Dana L. Peterson

Discriminating between cool season and warm season grassland cover types in northeastern Kansas

This study assesses the ability of multitemporal Landsat Thematic Mapper (TM) data and the normalized difference vegetation index (NDVI) to spectrally separate grazed cool season and warm season grassland cover types in Douglas County, Kansas. Biophysical data collected during the summer of 1997 suggest that differences in the per cent of total living vegetation cover, per cent of senescent vegetation, and proportion of forb cover between the two grassland cover types could make cool season and warm season grassland cover types spectrally distinct. The results show that the two grassland cover types were spectrally different in several spring (May) and mid-summer (July) bands, but not in any fall (September) bands. Furthermore, the two grassland cover types could be discriminated with a high level of accuracy. Accuracy assessments of the three single dates showed that the mid-summer (July) image and NDVI discriminated between the grassland cover types most accurately (81.8%). The multitemporal TM and NDVI data did not improve the spectral discrimination of the two grassland cover types over the mid-summer image or NDVI and had classification accuracy levels of 63.6% and 68.2%, respectively.

Identifying historical and recent land-cover changes in Kansas using post-classification change detection techniques

Abstract Statewide land-cover change detection analysis provides a useful tool for conservation planning and environmental monitoring and addresses issues of habitat fragmentation and urban sprawl. Furthermore, land-cover data offer a historical and recent perspective on landscape dynamics. To this end, the first alliance level land-cover map of Kansas (Kansas Vegetation Map) recently completed by the KARS Program was compared to Küchlers Potential Natural Vegetation map and the 1993 Kansas Land Cover Patterns map. The post-classification change detection technique was used along with co-occurrence matrices to identify areas and directions of land-cover change. Comparisons showed that the land cover of Kansas has changed drastically since European settlement. Over 48% of the land is now cultivated and native vegetation types such as tallgrass and shortgrass prairie have been reduced dramatically in area. There are, however, millions of ha of these vegetation types remaining in Kansas. Comparisons between the two recent land-cover maps reveal that over 80% of the land in Kansas has remained unchanged in the five years between map development. Recent land-cover changes include conversion of grassland to cropland, cropland to grassland, and grassland to woodland. Many areas changing from cropland to grassland have been identified as land being enrolled in the Conservation Reserve Program (CRP). Post-classification change detection analysis also shows that forest and woodland types have increased over the five-year period and over 1 million ha of grassland have been converted to cropland. The magnitude of increases in woodland and forest is questionable, however, and may be due to registration errors and classification methodologies used to generate the land-cover maps.

Investigating Grazing Intensity and Range Condition of Grasslands in Northeastern Kansas Using Landsat Thematic Mapper Data

Abstract Grazing changes plant species composition of grassland ecosystems by selective removal and trampling. Grazing also alters soil physical and biogeochemical properties and can dramatically change hydrologic processes that can impact water budgets and quality. For these reasons, practical means are needed to assess grazing management practices and its impacts upon the land. This study examines whether a grazing intensity and range condition gradient can be detected in spectral reflectance characteristics of grasslands in northeastern Kansas. Multitemporal Landsat Thematic Mapper (TM) data, the normalized difference vegetation index (NDVI), and field data collected concurrent with the TM overpasses, were used in the analysis. Correlation analysis was used to examine relationships between spectral data and biophysical data. Next, the study sites within each grassland type were classified into three spectrally similar clusters. Grazing intensity, range condition, and biophysical characteristics were summarized for each spectral cluster and compared. The results suggest that NDVI may be used as a surrogate for living biomass for both grassland types and may be useful for predicting grazing intensity in native warm season grasslands. And while there appeared to be relationships between total living and non‐living cover, and TM NIR and MIR bands, there were no direct relationships between spectral characteristics and grazing intensity or range condition.

Ecological niche modeling of Black-tailed prairie dog habitats in Kansas

Abstract Black-tailed prairie dog (BTPD) (Cynomys ludovicianus) populations in Kansas have declined significantly due to both natural and human-induced threats. To minimize the risk of future population declines, it is necessary to identify existing BTPD habitats in the state as well as areas suitable for BTPD habitat. This paper presents a method for modeling BTPD habitats in Kansas using geographic information systems (GIS), remote sensing, and ecological niche modeling with the Genetic Algorithm for Rule-Set Prediction (GARP). Environmental variables incorporated into the ecological niche modeling process include composite biweekly Normalized Difference Vegetation Index (NDVI) layers derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery, slope, soil depth, and soil texture. Species occurrence training and validation data were selected from an aerial survey of BTPD colonies by the Kansas Department of Wildlife and Parks (KDWP). Accuracy assessment methods, including Receiver Operating Characteristic (ROC) analysis, omission calculation, and validation with an independent BTPD colony dataset collected for the Cimarron National Grassland in Morton County, indicate a high degree of accuracy for the GARP models. A map of BTPD habitat suitability produced by the ecological niche modeling has the potential to aid state agencies and organizations in their efforts to prevent further population declines in the species.