Seasonal Land-Cover Regions of the United States

Abstract

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.

Performance of the MISR LAI and FPAR algorithm: a case study in Africa

“…The kappa coefficient (j) (Cohen, 1960), which provides a correction for the proportion of chance agreement between reference and test data, is 0.68 (Lotsch et al, 2003). When compared to maps generated from the same data but classified using the International Geosphere Biosphere Program (IGBP) classes (Hansen, Defries, Townshend, & Sohlberg, 2000;Loveland et al, 1995), the biomes were mapped with f 5% higher overall accuracy (Lotsch et al, 2003). It should be noted that this classification accuracy analysis is based on sites that are a priori pure and therefore will not include errors due to sub-pixel mixing.…”

Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data

“…Continuing research into the spatio-temporal phenological patterns of sky islands could assist in the conservation of these areas as biodiversity hotspots. Additionally, mapping of vegetation communities based on phenology could allow for the accounting of interannual and seasonal landscape-scale community responses to interacting environmental factors [67]. dominant vegetation types along the elevation gradient in the Santa Rita Mountains, AZ, USA.…”

Comparison between Vegetation and Rainfall of Bioclimatic Ecoregions in Central Africa

“…Satellite-derived vegetation indices are being integrated in interactive biosphere models as part of global climate modeling [2][3][4][5] and production efficiency models [6,7]. The Normalized Difference Vegetation Index (NDVI) is a satellite-based vegetation index, which is commonly used and based on the differential reflection of green vegetation in the visible and infrared portions of the magnetic spectrum [8][9][10][11][12]. A large number of studies have investigated the NDVI pattern over the world.…”