A Comparison of Raster-based Forest Land Data in Crop Data Layer and National Land Cover Database

Authors: Chinazor Azubike*, North Carolina Agricultural & Technical State University, Lyubov Kurkalova, North Carolina Agricultural & Technical State University, Timothy Mulrooney, North Carolina Central University
Topics: Geographic Information Science and Systems, Land Use and Land Cover Change, Land Use
Keywords: Crop Data Layer, Forest Land, Geographic Information Systems, National Land Cover Data, Raster Data
Session Type: Paper
Day: 4/8/2020
Start / End Time: 8:00 AM / 9:15 AM
Room: Governors Square 10, Sheraton, Concourse Level
Presentation File: No File Uploaded


The National Agricultural Statistics Service (NASS), the statistical arm of the US Department of Agriculture, (USDA) collects and publishes several land use and land cover data sets. The aim of this study is to analyze the consistency and compare forest land in two USDA data products, the National Land Cover Database (NLCD) and Crop Data Layer (CDL), both provide raster-formatted, land cover data. According to CDL, non-agricultural land cover data (forest data) is derived from NLCD; therefore (non-agricultural), forest land data from both databases should accurately match. However, the accuracy between these two datasets has not been studied for the Southeastern part of the United States. 2011 forest land data from CDL and NLCD for four random study areas in Duplin County in North Carolina are reclassified and overlaid in ArcGIS. Mismatched land areas are identified and maps are created to show the location and attributes of the inconsistencies. Preliminary results show discrepancies in forest land data between CDL and NLCD which has led to further analysis of each data set. This can lead to an explanation of the degree to which mismatches exist and provide correlations between mismatched pixels and the underlying spatial and attribute relationships with source data from which mismatches have been derived.

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