Russian River NDVI (Normalized Difference Vegetation Index) Methodology and Use, California Completed
In 2013, the SCWA updated the crop field GIS mapping in the watershed last completed in 2009. To facilitate the heads-up digitizing of crop fields, the SCWA developed a “screening tool” layer to identify changes in vegetation from the previous imagery to the most recent. The SCWA’s screening tool helped by highlighting changes using NDVI to track land use changes from 2006 to 2012. The SCWA calculated NDVI using the ArcMap NDVI function for two Landsat scenes from August 2006 and 2011. Imagery for the month of August was chosen because of reduced cloud cover as well as being far into the growing season.
In 2013, the SCWA updated the crop field GIS mapping in the watershed last completed in 2009. To facilitate the heads-up digitizing of crop fields, the SCWA developed a “screening tool” layer to identify changes in vegetation from the previous imagery to the most recent. The SCWA’s screening tool helped by highlighting changes using NDVI to track land use changes from 2006 to 2012. The SCWA calculated NDVI using the ArcMap NDVI function for two Landsat scenes from August 2006 and 2011 (fig. 1). Imagery for the month of August was chosen because of reduced cloud cover as well as being far into the growing season. These NDVI data sets were compared to aerial imagery from 2005 and 2012 to confirm that different vegetation was represented by different values. The “screening tool” layer that helped guide the staff to vegetative changes between the two years was calculated based on the difference between the 2006 and 2011 NDVI values. An iterative process was used to establish the criteria for identifying whether significant change was observed over the intermittent period (Todd Schram, Sonoma County Water Agency, oral commun. and written commun., 2013).
References:
Todd Schram, Agency Engineer, Water Resources Planning, Sonoma County Water Agency, California.
Case Studies of Landsat Imagery Use
- Overview
In 2013, the SCWA updated the crop field GIS mapping in the watershed last completed in 2009. To facilitate the heads-up digitizing of crop fields, the SCWA developed a “screening tool” layer to identify changes in vegetation from the previous imagery to the most recent. The SCWA’s screening tool helped by highlighting changes using NDVI to track land use changes from 2006 to 2012. The SCWA calculated NDVI using the ArcMap NDVI function for two Landsat scenes from August 2006 and 2011. Imagery for the month of August was chosen because of reduced cloud cover as well as being far into the growing season.
In 2013, the SCWA updated the crop field GIS mapping in the watershed last completed in 2009. To facilitate the heads-up digitizing of crop fields, the SCWA developed a “screening tool” layer to identify changes in vegetation from the previous imagery to the most recent. The SCWA’s screening tool helped by highlighting changes using NDVI to track land use changes from 2006 to 2012. The SCWA calculated NDVI using the ArcMap NDVI function for two Landsat scenes from August 2006 and 2011 (fig. 1). Imagery for the month of August was chosen because of reduced cloud cover as well as being far into the growing season. These NDVI data sets were compared to aerial imagery from 2005 and 2012 to confirm that different vegetation was represented by different values. The “screening tool” layer that helped guide the staff to vegetative changes between the two years was calculated based on the difference between the 2006 and 2011 NDVI values. An iterative process was used to establish the criteria for identifying whether significant change was observed over the intermittent period (Todd Schram, Sonoma County Water Agency, oral commun. and written commun., 2013).
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Todd Schram, Agency Engineer, Water Resources Planning, Sonoma County Water Agency, California.
- Science
Case Studies of Landsat Imagery Use
Having access to Landsat imagery provides the irreplaceable opportunity to observe landscape change on a long-term and global scale. These featured case studies demonstrate the value of Landsat imagery by providing specific examples of how people around the world are using the data to answer meaningful questions. - Partners