27 research outputs found

    Amazon Forests Green-Up During 2005 Drought

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    Vegetation‐groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data

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    Because groundwater recharge in dry regions is generally low, arid and semiarid environments have been considered well-suited for long-term isolation of hazardous materials (e.g., radioactive waste). In these dry regions, water lost (transpired) by plants and evaporated from the soil surface, collectively termed evapotranspiration (ET), is usually the primary discharge component in the water balance. Therefore, vegetation can potentially affect groundwater flow and contaminant transport at waste disposal sites. We studied vegetation health and ET dynamics at a Uranium Mill Tailings Radiation Control Act (UMTRCA) disposal site in Shiprock, New Mexico, where a floodplain alluvial aquifer was contaminated by mill effluent. Vegetation on the floodplain was predominantly deep-rooted, non-native tamarisk shrubs (Tamarix sp.). After the introduction of the tamarisk beetle (Diorhabda sp.) as a biocontrol agent, the health of the invasive tamarisk on the Shiprock floodplain declined. We used Landsat normalized difference vegetation index (NDVI) data to measure greenness and a remote sensing algorithm to estimate landscape-scale ET along the floodplain of the UMTRCA site in Shiprock prior to (2000-2009) and after (2010-2018) beetle establishment. Using groundwater level data collected from 2011 to 2014, we also assessed the role of ET in explaining seasonal variations in depth to water of the floodplain. Growing season scaled NDVI decreased 30% (p <.001), while ET decreased 26% from the pre- to post-beetle period and seasonal ET estimates were significantly correlated with groundwater levels from 2011 to 2014 (r(2) =.71; p =.009). Tamarisk greenness (a proxy for health) was significantly affected by Diorhabda but has partially recovered since 2012. Despite this, increased ET demand in the summer/fall period might reduce contaminant transport to the San Juan River during this period.Public domain articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

    Global EVI from Spring to Winter

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    Traditional satellite-based mapping of vegetation vigor and amount is based on the way vegetation interacts with red and infrared light. Occasionally, however, those two signals are not enough. MODIS measures light reflected from Earth at a variety of wavelengths, and the Arizona researchers incorporate the additional information into their Enhanced Vegetation Index (EVI). The EVI has increased sensitivity within very dense vegetation, and it has built-in corrections for several factors that can interfere with the satellite-based vegetation mapping, like smoke and background noise caused by light reflecting off soil. The bi-weekly and monthly vegetation index maps have wide usability by biologists, natural resources managers, and climate modelers. They can track naturally occurring fluctuations in vegetation, such as seasonal changes, as well as those that result from land use change, such as deforestation. The EVI can also monitor changes in vegetation resulting from climate change, such as expansion of deserts or extension of growing seasons. Educational levels: Undergraduate lower division, Undergraduate upper division, Graduate or professional

    United States EVI from Summer, 2000 to Spring, 2001.

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    Traditional satellite-based mapping of vegetation vigor and amount is based on the way vegetation interacts with red and infrared light. Occasionally, however, those two signals are not enough. MODIS measures light reflected from Earth at a variety of wavelengths, and the Arizona researchers incorporate the additional information into their Enhanced Vegetation Index (EVI). The EVI has increased sensitivity within very dense vegetation, and it has built-in corrections for several factors that can interfere with the satellite-based vegetation mapping, like smoke and background noise caused by light reflecting off soil. The bi-weekly and monthly vegetation index maps have wide usability by biologists, natural resources managers, and climate modelers. They can track naturally occurring fluctuations in vegetation, such as seasonal changes, as well as those that result from land use change, such as deforestation. The EVI can also monitor changes in vegetation resulting from climate change, such as expansion of deserts or extension of growing seasons. Educational levels: Undergraduate lower division, Undergraduate upper division, Graduate or professional

    The association between the incidence of Lyme disease in the USA and indicators of greenness and land cover

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    Lyme disease (LD) is the most common vector-borne illness in the USA. Incidence is related to specific environmental conditions such as temperature, metrics of land cover, and vertebrate species diversity. To determine whether greenness, as measured by the Normalized Difference Vegetation Index (NDVI), and other selected indices of land cover were associated with the incidence of LD in the northeastern USA for the years 2000–2018, we conducted an ecological analysis of incidence rates of LD in counties of 15 “high” incidence states and the District of Columbia for 2000–2018. Annual counts of LD by county were obtained from the US Centers for Disease Control and values of NDVI were acquired from the Moderate Resolution Imaging Spectroradiometer instrument aboard Terra and Aqua Satellites. County-specific values of human population density, area of land and water were obtained from the US Census. Using quasi-Poisson regression, multivariable associations were estimated between the incidence of LD, NDVI, land cover variables, human population density, and calendar year. We found that LD incidence increased by 7.1% per year (95% confidence interval: 6.8–8.2%). Land cover variables showed complex non-linear associations with incidence: average county-specific NDVI showed a “u-shaped” association, the standard deviation of NDVI showed a monotonic upward relationship, population density showed a decreasing trend, areas of land and water showed “n-shaped” relationships. We found an interaction between average and standard deviation of NDVI, with the highest average NDVI category; increased standard deviation of NDVI showed the greatest increase in rates. These associations cannot be interpreted as causal but indicate that certain patterns of land cover may have the potential to increase exposure to infected ticks and thereby may contribute indirectly to increased rates of LD. Public health interventions could make use of these results in informing people where risks may be high

    ESTIMATION OF THE FRACTION OF CANOPY COVER FROM MULTISPECTRAL DATA TO BE USED IN A WATER SOIL EROSION PREDICTION MODEL

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    Using the 16 day MODIS (aboard the EOS Terra satellite) 250m NDVI and ground biophysical and spectral measurements we established simple relationships between these parameters and the canopy cover. The canopy cover is used in water erosion models to estimate the amount of soil loss under precipitation events and specific geographic conditions. Two transects, in the grassland part of the Walnut Gulch Experimental Watershed (WGEW) located near the town of Tombstone in Arizona, were established for ground data collection. Ground measurements were performed every 16 days, to coincide with the Terra Satellite overpass. Erosion, in desert environment is a contributing factor to soil degradation and subsequently desertification. Erosion is strongly related with canopy cover, soil parameters, topography, and climate variables. Although ground point estimates of canopy cover are usually used in erosion models, their temporal and spatial variability need to be accounted for. Using MODIS NDVI data, calibrated with field measurements, we were able to estimate the canopy cover using regression analysis. This technique is very simple and properly accounts for the spatial and temporal variability of the canopy cover. We tested this technique with the WEPP erosion model and we found it to be very valuabl
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