gov.noaa.nmfs.inport:48347
eng
UTF8
dataset
Office for Coastal Management
resourceProvider
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
pointOfContact
2024-02-29T00:00:00
ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data
ISO 19115-2:2009(E)
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C-CAP Lanai, Hawaii 2005-2011 Land Cover Change Analysis
hi_lanai_2005_2011_hr_lc_20141204
2013-07-24
publication
NOAA/NMFS/EDM
48347
https://www.fisheries.noaa.gov/inport/item/48347
WWW:LINK-1.0-http--link
Full Metadata Record
View the complete metadata record on InPort for more information about this dataset.
information
https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires/
WWW:LINK-1.0-http--link
Citation URL
Online Resource
download
https://coast.noaa.gov/dataregistry
WWW:LINK-1.0-http--link
Citation URL
Online Resource
download
mapDigital
This data set contains the 2005 and 2011 classifications of Lanai and can be used to analyze change. This data set utilized utilized 14 full or partial WorldView2 multispectral scenes and the 2005 high-resolution Lanai C-CAP data set, which were analyzed according to the Coastal Change Analysis Program (C-CAP) protocol to determine land cover.
To improve the understanding of coastal uplands and
wetlands, and their linkages with the distribution,
abundance, and health of living marine resources.
completed
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
pointOfContact
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
custodian
5 years
EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER
EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER > LAND USE/LAND COVER CLASSIFICATION
theme
Global Change Master Directory (GCMD) Science Keywords
17.0
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > HAWAII
OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > HAWAIIAN ISLANDS > LANAI
place
Global Change Master Directory (GCMD) Location Keywords
17.0
CAMERAS
instrument
Global Change Master Directory (GCMD) Instrument Keywords
17.2
Airplane > Airplane
WORLDVIEW-2 > DigitalGlobe WORLDVIEW-2
WORLDVIEW-3 > DigitalGlobe WORLDVIEW-3
platform
Global Change Master Directory (GCMD) Platform Keywords
17.2
Change Detection Analysis
Land Cover Analysis
Remotely Sensed Imagery/Photos
theme
Coastal Zone
Lanai
place
DOC/NOAA/NOS/OCM > Office of Coastal Management, National Ocean Service, NOAA, U.S. Department of Commerce
dataCentre
Global Change Master Directory (GCMD) Data Center Keywords
2017-04-24
publication
8.5
C-CAP
project
InPort
otherRestrictions
Cite As: Office for Coastal Management, [Date of Access]: C-CAP Lanai, Hawaii 2005-2011 Land Cover Change Analysis [Data Date Range], https://www.fisheries.noaa.gov/inport/item/48347.
NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose.
otherRestrictions
Access Constraints: None
otherRestrictions
Use Constraints: Data set is not for use in litigation. While efforts have been
made to ensure that these data are accurate and reliable within
the state of the art, NOAA, cannot assume liability for any
damages, or misrepresentations, caused by any inaccuracies in the
data, or as a result of the data to be used on a particular
system. NOAA makes no warranty, expressed or implied, nor does
the fact of distribution constitute such a warranty.
otherRestrictions
Distribution Liability: Users must assume responsibility to determine the usability of these data.
unclassified
NOAA Data Management Plan (DMP)
NOAA/NMFS/EDM
48347
https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ocm/dmp/pdf/48347.pdf
WWW:LINK-1.0-http--link
NOAA Data Management Plan (DMP)
NOAA Data Management Plan for this record on InPort.
information
crossReference
grid
eng; US
imageryBaseMapsEarthCover
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; ESRI ArcGIS 10.1 SP 1
-157.040164
-156.475634
20.433185
20.560455
| Currentness: Acquisition dates of the source Quickbird and WorldView2 Scenes
2005-02-20
2011-01-22
false
eng
false
Layer_1
2017-11-16
publication
NOAA Office for Coastal Management
(843) 740-1202
2234 South Hobson Ave
Charleston
SC
29405-2413
coastal.info@noaa.gov
https://coast.noaa.gov
WWW:LINK-1.0-http--link
NOAA Office for Coastal Management Website
NOAA Office for Coastal Management Home Page
information
distributor
https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires/
WWW:LINK-1.0-http--link
https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires/
Online Resource
download
https://coast.noaa.gov/dataregistry
WWW:LINK-1.0-http--link
https://coast.noaa.gov/dataregistry
Online Resource
download
dataset
Accuracy
Attribute_Accuracy_Report
Horizontal Positional Accuracy
12 meters CE90
Vertical Positional Accuracy
There was no terrain correction in the geo-referencing
procedure.
Completeness Report
Data does not exist for all classes.
Many classes of from-to change never occurred in Lanai.
Conceptual Consistency
Tests for logical consistency indicate that all row and column
positions in the selected latitude/longitude window contain data.
Conversion and integration with vector files indicates that all
positions are consistent with earth coordinates covering the same
area. Attribute files are logically consistent.
Process_Description
This dataset, and the 2011-era classification was created by Photo Science. The 2005-era C-CAP classification was created by Sanborn.
This dataset contains the classifications of 2005 imagery and 2011 imagery. It is used for change analysis between these years. The
attributes include a from-to change description category. There are
521 classes corresponding to the 521 possible from-to change combinations.
In this section of the metadata, the 2005 classification
procedure is described, then the 2011 change detection classification procedure is
described. Finally in the post-processing section, the process of combining
the maps to generate a spatial matrix of change is discussed.
Early Date (2005) Classification: This section outlines the classification procedure for the Lanai High Resolution C-CAP. Quickbird imagery used in producing this land cover product was also utilized in producing an associated impervious surfaces layer for the island. The mapping approach utilized a boundary summary and refinement procedure developed by Sanborn to leverage previous moderate resolution C-CAP mapping efforts to create the high resolution land cover data set. A calibration visit was conducted and training data was collected for classification. Non impervious features were mapped using a 0.5 acre minimum mapping unit (MMU).
Pre-processing steps:
The Quickbird mosaic utilized for this project was provided from Digital Globe as an orthorectifed, georeferenced product and was consistent with the quoted 1:12000 spatial accuracy. In conjunction with the Quickbird mosaic, Sanborn used an ancillary Quickbird mosaic, as well as a DTM created from a 5m radar collect for the island. The original return image from the radar was also utilized.
Field-Collected Data:
Training data was collected between January 24, 2009 and January 28, 2009. Land cover observations were recorded by analysts. The referenced dataset went through a QA/QC procedure to ensure it met accuracy standards.
Classification:
Initial Segmentation - Image segmentation was completed at multiple scales using the multispectral (2.4 m) imagery in order to group like spectral and textural objects within the imagery. The initial segments were created at a larger scale (scale refers to the target size and shape of like features generalized by Definens software) of 100. Larger segments are required to leverage the 30 m data sets and incorporate the IFSAR data that is collected at spatial resolution of 5 m. For consistency, the associated impervious data set was incorporated into the segmentation layer as a boundary delimiter. Segments can share boundaries of an impervious surface, but can never overlap an impervious surface.
2013-05-01T00:00:00
Rule set Creation - The initial map of the island of Lanai is created by incorporating an existing C-CAP 2001 land cover data set through a logical rule set created by a Sanborn analyst. The rules are created such that image segments are labeled to the C-CAP classification scheme based on their underlying medium resolution components.
Initial Label and Edits - The automated labeling procedure created a reasonable representation of land cover using the labeling routine, however errors did occur. Gross inaccuracies in the data product that would inhibit the further classification of the segments at a smaller scale factor were corrected through knowledge based models or manual edits.
Secondary Segmentation - Further refinement of the map is only possible though classification of the image segments directly. Classification of the image segments is a hierarchical process, whereby larger scale segments are composed of smaller scale segments. The initial segmentation was used to further aid in the automated classification of the secondary (more detailed) image segments. The final scale factor for the mosaic was 35.
Automated Classification - Automated classification of the image segments is accomplished through a process modeling incorporated within Definiens software. Models are built to refine or reclassify land cover areas by utilizing the wealth of attribute information linked to each segment within Definiens. In a small amount of cases, the nearest neighbor classification routine was used to refine segments. Nearest neighbor training data is collected through analyst interpretation or ancillary data sets and used to calibrate the classification algorithm.
Automated Classification Edits - As with any automated or semi-automated land cover classification there are often inconsistencies in the land cover map. The final step before map finalization was to remove inaccuracies through manual segment labeling as interpreted by an analyst.
Map Finalization - Sanborn used independent reviewer's comments to further refine the land cover map.
Attributes for this product are as follows:
0 Background
1 Unclassified
2 Impervious
3
4
5 Developed, Open Space
6 Cultivated Crops
7 Pasture/Hay
8 Grassland/Herbaceous
9 Deciduous Forest
10 Evergreen Forest
11 Mixed Forest
12 Scrub/Shrub
13 Palustrine Forested Wetland
14 Palustrine Scrub/Shrub Wetland
15 Palustrine Emergent Wetland
16 Estuarine Forested Wetland
17 Estuarine Scrub/Shrub Wetland
18 Estuarine Emergent Wetland
19 Unconsolidated Shore
20 Bare Land
21 Open Water
22 Palustrine Aquatic Bed
23 Estuarine Aquatic Bed
24 Tundra
25 Snow/Ice
Late Date (2011) Classification:
This section outlines the classification procedure for the Lanai High Resolution C-CAP. WorldView2 imagery used in producing this land cover product was also utilized in producing an associated impervious surfaces layer for the island. The mapping approach utilized a boundary summary, outlier change detection process and refinement procedure developed by Photo Science to leverage the 2005 high resolution C-CAP data set to create the 2011 high resolution C-CAP. A calibration visit was not conducted though NOAA had access to local resources for validation. Non impervious features were mapped using a 0.25 acre minimum mapping unit (MMU) and impervious features were mapped using a 0.1 acre MMU.
2013-05-01T00:00:00
Pre-processing steps:
The WorldView2 mosaic utilized for this project was provided from Digital Globe as an orthorectified, georeferenced product. Multiple image primitives and indicies such as texture and NDVI were derived from the 8-band satellite data. The imagery was re-sampled from it's native 2m spatial resolution to 2.4m. The 2005 C-CAP classification and the base Quickbird imagery (used in the original mapping) were geometrically corrected to co-register to the WorldView2 data which has a higher geolocation accuracy.
Impervious Update:
The 2005 impervious was over-laid with semi-transparency on the 2011 satellite data. It was panned at a scale of 1:3,500 and manually updated to match the 2011 data. Analysts zoomed in to a larger scale when necessary to perform edits. The product went through a QC procedure to ensure features were accurately captured.
Segmentation and Outlier Detection Process:
The 2011 impervious was combined with the 2005 land cover to create a hybrid data set. Image segmentation, done in Trimble's eCognition software, was completed at multiple scales using the multispectral (2.4 m) imagery in order to group like spectral and textural objects within the imagery. For consistency, the associated hybrid data set was incorporated into the segmentation layer as a boundary delimiter. Segments contained image attributes and a label from the 2005 classification. These data were inputs to a custom multi-variate outlier detection tool that identified objects of potential change. These areas created the change mask.
Training Site Data:
Training data was photo interpreted and collected within the change mask and was super-sampled from features outside of the mask. The referenced data set went through a QA/QC procedure to ensure it met accuracy standards.
Classification:
Automated Classification - Image segments were classified using a decision tree classifier in Rulequest's See5 software based on the training data and image attributes.
Automated Classification Refinement - Models are built to refine or reclassify land cover areas by utilizing the wealth of attribute information linked to each segment within eCognition.
Classification Edits - As with any automated or semi-automated land cover classification there are often inconsistencies in the land cover map. The final step before map finalization was to remove inaccuracies through manual segment labeling as interpreted by an analyst.
Map Finalization - Photo Science used independent reviewer's comments to further refine the land cover map.
Attributes for this product are as follows:
0 Background
1 Unclassified
2 Impervious
3
4
5 Developed, Open Space
6 Cultivated Crops
7 Pasture/Hay
8 Grassland/Herbaceous
9 Deciduous Forest
10 Evergreen Forest
11 Mixed Forest
12 Scrub/Shrub
13 Palustrine Forested Wetland
14 Palustrine Scrub/Shrub Wetland
15 Palustrine Emergent Wetland
16 Estuarine Forested Wetland
17 Estuarine Scrub/Shrub Wetland
18 Estuarine Emergent Wetland
19 Unconsolidated Shore
20 Bare Land
21 Open Water
22 Palustrine Acquatic Bed
Post-Processing Steps:
A GIS matrix algorithm was run with 2005 and 2011 datasets as inputs. The algorithm generates
a from-to file where each combination is uniquely labeled from 1 to 625.
2013-05-01T00:00:00
Metadata imported
2013-07-24T00:00:00
Source Contribution: NOAA OCM | Source Geospatial Form: remote-sensing image | Type of Source Media: CD-ROM
C-CAP Lanai, Hawaii 2005-2011 Land Cover Change Analysis
2013-07-24
publication
Photo Science. www.photoscience.com
https://coast.noaa.gov/dataviewer/#/imagery/search/where:ID=4734
WWW:LINK-1.0-http--link
Source Citation URL
Source Citation URL
information
2005-02-20
2011-01-22