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United States, landcover, radiance or imagery, landuse, Maine, imageryBaseMapsEarthCover, land surface
Quantify land cover features boundaries at a 5 meter spatial resolution over the State of Maine.
MELCD is a land cover map for Maine primarily derived from Landsat Thematic Mapper 5 and 7 imagery, from the years 1999-2001. This imagery constitutes the basis for the National Land Cover Dataset (NLCD 2001) and the NOAA Coastal Change Analysis Program (C-CAP). This land cover map was refined to the State of Maine requirements using SPOT 5 panchromatic imagery from 2004. The Landsat imagery used was for three seasons: early spring (leaf-off), summer, and early fall (senescence) and was collected with a spatial resolution of 30 m. The SPOT 5 panchromatic imagery was collected at a spatial resolution of 5 m during the spring and summer months of 2004. The map was developed in two distinct stages, the first stage was the development of a state wide land cover data set consistent with the NOAAC-CAP land cover map. The second stage was: a) the update to 2004 conditions, b) a refinement of the classification system to Maine specific classes and, c) a refinement of the spatial boundaries to create a polygon map based on 5 m imagery.
Credit should always be given to the data source and/or originator when the data is transferred or printed.
Users must assume responsibility in determining the usability of this data for their purposes. Digital maps retain the accuracy of their source materials. The best use of data mapped at scales of 1:500,000 and 1:250,000 is in statewide planning and studies; at 1:100,000 in regional planning and studies; at 1:62,500 and 1:24,000 in detailed studies and local planning; and at 1:12,000 and 1:5,000 or larger scales in parcel level studies and detailed local planning. In the use of Maine GIS data, please check sources, scale, accuracy, currentness and other available information. Please confirm that you are using the correct copy of both data and metadata from the Maine GIS Data Catalog. Updates, corrections, and feedback, incorporated in the Maine GIS database are made in accordance with "Data Standards for Maine Geographic Information Systems", 2002, and coordinated by MEGIS
Extent
There is no extent for this item.
| Maximum (zoomed in) | 1:5,000 |
| Minimum (zoomed out) | 1:50,000 |
Monday through Friday
Image analysis techniques used in production of the map were a combination of supervised classification using Classification and Regression Tree (CART) algorithms and spatial modeling. The use of three Landsat image dates provided the ability to discriminate specific elements of the landscape. For example; the spring imagery was useful for the classification of wetlands and the separation of conifers and broadleaf species and the fall imagery was useful for the discrimination of broadleaf species. After the creation of the NOAA C-CAP base map, Sanborn used image segmentation to refine the spatial boundaries of the land cover classes, using a merge of the Landsat leaf on imagery and the SPOT 5 imagery. The segments produced by this process were labeled using automated methods to build the final Maine land cover dataset (MeLCD). After the completion of the classification, the map was extensively reviewed by Sanborn analysts and specific classes were modeled and edited by hand to remove class confusion.
Credit should always be given to the data source and/or originator when the data is transferred or printed.
ground condition
Sanborn Solutions - www.sanborn.com
Users must assume responsibility to determine the usability of this data for their purposes. Although these data have been processed successfully on a computer system at the Maine Office of Geographic Information Systems, no warranty expressed or implied is made by MEGIS regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty. Neither the Maine Office of Geographic Information Systems, nor any of its contributors, is liable for misuse of the data, for damage, for transmission of viruses, or for computer contamination through the distribution of these data sets.
Users must assume responsibility to determine the usability of this data for their purposes.
Users must assume responsibility in determining the usability of this data for their purposes. Digital maps retain the accuracy of their source materials. The best use of data mapped at scales of 1:500,000 and 1:250,000 is in statewide planning and studies; at 1:100,000 in regional planning and studies; at 1:62,500 and 1:24,000 in detailed studies and local planning; and at 1:12,000 and 1:5,000 or larger scales in parcel level studies and detailed local planning. In the use of Maine GIS data, please check sources, scale, accuracy, currentness and other available information. Please confirm that you are using the correct copy of both data and metadata from the Maine GIS Data Catalog. Updates, corrections, and feedback, incorporated in the Maine GIS database are made in accordance with "Data Standards for Maine Geographic Information Systems", 2002, and coordinated by MEGIS
Sanborn Solutions - www.sanborn.com
publication date
ground condition
ground condition
Monday through Friday
value attribute table
Environmental Systems Research Institute, Inc. (ESRI)
Classification
Sanborn Solutions - www.sanborn.com
MELCD is a land cover map for Maine primarily derived from Landsat Thematic Mapper 5 and 7 imagery, from the years 1999-2001. This imagery constitutes the basis for the National Land Cover Dataset (NLCD 2001) and the NOAA Coastal Change Analysis Program (C-CAP). This land cover map was refined to the State of Maine requirements using SPOT 5 panchromatic imagery from 2004. The Landsat imagery used was for three seasons: early spring (leaf-off), summer, and early fall (senescence) and was collected with a spatial resolution of 30 m. The SPOT 5 panchromatic imagery was collected at a spatial resolution of 5 m during the spring and summer months of 2004. The map was developed in two distinct stages, the first stage was the development of a state wide land cover data set consistent with the NOAAC-CAP land cover map. The second stage was: a) the update to 2004 conditions, b) a refinement of the classification system to Maine specific classes and, c) a refinement of the spatial boundaries to create a polygon map based on 5 m imagery.
Quantify land cover features boundaries at a 5 meter spatial resolution over the State of Maine.
Image analysis techniques used in production of the map were a combination of supervised classification using Classification and Regression Tree (CART) algorithms and spatial modeling. The use of three Landsat image dates provided the ability to discriminate specific elements of the landscape. For example; the spring imagery was useful for the classification of wetlands and the separation of conifers and broadleaf species and the fall imagery was useful for the discrimination of broadleaf species. After the creation of the NOAA C-CAP base map, Sanborn used image segmentation to refine the spatial boundaries of the land cover classes, using a merge of the Landsat leaf on imagery and the SPOT 5 imagery. The segments produced by this process were labeled using automated methods to build the final Maine land cover dataset (MeLCD). After the completion of the classification, the map was extensively reviewed by Sanborn analysts and specific classes were modeled and edited by hand to remove class confusion.
ground condition
none
Users must assume responsibility in determining the usability of this data for their purposes. Digital maps retain the accuracy of their source materials. The best use of data mapped at scales of 1:500,000 and 1:250,000 is in statewide planning and studies; at 1:100,000 in regional planning and studies; at 1:62,500 and 1:24,000 in detailed studies and local planning; and at 1:12,000 and 1:5,000 or larger scales in parcel level studies and detailed local planning. In the use of Maine GIS data, please check sources, scale, accuracy, currentness and other available information. Please confirm that you are using the correct copy of both data and metadata from the Maine GIS Data Catalog. Updates, corrections, and feedback, incorporated in the Maine GIS database are made in accordance with "Data Standards for Maine Geographic Information Systems", 2002, and coordinated by MEGIS
Sanborn Solutions - www.sanborn.com
Credit should always be given to the data source and/or originator when the data is transferred or printed.
The MeLCD accuracy database was assembled through a combination of photo interpretation and field verified ground visits. The final accuracy database consists of a total of 1617 points. Table below shows the break out of how the accuracy assessment database was compiled.
Point Type Number of Points
Sanborn Supplied Field Sites 315
State of Maine Supplied Field Sites 190
Sanborn Photointerpreted Sites 390
State of Maine Photointerpreted Sites 722
Photointerpreted Site Total 1112
Field Site Total 505
Accuracy Site Total 1617
Initially, approximately 1500 reference data sample points were selected at random in order to assist the State of Maine field crews in selecting field sites and destination planning. Field sites were visited by the State of Maine field crews in the late summer of 2005. Both photointerpreted and field sites were checked to ensure that each represented a homogenous feature on the SPOT imagery so that the points conformed to the MeLCD MMU requirements. The minimum mapping unit (MMU) used for the Accuracy Assessment refers to the requirement that an Accuracy Assessment point must fall in the center of a 0.89 acre area that consists of one and only one cover type. If these criteria are not met it will result in confusion/error caused by positional/spatial accuracy of the map rather than the thematic accuracy of the map.
Fuzzy interpretations were made and added to the database when warranted and agreed to by the State of Maine, i.e. when the interpretations from the DOQQs were ambiguous. 15% of the interpretations, or 237 out of 1617. If any of the fuzzy accuracy assessment calls matched the map, then that sample would be considered a positive match. This fuzzy accuracy assessment methodology is represented in the error matrices shown in this report.
Overall accuracy The use of fuzzy accuracy assessment methodologies are considered to be a necessary part of accuracy assessment or any sort of categorical interpretation (Congalton and Green, 1999). The MeLCD classification scheme was designed to be mutually exclusive. A given feature or area can be classified into one and only one class. Labeling of the ground features into one class can be difficult to make a positive determination from aerial photography and from the ground as well. Gopal and Woodcock (1994) state that "The assumption underlying fuzzy set theory is that the transition from membership to non-membership is seldom a step function". Therefore, a 100% Alder/Willow wetland can be easily labeled Shrub wetland and a 100% Cattail wetland can be called Emergent Wetland, a 49% shrub and 51% emergent wetland would be difficult to label definitively (Congalton and Green, 1999). In the Maine classification system, the same current status on the ground could have resulted from different causes, and as a result be classified differently. An example of this is the Heavy Cut class. An observer unaware of previous management could classify an area as shrub/scrub. That area could also be labeled as forest regeneration (based on a significant increase in canopy (1995 - 2001)) or heavy cut (based on significant decrease in canopy (1995-2001) unless the observer verified the previous conditions. Thus the need for a fuzzy accuracy assessment is pivotal to the true understanding of the accuracy of the map. (Congalton, R.G., Kass Green 1999. "Assessing the Accuracy of Remotely Sensed Data: Principles and Practices." CRC Press.;Gopal, S., Woodcock, C. 1994. Theory and methods for accuracy assessment of thematic maps using fuzzy sets. PERS. V60, N2, pp 181.)
The use of the error or confusion matrix, allows the user of the map to understand the individual map accuracies of each land cover class which are plainly described along with errors of omission (errors of exclusion) and commission (errors of inclusion) (Congalton and Green, 1999). Additionally, per class accuracies are stated as a User's and Producer's percentage. User's accuracy is defined as the proportion of pixels assigned to a class that are correctly classified. The producer's accuracy is the proportion of the land in each class was correctly identified. For example, the producer's accuracy of the Pasture/Hay is reported as 74.6% while its user's accuracy is reported as 66.7%. Meaning that although 3 times in 4 the map correctly identifies Pasture/Hay, only 2 times in 3 will the area on the map that is mapped as Pasture/Hay actually be Pasture/Hay on the ground. The other 1 out of 3 times it would probably be cultivated crops or grassland/herbaceous. (Congalton, R.G., Kass Green 1999. "Assessing the Accuracy of Remotely Sensed Data: Principles and Practices." CRC Press.)
It also must be noted that observations on the clear cut class (cut between 2001 - 2004) and forest regeneration class can not be made due to the lack of sufficient number of reference points to predict the class's accuracy with a reasonable degree of certainty. It is generally accepted that a minimum number of 30 points per class are needed to reliably predict the accuracy of any particular class. The low number of samples for these classes is due to either very few areas of that particular class exist, or that areas of the particular class were geographically clustered in a small area and not distributed over the state. While the accuracies for the above classes can not be predicted with certainty, their reference data are still reported as a factor in the maps overall accuracy.
MELCD is complete.
Horizontal accuracy is based on the accuracy of the underlying SPOT 5 data, which is < 15m error 95% of the time.
Horizontal accuracy is based on the accuracy of the underlying SPOT 5 data, which is < 15m error 95% of the time.
This land cover map was refined to the State of Maine requirements using NOAA Coastal Change Analysis Program (CCAP) SPOT 5 panchromatic imagery from 2004.
Fuzzy interpretations were made and added to the database when warranted and agreed to by the State of Maine, i.e. when the interpretations from the DOQQs were ambiguous.
The MELCD land cover map was primarily derived from Landsat Thematic Mapper 5 and 7 imagery, from the years 1999-2001.
MELCD is a land cover map for Maine primarily derived from Landsat Thematic Mapper 5 and 7 imagery, from the years 1999-2001. This imagery constitutes the basis for the National Land Cover Dataset (NLCD 2001) and the NOAA Coastal Change Analysis Program (C-CAP). This land cover map was refined to the State of Maine requirements using SPOT 5 panchromatic imagery from 2004. The Landsat imagery used was for three seasons: early spring (leaf-off), summer, and early fall (senescence) and was collected with a spatial resolution of 30 m. The SPOT 5 panchromatic imagery was collected at a spatial resolution of 5 m during the spring and summer months of 2004. The map was developed in two distinct stages, the first stage was the development of a state wide land cover data set consistent with the NOAAC-CAP land cover map. The second stage was: a) the update to 2004 conditions, b) a refinement of the classification system to Maine specific classes and, c) a refinement of the spatial boundaries to create a polygon map based on 5 m imagery.
Image analysis techniques used in production of the map were a combination of supervised classification using Classification and Regression Tree (CART) algorithms and spatial modeling. The use of three Landsat image dates provided the ability to discriminate specific elements of the landscape. For example; the spring imagery was useful for the classification of wetlands and the separation of conifers and broadleaf species and the fall imagery was useful for the discrimination of broadleaf species. After the creation of the NOAA C-CAP base map, Sanborn used image segmentation to refine the spatial boundaries of the land cover classes, using a merge of the Landsat leaf on imagery and the SPOT 5 imagery. The segments produced by this process were labeled using automated methods to build the final Maine land cover dataset (MeLCD). After the completion of the classification, the map was extensively reviewed by Sanborn analysts and specific classes were modeled and edited by hand to remove class confusion.
Sanborn Solutions - www.sanborn.com
MELCD is a raster whose pixel values represent the classification of areas into 23 classifications: developed high intensity; road/runway; developed medium intensity; developed low intensity; developed open space; cultivated land; blueberry field; pasture/hay; grassland/herbaceous; deciduous forest; evergreen forest; mixed forest; scrub-shrub; forested wetland; wetland; unconsolidated shore; bare land; open water; clear-cut; light partial cut (post 1995); heavy partial cut (post 1995); forest regeneration (post 1995); alpine/tundra.
Users must assume responsibility to determine the usability of this data for their purposes. Although these data have been processed successfully on a computer system at the Maine Office of Geographic Information Systems, no warranty expressed or implied is made by MEGIS regarding the utility of the data on any other system, nor shall the act of distribution constitute any such warranty. Neither the Maine Office of Geographic Information Systems, nor any of its contributors, is liable for misuse of the data, for damage, for transmission of viruses, or for computer contamination through the distribution of these data sets.
These data are available to Internet browsers for download from the Maine GIS Internet Data Catalog. Data available from this website is in .zip compressed format. WinZip is a Windows based, PKZip-compatible compression utility. You will need a program like this to extract the data. A link to a trial copy WinZip software is available at http://megis.maine.gov/software.asp.
Users must assume responsibility to determine the usability of this data for their purposes.
Please contact the Maine Office of GIS (MEGIS) for access instructions.
Sanborn Solutions - www.sanborn.com