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Download Facebook Timeline 2013 ~REPACK~

Facebook emailed me a link to download my data. The process took about 10 minutes. (The downloading time depends on how much data you've generated.) The data is segmented into groups: like ads, contact info, events, messages, timeline, and more.

download facebook timeline 2013

If you want to find a photo or a video on your timeline, you'll find those options under Filters as well. Searching for photos and videos is similar to the process mentioned above. However, these two options have fewer filters than Posts, modified according to the content type requirements. Here, you might also want to check out how to download Facebook photos and videos.

Creative Alive team specially made up a mock up PSD for facebook timeline cover picture. We have created Photoshop action and PSD file for this mock up to make your work easy and convenient. By using this mockup you can generate your facebook cover image and profile picture with in some seconds. Make your Facebook page or your profile page more creative using provided mockup PSD.

You might want to do this as a regular exercise if you regularly post content. It is advised you keep these files safe as it contains all your private data and information about all your posts, comments, and photos, and more confidential information. Go ahead and download all your Facebook information today and keep a backup of your Facebook timeline.

  • National CDL's:Download the national 2022 CDL zipped file 2022 National CDL (2.0 GB)

  • Download the national 2021 CDL zipped file 2021 National CDL (2.0 GB)

  • Download the national 2020 CDL zipped file 2020 National CDL (2.0 GB)

  • Download the national 2019 CDL zipped file 2019 National CDL (1.9 GB)

  • Download the national 2018 CDL zipped file 2018 National CDL (1.8 GB)

  • Download the national 2017 CDL zipped file 2017 National CDL (1.7 GB)

  • Download the national 2016 CDL zipped file 2016 National CDL (1.8 GB)

  • Download the national 2015 CDL zipped file 2015 National CDL (1.8 GB)

  • Download the national 2014 CDL zipped file 2014 National CDL (1.8 GB)

  • Download the national 2013 CDL zipped file 2013 National CDL (1.8 GB)

  • Download the national 2012 CDL zipped file 2012 National CDL (1.8 GB)

  • Download the national 2011 CDL zipped file 2011 National CDL (1.8 GB)

  • Download the national 2010 CDL zipped file 2010 National CDL (1.8 GB)

  • Download the national 2009 CDL zipped file 2009 National CDL (1.8 GB)

  • Download the national 2008 CDL zipped file 2008 National CDL (1.8 GB)

  • National Cultivated Layer:Download the national 2022 cultivated layer zipped file 2022 National Cultivated Layer (300 MB). The Cultivated Layer is based on the most recent five years (2018-2022).

  • National Frequency Layer:Download the national crop frequency layer zipped file 2022 National Frequency Layer (1.8 GB)

  • The 2022 Crop Frequency Layer identifies crop specific planting frequency and are based on land cover information derived from the 2008 through 2022 CDL's. There are currently four individual crop frequency data layers that represent four major crops: corn, cotton, soybeans, and wheat.

National Confidence Layer: The following description of the confidence layer is from the document titled 'MDA_NLCD_User_Guide.doc' which is available free for download with the NLCD Mapping Tool at The Confidence Layer "spatially represents the predicted confidence that is associated with that output pixel, based upon the rule(s) that were used to classify it. This is useful in that the user can see the spatial representation of distribution and magnitude of error or confidence for a given classification... This error layer represents a percent confidence associated with each rule and output categorical, classified value. It is expressed as a percentage of confidence. A value of zero would therefore have a low confidence (always wrong), while a value of 100 would have a very high confidence (always right)." For more information on the use of confidence layers please refer to the following paper: Liu, Weiguo, Sucharita Gopal and Curtis E. Woodcock, 2004. Uncertainty and confidence in land cover classification using a hybrid classifier approach, Photogrammetric Engineering & Remote Sensing, 70(8):963-971. Ultimately, however, the confidence value is not a measure of accuracy for a given pixel but rather how well it fit within the decision tree ruleset.


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