The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.; Brown, Jesslyn F.

doi:10.1080/17538947.2013.860196

Cited by 20 publications

(17 citation statements)

References 34 publications

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“…The cheatgrass start of spring growth model produced a spatially dynamic phenology guideline to parameterize the cheatgrass growing season (Boyte et al 2013). Because of the seasonality of cheatgrass response to weather and the study area's relatively wide elevational and latitudinal ranges, this model's strong use of certain weather variables in the prediction algorithm was expected.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…A regression-tree model was built that predicts annual cheatgrass start of spring growth based on cheatgrass-dominated pixel characteristics (Boyte et al 2013). The model was trained on 939 points where either 2001 data or 2006 data from the Nevada Natural Heritage Program 4 indicated that 30% or more cheatgrass or annual grass cover existed.…”

Section: Cheatgrass Start Of Spring Growthmentioning

confidence: 99%

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Mapping and Monitoring Cheatgrass Dieoff in Rangelands of the Northern Great Basin, USA

Boyte

Wylie

Major

2015

Rangeland Ecology & Management

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Section: Accepted Manuscriptmentioning

confidence: 99%

Section: Cheatgrass Start Of Spring Growthmentioning

confidence: 99%

Mapping and Monitoring Cheatgrass Dieoff in Rangelands of the Northern Great Basin, USA

Boyte

Wylie

Major

2015

Rangeland Ecology & Management

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“…The resulting relationship between the smoothed curve and the original data is statistically based [18]. The smoothed data can then be applied to various research and operational activities, such as identifying the presence of invasive species, characterizing phenological events, examining vegetation productivity and carbon flux dynamics, and capturing drought timing and severity [5,16,[19][20][21][22][23].…”

Section: Temporal Ndvi Filteringmentioning

confidence: 99%

Application-Ready Expedited MODIS Data for Operational Land Surface Monitoring of Vegetation Condition

et al. 2015

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Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An "expedited" processing system called "eMODIS" operated by the U.S. Geological Survey provides rapid MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1), the eMODIS Normalized Difference Vegetation Index (NDVI) maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra) or afternoon (Aqua) orbits. The Aqua eMODIS data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in eMODIS data.

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“…Despite the size and importance of US rangelands, disturbances, such as grazing and wildfire, accompanied by drought resulted in loss of native plant materials, weed invasion, and destabilization of soil resources through erosion and changing nutrient and water cycles (Norton, Monaco, & Norton, 2007). For example, because of such disturbances approximately 2 M ha, or 10%, of the Great Basinthe largest North American desertare now dominated by the annual grass Bromus tectorum L. with additional millions of hectares infested by this and other undesirable annual species (Boyte, Wylie, Major, & Brown, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparison of space‐plant versus sward plot selection in thickspike wheatgrass (Elymus lanceolatus)

Robins

Jensen

2018

Plant Breeding

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Thickspike wheatgrass (Elymus lanceolatus [Scribn. & J.G. Sm.] Gould) is an important native perennial grass species used for rangeland revegetation in North America. Plant breeding efforts relying on space‐plant evaluations have resulted in limited improvement in this species. The purpose of this study was to characterize the performance of thickspike wheatgrass half‐sib families under space‐plant and sward plot evaluations, estimate the correlation between measured traits in both evaluation settings, and determine the validity of selecting thickspike wheatgrass for rangeland revegetation in the nontarget environment space‐plant plots. The study included 50 thickspike wheatgrass half‐sib families and five commercial cultivars and experimental populations which were evaluated over 3 years in space‐plant and sward plot evaluations at a field site in Box Elder County, Utah, USA. Collected data included stand percentage, flag leaf height, and herbage dry mass. Narrow‐sense heritability estimates were low to moderate (h2 < 0.60) and Spearman and genetic correlation estimates among traits were also generally low to moderate. Overall, there was little evidence to suggest the use space‐plant evaluations in thickspike wheatgrass improvement programmes.

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The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

Cited by 20 publications

References 34 publications

Mapping and Monitoring Cheatgrass Dieoff in Rangelands of the Northern Great Basin, USA

Mapping and Monitoring Cheatgrass Dieoff in Rangelands of the Northern Great Basin, USA

Application-Ready Expedited MODIS Data for Operational Land Surface Monitoring of Vegetation Condition

Comparison of space‐plant versus sward plot selection in thickspike wheatgrass (Elymus lanceolatus)

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