Correcting satellite data to detect vegetation signal for eco-hydrologic analyses

Groeneveld, David P.; Baugh, W.

doi:10.1016/j.jhydrol.2007.07.001

Cited by 56 publications

(34 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a surrogate measure of the vegetation vigor and productivity of plants, normalized difference vegetation index (NDVI) is another estimator of plant response to water deficit [9]. This index is calculated from the red (R Red ) and near-infrared (R NIR ) reflectance from vegetation (Equation (1)).…”

Section: Introductionmentioning

confidence: 99%

Reduction in Water Stress for Tree Saplings Using Hydrogels in Soil

Kargar¹,

Suresh²,

Legrand³

et al. 2017

GEP

View full text Add to dashboard Cite

The effect of soil amendment with hydrogel on reducing water stress was tested for Siberian elm (Ulmus pumila) and silver maple (Acer saccharinum) saplings. The trees were planted in soils with one of two concentrations of hydrogel (0.5% or 1% dry weight) as compared to the control soil (0% of hydrogel) and watered either daily, weekly, or bi-weekly. Growth was monitored by measuring height and stem diameter. Stress was monitored by measuring SPAD readings and normalized difference vegetation index (NDVI), as proxy measures of chlorophyll content and photosynthetic activity, respectively. Water stress decreased NDVI (p < 0.05) but did not have a significant effect on SPAD readings. Soil with 0.5% concentration of hydrogel was positively associated with greater height and NDVI (p < 0.01) for both maple and elm trees. Hydrogels had a species-specific effect on SPAD readings. The interaction between hydrogel concentration and the watering regime had a significant effect on the height and NDVI (p < 0.01) of elms, but not maples. The improved performance of water-stressed tree saplings in hydrogel-amended soils was presumably due to the ability of hydrogels to absorb and then gradually release water and nutrients. This is of special interest for urban foresters, because water stress and nutrient deficiency are two important growthlimiting factors for street trees.

show abstract

Section: Introductionmentioning

confidence: 99%

Reduction in Water Stress for Tree Saplings Using Hydrogels in Soil

Kargar¹,

Suresh²,

Legrand³

et al. 2017

GEP

View full text Add to dashboard Cite

show abstract

“…The Single-Satellite-Scene (SSS) is a simple method of estimating annual riparian ET based on just one mid-summer satellite image and some ground-based meteorological data [35,36]. In this method, the annual riparian ET is a function of NDVI*, reference ET (ET o ), and precipitation as:…”

Section: Single-satellite-scene (Sss) Apporachmentioning

confidence: 99%

“…The conversion of NDVI to NDVI* is performed to remove the variations inherent in this parameter caused by atmospheric, soil, and vegetation factors [36,44,45], making it possible to use NDVI estimated by different sensors at different times and locations. The selection of NDVI o and NDVI s is a critical step.…”

Section: Single-satellite-scene (Sss) Apporachmentioning

confidence: 99%

“…The selection of NDVI o and NDVI s is a critical step. These parameters are estimated by developing a cumulative frequency distribution graph of NDVI values for the selected scene [36]. At the low end of this graph, the relationship (NDVI vs. cumulative pixel count) becomes asymptotic and choosing an appropriate NDVI o becomes subjective [36].…”

Section: Single-satellite-scene (Sss) Apporachmentioning

confidence: 99%

“…These parameters are estimated by developing a cumulative frequency distribution graph of NDVI values for the selected scene [36]. At the low end of this graph, the relationship (NDVI vs. cumulative pixel count) becomes asymptotic and choosing an appropriate NDVI o becomes subjective [36]. To minimize such subjectivity, a line is fitted to the near-linear lower portion of the NDVI cumulative frequency distribution and the x-intercept of the fitted line is taken as NDVI o .…”

Section: Single-satellite-scene (Sss) Apporachmentioning

confidence: 99%

See 2 more Smart Citations

Mapping Annual Riparian Water Use Based on the Single-Satellite-Scene Approach

2017

View full text Add to dashboard Cite

Abstract:The accurate estimation of water use by groundwater-dependent riparian vegetation is of great importance to sustainable water resource management in arid/semi-arid regions. Remote sensing methods can be effective in this regard, as they capture the inherent spatial variability in riparian ecosystems. The single-satellite-scene (SSS) method uses a derivation of the Normalized Difference Vegetation Index (NDVI) from a single space-borne image during the peak growing season and minimal ground-based meteorological data to estimate the annual riparian water use on a distributed basis. This method was applied to a riparian ecosystem dominated by tamarisk along a section of the lower Colorado River in southern California. The results were compared against the estimates of a previously validated remotely sensed energy balance model for the year 2008 at two different spatial scales. A pixel-wide comparison showed good correlation (R 2 = 0.86), with a mean residual error of less than 104 mm·year −1 (18%). This error reduced to less than 95 mm·year −1 (15%) when larger areas were used in comparisons. In addition, the accuracy improved significantly when areas with no and low vegetation cover were excluded from the analysis. The SSS method was then applied to estimate the riparian water use for a 23-year period . The average annual water use over this period was 748 mm·year −1 for the entire study area, with large spatial variability depending on vegetation density. Comparisons with two independent water use estimates showed significant differences. The MODIS evapotranspiration product (MOD16) was 82% smaller, and the crop-coefficient approach employed by the US Bureau of Reclamation was 96% larger, than that from the SSS method on average.

show abstract