How to Create NDVI Maps in ArcGIS

NDVI Maps in ArcGIS


What is NDVI?
Normalized Difference Vegetation Index or NDVI maps are being used in agriculture, forestry, ecology and more. But what is NDVI?

Healthy vegetation (or chlorophyll) reflects more near-infrared (NIR) and green light compared to other wavelengths. It absorbs more red and blue light.

This is why our eyes see vegetation as the color green. This is also why more near-infraredis reflected back into satellite sensors.

NDVI maps use NIR and red channels to measure of healthy vegetation.

NDVI Formula:
NDVI =

NDVI Definition:

NDVI is an index describing vegetation by showing the difference between near-infrared (which is strongly reflected by vegetation) and red light (which is absorbed by vegetation).

You can create NDVI maps with the image analysis toolbar in ArcGIS 10. All you need is imagery with red and NIR bands. Examples are Landsat, Quickbird and Worldview-2.

Related: USGS Earth Explorer: Download Free Landsat Imagery

How to create NDVI maps in ArcMap


The main objective is to classify high and low vegetation. This NDVI tutorial shows you step-by-step how to create NDVI maps in ArcMap.

In this NDVI example, we use Worldview-2 (WV-2). Worldview-2 is multispectral imagery. We say multispectral because it has red, green and blue – and other bands as well. The band configuration for WV-2 is:

Worldview-2 Band Configuration

Band 1: Coastal Band
Band 2: Blue
Band 3: Green
Band 4: Yellow
Band 5: Red
Band 6: Red Edge
Band 7: Near Infrared 1 (NIR-1)
Band 8: Near Infrared 2 (NIR-2)

To display true (visible) color composite, in layer properties – change the “Red” channel to band 5, “Green” channel to band 3 and the “Blue” channel to band 2. We say true colorbecause it is the same as how our eyes see.

True color composite – red, green, blue channels

To display near-infrared (NIR) false color composite, you need band 7 (NIR-1) as the “Red” channel, band 5 (red) as the “Green” channel, and 3 (green) as the “Blue” channel. We say near-infrared false color because this configuration uses NIR in the “Red” channel. The vegetation should already be shouting out at you in bright red!

Near-infrared false color composite – NIR-1, red and green channels

Step 1: Enable Image Analysis Toolbar

Enable the Image Analysis Toolbar (Windows > Image Analysis). The image analysis window will be displayed in ArcMap.

Image Analysis Toolbar

Step 2: Check Scientific Output Properties

Under image analysis options, select the red band and the near infrared band.



Image analysis toolbar options

For Worldview-2 imagery, under the NDVI tab – the red band is “band 5” and the NIR band is “band 7”.

NDVI band selection

Optionally select “Scientific Output” so your values range from -1 to 1.

Step 3: Click NDVI Icon

Highlight your layer by clicking it.



Highlight your image

Under properties, Select the NDVI icon which looks like a leaf.



NDVI button

This will create temporary layer in the table of contents.

NDVI temporary output

Step 4: Export Raster

Highlight the new NDVI layer that you want to export by selecting it in the image analysis toolbar.



Highlight NDVI raster

Right click layer, and export raster to save into memory.



Export raster

High positive NDVI values (green) means high vegetation. Urban and water will have negative NDVI values (yellow and red).

Where is NDVI being used?
NDVI maps have numerous uses and applications across different sectors.

• Agriculture: Precision farming, crop insurance fraud, biomass and food security
• Ecology: Animal migration patterns, environment change and population dynamics
• Forestry: Leaf area index, forest supply and fire danger

Learn more about NDVI and other remote sensing applications: 100 Earth Shattering Remote Sensing Applications & Uses



More information: NASA: Measuring Vegetation (NDVI & EVI)

Source

Mapping Current and Potential Distribution of Non-Native Prosopis juliflora in the Afar Region of Ethiopia

Article by: 

Tewodros T. Wakie , Paul H. Evangelista, Catherine S. Jarnevich, Melinda Laituri

Abstract

We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species- occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.

Full text here: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112854