LIVIVO - Search results -

Search results

Result 1 - 10 of total 30

Search options

Article ; Online: Optimization of Extraction Conditions of Carotenoids from Dunaliella parva by Response Surface Methodology

Yujia Li / Xiaojuan Huang / Lirong Luo / Changhua Shang

Molecules, Vol 27, Iss 1444, p

2022 Volume 1444

Abstract: Extraction conditions can exert a remarkable influence on extraction efficiency. The aim of this study was to improve the extraction efficiency of carotenoids from Dunaliella parva ( D. parva ). Dimethyl sulfoxide (DMSO) and 95% ethanol were used as the ... ...

Abstract	Extraction conditions can exert a remarkable influence on extraction efficiency. The aim of this study was to improve the extraction efficiency of carotenoids from Dunaliella parva ( D. parva ). Dimethyl sulfoxide (DMSO) and 95% ethanol were used as the extraction solvents. The extraction time, extraction temperature and the proportions of mixed solvent were taken as influencing factors, and the experimental scheme was determined by Central Composite Design (CCD) of Design Expert 10.0.4.0 to optimize the extraction process of carotenoids from D. parva . The absorbance values of the extract at 665 nm, 649 nm and 480 nm were determined by a microplate spectrophotometer, and the extraction efficiency of carotenoids was calculated. Analyses of the model fitting degree, variance and interaction term 3D surface were performed by response surface analysis. The optimal extraction conditions were as follows: extraction time of 20 min, extraction temperature of 40 °C, and a mixed solvent ratio (DMSO: 95% ethanol) of 3.64:1. Under the optimal conditions, the actual extraction efficiency of carotenoids was 0.0464%, which was increased by 18.19% (the initial extraction efficiency of 0.03926%) with a lower extraction temperature (i.e., lower energy consumption) compared to the standard protocol.
Keywords	Dunaliella parva ; Central Composite Design ; extraction efficiency ; carotenoids ; optimization ; Organic chemistry ; QD241-441
Subject code	660
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: An Open Data Approach for Estimating Vegetation Gross Primary Production at Fine Spatial Resolution

Shangrong Lin / Xiaojuan Huang / Yi Zheng / Xiao Zhang / Wenping Yuan

Remote Sensing, Vol 14, Iss 2651, p

2022 Volume 2651

Abstract: Accurate simulations of the spatial and temporal changes in vegetation gross primary production (GPP) play an important role in ecological studies. Previous studies highlighted large uncertainties in GPP datasets based on satellite data with coarse ... ...

Abstract	Accurate simulations of the spatial and temporal changes in vegetation gross primary production (GPP) play an important role in ecological studies. Previous studies highlighted large uncertainties in GPP datasets based on satellite data with coarse spatial resolutions (>500 m), and implied the need to produce high-spatial-resolution datasets. However, estimating fine spatial resolution GPP is time-consuming and requires an enormous amount of computing storage space. In this study, based on the Eddy Covariance-Light Use Efficiency (EC-LUE) model, we used Google Earth Engine (GEE) to develop a web application (EC-LUE APP) to generate 30-m-spatial-resolution GPP estimates within a region of interest. We examined the accuracy of the GPP estimates produced by the APP and compared them with observed GPP at 193 global eddy covariance sites. The results showed the good performance of the EC-LUE APP in reproducing the spatial and temporal variations in the GPP. The fine-spatial-resolution GPP product (GPP L ) explained 64% of the GPP variations and had fewer uncertainties (root mean square error = 2.34 g C m −2 d −1 ) and bias (−0.09 g C m −2 d −1 ) than the coarse-spatial-resolution GPP products. In particular, the GPP L significantly improved the GPP estimations for cropland and dryland ecosystems. With this APP, users can easily obtain 30-m-spatial-resolution GPP at any given location and for any given year since 1984.
Keywords	Google Earth Engine ; Landsat data ; gross primary production ; EC-LUE ; Science ; Q
Subject code	333
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Effect of Carbetocin on Postpartum Hemorrhage after Vaginal Delivery

Xiaojuan Huang / Wanxing Xue / Jin Zhou / Cuiyi Zhou / Feiyan Yang

Computational and Mathematical Methods in Medicine, Vol

A Meta-Analysis

2022 Volume 2022

Abstract: Background. The efficacy of oxytocin and carbetocin in preventing postpartum hemorrhage (PPH) in women with vaginal delivery has been controversial. This study is aimed at conducting a meta-analysis that compares the efficacy of carbetocin and oxytocin ... ...

Abstract	Background. The efficacy of oxytocin and carbetocin in preventing postpartum hemorrhage (PPH) in women with vaginal delivery has been controversial. This study is aimed at conducting a meta-analysis that compares the efficacy of carbetocin and oxytocin in the prevention of PPH among women with vaginal delivery. Methods. Literature was retrieved from PubMed, Medline, Embase, CENTRAL, and CNKI databases. The randomized controlled trials (RCTs) that compare the efficacy of carbetocin and oxytocin to prevent PPH were searched. Data from the included literatures were extracted by two researchers, including author, title, publication date, study type, study number, the incidence of PPH, number of patients requiring additional uterotonics, and number of patients requiring blood transfusion. Jadad scale was used to evaluate the quality of the included RCTs. The Chi-square test was adopted for the heterogeneity test. A fixed-effect model was used for analysis if heterogeneity did not exist between literatures. If heterogeneity exists between literatures, a random-effect model was used for analysis. The source of heterogeneity was explored by subgroup analysis and sensitivity analysis. Results. The incidence of PPH in the carbetocin group was lower than that in the oxytocin group (OR=0.62, 95% CI (0.46, 0.84), Z=3.14, P=0.002). There was no heterogeneity among studies (χ2=7.29, P=0.12, I2=45%) and no significant publication bias (P>0.05). The proportion of women requiring additional uterotonics in the carbetocin group was lower than that in the oxytocin group (OR=0.41, 95% CI (0.29, 0.56), Z=5.34, P<0.00001). There was no heterogeneity among studies (χ2=0.82, P=0.84, I2=0%) and no significant publication bias (P>0.05). There was no significant difference in the proportion of women needing blood transfusion between the carbetocin group and the oxytocin group (OR=0.92, 95% CI (0.66, 1.29), Z=0.46, P=0.64). There was no heterogeneity among studies (χ2=3.06, P=0.55, I2=0%) and no significant publication bias ...
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	610
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: How Well Can Matching High Spatial Resolution Landsat Data with Flux Tower Footprints Improve Estimates of Vegetation Gross Primary Production

Xiaojuan Huang / Shangrong Lin / Xiangqian Li / Mingguo Ma / Chaoyang Wu / Wenping Yuan

Remote Sensing, Vol 14, Iss 6062, p

2022 Volume 6062

Abstract: Eddy-covariance (EC) measurements are widely used to optimize the terrestrial vegetation gross primary productivity (GPP) model because they provide standardized and high-quality flux data within their footprint areas. However, the extent of flux data ... ...

Abstract	Eddy-covariance (EC) measurements are widely used to optimize the terrestrial vegetation gross primary productivity (GPP) model because they provide standardized and high-quality flux data within their footprint areas. However, the extent of flux data taken from a tower site within the EC footprint, represented by the satellite-based grid cell between Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS), and the performance of the model derived from the Normalized Difference Vegetation Index (NDVI) within the EC footprint at different spatial resolutions (e.g., Landsat and MODIS) remain unclear. Here, we first calculated the Landsat-footprint NDVI and MODIS-footprint NDVI and assessed their spatial representativeness at 78 FLUXNET sites at 30 m and 500 m scale, respectively. We then optimized the parameters of the revised Eddy Covariance-Light Use Efficiency (EC-LUE) model using NDVI within the EC-tower footprints that were calculated from the Landsat and MODIS sensor. Finally, we evaluated the performance of the optimized model at 30 m and 500 m scale. Our results showed that matching Landsat data with the flux tower footprint was able to improve the performance of the revised EC-LUE model by 18% for savannas, 14% for croplands, 9% for wetlands. The outperformance of the Landsat-footprint NDVI in driving model relied on the spatial heterogeneity of the flux sites. Our study assessed the advantages of remote sensing data with high spatial resolution in simulating GPP, especially for areas with high heterogeneity of landscapes. This could facilitate a more accurate estimation of global ecosystem carbon sink and a better understanding of plant productivity and carbon climate feedbacks.
Keywords	footprints ; light use efficiency ; gross primary production ; parameter optimization ; Science ; Q
Subject code	333
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Influencing Factors on the Household-Waste-Classification Behavior of Urban Residents

Decai Tang / Lei Shi / Xiaojuan Huang / Ziqian Zhao / Biao Zhou / Brandon J. Bethel

International Journal of Environmental Research and Public Health, Vol 19, Iss 6528, p

A Case Study in Shanghai

2022 Volume 6528

Abstract: As the process of urbanization in China continues to accelerate, the amount of domestic waste generated correspondingly increases and directly affects the living space of residents. This indirectly implies that to reduce the production of municipal solid ...

Abstract	As the process of urbanization in China continues to accelerate, the amount of domestic waste generated correspondingly increases and directly affects the living space of residents. This indirectly implies that to reduce the production of municipal solid waste and the need for garbage disposal and recycling, household-waste-classification activities by the residents are of great significance. Using Shanghai as a case study, this study investigated the influencing factors on residents’ household waste classification by conducting a survey. Statistical analysis was then adopted, which is specified below. First, this study proposed research hypotheses related to the influencing factors of residents’ domestic-waste-sorting behavior from three levels: government, society and individuals. Second, the study designed a questionnaire from five perspectives: individual characteristic variables, government, society, residents and classification behavior. Then, SPSS software was used to carry out descriptive statistical, reliability and validity assessments using ANOVA, correlation and regression analyses on the sample data obtained from the questionnaire. The results suggested that the research hypotheses were statistically significant: (1) females and residents with higher education were more likely to participate in domestic waste classification; (2) reward and punishment measures had the most significant impact on residents’ waste-classification behavior; and (3) publicity and education, classification standards, classification facilities, the recycling system, subjective norms, environmental knowledge and environmental attitudes all had a positive effect on residents’ household waste classification. Finally, based on the results of the empirical analysis, this paper provides reference suggestions for the further development of domestic waste classification in Shanghai.
Keywords	household waste classification ; influencing factors ; empirical analysis ; Medicine ; R
Subject code	710
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Evaluating the Performance of Satellite-Derived Vegetation Indices for Estimating Gross Primary Productivity Using FLUXNET Observations across the Globe

Xiaojuan Huang / Jingfeng Xiao / Mingguo Ma

Remote Sensing, Vol 11, Iss 15, p

2019 Volume 1823

Abstract: Satellite-derived vegetation indices (VIs) have been widely used to approximate or estimate gross primary productivity (GPP). However, it remains unclear how the VI-GPP relationship varies with indices, biomes, timescales, and the bidirectional ... ...

Abstract	Satellite-derived vegetation indices (VIs) have been widely used to approximate or estimate gross primary productivity (GPP). However, it remains unclear how the VI-GPP relationship varies with indices, biomes, timescales, and the bidirectional reflectance distribution function (BRDF) effect. We examined the relationship between VIs and GPP for 121 FLUXNET sites across the globe and assessed how the VI-GPP relationship varied among a variety of biomes at both monthly and annual timescales. We used three widely-used VIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and 2-band EVI (EVI2) as well as a new VI - NIR V and used surface reflectance both with and without BRDF correction from the moderate resolution imaging spectroradiometer (MODIS) to calculate these indices. The resulting traditional (NDVI, EVI, EVI2, and NIR V ) and BRDF-corrected (NDVI BRDF , EVI BRDF , EVI2 BRDF , and NIR V, BRDF ) VIs were used to examine the VI-GPP relationship. At the monthly scale, all VIs were moderate or strong predictors of GPP, and the BRDF correction improved their performance. EVI2 BRDF and NIR V, BRDF had similar performance in capturing the variations in tower GPP as did the MODIS GPP product. The VIs explained lower variance in tower GPP at the annual scale than at the monthly scale. The BRDF-correction of surface reflectance did not improve the VI-GPP relationship at the annual scale. The VIs had similar capability in capturing the interannual variability in tower GPP as MODIS GPP. VIs were influenced by temperature and water stresses and were more sensitive to temperature stress than to water stress. VIs in combination with environmental factors could improve the prediction of GPP than VIs alone. Our findings can help us better understand how the VI-GPP relationship varies among indices, biomes, and timescales and how the BRDF effect influences the VI-GPP relationship.
Keywords	carbon cycle ; gross primary production ; eddy covariance ; vegetation productivity ; MODIS ; vegetation activity ; photosynthesis ; remote sensing ; light use efficiency ; environmental stresses ; Science ; Q
Subject code	333
Language	English
Publishing date	2019-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: A dynamic-leaf light use efficiency model for improving gross primary production estimation

Lingxiao Huang / Wenping Yuan / Yi Zheng / Yanlian Zhou / Mingzhu He / Jiaxin Jin / Xiaojuan Huang / Siyuan Chen / Meng Liu / Xiaobin Guan / Shouzheng Jiang / Xiaofeng Lin / Zhao-Liang Li / Ronglin Tang

Environmental Research Letters, Vol 19, Iss 1, p

2024 Volume 014066

Abstract: Accurate quantification of terrestrial gross primary production (GPP) is integral for enhancing our understanding of the global carbon budget and climate change. The light use efficiency (LUE) model is undoubtedly the most extensively applied method for ... ...

Abstract	Accurate quantification of terrestrial gross primary production (GPP) is integral for enhancing our understanding of the global carbon budget and climate change. The light use efficiency (LUE) model is undoubtedly the most extensively applied method for GPP estimation. However, the two-leaf (TL)-LUE model using a ‘potential’ sunlit leaf area index (LAI _su ) can separate a portion of LAI _su even when the canopy does not receive any direct radiation, leading to the underestimation of GPP under cloudy and overcast days. Here, we developed a dynamic-leaf (DL) LUE model by introducing an ‘effective’ LAI _su to improve GPP estimation, which considers the comprehensive contribution of LAI _su when the canopy does and does not receive direct radiation. In particular, the new model decreases LAI _su to zero when direct radiation reaches zero. Our evaluation at eight ChinaFLUX sites showed that (1) the DL-LUE model outperformed the most well-known BL-LUE (namely, the MOD17 GPP algorithm) and TL-LUE models in reproducing the daily in situ GPP, especially at four forest sites [reducing the root mean square error (RMSE) from 1.74 g C m ^−2 d ^−1 and 1.53 g C m ^−2 d ^−1 to 1.36 g C m ^−2 d ^−1 and increasing the coefficient of determination ( R ^2 ) from 0.74 and 0.79–0.82, respectively]. Moreover, the improvements were particularly pronounced at longer temporal scales, as indicated by the RMSE decreasing from 29.32 g C m ^−2 month ^−1 and28.11 g C m ^−2 month ^−1 to 25.81 g C m ^−2 month ^−1 at a monthly scale and from 231.82 g C m ^−2 yr ^−1 and 221.60 g C m ^−2 yr ^−1 –200.00 g C m ^−2 yr ^−1 at a yearly scale; (2) the DL-LUE model mitigated the systematic underestimation of the in situ GPP by both the TL-LUE and BL-LUE models when the clearness index (CI) was below 0.5, as indicated by the Bias reductions of 0.25 g C m ^−2 d ^−1 and 0.46 g C m ^−2 d ^−1 , respectively; and (3) the contributions of the shaded GPP to the total GPP from the DL-LUE model were higher by 0.07–0.16 than those from the TL-LUE model across the ...
Keywords	gross primary production ; light use efficiency (LUE) models ; dynamic-leaf LUE model ; big-leaf and two-leaf LUE models ; sunlit and shaded leaves ; Environmental technology. Sanitary engineering ; TD1-1066 ; Environmental sciences ; GE1-350 ; Science ; Q ; Physics ; QC1-999
Subject code	550
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	IOP Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: The spatiotemporal pattern and influencing factors of land surface temperature change in China from 2003 to 2019

Zengjing Song / Hong Yang / Xiaojuan Huang / Wenping Yu / Jing Huang / Mingguo Ma

International Journal of Applied Earth Observations and Geoinformation, Vol 104, Iss , Pp 102537- (2021)

2021

Abstract: Land surface temperature (LST) is an essential parameter in land–atmosphere interaction. However, it is still poorly understood about the effects of seasonal LST on the interannual LST change and the dominant driving force for the variation in LST. In ... ...

Abstract	Land surface temperature (LST) is an essential parameter in land–atmosphere interaction. However, it is still poorly understood about the effects of seasonal LST on the interannual LST change and the dominant driving force for the variation in LST. In this study, trends of time-series LST were analyzed by using both linear and nonlinear methods. Two indices were developed to evaluate the effects of seasonal LST trends on interannual LST change. The main driving factor of LST was identified based on each pixel. Two turning points were founded in 2007 and 2011 during the study period of 2003–2019. A significant cooling trend of LST appeared from 2007 to 2011/2012 with the rates of −0.2237 K/year (daytime) and −0.1239 K/year (nighttime). LST increased in almost all seasons except the daytime in autumn. The warming effect in spring and winter contributed 69.43% to interannual warming of daytime LST, and accounted for 59.02% of interannual warming of nighttime LST. In most regions of China, air temperature and vegetation were the dominant factors influencing the change of LST. The current research improved our understanding of changes of LST and the results can serve for mitigating and adapting to climate change.
Keywords	Interannual and seasonal trends ; Albedo ; Air temperature ; Evapotranspiration ; Vegetation ; Land surface temperature ; Physical geography ; GB3-5030 ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: High spatial resolution vegetation gross primary production product

Xiaojuan Huang / Yi Zheng / Hui Zhang / Shangrong Lin / Shunlin Liang / Xiangqian Li / Mingguo Ma / Wenping Yuan

Science of Remote Sensing, Vol 5, Iss , Pp 100049- (2022)

Algorithm and validation

2022

Abstract: Vegetation gross primary production (GPP) in terrestrial ecosystems is a key element of the carbon cycle, and its estimation highly determines the accuracy of carbon budget assessments. Currently, several global datasets of vegetation production are ... ...

Abstract	Vegetation gross primary production (GPP) in terrestrial ecosystems is a key element of the carbon cycle, and its estimation highly determines the accuracy of carbon budget assessments. Currently, several global datasets of vegetation production are available at coarse or moderate spatial resolutions, but globally they still have large uncertainties, which hindered the application of GPP, especially in strongly heterogeneous agriculture ecosystems and mountainous areas. Here, we used the Markov chain Monte Carlo (MCMC) approach with the footprints of FLUXNET data to optimize the parameters of the high resolution of Global LAnd Surface Satellite (Hi-GLASS) GPP algorithm (i.e., the revised EC-LUE model) using 30 m spatial resolution Landsat data as driving data. Then, we generated a new set of algorithm parameters for high resolution GPP estimates. We used the optimized parameters with integrating footprint to calculate Hi-GLASS GPP based on Landsat data and our results revealed that on average, Hi-GLASS GPP explained 76% of variance in tower GPP at the total of 78 sites across ten vegetation types. Moreover, compared with previous 500 m GPP product such as GLASS GPP and MODerate Resolution Imaging Spectroradiometer (MODIS) GPP, our optimized Hi-GLASS algorithm using Landsat data had large superiority in simulating GPP for wetlands, savannas, shrubland and C3, C4 cropland ecosystems, and had a slightly improvement for deciduous broadleaf forests and evergreen broadleaf forest ecosystem. Our study is an effort to optimize and quantify parameter uncertainty of Hi-GLASS algorithm using high spatial resolution (30 m) Landsat data and improve the high resolution GPP estimation for better understanding global ecosystem carbon dynamics and carbon-climate feedbacks.
Keywords	Gross primary production ; Light use efficiency ; Footprints ; Landsat ; Remote sensing ; High resolution ; Physical geography ; GB3-5030 ; Science ; Q
Subject code	333
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: High-Resolution Mapping of Winter Cereals in Europe by Time Series Landsat and Sentinel Images for 2016–2020

Xiaojuan Huang / Yangyang Fu / Jingjing Wang / Jie Dong / Yi Zheng / Baihong Pan / Sergii Skakun / Wenping Yuan

Remote Sensing, Vol 14, Iss 2120, p

2022 Volume 2120

Abstract: Winter cereals, including wheat, rye, barley, and triticale, are important food crops, and it is crucial to identify the distribution of winter cereals for monitoring crop growth and predicting yield. The production and plating area of winter cereals in ... ...

Abstract	Winter cereals, including wheat, rye, barley, and triticale, are important food crops, and it is crucial to identify the distribution of winter cereals for monitoring crop growth and predicting yield. The production and plating area of winter cereals in Europe both contribute 12.57% to the total global cereal production and plating area in 2020. However, the distribution maps of winter cereals with high spatial resolution are scarce in Europe. Here, we first used synthetic aperture radar (SAR) data from Sentinel-1 A/B, in the Interferometric Wide (IW) swath mode, to distinguish rapeseed and winter cereals; we then used a time-weighted dynamic time warping (TWDTW) method to discriminate winter cereals from other crops by comparing the similarity of seasonal changes in the Normalized Difference Vegetation Index (NDVI) from Landsat and Sentinel-2 images. We generated winter cereal maps for 2016–2020 that cover 32 European countries with 30 m spatial resolution. Validation using field samples obtained from the Google Earth Engine (GEE) platform show that the producer’s and user’s accuracies are 91% ± 7.8% and 89% ± 10.3%, respectively, averaged over 32 countries in Europe. The winter cereal map agrees well with agricultural census data for planted winter cereal areas at municipal and country levels, with the averaged coefficient of determination R 2 as 0.77 ± 0.15 for 2016–2019. In addition, our method can identify the distribution of winter cereals two months before harvest, with an overall accuracy of 88.4%, indicating that TWDTW is an effective method for timely crop growth monitoring and identification at the continent level. The winter cereal maps in Europe are available via an open-data repository.
Keywords	winter cereals ; vegetation index ; time-weighted dynamic time warping ; Landsat ; Sentinel ; Google Earth Engine ; Science ; Q
Subject code	333
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED