• Mapping Total Vegetation Cover Across Western Rangelands With Moderate-Resolution Imaging Spectroradiometer Data

      Hagen, Stephen C.; Heilman, Philip; Marsett, Robert; Torbick, Nathan; Salas, William; van Ravensway, Jenni; Qi, Jiaguo (Society for Range Management, 2012-09-01)
      Remotely sensed observations of rangelands provide a synoptic view of vegetation condition unavailable from other means. Multiple satellite platforms in operation today (e.g. Landsat, moderate-resolution imaging spectroradiometer [MODIS]) offer opportunities for regional monitoring of rangelands. However, the spatial and temporal variability of rangelands pose challenges to consistent and accurate mapping of vegetation condition. For instance, soil properties can have a large impact on the reflectance registered at the satellite sensor. Additionally, senescent vegetation, which is often abundant on rangeland, is dynamic and its physical and photochemical properties can change rapidly along with moisture availability. Remote sensing has been successfully used to map local rangeland conditions. However, regional and frequently updated maps of vegetation cover in rangelands are not currently available. In this research, we compare ground measurements of total vegetation cover, including both green and senescent cover, to reflectance observed by the satellite and develop a robust method for estimating total vegetation canopy cover over diverse regions of the western United States. We test the effects of scaling from ground observations up to the Landsat 30-m scale, then to the MODIS 500-m scale, and quantify sources of noise. The soil-adjusted total vegetation index (SATVI) captures 55% of the variability in ground measured total vegetation cover from diverse sites in New Mexico, Arizona, Wyoming, and Nevada. Scaling from the Landsat to MODIS scale introduces noise and loss of spatial detail, but offers inexpensive and frequent observations and the ability to track trends in cover over large regions./Observaciones de pastizales con sensores remotos proporcionan una vista sin óptica de la condición de la vegetación que no está disponible usando otros medios. Múltiples plataformas satelitales en operación hoy en día (e.g. Landsat, MODIS) proporcionan oportunidades para un monitoreo regional de los pastizales. Sin embargo, la variabilidad espacial y temporal de los pastizales posee retos relacionados con el mapeo de la condición de la vegetación. Por ejemplo, las propiedades del suelo pueden tener gran impacto en la reflectancia registrada por el sensor del satélite. Adicionalmente, la vegetación senescente, lacual es a menudo abundante en los pastizales, es dinámica y sus propiedades físicas y fotoquímicas pueden cambiar rápidamente debido al contenido de humedad disponible. Los sensores remotos han sido utilizados con éxito para mapear las condiciones locales de los pastizales. Sin embargo, mapas regionales y frecuentemente actualizados de la cobertura de la vegetación en pastizales no están disponibles en la actualidad. En esta investigación, se compararon medidas del suelo del total de la cobertura, incluyendo ambas coberturas la verde y la senescente, contra la observada por el satélite para desarrollar un método robusto con la finalidad de estimar el total de la cobertura de la copa de la vegetación sobre la diversa región del Oeste de estado Unidos. Se evaluaron los efectos de escala desde observaciones al ras de suelo hasta aquellas usando Landsat auna escala de 30 m, entonces a la escala de 500 m en MODIS y se cuantificaron las fuentes de variación. El índice ajustado total de vegetación (SATV) captura 55% de la variabilidad en la estimación del total de la cobertura vegetal de diversos sitios en Nuevo México, Arizona, Wyoming, y Nevada. La conversión de escala de Landsat a MODIS introduce cierto margen de error y pérdida de detalle espacial, pero ofrece observaciones baratas y frecuentes así como la capacidad de rastrear las tendencias en cobertura sobre extensas regiones.
    • Remote Sensing for Grassland Management in the Arid Southwest

      Marsett, Robert C.; Qi, Jiaguo; Heilman, Philip; Biedenbender, Sharon H.; Watson, Carolyn M.; Amer, Sand; Weltz, Mark; Goodrich, David; Marsett, Roseann (Society for Range Management, 2006-09-01)
      We surveyed a group of rangeland managers in the Southwest about vegetation monitoring needs on grassland. Based on their responses, the objective of the RANGES (Rangeland Analysis Utilizing Geospatial Information Science) project was defined to be the accurate conversion of remotely sensed data (satellite imagery) to quantitative estimates of total (green and senescent) standing cover and biomass on grasslands and semidesert grasslands. Although remote sensing has been used to estimate green vegetation cover, in arid grasslands herbaceous vegetation is senescent much of the year and is not detected by current remote sensing techniques. We developed a ground truth protocol compatible with both range management requirements and Landsat’s 30 m resolution imagery. The resulting ground-truth data were then used to develop image processing algorithms that quantified total herbaceous vegetation cover, height, and biomass. Cover was calculated based on a newly developed Soil Adjusted Total Vegetation Index (SATVI), and height and biomass were estimated based on reflectance in the near infrared (NIR) band. Comparison of the remotely sensed estimates with independent ground measurements produced r2 values of 0.80, 0.85, and 0.77 and Nash Sutcliffe values of 0.78, 0.70, and 0.77 for the cover, plant height, and biomass, respectively. The approach for estimating plant height and biomass did not work for sites where forbs comprised more than 30% of total vegetative cover. The ground reconnaissance protocol and image processing techniques together offer land managers accurate and timely methods for monitoring extensive grasslands. The time-consuming requirement to collect concurrent data in the field for each image implies a need to share the high fixed costs of processing an image across multiple users to reduce the costs for individual rangeland managers.