Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue

The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere–biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997–1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources

Remote sensing for cover change assessment in southeast Arizona

Understanding landscape conversion is vital for assessing the impacts of ecological and anthropogenic disturbances at regional and global scales. Since rangelands cover nearly half of the global land surface, and because a large part of rangelands is located in semi-arid ecosystems, they serve as critical land cover types for determining regional biodiversity, global biogeochemical cycles, and energy and gas fluxes. For such vast ecosystems, satellite imagery is often used to inventory biophysical materials and man-made features on Earth's surface. The large area coverage and frequent acquisition cycle of remotely sensed satellite images make earth observation data useful for monitoring land conversion rates at different spatial scales. Remote sensing could also be used for temporal assessment of semi-arid ecosystems by providing complimentary sets of rangeland health indicators. In this paper, temporal satellite data from multiple sensors were examined to quantify land use and land cover change, and to relate spatial configuration and composition to landscape structure and pattern. The findings were correlated with the role of fire to better understand ecological functionality and human and/or natural activities that are generating environmental stressors in a rapidly developing, semi-urban census division located in southeastern Arizona. Results indicate that conversion of a fire-suppressed native grassland area has 2 spatial components; in the rural areas, grass is being eliminated by increasingly homogeneous shrub and mesquite-dominated areas, whereas in the urban and suburban areas, grass as well shrubs and mesquite are being eliminated by a fragmented and expanding built landscape.The Journal of Range Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202

Remote Distinction of A Noxious Weed (Musk Thistle: CarduusNutans) Using Airborne Hyperspectral Imagery and the Support Vector Machine Classifier

Remote detection of non-native invasive plant species using geospatial imagery may significantly improve monitoring, planning and management practices by eliminating shortfalls, such as observer bias and accessibility involved in ground-based surveys. The use of remote sensing for accurate mapping invasion extent and pattern offers several advantages, including repeatability, large area coverage, complete instead of sub-sampled assessments and greater cost-effectiveness over ground-based methods. It is critical for locating, early mapping and controlling small infestations before they reach economically prohibitive or ecologically significant levels over larger land areas. This study was designed to explore the ability of hyperspectral imagery for mapping infestation of musk thistle (Carduus nutans) on a native grassland during the preflowering stage in mid-April and during the peak flowering stage in mid-June using the support vector machine classifier and to assess and compare the resulting mapping accuracy for these two distinctive phenological stages. Accuracy assessment revealed that the overall accuracies were 79% and 91% for the classified images at preflowering and peak flowering stages, respectively. These results indicate that repeated detection of the infestation extent, as well as infestation severity or intensity, of this noxious weed in a spatial and temporal context is possible using hyperspectral remote sensing imagery