Bin Tan - Academia.edu (original) (raw)
Papers by Bin Tan
PloS one, 2015
The pandemic influenza A (H1N1) pdm09 virus, avian influenza A (H5N1) virus, and influenza A (H7N... more The pandemic influenza A (H1N1) pdm09 virus, avian influenza A (H5N1) virus, and influenza A (H7N9) virus induced severe morbidity and mortality throughout the world. Previous studies suggested a close association between the interferon-induced transmembrane protein-3 (IFITM3) genetic variant rs12252 and influenza. Here, we explored the correlation between the rs12252 and influenza susceptibility and severity using meta-analysis. Relevant studies published before May 22, 2014 were retrieved from PubMed, ISI web of knowledge, EBSCO, and Cochrane central register of controlled trials databases. Association between rs12252 and influenza susceptibility and severity were determined using statistical analysis of odds ratios (ORs). A total of four studies consisting of 445 cases and 4180 controls were included in our analysis. Generally, there is increased risk of influenza in subjects carrying rs12252 in the recessive model (CC vs. CT+TT: OR = 2.35, 95% CI: 1.49-3.70, P<0.001), the dom...
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
ABSTRACT We are developing an approach for generating ground reference data in support of a proje... more ABSTRACT We are developing an approach for generating ground reference data in support of a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. Since sufficient ground reference data for training and validation is not available from ground surveys, we are developing an interactive tool, called HSegLearn, to facilitate the photo-interpretation of 1 to 2 m spatial resolution imagery data, which we will use to generate the needed ground reference data at 30m. Through the submission of selected region objects and positive or negative examples of impervious surfaces, HSegLearn enables an analyst to automatically select groups of spectrally similar objects from a hierarchical set of image segmentations produced by the HSeg image segmentation program at an appropriate level of segmentation detail, and label these region objects as either impervious or non-impervious.
Organic letters, Jan 20, 2015
A metal-free direct remote C-H functionalization triggered by radical trifluoromethylation of alk... more A metal-free direct remote C-H functionalization triggered by radical trifluoromethylation of alkenes was explored, realizing highly selective 1,6-difunctionalization of alkenes toward valuable trifluoromethyl α-hydroxycarbonyl compounds. Furthermore, a metal-free direct intermolecular regioselective 1,2-oxytrifluoromethylation of alkenes is also disclosed. With Togni's reagent as both the CF3 source and oxidant, the reaction exhibits a broad substrate scope with excellent functionality tolerance under mild metal-free conditions, thus showing great potential for synthetic utility.
Zhongguo gu shang = China journal of orthopaedics and traumatology, 2009
International journal of clinical and experimental pathology, 2014
Single nucleotide polymorphisms (SNPs) of VKORC (1173T/C, rs9934438) and CYP2C9 (1075A/C, rs10579... more Single nucleotide polymorphisms (SNPs) of VKORC (1173T/C, rs9934438) and CYP2C9 (1075A/C, rs1057910) are major contributory factors on the sensitivity of warfarin in Chinese. Analysis of the two genomic loci could help warfarin treatment individual from bleeding or thrombosis events. An assay with the advantages of simplicity, speed, high sensitivity and low cost for genotyping is calling for clinical laboratories. High resolution method (HRM) meets these callings, but no study with large sample tested its performance in genotyping of rs9934438 and rs1057910. In this study, we identified polymorphisms of rs9934438 and rs1057910 in 255 unrelated Chinese heart valve replacement patients of Han ethnic group from West China Hospital. The two genomic loci were genotyped by HRM using LightCycler® 480 High Resolution Melting Master on LightCycler® 480 Real-Time PCR instruments (Roche Diagnostics), and all amplified PCR products were sent for direct DNA sequencing. The genotyping of rs10579...
Journal of virological methods, 2014
Bovine viral diarrhea virus (BVDV) can contaminate biological products produced in bovine or porc... more Bovine viral diarrhea virus (BVDV) can contaminate biological products produced in bovine or porcine cells or manufactured using bovine sera. A rapid, specific, sensitive, and practical method of detecting BVDV in bio-products is needed. The purpose of this study was to compare three assays with respect to their ability to accurately detect BVDV in biological samples, namely reverse-transcription loop-mediated isothermal amplification (RT-LAMP), SYBR green I-based real-time RT-PCR, and conventional RT-PCR. All assays detected BVDV nucleotide and differentiated between BVDV-free and -contaminated bovine sera successfully. In addition, the results were specific to BVDV: the amplification of samples containing the closely related classical swine fever virus or other pathogenic bovine viruses yielded negative results. The lowest detection threshold, 10(1) copies, was displayed by the SYBR green I-based real-time RT-PCR and RT-LAMP assay. This assay was also the most effective in the det...
Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2014
Bovine viral diarrhea virus (BVDV) is often detected in commercial bovine serum. BVDV genetic div... more Bovine viral diarrhea virus (BVDV) is often detected in commercial bovine serum. BVDV genetic diversity was investigated in commercial bovine serum of Chinese origin. Twenty-two batches of bovine serum were obtained from 10 suppliers with different geographic origins in China, and 20 batches of bovine serum were positive by reverse-transcription polymerase chain reaction (RT-PCR) and sequencing. Phylogenetic reconstructions of partial 5'UTR sequences indicated that the samples examined in this work clustered within the BVDV type 1 and BVDV type 2 genotypes. Interestingly, 3 sample sequences clustered into CSFV. These results suggest a high genetic diversity in Chinese BVDV field isolates. This study will benefit epidemiological surveys of BVDV detected in China.
European journal of pediatrics, 2014
Ventilator-associated pneumonia (VAP) is a common and serious problem among mechanically ventilat... more Ventilator-associated pneumonia (VAP) is a common and serious problem among mechanically ventilated patients in intensive care units (ICU), especially for the newborn. However, limited literatures have been reviewed to synthesize the finding of previous papers to investigate the risk factors for VAP although it has been a serious complication of mechanical ventilation (MV) with a high morbidity and mortality in the newborn. We performed this meta-analysis to extend previous knowledge for developing VAP prevention strategies by identifying the potential risk factors related to VAP in the neonatal intensive care unit (NICU). The relevant literatures published up to July 2013 were searched in the databases of PubMed, Cochrane Central Register of Controlled Trials, Embase, and Web of Science. Three reviewers screened those literatures and extracted data according to the inclusion and exclusion criteria independently. A total of eight studies including 370 cases and 1,071 controls were i...
This Guide is a living document that describes the smoothed and gap-filled MODIS VIs (LAI/FPAR fr... more This Guide is a living document that describes the smoothed and gap-filled MODIS VIs (LAI/FPAR from MOD15A2, and EVI/NDVI calculated from MOD09A2 and MOD09Q2). It is revised as progress is made in the development of these products. The purpose of the document is to give the potential user an understanding of the MOD09GFS and MOD15GFS products and the current state of the data in those products.
1] MODIS-based leaf area index (LAI) and normalized difference vegetation index (NDVI) are used t... more 1] MODIS-based leaf area index (LAI) and normalized difference vegetation index (NDVI) are used to examine detailed information regarding actual growing season and total annual production for various regions. Overall, MODIS LAI has larger variability and demonstrates more information regarding the evolution and structure of the seasonal vegetation characteristics. In contrast, the NDVI saturates around 0.7 and tends to overestimate the growing season in regions where it is already long. Next, a climatic impact index (CII) is derived to provide additional information regarding the potential sensitivity of vegetation to changes in climatic variables by accounting for the length of growing season. By normalizing the growth rate to the biome-average growth rate, this index can identify fractional loss of annual production, as opposed to the absolute loss which may be strongly weighted by the overall growth rate for different ecosystems. Our index provides a quantitative framework for assessing the importance of the length of the growing season in determining climatic vulnerability. In the last part of the paper, we use the long time series AVHRR products as a substitute for the MODIS products and test the temporal characteristics of the CII. Major drought events are well-captured by the CII, suggesting potential use as a monitoring and evaluation tool. Furthermore, the strong positive correlation between the CII and the vegetation condition index (VCI) suggests that the CII can quantitatively identify the effects of climatic variability upon vegetation activity. (2004), Climate-related vegetation characteristics derived from Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index and normalized difference vegetation index,
At seasonal to interannual time scales, vegetation phenology reflects dynamics of the Earth'... more At seasonal to interannual time scales, vegetation phenology reflects dynamics of the Earth's climate and hydrologic regimes, and is diagnostic of coupling between the Earth's biosphere and atmosphere. Information related to large scale phenology is therefore useful for studies of seasonal and interannual variability in carbon exchange and vegetation-climate interactions. Remote sensing provides a key means of measuring and monitoring phenology at continental to global scales and vegetation indices derived from satellite data are now commonly used for this purpose. Since April of 2000, the Moderate Resolution Imaging Spectroradiometer (MODIS) has been providing imagery of the Earth that is highly suitable for studies of phenology. At the same time, the use of MODIS data presents a number of significant technical challenges. In particular, residual atmospheric effects, clouds, and the presence of snow all introduce substantial uncertainty to estimates of phenology from MODIS. In this paper, we examine several key factors that affect the quality of phenological metrics derived from MODIS. These factors include: (1) the choice of vegetation index; (2) the method used to screen and correct the effects of snow; and (3) the technique used to fill time series gaps caused by clouds. We examined each of these factors using the MODIS land cover dynamics algorithm (MOD12Q2) for a set of locations that span a range of climate and ecosystem types. Our results show that the sensitivity of MOD12Q2 algorithm to the choice of vegetation index depends on the biome type. Specifically, we observed distinct differences in phenology inferred from EVI versus NDVI in densely vegetated areas caused by saturation of the NDVI. Conversely, in semi-arid areas we observed large differences arising from the different sensitivity of each index to sparse vegetation cover. Finally, our results indicate that the method used to account for snow has a pronounced effect on remotely sensed estimates for the beginning of the growing season.
ABSTRACT Time series from remote sensing data provide the unique capacity to estimate landscape l... more ABSTRACT Time series from remote sensing data provide the unique capacity to estimate landscape level phenology parameters for large regions through time. This presentation will describe a 250m x 250m spatial resolution phenology product for North America from 2001 to 2005. The phenology parameters are estimated from MODIS Normalized Difference Vegetation Index (NDVI) derived from the 8-day surface reflectance product. The algorithm for estimating phenology parameters is based on the TIMESAT software using enhancements that capitalize on the MODIS quality assurance data and an iterative procedure to fill gaps in space and time. The results provide the most spatially complete, highest resolution phenology product ever produced for the entire North American continent. These data are freely available through an on-line query and order system. The presentation will review the enhanced TIMESAT algorithm, provide a description of the phenology parameters included in the product, and an overview of the data distribution system. The advent of the US National Phenology Network will allow for coordination and disseminate of phenological observations at multiple scales and across scientific disciplines. The products presented here will be integrated into the NPN so that they can 1) promote landscape phenology research within NPN and 2) utilize NPN field and network data for validation studies. The presentation will describe our planned coordination with NPN.
ABSTRACT Vegetation indices (VIs) derived from satellite data are now commonly used for detecting... more ABSTRACT Vegetation indices (VIs) derived from satellite data are now commonly used for detecting vegetation phenology at continental to global scales. Vegetation phenology estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) VIs over North America from 2001 to 2006 have been produced and freely available online from http://www.accweb.nascom.nasa.gov. The algorithm to produce this MODIS phenology metrics is based on revised TIMESAT software, which uses the 3rd derivation of a fitted Gauss curve to locate four key phenology dates - begin and end of the greenup and browndown. In order to achieve a long-term phenology record, the same phenology detection algorithm is applied to 1982-2002 GIMMS AVHRR NDVI data sets over North America. To make the phenology estimations from different sensors consistent and comparable, several different methods are utilized in this research. We first compare the phenology metrics estimated from MODIS NDVI and AVHRR NDVI in 2001 and 2002. We found no significant latitudinal gradients in the AVHRR phenology metrics. At the same time, the length of the growing season is artificially overestimated in Northern US and Southern Canada. Both phenomena indicates lower quality from the AVHRR phenology metrics, which is mainly due to the unreliable snow flag of AVHRR data and the absence of ancillary land surface temperature data. To improve the quality of the AVHRR phenology metrics, a more accurate definition of non-growing season is required. We first use the 21-year climatologic mean of minimum NDVI as a threshold to refine the non-growing season pixels. In addition, a sensitivity analysis is performed to address the impact of the threshold on derived phenology metrics. Overall, this research will provide a 25-year phenology product for North America using both MODIS and AVHRR NDVI, which can be applied in regional/continental climate variation analysis and vegetation monitoring. The method to calibrate MODIS and AVHRR phenology products will provide a potential way for generating consistent vegetation phenology metrics from different sensors.
Information related to vegetation phenology is important for understanding seasonal and interannu... more Information related to vegetation phenology is important for understanding seasonal and interannual variability in ecosystems, carbon exchange, and vegetation-climate interactions. MODIS, the Moderate Resolution Imaging Spectroradiometer, provides an excellent source of data for large scale repeatable monitoring of phenology at global scales. This paper describes recent results from the Collection 5 (C5) MODIS Global Land Cover Dynamics product (MOD12Q2), which provides global data sets related to the timing, nature, and magnitude of vegetation phenology. The MOD12Q2 algorithm for estimating phenology is based on fitting piecewise logistic models to time series data of the Enhanced Vegetation Index (EVI) calculated from MODIS C5 Nadir BRDF-adjusted reflectance data. Our results show that the C5 Land Cover Dynamics product represents a significant step forward relative to previous MODIS products. In particular, the use of EVI data derived at 500-m spatial resolution and eight-day time intervals provides substantially improved temporal and spatial resolution relative to the Collection 4 (C4) product, which used 1-km, 16-day inputs. To assess C5 results, we evaluated the new C5 dataset extensively at a global scale for multiple years via (1) comparison with the MODIS C4 1-km product (a benchmark for our comparison), and (2) direct comparison of C5 phenological metrics with field observations collected at several sites in the northeastern United States. The results show general agreement of the C5 product with the C4 product in a majority of biomes, but with improved quality of the former compared to the latter. In addition, examination of C5 data sets exhibit significantly fewer missing values relative to C4, and generally in good agreement with ground measurements. Moving forward, the results from this analysis suggest that the MOD12Q2 product provides a good basis for seasonal to decadal scale studies of coupled climate-vegetation variability.
PloS one, 2015
The pandemic influenza A (H1N1) pdm09 virus, avian influenza A (H5N1) virus, and influenza A (H7N... more The pandemic influenza A (H1N1) pdm09 virus, avian influenza A (H5N1) virus, and influenza A (H7N9) virus induced severe morbidity and mortality throughout the world. Previous studies suggested a close association between the interferon-induced transmembrane protein-3 (IFITM3) genetic variant rs12252 and influenza. Here, we explored the correlation between the rs12252 and influenza susceptibility and severity using meta-analysis. Relevant studies published before May 22, 2014 were retrieved from PubMed, ISI web of knowledge, EBSCO, and Cochrane central register of controlled trials databases. Association between rs12252 and influenza susceptibility and severity were determined using statistical analysis of odds ratios (ORs). A total of four studies consisting of 445 cases and 4180 controls were included in our analysis. Generally, there is increased risk of influenza in subjects carrying rs12252 in the recessive model (CC vs. CT+TT: OR = 2.35, 95% CI: 1.49-3.70, P<0.001), the dom...
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
ABSTRACT We are developing an approach for generating ground reference data in support of a proje... more ABSTRACT We are developing an approach for generating ground reference data in support of a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. Since sufficient ground reference data for training and validation is not available from ground surveys, we are developing an interactive tool, called HSegLearn, to facilitate the photo-interpretation of 1 to 2 m spatial resolution imagery data, which we will use to generate the needed ground reference data at 30m. Through the submission of selected region objects and positive or negative examples of impervious surfaces, HSegLearn enables an analyst to automatically select groups of spectrally similar objects from a hierarchical set of image segmentations produced by the HSeg image segmentation program at an appropriate level of segmentation detail, and label these region objects as either impervious or non-impervious.
Organic letters, Jan 20, 2015
A metal-free direct remote C-H functionalization triggered by radical trifluoromethylation of alk... more A metal-free direct remote C-H functionalization triggered by radical trifluoromethylation of alkenes was explored, realizing highly selective 1,6-difunctionalization of alkenes toward valuable trifluoromethyl α-hydroxycarbonyl compounds. Furthermore, a metal-free direct intermolecular regioselective 1,2-oxytrifluoromethylation of alkenes is also disclosed. With Togni's reagent as both the CF3 source and oxidant, the reaction exhibits a broad substrate scope with excellent functionality tolerance under mild metal-free conditions, thus showing great potential for synthetic utility.
Zhongguo gu shang = China journal of orthopaedics and traumatology, 2009
International journal of clinical and experimental pathology, 2014
Single nucleotide polymorphisms (SNPs) of VKORC (1173T/C, rs9934438) and CYP2C9 (1075A/C, rs10579... more Single nucleotide polymorphisms (SNPs) of VKORC (1173T/C, rs9934438) and CYP2C9 (1075A/C, rs1057910) are major contributory factors on the sensitivity of warfarin in Chinese. Analysis of the two genomic loci could help warfarin treatment individual from bleeding or thrombosis events. An assay with the advantages of simplicity, speed, high sensitivity and low cost for genotyping is calling for clinical laboratories. High resolution method (HRM) meets these callings, but no study with large sample tested its performance in genotyping of rs9934438 and rs1057910. In this study, we identified polymorphisms of rs9934438 and rs1057910 in 255 unrelated Chinese heart valve replacement patients of Han ethnic group from West China Hospital. The two genomic loci were genotyped by HRM using LightCycler® 480 High Resolution Melting Master on LightCycler® 480 Real-Time PCR instruments (Roche Diagnostics), and all amplified PCR products were sent for direct DNA sequencing. The genotyping of rs10579...
Journal of virological methods, 2014
Bovine viral diarrhea virus (BVDV) can contaminate biological products produced in bovine or porc... more Bovine viral diarrhea virus (BVDV) can contaminate biological products produced in bovine or porcine cells or manufactured using bovine sera. A rapid, specific, sensitive, and practical method of detecting BVDV in bio-products is needed. The purpose of this study was to compare three assays with respect to their ability to accurately detect BVDV in biological samples, namely reverse-transcription loop-mediated isothermal amplification (RT-LAMP), SYBR green I-based real-time RT-PCR, and conventional RT-PCR. All assays detected BVDV nucleotide and differentiated between BVDV-free and -contaminated bovine sera successfully. In addition, the results were specific to BVDV: the amplification of samples containing the closely related classical swine fever virus or other pathogenic bovine viruses yielded negative results. The lowest detection threshold, 10(1) copies, was displayed by the SYBR green I-based real-time RT-PCR and RT-LAMP assay. This assay was also the most effective in the det...
Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2014
Bovine viral diarrhea virus (BVDV) is often detected in commercial bovine serum. BVDV genetic div... more Bovine viral diarrhea virus (BVDV) is often detected in commercial bovine serum. BVDV genetic diversity was investigated in commercial bovine serum of Chinese origin. Twenty-two batches of bovine serum were obtained from 10 suppliers with different geographic origins in China, and 20 batches of bovine serum were positive by reverse-transcription polymerase chain reaction (RT-PCR) and sequencing. Phylogenetic reconstructions of partial 5'UTR sequences indicated that the samples examined in this work clustered within the BVDV type 1 and BVDV type 2 genotypes. Interestingly, 3 sample sequences clustered into CSFV. These results suggest a high genetic diversity in Chinese BVDV field isolates. This study will benefit epidemiological surveys of BVDV detected in China.
European journal of pediatrics, 2014
Ventilator-associated pneumonia (VAP) is a common and serious problem among mechanically ventilat... more Ventilator-associated pneumonia (VAP) is a common and serious problem among mechanically ventilated patients in intensive care units (ICU), especially for the newborn. However, limited literatures have been reviewed to synthesize the finding of previous papers to investigate the risk factors for VAP although it has been a serious complication of mechanical ventilation (MV) with a high morbidity and mortality in the newborn. We performed this meta-analysis to extend previous knowledge for developing VAP prevention strategies by identifying the potential risk factors related to VAP in the neonatal intensive care unit (NICU). The relevant literatures published up to July 2013 were searched in the databases of PubMed, Cochrane Central Register of Controlled Trials, Embase, and Web of Science. Three reviewers screened those literatures and extracted data according to the inclusion and exclusion criteria independently. A total of eight studies including 370 cases and 1,071 controls were i...
This Guide is a living document that describes the smoothed and gap-filled MODIS VIs (LAI/FPAR fr... more This Guide is a living document that describes the smoothed and gap-filled MODIS VIs (LAI/FPAR from MOD15A2, and EVI/NDVI calculated from MOD09A2 and MOD09Q2). It is revised as progress is made in the development of these products. The purpose of the document is to give the potential user an understanding of the MOD09GFS and MOD15GFS products and the current state of the data in those products.
1] MODIS-based leaf area index (LAI) and normalized difference vegetation index (NDVI) are used t... more 1] MODIS-based leaf area index (LAI) and normalized difference vegetation index (NDVI) are used to examine detailed information regarding actual growing season and total annual production for various regions. Overall, MODIS LAI has larger variability and demonstrates more information regarding the evolution and structure of the seasonal vegetation characteristics. In contrast, the NDVI saturates around 0.7 and tends to overestimate the growing season in regions where it is already long. Next, a climatic impact index (CII) is derived to provide additional information regarding the potential sensitivity of vegetation to changes in climatic variables by accounting for the length of growing season. By normalizing the growth rate to the biome-average growth rate, this index can identify fractional loss of annual production, as opposed to the absolute loss which may be strongly weighted by the overall growth rate for different ecosystems. Our index provides a quantitative framework for assessing the importance of the length of the growing season in determining climatic vulnerability. In the last part of the paper, we use the long time series AVHRR products as a substitute for the MODIS products and test the temporal characteristics of the CII. Major drought events are well-captured by the CII, suggesting potential use as a monitoring and evaluation tool. Furthermore, the strong positive correlation between the CII and the vegetation condition index (VCI) suggests that the CII can quantitatively identify the effects of climatic variability upon vegetation activity. (2004), Climate-related vegetation characteristics derived from Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index and normalized difference vegetation index,
At seasonal to interannual time scales, vegetation phenology reflects dynamics of the Earth'... more At seasonal to interannual time scales, vegetation phenology reflects dynamics of the Earth's climate and hydrologic regimes, and is diagnostic of coupling between the Earth's biosphere and atmosphere. Information related to large scale phenology is therefore useful for studies of seasonal and interannual variability in carbon exchange and vegetation-climate interactions. Remote sensing provides a key means of measuring and monitoring phenology at continental to global scales and vegetation indices derived from satellite data are now commonly used for this purpose. Since April of 2000, the Moderate Resolution Imaging Spectroradiometer (MODIS) has been providing imagery of the Earth that is highly suitable for studies of phenology. At the same time, the use of MODIS data presents a number of significant technical challenges. In particular, residual atmospheric effects, clouds, and the presence of snow all introduce substantial uncertainty to estimates of phenology from MODIS. In this paper, we examine several key factors that affect the quality of phenological metrics derived from MODIS. These factors include: (1) the choice of vegetation index; (2) the method used to screen and correct the effects of snow; and (3) the technique used to fill time series gaps caused by clouds. We examined each of these factors using the MODIS land cover dynamics algorithm (MOD12Q2) for a set of locations that span a range of climate and ecosystem types. Our results show that the sensitivity of MOD12Q2 algorithm to the choice of vegetation index depends on the biome type. Specifically, we observed distinct differences in phenology inferred from EVI versus NDVI in densely vegetated areas caused by saturation of the NDVI. Conversely, in semi-arid areas we observed large differences arising from the different sensitivity of each index to sparse vegetation cover. Finally, our results indicate that the method used to account for snow has a pronounced effect on remotely sensed estimates for the beginning of the growing season.
ABSTRACT Time series from remote sensing data provide the unique capacity to estimate landscape l... more ABSTRACT Time series from remote sensing data provide the unique capacity to estimate landscape level phenology parameters for large regions through time. This presentation will describe a 250m x 250m spatial resolution phenology product for North America from 2001 to 2005. The phenology parameters are estimated from MODIS Normalized Difference Vegetation Index (NDVI) derived from the 8-day surface reflectance product. The algorithm for estimating phenology parameters is based on the TIMESAT software using enhancements that capitalize on the MODIS quality assurance data and an iterative procedure to fill gaps in space and time. The results provide the most spatially complete, highest resolution phenology product ever produced for the entire North American continent. These data are freely available through an on-line query and order system. The presentation will review the enhanced TIMESAT algorithm, provide a description of the phenology parameters included in the product, and an overview of the data distribution system. The advent of the US National Phenology Network will allow for coordination and disseminate of phenological observations at multiple scales and across scientific disciplines. The products presented here will be integrated into the NPN so that they can 1) promote landscape phenology research within NPN and 2) utilize NPN field and network data for validation studies. The presentation will describe our planned coordination with NPN.
ABSTRACT Vegetation indices (VIs) derived from satellite data are now commonly used for detecting... more ABSTRACT Vegetation indices (VIs) derived from satellite data are now commonly used for detecting vegetation phenology at continental to global scales. Vegetation phenology estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) VIs over North America from 2001 to 2006 have been produced and freely available online from http://www.accweb.nascom.nasa.gov. The algorithm to produce this MODIS phenology metrics is based on revised TIMESAT software, which uses the 3rd derivation of a fitted Gauss curve to locate four key phenology dates - begin and end of the greenup and browndown. In order to achieve a long-term phenology record, the same phenology detection algorithm is applied to 1982-2002 GIMMS AVHRR NDVI data sets over North America. To make the phenology estimations from different sensors consistent and comparable, several different methods are utilized in this research. We first compare the phenology metrics estimated from MODIS NDVI and AVHRR NDVI in 2001 and 2002. We found no significant latitudinal gradients in the AVHRR phenology metrics. At the same time, the length of the growing season is artificially overestimated in Northern US and Southern Canada. Both phenomena indicates lower quality from the AVHRR phenology metrics, which is mainly due to the unreliable snow flag of AVHRR data and the absence of ancillary land surface temperature data. To improve the quality of the AVHRR phenology metrics, a more accurate definition of non-growing season is required. We first use the 21-year climatologic mean of minimum NDVI as a threshold to refine the non-growing season pixels. In addition, a sensitivity analysis is performed to address the impact of the threshold on derived phenology metrics. Overall, this research will provide a 25-year phenology product for North America using both MODIS and AVHRR NDVI, which can be applied in regional/continental climate variation analysis and vegetation monitoring. The method to calibrate MODIS and AVHRR phenology products will provide a potential way for generating consistent vegetation phenology metrics from different sensors.
Information related to vegetation phenology is important for understanding seasonal and interannu... more Information related to vegetation phenology is important for understanding seasonal and interannual variability in ecosystems, carbon exchange, and vegetation-climate interactions. MODIS, the Moderate Resolution Imaging Spectroradiometer, provides an excellent source of data for large scale repeatable monitoring of phenology at global scales. This paper describes recent results from the Collection 5 (C5) MODIS Global Land Cover Dynamics product (MOD12Q2), which provides global data sets related to the timing, nature, and magnitude of vegetation phenology. The MOD12Q2 algorithm for estimating phenology is based on fitting piecewise logistic models to time series data of the Enhanced Vegetation Index (EVI) calculated from MODIS C5 Nadir BRDF-adjusted reflectance data. Our results show that the C5 Land Cover Dynamics product represents a significant step forward relative to previous MODIS products. In particular, the use of EVI data derived at 500-m spatial resolution and eight-day time intervals provides substantially improved temporal and spatial resolution relative to the Collection 4 (C4) product, which used 1-km, 16-day inputs. To assess C5 results, we evaluated the new C5 dataset extensively at a global scale for multiple years via (1) comparison with the MODIS C4 1-km product (a benchmark for our comparison), and (2) direct comparison of C5 phenological metrics with field observations collected at several sites in the northeastern United States. The results show general agreement of the C5 product with the C4 product in a majority of biomes, but with improved quality of the former compared to the latter. In addition, examination of C5 data sets exhibit significantly fewer missing values relative to C4, and generally in good agreement with ground measurements. Moving forward, the results from this analysis suggest that the MOD12Q2 product provides a good basis for seasonal to decadal scale studies of coupled climate-vegetation variability.