Characterizing a landscape using ecological sites and remote sensing
USDA ecological sites were designed to help with land management decisions at a smaller scale than landscapes. This can be problematic for most land managers. This project explores the potential for remote sensing to spatially, spectrally and temporally characterize land cover and vegetation structure of ecological sites in order to inform detection and management of changes in landscape condition. The project is utilizing 20 distinct sites across the grassland-forest gradient between North Dakota and Minnesota. This paper describes the process and results for an example site, Oakville Prairie that contains an area of undisturbed saline tall grass prairie. The area surrounding Oakville has largely been converted to cropland creating a highly structured landscape, bound and sectionalized by farmsteads and roads. Oakville and its surrounding landscape are differentiated into 15 ecological sites by the USDA. Multispectral Landsat 5 and 8 imagery spanning the time period from 1984 to 2014 is used to examine spectral and temporal components through the generation of several indices such as NDVI, MSAVI2, L-ATSAVI, PSRI, GVI and NDWI. Spatial structure within landscape was examined through a combination of LiDAR and aerial photos to create a composite image that can identify varying patch structures across the landscape.
The highest degree of variation of spectral indices of the ecological sites was found during late spring (May) due to the highly variable climate that is found with Northern Great Plains region. The seasonal pattern of spectral indices tracks the vegetation phenology with the highest NDVI occurring consistently in month of August. The Subirrigated Sands ecological class showed the greatest response to season fluctuations between years. It had the highest average August NDVI of 0.87 in 1996 while 1997 it 0.37 NDVI. Other ecological sites exhibited a similar pattern but with a lower amplitude. These yearly fluctuations are largely due to amount, rate, and time of the snow melt for the area. Spectral differences found among ecological sites may be related to differences in phenology and structure between patches of native vegetation, cropland, and invasive species. Discrimination of ecological sites with multispectral remote sensing is greatly enhanced by definition of sub-pixel variation, and fine scale patch structure with LIDAR and aerial photos. Multispectral remote sensing is particularly sensitive to inter- and intra-seasonal variation which may indicate changes in or transitions between vegetation states that are of interest to land managers.