A Protocol for Retrospective Remote Sensing–Based Ecological Monitoring of Rangelands

Abstract

The degree of rangeland degradation in the United States is unknown due to the failure of traditional field-based monitoring to capture the range of variability of ecological indicators and disturbances, including climatic effects and land use practices, at regional to national spatial scales, and temporal scales of decades. Here, a protocol is presented for retrospective monitoring and assessment of rangeland degradation using historical time series of remote sensing data and catastrophe theory as an ecological framework to account for both gradual and rapid changes of state. This protocol 1) justifies the use of time-series satellite imagery in terms of the spatial and temporal scale of data collection; 2) briefly explains how to acquire, process, and transform the data into ecological indicators; 3) discusses the use of time-series analysis as the appropriate procedure for detecting significant change; and 4) explains what reference conditions are appropriate. Landsat data have been collected and archived since 1972, and include complete coverage of US rangelands. Characteristics of land degradation can be retrospectively measured for a nearly 33-year trend using surrogate remote sensing-based indicators that correlate with changes in life-form composition (time series of thematic maps), declines in vegetation productivity (vegetation indices), accelerated soil erosion (soil indices), declines in soil quality (piospheric analysis), and changes in landscape configuration (time series of thematic maps). Aspects of 2 retrospective studies are presented as examples of application of the protocol to considerations of the land use impacts from military training and testing and ranching activities on rangelands. Resumen El grado de degradació n de los pastizales en los Estados Unidos de América es desconocido debido al fracaso del monitoreo tradicional de campo para capturar el rango de variabilidad de los indicadores ecoló gicos y disturbios, incluyendo los efectos climáticos y prácticas de uso de la tierra, a escalas espaciales de regional a nacional y escalas temporales de décadas. Consecuentemente, es presentado un protocolo para el monitoreo retrospectivo y la evaluació n de la degradació n de los pastizales usando series de tiempo histó ricas de sensores remotos y la teoría de catástrofe como un marco ecoló gico para cuantificar tanto los cambios graduales como los rápidos del estado del pastizal. Este protocolo: 1) justifica el uso de series de tiempo de imágenes de satélite en términos de escalas espacial y temporal de colecció n de datos; 2) explica brevemente como adquirir, procesar y transformar los datos en indicadores ecoló gicos; 3) discute el uso del análisis de series de tiempo como un procedimiento adecuado para detectar cambios significativos; y 4) explica que condiciones de referencia son apropiadas. Datos de Landsat han sido colectados y archivados desde 1972 e incluyen una cobertura completa de los pastizales de Estados Unidos de América. Las características de la degradació n de la tierra pueden...

Time Series Analysis of Land Cover Change: Developing Statistical Tools to Determine Significance of Land Cover Changes in Persistence Analyses

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“…This approach provides a comparative basis for time series behaviors, such as -stable‖, -increasing‖ or -decreasing‖, relative to the selected benchmark. The approach permits an assessment of ecological resilience, or system response, [39] to some disturbance [38]. However, within this framework there is still a need to determine the relevance of detected changes and ultimately their statistical significance [24].…”

“…Together, some or all of these persistence metrics at a pixel level scale, applied to monthly time series of up to 30 years, yield a more detailed understanding of landscapes [24]. Application of these techniques to remote sensing facilitates the identification of areas across the landscape in which statistically significant changes have occurred, and, within the concept of benchmark conditions [38], provides insight into the ecological resilience in the region. The potential power and utility of such techniques is diverse within the area of LCS and remote sensing studies, particularly in the context of global change studies.…”

Interannual Variability in Dry Mixed-Grass Prairie Yield: A Comparison of MODIS, SPOT, and Field Measurements

“…Many vegetation indices have been established from remotely sensed data. These indices provide proxies for vegetation biophysical properties, and can be used to diagnose rangeland conditions and trends [27,28]. The most commonly used vegetation index is the Normalized Difference Vegetation Index (NDVI) [21,29].…”