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Short Citation:
Alaska Regional Office, 2024: Catch-In-Areas Main, https://www.fisheries.noaa.gov/inport/item/27363.

Item Identification

Title: Catch-In-Areas Main
Short Name: Catch-In-Areas
Status: Completed
Publication Date: 2015-09-02
Abstract:

The Catch-In-Areas database integrates catch data from the Catch Accounting System (which has the spatial resolution of a NMFS Reporting Area) into a database that resolves the GIS data into polygons of approximately 7.5 km. In unrestricted outside waters, sixty four grid IDs fit inside one state statistical area. A state statistical area is = degree in latitude and one degree in longitude block. The 7.5 km grid size was picked for two reasons 1) we were likely to pick up at least one 30 minute VMS ping for a vessel running at fishing speed; and 2) the size (.125 degree latitude) is perfectly divisible in geographic coordinates so they fit perfectly inside a state statistical area. The grid polygons are often further divided into smaller polygons by the boundary of state statistical areas, the boundary of state and federal waters, or by the boundary of Steller sea lion critical habitat (broken out at 3, 6, 10, and 20 nautical miles from each of the 154 Steller sea lion rookeries and haulouts). Where confidentiality and mapping is an issue, seven-kilometer polygon are pre-coded for grouping into (3x3) 23km polygons. Each grid-id can queried individually or by sets of pre-coded attributes, such as reporting area and distance from Steller sea lion sites.

Purpose:

The Catch-In-Areas database integrates catch data from the Catch Accounting System (which has the spatial resolution of a NMFS Reporting Area) into a database that resolves the GIS data into polygons of approximately 7.8 km. The spatial resolution is added to Catch Accounting using a combination of Observer and VMS data, where for observed vessels observer data is joined with VMS data; for unobserved vessels, VMS data is used to find fishing locations based on time periods and reported state statistical areas.

Notes:

Loaded by FGDC Metadata Uploader, batch 7101, 09-22-2015 18:52

The following FGDC sections are not currently supported in InPort, but were preserved and will be included in the FGDC export:

- Spatial Reference Information (FGDC:spref),

- Spatial Data Organization Information (FGDC:spdoinfo)

Other Citation Details:

Steve Lewis

Supplemental Information:

Observed Fleet

We begin by separating VMS records as observed catch or unobserved. A record is considered observed when the federal observer logs the deploy time and retrieve time of a haul. The VMS records are processed when the vessel-id and date-time are within the observed times. A series of Speed algorithms clean the data of Observer or VMS outlier records. Speed is computed after each cleaning subset using several algorithms, simplified below.

When the speed is greater than 8.5knots, the VMS or Observer records are removed as long as there are greater than 2 records

When there is more than one VMS transponder associated with an observed haul, we only keep the VMS transponder that is closest to the observed retrieve location.

Most VMS data is removed from Hook-and-Line and Pot Observed records since the gear is dropped and retrieved while the vessels loiters or deploys other sets of gear.

When only a single observed record is available by haul, we add .002 to the Latitude and Longitude of the observed retrieve location in order to have enough points to build a line.

When a VMS or Observed point is greater than 120km from the observed deploy or retrieve point, the record is deleted.

The observed-VMS lines are built in ArcMap, grouped by the Catch Accounting Reference Key and sorted by the date-time from the Observed and VMS records. These lines can be simple, straight or very complex that run back and forth several times between the relevant VMS and observer points. All segments of the lines are used in the proportional calculations that follow.

After the lines are created, they are moved back to SQL Server and intersected onto the Grid Area GIS feature class. This spatial intersect operations splits each line into parts that are referenced by the grid IDs. The Catch-In-Area database attributes catch based on the effort a vessel spends fishing. In order to apply the effort, we divide the line length [by grid id] by the total line length. This gives us the proportion of the line falling into each grid id. In affect the Catch-In-Areas is an effort based product.

For catcher processors the catch is assigned by individual haul from the Catch Accounting System to each based on the length of the line.

For catcher vessels, the catch is split by individual haul into grid-IDs but then aggregated to the catcher vessels reported trip. A related algorithm applies the catch of the Observed haul to the trip. This is due to Catch Accounting assigning catch by a catcher vessel's trip rather than by individual haul.

Unobserved Fleet

A portion of the fishing fleet is unobserved because they are too small, are within a gray area of being a partially observed, or simply do not require a federal observer. Many of these vessels only report the state statistical area where they fished and time period (in days) when they were fishing. Almost all of these vessels are required to carry VMS though. Instead of attempting to build a line based on unobserved VMS data where data may be sparse and spread-out, we instead depend on the VMS-points intersected onto the grid-id feature class.

The criteria the Catch-In-Areas database uses to find a vessel that is fishing instead of cruising or being idle include 1) A vessel must be operating between .9 knots and 4.1 knots; 2) a vessel must not be in an area known not to be a fishing area, e.g., very near ports; 3) a vessel must be operating inside at least one of the state statistical areas reported on its fish ticket; and 4) the date-time of the VMS point must be within the date range on the fish ticket.

We use the vessels reported latitude and longitude to determine vessel speed. This calculation is based off the standard formula:

Radius_of_the_Earth*((2*ASIN(SQRT((SIN((RADIANS(LAT1)-RADIANS(LAT2))/2)2)+COS(RADIANS(LAT1))*COS(RADIANS(LAT2))*(SIN((RADIANS(LONG1)-RADIANS(LONG2))/2)2))))) Geoid 6371.1

A catch record in this process is weight

Keywords

Theme Keywords

Thesaurus Keyword
ISO 19115 Topic Category
elevation
ISO 19115 Topic Category
environment
ISO 19115 Topic Category
inlandWaters
ISO 19115 Topic Category
oceans
UNCONTROLLED
None Alaska Fisheries
None catch accounting
None catch data
None Catch-In-Areas
None CIA
None GIS
None polygon
None spatial

Physical Location

Organization: Alaska Regional Office
City: Juneau
State/Province: AK
Country: USA
Location Description:

SQL Server Database

Data Set Information

Data Set Scope Code: Data Set
Data Set Type: Database
Maintenance Frequency: Daily
Data Presentation Form: Document (digital)
Entity Attribute Overview:

Attribution included

Distribution Liability:

Confidential Fisheries Data

Data Set Credit: Steve Lewis, NOAA Fisheries, Alaska Region

Support Roles

Data Steward

CC ID: 235048
Date Effective From: 2024
Date Effective To:
Contact (Person): Jahn, Abby
Address: 709 West 9th Street
Juneau, AK 99801
USA
Email Address: abby.jahn@noaa.gov
Contact Instructions:

email: abby.jahn@noaa.gov

Distributor

CC ID: 267884
Date Effective From: 2015-12-24
Date Effective To:
Contact (Person): Lewis, Steve
Address: P.O. Box 21668
Juneau, AK 99801
USA
Email Address: steve.lewis@noaa.gov
Phone: 907-586-7858
Fax: 907-586-7255
Contact Instructions:

email

Metadata Contact

CC ID: 267882
Date Effective From: 2024-01-01
Date Effective To:
Contact (Person): Jahn, Abby
Address: 709 West 9th Street
Juneau, AK 99801
USA
Email Address: abby.jahn@noaa.gov
Contact Instructions:

email

Point of Contact

CC ID: 235050
Date Effective From: 2024
Date Effective To:
Contact (Person): Jahn, Abby
Address: 709 West 9th Street
Juneau, AK 99801
USA
Email Address: abby.jahn@noaa.gov
Contact Instructions:

email

Publisher

CC ID: 235053
Date Effective From: 2010
Date Effective To:
Contact (Organization): Alaska Regional Office (AKRO)
Address: 709 W. 9th St, P.O. Box 21668
Juneau, AK 99802-1668
USA
Phone: (907)586-7202
URL: http://alaskafisheries.noaa.gov/
Business Hours: 8:00 am - 4:30 pm, Mon-Fri.
Contact Instructions:

contact

Extents

Currentness Reference: none

Extent Group 1

Extent Group 1 / Geographic Area 1

CC ID: 223695
W° Bound: -180
E° Bound: -129
N° Bound: 69
S° Bound: 47

Extent Group 1 / Time Frame 1

CC ID: 223779
Time Frame Type: Continuing
Start: 2003
Description:

Dataset

Access Information

Security Class: Sensitive
Security Classification System:

Confidential

Data Access Policy:

Data is confidential and requires a confidentiality form.

Data Access Procedure:

contact abby.jahn@noaa.gov

Data Access Constraints:

None

Data Use Constraints:

None

Metadata Access Constraints:

.

Metadata Use Constraints:

.

Distribution Information

Distribution 1

CC ID: 223781
Download URL: http://alaskafisheries.noaa.gov/maps/
Distributor:
File Name: RES_Services_CIA
Description:

Splash page to mapping applications

File Type (Deprecated): ESRI REST
Distribution Format: ESRI REST Service
File Size: 22.1

Technical Environment

Description:

Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.3.1.4959

Data Quality

Representativeness:

Catch-In-Areas database matching algorithms match 99.976% of the Catch Accounting to spatial data.

Accuracy:

Data has embedded 'metadata' called the Match-Source column, that identifies each row in the database to a specific matching method.

Checksum and Go-NoGo tables are created in order for analytical products to be built.

Analytical Accuracy:

Data has embedded 'metadata' called the Match-Source column, that identifies each row in the database to a specific matching method.

Checksum and Go-NoGo tables are created in order for analytical products to be built.

Quantitation Limits:

Approximately 96% of the catch is matched directly and 4% of the catch is matched using very specific extrapolations.

Bias:

VMS units depend on satellites and while the vessel's transponders should buffer the signal until it has captured a satellite, it does not always work that way. Therefore we only match only 96% of the catch.

There other other issues with data including date mis-compares.

Comparability:

VMS-Obs-UnObs database; another part of the Catch-In-Areas.

Completeness Measure:

Tuning of database and adjusting for new types of data.

Precision:

7.8 kilometers.

Analytical Precision:

7.8 kilometers.

Field Precision:

variable

Sensitivity:

VMS

Completeness Report:

See Checksums

Conceptual Consistency:

See Checksums

Quality Control Procedures Employed:

Checksums, match-source, enterprise DBMS standards

Data Management

Have Resources for Management of these Data Been Identified?: Yes
Approximate Percentage of Budget for these Data Devoted to Data Management: 1
Do these Data Comply with the Data Access Directive?: Yes
Is Access to the Data Limited Based on an Approved Waiver?: No
If Distributor (Data Hosting Service) is Needed, Please Indicate: No
Approximate Delay Between Data Collection and Dissemination: 1 week
If Delay is Longer than Latency of Automated Processing, Indicate Under What Authority Data Access is Delayed:

Data has to be recompiled into a non-confidential dataset and moved to the public access location

Actual or Planned Long-Term Data Archive Location: Other
If World Data Center or Other, Specify: NA
Approximate Delay Between Data Collection and Archiving: 10 years
How Will the Data Be Protected from Accidental or Malicious Modification or Deletion Prior to Receipt by the Archive?:

Data is backed up in both DBMS and FileGeoDatabase format.

Lineage

Lineage Statement:

Observed Fleet

We begin by separating VMS records as observed catch or unobserved. A record is considered observed when the federal observer logs the deploy time and retrieve time of a haul. The VMS records are processed when the vessel-id and date-time are within the observed times.

Unobserved Fleet

A portion of the fishing fleet is unobserved because they are too small, are within a gray area of being a partially observed, or simply do not require a federal observer. Many of these vessels only report the state statistical area where they fished and time period (in days) when they were fishing. Almost all of these vessels are required to carry VMS though. Instead of attempting to build a line based on unobserved VMS data where data may be sparse and spread-out, we instead depend on the VMS-points intersected onto the grid-id feature class.

After the lines are created, they are moved back to SQL Server and intersected onto the Grid Area GIS feature class. This spatial intersect operations splits each line into parts that are referenced by the grid IDs. The Catch-In-Area database attributes catch based on the effort a vessel spends fishing. In order to apply the effort, we divide the line length [by grid id] by the total line length. This gives us the proportion of the line falling into each grid id. In affect the Catch-In-Areas is an effort based product.

Data is spatially intersected onto Grid and then joined to V_CAS_Primary_All using a precise matching algorithm.

The final table includes data from five tables

[V_CAS_TXN_PRIMARY_ALL]

.V_ELPR_VWPR_PRODUCT

.V_ELLR_SLOG_PRODUCT

.V_OBS_HAUL

.V_VMS_VESSEL_LOCATION

.V_OBS_HAUL_SPECIES_ALL]

Catalog Details

Catalog Item ID: 27363
GUID: gov.noaa.nmfs.inport:27363
Metadata Record Created By: Steve Lewis
Metadata Record Created: 2015-09-22 18:51+0000
Metadata Record Last Modified By: Abby Jahn
Metadata Record Last Modified: 2024-06-11 16:54+0000
Metadata Record Published: 2018-07-27
Owner Org: AKRO
Metadata Publication Status: Published Externally
Do Not Publish?: N
Metadata Last Review Date: 2018-07-27
Metadata Review Frequency: 1 Year
Metadata Next Review Date: 2019-07-27