Remote Sensing Lab 2NDVI in California

Normalized Difference Vegetation Index

The NDVI is a measure for bioactivityIt builds on the fact that a healthy vegetation with active photosynthesis absorbs light in the red spectrum but almost no light in the near infrared spectrum (see spectrum below).

In contrast to that, barren land and water surfaces do not exhibit this characteristic absorption and absorb light more uniform across the spectrum.

The NDVI is a measure for bioactivity

NDVI = 0.8 implies complete cover NDVI = 0 implies little canopy NDVI < 0 implies water and clouds.

● Used to map vegetation or identify eco-regions.

● Used to estimate NPP over various biomes.

● To detect length of growing season.● Detect long-term changes in growing

season.

For broad band satellites, red light in the above equations is replaced with a wider band representing visible light

Tucker, 1979

MODIS

Moderate Resolution Imaging SpectroradiometerOnboard the Terra (EOS AM) and Aqua (EOS PM) satellites.

https://worldview.earthdata.nasa.gov/

● MODIS sees every point on Earth every 1-2 days (viewing swath: 2,330 km) in 36 discrete spectral bands.• Products:

– MODIS Level 1 data, geolocation, cloud mask, and Atmosphere products: http://ladsweb.nascom.nasa.gov/

– MODIS land products: https://lpdaac.usgs.gov/

– MODIS cryosphere products: http://nsidc.org/daac/modis/index.html

– MODIS ocean color and sea surface temperature products:http://oceancolor.gsfc.nasa.gov/

Lab 2 Learning OutcomesAfter this lab you should be able to…

● Locate and download MODIS and Land type data● Combine bands to create satellite images. ● Identify land cover types from Satellite images alone● Relate land cover and NDVI to precipitation

This lab is meant to teach you the basics of QGIS. It may require you to use other resources such as google maps to answer some of the questions.

● Download Landsat data for any region and time you want in the United States, just make sure it is cloud free. (Use the steps from Lab 1). You may use data from Lab 1.

● Combine bands to create one type of image you want. (Ex. True color, false color etc. Feel free to get creative)

● Go to the USGS national land cover viewer www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/introduction-land-cover-viewer

● Find the region of your Landsat data image.● Visually compare Landsat image and the land cover map, identify in the Landsat

imagery 3 regions corresponding to 3 different land cover types. The regions need to be homogeneous enough in terms of land cover type (little mixture, only one class) and wide enough (3-4 km in diameter) to provide meaningful NDVI statistics. Record the center latitude-longitude of each site on your notes.

● Create polygons around each of the small regions you selected These are called Regions of Interest (ROI). Use different coloring for each land type. Ensure the coloring is noticeable yet transparent enough to see through.

Question:1. Describe the Landsat image that you selected (region, date, bands), and the 3 land cover types that you picked (name, center location, land cover type).

Land Mask and Land Type

Download precipitation data from the nearest CDEC (should be early 2000 to March 2020) to your 3 selected ROI:

● Stations can be found here: http://cdec.water.ca.gov/cdecstation/ . Click on ‘Stations’ and select ‘Precipitation: Monthly’, then in the Station Locator, type in the lat/lon location to find the nearest station to the ROI.

● To download data: http://cdec.water.ca.gov/, Click on “Query Tools”, Click on “Historical (CSV format)” and use “General Data Download”. Put the previously found Station ID, Sensor number=2 (precipitation). Date Start 2000/01/01 - Date End March 2020.

● Make one graph for each region with precipitation on the y-axis and time on the x-axis. Add these to your lab report, you will use them later.

● Mark the location of the weather station in the Landsat imagery in QGIS using a small polygon, take a screenshot for inclusion in the report that shows the three regions and the location of the weather stations.

Precipitation Data

● Retrieve a NDVI (Normalized Difference Vegetation Index) time series for each of the 3 regions using the NASA MODIS subsetting tool website (https://modis.ornl.gov/sites/?id=us_california_ca_fallbrook_5_ne)

● Find the available site closest to your selected region and click the site. ● When the site information come up click the Green button “Subset Data and

Visualization”● Under “MODIS Collection 6” Click the MODIS product you want which is either NDVI

from MODIS/TERRA or MODIS/AQUA. ● Once you click the product you want the data will appear. This is where you can

download the data, however if you scroll below NASA has created some interactive visualizations which will be useful for this lab. Scroll down to the first graph which is NDVI.

● Copy/Screenshot the NDVI plot for each of your sites to include with the lab report.

MODIS Time Series Data

In addition to the questions answered in the lab, please answer the following and include them in your lab.

Questions…2. Explain why NDVI is useful for studying vegetation3. What are typical values you observe for the 3 regions, how they vary with time? (e.g. with season and inter-annually, whether NDVI reaches a maximum during the year or not, and why does this happen)4. Compare the NDVI time series with precipitation and discuss the results in 2 sentences for each site (correlation? No correlation? Why or why not?)

Please include all of the 4 lab questions and screenshots you took in your Lab 2 submission. Please make sure it is organized in a way that makes sense

Lab 2 Wrap-up Questions

Machine learning to classify land types using QGIS.

https://semiautomaticclassificationmanual-v5.readthedocs.io/en/latest/tutorial_1.html

Extra stuff