NOTE -- The georeferenced TIFF image named "CDL_2015_clip.tif" that was created by the USDA is identical to the georeferenced TIFF image named "CROPS_2015_USDA_IN.TIF" that is distributed by the Indiana Geological and Water Survey (IGWS). Only the filename and metadata have been modified to conform to IGWS conventions.
"The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2015 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season.
"Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED) and the imperviousness and canopy data layers from the USGS National Land Cover Database 2011 (NLCD 2011).
"Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The most current version of the NLCD is used as non-agricultural training and validation data. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL.
"The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer."
"The purpose of the Cropland Data Layer Program is to use satellite imagery to (1) provide acreage estimates to the Agricultural Statistics Board for the state's major commodities and (2) produce digital, crop-specific, categorized geo-referenced output products."
"Please visit the following website to view the original metadata file - <https://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php>.
"NOTE: The final extent of the CDL is clipped to the state boundary even though the raw input data may encompass a larger area."
"The USDA, NASS Cropland Data Layer is provided to the public as is and is considered public domain and free to redistribute. The USDA, NASS does not warrant any conclusions drawn from these data. If the user does not have software capable of viewing GEOTIF (.tif) file formats then we suggest using the Cropscape website <http://nassgeodata.gmu.edu/CropScape/> or the freeware browser ESRI ArcGIS Explorer <http://www.esri.com/>."
INDIANA GEOLOGICAL AND WATER SURVEY DATA DISCLAIMER
This data set is provided by Indiana University, Indiana Geological and Water Survey, and contains data believed to be accurate; however, a degree of error is inherent in all data. This product is distributed "AS-IS" without warranties of any kind, either expressed or implied, including but not limited to warranties of suitability of a particular purpose or use. No attempt has been made in either the designed format or production of these data to define the limits or jurisdiction of any federal, state, or local government.
These data are intended for use only at the published scale or smaller and are for reference purposes only. They are not to be construed as a legal document or survey instrument. A detailed on-the-ground survey and historical analysis of a single site may differ from these data.
CREDIT
It is requested that the National Agricultural Statistics Service (NASS), United States Department of Agriculture (USDA), be cited in any products generated from this data set. The following source citation should be included: [CROPS_2015_USDA_IN.TIF: Crops in Indiana for 2015, Derived from National Agricultural Statistics Service (United States Department of Agriculture, 1:100,000, 30-Meter TIFF Image), 20171017].
WARRANTY
Indiana University, Indiana Geological and Water Survey warrants that the media on which this product is stored will be free from defect in materials and workmanship for ninety (90) days from the date of acquisition. If such a defect is found, return the media to Publication Sales, Indiana Geological and Water Survey, 611 North Walnut Grove, Bloomington, Indiana 47405-2208, and it will be replaced free of charge.
"Please visit this internet site <http://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php> to view the original metadata file.
"USDA, National Agricultural Statistics Service, 2015 Indiana Cropland Data Layer - STATEWIDE AGRICULTURAL ACCURACY REPORT
Crop-specific covers only *Correct Accuracy Error Kappa
------------------------- ------- -------- ----- -----
OVERALL ACCURACY** 609,379 93.9% 6.1% 0.889
Cover ***Attribute *Correct Producer's Omission User's Commission Cond'l
Type Code Pixels Accuracy Error Kappa Accuracy Error Kappa
---- ---- ------ -------- ----- ----- -------- ----- -----
Corn 1 301189 96.37% 3.63% 0.947 95.78% 4.22% 0.939
Sorghum 4 97 22.99% 77.01% 0.230 77.60% 22.40% 0.776
Soybeans 5 291062 96.18% 3.82% 0.945 95.91% 4.09% 0.941
Sunflower 6 0 0.00% 100.00% 0.000 n/a n/a n/a
Tobacco 11 0 n/a n/a n/a 0.00% 100.00% 0.000
Sweet Corn 12 9 12.50% 87.50% 0.125 90.00% 10.00% 0.900
Pop or Orn Corn 13 2037 37.93% 62.07% 0.378 90.21% 9.79% 0.902
Mint 14 0 0.00% 100.00% 0.000 n/a n/a n/a
Barley 21 2 9.09% 90.91% 0.091 22.22% 77.78% 0.222
Winter Wheat 24 6370 88.47% 11.53% 0.884 89.38% 10.62% 0.893
Dbl Crop WinWht/Soybeans 26 4331 87.28% 12.72% 0.872 87.34% 12.66% 0.873
Rye 27 0 0.00% 100.00% 0.000 0.00% 100.00% 0.000
Oats 28 3 3.37% 96.63% 0.034 17.65% 82.35% 0.176
Millet 29 0 0.00% 100.00% 0.000 n/a n/a n/a
Speltz 30 0 0.00% 100.00% 0.000 0.00% 100.00% 0.000
Canola 31 12 19.35% 80.65% 0.194 75.00% 25.00% 0.750
Alfalfa 36 2935 58.98% 41.02% 0.588 72.72% 27.28% 0.726
Other Hay/Non Alfalfa 37 743 19.39% 80.61% 0.193 48.37% 51.63% 0.482
Buckwheat 39 0 0.00% 100.00% 0.000 n/a n/a n/a
Dry Beans 42 0 0.00% 100.00% 0.000 0.00% 100.00% 0.000
Potatoes 43 20 71.43% 28.57% 0.714 64.52% 35.48% 0.645
Other Crops 44 0 0.00% 100.00% 0.000 n/a n/a n/a
Watermelons 48 136 59.91% 40.09% 0.599 79.53% 20.47% 0.795
Cucumbers 50 23 26.74% 73.26% 0.267 79.31% 20.69% 0.793
Tomatoes 54 17 13.93% 86.07% 0.139 43.59% 56.41% 0.436
Herbs 57 373 56.60% 43.40% 0.566 92.56% 7.44% 0.926
Clover/Wildflowers 58 1 1.41% 98.59% 0.014 20.00% 80.00% 0.200
Sod/Grass Seed 59 6 4.11% 95.89% 0.041 50.00% 50.00% 0.500
Fallow/Idle Cropland 61 1 1.33% 98.67% 0.013 25.00% 75.00% 0.250
Peaches 67 0 n/a n/a n/a 0.00% 100.00% 0.000
Apples 68 0 0.00% 100.00% 0.000 0.00% 100.00% 0.000
Grapes 69 1 50.00% 50.00% 0.500 100.00% 0.00% 1.000
Christmas Trees 70 0 0.00% 100.00% 0.000 n/a n/a n/a
Triticale 205 0 0.00% 100.00% 0.000 n/a n/a n/a
Cantaloupes 209 1 2.78% 97.22% 0.028 33.33% 66.67% 0.333
Squash 222 0 0.00% 100.00% 0.000 0.00% 100.00% 0.000
Dbl Crop WinWht/Corn 225 0 0.00% 100.00% 0.000 0.00% 100.00% 0.000
Pumpkins 229 10 7.81% 92.19% 0.078 29.41% 70.59% 0.294
Dbl Crop WinWht/Sorghum 236 0 0.00% 100.00% 0.000 n/a n/a n/a
Dbl Crop Soybeans/Oats 240 0 0.00% 100.00% 0.000 n/a n/a n/a
Dbl Crop Corn/Soybeans 241 0 n/a n/a n/a 0.00% 100.00% 0.000
Blueberries 242 0 0.00% 100.00% 0.000 0.00% 100.00% 0.000
Cabbage 243 0 n/a n/a n/a 0.00% 100.00% 0.000
Gourds 249 0 n/a n/a n/a 0.00% 100.00% 0.000
Dbl Crop Barley/Soybeans 254 0 0.00% 100.00% 0.000 n/a n/a n/a
"*NOTE: Correct Pixels represents the total number of independent validation pixels correctly identified in the error matrix.
"**NOTE: The Overall Accuracy represents only the FSA row crops and annual fruit and vegetables (codes 1-61 and 200-255). FSA-sampled tree and shrub crops, aquaculture, and all NLCD-sampled categories (codes 62-65 and 81-199) are not included in the Overall Accuracy.
"The accuracy of the non-agricultural land cover classes within the Cropland Data Layer is entirely dependent upon the USGS, National Land Cover Database (NLCD 2011). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover. For more information on the accuracy of the NLCD please reference <http://www.mrlc.gov/>.
"Classification accuracy is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the detailed accuracy report.
"The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes is entirely dependent upon the USGS, National Land Cover Database (NLCD 2011). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover.
"These definitions of accuracy statistics were derived from the following book: Congalton, Russell G. and Kass Green. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, Florida: CRC Press, Inc. 1999. The 'Producer's Accuracy' is calculated for each cover type in the ground truth and indicates the probability that a ground truth pixel will be correctly mapped (across all cover types) and measures 'errors of omission'. An 'Omission Error' occurs when a pixel is excluded from the category to which it belongs in the validation dataset. The 'User's Accuracy' indicates the probability that a pixel from the CDL classification actually matches the ground truth data and measures 'errors of commission'. The 'Commission Error' represent when a pixel is included in an incorrect category according to the validation data. It is important to take into consideration errors of omission and commission. For example, if you classify every pixel in a scene to 'wheat', then you have 100% Producer's Accuracy for the wheat category and 0% Omission Error. However, you would also have a very high error of commission as all other crop types would be included in the incorrect category. The 'Kappa' is a measure of agreement based on the difference between the actual agreement in the error matrix (i.e., the agreement between the remotely sensed classification and the reference data as indicated by the major diagonal) and the chance agreement which is indicated by the row and column totals. The 'Conditional Kappa Coefficient' is the agreement for an individual category within the entire error matrix."
"The Cropland Data Layer (CDL) has been produced using training and independent validation data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program (agricultural data) and United States Geological Survey (USGS) National Land Cover Database 2011 (NLCD 2011). More information about the FSA CLU Program can be found at <http://www.fsa.usda.gov/>. More information about the NLCD 2006 can be found at <http://www.mrlc.gov/>. The CDL encompasses the entire state unless noted otherwise in the 'Completeness Report' section of this metadata file."
"The entire state is covered by the Cropland Data Layer."
"The Cropland Data Layer retains the spatial attributes of the input imagery. The Landsat 8 OLI/TIRS and Landsat 7 ETM imagery was obtained via download from the USGS Global Visualization Viewer (Glovis) website <http://glovis.usgs.gov/>. Please reference the metadata on the Glovis website for each Landsat scene for positional accuracy. The majority of the Landsat data is available at Level 1T (precision and terrain corrected). The DEIMOS-1 and DMC-UK 2 imagery used in the production of the Cropland Data Layer is orthorectified to a radial root mean square error (RMSE) of approximately 10 meters."
"OVERVIEW: The United States Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) Program is a unique agricultural-specific land cover geospatial product that is produced annually in participating states. The CDL Program builds upon NASS' traditional crop acreage estimation program and integrates Farm Service Agency (FSA) grower-reported field data with satellite imagery to create an unbiased statistical estimator of crop area at the state and county level for internal use. It is important to note that the internal acreage estimates produced using the CDL are not simple pixel counting. It is more of an 'Adjusted Census by Satellite.'
"SOFTWARE: ERDAS Imagine is used in the pre- and post- processing of all raster-based data. ESRI ArcGIS is used to prepare the vector-based training and validation data. Rulequest See5.0 is used to create a decision tree based classifier. The NLCD Mapping Tool is used to apply the See5.0 decision-tree via ERDAS Imagine.
"DECISION TREE CLASSIFIER: This Cropland Data Layer used the decision tree classifier approach. Using a decision tree classifier is a departure from older versions of the CDL which were created using in-house software (Peditor) based upon a maximum likelihood classifier approach. Check the 'Process Description' section of the specific state and year metadata file to verify the methodology used. Decision trees offer several advantages over the more traditional maximum likelihood classification method. The advantages include being: 1) non-parametric by nature and thus not reliant on the assumption of the input data being normally distributed, 2) efficient to construct and thus capable of handling large and complex data sets, 3) able to incorporate missing and non-continuous data, and 4) able to sort out non-linear relationships.
"GROUND TRUTH: As with the maximum likelihood method, decision tree analysis is a supervised classification technique. Thus, it relies on having a sample of known ground truth areas in which to train the classifier. Older versions of the CDL (prior to 2006) utilized ground truth data from the annual June Agricultural Survey (JAS). Beginning in 2006, the CDL utilizes the very comprehensive ground truth data provided from the FSA Common Land Unit (CLU) Program as a replacement for the JAS data. The FSA CLU data have the advantage of natively being in a GIS and containing magnitudes more of field level information. Disadvantages include that it is not truly a probability sample of land cover and has bias toward subsidized program crops. Additional information about the FSA data can be found at <http://www.fsa.usda.gov/>. The most current version of the NLCD is used as non-agricultural training and validation data.
"INPUTS: The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season. The DEIMOS-1 and UK-DMC 2 imagery was resampled to 30 meters using cubic convolution, rigorous transformation to match the traditional Landsat spatial resolution. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED) and the imperviousness and canopy data layers from the USGS National Land Cover Database 2011 (NLCD 2011). Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery and ancillary data used to generate this state's CDL.
"ACCURACY: The accuracy of the land cover classifications are evaluated using independent validations data sets generated from the FSA CLU data (agricultural categories) and the NLCD 2011 (non-agricultural categories). The Producer's Accuracy is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the full accuracy report.
"PUBLIC RELEASE: The USDA, NASS Cropland Data Layer is considered public domain and free to redistribute. The official website is <http://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>. The data is available free for download through CropScape <http://nassgeodata.gmu.edu/CropScape/> and the Geospatial Data Gateway <http://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed download instructions. Please note that in no case are farmer reported data revealed or derivable from the public use Cropland Data Layer."
"The Cropland Data Layer (CDL) is produced using agricultural training data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program and non-agricultural training data from the most current version of the United States Geological Survey (USGS) National Land Cover Dataset (NLCD). The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes are entirely dependent upon the NLCD. Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover."
"If the following table does not display properly, then please visit the following Web site to view the original metadata file - <http://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php>."
"Data Dictionary: USDA, National Agricultural Statistics Service, 2015 Cropland Data Layer
"Source: USDA, National Agricultural Statistics Service
"The following is a cross reference list of the categorization codes and land covers. Note that not all land cover categories listed below will appear in an individual state.
Raster Attribute Domain Values and Definitions: NO DATA, BACKGROUND 0
Categorization Code Land Cover
---------------------------------
"0" Background
Raster Attribute Domain Values and Definitions: ROW CROPS 1-20
Categorization Code Land Cover
---------------------------------
"1" Corn
"2" Cotton
"3" Rice
"4" Sorghum
"5" Soybeans
"6" Sunflowers
"10" Peanuts
"11" Tobacco
"12" Sweet Corn
"13" Popcorn or Ornamental Corn
"14" Mint
Raster Attribute Domain Values and Definitions: GRAINS,HAY,SEEDS 21-40
Categorization Code Land Cover
------------------------------------
"21" Barley
"22" Durum Wheat
"23" Spring Wheat
"24" Winter Wheat
"25" Other Small Grains
"26" Dbl Crop WinWht/Soybeans
"27" Rye
"28" Oats
"29" Millet
"30" Speltz
"31" Canola
"32" Flaxseed
"33" Safflower
"34" Rape seed
"35" Mustard
"36" Alfalfa
"37" Other Hay/Non Alfalfa
"38" Camelina
"39" Buckwheat
Raster Attribute Domain Values and Definitions: OTHER CROPS 41-60
Categorization Code Land Cover
------------------------------------
"41" Sugarbeets
"42" Dry Beans
"43" Potatoes
"44" Other Crops
"45" Sugarcane
"46" Sweet Potatoes
"47" Misc Vegs & Fruit
"48" Watermelons
"49" Onions
"50" Cucumbers
"51" Chick Peas
"52" Lentils
"53" Peas
"54" Tomatoes
"55" Caneberries
"56" Hops
"57" Herbs
"58" Clover/Wildflowers
"59" Sod/Grass Seed
"60" Switchgrass
Raster Attribute Domain Values and Definitions: OPEN NON-CROP 61-65
Categorization Code Land Cover
-----------------------------------
"61" Fallow/Idle Cropland
"63" Forest
"64" Shrubland
"65" Barren
Raster Attribute Domain Values and Definitions: TREE CROPS 66-80
Categorization Code Land Cover
------------------------------------
"66" Cherries
"67" Peaches
"68" Apples
"69" Grapes
"70" Christmas Trees
"71" Other Tree Crops
"72" Citrus
"74" Peacans
"75" Almonds
"76" Walnuts
"77" Pears
Raster Attribute Domain Values and Definitions: OTHER NON-CROP 81-109
Categorization Code Land Cover
-------------------------------------
"81" Clouds/No Data
"82" Developed
"83" Water
"87" Wetlands
"88" Nonag/Undefined
"92" Aquaculture
Raster Attribute Domain Values and Definitions: NLCD-DERIVED CLASSES 110-195
Categorization Code Land Cover
-------------------------------------
"111" Open Water
"112" Perennial Ice/Snow
"121" Developed/Open Space
"122" Developed/Low Intensity
"123" Developed/Medium Intensity
"124" Developed/High Intensity
"131" Barren
"141" Deciduous Forest
"142" Evergreen Forest
"143" Mixed Forest
"152" Shrubland
"176" Grassland/Pasture
"190" Woody Wetlands
"195" Herbaceous Wetlands
Raster Attribute Domain Values and Definitions: CROPS 195-255
Categorization Code Land Cover
-------------------------------------
"204" Pistachios
"205" Triticale
"206" Carrots
"207" Asparagus
"208" Garlic
"209" Cantaloupes
"210" Prunes
"211" Olives
"212" Oranges
"213" Honeydew Melons
"214" Broccoli
"216" Peppers
"217" Pomegranates
"218" Nectarines
"219" Greens
"220" Plums
"221" Strawberries
"222" Squash
"223" Apricots
"224" Vetch
"225" Dbl Crop WinWht/Corn
"226" Dbl Crop Oats/Corn
"227" Lettuce
"229" Pumpkins
"230" Dbl Crop Lettuce/Durum Wht
"231" Dbl Crop Lettuce/Cantaloupe
"232" Dbl Crop Lettuce/Cotton
"233" Dbl Crop Lettuce/Barley
"234" Dbl Crop Durum Wht/Sorghum
"235" Dbl Crop Barley/Sorghum
"236" Dbl Crop WinWht/Sorghum
"237" Dbl Crop Barley/Corn
"238" Dbl Crop WinWht/Cotton
"239" Dbl Crop Soybeans/Cotton
"240" Dbl Crop Soybeans/Oats
"241" Dbl Crop Corn/Soybeans
"242" Blueberries
"243" Cabbage
"244" Cauliflower
"245" Celery
"246" Radishes
"247" Turnips
"248" Eggplants
"249" Gourds
"250" Cranberries
"254" Dbl Crop Barley/Soybeans
It is requested that the National Agricultural Statistics Service (NASS), United States Department of Agriculture (USDA), be cited in any products generated from this data set. The following source citation should be included: [CROPS_2015_USDA_IN.TIF: Crops in Indiana for 2015, Derived from National Agricultural Statistics Service (United States Department of Agriculture, 1:100,000, 30-Meter TIFF Image), 20171017].
WARRANTY
Indiana University, Indiana Geological and Water Survey warrants that the media on which this product is stored will be free from defect in materials and workmanship for ninety (90) days from the date of acquisition. If such a defect is found, return the media to Publication Sales, Indiana Geological and Water Survey, 611 North Walnut Grove, Bloomington, Indiana 47405-2208, and it will be replaced free of charge.
LIMITATION OF WARRANTIES AND LIABILITY
Except for the expressed warranty above, the product is provided "AS IS", without any other warranties or conditions, expressed or implied, including, but not limited to, warranties for product quality, or suitability to a particular purpose or use. The risk or liability resulting from the use of this product is assumed by the user. Indiana University, Indiana Geological and Water Survey shares no liability with product users indirect, incidental, special, or consequential damages whatsoever, including, but not limited to, loss of revenue or profit, lost or damaged data or other commercial or economic loss. Indiana University, Indiana Geological and Water Survey is not responsible for claims by a third party. The maximum aggregate liability to the original purchaser shall not exceed the amount paid by you for the product.
"Please visit the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> for distribution details. The Cropland Data Layer is available free for download at <http://nassgeodata.gmu.edu/CropScape/> and <http://datagateway.nrcs.usda.gov/>. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540"
"Users of the Cropland Data Layer (CDL) are solely responsible for interpretations made from these products. The CDL is provided 'as is' and the USDA, NASS does not warrant results you may obtain using the Cropland Data Layer. Contact our staff at (HQ_RDD_GIB@nass.usda.gov) if technical questions arise in the use of the CDL. NASS does maintain a Frequently Asked Questions (FAQ's) section on the CDL website at <http://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>. "