Research on enhancing the utilization of digital multispectral data and geographic information systems in global habitability studies

During 1986 to 1987, the Kansas Applied Remote Sensing (KARS) Program continued to build upon long-term research efforts oriented towards enhancement and development of technologies for using remote sensing in the inventory and evaluation of land use and renewable resources (both natural and agricultural). These research efforts directly addressed needs and objectives of NASA's Land-Related Global Habitability Program as well as needs of and interests of public agencies and private firms. The KARS Program placed particular emphasis on two major areas: development of intelligent algorithms to improve automated classification of digital multispectral data; and integrating and merging digital multispectral data with ancillary data in spatial modes

Interrelationships Among Landscapes, NDVI, and Stream Water Quality in the US Central Plains

During late spring through summer of 1994 and 1995, 290 randomly selected stream sites in Nebraska, Kansas, and Missouri were sampled once for several parameters including conductivity, turbidity, total phosphorus, nitrate-nitrite nitrogen, the index of biotic integrity, and a habitat index. Based on landscape data from watersheds that were delineated for each sampling location, interrelationships were examined between these water quality parameters and land use/land cover, the normalized difference vegetation index (NDVI), and vegetation phenological metrics derived from the NDVI. Statistically significant relationships were found between NDVI values and the derived metrics with the stream condition parameters (r values to 0.8, alpha = 0.05). The NDVI or vegetation phenological metrics (VPMs) were more highly correlated to the selected stream condition parameters than were the land use/land cover proportions. Knowledge of the general land use/land cover setting within the watersheds, however, was important for interpreting these relationships. The most common variables associated with the stream data were early spring NDVI values or VPMs associated with the date of onset of greenness. These results demonstrate the utility of NDVI and VPMs as broad-scale environmental indicators of watershed conditions

Remote Sensing Tools for Statewide Management: Developing a Landsat 7 Imagery Database of Kansas

ABSTRACT The Kansas Applied Remote Sensing (KARS) Program of the Kansas Biological Survey (KBS) is developing a publicly available multi-seasonal statewide Landsat 7 data archive of Kansas. This opportunity became available for two reasons: a reduced cost in Landsat satellite imagery and the ability to freely distribute the data to the public. The archive will consist of precision rectified spring, summer, and fall Landsat 7 Enhanced Thematic Mapper (ETM+) imagery in formats easily accessible to end users. Each rectified scene is being subset to create a database tiled by county allowing end users to quickly and easily display their area of interest. Each county will have 15 (3 dates, 5 products) images/maps. This satellite archive will offer educational and research opportunities to government and non-government entities and individuals and enables state agencies to conduct statewide assessments. The Landsat 7 Imagery Archive also will address a variety of policies and programs identified in the Kansas State Water Plan (SWP), including identifying relationships between surface water quality and land use, identification and inventory of agricultural land use types that contribute to non-point source pollution, and providing current information about the location of structures and infrastructure that lie in the floodplain. This database will also be the basis for making REMOTE SENSING TOOLS FOR STATEWIDE MANAGEMENT: DEVELOPING A LANDSAT 7 IMAGERY DATABASE OF KANSAS * ACSM-ASPRS 2002 ANNUAL CONFERENCE PROCEEDINGS future updates to the Kansas Land Cover Map by exploring automated land use/land cover classification techniques in several pilot projects

Differences in onset of Greenness: A multitemporal analysis of Grass and Wheat

ABSTRACT The time when vegetation emerges (begins active photosynthesis) each year can be monitored using remotely sensed data obtained from Earth observation satellites. This measurement, called the onset of greenness, can be calculated using time series data sets of the Normalized Difference Vegetation Index (NDVI), a ratio of red and near infra-red (NIR) light that is strongly correlated to plant biomass. The date at which the onset of greenness occurs varies depending on the region, type of vegetation present, weather conditions, land management practices, and other factors. Time series NDVI data are proving useful for a wide variety of applications including vegetation mapping, crop monitoring, and yield modeling. The onset of greenness metric values were extracted from bi-weekly AVHRR satellite data over the state of Kansas from 1989 through 2000. Four different locations in Kansas were sampled: 1) winter wheat from Sumner County, 2) winter wheat from Thomas County, 3) tall grass rangeland from Chase County, and 4) short grass rangeland from Logan County. The onset date was recorded from 20 AVHRR pixels from each location for each year of data. Samples from the same location were analyzed to detect differences in onset date between years and samples from different locations were compared to identify differences in onset date within the same year. Results show a significant difference in the onset of greenness date between cover types and a significant difference in onset dates between years for the same cover type at the same location. Regression analysis shows that the grasslands and wheat of northwestern Kansas have a negative slope (earlier onset), while the lines of best fit for grasslands and wheat in south central Kansas did not indicate a substantial change in onset date

Examining Storage Capacity Loss and Sedimentation Rate of Large Reservoirs in the Central U.S. Great Plains

Reservoirs created by impounding sediment-laden streams infill over time, reducing storage capacity and altering water quality. Increasing freshwater demand on a limited supply is adding pressure on reservoir water storage and management across much of the western and central U.S. Determining sedimentation rates is helpful to ensure a reliable and sustainable clean water supply for drinking, irrigation and recreation purposes. In the state of Kansas, located in the central Great Plains, bathymetric surveys have been completed recently for many major state and federally constructed reservoirs. In this paper, we examine sediment infill rate and storage capacity loss for all 24 federally operated reservoirs in Kansas. As of 2016, these reservoirs have an average age of 52 years and collectively have lost approximately 17% of their original capacity, with the highest single-reservoir loss of 45%, the highest annual loss rate of 0.84%, and the highest annual sediment yield of 1688 m3/km2/year. Results from this paper provide baseline information pertinent to the development, prioritization and assessment of remediation and mitigation strategies for addressing the sediment infill problem in Kansas, with general implications for other large reservoirs across the Great Plains as well as other climatologically and ecologically similar regions around the world