Introduction to Raster Data

Figure 1

raster concept
Raster Concept (Source: National Ecological Observatory Network (NEON))

Figure 2

elevation Harvard forest
Continuous Elevation Map: HARV Field Site

Figure 3

USA landcover classification
USA landcover classification

Figure 4

spatial extent objects
Spatial extent image (Image Source: National Ecological Observatory Network (NEON))

Figure 5

resolution image
Resolution image (Source: National Ecological Observatory Network (NEON))

Figure 6

multi-band raster
RGB multi-band raster image (Source: National Ecological Observatory Network (NEON).)

Introduction to Vector Data

Figure 1

vector data types
Types of vector objects (Image Source: National Ecological Observatory Network (NEON))

Figure 2

vector type examples
Vector Type Examples

Coordinate Reference Systems

Figure 1

US difference projections
Maps of the United States in different projections (Source: opennews.org)

Figure 2

datum fruit example
Datum Fruit Example (Image source)

Figure 3

projection citrus peel
Projection Citrus Peel Example (Image from Prof Drika Geografia, Projeções Cartográficas)

Figure 4

UTM zones across the CONUS
The UTM zones across the continental United States (Chrismurf at English Wikipedia, via Wikimedia Commons (CC-BY))

The Geospatial Landscape

Access satellite imagery using Python

Figure 1

STAC browser screenshots
Views of the STAC browser

Figure 2

earth-search stac catalog views
Views of the Earth Search STAC endpoint

Figure 3

thumbnail of the sentinel-2 scene
Overview of the true-color image (“thumbnail”)

Figure 4

thumbnail of the landsat-8 scene
Thumbnail of the Landsat-8 scene

Read and visualize raster data

Figure 1

raster plot with defualt setting
Raster plot with rioxarray

Figure 2

raster plot with robust setting
Raster plot using the “robust” setting

Figure 3

UTM zones across the CONUS
The UTM zones across the continental United States (Chrismurf at English Wikipedia, via Wikimedia Commons (CC-BY))

Figure 4

raster plot masking missing values
Raster plot after masking out missing values

Figure 5

multi-band raster
Sketch of a multi-band raster image

Figure 6

true-color image overview
Overview of the true-color image (multi-band raster)

Figure 7

raster plot with correct aspect ratio
Overview of the true-color image with the correct aspect ratio

Vector data in Python

Figure 1

Pandas and Geopandas

Figure 2

Crop fields inside the AOI

Figure 3

all wells in the NL

Figure 4

50m buffer around the fields

Figure 5

Wells within 50m buffer of fields

Figure 6

fields within 50m buffer of the wells, truncated

Figure 7

Fields in 50m buffer of wells, not truncated

Figure 8

waterways, rotated

Figure 9

waterways, corrected

Crop raster data with rioxarray and geopandas

Figure 1

Overview of the raster

Figure 2

Raster cropped by a bounding box

Figure 3

Ratser cropped by field polygons

Figure 4

Raster croped by fields with gewascode 257

Figure 5

Reproject match big to small

Figure 6

Reproject match small to big

Raster Calculations in Python

Figure 1

PONE-NDVI image
Source: Wu C-D, McNeely E, Cedeño-Laurent JG, Pan W-C, Adamkiewicz G, Dominici F, et al. (2014) Linking Student Performance in Massachusetts Elementary Schools with the “Greenness” of School Surroundings Using Remote Sensing. PLoS ONE 9(10): e108548. https://doi.org/10.1371/journal.pone.0108548

Figure 2

red band image

Figure 3

near infra-red band image

Figure 4

NDVI map

Figure 5

NDVI histogram

Figure 6

NDVI histogram with 50 bins

Figure 7

binned NDVI map

Figure 8

NDVI classes
Source: Image created for this lesson (license)

Figure 9

classified NDVI map

Figure 10

NDVI map Texel

Figure 11

NDVI histogram Texel

Calculating Zonal Statistics on RastersIntroductionMaking vector and raster data compatibleRasterizing the vector dataCalculate zonal statistics

Figure 1

rasterization results

Figure 2

Rasterization results Xarray

Parallel raster computations using Dask

Figure 1

true color image scene
Scene’s true-color image

Figure 2

median filter true color image
True-color image after median filtering

Figure 3

DataArray with Dask
Xarray Dask-backed DataArray

Figure 4

dask graph
Dask graph