Exploring the NDVI in Philadelphia¶

The normalized difference vegetation index (NDVI) is a commonly used index that measures the live vegetation coverage in an area in satellite image (remote sensing) analysis. The NDVI index is calculated as The NDVI is calculated from these individual measurements as follows:

NDVI = (NIR - Red)/(NIR + Red),

where red and NIR stand for the spectral reflectance measurements acquired in the red (visible) and near-infrared regions, respectively. In this part, I'll explore the NDVI in Philadelphia with both raster landsat data and vector data with two steps:

1. I'll compare the median NDVI within the city limits and the immediate suburbs
2. I'll calculate the NDVI around street trees in the city.

1. Comparing the NDVI in the city and the suburbs¶

1.1 Load Landsat data for Philadelphia¶

Use rasterio to load the landsat data for Philadelphia (available in the "data/" folder)

In [1]:
import numpy as np
import pandas as pd
import geopandas as gpd
import hvplot.pandas
import holoviews as hv
import cartopy.crs as ccrs
from matplotlib import pyplot as plt
%matplotlib inline