If you use a dark theme or other colorful theme that diverges from the typical black firstLevelElements on white background style, set the values for other structural colors and the primary text class colors. This ensures that data labels on charts with a label background match the anticipated style, are readable, and have visible axis gridlines.
To create an extended-format JSON file, with more detailed and granular control over all visual formatting in a report, add a visualStyles section to the JSON file to nest the formatting specifics. See the following example of the visualStyles section:
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If you have problems with Google Play Games Beta on PC after you install it on your computer, these steps may help you troubleshoot. Google Play Games is in its beta phase, so we expect some issues to happen.
An object with members to configure the placement and size of the chart area (where the chart itself is drawn, excluding axis and legends). Two formats are supported: a number, or a number followed by %. A simple number is a value in pixels; a number followed by % is a percentage. Example: chartArea:{left:20,top:0,width:'50%',height:'75%'}
If set to true, stacks the elements for all series at each domain value. Note: In Column, Area, and SteppedArea charts, Google Charts reverses the order of legend items to better correspond with the stacking of the series elements (E.g. series 0 will be the bottom-most legend item). This does not apply to Bar Charts.
You can specify either an array of objects, each of which applies to the series in the order given, or you can specify an object where each child has a numeric key indicating which series it applies to. For example, the following two declarations are identical, and declare the first series as black and absent from the legend, and the fourth as red and absent from the legend:
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At acceptance, please upload the text (this includes legends for print figures and Extended Data figures, complete print tables, and titles and legends only for Extended Data tables, but excludes print figures and Extended Data figures and tables themselves) of your paper to our server together with your production-quality figures and Extended Data figures and tables as separate files, and Supplementary Information, if any.
After acceptance for publication, we will subedit your manuscript (main text, full Methods, legends for print-only figures and Extended Data figures, complete print-only tables, and titles and legends only for Extended Data tables) to ensure that it is intelligible to our wide readership and that it conforms with house style. Our subeditors usually send authors the edited text for approval before it is typeset. This enables most queries to be resolved before proof stage. You will subsequently receive an e-proof, including the figures and Extended Data display items, for checking before the paper is signed off and is ready to schedule in print/online.
CropScape currently does not have the capability to create PDF maps with only one specific crop or group of crops shown. However, the user can export the actual CDL data with only a single crop or subset of crops in a Geotiff (TIF) format using the CropScape "Area of Interest Statistics" tool. That downloaded data can then be used to create a more polished PDF map using ESRI ArcGIS software. Below are the procedures:
1.Select your area of interest;
2.Use the "Area of Interest Statistics" tool to calculate statistics;
3.Check the box of the crop type(s) you wish to display in the pop-up statistical result window;
4.Click "Export the selected crop(s) for mapping";
5.Click the "Download" button to download the resulting image in a Geotiff (TIF) file format;
6.Load the downloaded TIF file in ArcGIS where you can then add additional data, such as boundaries and/or legends, to create your own map that can then be exported to a PDF file.
The AGRICULTURAL CATEGORIES are based on data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. Thus, all crop specific categories are determined by the FSA CLU/578 Program which offers detailed documentation at the following website: -and-services/laws-and-regulations/handbooks/index. The online manual titled 2-CP contains much of the crop information used for CDL purposes, especially the section "Exhibit 10 2003 and Subsequent Year Crops Reported on FSA-578."
There are hundreds of potential FSA crop types and thousands of other variables that we have done our best to crosswalk for CDL purposes. This Microsoft Excel spreadsheet FSA-to-CDL_Crosswalk details our current crosswalking and can be used to determine exactly what FSA crop types appear within grouped CDL categories, such as "Other Crops" (CDL code 44), "Misc Vegs and Fruit" (CDL code 47), "Herbs" (CDL code 57), "Other Tree Crops" (CDL code 71), and "Greens" (CDL code 219).
As for the NON-AGRICULTURAL CATEGORIES in the CDL, we sample non-ag training and validation from the USGS National Land Cover Database (NLCD). The NLCD legend with category definitions is available at: -land-cover-database-2016-nlcd2016-legend. In the CDL we have added 100 to their code numbers (i.e. NLCD code 11 "Open Water" is code 111 in the CDL). The NLCD Cultivated Crops category is ignored for CDL purposes. We have also made the decision to merge NLCD "Grassland/Herbaceous" and NLCD "Pasture/Hay" into a single CDL category called "Grassland/Pasture" (CDL code 176).
The primary focus of the Cropland Data Layer (CDL) is on large area summer crops. The Farm Service Agency CLU data is our primary source of agricultural training data for the CDL classifier. We depend on the data that the farmer reports on their FSA/CLU signup forms. The ground truth is prepared to show whether a single/double crop was planted in a particular field. For example, a winter wheat field planted in the Fall of 2009 will be identified in the 2010 CDL, as we consider the time of harvest as the current year of production. If the field is multi-use during a given year, for example winter wheat (ww) followed by soybeans (sb), then a double cropping situation exists and the category for that given field will be ww/sb, and is indicated as such in the legend. If a field is only sb during that year, then it will be identified as sb only. Therefore, all major crop rotations/patterns are captured with this method and are consider mutually exclusive for a given pixel/field. We do not monitor the fruit and vegetable winter industry (i.e., Florida/California), as we focus primarily on the large area summer crops and are not equipped to monitor triple or quad cropping practices. Please reference the official metadata for a complete list of all possible CDL categories, including valid double-crop categories.
All category codes, class names and legend colors are standardized and consistent for all states and all years of the Cropland Data Layer Program.
The 1997-2013 CDLs were recoded and re-released January 31, 2014 to better represent pasture and grass-related categories. A new category named Grass/Pasture (code 176) collapses the following historical CDL categories: Pasture/Grass (code 62), Grassland Herbaceous (code 171), and Pasture/Hay (code 181). This was done to eliminate confusion among these similar land cover types which were not always classified definitionally consistent from state to state or year to year and frequently had poor classification accuracies. Please view the 2013 crosswalk document for a detailed listing of the revisions.
This follows the recoding of the entire CDL archive in January 2012 to better align the historical CDLs with the current product. These revisions were done to eliminate redundant and/or unused categories. The majority of the changes apply to the non-agricultural domain. Please view the 2011 crosswalk document for a detailed listing of the revisions. be457b7860
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