LCMAP's Annual Land Cover Change product (LCACHG) is used for tracking thematic land cover change. LCACHG is not a direct output of the LCMAP analytical process, but is a synthesis product of the Primary Land Cover (LCPRI) of any given year and the LCPRI from the previous year. LCACHG identifies both locations that are unchanged between the two years (single-digit values) and locations that have been observed to change from one thematic land cover to another (two-digit values). LCACHG uses the same 8 values representing land cover that are used in LCPRI.
|Land Cover Class||LC Value|
An unchanged location is identified with its single-digit LC value, remaining identical to LCPRI. A changed location is identified with a two-digit value representing both the previous and the new LC value with a concatenation of values. For example, a value of
21 in LCACHG for 1998 would represent a thematic change from Cropland (
2) in 1997 to Developed (
1) in 1998. Additional information is available in the LCMAP Science Product Guide.
It is recommended to use Conda, an environment manager to set up a compatible Python environment. Download Conda for your OS here: https://www.anaconda.com/download/. Follow the instructions below to successfully setup a Python environment on Linux, MacOS, or Windows.
This workflow has been tested using Python version 3.9 on Windows 10 Enterprise.
Using your preferred command line interface (command prompt, terminal, cmder, etc.) type the following to successfully create a compatible python environment:
conda create -n thematic_change -c conda-forge --yes python=3.9 numpy rasterio geopandas bokeh geoviews firefox geckodriver selenium
conda activate thematic_change
conda install -c conda-forge --yes jupyter notebook
TIP: Having trouble activating your environment, or loading specific packages once you have activated your environment? Try the following:
conda update condaor
conda update --all
If you prefer to not install Conda, the same setup and dependencies can be achieved by using another package manager such as
# Import Packages import geopandas as gp import geoviews as gv import rasterio as rio from IPython import display import os import numpy as np from rasterio.merge import merge from matplotlib import pyplot as plt import rasterio.mask import matplotlib.colors as clr import pandas as pd import holoviews as hv from holoviews import opts hv.extension('bokeh') gv.extension('bokeh')