Assessing Impacts of a Climatologically Unique Year (1990) in the Midwest

Changnon, Stanley A.; Kunkel, Kenneth E.

doi:10.1080/02723646.1992.10642452

Cited by 4 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The median time-integrated NDVI is higher (3.13 vs. 2.76) and more variable as measured by the MADAM (0.285 vs. 0.409) in 1991, the year with an earlier greenup (Table 4). These results are consistent with statements by Changnon & Kunkel (1992) regarding the characteristics of 1990 weather patterns.…”

Section: Agricultural Cropssupporting

confidence: 92%

“…Phenological phenomena in nonirrigated agricultural areas are dependent on short-term weather events. Changnon & Kunkel (1992) pointed out, for example, that 1990 was an anomalous weather year in the Midwest, being both the warmest and wettest to date. Excessive precipitation from January through June in the Midwest delayed planting for several weeks.…”

Section: Phenological Characteristics Of Physiognomic Typesmentioning

confidence: 99%

See 1 more Smart Citation

Measuring phenological variability from satellite imagery

Reed¹,

Brown²,

VanderZee³

et al. 1994

J Vegetation Science

1,247

823

View full text Add to dashboard Cite

Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variability of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and predicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for largearea land cover mapping and monitoring. The utility of remotely sensed data as input to vegetation mapping is demonstrated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particularly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

show abstract

Section: Agricultural Cropssupporting

confidence: 92%

Section: Phenological Characteristics Of Physiognomic Typesmentioning

confidence: 99%

Measuring phenological variability from satellite imagery

Reed¹,

Brown²,

VanderZee³

et al. 1994

J Vegetation Science

1,247

823

View full text Add to dashboard Cite

show abstract

“…Our maps of the land-cover characteristics in the U.S. presented here are for 1990, hence they reflect climatic conditions in that year. As Changnon and Kunkel (1992) have pointed out, 1990 was an anomalous weather year in the midwest where it was both the warmest and wettest year on record. They also note that weather conditions across the country in 1990 were unusual.…”

Section: Understanding Seasonal Land-cover Characterizationmentioning

confidence: 99%

Seasonal Land-Cover Regions of the United States

Loveland

Merchant²,

Brown

et al. 1995

Annals of the Association of American Geographers

151

View full text Add to dashboard Cite

Global‐change investigations have been hindered by deficiencies in the availability and quality of land‐cover data. The U.S. Geological Survey and the University of Nebraska‐Lincoln have collaborated on the development of a new approach to land‐cover characterization that attempts to address requirements of the global‐change research community and others interested in regional patterns of land cover. An experimental 1 ‐kilometer‐resolution database of land‐cover characteristics for the coterminous U.S. has been prepared to test and evaluate the approach. Using multidate Advanced Very High Resolution Radiometer (AVHRR) satellite data complemented by elevation, climate, ecoregions, and other digital spatial datasets, the authors define 152, seasonal land‐cover regions. The regionalization is based on a taxonomy of areas with respect to data on land cover, seasonality or phenology, and relative levels of primary production. The resulting database consists of descriptions of the vegetation, land cover, and seasonal, spectral, and site characteristics for each region. These data are used in the construction of an illustrative 1:7,500,000‐scaIe map of the seasonal land‐cover regions as well as of smaller‐scale maps portraying general land cover and seasonality. The seasonal land‐cover characteristics database can also be tailored to provide a broad range of other landscape parameters useful in national and global‐scale environmental modeling and assessment.

show abstract

Warm Season Land Surface — Climate Interactions in the United States Midwest from Mesoscale Observations

Adegoke

Carleton

2000

Advances in Global Change Research

View full text Add to dashboard Cite

Assessing Impacts of a Climatologically Unique Year (1990) in the Midwest

Cited by 4 publications

References 5 publications

Measuring phenological variability from satellite imagery

Measuring phenological variability from satellite imagery

Seasonal Land-Cover Regions of the United States

Warm Season Land Surface — Climate Interactions in the United States Midwest from Mesoscale Observations

Contact Info

Product

Resources

About