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1st Amendment 04/15/2009 DANNY L. KOLHAGE CLERK OF THE CIRCUIT COURT DATE: May 1, 2009 TO: Andrew Trivette, Director Growth Management Division FROM: Mayra Tezanos x.P Executive Assistant r Isabel C. DeSantis, D.C. ~ ATTN: At the April 15, 2009, Board of County Commissioner's meeting the Board granted approval and authorized execution of the following: Interlocal Agreement between Monroe County and the City of Key Colony Beach providing funding assistance from Boating Improvement Funds for costs incurred for dock and seawall repairs at the 7th Street City Hall Annex Dock in the amount of$38,685.00. Interlocal Agreement between Monroe County and the City of Key West providing funding assistance from Boating Improvement Funds for costs incurred for maintenance at the Garrison Bight mooring field in the amount of$17,325.00. Am~mdment No. 1 to Contract between Monroe County and GMR Aerial Surveys to provide the development of a Geospatial Land Cover Dataset for the Florida Keys. Resolution No. 118-2009 for an exemption of 4, 113 square feet of non-residential floor area from the Non-Residential Rate of Growth Ordinance (NROGO) permit allocation system requested by the Craig Company, on behalf of the South Florida Council of the Boys Scouts of America, pursuant to Policy 101.3.4 of the Year 2010 Comprehensive Plan. The subject parcel is legally described as Westerly Part of Government Lot 2, Section 32, Township 66 South, Range 30 East, We:st Summerland Key, Monroe County, Florida, having real estate number 00106030.000000. Resolution No. 122-2009 amending the Planning and Environmental Resources fee schedule by changing the fee for a Beneficial Use Determination. Should you have any questions please do not hesitate to contact our office. cc: County Attorney Finance File AMENDMENT NUMBER ONE TO CONTRACT BETWEEN MONROE COUNTY AND GMR AERIAL SURVEYS, INC. THIS Af\~ENDMENT to the contract between Monroe County (County) and GMR Aerial Surveys, Inc. d/b/a PhotoScience (Contractor) dated December 17, 2008 is entered into on the I ~day of (iftU/ , 2009. WITNESSETH: WHEREAS, the County desires further refinement to the data from Contractor; and WHEREAS, Contractor desires to perform such work; ......, ;::t !=' g :2 :;:'~ i E . rT!:~ -< ,-, < · 6 1. The Scope of Work, Exhibit A, is amended as indicated. StrikethrouQt1s)iJtdicare ;0 deleted language and underlines indicate additions. :~3~~ ~ ~ :":. --0> Co.) C') . C) .. <::) ," .: rr1 ;:0 ... 0 NOW, THEREFORE, the parties agree as follows: 2. Exhibit B is amended as attached. 3. Compensation is increased by Six Thousand Dollars ($6,000.00) to be payable upon cOlmpletion of the contract, making the total payment One Hundred Six Thousand Dollars ($106,000.00). IN WITNESS WHEREOF, the parties have executed this Amendment Number One as indicated below. ATTEST: DANNYL.KOLHAGE,CLERK ~~Q.~ Deputy Clerk BOARD OF COUNTY COMMISSIONERS OF MONROE COUNTY ~~ L. 'tn......,.q-.. Mayor George Neugent :E;:~(~ GMR AERIAL SURVEYS ~ By:.... . ~ G.Michael Ritchie, President/CEO Q Go~T3~ Prin ~e ./1 ; A (2)~? ~ C l ~ i C;".~, tk Print Name Date: ~- /--0/ Amended Exhibit A to Contract with GMR Aerial Surveys, Inc. d/b/a Photo Science Scope of Work (April 15, 2009) Photo Science will provide Monroe County with professional mapping services using a well established methodology proven on similar projects within Florida and other similar projects throughout the United States. The delineation and classification of each land cover type will be performed by uniquely qualified photointerpreters who have strong backgrounds in natural resources and geography and who have an in-depth knowledge base of land use and land cover types specific to Florida natural systems, agricultural, as well as high density residential, commercial, and industrial areas. The SFWMD 2004-2005 FLUCCS dataset, along with the 1991 Advanced Identification (ADID) land cover feature class dataset referenced in the County's solicitation are ideal sources of collateral data that will be referenced throughout Photo Science's production work flow. During the photointerpretation process Photo Science will only reference the collateral data and not use any of the line work from these previous mapping efforts, (Le., ADID, FLUCCS). Rather, the 2008-09 mapping effort will be compiled using only original line work with the possible exception of shoreline data. Photo Science will apply the County's New Potential Land Cover Categories classification summarized below. 1 . Developed Land - Developed Lane is comprised of areas of intensive use with much of the land covered by structures. Examples are dwellinos, strip developments, industrial and commercial complexes, landfills, oolf courses and parks. All imperious surface areas below 0.5 acres will also be included within this cateoorv. 2. Undeveloped Land - This cateoorv includes open , scarified, or disturbed lands which tend to have uncertorn land uses and may contain native species. 3. Impervious Surface: This cateoorv includes all surfaces above 0.5 acres which do not allow or minimally allows" the penetration of water. Examples are buildino roofs, concrete and asphalt pavements/parkino lots and some fine orained soils such as clays. surf:lCO which does not :lllo~N, or minim311y 3110\'.(s, tho ponotr3tion of \~l3tor; includod 3E oX3mploc 3ro building roofs, norm31 concroto 3nd 3sph31t p3'.(Omonts, 3nd somo fino gr3inod soils, such 3S GIays. - 1 - ~. Hammock: This was used to designate most of the upland and upland hammock vegetation found throughout the Keys that is natural and generally undisturbed. 2. Pineland: an upland forest community with an open canopy dominated by the native slash pine composed of known species. 6. Exotic: Invasive exotic species include Melaleuca, Australian Pine, Brazilian Pepper, Leatherleaf and Sapodilla north of the seven mile bridge. L Scrub mangrove: Typically found in the lower Keys, coastal scrub mangrove of dwarf mangrove are dominated by known species. Plants are typically less than 5' tall. ~ Freshwater Wetland: wetland areas with either standing water or saturated sailor both where the water is fresh or brackish composed of known species. Some Freshwater Wetlands are isolated and therefore not subject to the MMU of 0.5 acres. Rather, photointerpreters will delineate them without regard to the MMU. ~. Saltmarsh 10. Buttonwood 11. Mangrove : a wetland plant association subject to tidal influence where the vegetation is dominated by Black, White or Red mangroves. 12. Beach Berm : all sandy shorelines or beach areas. ~. Water: All water bodies both fresh and tidal (saline) · Scarifiod Land: upland aroas that havo boen clo3rod for dovolopmont alroady dovelopod and or onco wore cloarod and havo boon loft untouched sinco that stage allowing natural and oxotic vogotation to ro vegetate. · Salt Marsh Buttonv/ood \^.'otland: Transitional are3S locatod botwoon tidal mangroves and hammocks dominatod by known spocios. · Boach Borm: a s:mdy shorolino 'J.'ith a mound or ridge of unconsolidatod sand that is immodiately landward of, and usually parallel to, tho shorelino and boach. The sand is calcaroous material that is tho romains of marino organisms such as corals, algao and molluscs. Tho borm may includo forostod, coastal ridgos and may bo colonizod by hammock vogetation. Photo Science shall capture land cover features at the minimum mappinq unit (MMU) of 0.5 acres with the exception of isolated wetlands and small hammock habitat. Isolated wetlands will be mapped at even smaller MMU's. Smaller hammock habitat will be captured at the MMU of .35 acres. Photo Science proposes a vector land cover data set be compiled from source imagery at the determined MMU. Format will be an ArcGIS Geodatabase. - 2 - Photo Science's work flow is summarized as follows: Note that Quality Assurance and Quality Control (QAlQC) procedures will be integrated through this work flow. · Kick-off meeting with the County · Collect and review collateral and source imagery · Set up computing environment · Data preparation · Photointerpretation (PI) · Field work · PI Update · GIS Processing · Metadata · Thematic Accuracy Assessment · Final Report · County Review · Project Close out Photo Science will provide the County with detailed progress reports on a monthly basis. All source materials received from the County will be controlled using a chain-of-custody documentation procedures which will track all source materials including the required referenced materials and optional referenced materials provided to the team by the County. Photo Science will produce a spatially, thematically and technically accurate ArcGIS 9.3 Land Cover geodatabase from the digital source imagery. The Land Cover dataset development will include documentation and metadata describing the methods and products. Photo Science will create a new land cover dataset that is correct in both classification and positional accuracy. Photo Science will create this dataset using uniquely qualified photointerpreters who have strong backgrounds in natural resources and geography and who have an in-depth knowledge base of Land Cover types specific to the Florida Keys natural systems, as well as high density residential and commercial areas. All of Photo Science's Photointerpreters assigned to this project will familiarize - 3 - themselves with spectral signatures associated with the project work areas to gain the necessary knowledge to establish the decision rule criteria necessary for accurate and consistent photoi nterpretation. All of Photo Science's photointerpretation will adhere to a minimum mapping unit that meets or 0.5 acres (except wetlands isolated which will be mapped if seen on the imagery regardless of the MMU) or other MMU defined by the County. Photointerpreters will delineate and classify Land Cover with the appropriate classification codes by utilizing the basic photo elements of shape, size, pattern, shadows, tone, texture, site, and color. These basic characteristics of photographic images provide distinct "clues" as to the proper classification of a mapping unit. Using collateral data, including input from the on-site field verification, our photointerpreters will be able to classify and delineate the Land Cover features throughout the project area. Photo Science's photointerpreters shall be able to distinguish between and among subtle spectral signatures. Most of the Land Cover features will be delineated and classified by Photo Science in a heads-up digital environment monoscopically. If, stereoscopic viewing is required Photo Science will do so using Socket Set soft copy photogrammetric workstations for on-screen stereo-viewing of 2006 pan- chromatic ADS40 imagery. Photo Science Photointerpreters will reference all appropriate collateral data along with input from County staff. This proposed approach follows standard aerial photography interpretation techniques that have been successfully used on similar inventories of large geographic areas. When using the 2006 ADS40 imagery, Photo Science photointerpreters will undoubtedly document discrepancies between the time of the source photography (2006) was taken and current (2009) ground truth field conditions. It is anticipated that many of these types of discrepancies between source imagery and ground truth will be associated with recent urban development on previously non- developed land. Although the source imagery typically takes priority on these types of situations, Photo Science photointerpreters will note the discrepancy and consult the County for advice. If during the photointerpretation and field verification effort Photo Science feels that modifiers to the classification system may apply, Photo Science shall make those recommendations to the County. Photo Science shall send samples of photointerpretation work to the County on a regular basis. Further, the County and Photo Science shall participate in a web conference at any time to view -4- progress and to discuss the application of the County's classification system to the land cover features extracted from the source imagery. During the photointerpretation phase, all unclassified polygons will be flagged by Photo Science for inspection in the field. Following a thorough review of all collateral data, the photointerpreters will select spectral signatures that represent various Land Cover codes that display "problem" or "low confidence" signatures. Photointerpreters will mark these features on the source photography for reference for a field site visit. Photo Science will also provide a narrative within the Final Report discussing probable reasons why a polygon may have been misclassified such as photo quality, signature variance, decisions rules, misinterpretations, mapping units or aggregation, etc. Field verification is a necessary component of a project of this scope and magnitude. Photo Science Photointerpreters must be able to accurately correlate spectral signatures from source imagery with actual Land Cover codes. Photo Science's photointerpreters will visit select sites in the field to accurately correlate the Land Cover codes with their respective unique spectral signatures. This local knowledge-base obtained from the field trip will assist the photointerpreters with updating both the classification and as needed the delineation of Land Cover data with a high degree of confidence not otherwise possible. Hard copy plots of imagery annotated with line work and Land Cover codes will be prepared for the photointerpreter to use in the field. A large sample site of the Land Cover codes updated will be visited in the field including all polygons flagged during the PI process. Additionally, Photo Science photointerpreters will visit a representative number of all other Land Cover codes. During the field preparation, the Photo Science will develop a plan that allows for the maximum number of codes to be visited. Photo Science maintains that the photointerpreters assigned to this project are the ones that must participate in the field work. The field work effort will not be delegated to anyone not directly involved in the photointerpretation process. Photo Science believes that the knowledge gained from the field is critical to insuring a high degree of classification accuracy. Photo Science shall provide field verification as a control measure for photointerpretation, classification of Land Cover types, and project documentation. Field verification will include visual assessment of selected Land Cover type. The photointerpreter will also collect a GPS point for each field site visited. A digital photo will be taken of each site at ground level and incorporated into the field data sheet and - 5 - the PI key. When photointerpreters return from the field they will incorporate all ground truth data collected and update the photointerpretation as needed. The Photo Science will utilize in-process, draft, and final review processes to assure a complete and accurate map product are compiled. Emphasis will be placed on creating effective mechanisms that will assure quality results in interpreted data content and supporting annotations. QC routines will be woven into the PI production. All work compiled, including all classification codes, will be reviewed upon completion of each image title before the Photointerpretation begins working on the next image title. The Project Manager as well as other Photo Science Photointerpreters will conduct "peer reviews" of each completed image title. To promote consistency and accuracy, the photointerpreter who did the original work will correct any and all edit calls associated with their own work. The emphasis of Photo Science's PI QC process will be to identify any critical defects, which could degrade the FLUCCS integrity of the LCLU map. These defects may include: . Improper selection of collateral data. . Incorrect feature interpretation and coding. . No feature consistency across project area. . Features not labeled clearly or completely. . Incorrect polygon annotations. . Missing polygons. . No adherence to minimum acreage size requirement. . Improper edgematch to adjoining maps. Photo Science's PI QA process will continually incorporate measures to assure the highest standard of accuracy. In order to provide unbiased and unencumbered quality assurance, Photo Science will organize all quality assurance functions to be separate from, and to operate independently of, the production team. This includes checking each delineated image title, inspecting it to assure that all land cover features are properly delineated and classified and are in compliance with a minimum mapping imit. - 6- Regular internal coordination meetings will be held between the Project Manager and the photointerpreters, the QA/QC Manager to discuss progress, findings, and any problems or anomalies encountered. Items typically discussed include characteristics of the imagery, collateral data, decision rules, and specific project objectives. The County is encouraged to participate in these meetings via conference call or web meeting or site visit. All Land Cover features compiled by Photo Science will be meet the following standards for logical consistency: · Polygon line work will not be generalized along sinuous features. Line work will properly characterize the shapes of boundaries appropriate to the resolution of the source imagery. · Minimum dimensions of mapped features will conform the Minimum Mapping Unit. · In the unlikely case that the source imagery does not edge match, Photo Science will notify the County for resolution · Identically coded polygons will not be adjacent to each other within a feature class · All features will exist wholly within the registration coverage title bounding arcs · There will be no duplicate features · Topology rules will be validated and corrected prior to delivery of each and any deliverable · All tolerances will be consistent across all deliverables. Photo Science will assure positional accuracy by checking that all coordinates are referenced, maintained and delivered in the State Plane Coordinate System, Florida East Zone, units survey feet, North American Datum (NAD) 1983/99 (NAD83/99). Projection information will be present in the metadata file and accessible through ArcCatalog Photo Science proposes that the thematic accuracy of the land cover dataset delivered to the County will have an overall minimum thematic classification accuracy of 90%. This overall classification accuracy will be calculated as a weighted average of all classes for each deliverable weighted by total area covered by each class. Photo Science proposes to confirm the thematic accuracy of the lands cover data set with a thematic accuracy assessment. The attribute table will contain their contract specified fields in the correct order and defined correctly. There will be no superfluous attributes or attribute fields in the final deliverable. All fields will be coded correctly and completely. There will be a value in every polygon for every attribute. - 7 - P.1. Decision Notes and General Notes will be filled out whenever deemed useful or appropriate by Photo Science's Photointerpreters and will be standardized in such a way that allows identical comments/issues to be identified. There will be a value in every polygon. Where no value applies the default will be "N./A". Attribute Codes: At a minimum, the following attributes will be associated with each digitized polygon: · LCCODE This attribute will be populated with a land cover value based on the County classification system. This field will be present in the final deliverable. · Modifier This attribute will be used to add additional detail to the classification, such as temporary conditions, minor features or management factors, that may be of particular interest to the County but do not warrant adding new classes to the Classification system. This will provide the County an opportunity to customize the classification without effecting overall consistency. This field will be present in the final deliverable. · Photointerpretation Code The photointerpreter responsible for the Land Cover determinations will be identified by this code value. This field will be present in the final deliverable. · PI Decision Notes This attribute will use standardized codes to record issues regarding the interpretation decision made for an individual polygon. This field will not be present in the final deliverable. · General Notes Decisions that record uncertainties or level of confidence will be recorded in this note field. Also, general rules for anecdotal data unrelated to the PI decision will be referenced here. This field will not be present in the final deliverable. · Field Check. Features identified for verification in the field are identified with this field. The Photo Science will develop QC protocols specific to this project that will ensure that all deliverables meet or exceed all accuracy standards established for this project under Monroe County's RFP. Photo Science's QC and editing process will continually incorporate measures to assure the highest standard of accuracy. Photo Science shall hold periodic coordination meetings between project management, photointerpreters, and related project support personnel to discuss progress, findings, and any problems or anomalies encountered. The County is encouraged to participate in any of these meetings via conference call, web meeting or site visit. - 8 - QC routines, developed by Photo Science will be used to review the digital data. In summary, Photo Science's automated and non-automated QC/QA routines will insure that the following standards for logical consistency apply: · Polygon topology is present and verified using the following rules : do not overlap and do not have gaps · Correct application of the MMU · No duplication of features · No sliver polygons will exist · No label errors will exist · No contiguous polygons Additionally, Photo Science's QA/QC process will insure all standards for positional accuracy apply to this mapping effort. This includes insuring that all coordinates are referenced to the State Plane Coordinate System, Florida East Zone, units survey feet, North American Datum (NAD) 1983-90 (HPGN). All projection information will be present in the metadata file and be accessible through ArcCatalog. Photo Science's process will insure that the attribute table contains their ArcGIS coverage default items and contract specified items in the correct order and defined correctly. There will be no superfluous attribute tables or attribute items in the final deliverable. All items will be coded correctly and completely. There will be a value in every polygon for every attribute. Where no value applies, we will use 9999. All .pat and .aat table definitions will be consistent across all deliverables. Photo Science shall produce a Photointerpretation (PI) Key for the County. The PI Key will be developed in order to document the decisions and mapping conventions applied during the photo interpretation process. It will describe and illustrate the classification system in detail. The PI Key will be used to assist the photo interpreters compile the land cover features and help to ensure that the photo interpretation is consistent throughout the project. It will be designed to provide descriptions of the visual and spatial distribution characteristics of the classification type used for the project and documents any special mapping conventions which may be developed. Its purpose is to define a common set of rules and standards that can be applied by many different interests to arrive at a consistent interpretation. Additionally, the PI Key will contain the general logic and details behind the decision rules for producing the Land Cover dataset. These details will be in the form of documentation that lists the appropriate Land Cover classes. - 9- Since the potential set of rules can be complex and endless, the County will be provided with a practical level of useful details conforming to the methodology and to the specific capabilities and needs of targeted users. The PI Key also serves to provide insight for future users into the rationale for the delineations and classifications appearing within the database. The PI Key will be in a digital format and will include the County's classification system. Users will be able to access the PI Key, point and click on a selected code to access the Photo interpretation Key file which describes the selected code. Aerial images will be clipped from the original imagery used for the photo interpretation. These image clips will be displayed on each key page. In addition, field pictures taken at ground level of each land cover code representing each classification type will also be included on each key page. Guidelines for each land cover code specific to this project will be specified in the PI Key. Each PI Key page will describe a unique land cover classification. The following sections will be included on each page of the key: 1. Classification Code: Indicates the land cover code as applied during photo interpretation. 2. Land Cover Description: This is the definition of the classification code exactly as it appears within County documents. 3. Keys to Photo interpretation: These will be descriptions which consist of the typical characteristics of each land cover code. Features which are associated with the class and which are visible on the imagery will be described. The apparent signature (colors, tones, textures, etc.) of the land cover code on the imagery will also be described. 4. Special Mapping Conventions: Describes the photo interpretation or mapping rules established to address the particular classification code. 5. Metadata: Documentation that describes the methods used to produce the PI Key including problems encountered, problem resolution, clarification in scope, etc. The metadata compiled will comply with Federal Geographic Data Committee (FGDC) STD-001-1998 Content Standards for Digital Metadata (version 2.0). 6. Anecdotal information including problems encountered and remedies deployed. To add clarification to the document, the approved PI Key may be modified with County approval during project implementation. It may also be necessary for land cover classes to be modified during mapping based on project working experience with the Land Cover classification system while maintaining - 10- consistency throughout the project area. All such changes will be submitted to the County for approval before processing. All mapped classes will be appropriately represented in the PI Key. The PI Key will be thoroughly tested to insure it is comprehensive and user friendly. Following internal testing of the PI Key, Photo Science will meet with County staff to demonstrate and deliver the PI Key as well as to demonstrate the working environment dedicated to this project. To insure the land cover dataset delivered to the County has a minimum classification accuracy of 90- percent for each Land Cover category at a confidence level of 90-percent, and that the overall accuracy of each section deliverable will have a minimum classification accuracy of 90-percent at a confidence interval of 90-percent, Photo Science proposes to conduct a thematic accuracy assessment as part of the QA procedure PRIOR to final delivery. Photo Science proposes to use a quantitative method (a statistical approach) described by Congalton and Mead (1983) to determine thematic accuracy of the final Monroe County Land Cover maps to be compiled. This method involves comparing the results of two separate and independent classifications of the same features. The first classification results from the initial 2008-09 Photo Science map compilation effort that used a combination of photointerpretation and field work techniques. The second classification results from the classification derived an independent photointerpretation conducted by HDR combined with direct field observations as needed. Similarities and/or differences between these two classifications (Photo Science and HDR) shall be displayed in an error matrix, (also referred to as a similarity matrix). The resultant error matrix will be used to measure the overall thematic accuracy of the first classification results. The following methodology shall be deployed: Step 1: Photo Science will use GIS tools to select a minimum of 20 polygons from each land cover codes from the classification that Photo compiled. This equates to over 200 polygons. Science Step 2: Photo Science shall drop all attributes associated with each of the selected, leaving only a polygon 10. polygons - 11 - Step 3: Photo Science subcontractor (HDR) shall conduct an independent classification using photointerpretation techniques of the selected polygons without referencing Photo Science's original classification. Signature identification may require field work. HDR classification results will be compared with Photo Science's classification. The following information shall be displayed when comparing these two datasets: · Total number of polygons for each classification, · Number of polygons which are correctly classified, · Number of polygons that are incorrectly classified. Photo Science shall perform a statistical analysis by running the Arc Intersect Command within ArcMap. This command allows the user to overlay the polygons from the original Photo Science classification and the second classification conducted by Photo Science's subcontractor (HDR). The resulting output will have the combined attributes of the features in the two inputs. From the analysis of the Arc Intersect generated layer, Photo Science shall compare the classifications from the two sources. The 'Notes' field within the Geodatabase shall be used by Photo Science to document comments for the sampled polygons as well as to identify where any errors are occurring outside of the sample polygon datasets. Photo Science shall then conduct a statistical analysis of the dataset. All generated polygons shall be combined to represent one batch sample. A statistical analysis shall then be performed solely on the batch sample containing all the sampled polygons. A similarity matrix (or error matrix) will be produced as a square array set out in rows and columns expressing the number of polygons assigned to a particular feature type relative to the independent classification. Once the error matrix is generated it will be analyzed using a discrete multivariate analysis technique using a program called KAPPA developed by Congalton et al (1982). The Kappa coefficient equation adjusts for polygons that may match purely by chance. The overall classification accuracy will then be calculated as a weighed average of all classes (weighed by total area covered by each class). The statistics used will be the maximum likelihood estimate from the multinomial distribution and shall be a measure of the actual agreement minus the chance agreement. The variance of these estimates will then be used to construct a hypothesis test for significant difference at varying confidence levels to determine if the two independent classifications are significantly different. The accuracy percentage - 12 - shall then be calculated for each mapping code by dividing the total number of matching polygons by the total number of sample polygons processed. Finally, Photo Science will provide the County with a Thematic Accuracy Report which compiles the results of the statistical analysis. Results will be summarized in a concise and organized form. The report will compare the data quality and discussed similarities and differences, providing conclusions about consistency and completeness. This report will also include suggestions as to what factors may have caused any observed differences and recommended possible remedies. Also included in this report will be a discussion on probable reasons why a polygon may have been misclassified such as photo quality, signature variance, decisions rules, misinterpretations, minimum mapping unit or aggregation, etc. The County shall be provided with the error matrix, a statistics review report based on the comparison of the two datasets and the KAPPA coefficient computation. The County will also be provided with a summary of systematically mismatched classes on a spreadsheet. Photo Science shall provide the County with high quality metadata that is compliant with the Federal Geographic Data Committee (FGDC) standards pursuant to Circular A-16 and Executive Order 12906. Photo Science will lead and organize all metadata creation and management activities for the Land Cover database development efforts. - 13 - Exhibit B (Revised March 19, 2009) to Contract with GMR Aerial Surveys, Inc. d/b/a Photo Science Project Schedule Task Date New Date Payment Assume Notice to Proceed: Dec. 12,2008 Photo Science Kick Off Meeting: Dec. 15,2008 Collect & Review Source Materials: Dec. 15,2008 Set Up Computer Environment: Dec. 15,2008 Monroe County / Photo Science Kick Off Meeting: Jan. 27,2009 Photointerpretation & ac & Draft PI Key: Jan. 28 - Mar. 31,2009 Upper Keys Deliverable - Preliminary Draft Map Products of Upper Keys available for County review: Mar. 06, 2009 March 11, 2009 Fieldwork, Post field photointerpretation & ac, GIS processing and ac Deliverable - Draft map product of Upper Keys available for County review: Mar. 16,2009 Lower Keys Deliverable - Preliminary draft Map product of Lower Keys available for County review: Apr. 17, 2009 May 1, 2009 Fieldwork, Post field photo interpretation & ac, GIS Processing & ac: Deliverable - Draft map product of Lower Keys available for County Review May 11, 2009 May 25,2009 Accuracy Assessment: May 11 - Jun 5, 2009 May 25-June 19, 2009 Revised draft map for County review: County Review: Jun 5, 2009 June 19,2009 County Review: Photo Science Edits, Metadata, Jun. 5 - July 5, 2009 June 19-July 20, 2009 Final Land Cover Dataset, Metadata, Final Report, Final PI Key, etc: Aug. 4,2009 $106,000.00 Deliverable Breakdown: Final Land Cover Dataset with Metadata Accuracy Assessment: Photointerpretation Key: $ 91,000.00 $ 10,000.00 $ 5,000.00 $106,000.00 Total: Note: Photo Science will provide the County with monthly progress reports and, if requested, preliminary draft map products on a monthly basis.