of the Layer Properties dialog, then apply and OK. The hillshade image will be displayed without creating a new later.

Slope and Contour Maps from LiDAR DEM Data in ArcGIS Slope can be derived from the DEM GeoTIFF files (or the LiDAR data) in ArcMAP. Like most of the tools described in this playbook, this tool can be found in the search bar of ArcMAP shown below (Figure 12). You must be sure to activate the 3D Analyst and Spatial Analyst extensions by enabling under Customize –> Extensions on the main ArcMAP menu bar.

Figure 12: 3D Analyst


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-> Select Windows->Search from the ArcMap main menu to start the search function -> Enter “Slope Spatial Analyst” for the search term, and then click on the search

(magnifying glass) icon -> Click on the first item in the search results “Surface Slope (Spatial Analyst) to start -> Enter the DSM filename Monterey_Peninsula_LiDAR_Mosaic_DSM.dat as the Input Raster

and your own output filename for the Output Raster, for example Monterey_Peninsula_LiDAR_Mosaic_DSM_Slope.dat, then click OK to calculate

-> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu, and navigate to where you saved the slope output file

-> Select the slope image output file that you created and click Add. Allow creation of pyramids is asked. The slope calculation result will be displayed in ArcMap. You can optionally apply a color table by right clicking on the new filename in the Layers dialog, choosing Symbology, and then selecting the color ramp you want to use from the pulldown menu and clicking apply followed by OK.

By defining the input raster surface, the user can select either degree or percentage slope derived layers. In the example slope image below, the degree of slope was calculated for the entire Monterey peninsula. This understanding of the slope can help emergency planners and responders identify escape routes, vehicle versus walking traffic ability, fire spread risk, landslide hazard, and suitable helicopter landing zones.

Figure 13: Degree of slope map for Monterey Peninsula

Many planners and responders may want to have the elevation contours added to their maps. These can be easily derived from the elevation data using the search for contour tool. Specify the input raster, output feature class (create a line class) and the interval. After they are created, use the label manager to add or remove the height interval label after various scales.


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Line of Sight using DSM from LiDAR Data in ArcGIS Much of the emergency lines of communication rely on line of sight. Wi-Max used to get internet connections to low or no bandwidth locations are highly dependent on line of sight. It’s important to optimize the placement of this equipment based on the terrain. With the high resolution LiDAR data, you can model whether an observer can see the other end of the communication link. This analysis is quickly incorporated with the 3D analyst toolbar shown below:

Figure 14: Line of Sight

-> Start ArcMap by double clicking the program icon or selecting from the Start menu -> Click the Add Data (+) button or select File->Add Data->Add Data from the main menu,

and navigate to the LiDAR data directory (Monterey_County_Data-06_LiDAR_Data/ Monterey_Peninsula_AMBAG_LiDAR_Mosaics)


-> Add the 3D Analyst Toolbar to your instance of ArcMap by selecting Customize->Toolbars->3D Analyst

-> To create the line of sight, click on the “eye” (Create line of sight) icon, then and place the starting and ending point of the two places chosen during planning or response by clicking on the image

-> Create dropdown graph of the line of sight by choosing the Graph Profile icon from the menu bar (this is only available to view the results after placing both ends of the line of sight). This plot can be used to help determine whether this link of your communications equipment would be a viable choice (Figure 15).

Figure 15: Line of Sight profile from LiDAR data (note obstructions).


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Playbook Directory This Playbook is one of a series of Playbooks designed to cover the technical breadth of the NPS-DHS Earthquake Response Project. Each Playbook describes one series of products and its use. These Playbooks can be printed, transmitted electronically as Portable Document Format (PDF) documents, or stored locally on existing emergency management networks, workstations, or mobile devices. The following summarizes the individual Playbooks developed as part of this project and available to emergency responders. See the listed Playbook for specifics and details.

Playbook#RSC-01: NPS-DHS Remote Sensing Project/Products Overview

Playbook documenting project and scope and big picture for other Playbooks

Playbook#RSC-02: Monterey County Baseline Products and Pre-Event Data Processing

Playbook documenting baseline data, preprocessing, use/analysis of basic products

Playbook#RSC-03: Monterey (City) Infrastructure Products

Critical Infrastructure data (location, description, pre-event photos, geolocated imagery

frames and metadata)

Playbook#RSC-04A: Airborne Imagery Change Detection Products (SDSU) Monterey baseline imagery of critical infrastructure, Camp Roberts imagery, and selected

change detection example products. Full-Resolution NEOS imagery

Playbook#RSC-04B: NOAA Night Lights/Power Change Detection and Fire Detection Products Night lights/power and fire detections (NOAA)

Playbook#RSC-05A: Social Networking Products (Ushahidi)

Ushahidi implementation and instructions for Monterey City/County

Playbook#RSC-05B: Social Networking Products (Twitter)

Twitter implementation and instructions for Monterey City/County

Playbook#RSC-06: Mobile Application Damage Assessment Product Lighthouse damage assessment application download, install, configure, execute

Playbook#RSC-07: Post Event Processing Scenarios Products

LiDAR DEM, DSM, derived products, NAIP/WV-2 Change Detection Examples

Playbook#RSC-08: Soft and Hardcopy Output Products and Distribution

GeoPDF Products, Monterey Map Books, w/National Grid Index, PDF and Printed

Playbook#RSC-09: Common Operating Picture (COP) Products

Sensor Island Common Operating Picture, UICDS to WebEOC Link

Playbook#RSC-10: Systems Integration, Transition, and Training

Hardware/Software Installation Details, Coordination, and Integration


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Scientific Background and Additional Notes AMBAG LiDAR Data The elevation data, which is all derived from LiDAR point clouds (see Raw LiDAR Metadata section for collection details), is provided in a variety of formats to assist the user. In order to make the file sizes manageable, they have been broken up into blocks based on geographical area of coverage in Monterey. In the figure on the next page, you can see the naming scheme in use for the City of Monterey. The first number of the file corresponds to the block, while the remaining portion refers to the horizontal and vertical column of the coverage extent.

Figure 16: The extent of the downtown Monterey elevation data and the filename, a full index of the data can be found in the “Read Me” folder.

All files are provided in the Monterey AMBAG LiDAR folder. The formats that are provided are listed below:


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Figure 17: Various LiDAR Archived Datasets

Each application or analyst may require a different format, so the most common formats have all been included. These include (in order):

the bare earth digital elevation model or “DEM” as GeoTIFF files

the data which includes the features on the surface of the earth such as buildings and trees, known as the digital surface model or “DSM” as GeoTIFF files

the Google Earth friendly overlay KML files

the raw LiDAR point cloud LAS files which include class and intensity attributes

the QTT files that can be used in QT Modeler or QT Reader (free) software

the triangulated irregular network or “TIN” files commonly used in ArcMAP software

Also included in the data folder are the mosaicked DSM and DEM files for coverage of downtown, and the extent available for the county. Finally, a virtual mosaic file format known as a “mosaic dataset” in ArcMAP is also included in the Monterey AMBAG LiDAR folder, located in the Monterey DSM file geodatabase. The footprint coverage areas of this data are shown in the figure below.


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Figure 18: The extent of the LiDAR coverage available for Monterey County. Each tile is available as a KML (Google Earth), TIN (ArcMAP), GeoTIFF DEM and DSM, LAS and QTT (Point Cloud).

Working raw LiDAR las files in ArcMap 10.1 In each of the Block Las Classified folders, a LAS dataset has been added. This is the new format in ArcMAP 10.1 which allows uses to display raw LiDAR point data. After adding the dataset to your table of contents, make sure the LiDARs Dataset toolbar has been activated under Customize-Toolbars-LAS Dataset. You should see the point cloud at a large scale zoom, and the las file boundaries at a small scale zoom.


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Figure 19: LAS dataset added to ArcMap 10.1 and displayed using the point cloud classification. This

can help emergency managers determine above the ground and water features.

Figure 20: 3D view of the LiDAR las file using the LAS Dataset toolbar in ArcMap 10.1

This new las dataset and toolbar allows users to visualize point data in three dimensions for the first time within ArcMAP. The importance of this visualization tool is described further in the next section. Working with GeoTIFF and QTT format data in Quick Terrain Reader Quick Terrain Reader provides a free software to visualize LiDAR derived data. While ArcMAP provides many opportunities for analysis, it does not do a very good job of


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rendering the data in three dimensions. For improved visualization of the data, QT Reader can ingest both the GeoTIFF and QTT format data to provide this capability. The two examples provided below demonstrate how this looks. Once imported, this visualization can provide emergency planners with an interactive experience to represent an area of responsibility, or the incident commander with detailed information on an area of ongoing operations. Using the measurement tool can assist with decisions to send resources, or an approximation of the building square footage damage after an earthquake. Finally, during the recovery stage, the city council could use this capability to show the area as it looked versus new construction.

Figure 21: Visualization of the LiDAR data in three dimensions using the GeoTIFF digital surface model.


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Figure 22: Measurement of the buildings in an area of downtown Monterey.

Working with raw LiDAR las files using LAStools For the more advanced user, the tools available in the software described above may not suffice. Therefore, we wanted to note that software is available at lastools.org that can extend the use of the raw las files. These are similar to command line tools, however, have been added to an ArcMAP toolbox for ease of use. Each script performs a different operation on the LiDAR data that might assist the more advanced GIS analyst customize applications and workflows. A few of the applications are obvious from the name of the script, while others require further reading.

Figure 23: LAS Tools


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Raw LiDAR Metadata Abstract: This metadata consists of descriptive information about the high resolution LIDAR (Light Detection and Ranging) data acquisition and processing for the Association of Monterey Bay Area Governments (AMBAG). LIDAR data was acquired in 2010 in the Central Coast region of California including areas of Monterey, San Benito and Santa Cruz Counties. The metadata of this dataset is for Block 1, which covers Santa Cruz County and portions of San Mateo and Santa Clara Counties. This block, the first out of nine total, is set in the State Plane Zone III coordinate system. It is this reason it will be separated from the other eight blocks, which are in Zone IV. The dataset consists of LIDAR classified and raw point clouds in LAS format, DEMs in Erdas.img format, TINs in ESRI TIN format, and breaklines with hydro-flattened water bodies in shapefile format. 10 feet (sf) resolution DEMs were generated from TINs. TINs and DEMs represent the Earth's surface where man-made structures and vegetation have been removed. Purpose: The LIDAR operation was designed to provide a highly detailed ground surface dataset to be used for the development of topographic, contour mapping, and hydraulic modeling. Oceanographic, agricultural, and atmospheric research facilities, etc. will directly benefit from the LIDAR and elevation data sets produced from this project. This project is funded through an American Reinvestment and Recovery Act of 2009 grant, awarded by the US Geological Survey (USGS). The Project is administered by AMBAG in consultation with the USGS staff. Data was analyzed to pinpoint areas that need to be adjusted. The Point Cloud Grid was reviewed to find and reclassify laser point noise and outliers. Contours were reviewed to ensure the correct classification of ground cover versus vegetation and man-made structures.</attraccr> -<qattracc> <attraccv>98</attraccv> <attracce>Vegetation and man-made structures were marked as unclassified, Code 1. Noise and other outliers were marked as Code 7. LIDAR points over water bodies were classified to water, Code 9, manually. The classified data within a average square kilometer area is at 98% accuracy.</attracce> </qattracc> </attracc> <logic>Atmospheric and meteorological measurements were recorded and adjusted for a calculated average ground level, as a setting for several algorithms to normalize other flight factors. Algorithms were conducted on each flight's trajectory with heading, roll, pitch, and mirror angle. Adjustments and calculations were conducted in accordance with these parameters to maintain data uniformity among all areas. Flights were conducted at constant speed (120 knots) and altitude (4,000 ft). The LIDAR system was calibrated by conducting two sets of flight passes over the airport runway. The calibration parameters were inserted into the post-processing software to eliminate IMU errors. Pre-flight checks such as cleaning the sensor head glass were performed. A five minute INS initialization was conducted on the ground, with the engines running, prior to flight, to establish fine-alignment of the INS. The LIDAR scan width angle was at 25 Degrees. The scan frequency was at 40 Hertz.</logic> <complete>The Zone 3 dataset covers Block 1. There are a total of 188 grid tiles covering 448.3 square miles of project area. Each tile is 12,000 sf by 8,000 sf. The entire project dataset covers an area of approximately 1,712.6 square miles. Not all the tiles are completely filled with data. The areas outside the project limit have no data value in DEMs. No areas were omitted during data collection. Tiles do not overlap each other. The Optech "ALTM NAV" software was used to plan and navigate the aircraft in real time. The LIDAR system


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operator uses this comprehensive flight management system to see, among other things, real-time swath coverage so that any gaps or GPS quality issues can be resolved before landing or leaving the site Horizontal accuracy of LIDAR dataset was checked against orthophotos provided by AMBAG. Horizontal accuracy was better than 2 sf.</horizpar> -<qhorizpa> <horizpav>2</horizpav> <horizpae>Accuracy is within specification.</horizpae> </qhorizpa> </horizpa> -<vertacc> <vertaccr>The final LIDAR product is within vertical accuracy of +/- 1.2 sf at the 95% confidence level which meets Base Lidar Specification for projects funded under the American Recovery and Reinvestment Act of 2009 U.S. Geological Survey Program Announcement 10HQPA0014.</vertaccr> -<qvertpa> <vertaccv>0.232</vertaccv> <vertacce>After final LIDAR classification, the bare earth data was evaluated using 20 surveyed GPS checkpoints that fall into Zone 3. The Average dZ of all check points is -0.032. The Consolidated Vertical Accuracy or RMSEz is 0.232 sf, or 7 cm. This is within the RMSEz limit of 15 cm. The NSSDA Accuracy z 95% was set for 30 cm. The score for Zone 3 RMSEz x 1.96 was 13.8 cm. This is within the 95% margin of error. The minumum dZ is -0.595, while the maximum is 0.315. The standard deviation of all points is 0.236.</vertacce> 1-Acquisition: The Lidar misson was flown in multiple days with a flight height of 4000' above mean terrain height. The Zone 3 project area consists of data from of 188 tiles. ALTM Gemini was used as the LIDAR scanner. Flight lines had 50% overlap. LIDAR flight settings were: System PRF (kHz), 100 Scan Freq (Hz), 40 Deg. Scan Angle +/-, 25 Deg. Scan Cutoff, 5 m Desired Resolution, 0.593 Swath (m): 887.75 2-Processing LIDAR data was processed and fit to the ground using DASHMap and GeoCue software. All of the data was calibrated to determine and eliminate systematic biases that might occur within the hardware of the ALTM Gemini system. A total of 20 aerial targets were surveyed and used to fit the LIDAR data to the ground for Zone 3. LIDAR points were broken out into five classes: Processed, but unclassified (code 1), Bare-earth ground (code 2), Noise (low or high, manually identified, if needed) (code 7), Water (code 9), Ignored Ground (Breakline Proximity) (code 10). Breaklines and water features were compiled as digitizing features from LIDAR intensity orthophotos. Water bodies (ponds and lakes), wide streams and rivers ("double-line"), and other non-tidal water bodies were hydro-flattened. Final bare earth was processed using first and last laser returns. Man-made structures including bridges and vegetation were removed from the bare earth data. TINs were created using bare earth LIDAR, breaklines, waterlines, and hydro-flattening water bodies in ArcGIS 3D Analyst software. The TINs were checked to find any artifact or outlier. Any object over the ground was removed. TIN elevations were checked against check points to be sure they meet the accuracy requirements. After the accuracy verification 10 feet gridded DEMs were produced from TINs. DEMs are in industry-standard, GIS-compatilble, 32-bit floating point raster format as ERDAS.img. State Plane Coordinate System 1983</gridsysn> -<spcs> <spcszone>0403</spcszone> -<lambertc> <stdparll>37.066667</stdparll> <stdparll>38.433333</stdparll> <longcm>-120.500000</longcm> <latprjo>36.500000</latprjo> <feast>6561666.666667</feast> <fnorth>1640416.666667</ horizdn>North American Datum of 1983</horizdn> <ellips>Geodetic Reference System 80</ellips> <semiaxis>6378137.000000</semiaxis> <denflat>298.257222</denflat> </geodetic> </horizsys> -<vertdef> -<altsys> <altdatum>North American Vertical Datum of 1988</altdatum>


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<altres>0.5</altres> <altunits>feet</altunits> <altenc>Explicit elevation coordinate included with horizontal coordinates</altenc> </altsys>

Wordview-2 Data Processing Final WV-2 Product Description WorldView 2 imagery of portions of Monterey County, California were orthorectified, and projected to UTM Zone 10 North using the WGS-84 datum. There are a total of 28 images for the project; 14 multispectral and 14 panchromatic. Mosaics of both the panchromatic and multispectral datasets are the principal WV-2 products. The multispectral data were also atmospherically corrected to radiance and converted to reflectance. Additional post-processing was performed using custom computer code to maintain consistency between scenes. Orthorectification WorldView 2 data were collected of north and western Monterey County, CA the 15th of April 2011. The data were ordered in LV1B (Basic), radiometrically corrected and sensor corrected, but not projected to a plane using a map projection or datum.1 Because of this, the data needed to be orthorectified and projected. The orthorectification, as well as some of the pre-processing was done in Exelis ENVI 4.8 (32-bit version). ERDAS IMAGINE 2011 was used to convert the NAIP images used as a reference from JPEG 2 or MrSID, to ERDAS IMG or TIFF. Any data used for the orthorectification process, except for the WorldView 2 data, were acquired from the USDA website.2 This includes a 10 Meter NED, and a NAIP image. A USGS National Elevation Dataset (NED) 10 meter with elevations portrayed in decimeters for a 7.5x7.5 minute quadrangle was used as the terrain model for the orthorectification. The datasets are in GeoTIFF format. New datasets are being released into the NED 1/9-arc-second collection on a monthly basis and in conjunction with the bi-monthly updates when possible.3 The data come in UTM zone 10 North NAD 83. They were re-projected to be in UTM Zone 10 North WGS 84. A 2010 NAIP (National Agriculture Imagery Program) was used as a reference during the orthorectification. The format the data comes in is either JPEG 2 or MrSID. Working with either of these file types can be slow in ENVI. Therefore, the data were converted to a DAT file, TIFF, or ERDAS IMG. After the file conversion, the data were re-projected to be in UTM Zone 10 North WGS 84. Orthorectification was accomplished by using the ENVI Orthorectification Module, and selecting Orthorectify WorldView with Ground Control. Geographically linking the NAIP with the NED aided in finding corresponding ground control points (GCPs) in the WorldView 2 data. GCPs were chosen by using geographic information from the NED. After a sufficient number of GCPs were created, the output file, DEM, and coordinate system were selected. The finished orthorectified files are in UTM Zone 10 North WGS-84.

1DigitalGlobe Core Imagery Products Guide

2 http://datagateway.nrcs.usda.gov/GDGHome.aspx

3 http://ned.usgs.gov/Ned/faq.asp#UPDATED


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Atmospheric Correction Workflow Worldview-2 Data were atmospherically corrected using commercial software (FLAASH). The workflow is described below.

1. Project data (done in the orthorectification)

2. WorldView-2 Radiance

3. Convert data (BIL, BIP, BSP)

4. Re-size data (Get rid of 0- value pixels)

5. Reflectance Conversion (FLAASH)

Exelis ENVI 4.8 (32-bit version) with the module for Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) was used for atmospheric correction. FLAASH requires the data to be in a projected coordinate system. Because of the orthorectification, the data were already projected into UTM Zone 10 North WGS-84. Data were corrected to radiance using the ENVI Basic Tools, Calibration Utilities, WorldView Radiance, and selecting the associated IMD file. The data were converted to BIL. Data must also be in a floating-point, long integer (4-byte signed), or integer (2-byte signed or unsigned) data type, BIL or BIP, ENVI file. FLAASH input parameters included Image Center Location, Latitude and Longitude in D, M, S.ss (Most of this information can be found in the IMD file).

Image Acquisition Date yyyy, mm, dd and Time hh, mm, ss (UTC)

Average ground elevation (km)

Acquisition altitude (km)

Choose atmospheric model (U.S. Standard was used, with no Aerosol)

Zenith and Azimuth angles (Advanced Settings)

Azimuth: 360 – meanSatAz = a

180 – a = Azimuth

Zenith: 180 – meanOffNadirViewAngle = Zenith

Tile size set to 855(or highest setting without crashing) Post processing was done using custom computer code to remove negative reflectance values by estimating based on adjacent pixels and spectral signatures. WorldView 2 imagery into ArcGIS Software ESRI ArcGIS 10.0 Final product Calculate Statistics (ArcGIS feature), and pyramid files were created for each image, as well as the panchromatic mosaic.


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References

These are some of the publications so-far describing elements of the NPS/RSC earthquake

response remote sensing research efforts and products:

Clasen, C.C., Kruse, F.A., and Kim, A.M., 2012, Analysis of LiDAR Data for Emergency

Management and Disaster Response: in Imaging and Applied Optics Technical Digest, 24

June - 28 June 2012, Monterey, CA, USA, Optical Society of America (paper

RTu2E.2.pdfon CD-ROM).

Kim, A.M., Kruse, F.A., Olsen, R.C., and Clasen, C.C., 2012, Extraction of Rooftops from

LiDAR and Multispectral Imagery: in Imaging and Applied Optics Technical Digest, 24

June - 28 June 2012, Monterey, CA, USA, Optical Society of America (paper

RTu2E.1.pdf on CD-ROM).

Kruse, F.A., Clasen, C.C., Kim, A.M., and Carlisle, S.C., 2012, Use of Imaging Spectrometer

Data and Multispectral Imagery for Improved Earthquake Response: in Imaging and

Applied Optics Technical Digest, 24 June - 28 June 2012, Monterey, CA, USA, Optical

Society of America (paper RM2E.1.pdf on CD-ROM).

Kruse, F.A., Clasen, C.C., Kim, A.M., Runyon, S.C., Carlisle, S.C., Esterline, C.H., Trask, D.M.,

and Olsen, R.C., 2012, Tiered remote sensing and geographic information system (GIS)

based map products for improved earthquake response: in Proceedings 34th International

Geologic Congress (IGC), 5 -10 August, 2012, Brisbane Australia.

Kruse, F.A., Clasen, C.C., Kim, A.M., and Carlisle, S.C., 2012, Effects of spatial and spectral

resolution on remote sensing for disaster response: In proceedings, IEEE International

Geoscience and Remote Sensing Symposium (IGARSS2012), 22 - 27 July 2012, Munich,

Germany.

Naval Postgraduate School Remote Sensing Center (RSC), 2011, Workshop report: Remote

sensing techniques for improved earthquake warning, monitoring, and response, NPS,

January 25 – 27, 2011, 19 p. (available as PDF file).

Naval Postgraduate School Remote Sensing Center (RSC), 2012, After action report for

NPS/RSC Earthquake Response Exercise, NPS RELIEF, August 15-16, 2012 (available

as PDF file).

Documents

Monterey County Baseline Products and Pre Event Data …faculty.nps.edu/.../NPS-DHS_Playbook_RSC-02_Baseline_Products.pdfMonterey Baseline Products and Pre-Event Data Playbook # RSC-02