The responses of vegetation water content (EWT) and assessment of drought monitoring along a coastal region using remote sensing

Gao, Zhiqiang; Wang, Qiuxian; Cao, Xiaoming; Gao, Wei

doi:10.1080/15481603.2014.882564

Cited by 27 publications

(16 citation statements)

References 25 publications

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“…Peñuelas et al [8, 9] used plant water content and the leaf relative water content to test the model developed from spectral reflectance data. At a canopy level and in larger scales, the quantification is more often expressed as equivalent water thickness (EWT) and canopy water content (CWC) [10, 11].…”

Section: Introductionmentioning

confidence: 99%

Assessment of plant water status in winter wheat (Triticum aestivum L.) based on canopy spectral indices

et al. 2019

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Rapid and non-destructive estimation of plant water status is essential for adjusting field practices and irrigation schemes of winter wheat. The objective of this study was to find new combination spectral indices based on canopy reflectance for the estimation of plant water status. Two experiments with different irrigation regimes were conducted in 2015–2016 and 2016–2017. The canopy spectra were collected at different growth stages of winter wheat. The raw and derivative reflectance of canopy spectra showed obvious responses to the change of plant water status. Except for equivalent water thickness (EWT), other water metrics had good relationships with new combination spectral indices (R 2 >0.7). An acceptable model of canopy water content (CWC) was established with the best spectral index (RVI (1605, 1712)). Models of leaf water content (LWC) and plant water content (PWC) had better performances. Optimal spectral index of LWC was FDRVI (687, 531), having R 2 , RMSE and RPD of 0.77, 2.181 and 2.09; R 2 , RMSE and RPD of 0.87, 2.652 and 2.34 for calibration and validation, respectively. And PWC could be well estimated with FDDVI (688, 532) (R 2 , RMSE and RPD of 0.79, 3.136 and 2.21; R 2 , RMSE and RPD of 0.83, 3.702 and 2.18 for calibration and validation, respectively). Comparing the performances of estimation models, the new combination spectral indices FDRVI (687, 531) based on canopy reflectance improved the accuracy of estimation of plant water status. Besides, based on FDRVI (687, 531), LWC was the optimal water metrics for plant water status estimation.

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Section: Introductionmentioning

confidence: 99%

Assessment of plant water status in winter wheat (Triticum aestivum L.) based on canopy spectral indices

et al. 2019

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“…Park et al (2016) evaluated sixteen remote sensing drought factors and found that vegetation-related factors, such as NDVI, are more effective in capturing agricultural drought status in both arid and humid regions. Gao et al (2014) evaluated the equivalent water thickness (EWT), a measure of vegetation water content derived from the near-infrared (NIR) and the short-wave infrared bands, for regional drought monitoring. They found that EWT is strongly affected by vegetation density and cover type, and is therefore of limited use for monitoring moderate to severe drought conditions.…”

Section: Introductionmentioning

confidence: 99%

Fallow-land Algorithm based on Neighborhood and Temporal Anomalies (FANTA) to map planted versus fallowed croplands using MODIS data to assist in drought studies leading to water and food security assessments

Wallace

Thenkabail

Rodriguez

et al. 2017

GIScience & Remote Sensing

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An important metric to monitor for optimizing water use in agricultural areas is the amount of cropland left fallowed, or unplanted. Fallowed croplands are difficult to model because they have many expressions; for example, they can be managed and remain free of vegetation or be abandoned and become weedy if the climate for that season permits. We used 250 m, 8-day composite Moderate Resolution Imaging Spectroradiometer normalized difference vegetation index data to develop an algorithm that can routinely map cropland status (planted or fallowed) with over 75% user's and producer's accuracies. The Fallow-land Algorithm based on Neighborhood and Temporal Anomalies (FANTA) compares the current greenness of a cultivated pixel to its historical greenness and to the greenness of all cultivated pixels within a defined spatial neighborhood, and is therefore transportable across space and through time. This article introduces FANTA and applies it to California from 2001 to 2015 as a case study for use in data-poor places and for use in historical modeling. Timely and accurate knowledge of the extent of fallowing can provide decision makers with insights and knowledge to mitigate the impacts of drought and provide a scientific basis for effective management response. This study is part of the WaterSMART (Sustain and Manage America's Resources for Tomorrow) project, an interdisciplinary and collaborative research effort focused on improving water conservation and optimizing water use.

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“…It is a very useful input to a number of primary productivity models based on simple light use efficiency considerations (Dinku, Funk, and Grimes al. 2008) passive microwave (PMW) sensors give better estimations than thermal infrared (TIR) sensors (Gruber and Levizzani 2008) Calculated from TIR or PMW sensors: high level of uncertainty in estimates (Hellmuth et al 2009;Dinku, Funk, and Grimes 2008;Gommes and Kayitakire 2013) Vegetation indices sensitive to drought (Black and Stephen 2014;Gao et al 2014) Production loss measured objectively (Chantarat et al 2013;Makaudze and Miranda 2010;Potter 2014) Good correlation with energy uptake by growing and senescent plants (Ceccato et al 2008;Duan et al 2012;Gao et al 2013;Phillips et al 2013) Not easily verifiable Validation is complex (Burke, de Janvry, and Quintero 2010) Availability of data For TIR sensor: spatially continuous acquisition of data over most of the globe (Dinku, Funk, and Grimes 2008) Availability of long archive (Gruber and Levizzani 2008) PMW sensors not geosynchronous: acquisition with low repetition rate (Hellmuth et al 2009;Dinku, Funk, and Grimes 2008) Short period of record ...…”

Section: Development Of An Index-based Insurance Product: Validation mentioning

confidence: 99%

Development of an index-based insurance product: validation of a forage production index derived from medium spatial resolution fCover time series

Roumiguié

Jacquin

Sigel

et al. 2015

GIScience & Remote Sensing

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An index-based insurance is being developed to estimate and monitor forage production in France in near real-time based on a forage production index (FPI) derived from the fraction of green vegetation cover (fCover) integral, obtained from medium spatial resolution time series. This article presents the first step of the scientific validation implemented. The grassland parcels, the field protocol established to collect biomass production data, and the method used to get the fCover are described. Local ground measurements of biomass production are compared with FPI values obtained from high-resolution space-based images. Discrepancies between the two variables are quantified by the coefficient of determination, the mean square error and the normalised root mean square error. First, fCover derived from the four sensors are coherent demonstrating the ability of the algorithm used to provide a consistent way of calculating fCover. Second, for the whole data set, the scatter plot between FPI and biomass shows an acceptable correlation (R 2 = 0.75) improved when only taking into account data recorded up until the production maximum (R 2 = 0.81). Third, the analysis carried out on the scale of the parcels, grass species, period of mowing or climatic conditions reveals variability on the regression coefficients indicating that other explanatory variables should be integrated to better compute the FPI.

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The responses of vegetation water content (EWT) and assessment of drought monitoring along a coastal region using remote sensing

Cited by 27 publications

References 25 publications

Assessment of plant water status in winter wheat (Triticum aestivum L.) based on canopy spectral indices

Assessment of plant water status in winter wheat (Triticum aestivum L.) based on canopy spectral indices

Fallow-land Algorithm based on Neighborhood and Temporal Anomalies (FANTA) to map planted versus fallowed croplands using MODIS data to assist in drought studies leading to water and food security assessments

Development of an index-based insurance product: validation of a forage production index derived from medium spatial resolution fCover time series

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