An Interactive System for U.S. Land Cover Information

Bin Fang
Posted on Aug 8, 2016

Background

The United States has a total land area of nearly 2.3 billion acres. By 2007, the major land uses were forestland at 671 million acres (30 percent); grassland pasture and rangeland at 614 million (27 percent); cropland at 408 million (18 percent); special uses (primarily parks and wildlife areas) at 313 million acres (14 percent); miscellaneous uses (like tundra or swamps) at 197 million acres (9 percent); and urban land at 61 million acres (3 percent).

Specifically, the six land types are: the cropland, including land planted for crops, cropland used for pasture and idled cropland; the grassland pasture and range, including all grazing land, cropland use of pasture and grazed forests; the forest use land, excluding forest land in parks and wildlife areas and other special uses; the urban and rural residential areas; the special-use areas, including rural transportation, national state parks, wilderness and wildlife areas, national defense and industrial areas, and farmsteads and farm roads; miscellaneous and other uses, including tundra and swamps.

The data was downloaded from USDA-ERS (United States Department, of Agriculture, Economic Research Service) data products center website at:  http://www.ers.usda.gov/data-products/major-land-uses.aspx

ERS has been providing major land use estimates in the United States for over 50 years. The land cover data is the longest running, most comprehensive accounting of all major uses of public and private land in the United States. The program was started in 1945 and has been published about every 5 years.

Spatial distribution pattern of U.S. land cover

For the cropland, the highest rate of coverage is found in corn belt, northern plain and lake states, with Iowa ranking first (74.756%) and 26729.71 million acres. Maine is found the highest rank in forestland covering 87.863% of whole state and 17354.62 million acres. Northeast and southeast states have relatively higher forestland coverage than other regions. There is a clear line between U.S. east and west to divide the grass pasture and rangeland of high percentages and low percentages, with Wyoming ranking first (71.854%) and 44653.06 million acres. Alaska ranks first for the special land type (39.164%) and with 143357.95 million acres, as this state has great portion of national state park and wildlife areas. For the urban land cover type, New Jersey ranks first, with 38.261% and 1816.26 million acres. The entire east coast, corn belt states, Texas and California have higher portion. Alaska has the highest rank of miscellaneous land type, with 34.94% and 127898.41 million acres.

Slide02

Slide03

 

Change trend between 1945-2007 in regions

The cropland coverage dropped in early 1960s and quickly rose in 1970s, and kept going down until 2007, which corresponds to the extreme weather caused droughts. Corn belt and northern plain states, with approximate over 50% coverage led other states. The forestland change trend is quite fluctuated. The percentage for all regions dropped between 1945-2000 and soon rose until 2007. Northeast, southeast, Appalachian and delta states led during the entire period than other regions. For the grass pasture and rangeland, the lines for all regions normally dropped from 1945-2000 and rose up after 2000. Southern plain and mountains states led. All regions slowly rose up through entire period for the special land cover type, while the urban land type rate increased rapidly through the whole period, which reflected the urbanization trend in U.S.. The miscellaneous land cover type fluctuated for all regions.

Slide04

Correlation between crop, forest and grass

As crop, grass and forest took approximately 75% of total percentages for most of states, the 3D scatter plot here showed the relationship between the top-three land cover types. It clearly separates the states by regions, that is: northern and southern plains correspond to high grass and crop rate and low forest rate. Mountain and pacific states correspond to low crop, medium forest and high grass rate. Corn belt and lake states correspond to very high crop and low grass and forest rate. Northeast, southeast, Appalachian and delta states correspond to high forest, low crop and grass rate.

Screen Shot 2016-08-07 at 10.28.13 PM

 

Land cover information by state

If analyze land cover information by specific state of different regions, it can be found that:

In the past 50 years, in New York state, forestland rose from 35.47% to 53.51%, while crop dropped from 27.28% to 13.7%. Other land cover types varied less than 5%.

In Texas, the grassland rose from 53.78% to 60.72%, while cropland dropped from 21.18% to 10.24%. Forestland didn’t change much from 20.66 % to 20.36%.

In Illinois, cropland rose from 65.86% to 67.62%, while forestland rose from 9.29% to 12.27%. Other land cover types varied less than 5% and took less than 10% percent of total.

In California, forestland dropped from 43.74% to 27.03%, while cropland rose from 22.48% to 27.58%.

In New Jersey, forestland dropped from 47.65% to 31.01%, urban rose from 15.85% to 38.26% and exceeded forestland. Cropland dropped from 23.6 to 10.09%.

Slide06

Slide07

Conclusion

It can be summarized that cropland across most of regions dropped a couple of percentages, while forestland and grassland fluctuated during the entire period and rose a little by 2007. Urban land dramatically rose for all regions by 5% - 7%. Crop, grass and forest took approximately 75% of total percentages for most of states The major land cover types for different regions are: forestland dominated east coast and south central states, cropland dominated corn belt, northern plain and lake states. Grassland dominated northern and southern plain as well as mountain states. Urban land dominated northeast, southeast and southwest coast.

Data tables and source code can be downloaded from the following Github repository here.

Please visit the App here.

About Author

Bin Fang

Bin Fang

With a multi-disciplinary background in earth science, electrical engineering and satellite technology, Bin has spent more than ten years in scientific research and teaching in university and research institute. His previous study aimed to integrate and interpret remote...
View all posts by Bin Fang >

Leave a Comment

Avatar
proxy list March 27, 2017
Hi there,I check your new stuff named "An Interactive System for U.S. Land Cover Information - NYC Data Science Academy BlogNYC Data Science Academy Blog" on a regular basis.Your humoristic style is witty, keep up the good work! And you can look our website about proxy list.

View Posts by Categories


Our Recent Popular Posts


View Posts by Tags

#python #trainwithnycdsa 2019 airbnb Alex Baransky alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus API Application artist aws beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep Bundles California Cancer Research capstone Career Career Day citibike clustering Coding Course Demo Course Report D3.js data Data Analyst data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization Deep Learning Demo Day Discount dplyr employer networking feature engineering Finance Financial Data Science Flask gbm Get Hired ggplot2 googleVis Hadoop higgs boson Hiring hiring partner events Hiring Partners Industry Experts Instructor Blog Instructor Interview Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter lasso regression Lead Data Scienctist Lead Data Scientist leaflet linear regression Logistic Regression machine learning Maps matplotlib Medical Research Meet the team meetup Networking neural network Neural networks New Courses nlp NYC NYC Data Science nyc data science academy NYC Open Data NYCDSA NYCDSA Alumni Online Online Bootcamp Open Data painter pandas Part-time Portfolio Development prediction Prework Programming PwC python python machine learning python scrapy python web scraping python webscraping Python Workshop R R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn Selenium sentiment analysis Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau team TensorFlow Testimonial tf-idf Top Data Science Bootcamp twitter visualization web scraping Weekend Course What to expect word cloud word2vec XGBoost yelp