Monitoring residual dry matter on rangelands with remote sensing

Tsalyuk, M., M. Kelly, K. Koy, W. M. Getz, and H. S. Butterfield. 2015. Monitoring the Impact of Grazing on Rangeland Conservation Easements Using MODIS Vegetation Indices. Rangeland Ecology and Management  68(2): 173–185

Residual dry matter (RDM), the dry grass biomass left on the ground in the fall, is a widely used proxy for rangeland conditions. We developed a method to efficiently monitor RDM using time series of three Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-based vegetation indices (VIs). We found a significant correlation between RDM and the VIs, especially the Leaf Area Index (LAI), which predicts compliance with RDM conservation easement terms.  Our rangeland management model uses time series of MODIS VIs to predict forage quantities, manage stocking rates, and monitor rangeland easement compliance, efficiently, rapidly, and reliably. Journal Link

Use of obia in public health - a review, and call for more

Kelly M., S. Blanchard. E. Kersten and K. Koy. 2011. Object-based analysis of imagery in support of public health: new avenues of research. Remote Sensing 3:2321-2345

The benefits of terrestrial remote sensing in the environmental sciences are clear across a range of applications, and increasingly remote sensing analyses are being integrated into public health research. This integration has largely been in two areas: first, through the inclusion of continuous remote sensing products such as normalized difference vegetation index (NDVI) or moisture indices to answer large-area questions associated with the epidemiology of vector-borne diseases or other health exposures; and second, through image classification to map discrete landscape patches that provide habitat to disease-vectors or that promote poor health. In this second arena, new improvements in object-based image analysis (or “OBIA”) can provide advantages for public health research. This paper provides a brief review of what has been done in the public health literature with continuous and discrete mapping, and then highlights the key concepts in OBIA that could be more of use to public health researchers interested in integrating remote sensing into their work.

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Cal-adapt is PE&RS cover story

June 2011 cover story on cal-adaptKoy,
 K.,
 S.
 V.
 Wart,
 B. Galey, 
M. 
O’Connor, 
and 
M. 
Kelly. 2011. 
Cal‐Adapt:
 Bringing
 global 
climate 
change 
data 
to 
local
 application. Photogrammetric Engineering and Remote Sensing 77(6): 546-550

June's PE&RS cover story features the Cal-Adapt web application developed by the GIF.  Cal-adapt has been developed to showcase the wealth of innovative climate change research being produced by the scientific community in California, as documented in the 2009 California Climate Adaptation Strategy. Through a combination of locally relevant information, visualization tools, and access to primary data, Cal-Adapt allows users to investigate how the climate is projected to change in their area of interest, and gives them tools to plan for these changes.

Our article can be found here.