Tracking Climate Effects on Plant-Pollinator Interaction Phenology with Satellites and Honey Bee Hives

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Esaias, Wayne E.; Nickeson, Jaime E.; Tan, Bin; Ma, Peter L.; Nightingale, Joanne M.; Wolfe, Robert E.

2011-01-01

Background/Question/Methods: The complexity of plant-pollinator interactions, the large number of species involved, and the lack of species response functions present challenges to understanding how these critical interactions may be impacted by climate and land cover change on large scales. Given the importance of this interaction for terrestrial ecosystems, it is desirable to develop new approaches. We monitor the daily weight change of honey bee (Apis mellifera) colonies to record the phenology of the Honey Bee Nectar Flow (HBNF) in a volunteer network (honeybeenet.gsfc.nasa.gov). The records document the successful interaction of a generalist pollinator with a variety of plant resources. We extract useful HBNF phenology metrics for three seasons. Sites currently exist in 35 states/provinces in North America, with a concentration in the Mid-Atlantic region. HBNF metrics are compared to standard phenology metrics derived from remotely sensed vegetation indices from NASA's MODIS sensor and published results from NOAA's A VHRR. At any given time the percentage of plants producing nectar is usually a sma11 fraction of the total satellite sensor signal. We are interested in determining how well the 'bulk' satellite vegetation parameters relate to the phenology of the HBNF, and how it varies spatially on landscape to continental scales. Results/Conclusions: We found the median and peak seasonal HBNF dates to be robust, with variation between replicate scale hives of only a few days. We developed quality assessment protocols to identify abnormal colony artifacts. Temporally, the peak and median of the HBNF in the Mid-Atlantic show a significant advance of 0.58 d/y beginning about 1970, very similar to that observed by the A VHRR since 1982 (0.57 d/y). Spatially, the HBNF metrics are highly correlated with elevation and winter minimum temperature distribution, and exhibit significant but regionally coherent inter-annual variation. The relationship between median of the

Phenology Data Products to Support Assessment and Forecasting of Phenology on Multiple Spatiotemporal Scales

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Gerst, K.; Enquist, C.; Rosemartin, A.; Denny, E. G.; Marsh, L.; Moore, D. J.; Weltzin, J. F.

2014-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and environmental change. The National Phenology Database maintained by USA-NPN now has over 3.7 million records for plants and animals for the period 1954-2014, with the majority of these observations collected since 2008 as part of a broad, national contributory science strategy. These data have been used in a number of science, conservation and resource management applications, including national assessments of historical and potential future trends in phenology, regional assessments of spatio-temporal variation in organismal activity, and local monitoring for invasive species detection. Customizable data downloads are freely available, and data are accompanied by FGDC-compliant metadata, data-use and data-attribution policies, vetted and documented methodologies and protocols, and version control. While users are free to develop custom algorithms for data cleaning, winnowing and summarization prior to analysis, the National Coordinating Office of USA-NPN is developing a suite of standard data products to facilitate use and application by a diverse set of data users. This presentation provides a progress report on data product development, including: (1) Quality controlled raw phenophase status data; (2) Derived phenometrics (e.g. onset, duration) at multiple scales; (3) Data visualization tools; (4) Tools to support assessment of species interactions and overlap; (5) Species responsiveness to environmental drivers; (6) Spatially gridded phenoclimatological products; and (7) Algorithms for modeling and forecasting future phenological responses. The prioritization of these data products is a direct response to stakeholder needs related to informing management and policy decisions. We anticipate that these products will contribute to broad understanding of plant

The plant phenology monitoring design for the National Ecological Observatory Network

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Elmendorf, Sarah C; Jones, Katherine D; Cook, Benjamin I.; Diez, Jeffrey M.; Enquist, Carolyn A.F.; Hufft, Rebecca A.; Jones, Matthew O.; Mazer, Susan J.; Miller-Rushing, Abraham J.; Moore, David J. P.; Schwartz, Mark D.; Weltzin, Jake F.

2016-01-01

Phenology is an integrative science that comprises the study of recurring biological activities or events. In an era of rapidly changing climate, the relationship between the timing of those events and environmental cues such as temperature, snowmelt, water availability or day length are of particular interest. This article provides an overview of the plant phenology sampling which will be conducted by the U.S. National Ecological Observatory Network NEON, the resulting data, and the rationale behind the design. Trained technicians will conduct regular in situ observations of plant phenology at all terrestrial NEON sites for the 30-year life of the observatory. Standardized and coordinated data across the network of sites can be used to quantify the direction and magnitude of the relationships between phenology and environmental forcings, as well as the degree to which these relationships vary among sites, among species, among phenophases, and through time. Vegetation at NEON sites will also be monitored with tower-based cameras, satellite remote sensing and annual high-resolution airborne remote sensing. Ground-based measurements can be used to calibrate and improve satellite-derived phenometrics. NEON’s phenology monitoring design is complementary to existing phenology research efforts and citizen science initiatives throughout the world and will produce interoperable data. By collocating plant phenology observations with a suite of additional meteorological, biophysical and ecological measurements (e.g., climate, carbon flux, plant productivity, population dynamics of consumers) at 47 terrestrial sites, the NEON design will enable continentalscale inference about the status, trends, causes and ecological consequences of phenological change.

Combining satellite derived phenology with climate data for climate change impact assessment

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Ivits, E.; Cherlet, M.; Tóth, G.; Sommer, S.; Mehl, W.; Vogt, J.; Micale, F.

2012-05-01

The projected influence of climate change on the timing and volume of phytomass production is expected to affect a number of ecosystem services. In order to develop coherent and locally effective adaptation and mitigation strategies, spatially explicit information on the observed changes is needed. Long-term variations of the vegetative growing season in different environmental zones of Europe for 1982-2006 have been derived by analysing time series of GIMMS NDVI data. The associations of phenologically homogenous spatial clusters to time series of temperature and precipitation data were evaluated. North-east Europe showed a trend to an earlier and longer growing season, particularly in the northern Baltic areas. Despite the earlier greening up large areas of Europe exhibited rather stable season length indicating the shift of the entire growing season to an earlier period. The northern Mediterranean displayed a growing season shift towards later dates while some agglomerations of earlier and shorter growing season were also seen. The correlation of phenological time series with climate data shows a cause-and-effect relationship over the semi natural areas consistent with results in literature. Managed ecosystems however appear to have heterogeneous change pattern with less or no correlation to climatic trends. Over these areas climatic trends seemed to overlap in a complex manner with more pronounced effects of local biophysical conditions and/or land management practices. Our results underline the importance of satellite derived phenological observations to explain local nonconformities to climatic trends for climate change impact assessment.

Phenology-based Spartina alterniflora mapping in coastal wetland of the Yangtze Estuary using time series of GaoFen satellite no. 1 wide field of view imagery

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Ai, Jinquan; Gao, Wei; Gao, Zhiqiang; Shi, Runhe; Zhang, Chao

2017-04-01

Spartina alterniflora is an aggressive invasive plant species that replaces native species, changes the structure and function of the ecosystem across coastal wetlands in China, and is thus a major conservation concern. Mapping the spread of its invasion is a necessary first step for the implementation of effective ecological management strategies. The performance of a phenology-based approach for S. alterniflora mapping is explored in the coastal wetland of the Yangtze Estuary using a time series of GaoFen satellite no. 1 wide field of view camera (GF-1 WFV) imagery. First, a time series of the normalized difference vegetation index (NDVI) was constructed to evaluate the phenology of S. alterniflora. Two phenological stages (the senescence stage from November to mid-December and the green-up stage from late April to May) were determined as important for S. alterniflora detection in the study area based on NDVI temporal profiles, spectral reflectance curves of S. alterniflora and its coexistent species, and field surveys. Three phenology feature sets representing three major phenology-based detection strategies were then compared to map S. alterniflora: (1) the single-date imagery acquired within the optimal phenological window, (2) the multitemporal imagery, including four images from the two important phenological windows, and (3) the monthly NDVI time series imagery. Support vector machines and maximum likelihood classifiers were applied on each phenology feature set at different training sample sizes. For all phenology feature sets, the overall results were produced consistently with high mapping accuracies under sufficient training samples sizes, although significantly improved classification accuracies (10%) were obtained when the monthly NDVI time series imagery was employed. The optimal single-date imagery had the lowest accuracies of all detection strategies. The multitemporal analysis demonstrated little reduction in the overall accuracy compared with the

Comparing MODIS and near-surface vegetation indexes for monitoring tropical dry forest phenology along a successional gradient using optical phenology towers

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Rankine, C.; Sánchez-Azofeifa, G. A.; Guzmán, J. Antonio; Espirito-Santo, M. M.; Sharp, Iain

2017-10-01

Tropical dry forests (TDFs) present strong seasonal greenness signals ideal for tracking phenology and primary productivity using remote sensing techniques. The tightly synchronized relationship these ecosystems have with water availability offer a valuable natural experiment for observing the complex interactions between the atmosphere and the biosphere in the tropics. To investigate how well the MODIS vegetation indices (normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)) represented the phenology of different successional stages of naturally regenerating TDFs, within a widely conserved forest fragment in the semi-arid southeast of Brazil, we installed several canopy towers with radiometric sensors to produce high temporal resolution near-surface vegetation greenness indices. Direct comparison of several years of ground measurements with a combined Aqua/Terra 8 day satellite product showed similar broad temporal trends, but MODIS often suffered from cloud contamination during the onset of the growing season and occasionally during the peak growing season. The strength of the in-situ and MODIS linear relationship was greater for NDVI than for EVI across sites but varied with forest stand age. Furthermore, we describe the onset dates and duration of canopy development phases for three years of in-situ monitoring. A seasonality analysis revealed significant discrepancies between tower and MODIS phenology transitions dates, with up to five weeks differences in growing season length estimation. Our results indicate that 8 and 16 day MODIS satellite vegetation monitoring products are suitable for tracking general patterns of tropical dry forest phenology in this region but are not temporally sufficient to characterize inter-annual differences in phenology phase onset dates or changes in productivity due to mid-season droughts. Such rapid transitions in canopy greenness are important indicators of climate change sensitivity of these

Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to MODIS satellite imagery

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Park, Isaac W.

2012-11-01

This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to satellite-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods.

Environmental Drivers of NDVI-Based Vegetation Phenology in Central Asia

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Jahan Kariyeva

2011-02-01

Full Text Available Through the application and use of geospatial data, this study aimed to detect and characterize some of the key environmental drivers contributing to landscape-scale vegetation response patterns in Central Asia. The objectives of the study were to identify the variables driving the year-to-year vegetation dynamics in three regional landscapes (desert, steppe, and mountainous; and to determine if the identified environmental drivers can be used to explain the spatial-temporal variability of these spatio-temporal dynamics over time. It was posed that patterns of change in terrestrial phenology, derived from the 8 km bi-weekly time series of Normalized Difference Vegetation Index (NDVI data acquired by the Advanced Very High Resolution Radiometer (AVHRR satellites (1981–2008, can be explained through a multi-scale analysis of a suite of environmental drivers. Multiple linear stepwise regression analyses were used to test the hypotheses and address the objectives of the study. The annually computed phenological response variables or pheno-metricstime (season start, season length, and an NDVI-based productivity metric were modeled as a function of ten environmental factors relating to soil, topography, and climate. Each of the three studied regional landscapes was shown to be governed by a distinctive suite of environmental drivers. The phenological responses of the steppe landscapes were affected by the year-to-year variation in temperature regimes. The phenology of the mountainous landscapes was influenced primarily by the elevation gradient. The phenological responses of desert landscapes were demonstrated to have the greatest variability over time and seemed to be affected by soil carbon content and year-to-year variation of both temperature regimes and winter precipitation patterns. Amounts and scales of observed phenological variability over time (measured through coefficient of variation for each pheno-metrictime in each of the regional

Shifts in Arctic phenology in response to climate and anthropogenic factors as detected from multiple satellite time series

International Nuclear Information System (INIS)

Zeng, Heqing; Jia, Gensuo; Forbes, Bruce C

2013-01-01

There is an urgent need to reduce the uncertainties in remotely sensed detection of phenological shifts of high latitude ecosystems in response to climate changes in past decades. In this study, vegetation phenology in western Arctic Russia (the Yamal Peninsula) was investigated by analyzing and comparing Normalized Difference Vegetation Index (NDVI) time series derived from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and SPOT-Vegetation (VGT) during the decade 2000–2010. The spatial patterns of key phenological parameters were highly heterogeneous along the latitudinal gradients based on multi-satellite data. There was earlier SOS (start of the growing season), later EOS (end of the growing season), longer LOS (length of the growing season), and greater MaxNDVI from north to south in the region. The results based on MODIS and VGT data showed similar trends in phenological changes from 2000 to 2010, while quite a different trend was found based on AVHRR data from 2000 to 2008. A significantly delayed EOS (p < 0.01), thus increasing the LOS, was found from AVHRR data, while no similar trends were detected from MODIS and VGT data. There were no obvious shifts in MaxNDVI during the last decade. MODIS and VGT data were considered to be preferred data for monitoring vegetation phenology in northern high latitudes. Temperature is still a key factor controlling spatial phenological gradients and variability, while anthropogenic factors (reindeer husbandry and resource exploitation) might explain the delayed SOS in southern Yamal. Continuous environmental damage could trigger a positive feedback to the delayed SOS. (letter)

Variations in global land surface phenology: a comparison of satellite optical and passive microwave data

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Tong, X.; Tian, F.; Brandt, M.; Zhang, W.; Liu, Y.; Fensholt, R.

2017-12-01

Changes in vegetation phenological events are among the most sensitive biological responses to climate change. In last decades, facilitating by satellite remote sensing techniques, land surface phenology (LSP) have been monitored at global scale using proxy approaches as tracking the temporal change of a satellite-derived vegetation index. However, the existing global assessments of changes in LSP are all established on the basis of leaf phenology using NDVI derived from optical sensors, being responsive to vegetation canopy cover and greenness. Instead, the vegetation optical depth (VOD) parameter from passive microwave sensors, which is sensitive to the aboveground vegetation water content by including as well the woody components in the observations, provides an alternative, independent and comprehensive means for global vegetation phenology monitoring. We used the unique long-term global VOD record available for the period 1992-2012 to monitoring the dynamics of LSP metrics (length of season, start of season and end of season) in comparison with the dynamics of LSP metrics derived from the latest GIMMS NDVI3G V1. We evaluated the differences in the linear trends of LSP metrics between two datasets. Currently, our results suggest that the level of seasonality variation of vegetation water content is less than the vegetation greenness. We found significant phenological changes in vegetation water content in African woodlands, where has been reported with little leaf phenological change regardless of the delays in rainfall onset. Therefore, VOD might allow us to detect temporal shifts in the timing difference of vegetation water storage vs. leaf emergence and to see if some ecophysiological thresholds seem to be reached, that could cause species turnover as climate change-driven alterations to the African monsoon proceed.

Using satellite data to improve the leaf phenology of a global terrestrial biosphere model

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MacBean, N.; Maignan, F.; Peylin, P.; Bacour, C.; Bréon, F.-M.; Ciais, P.

2015-12-01

Correct representation of seasonal leaf dynamics is crucial for terrestrial biosphere models (TBMs), but many such models cannot accurately reproduce observations of leaf onset and senescence. Here we optimised the phenology-related parameters of the ORCHIDEE TBM using satellite-derived Normalized Difference Vegetation Index data (MODIS NDVI v5) that are linearly related to the model fAPAR. We found the misfit between the observations and the model decreased after optimisation for all boreal and temperate deciduous plant functional types, primarily due to an earlier onset of leaf senescence. The model bias was only partially reduced for tropical deciduous trees and no improvement was seen for natural C4 grasses. Spatial validation demonstrated the generality of the posterior parameters for use in global simulations, with an increase in global median correlation of 0.56 to 0.67. The simulated global mean annual gross primary productivity (GPP) decreased by ~ 10 PgC yr-1 over the 1990-2010 period due to the substantially shortened growing season length (GSL - by up to 30 days in the Northern Hemisphere), thus reducing the positive bias and improving the seasonal dynamics of ORCHIDEE compared to independent data-based estimates. Finally, the optimisations led to changes in the strength and location of the trends in the simulated vegetation productivity as represented by the GSL and mean annual fraction of absorbed photosynthetically active radiation (fAPAR), suggesting care should be taken when using un-calibrated models in attribution studies. We suggest that the framework presented here can be applied for improving the phenology of all global TBMs.

Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

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Suepa, Tanita

The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability

Comparison of phenology models for predicting the onset of growing season over the Northern Hemisphere.

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Yang Fu

Full Text Available Vegetation phenology models are important for examining the impact of climate change on the length of the growing season and carbon cycles in terrestrial ecosystems. However, large uncertainties in present phenology models make accurate assessment of the beginning of the growing season (BGS a challenge. In this study, based on the satellite-based phenology product (i.e. the V005 MODIS Land Cover Dynamics (MCD12Q2 product, we calibrated four phenology models, compared their relative strength to predict vegetation phenology; and assessed the spatial pattern and interannual variability of BGS in the Northern Hemisphere. The results indicated that parameter calibration significantly influences the models' accuracy. All models showed good performance in cool regions but poor performance in warm regions. On average, they explained about 67% (the Growing Degree Day model, 79% (the Biome-BGC phenology model, 73% (the Number of Growing Days model and 68% (the Number of Chilling Days-Growing Degree Day model of the BGS variations over the Northern Hemisphere. There were substantial differences in BGS simulations among the four phenology models. Overall, the Biome-BGC phenology model performed best in predicting the BGS, and showed low biases in most boreal and cool regions. Compared with the other three models, the two-phase phenology model (NCD-GDD showed the lowest correlation and largest biases with the MODIS phenology product, although it could catch the interannual variations well for some vegetation types. Our study highlights the need for further improvements by integrating the effects of water availability, especially for plants growing in low latitudes, and the physiological adaptation of plants into phenology models.

Comparison of phenology models for predicting the onset of growing season over the Northern Hemisphere.

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Fu, Yang; Zhang, Haicheng; Dong, Wenjie; Yuan, Wenping

2014-01-01

Vegetation phenology models are important for examining the impact of climate change on the length of the growing season and carbon cycles in terrestrial ecosystems. However, large uncertainties in present phenology models make accurate assessment of the beginning of the growing season (BGS) a challenge. In this study, based on the satellite-based phenology product (i.e. the V005 MODIS Land Cover Dynamics (MCD12Q2) product), we calibrated four phenology models, compared their relative strength to predict vegetation phenology; and assessed the spatial pattern and interannual variability of BGS in the Northern Hemisphere. The results indicated that parameter calibration significantly influences the models' accuracy. All models showed good performance in cool regions but poor performance in warm regions. On average, they explained about 67% (the Growing Degree Day model), 79% (the Biome-BGC phenology model), 73% (the Number of Growing Days model) and 68% (the Number of Chilling Days-Growing Degree Day model) of the BGS variations over the Northern Hemisphere. There were substantial differences in BGS simulations among the four phenology models. Overall, the Biome-BGC phenology model performed best in predicting the BGS, and showed low biases in most boreal and cool regions. Compared with the other three models, the two-phase phenology model (NCD-GDD) showed the lowest correlation and largest biases with the MODIS phenology product, although it could catch the interannual variations well for some vegetation types. Our study highlights the need for further improvements by integrating the effects of water availability, especially for plants growing in low latitudes, and the physiological adaptation of plants into phenology models.

Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

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Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna

2016-01-01

This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

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Laura Ulsig

2017-01-01

Full Text Available Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI. This study investigates the potential of a Photochemical Reflectance Index (PRI, which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R2 = 0.36–0.8, which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R2 > 0.6 in all cases. The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

Remote Sensing of Lake Ice Phenology in Alaska

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Zhang, S.; Pavelsky, T.

2017-12-01

Lake ice phenology (e.g. ice break-up and freeze-up timing) in Alaska is potentially sensitive to climate change. However, there are few current lake ice records in this region, which hinders the comprehensive understanding of interactions between climate change and lake processes. To provide a lake ice database with over a comparatively long time period (2000 - 2017) and large spatial coverage (4000+ lakes) in Alaska, we have developed an algorithm to detect the timing of lake ice using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. This approach generally consists of three major steps. First, we use a cloud mask (MOD09GA) to filter out satellite images with heavy cloud contamination. Second, daily MODIS reflectance values (MOD09GQ) of lake surface are used to extract ice pixels from water pixels. The ice status of lakes can be further identified based on the fraction of ice pixels. Third, to improve the accuracy of ice phenology detection, we execute post-processing quality control to reduce false ice events caused by outliers. We validate the proposed algorithm over six lakes by comparing with Landsat-based reference data. Validation results indicate a high correlation between the MODIS results and reference data, with normalized root mean square error (NRMSE) ranging from 1.7% to 4.6%. The time series of this lake ice product is then examined to analyze the spatial and temporal patterns of lake ice phenology.

Interannual variability of plant phenology in tussock tundra: modelling interactions of plant productivity, plant phenology, snowmelt and soil thaw

NARCIS (Netherlands)

Wijk, van M.T.; Williams, M.; Laundre, J.A.; Shaver, G.R.

2003-01-01

We present a linked model of plant productivity, plant phenology, snowmelt and soil thaw in order to estimate interannual variability of arctic plant phenology and its effects on plant productivity. The model is tested using 8 years of soil temperature data, and three years of bud break data of

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

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Greg Easson

2007-12-01

Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

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Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

2015-12-01

Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

Investigating the Relationship between the Inter-Annual Variability of Satellite-Derived Vegetation Phenology and a Proxy of Biomass Production in the Sahel

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Michele Meroni

2014-06-01

Full Text Available In the Sahel region, moderate to coarse spatial resolution remote sensing time series are used in early warning monitoring systems with the aim of detecting unfavorable crop and pasture conditions and informing stakeholders about impending food security risks. Despite growing evidence that vegetation productivity is directly related to phenology, most approaches to estimate such risks do not explicitly take into account the actual timing of vegetation growth and development. The date of the start of the season (SOS or of the peak canopy density can be assessed by remote sensing techniques in a timely manner during the growing season. However, there is limited knowledge about the relationship between vegetation biomass production and these variables at the regional scale. This study describes the first attempt to increase our understanding of such a relationship through the analysis of phenological variables retrieved from SPOT-VEGETATION time series of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR. Two key phenological variables (growing season length (GSL; timing of SOS and the maximum value of FAPAR attained during the growing season (Peak are analyzed as potentially related to a proxy of biomass production (CFAPAR, the cumulative value of FAPAR during the growing season. GSL, SOS and Peak all show different spatial patterns of correlation with CFAPAR. In particular, GSL shows a high and positive correlation with CFAPAR over the whole Sahel (mean r = 0.78. The negative correlation between delays in SOS and CFAPAR is stronger (mean r = −0.71 in the southern agricultural band of the Sahel, while the positive correlation between Peak FAPAR and CFAPAR is higher in the northern and more arid grassland region (mean r = 0.75. The consistency of the results and the actual link between remote sensing-derived phenological parameters and biomass production were evaluated using field measurements of aboveground herbaceous biomass

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors.

Science.gov (United States)

Lange, Maximilian; Dechant, Benjamin; Rebmann, Corinna; Vohland, Michael; Cuntz, Matthias; Doktor, Daniel

2017-08-11

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.

Object-based Dimensionality Reduction in Land Surface Phenology Classification

Directory of Open Access Journals (Sweden)

Brian E. Bunker

2016-11-01

Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

Variability in the mechanisms controlling Southern Ocean phytoplankton bloom phenology in an ocean model and satellite observations

Science.gov (United States)

Rohr, Tyler; Long, Matthew C.; Kavanaugh, Maria T.; Lindsay, Keith; Doney, Scott C.

2017-05-01

A coupled global numerical simulation (conducted with the Community Earth System Model) is used in conjunction with satellite remote sensing observations to examine the role of top-down (grazing pressure) and bottom-up (light, nutrients) controls on marine phytoplankton bloom dynamics in the Southern Ocean. Phytoplankton seasonal phenology is evaluated in the context of the recently proposed "disturbance-recovery" hypothesis relative to more traditional, exclusively "bottom-up" frameworks. All blooms occur when phytoplankton division rates exceed loss rates to permit sustained net population growth; however, the nature of this decoupling period varies regionally in Community Earth System Model. Regional case studies illustrate how unique pathways allow blooms to emerge despite very poor division rates or very strong grazing rates. In the Subantarctic, southeast Pacific small spring blooms initiate early cooccurring with deep mixing and low division rates, consistent with the disturbance-recovery hypothesis. Similar systematics are present in the Subantarctic, southwest Atlantic during the spring but are eclipsed by a subsequent, larger summer bloom that is coincident with shallow mixing and the annual maximum in division rates, consistent with a bottom-up, light limited framework. In the model simulation, increased iron stress prevents a similar summer bloom in the southeast Pacific. In the simulated Antarctic zone (70°S-65°S) seasonal sea ice acts as a dominant phytoplankton-zooplankton decoupling agent, triggering a delayed but substantial bloom as ice recedes. Satellite ocean color remote sensing and ocean physical reanalysis products do not precisely match model-predicted phenology, but observed patterns do indicate regional variability in mechanism across the Atlantic and Pacific.

Operational data products to support phenological research and applications at local to continental scales

Science.gov (United States)

Weltzin, J. F.

2017-12-01

Phenological data from a variety of platforms - across a range of spatial and temporal scales - are required to support research, natural resource management, and policy- and decision-making in a changing world. Observational and modeled phenological data, especially when integrated with associated biophysical data (e.g., climate, land-use/land-cover, hydrology) has great potential to provide multi-faceted information critical to decision support systems, vulnerability and risk assessments, change detection applications, and early-warning and forecasting systems for natural and modified ecosystems. The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on understanding the drivers and feedback effects of phenological variation in changing environments. The Network maintains a centralized database of over 10M ground-based observations of plants and animals for 1954-present, and leverages these data to produce operational data products for use by a variety of audiences, including researchers and resource managers. This presentation highlights our operational data products, including the tools, maps, and services that facilitate discovery, accessibility and usability of integrated phenological information. We describe (1) the data download tool, a customizable GUI that provides geospatially referenced raw, bounded or summarized organismal and climatological data and associated metadata (including calendars, time-series curves, and XY graphs), (2) the visualization tool, which provides opportunities to explore, visualize and export or download both organismal and modeled (gridded) products at daily time-steps and relatively fine spatial resolutions ( 2.5 km to 4 km) for the period 1980 to 6 days into the future, and (3) web services that enable custom query and download of map, feature and cover services in a variety of standard formats. These operational products facilitate scaling of integrated

Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

Science.gov (United States)

Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

2014-08-01

The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

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Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

2010-01-01

Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing.

Science.gov (United States)

Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve

2018-04-09

Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

Object-Based Assessment of Satellite Precipitation Products

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Jingjing Li

2016-06-01

Full Text Available An object-based verification approach is employed to assess the performance of the commonly used high-resolution satellite precipitation products: Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN, Climate Prediction center MORPHing technique (CMORPH, and Tropical Rainfall Measurement Mission (TRMM Multi-Satellite Precipitation Analysis (TMPA 3B42RT. The evaluation of the satellite precipitation products focuses on the skill of depicting the geometric features of the localized precipitation areas. Seasonal variability of the performances of these products against the ground observations is investigated through the examples of warm and cold seasons. It is found that PERSIANN is capable of depicting the orientation of the localized precipitation areas in both seasons. CMORPH has the ability to capture the sizes of the localized precipitation areas and performs the best in the overall assessment for both seasons. 3B42RT is capable of depicting the location of the precipitation areas for both seasons. In addition, all of the products perform better on capturing the sizes and centroids of precipitation areas in the warm season than in the cold season, while they perform better on depicting the intersection area and orientation in the cold season than in the warm season. These products are more skillful on correctly detecting the localized precipitation areas against the observations in the warm season than in the cold season.

Adaptive value of phenological traits in stressful environments: predictions based on seed production and laboratory natural selection.

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Benjamin Brachi

Full Text Available Phenological traits often show variation within and among natural populations of annual plants. Nevertheless, the adaptive value of post-anthesis traits is seldom tested. In this study, we estimated the adaptive values of pre- and post-anthesis traits in two stressful environments (water stress and interspecific competition, using the selfing annual species Arabidopsis thaliana. By estimating seed production and by performing laboratory natural selection (LNS, we assessed the strength and nature (directional, disruptive and stabilizing of selection acting on phenological traits in A. thaliana under the two tested stress conditions, each with four intensities. Both the type of stress and its intensity affected the strength and nature of selection, as did genetic constraints among phenological traits. Under water stress, both experimental approaches demonstrated directional selection for a shorter life cycle, although bolting time imposes a genetic constraint on the length of the interval between bolting and anthesis. Under interspecific competition, results from the two experimental approaches showed discrepancies. Estimation of seed production predicted directional selection toward early pre-anthesis traits and long post-anthesis periods. In contrast, the LNS approach suggested neutrality for all phenological traits. This study opens questions on adaptation in complex natural environment where many selective pressures act simultaneously.

Long-term phenology and variability of Southern Africa

CSIR Research Space (South Africa)

Steenkamp, K

2008-11-01

Full Text Available and classification of vegetation, (ii) studying the impact of climate change, and influence of rainfall variability (iii) monitoring Satellite-derived phenology and (iv) detecting changes in land use/ land cover. This study analyzed vegetation phenology across...

Variability and Changes in Climate, Phenology, and Gross Primary Production of an Alpine Wetland Ecosystem

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Xiaoming Kang

2016-05-01

Full Text Available Quantifying the variability and changes in phenology and gross primary production (GPP of alpine wetlands in the Qinghai–Tibetan Plateau under climate change is essential for assessing carbon (C balance dynamics at regional and global scales. In this study, in situ eddy covariance (EC flux tower observations and remote sensing data were integrated with a modified, satellite-based vegetation photosynthesis model (VPM to investigate the variability in climate change, phenology, and GPP of an alpine wetland ecosystem, located in Zoige, southwestern China. Two-year EC data and remote sensing vegetation indices showed that warmer temperatures corresponded to an earlier start date of the growing season, increased GPP, and ecosystem respiration, and hence increased the C sink strength of the alpine wetlands. Twelve-year long-term simulations (2000–2011 showed that: (1 there were significantly increasing trends for the mean annual enhanced vegetation index (EVI, land surface water index (LSWI, and growing season GPP (R2 ≥ 0.59, p < 0.01 at rates of 0.002, 0.11 year−1 and 16.32 g·C·m−2·year−1, respectively, which was in line with the observed warming trend (R2 = 0.54, p = 0.006; (2 the start and end of the vegetation growing season (SOS and EOS experienced a continuous advancing trend at a rate of 1.61 days·year−1 and a delaying trend at a rate of 1.57 days·year−1 from 2000 to 2011 (p ≤ 0.04, respectively; and (3 with increasing temperature, the advanced SOS and delayed EOS prolonged the wetland’s phenological and photosynthetically active period and, thereby, increased wetland productivity by about 3.7–4.2 g·C·m−2·year−1 per day. Furthermore, our results indicated that warming and the extension of the growing season had positive effects on carbon uptake in this alpine wetland ecosystem.

Climate change impacts on corn phenology and productivity

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Climate is changing around the world and will impact future production of all food and feed crops. Corn is no exception to these impacts and to ensure a future supply of this vital crop we must begin to understand how climate impacts both the phenological development of corn and the productivity. Te...

Satellite derived phenology of southern Africa for 1985-2000 and functional classification of vegetation based on phenometrics

CSIR Research Space (South Africa)

Steenkamp, K

2009-05-01

Full Text Available analyzed vegetation phenometrics across South Africa (SA) in order to characterize phenological patterns and their inter-annual variability. A second objective is to distinguish biomes and sub-biome “bioregions” based on functional patterns. The long term...

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

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Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

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Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

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Guenther Seufert

2009-02-01

Full Text Available In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC with the aims of i improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

Season Spotter: Using Citizen Science to Validate and Scale Plant Phenology from Near-Surface Remote Sensing

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Margaret Kosmala

2016-09-01

Full Text Available The impact of a rapidly changing climate on the biosphere is an urgent area of research for mitigation policy and management. Plant phenology is a sensitive indicator of climate change and regulates the seasonality of carbon, water, and energy fluxes between the land surface and the climate system, making it an important tool for studying biosphere–atmosphere interactions. To monitor plant phenology at regional and continental scales, automated near-surface cameras are being increasingly used to supplement phenology data derived from satellite imagery and data from ground-based human observers. We used imagery from a network of phenology cameras in a citizen science project called Season Spotter to investigate whether information could be derived from these images beyond standard, color-based vegetation indices. We found that engaging citizen science volunteers resulted in useful science knowledge in three ways: first, volunteers were able to detect some, but not all, reproductive phenology events, connecting landscape-level measures with field-based measures. Second, volunteers successfully demarcated individual trees in landscape imagery, facilitating scaling of vegetation indices from organism to ecosystem. And third, volunteers’ data were used to validate phenology transition dates calculated from vegetation indices and to identify potential improvements to existing algorithms to enable better biological interpretation. As a result, the use of citizen science in combination with near-surface remote sensing of phenology can be used to link ground-based phenology observations to satellite sensor data for scaling and validation. Well-designed citizen science projects targeting improved data processing and validation of remote sensing imagery hold promise for providing the data needed to address grand challenges in environmental science and Earth observation.

Mapping Deforestation in North Korea Using Phenology-Based Multi-Index and Random Forest

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Yihua Jin

2016-12-01

Full Text Available Phenology-based multi-index with the random forest (RF algorithm can be used to overcome the shortcomings of traditional deforestation mapping that involves pixel-based classification, such as ISODATA or decision trees, and single images. The purpose of this study was to investigate methods to identify specific types of deforestation in North Korea, and to increase the accuracy of classification, using phenological characteristics extracted with multi-index and random forest algorithms. The mapping of deforestation area based on RF was carried out by merging phenology-based multi-indices (i.e., normalized difference vegetation index (NDVI, normalized difference water index (NDWI, and normalized difference soil index (NDSI derived from MODIS (Moderate Resolution Imaging Spectroradiometer products and topographical variables. Our results showed overall classification accuracy of 89.38%, with corresponding kappa coefficients of 0.87. In particular, for forest and farm land categories with similar phenological characteristic (e.g., paddy, plateau vegetation, unstocked forest, hillside field, this approach improved the classification accuracy in comparison with pixel-based methods and other classes. The deforestation types were identified by incorporating point data from high-resolution imagery, outcomes of image classification, and slope data. Our study demonstrated that the proposed methodology could be used for deciding on the restoration priority and monitoring the expansion of deforestation areas.

Beyond leaf color: Comparing camera-based phenological metrics with leaf biochemical, biophysical, and spectral properties throughout the growing season of a temperate deciduous forest

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Yang, Xi; Tang, Jianwu; Mustard, John F.

2014-03-01

Plant phenology, a sensitive indicator of climate change, influences vegetation-atmosphere interactions by changing the carbon and water cycles from local to global scales. Camera-based phenological observations of the color changes of the vegetation canopy throughout the growing season have become popular in recent years. However, the linkages between camera phenological metrics and leaf biochemical, biophysical, and spectral properties are elusive. We measured key leaf properties including chlorophyll concentration and leaf reflectance on a weekly basis from June to November 2011 in a white oak forest on the island of Martha's Vineyard, Massachusetts, USA. Concurrently, we used a digital camera to automatically acquire daily pictures of the tree canopies. We found that there was a mismatch between the camera-based phenological metric for the canopy greenness (green chromatic coordinate, gcc) and the total chlorophyll and carotenoids concentration and leaf mass per area during late spring/early summer. The seasonal peak of gcc is approximately 20 days earlier than the peak of the total chlorophyll concentration. During the fall, both canopy and leaf redness were significantly correlated with the vegetation index for anthocyanin concentration, opening a new window to quantify vegetation senescence remotely. Satellite- and camera-based vegetation indices agreed well, suggesting that camera-based observations can be used as the ground validation for satellites. Using the high-temporal resolution dataset of leaf biochemical, biophysical, and spectral properties, our results show the strengths and potential uncertainties to use canopy color as the proxy of ecosystem functioning.

Modeling the Effects of the Urban Built-Up Environment on Plant Phenology Using Fused Satellite Data

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Norman Gervais

2017-01-01

Full Text Available Understanding the effects that the Urban Heat Island (UHI has on plant phenology is important in predicting ecological impacts of expanding cities and the impacts of the projected global warming. However, the underlying methods to monitor phenological events often limit this understanding. Generally, one can either have a small sample of in situ measurements or use satellite data to observe large areas of land surface phenology (LSP. In the latter, a tradeoff exists among platforms with some allowing better temporal resolution to pick up discrete events and others possessing the spatial resolution appropriate for observing heterogeneous landscapes, such as urban areas. To overcome these limitations, we applied the Spatial and Temporal Adaptive Reflectance Model (STARFM to fuse Landsat surface reflectance and MODIS nadir BRDF-adjusted reflectance (NBAR data with three separate selection conditions for input data across two versions of the software. From the fused images, we derived a time-series of high temporal and high spatial resolution synthetic Normalized Difference Vegetation Index (NDVI imagery to identify the dates of the start of the growing season (SOS, end of the season (EOS, and the length of the season (LOS. The results were compared between the urban and exurban developed areas within the vicinity of Ogden, UT and across all three data scenarios. The results generally show an earlier urban SOS, later urban EOS, and longer urban LOS, with variation across the results suggesting that phenological parameters are sensitive to input changes. Although there was strong evidence that STARFM has the potential to produce images capable of capturing the UHI effect on phenology, we recommend that future work refine the proposed methods and compare the results against ground events.

Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn

DEFF Research Database (Denmark)

Wu, Chaoyang; Chen, Xi Jing; Black, T. Andrew

2013-01-01

To investigate the importance of autumn phenology in controlling interannual variability of forest net ecosystem productivity (NEP) and to derive new phenological metrics to explain the interannual variability of NEP. North America and Europe. Flux data from nine deciduous broadleaf forests (DBF......, soil water content and precipitation, were also used to explain the phenological variations. We found that interannual variability of NEP can be largely explained by autumn phenology, i.e. the autumn lag. While variation in neither annual gross primary productivity (GPP) nor in annual ecosystem...

Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health

Science.gov (United States)

Luvall, Jeffrey C.; Sprigg, W. A.; Huete, A.; Nickovic, S.; Pejanovic, G.; Levetin, E.; Van de water, P.; Myers, O.; Budge, A. M.; Krapfl, H.;

A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers.

Science.gov (United States)

Gamon, John A; Huemmrich, K Fred; Wong, Christopher Y S; Ensminger, Ingo; Garrity, Steven; Hollinger, David Y; Noormets, Asko; Peñuelas, Josep

2016-11-15

In evergreen conifers, where the foliage amount changes little with season, accurate detection of the underlying "photosynthetic phenology" from satellite remote sensing has been difficult, presenting challenges for global models of ecosystem carbon uptake. Here, we report a close correspondence between seasonally changing foliar pigment levels, expressed as chlorophyll/carotenoid ratios, and evergreen photosynthetic activity, leading to a "chlorophyll/carotenoid index" (CCI) that tracks evergreen photosynthesis at multiple spatial scales. When calculated from NASA's Moderate Resolution Imaging Spectroradiometer satellite sensor, the CCI closely follows the seasonal patterns of daily gross primary productivity of evergreen conifer stands measured by eddy covariance. This discovery provides a way of monitoring evergreen photosynthetic activity from optical remote sensing, and indicates an important regulatory role for carotenoid pigments in evergreen photosynthesis. Improved methods of monitoring photosynthesis from space can improve our understanding of the global carbon budget in a warming world of changing vegetation phenology.

Satellite-Based Sunshine Duration for Europe

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Bodo Ahrens

2013-06-01

Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

Coupling mammalian demography to climate through satellite time series of plant phenology

Science.gov (United States)

Stoner, D.; Sexton, J. O.; Nagol, J. R.; Ironside, K.; Choate, D.; Longshore, K.; Edwards, T., Jr.

2016-12-01

The seasonality of plant productivity governs the demography of primary and secondary consumers, and in arid ecosystems primary production is constrained by water availability. We relate the behavior, demography, and spatial distribution of large mammalian herbivores and their principal predator to remotely sensed indices of climate and vegetation across the western United States from 2000-2014. Terrain and plant community composition moderate the effects of climatological drought on primary productivity, resulting in spatial variation in ecosystem susceptibility to water stress. Herbivores track these patterns through habitat selection during key periods such as birthing and migration. Across a broad climatological gradient, timing of the start of growing season explains 75% of the variation in herbivore birth timing and 56% of the variation in neonatal survival rates. Initiation of autumn migration corresponds with the end of the growing season. Although indirectly coupled to primary production, carnivore home range size and population density are strongly correlated with plant productivity and growing-season length. Satellite measures of green reflectance during the peak of the growing season explain over 84% of the variation in carnivore home range size and 59% of the variation in density. Climate projections for the western United States predict warming temperatures and shifts in the timing and form of precipitation. Our analyses suggest that increased climatological variability will contribute to fluctuations in the composition and phenology of plant communities. These changes will propagate through consumer trophic levels, manifesting as increased home range area, shifts in the timing of migration, and greater volatility in large mammal populations. Combined with expansion and amplification of human land uses, these changes will likely have economic implications stemming from increased human-wildlife conflict and loss of ecosystem services.

Atmospheric circulation patterns and phenological anomalies of grapevine in Italy

Science.gov (United States)

Cola, Gabriele; Alilla, Roberta; Dal Monte, Giovanni; Epifani, Chiara; Mariani, Luigi; Parisi, Simone Gabriele

2014-05-01

Grapevine (Vitis vinifera L.) is a fundamental crop for Italian agriculture as testified by the first place of Italy in the world producers ranking. This justify the importance of quantitative analyses referred to this crucial crop and aimed to quantify meteorological resources and limitations to development and production. Phenological rhythms of grapevine are strongly affected by surface fields of air temperature which in their turn are affected by synoptic circulation. This evidence highlights the importance of an approach based on dynamic climatology in order to detect and explain phenological anomalies that can have relevant effects on quantity and quality of grapevine production. In this context, this research is aimed to study the existing relation among the 850 hPa circulation patterns over the Euro-Mediterranean area from NOAA Ncep dataset and grapevine phenological fields for Italy over the period 2006-2013, highlighting the main phenological anomalies and analyzing synoptic determinants. This work is based on phenological fields with a standard pixel of 2 km routinely produced from 2006 by the Iphen project (Italian Phenological network) on the base of phenological observations spatialized by means of a specific algorithm based on cumulated thermal resources expressed as Normal Heat Hours (NHH). Anomalies have been evaluated with reference to phenological normal fields defined for the Italian area on the base of phenological observations and Iphen model. Results show that relevant phenological anomalies observed over the reference period are primarily associated with long lasting blocking systems driving cold air masses (Arctic or Polar-Continental) or hot ones (Sub-Tropical) towards the Italian area. Specific cases are presented for some years like 2007 and 2011.

Biome-Scale Forest Properties in Amazonia Based on Field and Satellite Observations

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Liana O. Anderson

2012-05-01

Full Text Available Amazonian forests are extremely heterogeneous at different spatial scales. This review intends to present the large-scale patterns of the ecosystem properties of Amazonia, and focuses on two parts of the main components of the net primary production: the long-lived carbon pools (wood and short-lived pools (leaves. First, the focus is on forest biophysical properties, and secondly, on the macro-scale leaf phenological patterns of these forests, looking at field measurements and bringing into discussion the recent findings derived from remote sensing dataset. Finally, I discuss the results of the three major droughts that hit Amazonia in the last 15 years. The panorama that emerges from this review suggests that slow growing forests in central and eastern Amazonia, where soils are poorer, have significantly higher above ground biomass and higher wood density, trees are higher and present lower proportions of large-leaved species than stands in northwest and southwest Amazonia. However, the opposite pattern is observed in relation to forest productivity and dynamism, which is higher in western Amazonia than in central and eastern forests. The spatial patterns on leaf phenology across Amazonia are less marked. Field data from different forest formations showed that new leaf production can be unrelated to climate seasonality, timed with radiation, timed with rainfall and/or river levels. Oppositely, satellite images exhibited a large-scale synchronized peak in new leaf production during the dry season. Satellite data and field measurements bring contrasting results for the 2005 drought. Discussions on data processing and filtering, aerosols effects and a combined analysis with field and satellite images are presented. It is suggested that to improve the understanding of the large-scale patterns on Amazonian forests, integrative analyses that combine new technologies in remote sensing and long-term field ecological data are imperative.

Object-Based Land Use Classification of Agricultural Land by Coupling Multi-Temporal Spectral Characteristics and Phenological Events in Germany

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Knoefel, Patrick; Loew, Fabian; Conrad, Christopher

2015-04-01

Crop maps based on classification of remotely sensed data are of increased attendance in agricultural management. This induces a more detailed knowledge about the reliability of such spatial information. However, classification of agricultural land use is often limited by high spectral similarities of the studied crop types. More, spatially and temporally varying agro-ecological conditions can introduce confusion in crop mapping. Classification errors in crop maps in turn may have influence on model outputs, like agricultural production monitoring. One major goal of the PhenoS project ("Phenological structuring to determine optimal acquisition dates for Sentinel-2 data for field crop classification"), is the detection of optimal phenological time windows for land cover classification purposes. Since many crop species are spectrally highly similar, accurate classification requires the right selection of satellite images for a certain classification task. In the course of one growing season, phenological phases exist where crops are separable with higher accuracies. For this purpose, coupling of multi-temporal spectral characteristics and phenological events is promising. The focus of this study is set on the separation of spectrally similar cereal crops like winter wheat, barley, and rye of two test sites in Germany called "Harz/Central German Lowland" and "Demmin". However, this study uses object based random forest (RF) classification to investigate the impact of image acquisition frequency and timing on crop classification uncertainty by permuting all possible combinations of available RapidEye time series recorded on the test sites between 2010 and 2014. The permutations were applied to different segmentation parameters. Then, classification uncertainty was assessed and analysed, based on the probabilistic soft-output from the RF algorithm at the per-field basis. From this soft output, entropy was calculated as a spatial measure of classification uncertainty

Vegetation responses to sagebrush-reduction treatments measured by satellites

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Johnston, Aaron; Beever, Erik; Merkle, Jerod A.; Chong, Geneva W.

2018-01-01

Time series of vegetative indices derived from satellite imagery constitute tools to measure ecological effects of natural and management-induced disturbances to ecosystems. Over the past century, sagebrush-reduction treatments have been applied widely throughout western North America to increase herbaceous vegetation for livestock and wildlife. We used indices from satellite imagery to 1) quantify effects of prescribed-fire, herbicide, and mechanical treatments on vegetative cover, productivity, and phenology, and 2) describe how vegetation changed over time following these treatments. We hypothesized that treatments would increase herbaceous cover and accordingly shift phenologies towards those typical of grass-dominated systems. We expected prescribed burns would lead to the greatest and most-prolonged effects on vegetative cover and phenology, followed by herbicide and mechanical treatments. Treatments appeared to increase herbaceous cover and productivity, which coincided with signs of earlier senescence − signals expected of grass-dominated systems, relative to sagebrush-dominated systems. Spatial heterogeneity for most phenometrics was lower in treated areas relative to controls, which suggested treatment-induced homogenization of vegetative communities. Phenometrics that explain spring migrations of ungulates mostly were unaffected by sagebrush treatments. Fire had the strongest effect on vegetative cover, and yielded the least evidence for sagebrush recovery. Overall, treatment effects were small relative to those reported from field-based studies for reasons most likely related to sagebrush recovery, treatment specification, and untreated patches within mosaicked treatment applications. Treatment effects were also small relative to inter-annual variation in phenology and productivity that was explained by temperature, snowpack, and growing-season precipitation. Our results indicated that cumulative NDVI, late-season phenometrics, and spatial

Seasonal phenology and species composition of the aphid fauna in a northern crop production area.

Directory of Open Access Journals (Sweden)

Sascha M Kirchner

Full Text Available BACKGROUND: The species diversity of aphids and seasonal timing of their flight activity can have significant impacts on crop production, as aphid species differ in their ability to transmit plant viruses and flight timing affects virus epidemiology. The aim of the study was to characterise the species composition and phenology of aphid fauna in Finland in one of the northernmost intensive crop production areas of the world (latitude 64°. METHODOLOGY/PRINCIPAL FINDINGS: Flight activity was monitored in four growing seasons (2007-010 using yellow pan traps (YPTs placed in 4-8 seed potato fields and a Rothamsted suction trap. A total of 58,528 winged aphids were obtained, identified to 83 taxa based on morphology, and 34 species were additionally characterised by DNA barcoding. Seasonal flight activity patterns analysed based on YPT catch fell into three main phenology clusters. Monoecious taxa showed early or middle-season flight activity and belonged to species living on shrubs/trees or herbaceous plants, respectively. Heteroecious taxa occurred over the entire potato growing season (ca. 90 days. Abundance of aphids followed a clear 3-year cycle based on suction trap data covering a decade. Rhopalosiphum padi occurring at the end of the potato growing season was the most abundant species. The flight activity of Aphis fabae, the main vector of Potato virus Y in the region, and Aphis gossypii peaked in the beginning of potato growing season. CONCLUSIONS/SIGNIFICANCE: Detailed information was obtained on phenology of a large number aphid species, of which many are agriculturally important pests acting as vectors of plant viruses. Aphis gossypii is known as a pest in greenhouses, but our study shows that it occurs also in the field, even far in the north. The novel information on aphid phenology and ecology has wide implications for prospective pest management, particularly in light of climate change.

MODIS phenology image service ArcMap toolbox

Science.gov (United States)

Talbert, Colin; Kern, Tim J.; Morisette, Jeff; Brown, Don; James, Kevin

2013-01-01

Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales. A cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by

Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

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Singaiah Chintalapudi

2014-05-01

Full Text Available In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model To Evaluate Juniperus spp. Pollen Phenology and Dispersal

Science.gov (United States)

Luvall, J. C.; Sprigg, W. A.; Levetin, Estelle; Huete, Alfredo; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Myers, O. B.; Budge, A. M.;

Estimation of PV energy production based on satellite data

Science.gov (United States)

Mazurek, G.

2015-09-01

Photovoltaic (PV) technology is an attractive source of power for systems without connection to power grid. Because of seasonal variations of solar radiation, design of such a power system requires careful analysis in order to provide required reliability. In this paper we present results of three-year measurements of experimental PV system located in Poland and based on polycrystalline silicon module. Irradiation values calculated from results of ground measurements have been compared with data from solar radiation databases employ calculations from of satellite observations. Good convergence level of both data sources has been shown, especially during summer. When satellite data from the same time period is available, yearly and monthly production of PV energy can be calculated with 2% and 5% accuracy, respectively. However, monthly production during winter seems to be overestimated, especially in January. Results of this work may be helpful in forecasting performance of similar PV systems in Central Europe and allow to make more precise forecasts of PV system performance than based only on tables with long time averaged values.

Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

Science.gov (United States)

Liu, Z.; Shie, C. L.; Meyer, D. J.

2017-12-01

Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

Networked web-cameras monitor congruent seasonal development of birches with phenological field observations

Science.gov (United States)

Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Kubin, Eero; Linkosalmi, Maiju; Melih Tanis, Cemal; Nadir Arslan, Ali

2017-04-01

Ecosystems' potential to provide services, e.g. to sequester carbon is largely driven by the phenological cycle of vegetation. Timing of phenological events is required for understanding and predicting the influence of climate change on ecosystems and to support various analyses of ecosystem functioning. We established a network of cameras for automated monitoring of phenological activity of vegetation in boreal ecosystems of Finland. Cameras were mounted on 14 sites, each site having 1-3 cameras. In this study, we used cameras at 11 of these sites to investigate how well networked cameras detect phenological development of birches (Betula spp.) along the latitudinal gradient. Birches are interesting focal species for the analyses as they are common throughout Finland. In our cameras they often appear in smaller quantities within dominant species in the images. Here, we tested whether small scattered birch image elements allow reliable extraction of color indices and changes therein. We compared automatically derived phenological dates from these birch image elements to visually determined dates from the same image time series, and to independent observations recorded in the phenological monitoring network from the same region. Automatically extracted season start dates based on the change of green color fraction in the spring corresponded well with the visually interpreted start of season, and field observed budburst dates. During the declining season, red color fraction turned out to be superior over green color based indices in predicting leaf yellowing and fall. The latitudinal gradients derived using automated phenological date extraction corresponded well with gradients based on phenological field observations from the same region. We conclude that already small and scattered birch image elements allow reliable extraction of key phenological dates for birch species. Devising cameras for species specific analyses of phenological timing will be useful for

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

Science.gov (United States)

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom; Aubrecht, Donald M.; Chen, Min; Gray, Josh M.; Johnston, Miriam R.; Keenan, Trevor F.; Klosterman, Stephen T.; Kosmala, Margaret; Melaas, Eli K.; Friedl, Mark A.; Frolking, Steve

2018-03-01

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.

Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data

Directory of Open Access Journals (Sweden)

Stuart E. Marsh

2010-01-01

Full Text Available Climate change and variability are expected to impact the synchronicity and interactions between the Sonoran Desert and the forested sky islands which represent steep biological and environmental gradients. The main objectives were to examine how well satellite greenness time series data and derived phenological metrics (e.g., season start, peak greenness can characterize specific vegetation communities across an elevation gradient, and to examine the interactions between climate and phenological metrics for each vegetation community. We found that representative vegetation types (11, varying between desert scrub, mesquite, grassland, mixed oak, juniper and pine, often had unique seasonal and interannual phenological trajectories and spatial patterns. Satellite derived land surface phenometrics (11 for each of the vegetation communities along the cline showed numerous distinct significant relationships in response to temperature (4 and precipitation (7 metrics. Satellite-derived sky island vegetation phenology can help assess and monitor vegetation dynamics and provide unique indicators of climate variability and patterns of change.

Forests and Phenology: Designing the Early Warning System to Understand Forest Change

Science.gov (United States)

Pierce, T.; Phillips, M. B.; Hargrove, W. W.; Dobson, G.; Hicks, J.; Hutchins, M.; Lichtenstein, K.

2010-12-01

Vegetative phenology is the study of plant development and changes with the seasons, such as the greening-up and browning-down of forests, and how these events are influenced by variations in climate. A National Phenology Data Set, based on Moderate Resolution Imaging Spectroradiometer satellite images covering 2002 through 2009, is now available from work by NASA, the US Forest Service, and Oak Ridge National Laboratory. This new data set provides an easily interpretable product useful for detecting changes to the landscape due to long-term factors such as climate change, as well as finding areas affected by short-term forest threats such as insects or disease. The Early Warning System (EWS) is a toolset being developed by the US Forest Service and the University of North Carolina-Asheville to support distribution and use of the National Phenology Data Set. The Early Warning System will help research scientists, US Forest Service personnel, forest and natural resources managers, decision makers, and the public in the use of phenology data to better understand unexpected change within our nation’s forests. These changes could have multiple natural sources such as insects, disease, or storm damage, or may be due to human-induced events, like thinning, harvest, forest conversion to agriculture, or residential and commercial use. The primary goal of the Early Warning System is to provide a seamless integration between monitoring, detection, early warning and prediction of these forest disturbances as observed through phenological data. The system consists of PC and web-based components that are structured to support four user stages of increasing knowledge and data sophistication. Building Literacy: This stage of the Early Warning System educates potential users about the system, why the system should be used, and the fundamentals about the data the system uses. The channels for this education include a website, interactive tutorials, pamphlets, and other technology

Satellite Based Cropland Carbon Monitoring System

Science.gov (United States)

Bandaru, V.; Jones, C. D.; Sedano, F.; Sahajpal, R.; Jin, H.; Skakun, S.; Pnvr, K.; Kommareddy, A.; Reddy, A.; Hurtt, G. C.; Izaurralde, R. C.

2017-12-01

Agricultural croplands act as both sources and sinks of atmospheric carbon dioxide (CO2); absorbing CO2 through photosynthesis, releasing CO2 through autotrophic and heterotrophic respiration, and sequestering CO2 in vegetation and soils. Part of the carbon captured in vegetation can be transported and utilized elsewhere through the activities of food, fiber, and energy production. As well, a portion of carbon in soils can be exported somewhere else by wind, water, and tillage erosion. Thus, it is important to quantify how land use and land management practices affect the net carbon balance of croplands. To monitor the impacts of various agricultural activities on carbon balance and to develop management strategies to make croplands to behave as net carbon sinks, it is of paramount importance to develop consistent and high resolution cropland carbon flux estimates. Croplands are typically characterized by fine scale heterogeneity; therefore, for accurate carbon flux estimates, it is necessary to account for the contribution of each crop type and their spatial distribution. As part of NASA CMS funded project, a satellite based Cropland Carbon Monitoring System (CCMS) was developed to estimate spatially resolved crop specific carbon fluxes over large regions. This modeling framework uses remote sensing version of Environmental Policy Integrated Climate Model and satellite derived crop parameters (e.g. leaf area index (LAI)) to determine vertical and lateral carbon fluxes. The crop type LAI product was developed based on the inversion of PRO-SAIL radiative transfer model and downscaled MODIS reflectance. The crop emergence and harvesting dates were estimated based on MODIS NDVI and crop growing degree days. To evaluate the performance of CCMS framework, it was implemented over croplands of Nebraska, and estimated carbon fluxes for major crops (i.e. corn, soybean, winter wheat, grain sorghum, alfalfa) grown in 2015. Key findings of the CCMS framework will be presented

Phenological change detection while accounting for abrupt and gradual trends in satellite image time series

NARCIS (Netherlands)

Verbesselt, J.; Hyndman, R.; Zeileis, A.; Culvenor, D.

2010-01-01

A challenge in phenology studies is understanding what constitutes phenological change amidst background variation. The majority of phenological studies have focused on extracting critical points in the seasonal growth cycle, without exploiting the full temporal detail. The high degree of

Assessing satellite-based start-of-season trends in the US High Plains

International Nuclear Information System (INIS)

Lin, X; Sassenrath, G F; Hubbard, K G; Mahmood, R

2014-01-01

To adequately assess the effects of global warming it is necessary to address trends and impacts at the local level. This study examines phenological changes in the start-of-season (SOS) derived from satellite observations from 1982–2008 in the US High Plains region. The surface climate-based SOS was also evaluated. The averaged profiles of SOS from 37° to 49°N latitude by satellite- and climate-based methods were in reasonable agreement, especially for areas where croplands were masked out and an additional frost date threshold was adopted. The statistically significant trends of satellite-based SOS show a later spring arrival ranging from 0.1 to 4.9 days decade −1 over nine Level III ecoregions. We found the croplands generally exhibited larger trends (later arrival) than the non-croplands. The area-averaged satellite-based SOS for non-croplands (i.e. mostly grasslands) showed no significant trends. We examined the trends of temperatures, precipitation, and standardized precipitation index (SPI), as well as the strength of correlation between the satellite-based SOS and these climatic drivers. Our results indicate that satellite-based SOS trends are spatially and primarily related to annual maximum normalized difference vegetation index (NDVI, mostly in summertime) and/or annual minimum NDVI (mostly in wintertime) and these trends showed the best correlation with six-month SPI over the period 1982–2008 in the US High Plains region. (letter)

Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology.

Science.gov (United States)

Liu, Tianjiao; Liu, Xiangnan; Liu, Meiling; Wu, Ling

2018-03-14

Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors, but few studies have considered phenology, which can be sensitive to heavy metal stress. In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology. A phenological indicator relatively sensitive to heavy metal stress was chosen from the obtained phenological periods and phenological parameters. The Dry Weight of Roots (WRT), which directly affected by heavy metal stress, was simulated by the World Food Study (WOFOST) model; then, a feature space based on the phenological indicator and WRT was established for monitoring heavy metal stress. The results indicated that the feature space can distinguish the heavy metal stress levels in rice, with accuracy greater than 95% for distinguishing the severe stress level. This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice.

Developing A Model for Lake Ice Phenology Using Satellite Remote Sensing Observations

Science.gov (United States)

Skoglund, S. K.; Weathers, K. C.; Norouzi, H.; Prakash, S.; Ewing, H. A.

2017-12-01

Many northern temperate freshwater lakes are freezing over later and thawing earlier. This shift in timing, and the resulting shorter duration of seasonal ice cover, is expected to impact ecological processes, negatively affecting aquatic species and the quality of water we drink. Long-term, direct observations have been used to analyze changes in ice phenology, but those data are sparse relative to the number of lakes affected. Here we develop a model to utilize remote sensing data in approximating the dates of ice-on and ice-off for many years over a variety of lakes. Day and night surface temperatures from MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra (MYD11A1 and MOD11A1 data products) for 2002-2017 were utilized in combination with observed ice-on and ice-off dates of Lake Auburn, Maine, to determine the ability of MODIS data to match ground-based observations. A moving average served to interpolate MODIS temperature data to fill data gaps from cloudy days. The nighttime data were used for ice-off, and the daytime measurements were used for ice-on predictions to avoid fluctuations between day and night ice/water status. The 0˚C intercepts of those data were used to mark approximate days of ice-on or ice-off. This revealed that approximations for ice-off dates were satisfactory (average ±8.2 days) for Lake Auburn as well as for Lake Sunapee, New Hampshire (average ±8.1 days), while approximations for Lake Auburn ice-on were less accurate and showed consistently earlier-than-observed ice-on dates (average -33.8 days). The comparison of observed and remotely sensed Lake Auburn ice cover duration showed relative agreement with a correlation coefficient of 0.46. Other remote sensing observations, such as the new GOES-R satellite, and further exploration of the ice formation process can improve ice-on approximation methods. The model shows promise for estimating ice-on, ice-off, and ice cover duration for northern temperate lakes.

Seasonal and Inter-annual Phenological Varibility is Greatest in Low-Arctic and Wet Sites Across the North Slope of Alaska as Observed from Multiple Remote Sensing Platforms

Science.gov (United States)

Vargas, S. A., Jr.; Andresen, C. G.; May, J. L.; Oberbauer, S. F.; Hollister, R. D.; Tweedie, C. E.

2017-12-01

The Arctic is experiencing among the most dramatic impacts from climate variability on the planet. Arctic plant phenology has been identified as an ideal indicator of climate change impacts and provides great insight into seasonal and inter-annual vegetative trends and their responses to such changes. Traditionally, phenology has been quantified using satellite-based systems and plot-level observations but each approach presents limitations especially in high latitude regions. Mid-scale systems (e.g. automated sensor platforms and trams) have shown to provide alternative, and in most cases, cheaper solutions with comparable results to those acquired traditionally. This study contributes to the US Arctic Observing Network (AON) and assesses the effectiveness of using digital images acquired from pheno-cams, a kite aerial photography (KAP) system, and plot-level images (PLI) in their capacity to assess phenological variability (e.g. snow melt, greening and end-of-season) for dominant vegetation communities present at two sites in both Utqiagvik and Atqasuk, Alaska, namely the Mobile Instrumented Sensor Platform (MISP) and the Circum-arctic Active Layer Monitoring (CALM) grids. RGB indices (e.g. GEI and %G) acquired from these methods were compared to the normalized difference vegetation index (NDVI) calculated from multispectral ground-based reflectance measurements, which has been identified and used as a proxy of primary productivity across multiple ecosystems including the Arctic. The 5 years of growing season data collected generally resulted with stronger Pearson's correlations between indices located in plots containing higher soil moisture versus those that were drier. Future studies will extend platform inter-comparison to the satellite level by scaling trends to MODIS land surface products. Trends documented thus far, however, suggest that the long-term changes in satellite NDVI for these study areas, could be a direct response from wet tundra landscapes.

Detecting weather radar clutter using satellite-based nowcasting products

DEFF Research Database (Denmark)

Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

2006-01-01

This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

Detecting inter-annual variability in the phenological characteristics of southern Africa’s vegetation using satellite imagery

CSIR Research Space (South Africa)

Wessels, Konrad J

2011-01-01

Full Text Available provides consistent measurements of vegetation greenness which captures phenological cycles and vegetation function. Understanding the inter-annual variability in phenology is imperative, as phenological changes will be one of the first signs of the impact...

Assessing climate change effects on long-term forest development: adjusting growth, phenology, and seed production in a gap model

NARCIS (Netherlands)

Meer, van der P.J.; Jorritsma, I.T.M.; Kramer, K.

2002-01-01

The sensitivity of forest development to climate change is assessed using a gap model. Process descriptions in the gap model of growth, phenology, and seed production were adjusted for climate change effects using a detailed process-based growth modeland a regression analysis. Simulation runs over

Phenology of Succession: Tracking the Recovery of Dryland Forests after Wildfire Events

Science.gov (United States)

Walker, J.; Brown, J. F.; Sankey, J. B.; Wallace, C.; Weltzin, J. F.

2016-12-01

The frequency, size, and intensity of forest wildfires in the U.S. Southwest have increased over the past 30 years. In the coming decades, burn effects and altered climatic conditions may increasingly divert vegetation recovery trajectories from pre-disturbance forested ecosystems toward grassland or shrub woodlands. Dryland herbaceous and woody vegetation species exhibit different phenological responses to precipitation, resulting in temporal and spatial shifts in landscape phenology patterns as the proportions of plant functional groups change over time. We have developed time series of Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) greenness measures derived from satellite imagery from 1984 - 2015 to record the phenological signatures that characterize recovery trajectories towards predominantly grassland, shrubland, or forest land cover types. We leveraged the data and computational resources available through the Google Earth Engine cloud-based platform to analyze time series of Landsat Thematic Mapper and Enhanced Thematic Mapper Plus imagery collected over maturing (40 years or more post-fire) dryland forests in Arizona and New Mexico, USA. These time series provided the basis for long-term comparisons of phenology behavior in different successional trajectories and enabled the assessment of climatic influence on the eventual outcomes.

Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

Science.gov (United States)

Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

2016-12-01

Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa

CSIR Research Space (South Africa)

Wessels, Konrad J

2011-02-01

Full Text Available the distribution of the recently redefined biomes be predicted based on remotely sensed, phenology and productivity metrics? Ten-day, 1 km, NDVI AVHRR were analysed for the period 1985 to 2000. Phenological metrics such as start, end and length of the growing...

Intra- and interspecific variation in tropical tree and liana phenology derived from Unmanned Aerial Vehicle images

Science.gov (United States)

Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.

2017-12-01

Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However

Merging Satellite Precipitation Products for Improved Streamflow Simulations

Science.gov (United States)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

Satellite-Based Precipitation Datasets

Science.gov (United States)

Munchak, S. J.; Huffman, G. J.

2017-12-01

Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

Recent changes in phenology over the northern high latitudes detected from multi-satellite data

International Nuclear Information System (INIS)

Zeng Heqing; Jia Gensuo; Epstein, Howard

2011-01-01

Phenology of vegetation is a sensitive and valuable indicator of the dynamic responses of terrestrial ecosystems to climate change. Therefore, to better understand and predict ecosystems dynamics, it is important to reduce uncertainties in detecting phenological changes. Here, changes in phenology over the past several decades across the northern high-latitude region (≥60°N) were examined by calibrating and analyzing time series of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR). Over the past decade (2000–10), an expanded length of the growing season (LOS) was detected by MODIS, largely due to an earlier start of the growing season (SOS) by 4.7 days per decade and a delayed end of the growing season (EOS) by 1.6 days per decade over the northern high latitudes. There were significant differences between North America and Eurasia in phenology from 2000 to 2010 based on MODIS data (SOS: df = 21, F = 49.02, p < 0.0001; EOS: df = 21, F = 49.25, p < 0.0001; LOS: df = 21, F = 79.40, p < 0.0001). In northern America, SOS advanced by 11.5 days per decade, and EOS was delayed by 2.2 days per decade. In Eurasia, SOS advanced by 2.7 days per decade, and EOS was delayed by 3.5 days per decade. SOS has likely advanced due to the warming Arctic during April and May. Our results suggest that in recent decades the longer vegetation growing seasons can be attributed to more advanced SOS rather than delayed EOS. AVHRR detected longer LOS over the past three decades, largely related to delayed EOS rather than advanced SOS. These two datasets are significantly different in key phenological parameters (SOS: df = 17, F = 14.63, p = 0.0015; EOS: df = 17, F = 38.69, p < 0.0001; LOS: df = 17, F = 16.47, p = 0.0009) from 2000 to 2008 over the northern high latitudes. Thus, further inter-calibration between the sensors is needed to resolve the inconsistency and to better understand long-term trends of vegetation growth

Systematical estimation of GPM-based global satellite mapping of precipitation products over China

Science.gov (United States)

Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

2018-03-01

As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

Satellite derived forest phenology and its relation with nephropathia epidemica in Belgium.

Science.gov (United States)

Barrios, José Miguel; Verstraeten, Willem W; Maes, Piet; Clement, Jan; Aerts, Jean-Marie; Haredasht, Sara Amirpour; Wambacq, Julie; Lagrou, Katrien; Ducoffre, Geneviève; Van Ranst, Marc; Berckmans, Daniel; Coppin, Pol

2010-06-01

The connection between nephropathia epidemica (NE) and vegetation dynamics has been emphasized in recent studies. Changing climate has been suggested as a triggering factor of recently observed epidemiologic peaks in reported NE cases. We have investigated whether there is a connection between the NE occurrence pattern in Belgium and specific trends in remotely sensed phenology parameters of broad-leaved forests. The analysis of time series of the MODIS Enhanced Vegetation Index revealed that changes in forest phenology, considered in literature as an effect of climate change, may affect the mechanics of NE transmission.

Building a Shared Understanding of Phenology

Science.gov (United States)

Rosemartin, A.; Posthumus, E.; Gerst, K.

2017-12-01

The USA National Phenology Network (USA-NPN) seeks to advance the science of phenology and support the use of phenology information in decision-making. We envision that natural resource, human health, recreation and land-use decisions, in the context of a variable and changing climate, will be supported by USA-NPN products and tools. To achieve this vision we developed a logic model, breaking down the necessary inputs (e.g., IT infrastructure), participants, activities and the short- to long-term goals (e.g., use of phenological information in adaptive management). Here we compare the ongoing activities and outcomes of three recent collaborations to our logic model, in order to improve the model and inform future collaborations. At Midway Atoll National Wildlife Refuge, resource managers use the USA-NPN's phenology monitoring program to pinpoint the minimum number of days between initial growth and seed set in an invasive species. The data output and calendar visualizations that USA-NPN provides are sufficient to identify the appropriate treatment window. In contrast to a direct relationship with a natural resource manager using USA-NPN tools and products, some collaborations require substantive iterative work between partners. USA-NPN and National Park Service staff, along with academic researchers, assessed advancement in the timing of spring, and delivered the work in a format appropriate for park managers. Lastly, collaborations with indigenous communities reveal a requirement to reconsider the relationship between Western science and indigenous knowledge systems, as well as address ethical considerations and develop trust, before Western science can be meaningfully incorporated into decision-making. While the USA-NPN is a boundary organization, working in between federal agencies, states and universities, and is mandated to support decision-making, we still face challenges in generating usable science. We share lessons learned based on our experience with

[Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

Science.gov (United States)

Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

2018-02-01

Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

Spatio-Temporal Changes of Net Primary Productivity and its Response to Phenology in Northeast China during 2000-2015

Science.gov (United States)

Qiu, Y.; Zhang, L.; Fan, D.

2018-04-01

The relationship between net primary productivity (NPP) and phenological changes is of great significance to the study of regional ecosystem processes. In this study, firstly, NPP was estimated with the remote sensing model based on the SPOT-VGT NDVI dataset (2000-2015), meteorological data and the vegetation map in Northeast China. Then, using NDVI time series data which was reconstructed by polynomial fitting, phenology was extracted with the dynamic threshold method. Finally, the relationship between NPP and phenology was analyzed. The results showed that NPP mainly increased in the cropland, grassland, forestland and shrubland; however, vegetation NPP decreased in the ecotone among cropland, grassland and forestland. Correlation analysis suggested that the relationships between NPP and phenological metrics (i.e., the start of the growing season (SOS), the end of the growing season (EOS), the length of the growing season (LOS)) were different due to geographical location. On the whole, there was a positive correlation between NPP and the LOS in the forestland, and negative in the cropland and grassland, indicating that extended LOS can promote the accumulation of forestland NPP. By analyzing the monthly NDVI data during the vigorous growth period, the increase of NPP in the grassland and cropland was mainly due to the better growth from June to August, and shortened LOS did not lead to reduce the NPP. Generally, the response of NPP to phenology in Northeast China were more complex, showing obvious difference of vegetation types and spatial variability, we need to consider topography, community structure and other factors in the further studies.

e-phenology: monitoring leaf phenology and tracking climate changes in the tropics

Science.gov (United States)

Morellato, Patrícia; Alberton, Bruna; Almeida, Jurandy; Alex, Jefersson; Mariano, Greice; Torres, Ricardo

2014-05-01

The e-phenology is a multidisciplinary project combining research in Computer Science and Phenology. Its goal is to attack theoretical and practical problems involving the use of new technologies for remote phenological observation aiming to detect local environmental changes. It is geared towards three objectives: (a) the use of new technologies of environmental monitoring based on remote phenology monitoring systems; (b) creation of a protocol for a Brazilian long term phenology monitoring program and for the integration across disciplines, advancing our knowledge of seasonal responses within tropics to climate change; and (c) provide models, methods and algorithms to support management, integration and analysis of data of remote phenology systems. The research team is composed by computer scientists and biology researchers in Phenology. Our first results include: Phenology towers - We set up the first phenology tower in our core cerrado-savanna 1 study site at Itirapina, São Paulo, Brazil. The tower received a complete climatic station and a digital camera. The digital camera is set up to take daily sequence of images (five images per hour, from 6:00 to 18:00 h). We set up similar phenology towers with climatic station and cameras in five more sites: cerrado-savanna 2 (Pé de Gigante, SP), cerrado grassland 3 (Itirapina, SP), rupestrian fields 4 ( Serra do Cipo, MG), seasonal forest 5 (Angatuba, SP) and Atlantic raiforest 6 (Santa Virginia, SP). Phenology database - We finished modeling and validation of a phenology database that stores ground phenology and near-remote phenology, and we are carrying out the implementation with data ingestion. Remote phenology and image processing - We performed the first analyses of the cerrado sites 1 to 4 phenology derived from digital images. Analysis were conducted by extracting color information (RGB Red, Green and Blue color channels) from selected parts of the image named regions of interest (ROI). using the green color

A Land Product Characterization System for Comparative Analysis of Satellite Data and Products

Directory of Open Access Journals (Sweden)

Kevin Gallo

2017-12-01

Full Text Available A Land Product Characterization System (LPCS has been developed to provide land data and products to the community of individuals interested in validating space-based land products by comparing them with similar products available from other sensors or surface-based observations. The LPCS facilitates the application of global multi-satellite and in situ data for characterization and validation of higher-level, satellite-derived, land surface products (e.g., surface reflectance, normalized difference vegetation index, and land surface temperature. The LPCS includes data search, inventory, access, and analysis functions that will permit data to be easily identified, retrieved, co-registered, and compared statistically through a single interface. The system currently includes data and products available from Landsat 4 through 8, Moderate Resolution Imaging Spectroradiometer (MODIS Terra and Aqua, Suomi National Polar-Orbiting Partnership (S-NPP/Joint Polar Satellite System (JPSS Visible Infrared Imaging Radiometer Suite (VIIRS, and simulated data for the Geostationary Operational Environmental Satellite (GOES-16 Advanced Baseline Imager (ABI. In addition to the future inclusion of in situ data, higher-level land products from the European Space Agency (ESA Sentinel-2 and -3 series of satellites, and other high and medium resolution spatial sensors, will be included as available. When fully implemented, any of the sensor data or products included in the LPCS would be available for comparative analysis.

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

Science.gov (United States)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Prasad, A.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P. K.; Budge, A. M.;

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

Science.gov (United States)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A. R.; Nickovic, S.; Prasad, A. K.; Pejanovic, G.; Vukovic, A.; Van De Water, P. K.; Budge, A.; Hudspeth, W. B.; Krapfl, H.; Toth, B.; Zelicoff, A.; Myers, O.; Bunderson, L.; Ponce-Campos, G.; Menache, M.; Crimmins, T. M.; Vujadinovic, M.

2012-12-01

Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and concentrations of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen emission is based on MODIS-derived phenology of Juniperus spp. communities. Ground-based observational records of pollen release timing and quantities will be used as model verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Satellite Derived Forest Phenology and Its Relation with Nephropathia Epidemica in Belgium

Directory of Open Access Journals (Sweden)

José Miguel Barrios

2010-06-01

Full Text Available The connection between nephropathia epidemica (NE and vegetation dynamics has been emphasized in recent studies. Changing climate has been suggested as a triggering factor of recently observed epidemiologic peaks in reported NE cases. We have investigated whether there is a connection between the NE occurrence pattern in Belgium and specific trends in remotely sensed phenology parameters of broad-leaved forests. The analysis of time series of the MODIS Enhanced Vegetation Index revealed that changes in forest phenology, considered in literature as an effect of climate change, may affect the mechanics of NE transmission.

Trends in Spring Phenology of Western European Deciduous Forests

Directory of Open Access Journals (Sweden)

Eliakim Hamunyela

2013-11-01

Full Text Available Plant phenology is changing because of recent global warming, and this change may precipitate changes in animal distribution (e.g., pests, alter the synchronization between species, and have feedback effects on the climate system through the alteration of biogeochemical and physical processes of vegetated land surface. Here, ground observations (leaf unfolding/first leaf separation of six deciduous tree species and satellite-derived start-of-growing season (SOS are used to assess how the timing of leafing/SOS in Western European deciduous forest responded to climate variability between 2001 and 2011 and evaluate the reliability of satellite SOS estimates in tracking the response of forest leafing to climate variability in this area. Satellite SOS estimates are derived from the Normalized Difference Vegetation Index (NDVI time series of the Moderate Resolution Imaging Spectroradiometer (MODIS. Temporal trends in the SOS are quantified using linear regression, expressing SOS as a function of time. We demonstrated that the growing season was starting earlier between 2001 and 2011 for the majority of temperate deciduous forests in Western Europe, possibly influenced by regional spring warming effects experienced during the same period. A significant shift of up to 3 weeks to early leafing was found in both ground observations and satellite SOS estimates. We also show that the magnitude and trajectory of shifts in satellite SOS estimates are well comparable to that of in situ observations, hence highlighting the importance of satellite imagery in monitoring leaf phenology under a changing climate.

Towards an improved Land Surface Phenology mapping using a new MODIS product: A case study of Bavarian Forest National Park

Science.gov (United States)

Misra, Gourav; Buras, Allan; Asam, Sarah; Menzel, Annette

2017-04-01

Past work in remote sensing of land surface phenology have mapped vegetation cycles at multiple scales. Much has been discussed and debated about the uncertainties associated with the selection of data, data processing and the eventual conclusions drawn. Several studies do however provide evidence of strong links between different land surface phenology (LSP) metrics with specific ground phenology (GP) (Fisher and Mustard, 2007; Misra et al., 2016). Most importantly the use of high temporal and spatial resolution remote sensing data and ground truth information is critical for such studies. In this study, we use a higher temporal resolution 4 day MODIS NDVI product developed by EURAC (Asam et al., in prep) for the Bavarian Forest National Park during 2002-2015 period and extract various phenological metrics covering different phenophases of vegetation (start of season / sos and end of season / eos). We found the LSP-sos to be more strongly linked to the elevation of the area than LSP-eos which has been cited to be harder to detect (Stöckli et al., 2008). The LSP metrics were also correlated to GP information at 4 different stations covering elevations ranging from approx. 500 to 1500 metres. Results show that among the five dominant species in the area i.e. European ash, Norway spruce, European beech, Norway maple and orchard grass, only particular GP observations for some species show stronger correlations with LSP than others. Spatial variations in the LSP-GP correlations were also observed, with certain areas of the National Park showing positive correlations and others negative. An analysis of temporal trends of LSP also indicates the possibility to detect those areas in the National Park that were affected by extreme events. Further investigations are planned to explain the heterogeneity in the derived LSP metrics using high resolution ground truth data and multivariate statistical analyses. Acknowledgement: This research received funding from the Bavarian

a R-Shiny Based Phenology Analysis System and Case Study Using Digital Camera Dataset

Science.gov (United States)

Zhou, Y. K.

2018-05-01

Accurate extracting of the vegetation phenology information play an important role in exploring the effects of climate changes on vegetation. Repeated photos from digital camera is a useful and huge data source in phonological analysis. Data processing and mining on phenological data is still a big challenge. There is no single tool or a universal solution for big data processing and visualization in the field of phenology extraction. In this paper, we proposed a R-shiny based web application for vegetation phenological parameters extraction and analysis. Its main functions include phenological site distribution visualization, ROI (Region of Interest) selection, vegetation index calculation and visualization, data filtering, growth trajectory fitting, phenology parameters extraction, etc. the long-term observation photography data from Freemanwood site in 2013 is processed by this system as an example. The results show that: (1) this system is capable of analyzing large data using a distributed framework; (2) The combination of multiple parameter extraction and growth curve fitting methods could effectively extract the key phenology parameters. Moreover, there are discrepancies between different combination methods in unique study areas. Vegetation with single-growth peak is suitable for using the double logistic module to fit the growth trajectory, while vegetation with multi-growth peaks should better use spline method.

Can phenological models predict tree phenology accurately under climate change conditions?

Science.gov (United States)

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2014-05-01

The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

Phylogenetic Conservatism in Plant Phenology

Science.gov (United States)

Davies, T. Jonathan; Wolkovich, Elizabeth M.; Kraft, Nathan J. B.; Salamin, Nicolas; Allen, Jenica M.; Ault, Toby R.; Betancourt, Julio L.; Bolmgren, Kjell; Cleland, Elsa E.; Cook, Benjamin I.;

Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

Science.gov (United States)

Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

2017-12-01

In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery: A new, publicly-available dataset

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Richardson, A. D.

2015-12-01

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is highly sensitive to climate change and variability, and is thus a key aspect of global change ecology. The goal of the PhenoCam network is to serve as a long-term, continental-scale, phenological observatory. The network uses repeat digital photography—images captured using conventional, visible-wavelength, automated digital cameras—to characterize vegetation phenology in diverse ecosystems across North America and around the world. At present, imagery from over 200 research sites, spanning a wide range of ecoregions, climate zones, and plant functional types, is currently being archived and processed in near-real-time through the PhenoCam project web page (http://phenocam.sr.unh.edu/). Data derived from PhenoCam imagery have been previously used to evaluate satellite phenology products, to constrain and test new phenology models, to understand relationships between canopy phenology and ecosystem processes, and to study the seasonal changes in leaf-level physiology that are associated with changes in leaf color. I will describe a new, publicly-available phenological dataset, derived from over 600 site-years of PhenoCam imagery. For each archived image (ca. 5 million), we extracted RGB (red, green, blue) color channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 minute) imagery, we derived time series characterizing vegetation color, including "canopy greenness", processed to 1- and 3-day intervals. For ecosystems with a single annual cycle of vegetation activity, we derived estimates, with uncertainties, for the start, middle, and end of spring and autumn phenological transitions. Given the lack of multi-year, standardized, and geographically distributed phenological data for North America, we

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

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Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-08-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia's cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

SPATIO-TEMPORAL CHANGES OF NET PRIMARY PRODUCTIVITY AND ITS RESPONSE TO PHENOLOGY IN NORTHEAST CHINA DURING 2000–2015

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Y. Qiu

2018-04-01

Full Text Available The relationship between net primary productivity (NPP and phenological changes is of great significance to the study of regional ecosystem processes. In this study, firstly, NPP was estimated with the remote sensing model based on the SPOT-VGT NDVI dataset (2000–2015, meteorological data and the vegetation map in Northeast China. Then, using NDVI time series data which was reconstructed by polynomial fitting, phenology was extracted with the dynamic threshold method. Finally, the relationship between NPP and phenology was analyzed. The results showed that NPP mainly increased in the cropland, grassland, forestland and shrubland; however, vegetation NPP decreased in the ecotone among cropland, grassland and forestland. Correlation analysis suggested that the relationships between NPP and phenological metrics (i.e., the start of the growing season (SOS, the end of the growing season (EOS, the length of the growing season (LOS were different due to geographical location. On the whole, there was a positive correlation between NPP and the LOS in the forestland, and negative in the cropland and grassland, indicating that extended LOS can promote the accumulation of forestland NPP. By analyzing the monthly NDVI data during the vigorous growth period, the increase of NPP in the grassland and cropland was mainly due to the better growth from June to August, and shortened LOS did not lead to reduce the NPP. Generally, the response of NPP to phenology in Northeast China were more complex, showing obvious difference of vegetation types and spatial variability, we need to consider topography, community structure and other factors in the further studies.

USA National Phenology Network observational data documentation

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Rosemartin, Alyssa H.; Denny, Ellen G.; Gerst, Katharine L.; Marsh, R. Lee; Posthumus, Erin E.; Crimmins, Theresa M.; Weltzin, Jake F.

2018-04-25

The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal (http://dx.doi.org/10.5066/F78S4N1V) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.

Root phenology at Harvard Forest and beyond

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Abramoff, R. Z.; Finzi, A.

2013-12-01

Roots are hidden from view and heterogeneously distributed making them difficult to study in situ. As a result, the causes and timing of root production are not well understood. Researchers have long assumed that above and belowground phenology is synchronous; for example, most parameterizations of belowground carbon allocation in terrestrial biosphere models are based on allometry and represent a fixed fraction of net C uptake. However, using results from metaanalysis as well as empirical data from oak and hemlock stands at Harvard Forest, we show that synchronous root and shoot growth is the exception rather than the rule. We collected root and shoot phenology measurements from studies across four biomes (boreal, temperate, Mediterranean, and subtropical). General patterns of root phenology varied widely with 1-5 production peaks in a growing season. Surprisingly, in 9 out of the 15 studies, the first root production peak was not the largest peak. In the majority of cases maximum shoot production occurred before root production (Offset>0 in 32 out of 47 plant sample means). The number of days offset between maximum root and shoot growth was negatively correlated with median annual temperature and therefore differs significantly across biomes (ANOVA, F3,43=9.47, pGrowth form (woody or herbaceous) also influenced the relative timing of root and shoot growth. Woody plants had a larger range of days between root and shoot growth peaks as well as a greater number of growth peaks. To explore the range of phenological relationships within woody plants in the temperate biome, we focused on above and belowground phenology in two common northeastern tree species, Quercus rubra and Tsuga canadensis. Greenness index, rate of stem growth, root production and nonstructural carbohydrate content were measured beginning in April 2012 through August 2013 at the Harvard Forest in Petersham, MA, USA. Greenness and stem growth were highest in late May and early June with one clear

Evaluation of NWP-based Satellite Precipitation Error Correction with Near-Real-Time Model Products and Flood-inducing Storms

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Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.

2017-12-01

Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.

Forecasting wheat and barley crop production in arid and semi-arid regions using remotely sensed primary productivity and crop phenology: A case study in Iraq.

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Qader, Sarchil Hama; Dash, Jadunandan; Atkinson, Peter M

2018-02-01

Crop production and yield estimation using remotely sensed data have been studied widely, but such information is generally scarce in arid and semi-arid regions. In these regions, inter-annual variation in climatic factors (such as rainfall) combined with anthropogenic factors (such as civil war) pose major risks to food security. Thus, an operational crop production estimation and forecasting system is required to help decision-makers to make early estimates of potential food availability. Data from NASA's MODIS with official crop statistics were combined to develop an empirical regression-based model to forecast winter wheat and barley production in Iraq. The study explores remotely sensed indices representing crop productivity over the crop growing season to find the optimal correlation with crop production. The potential of three different remotely sensed indices, and information related to the phenology of crops, for forecasting crop production at the governorate level was tested and their results were validated using the leave-one-year-out approach. Despite testing several methodological approaches, and extensive spatio-temporal analysis, this paper depicts the difficulty in estimating crop yield on an annual base using current satellite low-resolution data. However, more precise estimates of crop production were possible. The result of the current research implies that the date of the maximum vegetation index (VI) offered the most accurate forecast of crop production with an average R 2 =0.70 compared to the date of MODIS EVI (Avg R 2 =0.68) and a NPP (Avg R 2 =0.66). When winter wheat and barley production were forecasted using NDVI, EVI and NPP and compared to official statistics, the relative error ranged from -20 to 20%, -45 to 28% and -48 to 22%, respectively. The research indicated that remotely sensed indices could characterize and forecast crop production more accurately than simple cropping area, which was treated as a null model against which to

ANALYSIS OF YEAR 2002 SEASONAL FOREST DYNAMICS USING TIME SERIES IN SITU LAI MEASUREMENTS AND MODIS LAI SATELLITE PRODUCTS

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Multitemporal satellite images are the standard basis for regional-scale land-cover (LC) change detection. However, embedded in the data are the confounding effects of vegetation dynamics (phenology). As photosynthetic vegetation progresses through its annual cycle, the spectral ...

An observation-based progression modeling approach to spring and autumn deciduous tree phenology

Science.gov (United States)

Yu, Rong; Schwartz, Mark D.; Donnelly, Alison; Liang, Liang

2016-03-01

It is important to accurately determine the response of spring and autumn phenology to climate change in forest ecosystems, as phenological variations affect carbon balance, forest productivity, and biodiversity. We observed phenology intensively throughout spring and autumn in a temperate deciduous woodlot at Milwaukee, WI, USA, during 2007-2012. Twenty-four phenophase levels in spring and eight in autumn were recorded for 106 trees, including white ash, basswood, white oak, boxelder, red oak, and hophornbeam. Our phenological progression models revealed that accumulated degree-days and day length explained 87.9-93.4 % of the variation in spring canopy development and 75.8-89.1 % of the variation in autumn senescence. In addition, the timing of community-level spring and autumn phenophases and the length of the growing season from 1871 to 2012 were reconstructed with the models developed. All simulated spring phenophases significantly advanced at a rate from 0.24 to 0.48 days/decade ( p ≤ 0.001) during the 1871-2012 period and from 1.58 to 2.00 days/decade ( p coloration) and 0.50 (full-leaf coloration) days/decade ( p coloration and leaf fall, and suggested accelerating simulated ecosystem responses to climate warming over the last four decades in comparison to the past 142 years.

Deriving phenological metrics from NDVI through an open source tool developed in QGIS

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Duarte, Lia; Teodoro, A. C.; Gonçalves, Hernãni

2014-10-01

Vegetation indices have been commonly used over the past 30 years for studying vegetation characteristics using images collected by remote sensing satellites. One of the most commonly used is the Normalized Difference Vegetation Index (NDVI). The various stages that green vegetation undergoes during a complete growing season can be summarized through time-series analysis of NDVI data. The analysis of such time-series allow for extracting key phenological variables or metrics of a particular season. These characteristics may not necessarily correspond directly to conventional, ground-based phenological events, but do provide indications of ecosystem dynamics. A complete list of the phenological metrics that can be extracted from smoothed, time-series NDVI data is available in the USGS online resources (http://phenology.cr.usgs.gov/methods_deriving.php).This work aims to develop an open source application to automatically extract these phenological metrics from a set of satellite input data. The main advantage of QGIS for this specific application relies on the easiness and quickness in developing new plug-ins, using Python language, based on the experience of the research group in other related works. QGIS has its own application programming interface (API) with functionalities and programs to develop new features. The toolbar developed for this application was implemented using the plug-in NDVIToolbar.py. The user introduces the raster files as input and obtains a plot and a report with the metrics. The report includes the following eight metrics: SOST (Start Of Season - Time) corresponding to the day of the year identified as having a consistent upward trend in the NDVI time series; SOSN (Start Of Season - NDVI) corresponding to the NDVI value associated with SOST; EOST (End of Season - Time) which corresponds to the day of year identified at the end of a consistent downward trend in the NDVI time series; EOSN (End of Season - NDVI) corresponding to the NDVI value

MEASURING WORKING HOURS INPUT IN VINE GROWING AT WORK ORGANIZATION BASED ON PHENOLOGICAL PHASES

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J BRAZSIL

2002-05-01

Full Text Available Research was based on phenological phases of Italian Riesling, involving differences in labour and financial input for dry, optimal and wet weather. Worktime demand for certain operations in vine growing was determined with an analytic method, work day survey and We worked out alternatives for dry, optimum and wet weather on the basis of phenological phaseses. The worktime demand for the phenological phases with all their operations were analysed and planned in an itemized way based on our findings. We used them to work out the worktime demand for the given vine land for each operation. To analyse differences coming from diverse methods of cultivation and spacing, the material, operational and total costs of hand and mechanized labour were projected for 1 hectare and variance analysis was made.

Characterizing phenological vegetation dynamics amidst extreme climate variability in Australia with MODIS VI data

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Broich, M.; Huete, A. R.; Xuanlon, M.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.

2012-12-01

Australia's climate is extremely variable with inter-annual rainfall at any given site varying by 5- or 6-fold or more, across the continent. In addition to such inter-annual variability, there can be significant intra-annual variability, especially in monsoonal Australia (e.g. the wet tropical savannas) and Mediterranean climates in SW Australia where prolonged dry seasons occur each year. This presents unique challenges to the characterization of seasonal dynamics with satellite datasets. In contrast to annual reoccurring temperature-driven phenology of northern hemisphere mid-latitudes, vegetation dynamics of the vast and dry Australian interior are poorly quantified by existing remote sensing products. For example, in the current global-based MODIS phenology product, central Australia is covered by ~30% fill values for any given year. Two challenges are specific to Australian landscapes: first, the difficulty of characterizing seasonality of rainfall-driven ecosystems in interior Australia where duration and magnitude of green-up and brown down cycles show high inter annual variability; second, modeling two phenologic layers, the trees and the grass in savannas were the trees are evergreen but the herbaceous understory varies with rainfall. Savannas cover >50% of Australia. Australia's vegetation and climate are different from other continents. A MODIS phenology product capable of characterizing vegetation dynamics across the continent is being developed in this research as part of the AusCover national expert network aiming to provide Australian biophysical remote sensing data time-series and continental-scale map products. These products aim to support the Terrestrial Ecosystem Research Network (TERN) serving ecosystem research in Australia. The MODIS land surface product for Australia first searches the entire time series of each Climate Modeling Grid pixel for low-high-low extreme point sequences. A double logistic function is then fit to each of these

Assessment of global precipitation measurement satellite products over Saudi Arabia

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Mahmoud, Mohammed T.; Al-Zahrani, Muhammad A.; Sharif, Hatim O.

2018-04-01

Most hydrological analysis and modeling studies require reliable and accurate precipitation data for successful simulations. However, precipitation measurements should be more representative of the true precipitation distribution. Many approaches and techniques are used to collect precipitation data. Recently, hydrometeorological and climatological applications of satellite precipitation products have experienced a significant improvement with the emergence of the latest satellite products, namely, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) products, which can be utilized to estimate and analyze precipitation data. This study focuses on the validation of the IMERG early, late and final run rainfall products using ground-based rain gauge observations throughout Saudi Arabia for the period from October 2015 to April 2016. The accuracy of each IMERG product is assessed using six statistical performance measures to conduct three main evaluations, namely, regional, event-based and station-based evaluations. The results indicate that the early run product performed well in the middle and eastern parts as well as some of the western parts of the country; meanwhile, the satellite estimates for the other parts fluctuated between an overestimation and an underestimation. The late run product showed an improved accuracy over the southern and western parts; however, over the northern and middle parts, it showed relatively high errors. The final run product revealed significantly improved precipitation estimations and successfully obtained higher accuracies over most parts of the country. This study provides an early assessment of the performance of the GPM satellite products over the Middle East. The study findings can be used as a beneficial reference for the future development of the IMERG algorithms.

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

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Mocko, David M.; Kumar, S. V.; Peters-Lidard, C. D.; Tian, Y.

2011-01-01

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Characterizing spatiotemporal dynamics in phenology of urban ecosystems based on Landsat data

Energy Technology Data Exchange (ETDEWEB)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.; Meng, Lin

2017-12-01

Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observations (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14 days) start-of season (SOS) and a later (13–20 days) end-of season (EOS), resulting in an extended (5–30 days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (-0.30 day per year), and increasing EOS and GSL (0.50 and 0.90 day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

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Luvall, J. C.; Sprigg, W.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P.; Budge, A.; Hudspeth, W.;

Space-Derived Phenology, Retrieval and Use for Drought and Food Security Monitoring

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Meroni, M.; Kayitakire, F.; Rembold, F.; Urbano, F.; Schucknecht, A.; LEO, O.

2014-12-01

Monitoring vegetation conditions is a critical activity for assessing food security in Africa. Rural populations relying on rain-fed agriculture and livestock grazing are highly exposed to large seasonal and inter-annual fluctuations in water availability. Monitoring the state, evolution, and productivity of vegetation, crops and pastures in particular, is important to conduct food emergency responses and plan for a long-term, resilient, development strategy in this area. The timing of onset, the duration, and the intensity of vegetation growth can be retrieved from space observations and used for food security monitoring to assess seasonal vegetation development and forecast the likely seasonal outcome when the season is ongoing. In this contribution we present a set of phenology-based remote sensing studies in support to food security analysis. Key phenological indicators are retrieved using a model-fit approach applied to SOPT-VEGETATION FAPAR time series. Remote-sensing phenology is first used to estimate i) the impact of the drought in the Horn of Africa, ii) crop yield in Tunisia and, iii) rangeland biomass production in Niger. Then the impact of the start and length of vegetation growing period on the total biomass production is assessed over the Sahel. Finally, a probabilistic approach using phenological information to forecast the occurrence of an end-of-season biomass production deficit is applied over the Sahel to map hot-spots of drought-related risk.

First-year Progress and Future Directions of the USA National Phenology Network

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Weltzin, J. F.; Losleben, M. V.

2008-12-01

Background Periodic plant and animal cycles driven by seasonal variations in climate (i.e., phenology) set the stage for dynamics of ecosystem processes, determine land surface properties, control biosphere-atmosphere interactions, and affect food production, health, conservation, and recreation. Phenological data and models have applications related to scientific research, education and outreach, as well as to stakeholders interested in agriculture, tourism and recreation, human health, and natural resource conservation and management. The predictive potential of phenology requires a new data resource-a national network of integrated phenological observations and the tools to access and analyze them at multiple scales. The USA National Phenology Network (USA-NPN) is an emerging and exciting partnership between federal agencies, the academic community, and the general public to monitor and understand the influence of seasonal cycles on the Nation's resources. The USA-NPN will establish a wall-to-wall science and monitoring initiative focused on phenology as a tool to understand how plants, animals and landscapes respond to climate variation, and as a tool to facilitate human adaptation to ongoing and potential future climate change. Results The National Coordinating Office of the USA-NPN began operation in August 2007 at the University of Arizona, Tucson, AZ. This first year of operation produced many new phenology products and venues for phenology research and citizen involvement, as well as identification of future directions for the USA NPN. Products include a new web-site (www.usanpn.org) that went live in June 2008; the web-site includes a tool for on-line data entry, and serves as a clearinghouse for products and information to facilitate research and communication related to phenology. The new core Plant Phenology Program includes profiles for 185 vetted local, regional, and national plant species with descriptions and monitoring protocols, as well as

Are satellite products good proxies for gauge precipitation over Singapore?

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Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

2018-05-01

The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate

The USA National Phenology Network: A national science and monitoring program for understanding climate change

Science.gov (United States)

Weltzin, J.

2009-04-01

Patterns of phenology for plants and animals control ecosystem processes, determine land surface properties, control biosphere-atmosphere interactions, and affect food production, health, conservation, and recreation. Although phenological data and models have applications related to scientific research, education and outreach, agriculture, tourism and recreation, human health, and natural resource conservation and management, until recently there was no coordinated effort to understand phenology at the national scale in the United States. The USA National Phenology Network (USA-NPN; www.usanpn.org), established in 2007, is an emerging and exciting partnership between federal agencies, the academic community, and the general public to establish a national science and monitoring initiative focused on phenology. The first year of operation of USA-NPN produced many new phenology products and venues for phenology research and citizen involvement. Products include a new web-site (www.usanpn.org) that went live in June 2008; the web-site includes a tool for on-line data entry, and serves as a clearinghouse for products and information to facilitate research and communication related to phenology. The new core Plant Phenology Program includes profiles for 200 vetted local, regional, and national plant species with descriptions and (BBCH-consistent) monitoring protocols, as well as templates for addition of new species. A partnership program describes how other monitoring networks can engage with USA-NPN to collect, manage or disseminate phenological information for science, health, education, management or predictive service applications. Project BudBurst, a USA-NPN field campaign for citizen scientists, went live in February 2008, and now includes over 3000 registered observers monitoring 4000 plants across the nation. For 2009 and beyond, we will initiate a new Wildlife Phenology Program, create an on-line clearing-house for phenology education and outreach, strengthen

Estimating and Analyzing Savannah Phenology with a Lagged Time Series Model

DEFF Research Database (Denmark)

Boke-Olen, Niklas; Lehsten, Veiko; Ardo, Jonas

2016-01-01

cycle due to their areal coverage and can have an effect on the food security in regions that depend on subsistence farming. In this study we investigate how soil moisture, mean annual precipitation, and day length control savannah phenology by developing a lagged time series model. The model uses...... climate data for 15 flux tower sites across four continents, and normalized difference vegetation index from satellite to optimize a statistical phenological model. We show that all three variables can be used to estimate savannah phenology on a global scale. However, it was not possible to create...... a simplified savannah model that works equally well for all sites on the global scale without inclusion of more site specific parameters. The simplified model showed no bias towards tree cover or between continents and resulted in a cross-validated r2 of 0.6 and root mean squared error of 0.1. We therefore...

Urban phenological studies – Past, present, future

International Nuclear Information System (INIS)

Jochner, Susanne; Menzel, Annette

2015-01-01

Phenology is believed to be a suitable bio-indicator to track climate change. Based on the strong statistical association between phenology and temperature phenological observations provide an inexpensive means for the temporal and spatial analysis of the urban heat island. However, other environmental factors might also weaken this relationship. In addition, the investigation of urban phenology allows an estimation of future phenology from current information since cities with their amplified temperatures may serve as a proxy for future conditions. Nevertheless, the design of spatial compared to long-term studies might be influenced by different factors which should be taken into consideration when interpreting results from a specific study. In general, plants located in urban areas tend to flush and bloom earlier than in the countryside. What are the consequences of these urban–rural differences? This review will document existing findings on urban phenology and will highlight areas in which further research is needed. - Highlights: • Urban phenology can be used for the estimation of the urban heat island effect. • Confounding factors weaken the phenology–temperature relationship. • Urban phenology is useful as a proxy for climate change impacts on phenology. • Differences in the study design hinder the generalisation of one specific method. • Urban–rural variations in phenology affect vegetation, meteorology, human health. - Studies on urban phenology can be used to detect urban heat islands and to assess climate change impacts but it still remains important to adequately link spatial and long-term data

High-resolution Monthly Satellite Precipitation Product over the Conterminous United States

Science.gov (United States)

Hashemi, H.; Fayne, J.; Knight, R. J.; Lakshmi, V.

2017-12-01

We present a data set that enhanced the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) monthly product 3B43 in its accuracy and spatial resolution. For this, we developed a correction function to improve the accuracy of TRMM 3B43, spatial resolution of 25 km, by estimating and removing the bias in the satellite data using a ground-based precipitation data set. We observed a strong relationship between the bias and land surface elevation; TRMM 3B43 tends to underestimate the ground-based product at elevations above 1500 m above mean sea level (m.amsl) over the conterminous United States. A relationship was developed between satellite bias and elevation. We then resampled TRMM 3B43 to the Digital Elevation Model (DEM) data set at a spatial resolution of 30 arc second ( 1 km on the ground). The produced high-resolution satellite-based data set was corrected using the developed correction function based on the bias-elevation relationship. Assuming that each rain gauge represents an area of 1 km2, we verified our product against 9,200 rain gauges across the conterminous United States. The new product was compared with the gauges, which have 50, 60, 70, 80, 90, and 100% temporal coverage within the TRMM period of 1998 to 2015. Comparisons between the high-resolution corrected satellite-based data and gauges showed an excellent agreement. The new product captured more detail in the changes in precipitation over the mountainous region than the original TRMM 3B43.

Vegetation phenology from Sentinel-2 and field cameras for a Dutch barrier island

NARCIS (Netherlands)

Vrieling, A.; Meroni, Michele; Darvishzadeh, R.; Skidmore, A.K.; Wang, Tiejun; Zurita-Milla, R.; Oosterbeek, Kees; O'Connor, Brian; Marc, Paganini

Remote sensing studies of vegetation phenology increasingly benefit from freely available satellite imagery acquired with high temporal frequency at fine spatial resolution. Particularly for heterogeneous landscapes this is good news, given the drawback of medium-resolution sensors commonly used for

Toward a Lake Ice Phenology Derived from VIIRS Data

Science.gov (United States)

Sütterlin, Melanie; Duguay-Tetzlaff, Anke; Wunderle, Stefan

2017-04-01

Ice cover on lakes plays an essential role in the physical, chemical, and biological processes of freshwater systems (e.g., ice duration controls the seasonal heat budget of lakes), and it also has many economic implications (e.g., for hydroelectricity, transportation, winter tourism). The variability and trends in the seasonal cycle of lake ice (e.g., timing of freeze-up and break-up) represent robust and direct indicators of climate change; they therefore emphasize the importance of monitoring lake ice phenology. Satellite remote sensing has proven its great potential for detecting and measuring the ice cover on lakes. Different remote sensing systems have been successfully used to collect recordings of freeze-up, break-up, and ice thickness and increase the spatial and temporal coverage of ground-based observations. Therefore, within the Global Climate Observing System (GCOS) Swiss project, "Integrated Monitoring of Ice in Selected Swiss Lakes," initiated by MeteoSwiss, satellite images from various sensors and different approaches are used and compared to perform investigations aimed at integrated monitoring of lake ice in Switzerland and contributing to the collection of lake ice phenology recordings. Within the framework of this project, the Remote Sensing Research Group of the University of Bern (RSGB) utilizes data acquired in the fine-resolution imagery (I) bands (1-5) of the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor that is mounted onboard the SUOMI-NPP. Visible and near-infrared reflectances, as well as thermal infrared-derived lake surface water temperatures (LSWT), are used to retrieve lake ice phenology dates. The VIIRS instrument, which combines a high temporal resolution ( 2 times per day) with a reasonable spatial resolution (375 m), is equipped with a single broad-band thermal I-channel (I05). Thus, a single-channel LSWT retrieval algorithm is employed to correct for the atmospheric influence. The single channel algorithm applied in

Fodder Biomass Monitoring in Sahelian Rangelands Using Phenological Metrics from FAPAR Time Series

DEFF Research Database (Denmark)

Diouf, Abdoul Aziz; Brandt, Martin Stefan; Verger, Aleixandre

2015-01-01

Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI) and in situ biomass data....... This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and in situ biomass. A model with three variables—large seasonal integral (LINTG), length of growing season......, and end of season decreasing rate—performed best (MAE = 605 kg·DM/ha; R2 = 0.68) across Sahelian ecosystems in Senegal (data for the period 1999–2013). A model with annual maximum (PEAK) and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64), allowing a timely estimation...

Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

Science.gov (United States)

Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

2017-10-01

As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

Science.gov (United States)

Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

2016-01-01

We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

Science.gov (United States)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

Science.gov (United States)

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-01-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia’s cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal

No Consistent Evidence for Advancing or Delaying Trends in Spring Phenology on the Tibetan Plateau

Science.gov (United States)

Wang, Xufeng; Xiao, Jingfeng; Li, Xin; Cheng, Guodong; Ma, Mingguo; Che, Tao; Dai, Liyun; Wang, Shaoying; Wu, Jinkui

2017-12-01

Vegetation phenology is a sensitive indicator of climate change and has significant effects on the exchange of carbon, water, and energy between the terrestrial biosphere and the atmosphere. The Tibetan Plateau, the Earth's "third pole," is a unique region for studying the long-term trends in vegetation phenology in response to climate change because of the sensitivity of its alpine ecosystems to climate and its low-level human disturbance. There has been a debate whether the trends in spring phenology over the Tibetan Plateau have been continuously advancing over the last two to three decades. In this study, we examine the trends in the start of growing season (SOS) for alpine meadow and steppe using the Global Inventory Modeling and Mapping Studies (GIMMS)3g normalized difference vegetation index (NDVI) data set (1982-2014), the GIMMS NDVI data set (1982-2006), the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data set (2001-2014), the Satellite Pour l'Observation de la Terre Vegetation (SPOT-VEG) NDVI data set (1999-2013), and the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) NDVI data set (1998-2007). Both logistic and polynomial fitting methods are used to retrieve the SOS dates from the NDVI data sets. Our results show that the trends in spring phenology over the Tibetan Plateau depend on both the NDVI data set used and the method for retrieving the SOS date. There are large discrepancies in the SOS trends among the different NDVI data sets and between the two different retrieval methods. There is no consistent evidence that spring phenology ("green-up" dates) has been advancing or delaying over the Tibetan Plateau during the last two to three decades. Ground-based budburst data also indicate no consistent trends in spring phenology. The responses of SOS to environmental factors (air temperature, precipitation, soil temperature, and snow depth) also vary among NDVI data sets and phenology retrieval methods. The increases in winter and spring

Impact of some climatic and phenological parameters on the ...

African Journals Online (AJOL)

In the first year, in control clones,climatic and phenological parameters explain 52.80% callogenesis variations, against 31.50% for SE. Therefore,climate and phenology significantly influence callogenesis, but not SE. For further industrial production of secondary metabolites such as butter, the obromin and chocolate aroma ...

Total Discharge Estimation in the Korean Peninsula Using Multi-Satellite Products

Directory of Open Access Journals (Sweden)

Jae Young Seo

2017-07-01

Full Text Available Estimation of total discharge is necessary to understand the hydrological cycle and to manage water resources efficiently. However, the task is problematic in an area where ground observations are limited. The North Korea region is one example. Here, the total discharge was estimated based on the water balance using multiple satellite products. They are the terrestrial water storage changes (TWSC derived from the Gravity Recovery and Climate Experiment (GRACE, precipitation from the Tropical Rainfall Measuring Mission (TRMM, and evapotranspiration from the Moderate Resolution Imaging Spectroradiometer (MODIS. The satellite-based discharge was compared with land surface model products of the Global Land Data Assimilation System (GLDAS, and a positive relationship between the results was obtained (r = 0.70–0.86; bias = −9.08–16.99 mm/month; RMSE = 36.90–62.56 mm/month; NSE = 0.01–0.62. Among the four land surface models of GLDAS (CLM, Mosaic, Noah, and VIC, CLM corresponded best with the satellite-based discharge, satellite-based discharge has a tendency to slightly overestimate compared to model-based discharge (CLM, Mosaic, Noah, and VIC in the dry season. Also, the total discharge data based on the Precipitation-Runoff Modeling System (PRMS and the in situ discharge for major five river basins in South Korea show comparable seasonality and high correlation with the satellite-based discharge. In spite of the relatively low spatial resolution of GRACE, and loss of information incurred during the process of integrating three different satellite products, the proposed methodology can be a practical tool to estimate the total discharge with reasonable accuracy, especially in a region with scarce hydrologic data.

Detecting inter-annual variations in the phenology of evergreen conifers using long-term MODIS vegetation index time series.

OpenAIRE

Ulsig, Laura

2016-01-01

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalised Difference Vegetation Index (NDVI). This study investigates the potential of the Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of ...

Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

Science.gov (United States)

Chen, H.; Chandrasekar, V.; Biswas, S.

2015-12-01

Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X

Can Growing Degree Days and Photoperiod Predict Spring Wheat Phenology?

Directory of Open Access Journals (Sweden)

Muhammad A. Aslam

2017-09-01

Full Text Available Wheat (Triticum aestivum production in the rainfed area of Pothwar Pakistan is extremely vulnerable to high temperature. The expected increase in temperature due to global warming should result in shorter crop life cycles, and thus lower biomass and grain yield. Two major factors control wheat phenological development: temperature and photoperiod. To evaluate wheat development in response to these factors, we conducted experiments that created diverse temperature and daylength conditions by adjusting the crop sowing time. The study was conducted during 2013–14 and 2014–15 using five spring wheat genotypes, four sowing times, at three sites under rainfed management in Pothwar, Pakistan. Wheat crops experienced more cold days with early sowing, but later sowing dates resulted in higher temperatures, especially from anthesis to maturity. These treatments produced large differences in phenology, biomass production, and yield. To investigate whether growing degree days (GDD and photoperiod algorithms could predict wheat phenology under these changing conditions, GDD was calculated based on the method proposed by Wang and Engel while photoperiod followed the approach introduced in the APSIM crop growth model. GDD was calculated separately and in combination with photoperiod from germination to anthesis. For the grain filling period, only GDD was calculated. The observed and predicted number of days to anthesis and maturity were in good agreement, showing that the combination of GDD and photoperiod algorithms provided good estimations of spring wheat phenology under variable temperature and daylength conditions.

Phenology MMS: a program to simulate crop phenological responses to water stress

Science.gov (United States)

Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet the phenologic...

An NDVI-Based Vegetation Phenology Is Improved to be More Consistent with Photosynthesis Dynamics through Applying a Light Use Efficiency Model over Boreal High-Latitude Forests

Directory of Open Access Journals (Sweden)

Siheng Wang

2017-07-01

Full Text Available Remote sensing of high-latitude forests phenology is essential for understanding the global carbon cycle and the response of vegetation to climate change. The normalized difference vegetation index (NDVI has long been used to study boreal evergreen needleleaf forests (ENF and deciduous broadleaf forests. However, the NDVI-based growing season is generally reported to be longer than that based on gross primary production (GPP, which can be attributed to the difference between greenness and photosynthesis. Instead of introducing environmental factors such as land surface or air temperature like previous studies, this study attempts to make VI-based phenology more consistent with photosynthesis dynamics through applying a light use efficiency model. NDVI (MOD13C2 was used as a proxy for both fractional of absorbed photosynthetically active radiation (APAR and light use efficiency at seasonal time scale. Results show that VI-based phenology is improved towards tracking seasonal GPP changes more precisely after applying the light use efficiency model compared to raw NDVI or APAR, especially over ENF.

A Modified Spatiotemporal Fusion Algorithm Using Phenological Information for Predicting Reflectance of Paddy Rice in Southern China

Directory of Open Access Journals (Sweden)

Mengxue Liu

2018-05-01

Full Text Available Satellite data for studying surface dynamics in heterogeneous landscapes are missing due to frequent cloud contamination, low temporal resolution, and technological difficulties in developing satellites. A modified spatiotemporal fusion algorithm for predicting the reflectance of paddy rice is presented in this paper. The algorithm uses phenological information extracted from a moderate-resolution imaging spectroradiometer enhanced vegetation index time series to improve the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM. The algorithm is tested with satellite data on Yueyang City, China. The main contribution of the modified algorithm is the selection of similar neighborhood pixels by using phenological information to improve accuracy. Results show that the modified algorithm performs better than ESTARFM in visual inspection and quantitative metrics, especially for paddy rice. This modified algorithm provides not only new ideas for the improvement of spatiotemporal data fusion method, but also technical support for the generation of remote sensing data with high spatial and temporal resolution.

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

OpenAIRE

Ulsig, Laura; Nichol, Caroline J.; Huemmrich, Karl F.; Landis, David R.; Middleton, Elizabeth M.; Lyapustin, Alexei I.; Mammarella, Ivan; Levula, Janne; Porcar-Castell, Albert

2017-01-01

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MO...

Site-level evaluation of satellite-based global terrestrial gross primary production and net primary production monitoring.

Science.gov (United States)

David P. Turner; William D. Ritts; Warren B. Cohen; Thomas K. Maeirsperger; Stith T. Gower; Al A. Kirschbaum; Steve W. Runnings; Maosheng Zhaos; Steven C. Wofsy; Allison L. Dunn; Beverly E. Law; John L. Campbell; Walter C. Oechel; Hyo Jung Kwon; Tilden P. Meyers; Eric E. Small; Shirley A. Kurc; John A. Gamon

2005-01-01

Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling...

Old Plants, New Tricks: Phenological Research Using Herbarium Specimens.

Science.gov (United States)

Willis, Charles G; Ellwood, Elizabeth R; Primack, Richard B; Davis, Charles C; Pearson, Katelin D; Gallinat, Amanda S; Yost, Jenn M; Nelson, Gil; Mazer, Susan J; Rossington, Natalie L; Sparks, Tim H; Soltis, Pamela S

2017-07-01

The timing of phenological events, such as leaf-out and flowering, strongly influence plant success and their study is vital to understanding how plants will respond to climate change. Phenological research, however, is often limited by the temporal, geographic, or phylogenetic scope of available data. Hundreds of millions of plant specimens in herbaria worldwide offer a potential solution to this problem, especially as digitization efforts drastically improve access to collections. Herbarium specimens represent snapshots of phenological events and have been reliably used to characterize phenological responses to climate. We review the current state of herbarium-based phenological research, identify potential biases and limitations in the collection, digitization, and interpretation of specimen data, and discuss future opportunities for phenological investigations using herbarium specimens. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulating crop phenological responses to water stress using the phenology mms software component

Science.gov (United States)

Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet the phenologic...

The Stackelberg Model for a Leader of Production and Many Satellites

Directory of Open Access Journals (Sweden)

Catalin Angelo Ioan

2015-05-01

Full Text Available Oligopoly is a market situation where there are a small number of bidders (at least two of a good non-substituent and a sufficient number of consumers. The paper analyses the Stackelberg model for a leader of production and many satellites. There are obtained the equilibrium productions, maximum profits and sales price where one of the company is the leader of quantity, and other satellites. There are also survey the situations where the firm based on its marginal cost of production can effectively take the lead of production.

A Passive Microwave L-Band Boreal Forest Freeze/Thaw and Vegetation Phenology Study

Science.gov (United States)

Roy, A.; Sonnentag, O.; Pappas, C.; Mavrovic, A.; Royer, A.; Berg, A. A.; Rowlandson, T. L.; Lemay, J.; Helgason, W.; Barr, A.; Black, T. A.; Derksen, C.; Toose, P.

2016-12-01

The boreal forest is the second largest land biome in the world and thus plays a major role in the global and regional climate systems. The extent, timing and duration of seasonal freeze/thaw (F/T) state influences vegetation developmental stages (phenology) and, consequently, constitute an important control on how boreal forest ecosystems exchange carbon, water and energy with the atmosphere. The effective retrieval of seasonal F/T state from L-Band radiometry was demonstrated using satellite mission. However, disentangling the seasonally differing contributions from forest overstory and understory vegetation, and the soil surface to the satellite signal remains challenging. Here we present initial results from a radiometer field campaign to improve our understanding of the L-Band derived boreal forest F/T signal and vegetation phenology. Two L-Band surface-based radiometers (SBR) are installed on a micrometeorological tower at the Southern Old Black Spruce site in central Saskatchewan over the 2016-2017 F/T season. One radiometer unit is installed on the flux tower so it views forest including all overstory and understory vegetation and the moss-covered ground surface. A second radiometer unit is installed within the boreal forest overstory, viewing the understory and the ground surface. The objectives of our study are (i) to disentangle the L-Band F/T signal contribution of boreal forest overstory from the understory and ground surface, (ii) to link the L-Band F/T signal to related boreal forest structural and functional characteristics, and (iii) to investigate the use of the L-Band signal to characterize boreal forest carbon, water and energy fluxes. The SBR observations above and within the forest canopy are used to retrieve the transmissivity (γ) and the scattering albedo (ω), two parameters that describe the emission of the forest canopy though the F/T season. These two forest parameters are compared with boreal forest structural and functional

Phenological Indicators of Vegetation Recovery in Wetland Ecosystems

Science.gov (United States)

Taddeo, S.; Dronova, I.

2017-12-01

Landscape phenology is increasingly used to measure the impacts of climatic and environmental disturbances on plant communities. As plants show rapid phenological responses to environmental changes, variation in site phenology can help characterize vegetation recovery following restoration treatments and qualify their resistance to environmental fluctuations. By leveraging free remote sensing datasets, a phenology-based analysis of vegetation dynamics could offer a cost-effective assessment of restoration progress in wetland ecosystems. To fulfill this objective, we analyze 20 years of free remote sensing data from NASA's Landsat archive to offer a landscape-scale synthesis of wetland restoration efforts in the Sacramento-San Joaquin Delta of California, USA. Through an analysis of spatio-temporal changes in plant phenology and greenness, we assess how 25 restored wetlands across the Delta have responded to restoration treatments, time, and landscape context. We use a spline smoothing approach to generate both site-wide and pixel-specific phenological curves and identify key phenological events. Preliminary results reveal a greater variability in greenness and growing season length during the initial post-restoration years and a significant impact of landscape context in the time needed to reach phenological stability. Well-connected sites seem to benefit from an increased availability of propagules enabling them to reach peak greenness and maximum growing season length more rapidly. These results demonstrate the potential of phenological analyses to measure restoration progress and detect factors promoting wetland recovery. A thorough understanding of wetland phenology is key to the quantification of ecosystem processes including carbon sequestration and habitat provisioning.

Refined shape model fitting methods for detecting various types of phenological information on major U.S. crops

Science.gov (United States)

Sakamoto, Toshihiro

2018-04-01

Crop phenological information is a critical variable in evaluating the influence of environmental stress on the final crop yield in spatio-temporal dimensions. Although the MODIS (Moderate Resolution Imaging Spectroradiometer) Land Cover Dynamics product (MCD12Q2) is widely used in place of crop phenological information, the definitions of MCD12Q2-derived phenological events (e.g. green-up date, dormancy date) were not completely consistent with those of crop development stages used in statistical surveys (e.g. emerged date, harvested date). It has been necessary to devise an alternative method focused on detecting continental-scale crop developmental stages using a different approach. Therefore, this study aimed to refine the Shape Model Fitting (SMF) method to improve its applicability to multiple major U.S. crops. The newly-refined SMF methods could estimate the timing of 36 crop-development stages of major U.S. crops, including corn, soybeans, winter wheat, spring wheat, barley, sorghum, rice, and cotton. The newly-developed calibration process did not require any long-term field observation data, and could calibrate crop-specific phenological parameters, which were used as coefficients in estimated equation, by using only freely accessible public data. The calibration of phenological parameters was conducted in two steps. In the first step, the national common phenological parameters, referred to as X0[base], were calibrated by using the statistical data of 2008. The SMF method coupled using X0[base] was named the rSMF[base] method. The second step was a further calibration to gain regionally-adjusted phenological parameters for each state, referred to as X0[local], by using additional statistical data of 2015 and 2016. The rSMF method using the X0[local] was named the rSMF[local] method. This second calibration process improved the estimation accuracy for all tested crops. When applying the rSMF[base] method to the validation data set (2009-2014), the root

Next-Generation Satellite Precipitation Products for Understanding Global and Regional Water Variability

Science.gov (United States)

Hou, Arthur Y.

2011-01-01

A major challenge in understanding the space-time variability of continental water fluxes is the lack of accurate precipitation estimates over complex terrains. While satellite precipitation observations can be used to complement ground-based data to obtain improved estimates, space-based and ground-based estimates come with their own sets of uncertainties, which must be understood and characterized. Quantitative estimation of uncertainties in these products also provides a necessary foundation for merging satellite and ground-based precipitation measurements within a rigorous statistical framework. Global Precipitation Measurement (GPM) is an international satellite mission that will provide next-generation global precipitation data products for research and applications. It consists of a constellation of microwave sensors provided by NASA, JAXA, CNES, ISRO, EUMETSAT, DOD, NOAA, NPP, and JPSS. At the heart of the mission is the GPM Core Observatory provided by NASA and JAXA to be launched in 2013. The GPM Core, which will carry the first space-borne dual-frequency radar and a state-of-the-art multi-frequency radiometer, is designed to set new reference standards for precipitation measurements from space, which can then be used to unify and refine precipitation retrievals from all constellation sensors. The next-generation constellation-based satellite precipitation estimates will be characterized by intercalibrated radiometric measurements and physical-based retrievals using a common observation-derived hydrometeor database. For pre-launch algorithm development and post-launch product evaluation, NASA supports an extensive ground validation (GV) program in cooperation with domestic and international partners to improve (1) physics of remote-sensing algorithms through a series of focused field campaigns, (2) characterization of uncertainties in satellite and ground-based precipitation products over selected GV testbeds, and (3) modeling of atmospheric processes and

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.

Science.gov (United States)

Stucky, Brian J; Guralnick, Rob; Deck, John; Denny, Ellen G; Bolmgren, Kjell; Walls, Ramona

2018-01-01

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

Perspectivs and challenges of phenology research on South America

Science.gov (United States)

Patrícia Morellato, Leonor

2017-04-01

Detecting plant responses to environmental changes across the Southern Hemisphere is an important question in the global agenda, as there is still a shortage of studies addressing phenological trends related to global warming. Here I bring a fresh perspective on the current knowledge of South America's phenology, and discusss the challenges and future research agendas for one of the most diverse regions of the world. I will syntethize: (i) What is the current focus of contemporany phenological research in South America? (ii) Is phenology contributing to the detection of trends and shifts related to climate or antropogenic changes? (iii) How has phenology been integrated to conservation, restoration, and management of natural vegetation and endangered species? (iv) What would be the main challenges and new avenues for South American phenological research in the 21st century? (v) Can we move towards phenology monitoring networks, linked to citizen science and education? My perspective is based on recent reviews addressing the Southeastern Hemisphere, South America, and Neotropical phenology; and on reviews and essays on the contribution of phenological research to biodiversity conservation, management, and ecological restoration, emphasizing tropical, species-rich ecosystems. Phenological research has grown at an unprecedented rate in the last 20 years, surpassing 100 articles per year after 2010. There is still a predominance of short-term studies (2-3 years) describing patterns and drivers for reproduction and leaf exchange. Only 10 long-term studies were found, based on direct observations or plant traps, and this number did not add much to the previous surveys. Therefore, we remain in need of more long-term studies to enhance the contribution of phenology to climate change research in South America. It is also mandatory to bring conservation issues to phenology research. The effects of climatic and antropogenic changes on plant phenology have been addressed

European-wide simulations of croplands using an improved terrestrial biosphere model: Phenology and productivity

Science.gov (United States)

Smith, P. C.; de Noblet-Ducoudré, N.; Ciais, P.; Peylin, P.; Viovy, N.; Meurdesoif, Y.; Bondeau, A.

2010-03-01

Aiming at producing improved estimates of carbon source/sink spatial and interannual patterns across Europe (35% croplands), this work combines the terrestrial biosphere model Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE), for vegetation productivity, water balance, and soil carbon dynamics, and the generic crop model Simulateur Multidisciplinaire pour les Cultures Standard (STICS), for phenology, irrigation, nitrogen balance, and harvest. The ORCHIDEE-STICS model, relying on three plant functional types for the representation of temperate agriculture, is evaluated over the last few decades at various spatial and temporal resolutions. The simulated leaf area index seasonal cycle is largely improved relative to the original ORCHIDEE simulating grasslands, and compares favorably with remote-sensing observations (correlation doubles over Europe). Crop yield is derived from annual net primary productivity and compared with wheat and grain maize harvest data for five European countries. Discrepancies between 30 year mean simulated and reported yields are large in Mediterranean countries. Interannual variability amplitude expressed relative to the mean is reduced toward the observed variability (≈10%) when using ORCHIDEE-STICS. Overall, this study highlights the importance of accounting for the specific phenologies of crops sown both in winter and in spring and for irrigation applied to spring crops in regional/global models of the terrestrial carbon cycle. Limitations suggest to account for temporal and spatial variability in agricultural practices for further simulation improvement.

Disaggregating tree and grass phenology in tropical savannas

Science.gov (United States)

Zhou, Qiang

Savannas are mixed tree-grass systems and as one of the world's largest biomes represent an important component of the Earth system affecting water and energy balances, carbon sequestration and biodiversity as well as supporting large human populations. Savanna vegetation structure and its distribution, however, may change because of major anthropogenic disturbances from climate change, wildfire, agriculture, and livestock production. The overstory and understory may have different water use strategies, different nutrient requirements and have different responses to fire and climate variation. The accurate measurement of the spatial distribution and structure of the overstory and understory are essential for understanding the savanna ecosystem. This project developed a workflow for separating the dynamics of the overstory and understory fractional cover in savannas at the continental scale (Australia, South America, and Africa). Previous studies have successfully separated the phenology of Australian savanna vegetation into persistent and seasonal greenness using time series decomposition, and into fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS) using linear unmixing. This study combined these methods to separate the understory and overstory signal in both the green and senescent phenological stages using remotely sensed imagery from the MODIS (MODerate resolution Imaging Spectroradiometer) sensor. The methods and parameters were adjusted based on the vegetation variation. The workflow was first tested at the Australian site. Here the PV estimates for overstory and understory showed best performance, however NPV estimates exhibited spatial variation in validation relationships. At the South American site (Cerrado), an additional method based on frequency unmixing was developed to separate green vegetation components with similar phenology. When the decomposition and frequency methods were compared, the frequency

On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

Science.gov (United States)

Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

2014-12-01

Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

Remote sensing of land surface phenology

Science.gov (United States)

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

The phenological development of Themeda triandra, Elyonurus ...

African Journals Online (AJOL)

The phenological development of Themeda triandra, Elyonurus argenteus and ... fire or drought may have a detrimental effect on leaf, shoot and seed production. ... Keywords: afrikaans; botany; carbohydrate; crude protein content; cutting; ...

Satellite image simulations for model-supervised, dynamic retrieval of crop type and land use intensity

Science.gov (United States)

Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.

2015-04-01

To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is

Species- and community-level responses combine to drive phenology of lake phytoplankton

Science.gov (United States)

Walters, Annika; Sagrario, María de los Ángeles González; Schindler, Daniel E.

2013-01-01

Global change is leading to shifts in the seasonal timing of growth and maturation for primary producers. Remote sensing is increasingly used to measure the timing of primary production in both aquatic and terrestrial ecosystems, but there is often a poor correlation between these results and direct observations of life-history responses of individual species. One explanation may be that in addition to phenological shifts, global change is also causing shifts in community composition among species with different seasonal timing of growth and maturation. We quantified how shifts in species phenology and in community composition translated into phenological change in a diverse phytoplankton community from 1962-2000. During this time the aggregate community spring-summer phytoplankton peak has shifted 63 days earlier. The mean taxon shift was only 3 days earlier and shifts in taxa phenology explained only 40% of the observed community phenological shift. The remaining community shift was attributed to dominant early season taxa increasing in abundance while a dominant late season taxon decreased in abundance. In diverse producer communities experiencing multiple stressors, changes in species composition must be considered to fully understand and predict shifts in the seasonal timing of primary production.

Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

Directory of Open Access Journals (Sweden)

Hao Guo

2015-06-01

Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.

Satellite-Based Derivation of High-Resolution Forest Information Layers for Operational Forest Management

Directory of Open Access Journals (Sweden)

Johannes Stoffels

2015-06-01

Full Text Available A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.

Genetic variation in flowering phenology and avoidance of seed predation in native populations of Ulex europaeus.

Science.gov (United States)

Atlan, A; Barat, M; Legionnet, A S; Parize, L; Tarayre, M

2010-02-01

The genetic variation in flowering phenology may be an important component of a species' capacity to colonize new environments. In native populations of the invasive species Ulex europaeus, flowering phenology has been shown to be bimodal and related to seed predation. The aim of the present study was to determine if this bimodality has a genetic basis, and to investigate whether the polymorphism in flowering phenology is genetically linked to seed predation, pod production and growth patterns. We set up an experiment raising maternal families in a common garden. Based on mixed analyses of variance and correlations among maternal family means, we found genetic differences between the two main flowering types and confirmed that they reduced seed predation in two different ways: escape in time or predator satiation. We suggest that this polymorphism in strategy may facilitate maintain high genetic diversity for flowering phenology and related life-history traits in native populations of this species, hence providing high evolutionary potential for these traits in invaded areas.

Monitoring Seasonal Evapotranspiration in Vulnerable Agriculture using Time Series VHSR Satellite Data

Science.gov (United States)

Dalezios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2015-04-01

The research work stems from the hypothesis that it is possible to perform an estimation of seasonal water needs of olive tree farms under drought periods by cross correlating high spatial, spectral and temporal resolution (~monthly) of satellite data, acquired at well defined time intervals of the phenological cycle of crops, with ground-truth information simultaneously applied during the image acquisitions. The present research is for the first time, demonstrating the coordinated efforts of space engineers, satellite mission control planners, remote sensing scientists and ground teams to record at specific time intervals of the phenological cycle of trees from ground "zero" and from 770 km above the Earth's surface, the status of plants for subsequent cross correlation and analysis regarding the estimation of the seasonal evapotranspiration in vulnerable agricultural environment. The ETo and ETc derived by Penman-Montieth equation and reference Kc tables, compared with new ETd using the Kc extracted from the time series satellite data. Several vegetation indices were also used especially the RedEdge and the chlorophyll one based on WorldView-2 RedEdge and second NIR bands to relate the tree status with water and nutrition needs. Keywords: Evapotransipration, Very High Spatial Resolution - VHSR, time series, remote sensing, vulnerability, agriculture, vegetation indeces.

Extreme warm temperatures alter forest phenology and productivity in Europe

Czech Academy of Sciences Publication Activity Database

Crabbe, Richard A.; Dash, J.; Rodriguez-Galiano, V. F.; Janouš, Dalibor; Pavelka, Marian; Marek, Michal V.

563-564, sep (2016), s. 486-495 ISSN 0048-9697 Institutional support: RVO:67179843 Keywords : land surface phenology * Envisat MTCI * anomalous temperature * climate variability * lagged effect * forest ecology Subject RIV: EH - Ecology, Behaviour Impact factor: 4.900, year: 2016

The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange

Science.gov (United States)

Joiner, J.; Yoshida, Y.; Vasilkov, A. P.; Schaefer, K.; Jung, M.; Guanter, L.; Zhang, Y; Garrity, S.; Middleton, E. M.; Huemmrich, K. F.;

Hydrological Controls on Floodplain Forest Phenology Assessed using Remotely Sensed Vegetation Indices

Science.gov (United States)

Lemon, M. G.; Keim, R.

2017-12-01

Although specific controls are not well understood, the phenology of temperate forests is generally thought to be controlled by photoperiod and temperature, although recent research suggests that soil moisture may also be important. The phenological controls of forested wetlands have not been thoroughly studied, and may be more controlled by site hydrology than other forests. For this study, remotely sensed vegetation indices were used to investigate hydrological controls on start-of-season timing, growing season length, and end-of-season timing at five floodplains in Louisiana, Arkansas, and Texas. A simple spring green-up model was used to determine the null spring start of season time for each site as a function of land surface temperature and photoperiod, or two remotely sensed indices: MODIS phenology data product and the MODIS Nadir Bidirectional Reflectance Distribution Function-Adjusted Reflectance (NBAR) product. Preliminary results indicate that topographically lower areas within the floodplain with higher flood frequency experience later start-of-season timing. In addition, start-of-season is delayed in wet years relative to predicted timing based solely on temperature and photoperiod. The consequences for these controls unclear, but results suggest hydrological controls on floodplain ecosystem structure and carbon budgets are likely at least partially expressed by variations in growing season length.

Improvement of Alternative Crop Phenology Detection Algorithms using MODIS NDVI Time Series Data in US Corn Belt Region

Science.gov (United States)

Lee, J.; Kang, S.; Seo, B.; Lee, K.

2017-12-01

Predicting crop phenology is important for understanding of crop development and growth processes and improving the accuracy of crop model. Remote sensing offers a feasible tool for monitoring spatio-temporal patterns of crop phenology in region and continental scales. Various methods have been developed to determine the timing of crop phenological stages using spectral vegetation indices (i.e. NDVI and EVI) derived from satellite data. In our study, it was compared four alternative detection methods to identify crop phenological stages (i.e. the emergence and harvesting date) using high quality NDVI time series data derived from MODIS. Also we investigated factors associated with crop development rate. Temperature and photoperiod are the two main factors which would influence the crop's growth pattern expressed in the VI data. Only the effect of temperature on crop development rate was considered. The temperature response function in the Wang-Engel (WE) model was used, which simulates crop development using nonlinear models with response functions that range from zero to one. It has attempted at the state level over 14 years (2003-2016) in Iowa and Illinois state of USA, where the estimated phenology date by using four methods for both corn and soybean. Weekly crop progress reports produced by the USDA NASS were used to validate phenology detection algorithms effected by temperature. All methods showed substantial uncertainty but the threshold method showed relatively better agreement with the State-level data for soybean phenology.

Validating GPM-based Multi-satellite IMERG Products Over South Korea

Science.gov (United States)

Wang, J.; Petersen, W. A.; Wolff, D. B.; Ryu, G. H.

2017-12-01

Accurate precipitation estimates derived from space-borne satellite measurements are critical for a wide variety of applications such as water budget studies, and prevention or mitigation of natural hazards caused by extreme precipitation events. This study validates the near-real-time Early Run, Late Run and the research-quality Final Run Integrated Multi-Satellite Retrievals for GPM (IMERG) using Korean Quantitative Precipitation Estimation (QPE). The Korean QPE data are at a 1-hour temporal resolution and 1-km by 1-km spatial resolution, and were developed by Korea Meteorological Administration (KMA) from a Real-time ADjusted Radar-AWS (Automatic Weather Station) Rainrate (RAD-RAR) system utilizing eleven radars over the Republic of Korea. The validation is conducted by comparing Version-04A IMERG (Early, Late and Final Runs) with Korean QPE over the area (124.5E-130.5E, 32.5N-39N) at various spatial and temporal scales during March 2014 through November 2016. The comparisons demonstrate the reasonably good ability of Version-04A IMERG products in estimating precipitation over South Korea's complex topography that consists mainly of hills and mountains, as well as large coastal plains. Based on this data, the Early Run, Late Run and Final Run IMERG precipitation estimates higher than 0.1mm h-1 are about 20.1%, 7.5% and 6.1% higher than Korean QPE at 0.1o and 1-hour resolutions. Detailed comparison results are available at https://wallops-prf.gsfc.nasa.gov/KoreanQPE.V04/index.html

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Improving models to predict phenological responses to global change

Energy Technology Data Exchange (ETDEWEB)

Richardson, Andrew D. [Harvard College, Cambridge, MA (United States)

2015-11-25

The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

Fine-tuning satellite-based rainfall estimates

Science.gov (United States)

Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

2018-05-01

Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

Trends in land surface phenology and atmospheric CO2 seasonality in the Northern Hemisphere terrestrial ecosystems

Science.gov (United States)

Gonsamo, A.; Chen, J. M.

2017-12-01

Northern terrestrial ecosystems have shown global warming-induced advances in start, delays in end, and thus increased lengths of growing season and gross photosynthesis in recent decades. The tradeoffs between seasonal dynamics of two opposing fluxes, CO2 uptake through photosynthesis and release through respiration, determine the influence of the terrestrial ecosystems on the atmospheric CO2 concentration and 13C/12C isotope ratio seasonality. Atmospheric CO2 and 13C/12C seasonality is controlled by vegetation phenology, but is not identical because growth will typically commence some time before and terminate some time after the net carbon exchange changes sign in spring and autumn, respectively. Here, we use 34-year satellite normalized difference vegetation index (NDVI) observations to determine how changes in vegetation productivity and phenology affect both the atmospheric CO2 and 13C/12C seasonality. Differences and similarities in recent trends of CO2 and 13C/12C seasonality and vegetation phenology will be discussed. Furthermore, we use the NDVI observations, and atmospheric CO2 and 13C/12C data to show the trends and variability of the timing of peak season plant activity. Preliminary results show that the peak season plant activity of the Northern Hemisphere extra-tropical terrestrial ecosystems is shifting towards spring, largely in response to the warming-induced advance of the start of growing season. Besides, the spring-ward shift of the peak plant activity is contributing the most to the increasing peak season productivity. In other words, earlier start of growing season is highly linked to earlier arrival of peak of season and higher NDVI. Changes in the timing of peak season plant activity are expected to disrupt the synchrony of biotic interaction and exert strong biophysical feedbacks on climate by modifying the surface albedo and energy budget.

Role of MODIS Vegetation Phenology Products in the U.S. for Warn Early Warning System for Forest Threats

Science.gov (United States)

Spruce, Joseph; Hargrove, William; Norman, Steve; Gasser, Gerald; Smoot, James; Kuper, Philip

2012-01-01

U.S. forests occupy approx 751 million acres (approx 1/3 of total land). Several abiotic and biotic damage agents disturb, damage, kill, and/or threaten these forests. Regionally extensive forest disturbances can also threaten human life and property, bio-diversity and water supplies. timely regional forest disturbance monitoring products are needed to aid forest health management work at finer scales. daily MODIS data provide a means to monitor regional forest disturbances on a weekly basis, leveraging vegetation phenology. In response, the USFS and NASA began collaborating in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat Early Warning System (EWS).

How Resource Phenology Affects Consumer Population Dynamics.

Science.gov (United States)

Bewick, Sharon; Cantrell, R Stephen; Cosner, Chris; Fagan, William F

2016-02-01

Climate change drives uneven phenology shifts across taxa, and this can result in changes to the phenological match between interacting species. Shifts in the relative phenology of partner species are well documented, but few studies have addressed the effects of such changes on population dynamics. To explore this, we develop a phenologically explicit model describing consumer-resource interactions. Focusing on scenarios for univoltine insects, we show how changes in resource phenology can be reinterpreted as transformations in the year-to-year recursion relationships defining consumer population dynamics. This perspective provides a straightforward path for interpreting the long-term population consequences of phenology change. Specifically, by relating the outcome of phenological shifts to species traits governing recursion relationships (e.g., consumer fecundity or competitive scenario), we demonstrate how changes in relative phenology can force systems into different dynamical regimes, with major implications for resource management, conservation, and other areas of applied dynamics.

Responses of rubber leaf phenology to climatic variations in Southwest China

Science.gov (United States)

Zhai, De-Li; Yu, Haiying; Chen, Si-Chong; Ranjitkar, Sailesh; Xu, Jianchu

2017-11-01

The phenology of rubber trees (Hevea brasiliensis) could be influenced by meteorological factors and exhibits significant changes under different geoclimates. In the sub-optimal environment in Xishuangbanna, rubber trees undergo lengthy periods of defoliation and refoliation. The timing of refoliation from budburst to leaf aging could be affected by powdery mildew disease (Oidium heveae), which negatively impacts seed and latex production. Rubber trees are most susceptible to powdery mildew disease at the copper and leaf changing stages. Understanding and predicting leaf phenology of rubber trees are helpful to develop effective means of controlling the disease. This research investigated the effect of several meteorological factors on different leaf phenological stages in a sub-optimal environment for rubber cultivation in Jinghong, Yunnan in Southwest China. Partial least square regression was used to quantify the relationship between meteorological factors and recorded rubber phenologies from 2003 to 2011. Minimum temperature in December was found to be the critical factor for the leaf phenology development of rubber trees. Comparing the delayed effects of minimum temperature, the maximum temperature, diurnal temperature range, and sunshine hours were found to advancing leaf phenologies. A comparatively lower minimum temperature in December would facilitate the advancing of leaf phenologies of rubber trees. Higher levels of precipitation in February delayed the light green and the entire process of leaf aging. Delayed leaf phenology was found to be related to severe rubber powdery mildew disease. These results were used to build predictive models that could be applied to early warning systems of rubber powdery mildew disease.

The International Satellite Cloud Climatology Project H-Series climate data record product

Science.gov (United States)

Young, Alisa H.; Knapp, Kenneth R.; Inamdar, Anand; Hankins, William; Rossow, William B.

2018-03-01

This paper describes the new global long-term International Satellite Cloud Climatology Project (ISCCP) H-series climate data record (CDR). The H-series data contain a suite of level 2 and 3 products for monitoring the distribution and variation of cloud and surface properties to better understand the effects of clouds on climate, the radiation budget, and the global hydrologic cycle. This product is currently available for public use and is derived from both geostationary and polar-orbiting satellite imaging radiometers with common visible and infrared (IR) channels. The H-series data currently span July 1983 to December 2009 with plans for continued production to extend the record to the present with regular updates. The H-series data are the longest combined geostationary and polar orbiter satellite-based CDR of cloud properties. Access to the data is provided in network common data form (netCDF) and archived by NOAA's National Centers for Environmental Information (NCEI) under the satellite Climate Data Record Program (https://doi.org/10.7289/V5QZ281S" target="_blank">https://doi.org/10.7289/V5QZ281S). The basic characteristics, history, and evolution of the dataset are presented herein with particular emphasis on and discussion of product changes between the H-series and the widely used predecessor D-series product which also spans from July 1983 through December 2009. Key refinements included in the ISCCP H-series CDR are based on improved quality control measures, modified ancillary inputs, higher spatial resolution input and output products, calibration refinements, and updated documentation and metadata to bring the H-series product into compliance with existing standards for climate data records.

Building a satellite climate diagnostics data base for real-time climate monitoring

International Nuclear Information System (INIS)

Ropelewski, C.F.

1991-01-01

The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

A new herbarium-based method for reconstructing the phenology of plant species across large areas.

Science.gov (United States)

Lavoie, Claude; Lachance, Daniel

2006-04-01

Phenological data have recently emerged as particularly effective tools for studying the impact of climate change on plants, but long phenological records are rare. The lack of phenological observations can nevertheless be filled by herbarium specimens as long as some correction procedures are applied to take into account the different climatic conditions associated with sampling locations. In this study, we propose a new herbarium-based method for reconstructing the flowering dates of plant species that have been collected across large areas. Coltsfoot (Tussilago farfara L.) specimens from southern Quebec were used to test the method. Flowering dates for coltsfoot herbarium specimens were adjusted according to the date of disappearance of snow cover in the region where they were collected and compared using a reference point (the date of earliest snowmelt). In southern Quebec, coltsfoot blooms earlier at present (15-31 d) than during the first part of the 20th century. This phenomenon is likely associated with the climate warming trends recorded in this region in the last century, especially during the last three decades when the month of April became warmer, thereby favoring very early-flowering cases. The earlier flowering of coltsfoot is, however, only noticeable in large urban areas (Montreal, Quebec City), suggesting a strong urban heat island effect on the flowering of this plant. Herbarium specimens are useful phenological indicators; however, the databases should be carefully examined prior to analysis to detect biases or trends associated with sampling locations.

Mapping changes in plant phenology across Eurasia, Africa, North and South America from time series image data

DEFF Research Database (Denmark)

McCloy, Keith Raymond; Tind, Sonja Li

2011-01-01

There is considerable evidence of changes in vegetation phenology in response to climate change, where some of this evidence comes from field studies and some comes from the analysis of satellite image data. This paper reports on the analysis of a suite of six indices that depict the way that the...

K-12 Phenology Lessons for the Phenocam Project

Science.gov (United States)

Bennett, K. F.

2013-12-01

Phenology is defined as periodic [or annual] life cycles of plants and animals driven by seasonal environmental changes. Climate change impinges a strong effect on phenology, potentially altering the structure and functioning of ecosystems. In the fall of 2011, the Ashburnham-Westminster Regional School District became the first of five schools to join Harvard University's Phenocam Network with the installation of a webcam to monitor phenology (or 'phenocam') at Overlook Middle School in Ashburnham, Massachusetts. Our school district is now part of a network of near-surface remote sensing phenocams that capture and send images of forest, shrub, and grassland vegetation cover at more than 130 diverse sites in North America. Our phenocam provides a digital image every half hour of the mixed forest canopy north from the school, enabling the detection of changes in canopy development, quantified as canopy 'greenness'. As a part of the Phenocam project, students at the K-12 level have expanded the scope of phenological monitoring protocol that is part of the Harvard Forest Schoolyard Ecology Program, Buds, Leaves, and Global Warming. In this protocol, students work with ecologists at Harvard Forest to monitor buds and leaves on schoolyard trees to determine the length of the growing season, giving them the opportunity to be a part of real and important research concerning the critical environmental issue of climate change. Students involved in the Buds, Leaves, and Global Warming study have the opportunity to compare their ground data on budburst, color change, and leaf drop to the phenocam images, as well as to similar forested sites in locations throughout the United States. Lessons have been developed for comparing student data to phenocam images, canopy greenness time series graphs extracted from the images, and satellite data. Lessons addressing map scale and the Urban Heat Island effect will also be available for teachers. This project will greatly enhance the

Climate change, phenology, and butterfly host plant utilization.

Science.gov (United States)

Navarro-Cano, Jose A; Karlsson, Bengt; Posledovich, Diana; Toftegaard, Tenna; Wiklund, Christer; Ehrlén, Johan; Gotthard, Karl

2015-01-01

Knowledge of how species interactions are influenced by climate warming is paramount to understand current biodiversity changes. We review phenological changes of Swedish butterflies during the latest decades and explore potential climate effects on butterfly-host plant interactions using the Orange tip butterfly Anthocharis cardamines and its host plants as a model system. This butterfly has advanced its appearance dates substantially, and its mean flight date shows a positive correlation with latitude. We show that there is a large latitudinal variation in host use and that butterfly populations select plant individuals based on their flowering phenology. We conclude that A. cardamines is a phenological specialist but a host species generalist. This implies that thermal plasticity for spring development influences host utilization of the butterfly through effects on the phenological matching with its host plants. However, the host utilization strategy of A. cardamines appears to render it resilient to relatively large variation in climate.

Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series MODIS and LANDSAT satellite images

Science.gov (United States)

Georgopoulou, Danai; Koutsias, Nikos

2015-04-01

Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS and LANDSAT satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. Satellite remote sensing data from MODIS and LANDSAT satellites in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the satellite data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we

Accuracy and precision in the calculation of phenology metrics

DEFF Research Database (Denmark)

Ferreira, Ana Sofia; Visser, Andre; MacKenzie, Brian

2014-01-01

a phenology metric is first determined from a noise- and gap-free time series, and again once it has been modified. We show that precision is a greater concern than accuracy for many of these metrics, an important point that has been hereto overlooked in the literature. The variability in precision between...... phenology metrics is substantial, but it can be improved by the use of preprocessing techniques (e.g., gap-filling or smoothing). Furthermore, there are important differences in the inherent variability of the metrics that may be crucial in the interpretation of studies based upon them. Of the considered......Phytoplankton phenology (the timing of seasonal events) is a commonly used indicator for evaluating responses of marine ecosystems to climate change. However, phenological metrics are vulnerable to observation-(bloom amplitude, missing data, and observational noise) and analysis-related (temporal...

Investigating the impact of climate change on crop phenological events in Europe with a phenology model

Science.gov (United States)

Ma, Shaoxiu; Churkina, Galina; Trusilova, Kristina

2012-07-01

Predicting regional and global carbon and water dynamics requires a realistic representation of vegetation phenology. Vegetation models including cropland models exist (e.g. LPJmL, Daycent, SIBcrop, ORCHIDEE-STICS, PIXGRO) but they have various limitations in predicting cropland phenological events and their responses to climate change. Here, we investigate how leaf onset and offset days of major European croplands responded to changes in climate from 1971 to 2000 using a newly developed phenological model, which solely relies on climate data. Net ecosystem exchange (NEE) data measured with eddy covariance technique at seven sites in Europe were used to adjust model parameters for wheat, barley, and rapeseed. Observational data from the International Phenology Gardens were used to corroborate modeled phenological responses to changes in climate. Enhanced vegetation index (EVI) and a crop calendar were explored as alternative predictors of leaf onset and harvest days, respectively, over a large spatial scale. In each spatial model simulation, we assumed that all European croplands were covered by only one crop type. Given this assumption, the model estimated that the leaf onset days for wheat, barley, and rapeseed in Germany advanced by 1.6, 3.4, and 3.4 days per decade, respectively, during 1961-2000. The majority of European croplands (71.4%) had an advanced mean leaf onset day for wheat, barley, and rapeseed (7.0% significant), whereas 28.6% of European croplands had a delayed leaf onset day (0.9% significant) during 1971-2000. The trend of advanced onset days estimated by the model is similar to observations from the International Phenology Gardens in Europe. The developed phenological model can be integrated into a large-scale ecosystem model to simulate the dynamics of phenological events at different temporal and spatial scales. Crop calendars and enhanced vegetation index have substantial uncertainties in predicting phenological events of croplands. Caution

Fodder Biomass Monitoring in Sahelian Rangelands Using Phenological Metrics from FAPAR Time Series

Directory of Open Access Journals (Sweden)

Abdoul Aziz Diouf

2015-07-01

Full Text Available Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI and in situ biomass data. This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR and in situ biomass. A model with three variables—large seasonal integral (LINTG, length of growing season, and end of season decreasing rate—performed best (MAE = 605 kg·DM/ha; R2 = 0.68 across Sahelian ecosystems in Senegal (data for the period 1999–2013. A model with annual maximum (PEAK and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64, allowing a timely estimation of forage availability. The subdivision of the study area in ecoregions increased overall accuracy (MAE = 489.21 kg·DM/ha; R2 = 0.77, indicating that a relation between metrics and ecosystem properties exists. LINTG was the main explanatory variable for woody rangelands with high leaf biomass, whereas for areas dominated by herbaceous vegetation, it was the PEAK metric. The proposed approach outperformed the established biomass NDVI-based product (MAE = 818 kg·DM/ha and R2 = 0.51 and should improve the operational monitoring of forage resources in Sahelian rangelands.

The Indigenous Phenology Network: Engage, Observe, and Adapt to Change

Science.gov (United States)

Miller, B. W.; Davíd-Chavez, D. M.; Elevitch, C.; Hamilton, A.; Hatfield, S. C.; Jones, K. D.; Rabin, R.; Rosemartin, A.; Souza, M. K.; Sparrow, E.

2017-12-01

The Indigenous Phenology Network (IPN) is a grassroots organization whose participants are interested in understanding changes to seasonality and timing of life cycle events, and forecasting impacts to lands and species of importance to native peoples. The group focuses on building relationships, ensuring benefit to indigenous communities, and integrating indigenous and western knowledge systems. The IPN's work is guided by the Relational Doctrine, a set of principles founded on the notion that all things are connected. This multimedia presentation and dialogue will bring together IPN members and their experiences in diverse communities and landscapes facing impacts from a changing climate and extreme weather events. Impacts on water supply, vegetation, wildlife, and living conditions, and ideas for minimizing and responding to the projected impacts of continued change will be discussed in the context of multi-generational, place-based traditional knowledge and community resilience. Scalable, community-based gardens, for example, provide a sustainable source of traditional, locally grown food, most valuable in times of disaster when supplies from the outside world are unavailable. Following the concept of Victory Gardens, the model of small-scale agroforestry (VICTree Gardens - Virtually Interconnected Community Tree Gardens), being implemented in Hawaii, has the potential to provide a diverse diet of food grown in very limited space. Gardens build resilience by connecting people with each other, with local food, and with nature. We envision community-based projects which will apply local, multi-generational knowledge to adapt the gardens to changing environments. Going forward, direct observation of garden conditions can be combined with satellite and ground-based measurements of environmental conditions, such as soil moisture, soil and air temperature, precipitation, and phenology, to further assess and manage these gardens in the context of the surrounding

Evaluating the hydrological consistency of satellite based water cycle components

KAUST Repository

Lopez Valencia, Oliver Miguel

2016-06-15

Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological

The European Phenology Network

NARCIS (Netherlands)

Vliet, van A.J.H.; Groot, de R.S.; Bellens, Y.; Braun, P.; Bruegger, R.; Bruns, E.; Clevers, J.G.P.W.; Estreguil, C.; Flechsig, M.; Jeanneret, F.; Maggi, M.; Martens, P.; Menne, B.; Menzel, A.; Sparks, T.

2003-01-01

The analysis of changes in the timing of life cycle-events of organisms (phenology) has been able to contribute significantly to the assessment of potential impacts of climate change on ecology. These phenological responses of species to changes in climate are likely to have significant relevance

Uncertainties and applications of satellite-derived coastal water quality products

Science.gov (United States)

Zheng, Guangming; DiGiacomo, Paul M.

2017-12-01

Recent and forthcoming launches of a plethora of ocean color radiometry sensors, coupled with increasingly adopted free and open data policies are expected to boost usage of satellite ocean color data and drive the demand to use these data in a quantitative and routine manner. Here we review factors that introduce uncertainties to various satellite-derived water quality products and recommend approaches to minimize the uncertainty of a specific product. We show that the regression relationships between remote-sensing reflectance and water turbidity (in terms of nephelometric units) established for different regions tend to converge and therefore it is plausible to develop a global satellite water turbidity product derived using a single algorithm. In contrast, solutions to derive suspended particulate matter concentration are much less generalizable; in one case it might be more accurate to estimate this parameter based on satellite-derived particulate backscattering coefficient, whereas in another the nonagal particulate absorption coefficient might be a better proxy. Regarding satellite-derived chlorophyll concentration, known to be subject to large uncertainties in coastal waters, studies summarized here clearly indicate that the accuracy of classical reflectance band-ratio algorithms depends largely on the contribution of phytoplankton to total light absorption coefficient as well as the degree of correlation between phytoplankton and the dominant nonalgal contributions. Our review also indicates that currently available satellite-derived water quality products are restricted to optically significant materials, whereas many users are interested in toxins, nutrients, pollutants, and pathogens. Presently, proxies or indicators for these constituents are inconsistently (and often incorrectly) developed and applied. Progress in this general direction will remain slow unless, (i) optical oceanographers and environmental scientists start collaborating more closely

Production process for advanced space satellite system cables/interconnects.

Energy Technology Data Exchange (ETDEWEB)

Mendoza, Luis A.

2007-12-01

This production process was generated for the satellite system program cables/interconnects group, which in essences had no well defined production process. The driver for the development of a formalized process was based on the set backs, problem areas, challenges, and need improvements faced from within the program at Sandia National Laboratories. In addition, the formal production process was developed from the Master's program of Engineering Management for New Mexico Institute of Mining and Technology in Socorro New Mexico and submitted as a thesis to meet the institute's graduating requirements.

Phenology prediction component of GypsES

Science.gov (United States)

Jesse A. Logan; Lukas P. Schaub; F. William Ravlin

1991-01-01

Prediction of phenology is an important component of most pest management programs, and considerable research effort has been expended toward development of predictive tools for gypsy moth phenology. Although phenological prediction is potentially valuable for timing of spray applications (e.g. Bt, or Gypcheck) and other management activities (e.g. placement and...

Pan European Phenological database (PEP725): a single point of access for European data

Science.gov (United States)

Templ, Barbara; Koch, Elisabeth; Bolmgren, Kjell; Ungersböck, Markus; Paul, Anita; Scheifinger, Helfried; Rutishauser, This; Busto, Montserrat; Chmielewski, Frank-M.; Hájková, Lenka; Hodzić, Sabina; Kaspar, Frank; Pietragalla, Barbara; Romero-Fresneda, Ramiro; Tolvanen, Anne; Vučetič, Višnja; Zimmermann, Kirsten; Zust, Ana

2018-02-01

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/. Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Pan European Phenological database (PEP725): a single point of access for European data

Science.gov (United States)

Templ, Barbara; Koch, Elisabeth; Bolmgren, Kjell; Ungersböck, Markus; Paul, Anita; Scheifinger, Helfried; Rutishauser, This; Busto, Montserrat; Chmielewski, Frank-M.; Hájková, Lenka; Hodzić, Sabina; Kaspar, Frank; Pietragalla, Barbara; Romero-Fresneda, Ramiro; Tolvanen, Anne; Vučetič, Višnja; Zimmermann, Kirsten; Zust, Ana

2018-06-01

The Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

Large-scale heterogeneity of Amazonian phenology revealed from 26-year long AVHRR/NDVI time-series

International Nuclear Information System (INIS)

Silva, Fabrício B; Shimabukuro, Yosio E; Aragão, Luiz E O C; Anderson, Liana O; Pereira, Gabriel; Cardozo, Franciele; Arai, Egídio

2013-01-01

Depiction of phenological cycles in tropical forests is critical for an understanding of seasonal patterns in carbon and water fluxes as well as the responses of vegetation to climate variations. However, the detection of clear spatially explicit phenological patterns across Amazonia has proven difficult using data from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this work, we propose an alternative approach based on a 26-year time-series of the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR) to identify regions with homogeneous phenological cycles in Amazonia. Specifically, we aim to use a pattern recognition technique, based on temporal signal processing concepts, to map Amazonian phenoregions and to compare the identified patterns with field-derived information. Our automated method recognized 26 phenoregions with unique intra-annual seasonality. This result highlights the fact that known vegetation types in Amazonia are not only structurally different but also phenologically distinct. Flushing of new leaves observed in the field is, in most cases, associated to a continuous increase in NDVI. The peak in leaf production is normally observed from the beginning to the middle of the wet season in 66% of the field sites analyzed. The phenoregion map presented in this work gives a new perspective on the dynamics of Amazonian canopies. It is clear that the phenology across Amazonia is more variable than previously detected using remote sensing data. An understanding of the implications of this spatial heterogeneity on the seasonality of Amazonian forest processes is a crucial step towards accurately quantifying the role of tropical forests within global biogeochemical cycles. (letter)

Tracking global change at local scales: Phenology for science, outreach, conservation

Science.gov (United States)

Sharron, Ed; Mitchell, Brian

2011-06-01

A Workshop Exploring the Use of Phenology Studies for Public Engagement; New Orleans, Louisiana, 14 March 2011 ; During a George Wright Society Conference session that was led by the USA National Phenology Network (USANPN; http://www.usanpn.org) and the National Park Service (NPS), professionals from government organizations, nonprofits, and higher-education institutions came together to explore the possibilities of using phenology monitoring to engage the public. One of the most visible effects of global change on ecosystems is shifts in phenology: the timing of biological events such as leafing and flowering, maturation of agricultural plants, emergence of insects, and migration of birds. These shifts are already occurring and reflect biological responses to climate change at local to regional scales. Changes in phenology have important implications for species ecology and resource management and, because they are place-based and tangible, serve as an ideal platform for education, outreach, and citizen science.

The role of spring and autumn phenological switches on spatiotemporal variation in temperate and boreal forest C balance: A FLUXNET synthesis

Science.gov (United States)

Richardson, A. D.; Reichstein, M.; Piao, S.; Ciais, P.; Luyssaert, S.; Stockli, R.; Friedl, M.; Gobron, N.; Fluxnet Site Pis, 21

2009-04-01

In temperate and boreal ecosystems, phenological transitions (particularly the timing of spring onset and autumn senescence) are thought to represent a major control on spatial and temporal variation in forest carbon sequestration. To investigate these patterns, we analyzed 153 site-years of data from the FLUXNET ‘La Thuile' database. Eddy covariance measurements of surface-atmosphere exchanges of carbon and water from 21 research sites at latitudes from 36°N to 67°N were used in the synthesis. We defined a range of phenological indicators based on the first (spring) and last (autumn) dates of (1) C source/sink transitions (‘carbon uptake period'); (2) measurable photosynthetic uptake (‘physiologically active period'); (3) relative thresholds for latent heat (evapotranspiration) flux; (4) phenological thresholds derived from a range of remote sensing products (JRC fAPAR, MOD12Q2, and the PROGNOSTIC model with MODIS data assimilation); and (5) a climatological metric based on the date where soil temperature equals mean annual air temperature. We then tested whether site-level flux anomalies were significantly correlated with phenological anomalies across these metrics, and whether the slopes of these relationships (representing the sensitivity to phenological variation) differed between deciduous broadleaf (DBF) and evergreen needleleaf (ENF) forests. Within sites, interannual variation in most phenological metrics was about 5-10 d, compared to 10-30 d across sites. Both spatial and temporal phenological variation were consistently larger at ENF, compared to DBF, sites. Averaged across metrics, phenological variability was roughly comparable in spring and autumn, both across (17 d) and within (9 d) sites. However, patterns of interannual variation in fluxes were less well explained by the derived phenological metrics than were patterns of spatial variation in fluxes. Also, the observed pattern strongly depended on the metric used, with flux-derived metrics

PHENOALP: a new project on phenology in the Western Alps

Science.gov (United States)

Cremonese, E.

2009-04-01

PHENOALP is a new EU co-funded Interreg Project under the operational programme for cross-border cooperation "Italy-France (Alps-ALCOTRA)" 2007 - 2013, aiming to get a better understanding of phenological changes in the Alps. The major goals of the project are: 1- The implementation of an observation network in the involved territories (i.e. the Aosta Valley and the Savoies in the Western Alps); 2- The definition of a common observation strategy and common protocols; 3- The involvement of local community members (e.g. through schools) in the observation activities as a way to increase the awareness on the issue of the effects of climate change. Project leader is the Environmental Protection Agency of Aosta Valley (ARPA Valle d'Aosta - IT) and the partners are the Research Center on High Altitude Ecosystem (CREA - FR), Mont Avic Regional Parc (IT), Bauges Massif Regional Natural Parc (FR) and the Protected Area Service of Aosta Valley (IT). Project activities are: 1. Pheno-plantes: definition of common observation protocols (e.g. field observation and webcams) of different alpine species (trees and herbaceous) and implementation of the observation network; analysis of the relations between climate and phenological events; application and evaluation of phenological models. 2. Pheno-detection: remote sensing of European larch and high elevation pastures with MODIS data; multitemporal analysis (2000-2011) of phenological variations in the Western Alps. 3. Pheno-flux: analysis of the relation between the seasonal and interannual variability of plant phenology and productivity, assessed measuring CO2 fluxes (eddy-covariance technique), radiometric indexes and phenological events at specific (European larch stand and alpine pastures) monitoring site. 4. Pheno-zoo: definition of common observation protocols for the phenology of animal taxa (birds, mammals, amphibians and insects) along altitudinal gradients; implementation of the observation network. 5. Inter

Investigations into the effect of automobile exhausts on the phenology, periodicity and productivity of some roadside trees

Directory of Open Access Journals (Sweden)

Ghulam Bhatti

2014-01-01

Full Text Available In response to a polluted atmosphere, the phenology of Ficus benyalensis and Eucalyptus sp. was highly affected. The yield of seeds and fruits of Gunincun officinale and Azadirachta indica was lessened at the polluted sites. The automobile emissions significantly reduced the productivity in G. officinale, F. bengalensis and Eucalyptus sp., whereas, A. indica was comparatively resistant to vehicle exhaust pollution. Leaf area and dry weight were significantly reduced in most of the plants.

The plant phenological online database (PPODB): an online database for long-term phenological data

Science.gov (United States)

Dierenbach, Jonas; Badeck, Franz-W.; Schaber, Jörg

2013-09-01

We present an online database that provides unrestricted and free access to over 16 million plant phenological observations from over 8,000 stations in Central Europe between the years 1880 and 2009. Unique features are (1) a flexible and unrestricted access to a full-fledged database, allowing for a wide range of individual queries and data retrieval, (2) historical data for Germany before 1951 ranging back to 1880, and (3) more than 480 curated long-term time series covering more than 100 years for individual phenological phases and plants combined over Natural Regions in Germany. Time series for single stations or Natural Regions can be accessed through a user-friendly graphical geo-referenced interface. The joint databases made available with the plant phenological database PPODB render accessible an important data source for further analyses of long-term changes in phenology. The database can be accessed via www.ppodb.de .

Hydrological Utility and Uncertainty of Multi-Satellite Precipitation Products in the Mountainous Region of South Korea

Directory of Open Access Journals (Sweden)

Jong Pil Kim

2016-07-01

Full Text Available Satellite-derived precipitation can be a potential source of forcing data for assessing water availability and managing water supply in mountainous regions of East Asia. This study investigates the hydrological utility of satellite-derived precipitation and uncertainties attributed to error propagation of satellite products in hydrological modeling. To this end, four satellite precipitation products (tropical rainfall measuring mission (TRMM multi-satellite precipitation analysis (TMPA version 6 (TMPAv6 and version 7 (TMPAv7, the global satellite mapping of precipitation (GSMaP, and the climate prediction center (CPC morphing technique (CMORPH were integrated into a physically-based hydrologic model for the mountainous region of South Korea. The satellite precipitation products displayed different levels of accuracy when compared to the intra- and inter-annual variations of ground-gauged precipitation. As compared to the GSMaP and CMORPH products, superior performances were seen when the TMPA products were used within streamflow simulations. Significant dry (negative biases in the GSMaP and CMORPH products led to large underestimates of streamflow during wet-summer seasons. Although the TMPA products displayed a good level of performance for hydrologic modeling, there were some over/underestimates of precipitation by satellites during the winter season that were induced by snow accumulation and snowmelt processes. These differences resulted in streamflow simulation uncertainties during the winter and spring seasons. This study highlights the crucial need to understand hydrological uncertainties from satellite-derived precipitation for improved water resource management and planning in mountainous basins. Furthermore, it is suggested that a reliable snowfall detection algorithm is necessary for the new global precipitation measurement (GPM mission.

14 CFR 141.91 - Satellite bases.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Satellite bases. 141.91 Section 141.91... OTHER CERTIFICATED AGENCIES PILOT SCHOOLS Operating Rules § 141.91 Satellite bases. The holder of a... assistant chief instructor is designated for each satellite base, and that assistant chief instructor is...

Evaluating Gridded Spring Indices Using the USA National Phenology Network's Observational Phenology Data

Science.gov (United States)

Crimmins, T. M.; Gerst, K.

2017-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) produces and freely delivers daily and short-term forecast maps of spring onset dates at fine spatial scale for the conterminous United States and Alaska using the Spring Indices. These models, which represent the start of biological activity in the spring season, were developed using a long-term observational record of four species of lilacs and honeysuckles contributed by volunteer observers. Three of the four species continue to be tracked through the USA-NPN's phenology observation program, Nature's Notebook. The gridded Spring Index maps have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, anticipating allergy outbreaks and planning agricultural harvest dates. However, to date, there has not been a comprehensive assessment of how well the gridded Spring Index maps accurately reflect phenological activity in lilacs and honeysuckles or other species of plants. In this study, we used observational plant phenology data maintained by the USA-NPN to evaluate how well the gridded Spring Index maps match leaf and flowering onset dates in a) the lilac and honeysuckle species used to construct the models and b) in several species of deciduous trees. The Spring Index performed strongly at predicting the timing of leaf-out and flowering in lilacs and honeysuckles. The average error between predicted and observed date of onset ranged from 5.9 to 11.4 days. Flowering models performed slightly better than leaf-out models. The degree to which the Spring Indices predicted native deciduous tree leaf and flower phenology varied by year, species, and region. Generally, the models were better predictors of leaf and flowering onset dates in the Northeastern and Midwestern US. These results reveal when and where the Spring Indices are a meaningful proxy of phenological activity across the United States.

Recent lake ice-out phenology within and among lake districts of Alaska, U.S.A.

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Arp, Christopher D.; Jones, Benjamin M.; Grosse, Guido

2013-01-01

The timing of ice-out in high latitudes is a fundamental threshold for lake ecosystems and an indicator of climate change. In lake-rich regions, the loss of ice cover also plays a key role in landscape and climatic processes. Thus, there is a need to understand lake ice phenology at multiple scales. In this study, we observed ice-out timing on 55 large lakes in 11 lake districts across Alaska from 2007 to 2012 using satellite imagery. Sensor networks in two lake districts validated satellite observations and provided comparison with smaller lakes. Over this 6 yr period, the mean lake ice-out for all lakes was 27 May and ranged from 07 May in Kenai to 06 July in Arctic Coastal Plain lake districts with relatively low inter-annual variability. Approximately 80% of the variation in ice-out timing was explained by the date of 0°C air temperature isotherm and lake area. Shoreline irregularity, watershed area, and river connectivity explained additional variation in some districts. Coherence in ice-out timing within the lakes of each district was consistently strong over this 6 yr period, ranging from r-values of 0.5 to 0.9. Inter-district analysis of coherence also showed synchronous ice-out patterns with the exception of the two arctic coastal districts where ice-out occurs later (June–July) and climatology is sea-ice influenced. These patterns of lake ice phenology provide a spatially extensive baseline describing short-term temporal variability, which will help decipher longer term trends in ice phenology and aid in representing the role of lake ice in land and climate models in northern landscapes.

Toward a U.S. National Phenological Assessment

Science.gov (United States)

Henebry, Geoffrey M.; Betancourt, Julio L.

2010-01-01

Third USA National Phenology Network (USA-NPN) and Research Coordination Network (RCN) Annual Meeting; Milwaukee, Wisconsin, 5-9 October 2009; Directional climate change will have profound and lasting effects throughout society that are best understood through fundamental physical and biological processes. One such process is phenology: how the timing of recurring biological events is affected by biotic and abiotic forces. Phenology is an early and integrative indicator of climate change readily understood by nonspecialists. Phenology affects the planting, maturation, and harvesting of food and fiber; pollination; timing and magnitude of allergies and disease; recreation and tourism; water quantity and quality; and ecosystem function and resilience. Thus, phenology is the gateway to climatic effects on both managed and unmanaged ecosystems. Adaptation to climatic variability and change will require integration of phenological data and models with climatic forecasts at seasonal to decadal time scales. Changes in phenologies have already manifested myriad effects of directional climate change. As these changes continue, it is critical to establish a comprehensive suite of benchmarks that can be tracked and mapped at local to continental scales with observations and climate models.

ASSESSMENT OF SATELLITE PRECIPITATION PRODUCTS IN THE PHILIPPINE ARCHIPELAGO

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M. D. Ramos

2016-06-01

Full Text Available Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1 the Tropical Rainfall Measuring Mission (TRMM, (2 the CPC Morphing technique (CMORPH of NOAA and (3 the Global Satellite Mapping of Precipitation (GSMAP and (4 Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN. Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE and Root Mean Square Error (RMSE. In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

Assessment of Satellite Precipitation Products in the Philippine Archipelago

Science.gov (United States)

Ramos, M. D.; Tendencia, E.; Espana, K.; Sabido, J.; Bagtasa, G.

2016-06-01

Precipitation is the most important weather parameter in the Philippines. Made up of more than 7100 islands, the Philippine archipelago is an agricultural country that depends on rain-fed crops. Located in the western rim of the North West Pacific Ocean, this tropical island country is very vulnerable to tropical cyclones that lead to severe flooding events. Recently, satellite-based precipitation estimates have improved significantly and can serve as alternatives to ground-based observations. These data can be used to fill data gaps not only for climatic studies, but can also be utilized for disaster risk reduction and management activities. This study characterized the statistical errors of daily precipitation from four satellite-based rainfall products from (1) the Tropical Rainfall Measuring Mission (TRMM), (2) the CPC Morphing technique (CMORPH) of NOAA and (3) the Global Satellite Mapping of Precipitation (GSMAP) and (4) Precipitation Estimation from Remotely Sensed information using Artificial Neural Networks (PERSIANN). Precipitation data were compared to 52 synoptic weather stations located all over the Philippines. Results show GSMAP to have over all lower bias and CMORPH with lowest Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, a dichotomous rainfall test reveals GSMAP and CMORPH have low Proportion Correct (PC) for convective and stratiform rainclouds, respectively. TRMM consistently showed high PC for almost all raincloud types. Moreover, all four satellite precipitation showed high Correct Negatives (CN) values for the north-western part of the country during the North-East monsoon and spring monsoonal transition periods.

Intensity of heat stress in winter wheat—phenology compensates for the adverse effect of global warming

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Eyshi Rezaei, Ehsan; Siebert, Stefan; Ewert, Frank

2015-02-01

Higher temperatures during the growing season are likely to reduce crop yields with implications for crop production and food security. The negative impact of heat stress has also been predicted to increase even further for cereals such as wheat under climate change. Previous empirical modeling studies have focused on the magnitude and frequency of extreme events during the growth period but did not consider the effect of higher temperature on crop phenology. Based on an extensive set of climate and phenology observations for Germany and period 1951-2009, interpolated to 1 × 1 km resolution and provided as supplementary data to this article (available at stacks.iop.org/ERL/10/024012/mmedia), we demonstrate a strong relationship between the mean temperature in spring and the day of heading (DOH) of winter wheat. We show that the cooling effect due to the 14 days earlier DOH almost fully compensates for the adverse effect of global warming on frequency and magnitude of crop heat stress. Earlier heading caused by the warmer spring period can prevent exposure to extreme heat events around anthesis, which is the most sensitive growth stage to heat stress. Consequently, the intensity of heat stress around anthesis in winter crops cultivated in Germany may not increase under climate change even if the number and duration of extreme heat waves increase. However, this does not mean that global warning would not harm crop production because of other impacts, e.g. shortening of the grain filling period. Based on the trends for the last 34 years in Germany, heat stress (stress thermal time) around anthesis would be 59% higher in year 2009 if the effect of high temperatures on accelerating wheat phenology were ignored. We conclude that climate impact assessments need to consider both the effect of high temperature on grain set at anthesis but also on crop phenology.

Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

Science.gov (United States)

Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

A study on land surface phenology in eastern China based on SPOT/VGT datasets

International Nuclear Information System (INIS)

Han, Guifeng; Xie, Hongxia

2014-01-01

Vegetation phenology provides a relevant indicator of the response of terrestrial ecosystems to climate change. In this study, vegetation phenology measurements were extracted and the spatial distributions were investigated using time series SPOT/VGT NDVI datasets for eastern China. Four phenology measurements were analyzed: the start of the growing season (SOS), the end of the growing season (EOS), the length of the growing season (GSL) and the time of the peak NDVI. The SOS in the northern part of the study area occurred earlier than in the rest of the study area due to larger amounts of cropland. The EOS showed a strong latitudinal pattern, especially in the southern portion of the study area. The GSL also showed a clear spatial pattern along the latitudinal gradient from north to south. The time of peak NDVI did not show a spatial pattern along the latitudinal gradient, which is likely due to the influence of vegetation types and the types of farming systems. In addition, there were no significant correlations between longitude and the four phenology measurements. SOS does not correlate with latitude, longitude or altitude, but EOS, GSL and the time of peak NDVI all correlated with latitude and altitude

Influence of spring and autumn phenological transitions on forest ecosystem productivit

NARCIS (Netherlands)

Richardson, A.D.; Black, T.A.; Ciais, P.; Delbart, N.; Moors, E.J.

2010-01-01

We use eddy covariance measurements of net ecosystem productivity (NEP) from 21 FLUXNET sites (153 site-years of data) to investigate relationships between phenology and productivity (in terms of both NEP and gross ecosystem photosynthesis, GEP) in temperate and boreal forests. Results are used to

Variability and climate change trend in vegetation phenology of recent decades in the Greater Khingan Mountain area, Northeastern China

Directory of Open Access Journals (Sweden)

Huan Tang

2015-09-01

Full Text Available Vegetation phenology has been used in studies as an indicator of an ecosystem’s responses to climate change. Satellite remote sensing techniques can capture changes in vegetation greenness, which can be used to estimate vegetation phenology. In this study, a long-term vegetation phenology study of the Greater Khingan Mountain area in Northeastern China was performed by using the Global Inventory Modeling and Mapping Studies (GIMMS normalized difference vegetation index version 3 (NDVI3g dataset from the years 1982–2012. After reconstructing the NDVI time series, the start date of the growing season (SOS, the end date of the growing season (EOS and the length of the growing season (LOS were extracted using a dynamic threshold method. The response of the variation in phenology with climatic factors was also analyzed. The results showed that the phenology in the study area changed significantly in the three decades between 1982 and 2012, including a 12.1-day increase in the entire region’s average LOS, a 3.3-day advance in the SOS and an 8.8-day delay in the EOS. However, differences existed between the steppe, forest and agricultural regions, with the LOSs of the steppe region, forest region and agricultural region increasing by 4.40 days, 10.42 days and 1.71 days, respectively, and a later EOS seemed to more strongly affect the extension of the growing season. Additionally, temperature and precipitation were closely correlated with the phenology variations. This study provides a useful understanding of the recent change in phenology and its variability in this high-latitude study area, and this study also details the responses of several ecosystems to climate change.

A meta-analysis of cambium phenology and growth: linear and non-linear patterns in conifers of the northern hemisphere.

Science.gov (United States)

Rossi, Sergio; Anfodillo, Tommaso; Cufar, Katarina; Cuny, Henri E; Deslauriers, Annie; Fonti, Patrick; Frank, David; Gricar, Jozica; Gruber, Andreas; King, Gregory M; Krause, Cornelia; Morin, Hubert; Oberhuber, Walter; Prislan, Peter; Rathgeber, Cyrille B K

2013-12-01

Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-linear patterns according to limiting factors that generate shifts and discontinuities, or contain thresholds beyond which responses change abruptly. This study investigates to what extent cambium phenology is associated with xylem growth and differentiation across conifer species of the northern hemisphere. Xylem cell production is compared with the periods of cambial activity and cell differentiation assessed on a weekly time scale on histological sections of cambium and wood tissue collected from the stems of nine species in Canada and Europe over 1-9 years per site from 1998 to 2011. The dynamics of xylogenesis were surprisingly homogeneous among conifer species, although dispersions from the average were obviously observed. Within the range analysed, the relationships between the phenological timings were linear, with several slopes showing values close to or not statistically different from 1. The relationships between the phenological timings and cell production were distinctly non-linear, and involved an exponential pattern. The trees adjust their phenological timings according to linear patterns. Thus, shifts of one phenological phase are associated with synchronous and comparable shifts of the successive phases. However, small increases in the duration of xylogenesis could correspond to a substantial increase in cell production. The findings suggest that the length of the growing season and the resulting amount of growth could respond differently to changes in environmental conditions.

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

Science.gov (United States)

Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.

2011-01-01

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

International Nuclear Information System (INIS)

Boresjoe Bronge, Laine

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

Energy Technology Data Exchange (ETDEWEB)

Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

Estimating Next Primary Productivity using Satellite and Ancillary Data

Science.gov (United States)

Choudhury, B. J.

The net primary productivity (C) or annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of the rate of gross photosynthesis (Ag) and autotrophic respiration (R) per unit ground area. Although available observations show that R is a large and variable fraction of Ag, viz., 0.3 to 0.7, it is generally recognized that much uncertainties exist in this fraction due to difficulties associated with the needed measurements. Additional uncertainties arise when these measurements are extrapolated to regional or global land surface using empirical equations, for example, using regression equations relating C to mean annual precipitation and air temperature. Here, a process- based approach has been taken to calculate Ag and R using satellite and ancillary data. Ag has been expressed as a product of radiation use efficiency, magnitude of intercepted photosynthetically active radiation (PAR), and normalized by stresses due to soil water shortage and air temperature away from the optimum range. A biophysical model has been used to determine the radiation use efficiency from the maximum rate of carbon assimilation by a leaf, foliage temperature, and the fraction of diffuse PAR incident on a canopy. All meteorological data (PAR, air temperature, precipitation, etc.) needed for the calculation are derived from satellite observations, while a land use, land cover data (based on satellite and ground measurements) have been used to assess the maximum rate of carbon assimilation by a leaf of varied cover type based on field measurements. R has been calculated as the sum of maintenance and growth components. The maintenance respiration of foliage and live fine roots at a standard temperature of different land cover has been determined from their nitrogen content using field and satellite measurements, while that of living fraction of woody stem (viz., sapwood) from the seasonal maximum leaf area index as determined from satellite

How to Get Data from NOAA Environmental Satellites: An Overview of Operations, Products, Access and Archive

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Donoho, N.; Graumann, A.; McNamara, D. P.

2015-12-01

In this presentation we will highlight access and availability of NOAA satellite data for near real time (NRT) and retrospective product users. The presentation includes an overview of the current fleet of NOAA satellites and methods of data distribution and access to hundreds of imagery and products offered by the Environmental Satellite Processing Center (ESPC) and the Comprehensive Large Array-data Stewardship System (CLASS). In particular, emphasis on the various levels of services for current and past observations will be presented. The National Environmental Satellite, Data, and Information Service (NESDIS) is dedicated to providing timely access to global environmental data from satellites and other sources. In special cases, users are authorized direct access to NESDIS data distribution systems for environmental satellite data and products. Other means of access include publicly available distribution services such as the Global Telecommunication System (GTS), NOAA satellite direct broadcast services and various NOAA websites and ftp servers, including CLASS. CLASS is NOAA's information technology system designed to support long-term, secure preservation and standards-based access to environmental data collections and information. The National Centers for Environmental Information (NCEI) is responsible for the ingest, quality control, stewardship, archival and access to data and science information. This work will also show the latest technology improvements, enterprise approach and future plans for distribution of exponentially increasing data volumes from future NOAA missions. A primer on access to NOAA operational satellite products and services is available at http://www.ospo.noaa.gov/Organization/About/access.html. Access to post-operational satellite data and assorted products is available at http://www.class.noaa.gov

Herbarium records are reliable sources of phenological change driven by climate and provide novel insights into species' phenological cueing mechanisms.

Science.gov (United States)

Davis, Charles C; Willis, Charles G; Connolly, Bryan; Kelly, Courtland; Ellison, Aaron M

2015-10-01

Climate change has resulted in major changes in the phenology of some species but not others. Long-term field observational records provide the best assessment of these changes, but geographic and taxonomic biases limit their utility. Plant specimens in herbaria have been hypothesized to provide a wealth of additional data for studying phenological responses to climatic change. However, no study to our knowledge has comprehensively addressed whether herbarium data are accurate measures of phenological response and thus applicable to addressing such questions. We compared flowering phenology determined from field observations (years 1852-1858, 1875, 1878-1908, 2003-2006, 2011-2013) and herbarium records (1852-2013) of 20 species from New England, United States. Earliest flowering date estimated from herbarium records faithfully reflected field observations of first flowering date and substantially increased the sampling range across climatic conditions. Additionally, although most species demonstrated a response to interannual temperature variation, long-term temporal changes in phenological response were not detectable. Our findings support the use of herbarium records for understanding plant phenological responses to changes in temperature, and also importantly establish a new use of herbarium collections: inferring primary phenological cueing mechanisms of individual species (e.g., temperature, winter chilling, photoperiod). These latter data are lacking from most investigations of phenological change, but are vital for understanding differential responses of individual species to ongoing climate change. © 2015 Botanical Society of America.

Community patterns of tropical tree phenology derived from Unmanned Aerial Vehicle images: intra- and interspecific variation, association with species plant traits, and response to interannual climate variation

Science.gov (United States)

Bohlman, Stephanie; Rifai, Sami; Park, John; Dandois, Jonathan; Muller-Landau, Helene

2017-04-01

Phenology is a key life history trait of plant species and critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical forest phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns, which makes it difficult to collect sufficient ground-based field data to characterize individual tropical tree species phenologies. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. The objective of this study is to quantify inter- and intra-specific responses of tropical tree leaf phenology to environmental variation over large spatial scales and identify key environmental variables and physiological mechanisms underpinning phenological variation. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. UAV imagery was corrected for exposure, orthorectified, and then processed to extract spectral, texture, and image information for individual tree crowns, which was then used as inputs for a machine learning algorithm that successfully predicted the percentages of leaf, branch, and flower cover for each tree crown (r2=0.76 between observed and predicted percent branch cover for individual tree crowns). We then quantified cumulative annual deciduousness for each crown by fitting a non-parametric curve of flexible shape to its predicted percent branch time series and calculated the area under the curve. We obtained the species

Ecosystem Responses To Plant Phenology Across Scales And Trophic Levels

Science.gov (United States)

Stoner, D.; Sexton, J. O.; Nagol, J. R.; Ironside, K.; Choate, D.; Longshore, K.; Edwards, T., Jr.

2015-12-01

Plant phenology in arid and semi-arid ecoregions is constrained by water availability and governs the life history characteristics of primary and secondary consumers. We related the behavior, demography, and distribution of mammalian herbivores and their principal predator to remotely sensed vegetation and climatological indices across the western United States for the period 2000-2014. Across scales, terrain and topographic position moderates the effects of climatological drought on primary productivity, resulting in differential susceptibility among plant functional types to water stress. At broad scales, herbivores tie parturition to moist sites during the period of maximum increase in local forage production. Consequently, juvenile mortality is highest in regions of extreme phenological variability. Although decoupled from primary production by one or more trophic levels, carnivore home range size and density is negatively correlated to plant productivity and growing season length. At the finest scales, predation influences the behavior of herbivore prey through compromised habitat selection, in which maternal females trade nutritional benefits of high plant biomass for reduced mortality risk associated with increased visibility. Climate projections for the western United States predict warming combined with shifts in the timing and form of precipitation. Our analyses suggest that these changes will propagate through trophic levels as increased phenological variability and shifts in plant distributions, larger consumer home ranges, altered migration behavior, and generally higher volatility in wildlife populations. Combined with expansion and intensification of human land use across the region, these changes will likely have economic implications stemming from increased human-wildlife conflict (e.g., crop damage, vehicle collisions) and changes in wildlife-related tourism.

PEP725 Pan European Phenological Database

Science.gov (United States)

Koch, E.; Adler, S.; Lipa, W.; Ungersböck, M.; Zach-Hermann, S.

2010-09-01

Europe is in the fortunate situation that it has a long tradition in phenological networking: the history of collecting phenological data and using them in climatology has its starting point in 1751 when Carl von Linné outlined in his work Philosophia Botanica methods for compiling annual plant calendars of leaf opening, flowering, fruiting and leaf fall together with climatological observations "so as to show how areas differ". Recently in most European countries, phenological observations have been carried out routinely for more than 50 years by different governmental and non governmental organisations and following different observation guidelines, the data stored at different places in different formats. This has been really hampering pan European studies as one has to address many network operators to get access to the data before one can start to bring them in a uniform style. From 2004 to 2009 the COST-action 725 established a European wide data set of phenological observations. But the deliverables of this COST action was not only the common phenological database and common observation guidelines - COST725 helped to trigger a revival of some old networks and to establish new ones as for instance in Sweden. At the end of 2009 the COST action the database comprised about 8 million data in total from 15 European countries plus the data from the International Phenological Gardens IPG. In January 2010 PEP725 began its work as follow up project with funding from EUMETNET the network of European meteorological services and of ZAMG the Austrian national meteorological service. PEP725 not only will take over the part of maintaining, updating the COST725 database, but also to bring in phenological data from the time before 1951, developing better quality checking procedures and ensuring an open access to the database. An attractive webpage will make phenology and climate impacts on vegetation more visible in the public enabling a monitoring of vegetation development.

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

Science.gov (United States)

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology.

Science.gov (United States)

Jepsen, Jane U; Hagen, Snorre B; Karlsen, Stein-Rune; Ims, Rolf A

2009-12-07

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000-2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks.

Phenology of the reproductive development of Elaeis oleifera (Kunth Cortes

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Leidy Paola Moreno

2015-04-01

Full Text Available The phenological stages of oil palm can be coded using the BBCH scale, which has three digits due to the inclusion of intermediate stages between the principal and secondary stages in order to provide greater detail on each developmental stage. For the phenological description of the reproductive development of Elaeis oleifera, the principal stages used were emergence of inflorescence, flowering, fruit growth and development, and fruit ripening. The observations were made in Colombia over a 12 month-period on E. oleifera palms planted in 1991; the observations were made on the daily course or depending on the development stage. The duration of each phenological stage was measured in days. Thus, the appearance of new leaves took 20.1±2.8 days, reaching preanthesis I (601 took 145.09±19.61 days, from this stage to preanthesis II (602 took 7.50±1.50 days, then to preanthesis III (603 took 7.39±1.56 days and finally to anthesis (607 took 5.74±1.32 days. At the population level, it was found that the phenology cycle of inflorescence is annual and that the production of flowers and the opening of inflorescences with pistils is asynchronous.

Declining effect of warm temperature on spring phenology of tree species at low elevation in the Alps

Science.gov (United States)

Asse, Daphné; Randin, Christophe; Chuine, Isabelle

2017-04-01

Mountain regions are particularly exposed to climate change and temperature. In the Alps increased twice faster than in the northern hemisphere during the 20th century. As an immediate response, spring phenological phases of plant species such as budburst and flowering, have tended to occur earlier. In 2004, the CREA (Centre de Recherches sur les Ecosystèmes d'Altitude, Chamonix, France) initiated the citizen science program Phenoclim, which aims at assessing the long-term effects of climate changes on plant phenology over the entire French Alps. Sixty sites with phenological observations were equipped with temperature stations across a large elevational gradient. Here we used phenological records for five tree species (birch, ash, hazel, spruce and larch) combined with measurements or projections of temperature. We first tested the effects of geographic and topo-climatic factors on the timing of spring phenological phases. We then tested the hypothesis that a lack of chilling temperature during winter delayed dormancy release and subsequently spring phenological phases. Our data are currently being used to calibrate process-based phenological models to test to which extent soil temperature and photoperiod affect the timing of spring phenological phases. We found that growing degree-days was the best predictor of the timing of spring phenological phases, with a significant contribution of chilling. Our results also suggest that spring phenological phases were consistently delayed at low elevation by a lack of chilling in fall during warm years for the three deciduous species. Key words: Spring phenology, elevation gradients, citizen science, empirical and process-based modeling

Long-term shifts in the phenology of rare and endemic Rocky Mountain plants.

Science.gov (United States)

Munson, Seth M; Sher, Anna A

2015-08-01

• Mountainous regions support high plant productivity, diversity, and endemism, yet are highly vulnerable to climate change. Historical records and model predictions show increasing temperatures across high elevation regions including the Southern Rocky Mountains, which can have a strong influence on the performance and distribution of montane plant species. Rare plant species can be particularly vulnerable to climate change because of their limited abundance and distribution.• We tracked the phenology of rare and endemic species, which are identified as imperiled, across three different habitat types with herbarium records to determine if flowering time has changed over the last century, and if phenological change was related to shifts in climate.• We found that the flowering date of rare species has accelerated 3.1 d every decade (42 d total) since the late 1800s, with plants in sagebrush interbasins showing the strongest accelerations in phenology. High winter temperatures were associated with the acceleration of phenology in low elevation sagebrush and barren river habitats, whereas high spring temperatures explained accelerated phenology in the high elevation alpine habitat. In contrast, high spring temperatures delayed the phenology of plant species in the two low-elevation habitats and precipitation had mixed effects depending on the season.• These results provide evidence for large shifts in the phenology of rare Rocky Mountain plants related to climate, which can have strong effects on plant fitness, the abundance of associated wildlife, and the future of plant conservation in mountainous regions. © 2015 Botanical Society of America, Inc.

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

Science.gov (United States)

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

OpenAIRE

Ayehu, Getachew Tesfaye; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-01-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through...

Phenological Records

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Phenology is the scientific study of periodic biological phenomena, such as flowering, breeding, and migration, in relation to climatic conditions. The few records...

Improving the Regional Applicability of Satellite Precipitation Products by Ensemble Algorithm

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Waseem Muhammad

2018-04-01

Full Text Available Satellite-based precipitation products (e.g., Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG and its predecessor, Tropical Rainfall Measuring Mission (TRMM are a critical source of precipitation estimation, particularly for a region with less, or no, hydrometric networking. However, the inconsistency in the performance of these products has been observed in different climatic and topographic diverse regions, timescales, and precipitation intensities and there is still room for improvement. Hence, using a projected ensemble algorithm, the regional precipitation estimate (RP is introduced here. The RP concept is mainly based on the regional performance weights derived from the Mean Square Error (MSE and the precipitation estimate from the TRMM product, that is, TRMM 3B42 (TR, real-time (late (IT and the research (post-real-time (IR products of IMERG. The overall results of the selected contingency table (e.g., Probability of detection (POD and statistical indices (e.g., Correlation Coefficient (CC signposted that the proposed RP product has shown an overall better potential to capture the gauge observations compared with the TR, IR, and IT in five different climatic regions of Pakistan from January 2015 to December 2016, at a diurnal time scale. The current study could be the first research providing preliminary feedback from Pakistan for global precipitation measurement researchers by highlighting the need for refinement in the IMERG.

Automated mapping of soybean and corn using phenology

Science.gov (United States)

Zhong, Liheng; Hu, Lina; Yu, Le; Gong, Peng; Biging, Gregory S.

2016-09-01

For the two of the most important agricultural commodities, soybean and corn, remote sensing plays a substantial role in delivering timely information on the crop area for economic, environmental and policy studies. Traditional long-term mapping of soybean and corn is challenging as a result of the high cost of repeated training data collection, the inconsistency in image process and interpretation, and the difficulty of handling the inter-annual variability of weather and crop progress. In this study, we developed an automated approach to map soybean and corn in the state of Paraná, Brazil for crop years 2010-2015. The core of the approach is a decision tree classifier with rules manually built based on expert interaction for repeated use. The automated approach is advantageous for its capacity of multi-year mapping without the need to re-train or re-calibrate the classifier. Time series MODerate-resolution Imaging Spectroradiometer (MODIS) reflectance product (MCD43A4) were employed to derive vegetation phenology to identify soybean and corn based on crop calendar. To deal with the phenological similarity between soybean and corn, the surface reflectance of the shortwave infrared band scaled to a phenological stage was used to fully separate the two crops. Results suggested that the mapped areas of soybean and corn agreed with official statistics at the municipal level. The resultant map in the crop year 2012 was evaluated using an independent reference data set, and the overall accuracy and Kappa coefficient were 87.2% and 0.804 respectively. As a result of mixed pixel effect at the 500 m resolution, classification results were biased depending on topography. In the flat, broad and highly-cropped areas, uncultivated lands were likely to be identified as soybean or corn, causing over-estimation of cropland area. By contrast, scattered crop fields in mountainous regions with dense natural vegetation tend to be overlooked. For future mapping efforts, it has great

IR-BASED SATELLITE PRODUCTS FOR THE MONITORING OF ATMOSPHERIC WATER VAPOR OVER THE BLACK SEA

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VELEA LILIANA

2016-03-01

Full Text Available The amount of precipitable water (TPW in the atmospheric column is one of the important information used weather forecasting. Some of the studies involving the use of TPW relate to issues like lightning warning system in airports, tornadic events, data assimilation in numerical weather prediction models for short-range forecast, TPW associated with intense rain episodes. Most of the available studies on TPW focus on properties and products at global scale, with the drawback that regional characteristics – due to local processes acting as modulating factors - may be lost. For the Black Sea area, studies on the climatological features of atmospheric moisture are available from sparse or not readily available observational databases or from global reanalysis. These studies show that, although a basin of relatively small dimensions, the Black Sea presents features that may significantly impact on the atmospheric circulation and its general characteristics. Satellite observations provide new opportunities for extending the knowledge on this area and for monitoring atmospheric properties at various scales. In particular, observations in infrared (IR spectrum are suitable for studies on small-scale basins, due to the finer spatial sampling and reliable information in the coastal areas. As a first step toward the characterization of atmospheric moisture over the Black Sea from satellite-based information, we investigate three datasets of IR-based products which contain information on the total amount of moisture and on its vertical distribution, available in the area of interest. The aim is to provide a comparison of these data with regard to main climatological features of moisture in this area and to highlight particular strengths and limits of each of them, which may be helpful in the choice of the most suitable dataset for a certain application.

Phenological Changes in the Southern Hemisphere

Science.gov (United States)

Chambers, Lynda E.; Altwegg, Res; Barbraud, Christophe; Barnard, Phoebe; Beaumont, Linda J.; Crawford, Robert J. M.; Durant, Joel M.; Hughes, Lesley; Keatley, Marie R.; Low, Matt; Morellato, Patricia C.; Poloczanska, Elvira S.; Ruoppolo, Valeria; Vanstreels, Ralph E. T.; Woehler, Eric J.; Wolfaardt, Anton C.

2013-01-01

Current evidence of phenological responses to recent climate change is substantially biased towards northern hemisphere temperate regions. Given regional differences in climate change, shifts in phenology will not be uniform across the globe, and conclusions drawn from temperate systems in the northern hemisphere might not be applicable to other regions on the planet. We conduct the largest meta-analysis to date of phenological drivers and trends among southern hemisphere species, assessing 1208 long-term datasets from 89 studies on 347 species. Data were mostly from Australasia (Australia and New Zealand), South America and the Antarctic/subantarctic, and focused primarily on plants and birds. This meta-analysis shows an advance in the timing of spring events (with a strong Australian data bias), although substantial differences in trends were apparent among taxonomic groups and regions. When only statistically significant trends were considered, 82% of terrestrial datasets and 42% of marine datasets demonstrated an advance in phenology. Temperature was most frequently identified as the primary driver of phenological changes; however, in many studies it was the only climate variable considered. When precipitation was examined, it often played a key role but, in contrast with temperature, the direction of phenological shifts in response to precipitation variation was difficult to predict a priori. We discuss how phenological information can inform the adaptive capacity of species, their resilience, and constraints on autonomous adaptation. We also highlight serious weaknesses in past and current data collection and analyses at large regional scales (with very few studies in the tropics or from Africa) and dramatic taxonomic biases. If accurate predictions regarding the general effects of climate change on the biology of organisms are to be made, data collection policies focussing on targeting data-deficient regions and taxa need to be financially and logistically

Phenological changes in the southern hemisphere.

Directory of Open Access Journals (Sweden)

Lynda E Chambers

Full Text Available Current evidence of phenological responses to recent climate change is substantially biased towards northern hemisphere temperate regions. Given regional differences in climate change, shifts in phenology will not be uniform across the globe, and conclusions drawn from temperate systems in the northern hemisphere might not be applicable to other regions on the planet. We conduct the largest meta-analysis to date of phenological drivers and trends among southern hemisphere species, assessing 1208 long-term datasets from 89 studies on 347 species. Data were mostly from Australasia (Australia and New Zealand, South America and the Antarctic/subantarctic, and focused primarily on plants and birds. This meta-analysis shows an advance in the timing of spring events (with a strong Australian data bias, although substantial differences in trends were apparent among taxonomic groups and regions. When only statistically significant trends were considered, 82% of terrestrial datasets and 42% of marine datasets demonstrated an advance in phenology. Temperature was most frequently identified as the primary driver of phenological changes; however, in many studies it was the only climate variable considered. When precipitation was examined, it often played a key role but, in contrast with temperature, the direction of phenological shifts in response to precipitation variation was difficult to predict a priori. We discuss how phenological information can inform the adaptive capacity of species, their resilience, and constraints on autonomous adaptation. We also highlight serious weaknesses in past and current data collection and analyses at large regional scales (with very few studies in the tropics or from Africa and dramatic taxonomic biases. If accurate predictions regarding the general effects of climate change on the biology of organisms are to be made, data collection policies focussing on targeting data-deficient regions and taxa need to be financially

Impact of climate change on the timing of strawberry phenological processes in the Baltic States

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Līga Bethere

2016-02-01

Full Text Available Climate change has been shown to impact aspects of agriculture and phenology. This study aims to quantify changes in the timing of garden strawberry blooms and harvests in the Baltic States using Regional Climate Models (RCMs. First, parameters for a strawberry phenology model based on the growing degree day (GDD methodology were determined. Growing degree days were calculated using a modified sine wave method that estimates the diurnal temperature cycle from the daily maximum and minimum temperature. Model parameters include the base temperature and the required cumulative GDD sum, estimated from phenological and meteorological observations in Latvia for the years 2010–2013 via iterative calibration. Then an ensemble of bias-corrected RCM results (ENSEMBLES project was used as input to the phenological model to estimate the timing of strawberry phenological processes for the years 1951–2099. The results clearly show that strawberry phenological processes can be expected to occur earlier in the future, with a significant change in regional patterns. Differences between coastal and inland regions are expected to decrease over time. The uncertainty of the results was estimated using the RCM ensemble spread, with northern coastal locations showing the largest spread.

Coral Bleaching Products - Office of Satellite and Product Operations

Science.gov (United States)

satellite remotely sensed global sea surface temperature (SST) measurements and derived indices of coral HotSpots, Degree Heating Weeks, Time Series, SST Contour Charts, Ocean Surface Winds, and On-site Buoys as the product, are derived from Coral Bleaching HotSpots and Degree Heating Weeks (DHW) values measured

Automated processing of webcam images for phenological classification.

Science.gov (United States)

Bothmann, Ludwig; Menzel, Annette; Menze, Bjoern H; Schunk, Christian; Kauermann, Göran

2017-01-01

Along with the global climate change, there is an increasing interest for its effect on phenological patterns such as start and end of the growing season. Scientific digital webcams are used for this purpose taking every day one or more images from the same natural motive showing for example trees or grassland sites. To derive phenological patterns from the webcam images, regions of interest are manually defined on these images by an expert and subsequently a time series of percentage greenness is derived and analyzed with respect to structural changes. While this standard approach leads to satisfying results and allows to determine dates of phenological change points, it is associated with a considerable amount of manual work and is therefore constrained to a limited number of webcams only. In particular, this forbids to apply the phenological analysis to a large network of publicly accessible webcams in order to capture spatial phenological variation. In order to be able to scale up the analysis to several hundreds or thousands of webcams, we propose and evaluate two automated alternatives for the definition of regions of interest, allowing for efficient analyses of webcam images. A semi-supervised approach selects pixels based on the correlation of the pixels' time series of percentage greenness with a few prototype pixels. An unsupervised approach clusters pixels based on scores of a singular value decomposition. We show for a scientific webcam that the resulting regions of interest are at least as informative as those chosen by an expert with the advantage that no manual action is required. Additionally, we show that the methods can even be applied to publicly available webcams accessed via the internet yielding interesting partitions of the analyzed images. Finally, we show that the methods are suitable for the intended big data applications by analyzing 13988 webcams from the AMOS database. All developed methods are implemented in the statistical software

Automated processing of webcam images for phenological classification.

Directory of Open Access Journals (Sweden)

Ludwig Bothmann

Full Text Available Along with the global climate change, there is an increasing interest for its effect on phenological patterns such as start and end of the growing season. Scientific digital webcams are used for this purpose taking every day one or more images from the same natural motive showing for example trees or grassland sites. To derive phenological patterns from the webcam images, regions of interest are manually defined on these images by an expert and subsequently a time series of percentage greenness is derived and analyzed with respect to structural changes. While this standard approach leads to satisfying results and allows to determine dates of phenological change points, it is associated with a considerable amount of manual work and is therefore constrained to a limited number of webcams only. In particular, this forbids to apply the phenological analysis to a large network of publicly accessible webcams in order to capture spatial phenological variation. In order to be able to scale up the analysis to several hundreds or thousands of webcams, we propose and evaluate two automated alternatives for the definition of regions of interest, allowing for efficient analyses of webcam images. A semi-supervised approach selects pixels based on the correlation of the pixels' time series of percentage greenness with a few prototype pixels. An unsupervised approach clusters pixels based on scores of a singular value decomposition. We show for a scientific webcam that the resulting regions of interest are at least as informative as those chosen by an expert with the advantage that no manual action is required. Additionally, we show that the methods can even be applied to publicly available webcams accessed via the internet yielding interesting partitions of the analyzed images. Finally, we show that the methods are suitable for the intended big data applications by analyzing 13988 webcams from the AMOS database. All developed methods are implemented in the

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

Science.gov (United States)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

SISCAL project: establishing an internet-based delivery of near-real-time data products on coastal areas and lakes from satellite imagery

Science.gov (United States)

Fell, Frank; Burgess, Phelim; Gruenewald, Alexander; Meyer, Mia V.; Santer, Richard P.; Koslowsky, Dirk; Ganor, Dov; Herut, Barak; Nimre, Saleem; Tibor, Gideon; Berastegui, Diego A.; Nyborg, Lotte; Schultz-Rasmussen, Michael; Johansen, Torunn; Johnsen, Geir; Brozek, Morten; Joergensen, Henrik; Habberstad, Jan; Hanssen, Frank; Amir, Ran; Zask, Alon; Koehler, Antje

2003-05-01

SISCAL (Satellite-based Information System on Coastal Areas and Lakes) is a pan-European project dedicated to develop facilities to provide end-users with customized and easy-to-use data for environmental monitoring of coastal areas and lakes. The main task will be to create a software system providing Near-Real-Time information on the aquatic environment (using instruments such as AVHRR, MODIS or MERIS) and ancillary GIS-data. These products will be tailored to individual customers needs, allowing them to exploit Earth Observation (EO) data without extensive in-house knowledge. This way, SISCAL aims at closing the gap between research institutes, satellite data providers and the actual end-users. Data and information exchange will entirely take place over the internet, from the acquisition of satellite data raw from the providers to the dissemination of finalized data products to the end-users. The focus of SISCAL is set on the optimal integration of existing techniques. The co-operation between the ten SISCAL partners, including four end-users representative of public authorities from local to national scale, aims at strengthening the operational use of EO data in the management of coastal areas and lakes.

Drought footprint on European ecosystems between 1999 and 2010 assessed by remotely sensed vegetation phenology and productivity

DEFF Research Database (Denmark)

Ivits, Eva; Horion, Stéphanie Marie Anne F; Fensholt, Rasmus

2014-01-01

bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time-series of Normalized Difference Vegetation Index (NDVI). Drought spatio...... length, indicating that these ecosystems did not buffer the effects of drought well. In a climate change perspective, increase in drought frequency or intensity may result in larger impacts over these ecosystems, thus management and adaptation strategies should be strengthened in these areas of concerns.......Drought affects more people than any other natural disaster but there is little understanding of how ecosystems react to droughts. This study jointly analyzed spatio-temporal changes of drought patterns with vegetation phenology and productivity changes between 1999 and 2010 in major European...

Improvement of Management of Rhagoletis Cerasi in Bosnia and Herzegovina Based on a Phenological Model

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Nježić Branimir

2017-06-01

Full Text Available European cherry fruit fly (Rhagoletis cerasi is the key pest of sweet and sour cherry throughout Europe. Pest management is usually based on pesticide application. The key of successful management is knowing the proper time of pesticide application, based on the phenological model. To develop a phenological model, a local population of the pest from the northern part of Bosnia and Herzegovina was studied. First adult appearance and population densities were monitored by yellow sticky traps. Soil and air temperatures were compared at two thermal thresholds, 5 °C and 7 °C. Air temperature was applied in the model since it is more suitable for farmers and is related to soil temperature. Both thermal thresholds can be used. The first adult flies were captured after 435 degree-days (dd and the first cumulative 5% of the catch after 605 dd. These two times should be considered for time of application of pesticides. Regarding time for first egg hatch, the first larva burrowed into fruits at 730 dd. Cultivars that can be harvested beginning on the 730 dd calculate from 1 March are considered to have low risk of cherry fruit fly damage.

First Plant Phenological Records in the Carpathians and their Possible Use

Science.gov (United States)

Tekusova, M.; Horecká, V.; Mikulová, K.

2009-04-01

Phenological observations have a long history. The long time series come from Korea and some other parts of Asia, while wine harvest dates form the oldest phenological data sets in Europe. One of them started as early as 1457 year in Vienna, i.e. on the border of the Carpathian region. However, the first systematic phenological observations started in the south Carpathians almost four hundred years later following the establishment of the phenological network in Austria and later in the Hungarian Kingdom. A medical doctor P. Wierbitzky did first phenological observations in the Carpathian region in the beginning of thirties of the nineteenth century in Orawicza. The first systematic observations and records of plant development in this region are connected with the establishment of Austrian Institute for Meteorology and Geomagnetism since 1851. Although the historical significance of these observations is high, the data recorded are of lower quality, frequently interrupted and fragmented. Further development of phenological observations came with the introduction of the methodology of the observations introduced by Karl Fritsch in the beginning of the sixties of the nineteenth century mainly with the establishment of Hungarian Meteorological Service in 1871. These historical data were recorded and published in the yearbooks and, despite of the fragmentary character of the records, they are usable for some evaluations. This article brings the description of the data sets of systematic phenological network in the Carpathian region and considers some possible phenological evaluations. The phenological observations were done in some cases at the same localities as the climatologic observations but the number of phenological stations was quite lower in several years. The historical plant phenological records were based in many cases on the observation of four phenological phases: leafing, flowering, ripening and fall of leaves. Both the volume and the quality of the

A near real-time satellite-based global drought climate data record

International Nuclear Information System (INIS)

AghaKouchak, Amir; Nakhjiri, Navid

2012-01-01

Reliable drought monitoring requires long-term and continuous precipitation data. High resolution satellite measurements provide valuable precipitation information on a quasi-global scale. However, their short lengths of records limit their applications in drought monitoring. In addition to this limitation, long-term low resolution satellite-based gauge-adjusted data sets such as the Global Precipitation Climatology Project (GPCP) one are not available in near real-time form for timely drought monitoring. This study bridges the gap between low resolution long-term satellite gauge-adjusted data and the emerging high resolution satellite precipitation data sets to create a long-term climate data record of droughts. To accomplish this, a Bayesian correction algorithm is used to combine GPCP data with real-time satellite precipitation data sets for drought monitoring and analysis. The results showed that the combined data sets after the Bayesian correction were a significant improvement compared to the uncorrected data. Furthermore, several recent major droughts such as the 2011 Texas, 2010 Amazon and 2010 Horn of Africa droughts were detected in the combined real-time and long-term satellite observations. This highlights the potential application of satellite precipitation data for regional to global drought monitoring. The final product is a real-time data-driven satellite-based standardized precipitation index that can be used for drought monitoring especially over remote and/or ungauged regions. (letter)

Minimizing Gaps of Daily Ndvi Map with Geostationary Satellite Remote Sensing Data

Science.gov (United States)

Lee, S.; Ryu, Y.; Jiang, C.

2015-12-01

Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI

Partitioning of the net CO2 exchange using an automated chamber system reveals plant phenology as key control of production and respiration fluxes in a boreal peatland.

Science.gov (United States)

Järveoja, Järvi; Nilsson, Mats B; Gažovič, Michal; Crill, Patrick M; Peichl, Matthias

2018-04-30

The net ecosystem CO 2 exchange (NEE) drives the carbon (C) sink-source strength of northern peatlands. Since NEE represents a balance between various production and respiration fluxes, accurate predictions of its response to global changes require an in depth understanding of these underlying processes. Currently, however, detailed information of the temporal dynamics as well as the separate biotic and abiotic controls of the NEE component fluxes is lacking in peatland ecosystems. In this study, we address this knowledge gap by using an automated chamber system established across natural and trenching-/vegetation removal plots to partition NEE into its production (i.e. gross and net primary production; GPP and NPP) and respiration (i.e. ecosystem, heterotrophic and autotrophic respiration; ER, Rh and Ra) fluxes in a boreal peatland in northern Sweden. Our results showed that daily NEE patterns were driven by GPP while variations in ER were governed by Ra rather than Rh. Moreover, we observed pronounced seasonal shifts in the Ra/Rh and above-/belowground NPP ratios throughout the main phenological phases. Generalized linear model analysis revealed that the greenness index derived from digital images (as a proxy for plant phenology) was the strongest control of NEE, GPP and NPP while explaining considerable fractions also in the variations of ER and Ra. In addition, our data exposed greater temperature sensitivity of NPP compared to Rh resulting in enhanced C sequestration with increasing temperature. Overall, our study suggests that the temporal patterns in NEE and its component fluxes are tightly coupled to vegetation dynamics in boreal peatlands and thus challenges previous studies that commonly identify abiotic factors as key drivers. These findings further emphasize the need for integrating detailed information on plant phenology into process-based models to improve predictions of global change impacts on the peatland C cycle. This article is protected by

Proximate weather patterns and spring green-up phenology effect Eurasian beaver (Castor fiber) body mass and reproductive success: the implications of climate change and topography.

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Campbell, Ruairidh D; Newman, Chris; Macdonald, David W; Rosell, Frank

2013-04-01

Low spring temperatures have been found to benefit mobile herbivores by reducing the rate of spring-flush, whereas high rainfall increases forage availability. Cold winters prove detrimental, by increasing herbivore thermoregulatory burdens. Here we examine the effects of temperature and rainfall variability on a temperate sedentary herbivore, the Eurasian beaver, Castor fiber, in terms of inter-annual variation in mean body weight and per territory offspring production. Data pertain to 198 individuals, over 11 years, using capture-mark-recapture. We use plant growth (tree cores) and fAPAR (a satellite-derived plant productivity index) to examine potential mechanisms through which weather conditions affect the availability and the seasonal phenology of beaver forage. Juvenile body weights were lighter after colder winters, whereas warmer spring temperatures were associated with lighter adult body weights, mediated by enhanced green-up phenology rates. Counter-intuitively, we observed a negative association between rainfall and body weight in juveniles and adults, and also with reproductive success. Alder, Alnus incana, (n = 68) growth rings (principal beaver food in the study area) exhibited a positive relationship with rainfall for trees growing at elevations >2 m above water level, but a negative relationship for trees growing beavers at the landscape scale via effects on spring green-up phenology and winter thermoregulation. Rainfall influences beavers at finer spatial scales through topographical interactions with plant growth, where trees near water level, prone to water logging, producing poorer forage in wetter years. Unlike most other herbivores, beavers are an obligate aquatic species that utilize a restricted 'central-place' foraging range, limiting their ability to take advantage of better forage growth further from water during wetter years. With respect to anthropogenic climate change, interactions between weather variables, plant phenology and

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

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Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods

Feedbacks between earlywood anatomy and non-structural carbohydrates affect spring phenology and wood production in ring-porous oaks

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Pérez-de-Lis, Gonzalo; García-González, Ignacio; Rozas, Vicente; Olano, José Miguel

2016-10-01

Non-structural carbohydrates (NSC) play a central role in the construction and maintenance of a tree's vascular system, but feedbacks between the NSC status of trees and wood formation are not fully understood. We aimed to evaluate multiple dependencies among wood anatomy, winter NSC, and phenology for coexisting temperate (Quercus robur) and sub-Mediterranean (Q. pyrenaica) oaks along a water-availability gradient in the NW Iberian Peninsula. Sapwood NSC concentrations were quantified at three sites in December 2012 (N = 240). Leaf phenology and wood anatomy were surveyed in 2013. Structural equation modelling was used to analyse the interplay among hydraulic diameter (Dh), winter NSC, budburst date, and earlywood vessel production (EVP), while the effect of Dh and EVP on latewood width was assessed by using a mixed-effects model. NSC and wood production increased under drier conditions for both species. Q. robur showed a narrower Dh and lower soluble sugar (SS) concentration (3.88-5.08 % dry matter) than Q. pyrenaica (4.06-5.57 % dry matter), but Q. robur exhibited larger EVP and wider latewood (1403 µm) than Q. pyrenaica (667 µm). Stem diameter and Dh had a positive effect on SS concentrations, which were related to an earlier leaf flushing in both species. Sapwood sugar content appeared to limit EVP exclusively in Q. pyrenaica. In turn, Dh and EVP were found to be key predictors of latewood growth. Our results confirm that sapwood SS concentrations are involved in modulating growth resumption and xylem production in spring. Q. pyrenaica exhibited a tighter control of carbohydrate allocation to wood formation than Q. robur, which would play a role in protecting against environmental stress in the sub-Mediterranean area.

Assessment of the Latest GPM-Era High-Resolution Satellite Precipitation Products by Comparison with Observation Gauge Data over the Chinese Mainland

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Shaowei Ning

2016-10-01

Full Text Available The Global Precipitation Mission (GPM Core Observatory that was launched on 27 February 2014 ushered in a new era for estimating precipitation from satellites. Based on their high spatial–temporal resolution and near global coverage, satellite-based precipitation products have been applied in many research fields. The goal of this study was to quantitatively compare two of the latest GPM-era satellite precipitation products (GPM IMERG and GSMap-Gauge Ver. 6 with a network of 840 precipitation gauges over the Chinese mainland. Direct comparisons of satellite-based precipitation products with rain gauge observations over a 20 month period from April 2014 to November 2015 at 0.1° and daily/monthly resolutions showed the following results: Both of the products were capable of capturing the overall spatial pattern of the 20 month mean daily precipitation, which was characterized by a decreasing trend from the southeast to the northwest. GPM IMERG overestimated precipitation by approximately 0.09 mm/day while GSMap-Gauge Ver. 6 underestimated precipitation by −0.04 mm/day. The two satellite-based precipitation products performed better over wet southern regions than over dry northern regions. They also showed better performance in summer than in winter. In terms of mean error, root mean square error, correlation coefficient, and probability of detection, GSMap-Gauge was better able to estimate precipitation and had more stable quality results than GPM IMERG on both daily and monthly scales. GPM IMERG was more sensitive to conditions of no rain or light rainfall and demonstrated good capability of capturing the behavior of extreme precipitation events. Overall, the results revealed some limitations of these two latest satellite-based precipitation products when used over the Chinese mainland, helping to characterize some of the error features in these datasets for potential users.

Evaluation of the MiKlip decadal prediction system using satellite based cloud products

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Thomas Spangehl

2016-12-01

Full Text Available The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1 provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF and from the International Satellite Cloud Climatology Project (ISCCP. The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA, analysis rank histograms (ARH and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0 emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP. By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only

Intensity of heat stress in winter wheat—phenology compensates for the adverse effect of global warming

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Rezaei, Ehsan Eyshi; Siebert, Stefan; Ewert, Frank

2015-01-01

Higher temperatures during the growing season are likely to reduce crop yields with implications for crop production and food security. The negative impact of heat stress has also been predicted to increase even further for cereals such as wheat under climate change. Previous empirical modeling studies have focused on the magnitude and frequency of extreme events during the growth period but did not consider the effect of higher temperature on crop phenology. Based on an extensive set of climate and phenology observations for Germany and period 1951–2009, interpolated to 1 × 1 km resolution and provided as supplementary data to this article (available at stacks.iop.org/ERL/10/024012/mmedia), we demonstrate a strong relationship between the mean temperature in spring and the day of heading (DOH) of winter wheat. We show that the cooling effect due to the 14 days earlier DOH almost fully compensates for the adverse effect of global warming on frequency and magnitude of crop heat stress. Earlier heading caused by the warmer spring period can prevent exposure to extreme heat events around anthesis, which is the most sensitive growth stage to heat stress. Consequently, the intensity of heat stress around anthesis in winter crops cultivated in Germany may not increase under climate change even if the number and duration of extreme heat waves increase. However, this does not mean that global warning would not harm crop production because of other impacts, e.g. shortening of the grain filling period. Based on the trends for the last 34 years in Germany, heat stress (stress thermal time) around anthesis would be 59% higher in year 2009 if the effect of high temperatures on accelerating wheat phenology were ignored. We conclude that climate impact assessments need to consider both the effect of high temperature on grain set at anthesis but also on crop phenology. (letter)

A Hidden Markov Models Approach for Crop Classification: Linking Crop Phenology to Time Series of Multi-Sensor Remote Sensing Data

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Sofia Siachalou

2015-03-01

Full Text Available Vegetation monitoring and mapping based on multi-temporal imagery has recently received much attention due to the plethora of medium-high spatial resolution satellites and the improved classification accuracies attained compared to uni-temporal approaches. Efficient image processing strategies are needed to exploit the phenological information present in temporal image sequences and to limit data redundancy and computational complexity. Within this framework, we implement the theory of Hidden Markov Models in crop classification, based on the time-series analysis of phenological states, inferred by a sequence of remote sensing observations. More specifically, we model the dynamics of vegetation over an agricultural area of Greece, characterized by spatio-temporal heterogeneity and small-sized fields, using RapidEye and Landsat ETM+ imagery. In addition, the classification performance of image sequences with variable spatial and temporal characteristics is evaluated and compared. The classification model considering one RapidEye and four pan-sharpened Landsat ETM+ images was found superior, resulting in a conditional kappa from 0.77 to 0.94 per class and an overall accuracy of 89.7%. The results highlight the potential of the method for operational crop mapping in Euro-Mediterranean areas and provide some hints for optimal image acquisition windows regarding major crop types in Greece.

Overview of Boundary Layer Clouds Using Satellite and Ground-Based Measurements

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Xi, B.; Dong, X.; Wu, P.; Qiu, S.

2017-12-01

A comprehensive summary of boundary layer clouds properties based on our few recently studies will be presented. The analyses include the global cloud fractions and cloud macro/micro- physical properties based on satellite measurements using both CERES-MODIS and CloudSat/Caliposo data products,; the annual/seasonal/diurnal variations of stratocumulus clouds over different climate regions (mid-latitude land, mid-latitude ocean, and Arctic region) using DOE ARM ground-based measurements over Southern great plain (SGP), Azores (GRW), and North slope of Alaska (NSA) sites; the impact of environmental conditions to the formation and dissipation process of marine boundary layer clouds over Azores site; characterizing Arctice mixed-phase cloud structure and favorable environmental conditions for the formation/maintainess of mixed-phase clouds over NSA site. Though the presentation has widely spread topics, we will focus on the representation of the ground-based measurements over different climate regions; evaluation of satellite retrieved cloud properties using these ground-based measurements, and understanding the uncertainties of both satellite and ground-based retrievals and measurements.

Predicting Phenologic Response to Water Stress and Implications for Carbon Uptake across the Southeast U.S.

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Lowman, L.; Barros, A. P.

2016-12-01

Representation of plant photosynthesis in modeling studies requires phenologic indicators to scale carbon assimilation by plants. These indicators are typically the fraction of photosynthetically active radiation (FPAR) and leaf area index (LAI) which represent plant responses to light and water availability, as well as temperature constraints. In this study, a prognostic phenology model based on the growing season index is adapted to determine the phenologic indicators of LAI and FPAR at the sub-daily scale based on meteorological and soil conditions. Specifically, we directly model vegetation green-up and die-off responses to temperature, vapor pressure deficit, soil water potential, and incoming solar radiation. The indices are based on the properties of individual plant functional types, driven by observational data and prior modeling applications. First, we describe and test the sensitivity of the carbon uptake response to predicted phenology for different vegetation types. Second, the prognostic phenology model is incorporated into a land-surface hydrology model, the Duke Coupled Hydrology Model with Prognostic Vegetation (DCHM-PV), to demonstrate the impact of dynamic phenology on modeled carbon assimilation rates and hydrologic feedbacks. Preliminary results show reduced carbon uptake rates when incorporating a prognostic phenology model that match well against the eddy-covariance flux tower observations. Additionally, grassland vegetation shows the most variability in LAI and FPAR tied to meteorological and soil conditions. These results highlight the need to incorporate vegetation-specific responses to water limitation in order to accurately estimate the terrestrial carbon storage component of the global carbon budget.

The Phenological Network of Catalonia: an historical perspective

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Busto, Montserrat; Cunillera, Jordi; de Yzaguirre, Xavier

2017-04-01

The Meteorological Service of Catalonia (SMC) began systematic phenological observation in 1932. Forty-four observers registered the phenophases of 45 plant species, the first or last sighting of six bird species and the first sighting of one species of butterfly. The study First results of phenological observation in Catalonia was published in 1936, showing the different behaviour of the vegetal species and birds according to geographical location. The SMC worked against the military fascist uprising during the Spanish Civil War (1936-1939). Therefore, once the war was finished, the organisation was quickly closed by the Franco dictatorship and the National Meteorological Service became the official institution in Spain. This organization created the Spanish Phenological Network in 1943 following similar standards to the former Catalan network. The reintroduction of democracy and the return of the Catalan self-government structures (1977) allowed the re-foundation of the SMC in 1996. The Climatology Department needed phenological data to complement the study of climatic indicators and realised the fragile situation of phenology observations in Catalonia, with very few operational series. Following a preliminary analysis of the different systems of recording and saving data, the Phenological network of Catalonia (Fenocat) was re-established in 2013. Fenocat is an active partner of the Pan European Phenology Database (PEP725) that uses BBCH-scale coding and the USA National Phenology Network observation system. It is an example of citizen science. As at December 2016, Fenocat had recorded more than 450,000 data. The extension of summer climatic conditions in the Western Mediterranean region has resulted in repetition of phenopases in the same year, such as the second flowering of the holm oak (Quercus ilex), almond tree (Prunus dulcis) and sweet cherry tree (Prunus avium), or the delay in the departure data of the swallow (Hirundo rustica) and hoopoe (Upupa epops

Decadal declines in avian herbivore reproduction: density-dependent nutrition and phenological mismatch in the Arctic

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Ross, Megan V.; Alisaukas, Ray T.; Douglas, David C.; Kellett, Dana K.

2017-01-01

A full understanding of population dynamics depends not only on estimation of mechanistic contributions of recruitment and survival, but also knowledge about the ecological processes that drive each of these vital rates. The process of recruitment in particular may be protracted over several years, and can depend on numerous ecological complexities until sexually mature adulthood is attained. We addressed long-term declines (23 breeding seasons, 1992–2014) in the per capita production of young by both Ross's Geese (Chen rossii) and Lesser Snow Geese (Chen caerulescens caerulescens) nesting at Karrak Lake in Canada's central Arctic. During this period, there was a contemporaneous increase from 0.4 to 1.1 million adults nesting at this colony. We evaluated whether (1) density-dependent nutritional deficiencies of pre-breeding females or (2) phenological mismatch between peak gosling hatch and peak forage quality, inferred from NDVI on the brood-rearing areas, may have been behind decadal declines in the per capita production of goslings. We found that, in years when pre-breeding females arrived to the nesting grounds with diminished nutrient reserves, the proportional composition of young during brood-rearing was reduced for both species. Furthermore, increased mismatch between peak gosling hatch and peak forage quality contributed additively to further declines in gosling production, in addition to declines caused by delayed nesting with associated subsequent negative effects on clutch size and nest success. The degree of mismatch increased over the course of our study because of advanced vegetation phenology without a corresponding advance in Goose nesting phenology. Vegetation phenology was significantly earlier in years with warm surface air temperatures measured in spring (i.e., 25 May–30 June). We suggest that both increased phenological mismatch and reduced nutritional condition of arriving females were behind declines in population-level recruitment

Response of the Fine Root Production, Phenology, and Turnover Rate of Six Shrub Species from a Subtropical Forest to a Soil Moisture Gradient and Shading

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Fu, X.; Dai, X.; Wang, H.

2015-12-01

Knowledge of the fine root dynamics of different life forms in forest ecosystems is critical to understanding how the overall belowground carbon cycling is affected by climate change. However, our current knowledge regarding how endogenous or exogenous factors regulate the root dynamics of understory vegetation is limited. We selected a suite of study sites representing different habitats with gradients of soil moisture and solar radiation (shading or no shading). We assessed the fine root production phenology, the total fine root production, and the turnover among six understory shrub species in a subtropical climate, and examined the responses of the fine root dynamics to gradients in the soil moisture and solar radiation. The shrubs included three evergreen species, Loropetalum chinense, Vaccinium bracteatum, and Adinandra millettii, and three deciduous species, Serissa serissoides, Rubus corchorifolius, and Lespedeza davidii. We observed that variations in the annual fine root production and turnover among species were significant in the deciduous group but not in the evergreen group. Notably, V. bracteatum and S. serissoides presented the greatest responses in terms of root phenology to gradients in the soil moisture and shading: high-moisture habitat led to a decrease and shade led to an increase in fine root production during spring. Species with smaller fine roots of the 1st+2nd-order diameter presented more sensitive responses in terms of fine root phenology to a soil moisture gradient. Species with a higher fine root nitrogen-to -carbon ratio exhibited more sensitive responses in terms of fine root annual production to shading. Soil moisture and shading did not change the annual fine root production as much as the turnover rate. The fine root dynamics of some understory shrubs varied significantly with soil moisture and solar radiation status and may be different from tree species. Our results emphasize the need to study the understory fine root dynamics

Phenological plasticity will not help all species adapt to climate change.

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Duputié, Anne; Rutschmann, Alexis; Ronce, Ophélie; Chuine, Isabelle

2015-08-01

Concerns are rising about the capacity of species to adapt quickly enough to climate change. In long-lived organisms such as trees, genetic adaptation is slow, and how much phenotypic plasticity can help them cope with climate change remains largely unknown. Here, we assess whether, where and when phenological plasticity is and will be adaptive in three major European tree species. We use a process-based species distribution model, parameterized with extensive ecological data, and manipulate plasticity to suppress phenological variations due to interannual, geographical and trend climate variability, under current and projected climatic conditions. We show that phenological plasticity is not always adaptive and mostly affects fitness at the margins of the species' distribution and climatic niche. Under current climatic conditions, phenological plasticity constrains the northern range limit of oak and beech and the southern range limit of pine. Under future climatic conditions, phenological plasticity becomes strongly adaptive towards the trailing edges of beech and oak, but severely constrains the range and niche of pine. Our results call for caution when interpreting geographical variation in trait means as adaptive, and strongly point towards species distribution models explicitly taking phenotypic plasticity into account when forecasting species distribution under climate change scenarios. © 2015 John Wiley & Sons Ltd.

Improving dynamic global vegetation model (DGVM) simulation of western U.S. rangelands vegetation seasonal phenology and productivity

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Kerns, B. K.; Kim, J. B.; Day, M. A.; Pitts, B.; Drapek, R. J.

2017-12-01

Ecosystem process models are increasingly being used in regional assessments to explore potential changes in future vegetation and NPP due to climate change. We use the dynamic global vegetation model MAPSS-Century 2 (MC2) as one line of evidence for regional climate change vulnerability assessments for the US Forest Service, focusing our fine tuning model calibration from observational sources related to forest vegetation. However, there is much interest in understanding projected changes for arid rangelands in the western US such as grasslands, shrublands, and woodlands. Rangelands provide many ecosystem service benefits and local rural human community sustainability, habitat for threatened and endangered species, and are threatened by annual grass invasion. Past work suggested MC2 performance related to arid rangeland plant functional types (PFT's) was poor, and the model has difficulty distinguishing annual versus perennial grasslands. Our objectives are to increase the model performance for rangeland simulations and explore the potential for splitting the grass plant functional type into annual and perennial. We used the tri-state Blue Mountain Ecoregion as our study area and maps of potential vegetation from interpolated ground data, the National Land Cover Data Database, and ancillary NPP data derived from the MODIS satellite. MC2 historical simulations for the area overestimated woodland occurrence and underestimated shrubland and grassland PFT's. The spatial location of the rangeland PFT's also often did not align well with observational data. While some disagreement may be due to differences in the respective classification rules, the errors are largely linked to MC2's tree and grass biogeography and physiology algorithms. Presently, only grass and forest productivity measures and carbon stocks are used to distinguish PFT's. MC2 grass and tree productivity simulation is problematic, in particular grass seasonal phenology in relation to seasonal patterns

Temporal coherence of phenological and climatic rhythmicity in Beijing

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Chen, Xiaoqiu; Zhang, Weiqi; Ren, Shilong; Lang, Weiguang; Liang, Boyi; Liu, Guohua

2017-10-01

Using woody plant phenological data in the Beijing Botanical Garden from 1979 to 2013, we revealed three levels of phenology rhythms and examined their coherence with temperature rhythms. First, the sequential and correlative rhythm shows that occurrence dates of various phenological events obey a certain time sequence within a year and synchronously advance or postpone among years. The positive correlation between spring phenophase dates is much stronger than that between autumn phenophase dates and attenuates as the time interval between two spring phenophases increases. This phenological rhythm can be explained by positive correlation between above 0 °C mean temperatures corresponding to different phenophase dates. Second, the circannual rhythm indicates that recurrence interval of a phenophase in the same species in two adjacent years is about 365 days, which can be explained by the 365-day recurrence interval in the first and last dates of threshold temperatures. Moreover, an earlier phenophase date in the current year may lead to a later phenophase date in the next year through extending recurrence interval. Thus, the plant phenology sequential and correlative rhythm and circannual rhythm are interacted, which mirrors the interaction between seasonal variation and annual periodicity of temperature. Finally, the multi-year rhythm implies that phenophase dates display quasi-periodicity more than 1 year. The same 12-year periodicity in phenophase and threshold temperature dates confirmed temperature controls of the phenology multi-year rhythm. Our findings provide new perspectives for examining phenological response to climate change and developing comprehensive phenology models considering temporal coherence of phenological and climatic rhythmicity.

The Use of Geostatistics in the Study of Floral Phenology of Vulpia geniculata (L. Link

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Eduardo J. León Ruiz

2012-01-01

Full Text Available Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L. Link throughout the study area during sampling season. Ten sampling points, scattered troughout the city and low mountains in the “Sierra de Córdoba” were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to ellaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.

Citizen Science in Grand Teton National Park Reveals Phenological Response of Wildlife to Climate Change and Increases Public Involvement in Earth Science

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Bloom, T. D. S.; Riginos, C.

2017-12-01

Around the world, phenology —or the timing of ecological events — is shifting as the climate warms. This can lead to a variety of consequences for individual species and for ecological communities as a whole, most notably through asynchronies that can develop between plants and animals that depend upon each other (e.g. nectar-consuming pollinators). Within the Greater Yellowstone Ecosystem (GYE) and Grand Teton National Park (GTNP), there is little understanding of how climate change is affecting plant and animal phenology, yet through detailed scientific and citizen science observation there is tremendous potential to further our knowledge of this topic and increase public awareness. Detailed historic data are rare, but in GTNP we have the opportunity to capitalize on phenology data gathered by Dr. Frank Craighead, Jr. in the 1970s, before significant warming had occurred. We have already gathered, digitized, and quality-controlled Craighead's observations of plant first flowering dates. First flowering date for 87% of a 72-species data set correlate significantly with spring temperatures in the 1970s, suggesting that these plants are now flowering earlier and will continue to flower earlier in the future. Our multi-year project has project has 3 primary goals: (1) initiate a citizen science project, Wildflower Watch GTNP, to train volunteer scientists to collect contemporary phenology data on these species (2) gather further historical records of plant phenology in the region, and (3) model continued phenological changes under future climate change scenarios using satellite derived climate data and on the ground observations. This project simultaneously increases public involvement in climate research, collaborates with the National Park Service to inform management strategies for at-risk species, and furthers scientific understanding of phenological response to climate change in the Rocky Mountains.

Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data

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López, Oliver; Houborg, Rasmus; McCabe, Matthew Francis

2017-01-01

Advances in space-based observations have provided the capacity to develop regional- to global-scale estimates of evaporation, offering insights into this key component of the hydrological cycle. However, the evaluation of large-scale evaporation retrievals is not a straightforward task. While a number of studies have intercompared a range of these evaporation products by examining the variance amongst them, or by comparison of pixel-scale retrievals against ground-based observations, there is a need to explore more appropriate techniques to comprehensively evaluate remote-sensing-based estimates. One possible approach is to establish the level of product agreement between related hydrological components: for instance, how well do evaporation patterns and response match with precipitation or water storage changes? To assess the suitability of this consistency-based approach for evaluating evaporation products, we focused our investigation on four globally distributed basins in arid and semi-arid environments, comprising the Colorado River basin, Niger River basin, Aral Sea basin, and Lake Eyre basin. In an effort to assess retrieval quality, three satellite-based global evaporation products based on different methodologies and input data, including CSIRO-PML, the MODIS Global Evapotranspiration product (MOD16), and Global Land Evaporation: the Amsterdam Methodology (GLEAM), were evaluated against rainfall data from the Global Precipitation Climatology Project (GPCP) along with Gravity Recovery and Climate Experiment (GRACE) water storage anomalies. To ensure a fair comparison, we evaluated consistency using a degree correlation approach after transforming both evaporation and precipitation data into spherical harmonics. Overall we found no persistent hydrological consistency in these dryland environments. Indeed, the degree correlation showed oscillating values between periods of low and high water storage changes, with a phase difference of about 2-3 months

The extent of shifts in vegetation phenology between rural and urban areas within a human-dominated region.

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Dallimer, Martin; Tang, Zhiyao; Gaston, Kevin J; Davies, Zoe G

2016-04-01

Urbanization is one of the major environmental challenges facing the world today. One of its particularly pressing effects is alterations to local and regional climate through, for example, the Urban Heat Island. Such changes in conditions are likely to have an impact on the phenology of urban vegetation, which will have knock-on implications for the role that urban green infrastructure can play in delivering multiple ecosystem services. Here, in a human-dominated region, we undertake an explicit comparison of vegetation phenology between urban and rural zones. Using satellite-derived MODIS-EVI data from the first decade of the 20th century, we extract metrics of vegetation phenology (date of start of growing season, date of end of growing season, and length of season) for Britain's 15 largest cities and their rural surrounds. On average, urban areas experienced a growing season 8.8 days longer than surrounding rural zones. As would be expected, there was a significant decline in growing season length with latitude (by 3.4 and 2.4 days/degree latitude in rural and urban areas respectively). Although there is considerable variability in how phenology in urban and rural areas differs across our study cities, we found no evidence that built urban form influences the start, end, or length of the growing season. However, the difference in the length of the growing season between rural and urban areas was significantly negatively associated with the mean disposable household income for a city. Vegetation in urban areas deliver many ecosystem services such as temperature mitigation, pollution removal, carbon uptake and storage, the provision of amenity value for humans and habitat for biodiversity. Given the rapid pace of urbanization and ongoing climate change, understanding how vegetation phenology will alter in the future is important if we wish to be able to manage urban greenspaces effectively.

Evaluation of Satellite and Model Precipitation Products Over Turkey

Science.gov (United States)

Yilmaz, M. T.; Amjad, M.

2017-12-01

Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

A global synthesis of animal phenological responses to climate change

Science.gov (United States)

Cohen, Jeremy M.; Lajeunesse, Marc J.; Rohr, Jason R.

2018-03-01

Shifts in phenology are already resulting in disruptions to the timing of migration and breeding, and asynchronies between interacting species1-5. Recent syntheses have concluded that trophic level1, latitude6 and how phenological responses are measured7 are key to determining the strength of phenological responses to climate change. However, researchers still lack a comprehensive framework that can predict responses to climate change globally and across diverse taxa. Here, we synthesize hundreds of published time series of animal phenology from across the planet to show that temperature primarily drives phenological responses at mid-latitudes, with precipitation becoming important at lower latitudes, probably reflecting factors that drive seasonality in each region. Phylogeny and body size are associated with the strength of phenological shifts, suggesting emerging asynchronies between interacting species that differ in body size, such as hosts and parasites and predators and prey. Finally, although there are many compelling biological explanations for spring phenological delays, some examples of delays are associated with short annual records that are prone to sampling error. Our findings arm biologists with predictions concerning which climatic variables and organismal traits drive phenological shifts.

Phenological shifts conserve thermal niches in North American birds and reshape expectations for climate-driven range shifts.

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Socolar, Jacob B; Epanchin, Peter N; Beissinger, Steven R; Tingley, Morgan W

2017-12-05

Species respond to climate change in two dominant ways: range shifts in latitude or elevation and phenological shifts of life-history events. Range shifts are widely viewed as the principal mechanism for thermal niche tracking, and phenological shifts in birds and other consumers are widely understood as the principal mechanism for tracking temporal peaks in biotic resources. However, phenological and range shifts each present simultaneous opportunities for temperature and resource tracking, although the possible role for phenological shifts in thermal niche tracking has been widely overlooked. Using a canonical dataset of Californian bird surveys and a detectability-based approach for quantifying phenological signal, we show that Californian bird communities advanced their breeding phenology by 5-12 d over the last century. This phenological shift might track shifting resource peaks, but it also reduces average temperatures during nesting by over 1 °C, approximately the same magnitude that average temperatures have warmed over the same period. We further show that early-summer temperature anomalies are correlated with nest success in a continental-scale database of bird nests, suggesting avian thermal niches might be broadly limited by temperatures during nesting. These findings outline an adaptation surface where geographic range and breeding phenology respond jointly to constraints imposed by temperature and resource phenology. By stabilizing temperatures during nesting, phenological shifts might mitigate the need for range shifts. Global change ecology will benefit from further exploring phenological adjustment as a potential mechanism for thermal niche tracking and vice versa.

Satellite-based laser windsounder

International Nuclear Information System (INIS)

Schultz, J.F.; Czuchlewski, S.J.; Quick, C.R.

1997-01-01

This is the final report of a one-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project''s primary objective is to determine the technical feasibility of using satellite-based laser wind sensing systems for detailed study of winds, aerosols, and particulates around and downstream of suspected proliferation facilities. Extensive interactions with the relevant operational organization resulted in enthusiastic support and useful guidance with respect to measurement requirements and priorities. Four candidate wind sensing techniques were evaluated, and the incoherent Doppler technique was selected. A small satellite concept design study was completed to identify the technical issues inherent in a proof-of-concept small satellite mission. Use of a Mach-Zehnder interferometer instead of a Fabry-Perot would significantly simplify the optical train and could reduce weight, and possibly power, requirements with no loss of performance. A breadboard Mach-Zehnder interferometer-based system has been built to verify these predictions. Detailed plans were made for resolving other issues through construction and testing of a ground-based lidar system in collaboration with the University of Wisconsin, and through numerical lidar wind data assimilation studies

An integrated, indicator framework for assessing large-scale variations and change in seasonal timing and phenology (Invited)

Science.gov (United States)

Betancourt, J. L.; Weltzin, J. F.

2013-12-01

As part of an effort to develop an Indicator System for the National Climate Assessment (NCA), the Seasonality and Phenology Indicators Technical Team (SPITT) proposed an integrated, continental-scale framework for understanding and tracking seasonal timing in physical and biological systems. The framework shares several metrics with the EPA's National Climate Change Indicators. The SPITT framework includes a comprehensive suite of national indicators to track conditions, anticipate vulnerabilities, and facilitate intervention or adaptation to the extent possible. Observed, modeled, and forecasted seasonal timing metrics can inform a wide spectrum of decisions on federal, state, and private lands in the U.S., and will be pivotal for international efforts to mitigation and adaptation. Humans use calendars both to understand the natural world and to plan their lives. Although the seasons are familiar concepts, we lack a comprehensive understanding of how variability arises in the timing of seasonal transitions in the atmosphere, and how variability and change translate and propagate through hydrological, ecological and human systems. For example, the contributions of greenhouse warming and natural variability to secular trends in seasonal timing are difficult to disentangle, including earlier spring transitions from winter (strong westerlies) to summer (weak easterlies) patterns of atmospheric circulation; shifts in annual phasing of daily temperature means and extremes; advanced timing of snow and ice melt and soil thaw at higher latitudes and elevations; and earlier start and longer duration of the growing and fire seasons. The SPITT framework aims to relate spatiotemporal variability in surface climate to (1) large-scale modes of natural climate variability and greenhouse gas-driven climatic change, and (2) spatiotemporal variability in hydrological, ecological and human responses and impacts. The hierarchical framework relies on ground and satellite observations

Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

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Tarendra Lakhankar

2013-08-01

Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

Improved Satellite-based Photosysnthetically Active Radiation (PAR) for Air Quality Studies

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Pour Biazar, A.; McNider, R. T.; Cohan, D. S.; White, A.; Zhang, R.; Dornblaser, B.; Doty, K.; Wu, Y.; Estes, M. J.

2015-12-01

One of the challenges in understanding the air quality over forested regions has been the uncertainties in estimating the biogenic hydrocarbon emissions. Biogenic volatile organic compounds, BVOCs, play a critical role in atmospheric chemistry, particularly in ozone and particulate matter (PM) formation. In southeastern United States, BVOCs (mostly as isoprene) are the dominant summertime source of reactive hydrocarbon. Despite significant efforts in improving BVOC estimates, the errors in emission inventories remain a concern. Since BVOC emissions are particularly sensitive to the available photosynthetically active radiation (PAR), model errors in PAR result in large errors in emission estimates. Thus, utilization of satellite observations to estimate PAR can help in reducing emission uncertainties. Satellite-based PAR estimates rely on the technique used to derive insolation from satellite visible brightness measurements. In this study we evaluate several insolation products against surface pyranometer observations and offer a bias correction to generate a more accurate PAR product. The improved PAR product is then used in biogenic emission estimates. The improved biogenic emission estimates are compared to the emission inventories over Texas and used in air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). A series of sensitivity simulations will be performed and evaluated against Discover-AQ observations to test the impact of satellite-derived PAR on air quality simulations.

Grassland Growth in Response to Climate Variability in the Upper Indus Basin, Pakistan

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Sawaid Abbas

2015-08-01

Full Text Available Grasslands in the upper Indus basin provide a resource base for nomadic livestock grazing which is one of the major traditional livelihood practices in the area. The study presents climate patterns, grassland phenology, productivity and spatio-temporal climate controls on grassland growth using satellite data over the upper Indus basin of the Himalayan region, Pakistan. Phenology and productivity metrics of the grasses were estimated using a combination of derivative and threshold methods applied on fitted seasonal vegetation indices data over the period of 2001–2011. Satellite based rainfall and land surface temperature data are considered as representative explanatory variables to climate variability. The results showed distinct phenology and productivity patterns across four bioclimatic regions: (i humid subtropical region (HSR—late start and early end of season with short length of season and low productivity (ii temperate region (TR—early start and late end of season with higher length of season and moderate productivity (iii sub alpine region (SAR—late start and late end of season with very high length of season and the most productive grasses, and (iv alpine region (AR—late start and early end of season with small length of season and least productive grasses. Grassland productivity is constrained by temperature in the alpine region and by rainfall in the humid sub-tropical region. Spring temperature, winter and summer rainfall has shown significant and varied impact on phenology across different altitudes. The productivity is being influenced by summer and annual rainfall in humid subtropical regions, spring temperature in alpine and sub-alpine regions and both temperature and rainfall are contributing in temperate regions. The results revealing a strong relationship between grassland dynamics and climate variability put forth strong signals for drawing more scientific management of rangelands in the area.

Dissemination of satellite-based river discharge and flood data

Science.gov (United States)

Kettner, A. J.; Brakenridge, G. R.; van Praag, E.; de Groeve, T.; Slayback, D. A.; Cohen, S.

2014-12-01

In collaboration with NASA Goddard Spaceflight Center and the European Commission Joint Research Centre, the Dartmouth Flood Observatory (DFO) daily measures and distributes: 1) river discharges, and 2) near real-time flood extents with a global coverage. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations', and observed time series cover 1998 to the present. The advantages over in-situ gauged discharges are: a) easy access to remote or due to political reasons isolated locations, b) relatively low maintenance costs to maintain a continuous observational record, and c) the capability to obtain measurements during floods, hazardous conditions that often impair or destroy in-situ stations. Two MODIS instruments aboard the NASA Terra and Aqua satellites provide global flood extent coverage at a spatial resolution of 250m. Cloud cover hampers flood extent detection; therefore we ingest 6 images (the Terra and Aqua images of each day, for three days), in combination with a cloud shadow filter, to provide daily global flood extent updates. The Flood Observatory has always made it a high priority to visualize and share its data and products through its website. Recent collaborative efforts with e.g. GeoSUR have enhanced accessibility of DFO data. A web map service has been implemented to automatically disseminate geo-referenced flood extent products into client-side GIS software. For example, for Latin America and the Caribbean region, the GeoSUR portal now displays current flood extent maps, which can be integrated and visualized with other relevant geographical data. Furthermore, the flood state of satellite-observed river discharge sites are displayed through the portal as well. Additional efforts include implementing Open Geospatial Consortium (OGC) standards to incorporate Water Markup Language (WaterML) data exchange mechanisms to further facilitate the distribution of the satellite

Discriminating the Mediterranean Pinus spp. using the land surface phenology extracted from the whole MODIS NDVI time series and machine learning algorithms

Science.gov (United States)

Rodriguez-Galiano, Victor; Aragones, David; Caparros-Santiago, Jose A.; Navarro-Cerrillo, Rafael M.

2017-10-01

Land surface phenology (LSP) can improve the characterisation of forest areas and their change processes. The aim of this work was: i) to characterise the temporal dynamics in Mediterranean Pinus forests, and ii) to evaluate the potential of LSP for species discrimination. The different experiments were based on 679 mono-specific plots for the 5 native species on the Iberian Peninsula: P. sylvestris, P. pinea, P. halepensis, P. nigra and P. pinaster. The entire MODIS NDVI time series (2000-2016) of the MOD13Q1 product was used to characterise phenology. The following phenological parameters were extracted: the start, end and median days of the season, and the length of the season in days, as well as the base value, maximum value, amplitude and integrated value. Multi-temporal metrics were calculated to synthesise the inter-annual variability of the phenological parameters. The species were discriminated by the application of Random Forest (RF) classifiers from different subsets of variables: model 1) NDVI-smoothed time series, model 2) multi-temporal metrics of the phenological parameters, and model 3) multi-temporal metrics and the auxiliary physical variables (altitude, slope, aspect and distance to the coastline). Model 3 was the best, with an overall accuracy of 82%, a kappa coefficient of 0.77 and whose most important variables were: elevation, coast distance, and the end and start days of the growing season. The species that presented the largest errors was P. nigra, (kappa= 0.45), having locations with a similar behaviour to P. sylvestris or P. pinaster.

Global trends in satellite-based emergency mapping

Science.gov (United States)

Voigt, Stefan; Giulio-Tonolo, Fabio; Lyons, Josh; Kučera, Jan; Jones, Brenda; Schneiderhan, Tobias; Platzeck, Gabriel; Kaku, Kazuya; Hazarika, Manzul Kumar; Czaran, Lorant; Li, Suju; Pedersen, Wendi; James, Godstime Kadiri; Proy, Catherine; Muthike, Denis Macharia; Bequignon, Jerome; Guha-Sapir, Debarati

2016-01-01

Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

Examining spring phenology of forest understory using digital photography

Science.gov (United States)

Liang Liang; Mark D. Schwartz; Songlin Fei

2011-01-01

Phenology is an important indicator of forest health in relation to energy/nutrient cycles and species interactions. Accurate characterization of forest understory phenology is a crucial part of forest phenology observation. In this study, ground plots set up in a temperate mixed forest in Wisconsin were observed with a visible-light digital camera during spring 2007....

Phenology of two Ficus species in seasonal semi-deciduous forest in Southern Brazil

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E. Bianchini

Full Text Available Abstract We analyzed the phenology of Ficus adhatodifolia Schott ex Spreng. (23 fig tree and F. eximia Schott (12 fig tree for 74 months in a remnant of seasonal semi-deciduous forest (23°27’S and 51°15’W, Southern Brazil and discussed their importance to frugivorous. Leaf drop, leaf flush, syconia production and dispersal were recorded. These phenophases occurred year-round, but seasonal peaks were recorded in both leaf phenophases for F. eximia and leaf flushing for F. adhatodifolia. Climatic variables analyzed were positively correlated with reproductive phenophases of F. adhatodifolia and negatively correlated with the vegetative phenophases of F. eximia. In despite of environmental seasonality, little seasonality in the phenology of two species was observed, especially in the reproductive phenology. Both species were important to frugivorous, but F. adhatodifolia can play a relevant role in the remnant.

Applications of satellite 'hyper-sensing' in Chinese agriculture: Challenges and opportunities

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Onojeghuo, Alex Okiemute; Blackburn, George Alan; Huang, Jingfeng; Kindred, Daniel; Huang, Wenjiang

2018-02-01

Ensuring adequate food supplies to a large and increasing population continues to be the key challenge for China. Given the increasing integration of China within global markets for agricultural products, this issue is of considerable significance for global food security. Over the last 50 years, China has increased the production of its staple crops mainly by increasing yield per unit land area. However, this has largely been achieved through inappropriate agricultural practices, which have caused environmental degradation, with deleterious consequences for future agricultural productivity. Hence, there is now a pressing need to intensify agriculture in China using practices that are environmentally and economically sustainable. Given the dynamic nature of crops over space and time, the use of remote sensing technology has proven to be a valuable asset providing end-users in many countries with information to guide sustainable agricultural practices. Recently, the field has experienced considerable technological advancements reflected in the availability of 'hyper-sensing' (high spectral, spatial and temporal) satellite imagery useful for monitoring, modelling and mapping of agricultural crops. However, there still remains a significant challenge in fully exploiting such technologies for addressing agricultural problems in China. This review paper evaluates the potential contributions of satellite 'hyper-sensing' to agriculture in China and identifies the opportunities and challenges for future work. We perform a critical evaluation of current capabilities in satellite 'hyper-sensing' in agriculture with an emphasis on Chinese sensors. Our analysis draws on a series of in-depth examples based on recent and on-going projects in China that are developing 'hyper-sensing' approaches for (i) measuring crop phenology parameters and predicting yields; (ii) specifying crop fertiliser requirements; (iii) optimising management responses to abiotic and biotic stress in crops

Variation of Main Phenophases in Phenological Calendar in East China and Their Response to Climate Change

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Fengyi Zheng

2016-01-01

Full Text Available Based on the phenological data from China Phenological Observation Network, we compiled the phenological calendars of 3 phenological observation stations (Shanghai, Nanjing, and Hefei in East China for 1987–1996 and 2003–2012 according to the sequences of mean phenophases. We calculated the correlated coefficient and the root mean square error (RMSE between phenophases and the beginning of meteorological seasons to determine the beginning date of phenological season. By comparing new phenological calendars with the old ones, we discussed the variation of phenophases and their responses to temperature. The conclusions are as follows. (1 The beginning dates of spring and summer advanced, while those of autumn and winter delayed. Thus, summers got longer and winters got shorter. (2 The beginning time of the four phenological seasons was advancing during 1987–1996, while it was delaying during 2003–2012. (3 Most spring and summer phenophases occur earlier and most autumn and winter phenophases occur later in 2003–2012 than in 1987–1996. (4 The beginning time of phenological seasons was significantly correlated with temperature. The phenological sensitivities to temperature ranged from −6.49 to −6.55 days/°C in spring, −3.65 to −5.02 days/°C in summer, 8.13 to 10.27 days/°C in autumn, and 4.76 to 10.00 days/°C in winter.

Exploring Connections between Global Climate Indices and African Vegetation Phenology

Science.gov (United States)

Brown, Molly E.; deBeurs, Kirsten; Vrieling, Anton

2009-01-01

Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the continent in Africa. Agriculturally destructive droughts and floods are monitored from space using satellite remote sensing by organizations seeking to provide quantitative and predictive information about food security crises. Better knowledge on the relation between climate indices and food production may increase the use of these indices in famine early warning systems and climate outlook forums on the continent. Here we explore the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), the Multivariate ENSO Index (MEI) and the Southern Oscillation Index (SOI). We explore spatial relationships between growing conditions as measured by the NDVI and the five climate indices in Eastern, Western and Southern Africa to determine the regions and periods when they have a significant impact. The focus is to provide a clear indication as to which climate index has the most impact on the three regions during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by variations in the climate indices. The particular climate index and the timing showing highest correlation depended heavily on the region examined. The research shows that climate indices can contribute to understanding growing season variability in Eastern, Western and Southern Africa.

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

Science.gov (United States)

Liu, Zhong; Heo, Gil

2015-01-01

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

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Ying Qu

2015-01-01

Full Text Available Surface albedo is one of the key controlling geophysical parameters in the surface energy budget studies, and its temporal and spatial variation is closely related to the global climate change and regional weather system due to the albedo feedback mechanism. As an efficient tool for monitoring the surfaces of the Earth, remote sensing is widely used for deriving long-term surface broadband albedo with various geostationary and polar-orbit satellite platforms in recent decades. Moreover, the algorithms for estimating surface broadband albedo from satellite observations, including narrow-to-broadband conversions, bidirectional reflectance distribution function (BRDF angular modeling, direct-estimation algorithm and the algorithms for estimating albedo from geostationary satellite data, are developed and improved. In this paper, we present a comprehensive literature review on algorithms and products for mapping surface broadband albedo with satellite observations and provide a discussion of different algorithms and products in a historical perspective based on citation analysis of the published literature. This paper shows that the observation technologies and accuracy requirement of applications are important, and long-term, global fully-covered (including land, ocean, and sea-ice surfaces, gap-free, surface broadband albedo products with higher spatial and temporal resolution are required for climate change, surface energy budget, and hydrological studies.

Hierarchical Satellite-based Approach to Global Monitoring of Crop Condition and Food Production

Science.gov (United States)

Zheng, Y.; Wu, B.; Gommes, R.; Zhang, M.; Zhang, N.; Zeng, H.; Zou, W.; Yan, N.

2014-12-01

The assessment of global food security goes beyond the mere estimate of crop production: It needs to take into account the spatial and temporal patterns of food availability, as well as physical and economic access. Accurate and timely information is essential to both food producers and consumers. Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, such as FY-2/3A, HJ-1 CCD, CropWatch has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The new monitoring approach adopts a hierarchical system covering four spatial levels of detail: global (sixty-five Monitoring and Reporting Units, MRU), seven major production zones (MPZ), thirty-one key countries (including China) and "sub- countries." The thirty-one countries encompass more that 80% of both global exports and production of four major crops (maize, rice, soybean and wheat). The methodology resorts to climatic and remote sensing indicators at different scales, using the integrated information to assess global, regional, and national (as well as sub-national) crop environmental condition, crop condition, drought, production, and agricultural trends. The climatic indicators for rainfall, temperature, photosynthetically active radiation (PAR) as well as potential biomass are first analysed at global scale to describe overall crop growing conditions. At MPZ scale, the key indicators pay more attention to crops and include Vegetation health index (VHI), Vegetation condition index (VCI), Cropped arable land fraction (CALF) as well as Cropping intensity (CI). Together, they characterise agricultural patterns, farming intensity and stress. CropWatch carries out detailed crop condition analyses for thirty one individual countries at the national scale with a comprehensive array of variables and indicators. The Normalized difference vegetation index (NDVI), cropped areas and crop condition are

Morphological constraints on changing avian migration phenology.

Science.gov (United States)

Møller, A P; Rubolini, D; Saino, N

2017-06-01

Many organisms at northern latitudes have responded to climate warming by advancing their spring phenology. Birds are known to show earlier timing of spring migration and reproduction in response to warmer springs. However, species show heterogeneous phenological responses to climate warming, with those that have not advanced or have delayed migration phenology experiencing population declines. Although some traits (such as migration distance) partly explain heterogeneity in phenological responses, the factors affecting interspecies differences in the responsiveness to climate warming have yet to be fully explored. In this comparative study, we investigate whether variation in wing aspect ratio (reflecting relative wing narrowness), an ecomorphological trait that is strongly associated with flight efficiency and migratory behaviour, affects the ability to advance timing of spring migration during 1960-2006 in a set of 80 European migratory bird species. Species with larger aspect ratio (longer and narrower wings) showed smaller advancement of timing of spring migration compared to species with smaller aspect ratio (shorter and wider wings) while controlling for phylogeny, migration distance and other life-history traits. In turn, migration distance positively predicted aspect ratio across species. Hence, species that are better adapted to migration appear to be more constrained in responding phenologically to rapid climate warming by advancing timing of spring migration. Our findings corroborate the idea that aspect ratio is a major evolutionary correlate of migration, and suggest that selection for energetically efficient flights, as reflected by high aspect ratio, may hinder phenotypically plastic/microevolutionary adjustments of migration phenology to ongoing climatic changes. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Decadal declines in avian herbivore reproduction: density-dependent nutrition and phenological mismatch in the Arctic.

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Ross, Megan V; Alisauskas, Ray T; Douglas, David C; Kellett, Dana K

2017-07-01

A full understanding of population dynamics depends not only on estimation of mechanistic contributions of recruitment and survival, but also knowledge about the ecological processes that drive each of these vital rates. The process of recruitment in particular may be protracted over several years, and can depend on numerous ecological complexities until sexually mature adulthood is attained. We addressed long-term declines (23 breeding seasons, 1992-2014) in the per capita production of young by both Ross's Geese (Chen rossii) and Lesser Snow Geese (Chen caerulescens caerulescens) nesting at Karrak Lake in Canada's central Arctic. During this period, there was a contemporaneous increase from 0.4 to 1.1 million adults nesting at this colony. We evaluated whether (1) density-dependent nutritional deficiencies of pre-breeding females or (2) phenological mismatch between peak gosling hatch and peak forage quality, inferred from NDVI on the brood-rearing areas, may have been behind decadal declines in the per capita production of goslings. We found that, in years when pre-breeding females arrived to the nesting grounds with diminished nutrient reserves, the proportional composition of young during brood-rearing was reduced for both species. Furthermore, increased mismatch between peak gosling hatch and peak forage quality contributed additively to further declines in gosling production, in addition to declines caused by delayed nesting with associated subsequent negative effects on clutch size and nest success. The degree of mismatch increased over the course of our study because of advanced vegetation phenology without a corresponding advance in Goose nesting phenology. Vegetation phenology was significantly earlier in years with warm surface air temperatures measured in spring (i.e., 25 May-30 June). We suggest that both increased phenological mismatch and reduced nutritional condition of arriving females were behind declines in population-level recruitment, leading

Predicting phenology by integrating ecology, evolution and climate science

Science.gov (United States)

Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.

2011-01-01

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Attributing the effects of climate on phenology change suggests high sensitivity in coastal zones

Science.gov (United States)

Seyednasrollah, B.; Clark, J. S.

2015-12-01

The impact of climate change on spring phenology depends on many variables that cannot be separated using current models. Phenology can influence carbon sequestration, plant nutrition, forest health, and species distributions. Leaf phenology is sensitive to changes of environmental factors, including climate, species composition, latitude, and solar radiation. The many variables and their interactions frustrate efforts to attribute variation to climate change. We developed a Bayesian framework to quantify the influence of environment on the speed of forest green-up. This study presents a state-space hierarchical model to infer and predict change in forest greenness over time using satellite observations and ground measurements. The framework accommodates both observation and process errors and it allows for main effects of variables and their interactions. We used daily spaceborne remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify temporal variability in the enhanced vegetation index (EVI) along a habitat gradient in the Southeastern United States. The ground measurements of meteorological parameters are obtained from study sites located in the Appalachian Mountains, the Piedmont and the Atlantic Coastal Plain between years 2000 and 2015. Results suggest that warming accelerates spring green-up in the Coastal Plain to a greater degree than in the Piedmont and Appalachian. In other words, regardless of variation in the timing of spring onset, the rate of greenness in non-coastal zones decreases with increasing temperature and hence with time over the spring transitional period. However, in coastal zones, as air temperature increases, leaf expansion becomes faster. This may indicate relative vulnerability to warming in non-coastal regions where moisture could be a limiting factor, whereas high temperatures in regions close to the coast enhance forest physiological activities. Model predictions agree with the remotely

SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

A. Sharma

2015-03-01

Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-04-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by

Phenological responses of juvenile pecan and white oak on an upland site

Science.gov (United States)

Pecan (Carya illinoiensis) and white oak (Quercus alba) produce multiple products and wildlife values, but their phenological responses to N fertilization have not been well characterized in an mixed species agroforestry practice. We compared tree height at planting and for six consecutive growing ...

Phenological characteristics of the main vegetation types on the Tibetan Plateau based on vegetation and water indices

International Nuclear Information System (INIS)

Peng, D L; Huang, W J; Zhou, B; Li, C J; Wu, Y P; Yang, X H

2014-01-01

Plant phenology is considered one of the most sensitive and easily observable natural indicators of climate change, though few studies have focused on the heterogeneities of phenology across the different vegetation types. In this study, we tried to find the phenological characteristics of the main vegetation types on the Tibetan Plateau. MCD12Q1 images over the Tibetan Plateau from 2001 to 2010 were used to extract the main vegetation types. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) were calculated using surface reflectance values from the blue, red, near-infrared, short-wave infrared (SWIR) 6 (for LSIW6), and SWIR7 (for LSIW7) bands derived from MOD09A1 and used to explore the phenological characteristics of the main vegetation types on the Tibetan Plateau. The results showed that there were eight constant vegetation types on the Tibetan Plateau from 2001 to 2010 demonstrating multiple phenological characteristics. Evergreen needleleaf forest, evergreen broadleaf forest, and permanent wetland had the minimum NDVI values during the summer season, while open shrubland and grassland had the maximum NDVI/EVI values during this period. NDVI and EVI of cropland/natural vegetation had two peaks for their seasonal variations. EVI showed a more significant correlation with LSWI6/LSWI7 than NDVI. Compared to LSWI7, larger EVI values occurred in evergreen needleleaf forest, evergreen broadleaf forest, mixed forest, and permanent wetland, while smaller values occurred in shrubland and barren or sparsely vegetated cover, and nearly equal values occurred in grassland and cropland

Recent Enhancements in NOAA's JPSS Land Product Suite and Key Operational Applications

Science.gov (United States)

Csiszar, I. A.; Yu, Y.; Zhan, X.; Vargas, M.; Ek, M. B.; Zheng, W.; Wu, Y.; Smirnova, T. G.; Benjamin, S.; Ahmadov, R.; James, E.; Grell, G. A.

2017-12-01

A suite of operational land products has been produced as part of NOAA's Joint Polar Satellite System (JPSS) program to support a wide range of operational applications in environmental monitoring, prediction, disaster management and mitigation, and decision support. The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) and the operational JPSS satellite series forms the basis of six fundamental and multiple additional added-value environmental data records (EDRs). A major recent improvement in the land-based VIIRS EDRs has been the development of global gridded products, providing a format and science content suitable for ingest into NOAA's operational land surface and coupled numerical weather prediction models. VIIRS near-real-time Green Vegetation Fraction is now in the process of testing for full operational use, while land surface temperature and albedo are under testing and evaluation. The operational 750m VIIRS active fire product, including fire radiative power, is used to support emission modeling and air quality applications. Testing the evaluation for operational NOAA implementation of the improved 375m VIIRS active fire product is also underway. Added-value and emerging VIIRS land products include vegetation health, phenology, near-real-time surface type and surface condition change, and other biogeophysical variables. As part of the JPSS program, a global soil moisture data product has also been generated from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor on the GCOM-W1 (Global Change Observation Mission - Water 1) satellite since July 2012. This product is included in the blended NESDIS Soil Moisture Operational Products System, providing soil moisture data as a critical input for land surface modeling.

Responses of phenological and physiological stages of spring ...

African Journals Online (AJOL)

In order to investigate impact of complementary irrigation on phenological stages, chlorophyll content, radiation absorption and extinction coefficient, as well as some aspects concerning the yield of spring safflower, a split-plot experiment based on randomized complete block design with three replication was conducted at ...

New satellite altimetry products for coastal oceans

Science.gov (United States)

Dufau, Claire; Mercier, F.; Ablain, M.; Dibarboure, G.; Carrere, L.; Labroue, S.; Obligis, E.; Sicard, P.; Thibaut, P.; Birol, F.; Bronner, E.; Lombard, A.; Picot, N.

Since the launch of Topex-Poseidon in 1992, satellite altimetry has become one of the most essential elements of the Earth's observing system. Its global view of the ocean state has permitted numerous improvements in the environment understanding, particularly in the global monitoring of climate changes and ocean circulation. Near the coastlines where human activities have a major impact on the ocean, satellite altimeter techniques are unfortunately limited by a growth of their error budget. This quality loss is due to land contamination in the altimetric and radiometric footprints but also to inaccurate geophysical corrections (tides, high-frequency processes linked to atmospheric forcing).Despite instrumental perturbations by emerged lands until 10 km (altimeter) and 50 km (radiometer) off the coasts, measurements are made and may contain useful information for coastal studies. In order to recover these data close to the coast, the French Spatial Agency (CNES) has funded the development of the PISTACH prototype dedicated to Jason-2 altimeter processing in coastal ocean. Since November 2008, these new satellite altimeter products have been providing new retracking solutions, several state-of-the-art or with higher resolution corrections in addition to standard fields. This presentation will present and illustrate this new set of satellite data for the coastal oceans.

Assessment of Export Efficiency Equations in the Southern Ocean Applied to Satellite-Based Net Primary Production

Science.gov (United States)

Arteaga, Lionel; Haëntjens, Nils; Boss, Emmanuel; Johnson, Kenneth S.; Sarmiento, Jorge L.

2018-04-01

Carbon export efficiency (e-ratio) is defined as the fraction of organic carbon fixed through net primary production (NPP) that is exported out of the surface productive layer of the ocean. Recent observations for the Southern Ocean suggest a negative e-ratio versus NPP relationship, and a reduced dependency of export efficiency on temperature, different than in the global domain. In this study, we complement information from a passive satellite sensor with novel space-based lidar observations of ocean particulate backscattering to infer NPP over the entire annual cycle, and estimate Southern Ocean export rates from five different empirical models of export efficiency. Inferred Southern Ocean NPP falls within the range of previous studies, with a mean estimate of 15.8 (± 3.9) Pg C yr-1 for the region south of 30°S during the 2005-2016 period. We find that an export efficiency model that accounts for silica(Si)-ballasting, which is constrained by observations with a negative e-ratio versus NPP relationship, shows the best agreement with in situ-based estimates of annual net community production (annual export of 2.7 ± 0.6 Pg C yr-1 south of 30°S). By contrast, models based on the analysis of global observations with a positive e-ratio versus NPP relationship predict annually integrated export rates that are ˜ 33% higher than the Si-dependent model. Our results suggest that accounting for Si-induced ballasting is important for the estimation of carbon export in the Southern Ocean.

SAMIRA - SAtellite based Monitoring Initiative for Regional Air quality

Science.gov (United States)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nicolae, Doina; Stachlewska, Iwona; Zehner, Claus

2016-04-01

Here, we present a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellites, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. Despite considerable improvements in the past decades, Europe is still far from achieving levels of air quality that do not pose unacceptable hazards to humans and the environment. Main concerns in Europe are exceedances of particulate matter (PM), ground-level ozone, benzo(a)pyrene (BaP) and nitrogen dioxide (NO2). While overall sulfur dioxide (SO2) emissions have decreased in recent years, regional concentrations can still be high in some areas. The objectives of SAMIRA are to improve algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from SEVIRI, and to develop robust methods for deriving column- and near-surface PM maps for the study area by combining satellite AOD with information from regional models. The benefit to existing monitoring networks (in situ, models, satellite) by combining these datasets using data fusion methods will be tested for satellite-based NO2, SO2, and PM/AOD. Furthermore, SAMIRA will test and apply techniques for downscaling air quality-related EO products to a spatial resolution that is more in line with what is generally required for studying urban and regional scale air quality. This will be demonstrated for a set of study sites that include the capitals of the four countries and the highly polluted areas along the border of Poland and the

How consistent are global long-term satellite LAI products in terms of interannual variability and trend?

Science.gov (United States)

Jiang, C.; Ryu, Y.; Fang, H.

2016-12-01

Proper usage of global satellite LAI products requires comprehensive evaluation. To address this issue, the Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup proposed a four-stage validation hierarchy. During the past decade, great efforts have been made following this validation framework, mainly focused on absolute magnitude, seasonal trajectory, and spatial pattern of those global satellite LAI products. However, interannual variability and trends of global satellite LAI products have been investigated marginally. Targeting on this gap, we made an intercomparison between seven global satellite LAI datasets, including four short-term ones: MODIS C5, MODIS C6, GEOV1, MERIS, and three long-term products ones: LAI3g, GLASS, and GLOBMAP. We calculated global annual LAI time series for each dataset, among which we found substantial differences. During the overlapped period (2003 - 2011), MODIS C5, GLASS and GLOBMAP have positive correlation (r > 0.6) between each other, while MODIS C6, GEOV1, MERIS, and LAI3g are highly consistent (r > 0.7) in interannual variations. However, the previous three datasets show negative trends, all of which use MODIS C5 reflectance data, whereas the latter four show positive trends, using MODIS C6, SPOT/VGT, ENVISAT/MERIS, and NOAA/AVHRR, respectively. During the pre-MODIS era (1982 - 1999), the three AVHRR-based datasets (LAI3g, GLASS and GLOBMAP) agree well (r > 0.7), yet all of them show oscillation related with NOAA platform changes. In addition, both GLASS and GLOBMAP show clear cut-points around 2000 when they move from AVHRR to MODIS. Such inconsistency is also visible for GEOV1, which uses SPOT-4 and SPOT-5 before and after 2002. We further investigate the map-to-map deviations among these products. This study highlights that continuous sensor calibration and cross calibration are essential to obtain reliable global LAI time series.

The USA-NPN Information Management System: A tool in support of phenological assessments

Science.gov (United States)

Rosemartin, A.; Vazquez, R.; Wilson, B. E.; Denny, E. G.

2009-12-01

The USA National Phenology Network (USA-NPN) serves science and society by promoting a broad understanding of plant and animal phenology and the relationships among phenological patterns and all aspects of environmental change. Data management and information sharing are central to the USA-NPN mission. The USA-NPN develops, implements, and maintains a comprehensive Information Management System (IMS) to serve the needs of the network, including the collection, storage and dissemination of phenology data, access to phenology-related information, tools for data interpretation, and communication among partners of the USA-NPN. The IMS includes components for data storage, such as the National Phenology Database (NPD), and several online user interfaces to accommodate data entry, data download, data visualization and catalog searches for phenology-related information. The IMS is governed by a set of standards to ensure security, privacy, data access, and data quality. The National Phenology Database is designed to efficiently accommodate large quantities of phenology data, to be flexible to the changing needs of the network, and to provide for quality control. The database stores phenology data from multiple sources (e.g., partner organizations, researchers and citizen observers), and provides for integration with legacy datasets. Several services will be created to provide access to the data, including reports, visualization interfaces, and web services. These services will provide integrated access to phenology and related information for scientists, decision-makers and general audiences. Phenological assessments at any scale will rely on secure and flexible information management systems for the organization and analysis of phenology data. The USA-NPN’s IMS can serve phenology assessments directly, through data management and indirectly as a model for large-scale integrated data management.

Phenology and Growth dynamics of Avicennia marina in the Central Red Sea

KAUST Repository

Almahasheer, Hanan

2016-11-28

The formation of nodes, stem elongation and the phenology of stunted Avicennia marina was examined in the Central Red Sea, where Avicennia marina is at the limit of its distribution range and submitted to extremely arid conditions with salinity above 38 psu and water temperature as high as 35° C. The annual node production was rather uniform among locations averaging 9.59 node y−1, which resulted in a plastocron interval, the interval in between production of two consecutive nodes along a stem, of 38 days. However, the internodal length varied significantly between locations, resulting in growth differences possibly reflecting the environmental conditions of locations. The reproductive cycle lasted for approximately 12 months, and was characterized by peak flowering and propagule development in November and January. These phenological observations provide a starting point for research and restoration programs on the ecology of mangroves in the Central Red Sea, while the plastochrone index reported here would allow calculations of the growth and production of the species from simple morphological measurements.

Phenology and Growth dynamics of Avicennia marina in the Central Red Sea

Science.gov (United States)

Almahasheer, Hanan; Duarte, Carlos M.; Irigoien, Xabier

2016-01-01

The formation of nodes, stem elongation and the phenology of stunted Avicennia marina was examined in the Central Red Sea, where Avicennia marina is at the limit of its distribution range and submitted to extremely arid conditions with salinity above 38 psu and water temperature as high as 35° C. The annual node production was rather uniform among locations averaging 9.59 node y−1, which resulted in a plastocron interval, the interval in between production of two consecutive nodes along a stem, of 38 days. However, the internodal length varied significantly between locations, resulting in growth differences possibly reflecting the environmental conditions of locations. The reproductive cycle lasted for approximately 12 months, and was characterized by peak flowering and propagule development in November and January. These phenological observations provide a starting point for research and restoration programs on the ecology of mangroves in the Central Red Sea, while the plastochrone index reported here would allow calculations of the growth and production of the species from simple morphological measurements. PMID:27892956

Phenological characters and genetic divergence in aromatic rices

African Journals Online (AJOL)

STORAGESEVER

2009-07-20

Jul 20, 2009 ... Phenological properties of a plant are measured in time duration between ... The time interval between sowing and flowering in rice (Oryza sativa L.) ... locally adapted genotypes of aromatic rices have evolved because of natural ... classification of genotypes based on suitable scale is quite imperative to ...

Pituophis ruthveni (Louisiana pinesnake) Reproduction/breeding phenology

Science.gov (United States)

Josh B. Pierce; Craig Rudolph; Christopher A. Melder; Beau B. Gregory

2016-01-01

Determing the reproductive phenology of snakes is important since it marks a time period where snakes are particularly vulnerable to predation. In addition, knowledge of reproductive phenology may help captive breeding programs specify appropriate times to pair snakes for reproduction.

Fine Root Growth Phenology, Production, and Turnover in a Northern Hardwood Forest Ecosystem

Science.gov (United States)

Dudley J. Raynal

1994-01-01

A large part of the nutrient flux in deciduous forests is through fine root turnover, yet this process is seldom measured. As part of a nutrient cycling study, fine root dynamics were studied for two years at Huntington Forest in the Adirondack Mountain region of New York, USA. Root growth phenology was characterized using field rhizotrons, three methods were used to...

Xylem and phloem phenology in co-occurring conifers exposed to drought.

Science.gov (United States)

Swidrak, Irene; Gruber, Andreas; Oberhuber, Walter

2014-01-01

Variability in xylem and phloem phenology among years and species is caused by contrasting temperatures prevailing at the start of the growing season and species-specific sensitivity to drought. The focus of this study was to determine temporal dynamics of xylem and phloem formation in co-occurring deciduous and evergreen coniferous species in a dry inner Alpine environment (750 m a.s.l., Tyrol, Austria). By repeated micro-sampling of the stem, timing of key phenological dates of xylem and phloem formation was compared among mature Pinus sylvestris , Larix decidua and Picea abies during two consecutive years. Xylem formation in P. sylvestris started in mid and late April 2011 and 2012, respectively, and in both years about 2 week later in P. abies and L. decidua . Phloem formation preceded xylem formation on average by 3 week in P. sylvestris , and c . 5 week in P. abies and L. decidua . Based on modeled cell number increase, tracheid production peaked between early through late May 2011 and late May through mid-June 2012. Phloem formation culminated between late April and mid-May in 2011 and in late May 2012. Production of xylem and phloem cells continued for about 4 and 5-6 months, respectively. High variability in xylem increment among years and species is related to exogenous control by climatic factors and species-specific sensitivity to drought, respectively. On the other hand, production of phloem cells was quite homogenous and showed asymptotic decrease with respect to xylem cells indicating endogenous control. Results indicate that onset and culmination of xylem and phloem formation are controlled by early spring temperature, whereby strikingly advanced production of phloem compared to xylem cells suggests lower temperature requirement for initiation of the former.

Precipitation Analysis at Fine Time Scales Using Multiple Satellites: Real-time and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) in 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O"N-5O0S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

Science.gov (United States)

Chen, Jung-Chieh

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forests.

Science.gov (United States)

Richardson, Andrew D; Hollinger, David Y; Dail, D Bryan; Lee, John T; Munger, J William; O'keefe, John

2009-03-01

Spring phenology is thought to exert a major influence on the carbon (C) balance of temperate and boreal ecosystems. We investigated this hypothesis using four spring onset phenological indicators in conjunction with surface-atmosphere CO(2) exchange data from the conifer-dominated Howland Forest and deciduous-dominated Harvard Forest AmeriFlux sites. All phenological measures, including CO(2) source-sink transition dates, could be well predicted on the basis of a simple two-parameter spring warming model, indicating good potential for improving the representation of phenological transitions and their dynamic responsiveness to climate variability in land surface models. The date at which canopy-scale photosynthetic capacity reached a threshold value of 12 micromol m(-2) s(-1) was better correlated with spring and annual flux integrals than were either deciduous or coniferous bud burst dates. For all phenological indicators, earlier spring onset consistently, but not always significantly, resulted in higher gross primary productivity (GPP) and ecosystem respiration (RE) for both seasonal (spring months, April-June) and annual flux integrals. The increase in RE was less than that in GPP; depending on the phenological indicator used, a one-day advance in spring onset increased springtime net ecosystem productivity (NEP) by 2-4 g C m(-2) day(-1). In general, we could not detect significant differences between the two forest types in response to earlier spring, although the response to earlier spring was generally more pronounced for Harvard Forest than for Howland Forest, suggesting that future climate warming may favor deciduous species over coniferous species, at least in this region. The effect of earlier spring tended to be about twice as large when annual rather than springtime flux integrals were considered. This result is suggestive of both immediate and lagged effects of earlier spring onset on ecosystem C cycling, perhaps as a result of accelerated N cycling

Potential and Limitations of Low-Cost Unmanned Aerial Systems for Monitoring Altitudinal Vegetation Phenology in the Tropics

Science.gov (United States)

Silva, T. S. F.; Torres, R. S.; Morellato, P.

2017-12-01

Vegetation phenology is a key component of ecosystem function and biogeochemical cycling, and highly susceptible to climatic change. Phenological knowledge in the tropics is limited by lack of monitoring, traditionally done by laborious direct observation. Ground-based digital cameras can automate daily observations, but also offer limited spatial coverage. Imaging by low-cost Unmanned Aerial Systems (UAS) combines the fine resolution of ground-based methods with and unprecedented capability for spatial coverage, but challenges remain in producing color-consistent multitemporal images. We evaluated the applicability of multitemporal UAS imaging to monitor phenology in tropical altitudinal grasslands and forests, answering: 1) Can very-high resolution aerial photography from conventional digital cameras be used to reliably monitor vegetative and reproductive phenology? 2) How is UAS monitoring affected by changes in illumination and by sensor physical limitations? We flew imaging missions monthly from Feb-16 to Feb-17, using a UAS equipped with an RGB Canon SX260 camera. Flights were carried between 10am and 4pm, at 120-150m a.g.l., yielding 5-10cm spatial resolution. To compensate illumination changes caused by time of day, season and cloud cover, calibration was attempted using reference targets and empirical models, as well as color space transformations. For vegetative phenological monitoring, multitemporal response was severely affected by changes in illumination conditions, strongly confounding the phenological signal. These variations could not be adequately corrected through calibration due to sensor limitations. For reproductive phenology, the very-high resolution of the acquired imagery allowed discrimination of individual reproductive structures for some species, and its stark colorimetric differences to vegetative structures allowed detection of the reproductive timing on the HSV color space, despite illumination effects. We conclude that reliable

Temporal analysis of vegetation indices related to biophysical parameters using Sentinel 2A images to estimate maize production

Science.gov (United States)

Macedo, Lucas Saran; Kawakubo, Fernando Shinji

2017-10-01

Agricultural production is one of the most important Brazilian economic activities accounting for about 21,5% of total Gross Domestic Product. In this scenario, the use of satellite images for estimating biophysical parameters along the phenological development of agricultural crops allows the conclusion about the sanity of planting and helps the projection on design production trends. The objective of this study is to analyze the temporal patterns and variation of six vegetion indexes obtained from the bands of Sentinel 2A satellite, associated with greenness (NDVI and ClRE), senescence (mARI and PSRI) and water content (DSWI and NDWI) to estimate maize production. The temporal pattern of the indices was analyzed in function of productivity data collected in-situ. The results obtained evidenced the importance of the SWIR and Red Edge ranges with Pearson correlation values of the temporal mean for NDWI 0.88 and 0.76 for CLRE.

Introducing the VISAGE project - Visualization for Integrated Satellite, Airborne, and Ground-based data Exploration

Science.gov (United States)

Gatlin, P. N.; Conover, H.; Berendes, T.; Maskey, M.; Naeger, A. R.; Wingo, S. M.

2017-12-01

A key component of NASA's Earth observation system is its field experiments, for intensive observation of particular weather phenomena, or for ground validation of satellite observations. These experiments collect data from a wide variety of airborne and ground-based instruments, on different spatial and temporal scales, often in unique formats. The field data are often used with high volume satellite observations that have very different spatial and temporal coverage. The challenges inherent in working with such diverse datasets make it difficult for scientists to rapidly collect and analyze the data for physical process studies and validation of satellite algorithms. The newly-funded VISAGE project will address these issues by combining and extending nascent efforts to provide on-line data fusion, exploration, analysis and delivery capabilities. A key building block is the Field Campaign Explorer (FCX), which allows users to examine data collected during field campaigns and simplifies data acquisition for event-based research. VISAGE will extend FCX's capabilities beyond interactive visualization and exploration of coincident datasets, to provide interrogation of data values and basic analyses such as ratios and differences between data fields. The project will also incorporate new, higher level fused and aggregated analysis products from the System for Integrating Multi-platform data to Build the Atmospheric column (SIMBA), which combines satellite and ground-based observations into a common gridded atmospheric column data product; and the Validation Network (VN), which compiles a nationwide database of coincident ground- and satellite-based radar measurements of precipitation for larger scale scientific analysis. The VISAGE proof-of-concept will target "golden cases" from Global Precipitation Measurement Ground Validation campaigns. This presentation will introduce the VISAGE project, initial accomplishments and near term plans.

Effects of recent warm and cold spells on European plant phenology

Science.gov (United States)

Menzel, A.; Estrella, N.; Seifert, H.

2009-04-01

Numerous studies have concurrently documented a progressively earlier start for vegetation activity in spring and a lengthening of the growing season during the last 2 to 5 decades in the temperate northern hemisphere. In contrast to climatic factors influencing autumn phenology, the climate signal controlling spring and summer phenology is fairly well understood: nearly all phenophases correlate with temperatures in the preceding 1 to 3 months. The changes currently experienced by emergence of vegetation may reach 6 to 8 d per °C. But how will this well-known, often linearly described relationship change in case of more frequent and more stronger temperature extremes? We thus studied the temperature response of European phenological records to cold and warm spells using the COST725 data base (www.cost725.org). We restricted our analysis to the time period 1951-2006 due to the relatively better coverage of Europe by phenological records. Up to now, 20 European countries contributed more than 7 Mio. phenological observations to this data base including 64 species and 22 different phases. The phenological observations compiled originated from different sources and phenological networks. Unfortunately there is no entire coverage and the data are very lumped. Cold and warm spells were identified using daily mean temperature data (1951-2006) on a 0.5° grid for Europe provided by the EU-FP6 project ENSEMBLES (http://www.ensembles-eu.org, http://eca.knmi.nl). The study area covered Europe and was limited to 40°E. For the whole study period, mean monthly and seasonal mean temperatures well as the corresponding standard deviations were calculated for each grid point. The annual monthly or seasonal temperature at a grid point was defined as cold (very cold, warm, very warm) by its deviation from the long-term average (more than 1.5 or 3sd, respectively). Warm and cold spells were selected when either the percentages of crossing 1.5sd were greater than 50% for the total

The CACAO Method for Smoothing, Gap Filling, and Characterizing Seasonal Anomalies in Satellite Time Series

Science.gov (United States)

Verger, Aleixandre; Baret, F.; Weiss, M.; Kandasamy, S.; Vermote, E.

2013-01-01

Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction.

Ground test of satellite constellation based quantum communication

OpenAIRE

Liao, Sheng-Kai; Yong, Hai-Lin; Liu, Chang; Shentu, Guo-Liang; Li, Dong-Dong; Lin, Jin; Dai, Hui; Zhao, Shuang-Qiang; Li, Bo; Guan, Jian-Yu; Chen, Wei; Gong, Yun-Hong; Li, Yang; Lin, Ze-Hong; Pan, Ge-Sheng

2016-01-01

Satellite based quantum communication has been proven as a feasible way to achieve global scale quantum communication network. Very recently, a low-Earth-orbit (LEO) satellite has been launched for this purpose. However, with a single satellite, it takes an inefficient 3-day period to provide the worldwide connectivity. On the other hand, similar to how the Iridium system functions in classic communication, satellite constellation (SC) composed of many quantum satellites, could provide global...

Seasonal changes in camera-based indices from an open canopy black spruce forest in Alaska, and comparison with indices from a closed canopy evergreen coniferous forest in Japan

Science.gov (United States)

Nagai, Shin; Nakai, Taro; Saitoh, Taku M.; Busey, Robert C.; Kobayashi, Hideki; Suzuki, Rikie; Muraoka, Hiroyuki; Kim, Yongwon

2013-06-01

Evaluation of the carbon, water, and energy balances in evergreen coniferous forests requires accurate in situ and satellite data regarding their spatio-temporal dynamics. Daily digital camera images can be used to determine the relationships among phenology, gross primary productivity (GPP), and meteorological parameters, and to ground-truth satellite observations. In this study, we examine the relationship between seasonal variations in camera-based canopy surface indices and eddy-covariance-based GPP derived from field studies in an Alaskan open canopy black spruce forest and in a Japanese closed canopy cedar forest. The ratio of the green digital number to the total digital number, hue, and GPP showed a bell-shaped seasonal profile at both sites. Canopy surface images for the black spruce forest and cedar forest mainly detected seasonal changes in vegetation on the floor of the forest and in the tree canopy, respectively. In contrast, the seasonal cycles of the ratios of the red and blue digital numbers to the total digital numbers differed between the two sites, possibly due to differences in forest structure and leaf color. These results suggest that forest structural characteristics, such as canopy openness and seasonal forest-floor changes, should be considered during continuous observations of phenology in evergreen coniferous forests.

Connecting Satellite-Based Precipitation Estimates to Users

Science.gov (United States)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric

2018-01-01

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

Application of Near-Surface Remote Sensing and computer algorithms in evaluating impacts of agroecosystem management on Zea mays (corn) phenological development in the Platte River - High Plains Aquifer Long Term Agroecosystem Research Network field sites.

Science.gov (United States)

Okalebo, J. A.; Das Choudhury, S.; Awada, T.; Suyker, A.; LeBauer, D.; Newcomb, M.; Ward, R.

2017-12-01

The Long-term Agroecosystem Research (LTAR) network is a USDA-ARS effort that focuses on conducting research that addresses current and emerging issues in agriculture related to sustainability and profitability of agroecosystems in the face of climate change and population growth. There are 18 sites across the USA covering key agricultural production regions. In Nebraska, a partnership between the University of Nebraska - Lincoln and ARD/USDA resulted in the establishment of the Platte River - High Plains Aquifer LTAR site in 2014. The site conducts research to sustain multiple ecosystem services focusing specifically on Nebraska's main agronomic production agroecosystems that comprise of abundant corn, soybeans, managed grasslands and beef production. As part of the national LTAR network, PR-HPA participates and contributes near-surface remotely sensed imagery of corn, soybean and grassland canopy phenology to the PhenoCam Network through high-resolution digital cameras. This poster highlights the application, advantages and usefulness of near-surface remotely sensed imagery in agroecosystem studies and management. It demonstrates how both Infrared and Red-Green-Blue imagery may be applied to monitor phenological events as well as crop abiotic stresses. Computer-based algorithms and analytic techniques proved very instrumental in revealing crop phenological changes such as green-up and tasseling in corn. This poster also reports the suitability and applicability of corn-derived computer based algorithms for evaluating phenological development of sorghum since both crops have similarities in their phenology; with sorghum panicles being similar to corn tassels. This later assessment was carried out using a sorghum dataset obtained from the Transportation Energy Resources from Renewable Agriculture Phenotyping Reference Platform project, Maricopa Agricultural Center, Arizona.

Results of a first look into the Austrian animal phenological records

Energy Technology Data Exchange (ETDEWEB)

Scheifinger, H.; Koch, E. [Central Inst. for Meteorology and Geodynamics, Vienna (Austria); Winkler, H. [Konrad Lorenz Inst. for Ethology, Vienna (Austria)

2005-04-01

The year to year variability and trends of animal phenological phases (honey bee, cockchafer, 3 butterfly species, swallow and cuckoo) of the Austrian phenological observational network were related to each other and to mean monthly temperatures over the time period 1951-1998. Insect phases were well correlated with each other (r{sup 2} = 0.4 to 0.6) and with temperature (r{sup 2} = 0.25 to 0.55), whereas both bird phases were only well correlated with each other (r{sup 2} = 0.57), but showed low common variance values with temperature and with other animal phases. The slope of the temperature-pheno regression, also termed as temperature sensitivity of the phenological phase, was high in the case of the insect phases (-3 to -5 days/ C), but low in the cases of both bird phases (about -1 days/ C). All animal phenological time series showed a trend towards later occurrence dates. The trends of the bird phases were even significant (p<0.1). There was a marked discrepancy between the trends of all animal phenological and temperature time series, especially between the insects and temperature: the mean temperature time series of February, March and April with the highest common variance with the insect phases showed a strongly increasing trend (0.027 C/year), whereas the first appearance dates of the insects tended to occur later (0.06 to 0.15 days/year). Both bird phases correlated weakly with the mean April temperature (r{sup 2} about 0.1). The temperature trend of April was 0.0003 C/year, whereas the trend of the bird phases was 0.2 days/year for the cuckoo and 0.25 days/year for the swallow. From these observations we conclude that a strong temperature sensitivity of the phenological phase based on the year to year variability (in days/ C) does not necessarily result in corresponding trends of temperature and phenological phase. A strong trend of non-atmospheric factors such as population density influencing the animal phases is suspected. Factors other than local

EcoIS: An image serialization library for plot-based plant flowering phenology

DEFF Research Database (Denmark)

Granados, Joel A.; Bonnet, Philippe; Hansen, Lars Hostrup

2013-01-01

they are produced by introducing an open source Python (www.python.org) library called EcoIS that creates image series from unaligned pictures of specially equipped plots. We use EcoIS to sample flowering phenology plots in a high arctic environment and create image series that later generate phenophase counts...

Improving carbon model phenology using data assimilation

Science.gov (United States)

Exrayat, Jean-François; Smallman, T. Luke; Bloom, A. Anthony; Williams, Mathew

2015-04-01

Carbon cycle dynamics is significantly impacted by ecosystem phenology, leading to substantial seasonal and inter-annual variation in the global carbon balance. Representing inter-annual variability is key for predicting the response of the terrestrial ecosystem to climate change and disturbance. Existing terrestrial ecosystem models (TEMs) often struggle to accurately simulate observed inter-annual variability. TEMs often use different phenological models based on plant functional type (PFT) assumptions. Moreover, due to a high level of computational overhead in TEMs they are unable to take advantage of globally available datasets to calibrate their models. Here we describe the novel CARbon DAta MOdel fraMework (CARDAMOM) for data assimilation. CARDAMOM is used to calibrate the Data Assimilation Linked Ecosystem Carbon version 2 (DALEC2) model using Bayes' Theorem within a Metropolis Hastings - Markov Chain Monte Carlo (MH-MCMC). CARDAMOM provides a framework which combines knowledge from observations, such as remotely sensed LAI, and heuristic information in the form of Ecological and Dynamical Constraints (EDCs). The EDCs are representative of real world processes and constrain parameter interdependencies and constrain carbon dynamics. We used CARDAMOM to bring together globally spanning datasets of LAI and the DALEC2 and DALEC2-GSI models. These analyses allow us to investigate the sensitivity ecosystem processes to the representation of phenology. DALEC2 uses an analytically solved model of phenology which is invariant between years. In contrast DALEC2-GSI uses a growing season index (GSI) calculated as a function of temperature, vapour pressure deficit (VPD) and photoperiod to calculate bud-burst and leaf senescence, allowing the model to simulate inter-annual variability in response to climate. Neither model makes any PFT assumptions about the phenological controls of a given ecosystem, allowing the data alone to determine the impact of the meteorological

Synergistic Use of Citizen Science and Remote Sensing for Continental-Scale Measurements of Forest Tree Phenology

Directory of Open Access Journals (Sweden)

Andrew J. Elmore

2016-06-01

Full Text Available There is great potential value in linking geographically dispersed multitemporal observations collected by lay volunteers (or “citizen scientists” with remotely-sensed observations of plant phenology, which are recognized as useful indicators of climate change. However, challenges include a large mismatch in spatial scale and diverse sources of uncertainty in the two measurement types. These challenges must be overcome if the data from each source are to be compared and jointly used to understand spatial and temporal variation in phenology, or if remote observations are to be used to predict ground-based observations. We investigated the correlation between land surface phenology derived from Moderate Resolution Imaging Spectrometer (MODIS data and citizen scientists’ phenology observations from the USA National Phenology Network (NPN. The volunteer observations spanned 2004 to 2013 and represented 25 plant species and nine phenophases. We developed quality control procedures that removed observations outside of an a priori determined acceptable period and observations that were made more than 10 days after a preceding observation. We found that these two quality control steps improved the correlation between ground- and remote-observations, but the largest improvement was achieved when the analysis was restricted to forested MODIS pixels. These results demonstrate a high degree of correlation between the phenology of individual trees (particularly dominant forest trees such as quaking aspen, white oak, and American beech and the phenology of the surrounding forested landscape. These results provide helpful guidelines for the joint use of citizen scientists’ observations and remote sensing phenology in work aimed at understanding continental scale variation and temporal trends.

Flower power: tree flowering phenology as a settlement cue for migrating birds.

Science.gov (United States)

McGrath, Laura J; van Riper, Charles; Fontaine, Joseph J

2009-01-01

1. Neotropical migrant birds show a clear preference for stopover habitats with ample food supplies; yet, the proximate cues underlying these decisions remain unclear. 2. For insectivorous migrants, cues associated with vegetative phenology (e.g. flowering, leaf flush, and leaf loss) may reliably predict the availability of herbivorous arthropods. Here we examined whether migrants use the phenology of five tree species to choose stopover locations, and whether phenology accurately predicts food availability. 3. Using a combination of experimental and observational evidence, we show migrant populations closely track tree phenology, particularly the flowering phenology of honey mesquite (Prosopis glandulosa), and preferentially forage in trees with more flowers. Furthermore, the flowering phenology of honey mesquite reliably predicts overall arthropod abundance as well as the arthropods preferred by migrants for food. 4. Together, these results suggest that honey mesquite flowering phenology is an important cue used by migrants to assess food availability quickly and reliably, while in transit during spring migration.

Phenology Atlas of Czechia in preparation - aim & content

Science.gov (United States)

Hajkova, L.; Nekovar, J.; Novak, M.; Richterova, D.

2009-09-01

The main task is to create Phenology Atlas of Czechia for the period 1991 - 2010 by using geographic information systems. The general outputs will be maps (average phenophase onset at different altitudes), graphs (evaluation of phenophase onset in time) and tables (statistical results) with text, picture and botanical specification. The publication will be divided into 6 main chapters (Introduction, Phenology in Czechia & Europe, Methodology of observation, Field crops & Fruit trees & Wild plants, Phenology regionalisation, Temporal and Spatial variability). The essantial emphasis will be enforced on wild plants especially allergology important plants and phenophases. CHMI phenological and meteorological data will be used as an input data. This publication will be allocated for general public, supposed size B4, 270 - 300 pages. The research project is proposed for 3 years (2009 - 2011). In the presentation will be given several examples of Atlas content (Norway Spruce and Birch phenophases from Transaction of CHMI Nr.50, 2007).

Reproductive phenology of coastal plain Atlantic forest vegetation: comparisons from seashore to foothills.

Science.gov (United States)

Staggemeier, Vanessa Graziele; Morellato, Leonor Patrícia Cerdeira

2011-11-01

The diversity of tropical forest plant phenology has called the attention of researchers for a long time. We continue investigating the factors that drive phenological diversity on a wide scale, but we are unaware of the variation of plant reproductive phenology at a fine spatial scale despite the high spatial variation in species composition and abundance in tropical rainforests. We addressed fine scale variability by investigating the reproductive phenology of three contiguous vegetations across the Atlantic rainforest coastal plain in Southeastern Brazil. We asked whether the vegetations differed in composition and abundance of species, the microenvironmental conditions and the reproductive phenology, and how their phenology is related to regional and local microenvironmental factors. The study was conducted from September 2007 to August 2009 at three contiguous sites: (1) seashore dominated by scrub vegetation, (2) intermediary covered by restinga forest and (3) foothills covered by restinga pre-montane transitional forest. We conducted the microenvironmental, plant and phenological survey within 30 transects of 25 m × 4 m (10 per site). We detected significant differences in floristic, microenvironment and reproductive phenology among the three vegetations. The microenvironment determines the spatial diversity observed in the structure and composition of the flora, which in turn determines the distinctive flowering and fruiting peaks of each vegetation (phenological diversity). There was an exchange of species providing flowers and fruits across the vegetation complex. We conclude that plant reproductive patterns as described in most phenological studies (without concern about the microenvironmental variation) may conceal the fine scale temporal phenological diversity of highly diverse tropical vegetation. This phenological diversity should be taken into account when generating sensor-derived phenologies and when trying to understand tropical vegetation

A WebGIS system on the base of satellite data processing system for marine application

Science.gov (United States)

Gong, Fang; Wang, Difeng; Huang, Haiqing; Chen, Jianyu

2007-10-01

From 2002 to 2004, a satellite data processing system for marine application had been built up in State Key Laboratory of Satellite Ocean Environment Dynamics (Second Institute of Oceanography, State Oceanic Administration). The system received satellite data from TERRA, AQUA, NOAA-12/15/16/17/18, FY-1D and automatically generated Level3 products and Level4 products(products of single orbit and merged multi-orbits products) deriving from Level0 data, which is controlled by an operational control sub-system. Currently, the products created by this system play an important role in the marine environment monitoring, disaster monitoring and researches. Now a distribution platform has been developed on this foundation, namely WebGIS system for querying and browsing of oceanic remote sensing data. This system is based upon large database system-Oracle. We made use of the space database engine of ArcSDE and other middleware to perform database operation in addition. J2EE frame was adopted as development model, and Oracle 9.2 DBMS as database background and server. Simply using standard browsers(such as IE6.0), users can visit and browse the public service information that provided by system, including browsing for oceanic remote sensing data, and enlarge, contract, move, renew, traveling, further data inquiry, attribution search and data download etc. The system is still under test now. Founding of such a system will become an important distribution platform of Chinese satellite oceanic environment products of special topic and category (including Sea surface temperature, Concentration of chlorophyll, and so on), for the exaltation of satellite products' utilization and promoting the data share and the research of the oceanic remote sensing platform.

Geographically weighted regression based methods for merging satellite and gauge precipitation

Science.gov (United States)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

On the uncertainty of phenological responses to climate change, and implications for a terrestrial biosphere model

Directory of Open Access Journals (Sweden)

M. Migliavacca

2012-06-01

degree of warming varied between 2.2 days °C⁻¹ and 5.2 days °C⁻¹ depending on model structure.

We quantified the impact of uncertainties in bud-burst forecasts on simulated photosynthetic CO₂ uptake and evapotranspiration (ET using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of forest seasonality, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP and ET of 9.6% and 2.9%, respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET.

For phenology models, differences among future climate scenarios (i.e. driver represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of ecosystem processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

Directory of Open Access Journals (Sweden)

G. T. Ayehu

2018-04-01

Full Text Available Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor ground observations or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3 and the African Rainfall Climatology (ARC 2 products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD  =  0.99, 1.00 and measure of volumetric rainfall (VHI  =  1.00, 1.00, the highest correlation coefficients (r =  0.81, 0.88, better bias values (0.96, 0.96, and the lowest RMSE (28.45 mm dekad−1, 59.03 mm month−1 than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale, although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance

Effects of an accidental dry-season fire on the reproductive phenology of two Neotropical savanna shrubs.

Science.gov (United States)

Dodonov, P; Zanelli, C B; Silva-Matos, D M

2017-10-30

Fire is a recurrent disturbance in savanna vegetation and savanna species are adapted to it. Even so, fire may affect various aspects of plant ecology, including phenology. We studied the effects of a spatially heterogeneous fire on the reproductive phenology of two dominant woody plant species, Miconia albicans (Melastomataceae) and Schefflera vinosa (Araliaceae), in a savanna area in South-eastern Brazil. The study site was partially burnt by a dry-season accidental fire in August 2006, and we monitored the phenolology of 30 burnt and 30 unburnt individuals of each species between September 2007 and September 2008. We used restricted randomizations to assess phenological differences between the burnt and unburnt individuals. Fire had negative effects on the phenology of M. albicans, with a smaller production of reproductive structures in general and of floral buds, total fruits, and ripe fruits in burnt plants. All unburnt but only 16% of the burnt M. albicans plants produced ripe fruits during the study. Fire effects on S. vinosa were smaller, but there was a greater production of floral buds and fruits (but not ripe fruits) by burnt plants; approximately 90% of the individuals of S. vinosa produced ripe fruits during the study, regardless of having been burnt or not. The differences between the two species may be related to S. vinosa's faster growth and absence from the seed bank at the study site, whereas M. albicans grows more slowly and is dominant in the seed bank.

Validation of an Innovative Satellite-Based UV Dosimeter

Science.gov (United States)

Morelli, Marco; Masini, Andrea; Simeone, Emilio; Khazova, Marina

2016-08-01

We present an innovative satellite-based UV (ultraviolet) radiation dosimeter with a mobile app interface that has been validated by exploiting both ground-based measurements and an in-vivo assessment of the erythemal effects on some volunteers having a controlled exposure to solar radiation.Both validations showed that the satellite-based UV dosimeter has a good accuracy and reliability needed for health-related applications.The app with this satellite-based UV dosimeter also includes other related functionalities such as the provision of safe sun exposure time updated in real-time and end exposure visual/sound alert. This app will be launched on the global market by siHealth Ltd in May 2016 under the name of "HappySun" and available both for Android and for iOS devices (more info on http://www.happysun.co.uk).Extensive R&D activities are on-going for further improvement of the satellite-based UV dosimeter's accuracy.

Satellite Imagery Production and Processing Using Apache Hadoop

Science.gov (United States)

Hill, D. V.; Werpy, J.

2011-12-01

The United States Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center Land Science Research and Development (LSRD) project has devised a method to fulfill its processing needs for Essential Climate Variable (ECV) production from the Landsat archive using Apache Hadoop. Apache Hadoop is the distributed processing technology at the heart of many large-scale, processing solutions implemented at well-known companies such as Yahoo, Amazon, and Facebook. It is a proven framework and can be used to process petabytes of data on thousands of processors concurrently. It is a natural fit for producing satellite imagery and requires only a few simple modifications to serve the needs of science data processing. This presentation provides an invaluable learning opportunity and should be heard by anyone doing large scale image processing today. The session will cover a description of the problem space, evaluation of alternatives, feature set overview, configuration of Hadoop for satellite image processing, real-world performance results, tuning recommendations and finally challenges and ongoing activities. It will also present how the LSRD project built a 102 core processing cluster with no financial hardware investment and achieved ten times the initial daily throughput requirements with a full time staff of only one engineer. Satellite Imagery Production and Processing Using Apache Hadoop is presented by David V. Hill, Principal Software Architect for USGS LSRD.

Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

Directory of Open Access Journals (Sweden)

Gijs Simons

2016-03-01

Full Text Available With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P and land use/land cover (LULC is currently being expanded with the application of actual evapotranspiration (ETact algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products.

Method for validating cloud mask obtained from satellite measurements using ground-based sky camera.

Science.gov (United States)

Letu, Husi; Nagao, Takashi M; Nakajima, Takashi Y; Matsumae, Yoshiaki

2014-11-01

Error propagation in Earth's atmospheric, oceanic, and land surface parameters of the satellite products caused by misclassification of the cloud mask is a critical issue for improving the accuracy of satellite products. Thus, characterizing the accuracy of the cloud mask is important for investigating the influence of the cloud mask on satellite products. In this study, we proposed a method for validating multiwavelength satellite data derived cloud masks using ground-based sky camera (GSC) data. First, a cloud cover algorithm for GSC data has been developed using sky index and bright index. Then, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived cloud masks by two cloud-screening algorithms (i.e., MOD35 and CLAUDIA) were validated using the GSC cloud mask. The results indicate that MOD35 is likely to classify ambiguous pixels as "cloudy," whereas CLAUDIA is likely to classify them as "clear." Furthermore, the influence of error propagations caused by misclassification of the MOD35 and CLAUDIA cloud masks on MODIS derived reflectance, brightness temperature, and normalized difference vegetation index (NDVI) in clear and cloudy pixels was investigated using sky camera data. It shows that the influence of the error propagation by the MOD35 cloud mask on the MODIS derived monthly mean reflectance, brightness temperature, and NDVI for clear pixels is significantly smaller than for the CLAUDIA cloud mask; the influence of the error propagation by the CLAUDIA cloud mask on MODIS derived monthly mean cloud products for cloudy pixels is significantly smaller than that by the MOD35 cloud mask.

Three Decades of Remote Sensing Based Tropical Forests Phenological Patterns and Trends

Science.gov (United States)

Didan, K.

2010-12-01

The faint climatic seasonality of tropical rain forests is believed to be the reason these biomes lack strong and detectable seasonality. Forest seasonality is a critical element of ecosystem functions. It moderates the echo-hydrology, carbon, and nutrient exchange of the area. While deciduous forests exhibit distinct and strong seasonality, tropical forests do not, yet they play a large role in the cycling of energy and mass. Tropical forests represent a large percentage of vegetated land and their importance to the Earth system stems from their biological diversity, their habitat role, their role in regulating global weather, and the role they play in carbon storage. While Tropical forests are well buffered by their sheer size, their vulnerability to climate change is exacerbated by the human pressure. All of this begs the questions of what are the patterns and characteristic of tropical forests phenology and are there any detectable trends over the last three decades of synoptic remote sensing. These three decades comprise different episodes of droughts and an ever increasing level of human encroachment. In so far understanding the function and dynamic of these biomes, field studies continue to play a major role, but synoptic remote sensing is emerging as a viable tool to addressing the spatial and temporal scale associated with this problem. Recent studies of Brazilian rainforest with synoptic remote sensing point to a sizable seasonal signal coincident with the dry season. However, these studies were not extensive in time or space and did not look at other rainforests. Using data from AVHRR and MODIS, we generated a 30 year record of the 2 bands Enhance Vegetation Index (EVI2), and analyzed the patterns and trends of land surface phenology across all tropical forests using the homogeneous phenology cluster approach. We chose EVI because of its superior performance over these dense forests, and we selected the homogeneous phenology cluster approach to abate the

A 6-year-long manipulation with soil warming and canopy nitrogen additions does not affect xylem phenology and cell production of mature black spruce

Directory of Open Access Journals (Sweden)

Madjelia Cangre Ebou eDAO

2015-11-01

Full Text Available The predicted climate warming and increased atmospheric inorganic nitrogen deposition are expected to have dramatic impacts on plant growth. However, the extent of these effects and their interactions remains unclear for boreal forest trees. The aim of this experiment was to investigate the effects of increased soil temperature and nitrogen (N depositions on stem intra-annual growth of two mature stands of black spruce [Picea mariana (Mill. BSP] in Quebec, Canada. During 2008-2013, the soil around mature trees was warmed up by 4 °C with heating cables during the growing season and precipitations containing three times the current inorganic N concentration were added by frequent canopy applications. Xylem phenology and cell production were monitored weekly from April to October. The 6-year-long experiment performed in two sites at different altitude showed no substantial effect of warming and N-depositions on xylem phenological phases of cell enlargement, wall thickening and lignification. Cell production, in terms of number of tracheids along the radius, also did not differ significantly and followed the same patterns in control and treated trees. These findings allowed the hypothesis of a medium-term effect of soil warming and N depositions on the growth of mature black spruce to be rejected.

Phenological responses of juvenile pecan and white oak on an upland site

Science.gov (United States)

D. M. Burner; D. K. Brauer; J. L. Snider; C. A. Harrington; P. A. Moore

2014-01-01

Pecan (Carya illinoiensis) and white oak (Quercus alba) produce multiple products and wildlife values, but their phenological responses to N fertilization have not been well characterized. We compared tree growth at planting and for six consecutive growing seasons during establishment (2003–2008, Test 1), and determined if...

Phenology for science, resource management, decision making, and education

Science.gov (United States)

Nolan, V.P.; Weltzin, J.F.

2011-01-01

Fourth USA National Phenology Network (USA-NPN) Research Coordination Network (RCN) Annual Meeting and Stakeholders Workshop; Milwaukee, Wisconsin, 21-22 September 2010; Phenology, the study of recurring plant and animal life cycle events, is rapidly emerging as a fundamental approach for understanding how ecological systems respond to environmental variation and climate change. The USA National Phenology Network (USA-NPN; http://www.usanpn.org) is a large-scale network of governmental and nongovernmental organizations, academic institutions, resource management agencies, and tribes. The network is dedicated to conducting and promoting repeated and integrated plant and animal phenological observations, identifying linkages with other relevant biological and physical data sources, and developing and distributing the tools to analyze these data at local to national scales. The primary goal of the USA-NPN is to improve the ability of decision makers to design strategies for climate adaptation.

Assessment of satellite and model derived long term solar radiation for spatial crop models: A case study using DSSAT in Andhra Pradesh

Directory of Open Access Journals (Sweden)

Anima Biswal

2014-09-01

Full Text Available Crop Simulation models are mathematical representations of the soil plant-atmosphere system that calculate crop growth and yield, as well as the soil and plant water and nutrient balances, as a function of environmental conditions and crop management practices on daily time scale. Crop simulation models require meteorological data as inputs, but data availability and quality are often problematic particularly in spatialising the model for a regional studies. Among these weather variables, daily total solar radiation and air temperature (Tmax and Tmin have the greatest influence on crop phenology and yield potential. The scarcity of good quality solar radiation data can be a major limitation to the use of crop models. Satellite-sensed weather data have been proposed as an alternative when weather station data are not available. These satellite and modeled based products are global and, in general, contiguous in time and also been shown to be accurate enough to provide reliable solar and meteorological resource data over large regions where surface measurements are sparse or nonexistent. In the present study, an attempt was made to evaluate the satellite and model derived daily solar radiation for simulating groundnut crop growth in the rainfed distrcits of Andhra Pradesh. From our preliminary investigation, we propose that satellite derived daily solar radiation data could be used along with ground observed temperature and rainfall data for regional crop simulation studies where the information on ground observed solar radiation is missing or not available.

Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity

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S. A. Henson

2010-02-01

Full Text Available Global climate change is predicted to alter the ocean's biological productivity. But how will we recognise the impacts of climate change on ocean productivity? The most comprehensive information available on its global distribution comes from satellite ocean colour data. Now that over ten years of satellite-derived chlorophyll and productivity data have accumulated, can we begin to detect and attribute climate change-driven trends in productivity? Here we compare recent trends in satellite ocean colour data to longer-term time series from three biogeochemical models (GFDL, IPSL and NCAR. We find that detection of climate change-driven trends in the satellite data is confounded by the relatively short time series and large interannual and decadal variability in productivity. Thus, recent observed changes in chlorophyll, primary production and the size of the oligotrophic gyres cannot be unequivocally attributed to the impact of global climate change. Instead, our analyses suggest that a time series of ~40 years length is needed to distinguish a global warming trend from natural variability. In some regions, notably equatorial regions, detection times are predicted to be shorter (~20–30 years. Analysis of modelled chlorophyll and primary production from 2001–2100 suggests that, on average, the climate change-driven trend will not be unambiguously separable from decadal variability until ~2055. Because the magnitude of natural variability in chlorophyll and primary production is larger than, or similar to, the global warming trend, a consistent, decades-long data record must be established if the impact of climate change on ocean productivity is to be definitively detected.

What You See Depends on Your Point of View: Comparison of Greenness Indices Across Spatial and Temporal Scales and What That Means for Mule Deer Migration and Fitness

Science.gov (United States)

Miller, B. W.; Chong, G.; Steltzer, H.; Aikens, E.; Morisette, J. T.; Talbert, C.; Talbert, M.; Shory, R.; Krienert, J. M.; Gurganus, D.

2015-12-01

Climate change models for the north­ern Rocky Mountains predict warming and changes in water availability that may alter vegetation. Changes to vegetation may include timing of plant life-history events, or phenology, such as green-up, flower­ing, and senescence. These changes could make forage available earlier in the growing season, but shifts in phenol­ogy may also result in earlier senescence (die-off or dormancy) and reduced overall production. Greenness indices such as the normalized difference vegetation index (NDVI) are regularly used to quantify greenness over large areas using remotely sensed reflectance data. The timing and scale of current satellite data, however, may be insufficient to capture fine-scale differences in phenology that are important indicators of habitat quality. The Wyoming Range Mule Deer herd is one of the largest in the west but it declined precipitously in the early 1990s and has not recovered. Accurate measurement of greenness over space and time would allow managers to better understand the role of plant phenology and productivity in mule deer population dynamics, for example. To connect spatial and temporal patterns of plant productivity with habitat quality, we compare greenness patterns (MODIS data) with migratory mule deer movement (GPS collars). Sagebrush systems provide winter habitat for mule deer. To understand sagebrush phenology as an indicator of productivity, we constructed NDVI time series and compared dates of phenological stages and magnitudes of greenness from three perspectives: at-surface/species-specific (mantis sensors: downward looking, <1m above vegetation); near surface/site-specific (PhenoCam: oblique, 2m); and satellite/landscape-scale (varied platforms). Greenness indices from these sensors contribute unique insights to understanding vegetation phenology, snow cover and reflectance. Understanding phenology and productivity at multiple scales can help guide resource management decisions related to

Recent history of large-scale ecosystem disturbances in North America derived from the AVHRR satellite record.

Science.gov (United States)

Christopher Potter; Tan Pang-Ning; Vipin Kumar; Chris Kucharik; Steven Klooster; Vanessa Genovese; Warren Cohen; Sean. Healey

2005-01-01

Ecosystem structure and function are strongly affected by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the advanced very high resolution radiometer (AVHRR...

A Space Based Solar Power Satellite System

Science.gov (United States)

Engel, J. M.; Polling, D.; Ustamujic, F.; Yaldiz, R.; et al.

2002-01-01

(SPoTS) supplying other satellites with energy. SPoTS is due to be commercially viable and operative in 2020. of Technology designed the SPoTS during a full-time design period of six weeks as a third year final project. The team, organized according to the principles of systems engineering, first conducted a literature study on space wireless energy transfer to select the most suitable candidates for use on the SPoTS. After that, several different system concepts have been generated and evaluated, the most promising concept being worked out in greater detail. km altitude. Each SPoTS satellite has a 50m diameter inflatable solar collector that focuses all received sunlight. Then, the received sunlight is further redirected by means of four pointing mirrors toward four individual customer satellites. A market-analysis study showed, that providing power to geo-stationary communication satellites during their eclipse would be most beneficial. At arrival at geo-stationary orbit, the focused beam has expended to such an extent that its density equals one solar flux. This means that customer satellites can continue to use their regular solar arrays during their eclipse for power generation, resulting in a satellite battery mass reduction. the customer satellites in geo-stationary orbit, the transmitted energy beams needs to be pointed with very high accuracy. Computations showed that for this degree of accuracy, sensors are needed, which are not mainstream nowadays. Therefore further research must be conducted in this area in order to make these high-accuracy-pointing systems commercially attractive for use on the SPoTS satellites around 2020. Total 20-year system lifetime cost for 18 SPoT satellites are estimated at approximately USD 6 billion [FY2001]. In order to compete with traditional battery-based satellite power systems or possible ground based wireless power transfer systems the price per kWh for the customer must be significantly lower than the present one

Greater temperature sensitivity of plant phenology at colder sites

DEFF Research Database (Denmark)

Prevey, Janet; Vellend, Mark; Ruger, Nadja

2017-01-01

Warmer temperatures are accelerating the phenology of organisms around the world. Temperature sensitivity of phenology might be greater in colder, higher latitude sites than in warmer regions, in part because small changes in temperature constitute greater relative changes in thermal balance...

Building capacity for in-situ phenological observation data to support integrated biodiversity information at local to national scales

Science.gov (United States)

Weltzin, J. F.

2016-12-01

Earth observations from a variety of platforms and across a range of scales are required to support research, natural resource management, and policy- and decision-making in a changing world. Integrated earth observation data provides multi-faceted information critical to decision support, vulnerability and change detection, risk assessments, early warning and modeling, simulation and forecasting in the natural resource societal benefit area. The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on phenology - the study of seasonal life-cycle events such as leafing, flowering, reproduction, and migration - as a tool to understand the response of biodiversity to environmental variation and change. USA-NPN provides a hierarchical, national monitoring framework that enables other organizations to leverage the capacity of the Network for their own applications - minimizing investment and duplication of effort - while promoting interoperability and sustainability. Over the last decade, the network has focused on the development of a centralized database for in-situ (ground based) observations of plants and animals, now with 8 M records for the period 1954-present. More recently, we have developed a workflow for the production and validation of spatially gridded phenology products based on models that couple the organismal data with climatological and meteorological data at daily time-steps and relatively fine spatial resolutions ( 2.5 km to 4 km). These gridded data are now ripe for integration with other modeled or earth observation gridded data, e.g., indices of drought impact or land surface reflectance. This greatly broadens capacity to scale organismal observational data to landscapes and regions, and enables novel investigations of biophysical interactions at unprecedented scales, e.g., continental-scale migrations. Sustainability emerges from identification of stakeholder needs, segmentation of

Impact analysis of satellite rainfall products on flow simulations in the Magdalena River Basin, Colombia

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Amr Elgamal

2017-02-01

Full Text Available The Magdalena River is the most important river in Colombia in terms of economic activities and is home to about 77% of the country’s population. The river faces water resources allocation challenges, which require reliable hydrological assessments. However, hydrological analysis and model simulations are hampered by insufficient and uncertain knowledge of the actual rainfall fields. In this research the reliability of groundbased measurements, different satellite products of rainfall and their combinations are tested for their impact on the discharge simulations of the Magdalena River. Two different satellite rainfall products from the Tropical Rainfall Measuring Mission (TRMM, have been compared and merged with the ground-based measurements and their impact on the Magdalena river flows quantified using the Representative Elementary Watershed (REW distributed hydrological model.

Detecting robust signals of interannual variability of gross primary productivity in Asia from multiple terrestrial carbon cycle models and long-term satellite-based vegetation data

Science.gov (United States)

Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.

2014-12-01

Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently

A meta-analysis of cambium phenology and growth: linear and non-linear patterns in conifers of the northern hemisphere

OpenAIRE

Rossi, Sergio; Anfodillo, Tommaso; Čufar, Katarina; Cuny, Henri E.; Deslauriers, Annie; Fonti, Patrick; Frank, David; Gričar, Jožica; Gruber, Andreas; King, Gregory M.; Krause, Cornelia; Morin, Hubert; Oberhuber, Walter; Prislan, Peter; Rathgeber, Cyrille B. K.

2017-01-01

Background and Aims Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-l...

Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

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Tao Yu

2018-02-01

Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

Effects of heavy-metal-contaminated soil on growth, phenology and biomass turnover of Hieracium piloselloides

International Nuclear Information System (INIS)

Ryser, Peter; Sauder, Wendy R.

2006-01-01

The effects of low levels of heavy metals on plant growth, biomass turnover and reproduction were investigated for Hieracium pilosella. Plants were grown for 12 weeks on substrates with different concentrations of heavy metals obtained by diluting contaminated soils with silica sand. To minimize effects of other soil factors, the substrates were limed, fertilized, and well watered. The more metal-contaminated soil the substrate contained, the lower the leaf production rate and the plant mass were, and the more the phenological development was delayed. Flowering phenology was very sensitive to metals. Leaf life span was reduced at the highest and the lowest metal levels, the latter being a result of advanced seed ripening. Even if the effect of low metal levels on plant growth may be small, the delayed and reduced reproduction may have large effects at population, community and ecosystem level, and contribute to rapid evolution of metal tolerance. - Flowering phenology shows a very sensitive response to heavy metal contamination of soils

Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables

Science.gov (United States)

Guillevic, P. C.; Nickeson, J. E.; Roman, M. O.; camacho De Coca, F.; Wang, Z.; Schaepman-Strub, G.

2016-12-01

The Global Climate Observing System (GCOS) has specified the need to systematically produce and validate Essential Climate Variables (ECVs). The Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and in particular its subgroup on Land Product Validation (LPV) is playing a key coordination role leveraging the international expertise required to address actions related to the validation of global land ECVs. The primary objective of the LPV subgroup is to set standards for validation methods and reporting in order to provide traceable and reliable uncertainty estimates for scientists and stakeholders. The Subgroup is comprised of 9 focus areas that encompass 10 land surface variables. The activities of each focus area are coordinated by two international co-leads and currently include leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR), vegetation phenology, surface albedo, fire disturbance, snow cover, land cover and land use change, soil moisture, land surface temperature (LST) and emissivity. Recent additions to the focus areas include vegetation indices and biomass. The development of best practice validation protocols is a core activity of CEOS LPV with the objective to standardize the evaluation of land surface products. LPV has identified four validation levels corresponding to increasing spatial and temporal representativeness of reference samples used to perform validation. Best practice validation protocols (1) provide the definition of variables, ancillary information and uncertainty metrics, (2) describe available data sources and methods to establish reference validation datasets with SI traceability, and (3) describe evaluation methods and reporting. An overview on validation best practice components will be presented based on the LAI and LST protocol efforts to date.

A novel cross-satellite based assessment of the spatio-temporal development of a cyanobacterial harmful algal bloom

Science.gov (United States)

Page, Benjamin P.; Kumar, Abhishek; Mishra, Deepak R.

2018-04-01

As the frequency of cyanobacterial harmful algal blooms (CyanoHABs) become more common in recreational lakes and water supply reservoirs, demand for rapid detection and temporal monitoring will be imminent for effective management. The goal of this study was to demonstrate a novel and potentially operational cross-satellite based protocol for synoptic monitoring of rapidly evolving and increasingly common CyanoHABs in inland waters. The analysis involved a novel way to cross-calibrate a chlorophyll-a (Chl-a) detection model for the Landsat-8 OLI sensor from the relationship between the normalized difference chlorophyll index and the floating algal index derived from Sentinel-2A on a coinciding overpass date during the summer CyanoHAB bloom in Utah Lake. This aided in the construction of a time-series phenology of the Utah Lake CyanoHAB event. Spatio-temporal cyanobacterial density maps from both Sentinel-2A and Landsat-8 sensors revealed that the bloom started in the first week of July 2016 (July 3rd, mean cell count: 9163 cells/mL), reached peak in mid-July (July 15th, mean cell count: 108176 cells/mL), and reduced in August (August 24th, mean cell count: 9145 cells/mL). Analysis of physical and meteorological factors suggested a complex interaction between landscape processes (high surface runoff), climatic conditions (high temperature, high rainfall followed by negligible rainfall, stable wind), and water quality (low water level, high Chl-a) which created a supportive environment for triggering these blooms in Utah Lake. This cross satellite-based monitoring methods can be a great tool for regular monitoring and will reduce the budget cost for monitoring and predicting CyanoHABs in large lakes.

Leo satellite-based telecommunication network concepts

Science.gov (United States)

Aiken, John G.; Swan, Peter A.; Leopold, Ray J.

1991-01-01

Design considerations are discussed for Low Earth Orbit (LEO) satellite based telecommunications networks. The satellites are assumed to be connected to each other via intersatellite links. They are connected to the end user either directly or through gateways to other networks. Frequency reuse, circuit switching, packet switching, call handoff, and routing for these systems are discussed by analogy with terrestrial cellular (mobile radio) telecommunication systems.

Combined impact of climate change, cultivar shift, and sowing date on spring wheat phenology in Northern China

Science.gov (United States)

Xiao, Dengpan; Tao, Fulu; Shen, Yanjun; Qi, Yongqing

2016-08-01

Distinct climate changes since the end of the 1980s have led to clear responses in crop phenology in many parts of the world. This study investigated the trends in the dates of spring wheat phenology in relation to mean temperature for different growth stages. It also analyzed the impacts of climate change, cultivar shift, and sowing date adjustments on phenological events/phases of spring wheat in northern China (NC). The results showed that significant changes have occurred in spring wheat phenology in NC due to climate warming in the past 30 years. Specifically, the dates of anthesis and maturity of spring wheat advanced on average by 1.8 and 1.7 day (10 yr)-1. Moreover, while the vegetative growth period (VGP) shortened at most stations, the reproductive growth period (RGP) prolonged slightly at half of the investigated stations. As a result, the whole growth period (WGP) of spring wheat shortened at most stations. The findings from the Agricultural Production Systems Simulator (APSIM)-Wheat model simulated results for six representative stations further suggested that temperature rise generally shortened the spring wheat growth period in NC. Although the warming trend shortened the lengths of VGP, RGP, and WGP, the shift of new cultivars with high accumulated temperature requirements, to some extent, mitigated and adapted to the ongoing climate change. Furthermore, shifts in sowing date exerted significant impacts on the phenology of spring wheat. Generally, an advanced sowing date was able to lower the rise in mean temperature during the different growth stages (i.e., VGP, RGP, and WGP) of spring wheat. As a result, the lengths of the growth stages should be prolonged. Both measures (cultivar shift and sowing date adjustments) could be vital adaptation strategies of spring wheat to a warming climate, with potentially beneficial effects in terms of productivity.

Communicating Research Through Student Involvement in Phenological Investigations

Science.gov (United States)

Sparrow, E. B.; Kopplin, M.; Gazal, R. M.; Robin, J. H.; Boger, R. A.

2011-12-01

Phenology plays a key role in the environment and ecosystem. Primary and secondary students around the world have been collecting vegetation phenology data and contributing to ongoing scientific investigations. They have increased research capacity by increasing spatial coverage of ground observations that can be useful for validation of remotely sensed data. The green-up and green-down phenology measurement protocols developed at the University of Alaska Fairbanks (UAF) as part of the Global Learning and Observations to Benefit the Environment (GLOBE) program, have been used in more than 250 schools in over 20 countries. In addition to contributing their data, students have conducted their own investigations and presented them at science fairs and symposiums, and international conferences. An elementary school student in Alaska conducted a comprehensive study on the green-down rates of native and introduced trees and shrubs. Her project earned her a one-year college scholarship at UAF. Students from the Model Secondary School for the Deaf in Washington, D. C. and from the Indiana School for the Deaf collaborated on a comparative green-up study, and were chosen to present at an international conference where students from more than 20 countries participated. Similarly, students in Thailand presented at national conferences, their studies such as "The Relationship between Environmental Conditions and Green-down of Teak Trees (Tectona grandis L.)" at Roong Aroon School, Bangkok and "The Comparison of Budburst and Green-up of Leab Trees (Ficus infectoria Roxb.) at Rob Wiang and Mae Khao Tom Sub-district in Chiang Rai Province". Some challenges in engaging students in phenological studies include the mismatch in timing of the start and end of the plant growing season with that of the school year in northern latitudes and the need for scientists and teachers to work with students to ensure accurate measurements. However these are outweighed by benefits to the scientists

Contributions of meteorology to the phenology of cyanobacterial blooms: implications for future climate change.

Science.gov (United States)

Zhang, Min; Duan, Hongtao; Shi, Xiaoli; Yu, Yang; Kong, Fanxiang

2012-02-01

Cyanobacterial blooms are often a result of eutrophication. Recently, however, their expansion has also been found to be associated with changes in climate. To elucidate the effects of climatic variables on the expansion of cyanobacterial blooms in Taihu, China, we analyzed the relationships between climatic variables and bloom events which were retrieved by satellite images. We then assessed the contribution of each climate variable to the phenology of blooms using multiple regression models. Our study demonstrates that retrieving ecological information from satellite images is meritorious for large-scale and long-term ecological research in freshwater ecosystems. Our results show that the phenological changes of blooms at an inter-annual scale are strongly linked to climate in Taihu during the past 23 yr. Cyanobacterial blooms occur earlier and last longer with the increase of temperature, sunshine hours, and global radiation and the decrease of wind speed. Furthermore, the duration increases when the daily averages of maximum, mean, and minimum temperature each exceed 20.3 °C, 16.7 °C, and 13.7 °C, respectively. Among these factors, sunshine hours and wind speed are the primary contributors to the onset of the blooms, explaining 84.6% of their variability over the past 23 yr. These factors are also good predictors of the variability in the duration of annual blooms and determined 58.9% of the variability in this parameter. Our results indicate that when nutrients are in sufficiently high quantities to sustain the formation of cyanobacterial blooms, climatic variables become crucial in predicting cyanobacterial bloom events. Climate changes should be considered when we evaluate how much the amount of nutrients should be reduced in Taihu for lake management. Copyright © 2011 Elsevier Ltd. All rights reserved.

An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

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Margaret Wambui Kimani

2017-05-01

Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

Trends and Variability in Temperature Sensitivity of Lilac Flowering Phenology

Science.gov (United States)

Wang, Huanjiong; Dai, Junhu; Rutishauser, This; Gonsamo, Alemu; Wu, Chaoyang; Ge, Quansheng

2018-03-01

The responses of plant phenology to temperature variability have many consequences for ecological processes, agriculture, forestry, and human health. Temperature sensitivity (ST) of phenology could measure how and to what degree plant could phenologically track climate change. The long-term trends and spatial patterns in ST have been well studied for vegetative phenology such as leaf unfolding, but trends to be expected for reproductive phenology in the future remain unknown. Here we investigate trends and factors driving the temporal variation of ST of first bloom date (FBD). Using the long-term FBD records during 1963-2013 for common lilac (Syringa vulgaris) from 613 stations in Europe, we compared changes in ST from the beginning to the end of the study period. The Spearman partial correlations were used to assess the importance of four influencing factors. The results showed that the temporal changes in ST of FBD varied considerably among time scales. Mean ST decreased significantly by 0.92 days °C-1 from 1963-1972 to 2004-2013 (P plant species in other climates and environments using similar methods to our study.

Relationships between Wood Formation and Cambium Phenology on the Tibetan Plateau during 1960–2014

Directory of Open Access Journals (Sweden)

Minhui He

2018-02-01

Full Text Available The variability of tree stem phenology plays a critical role in determining the productivity of forest ecosystems. Therefore, we aim to identify the relationships between the timings of cambium phenology, and forest growth in terms of tree-ring width over a long-term scale. A meta-analysis was performed that combined the timings of xylem formation, which were calculated by a tree-ring formation model of the VS (Vaganov-Shashkin-oscilloscope during the period 1960–2014, and a tree-ring width series at 20 composite sites on the Tibetan Plateau. Both the start and length of the growing season significantly affected the formation of wood at 70% of the 20 composite sites within the study region. A wider tree ring probably resulted from an earlier start and a longer duration of the growing season. The influence of ending dates on tree-ring width was less evident, and more site-dependent. Weak relationships were identified between the start and end of the growing season at 85% of the composite sites. Compared to the monitoring results, which could only detect the relationships between cambium phenology and xylem cell production from a limited number of trees and years, our long-term relationships deepened such connections, and therefore should be used to improve mechanism models for the accurate evaluating and predicting of wood production and carbon sequestration in forest ecosystems under current and future climate change.

Rainfall frequency analysis for ungauged sites using satellite precipitation products

Science.gov (United States)

Gado, Tamer A.; Hsu, Kuolin; Sorooshian, Soroosh

2017-11-01

The occurrence of extreme rainfall events and their impacts on hydrologic systems and society are critical considerations in the design and management of a large number of water resources projects. As precipitation records are often limited or unavailable at many sites, it is essential to develop better methods for regional estimation of extreme rainfall at these partially-gauged or ungauged sites. In this study, an innovative method for regional rainfall frequency analysis for ungauged sites is presented. The new method (hereafter, this is called the RRFA-S) is based on corrected annual maximum series obtained from a satellite precipitation product (e.g., PERSIANN-CDR). The probability matching method (PMM) is used here for bias correction to match the CDF of satellite-based precipitation data with the gauged data. The RRFA-S method was assessed through a comparative study with the traditional index flood method using the available annual maximum series of daily rainfall in two different regions in USA (11 sites in Colorado and 18 sites in California). The leave-one-out cross-validation technique was used to represent the ungauged site condition. Results of this numerical application have found that the quantile estimates obtained from the new approach are more accurate and more robust than those given by the traditional index flood method.

PERPHECLIM ACCAF Project - Perennial fruit crops and forest phenology evolution facing climatic changes

Science.gov (United States)

Garcia de Cortazar-Atauri, Iñaki; Audergon, Jean Marc; Bertuzzi, Patrick; Anger, Christel; Bonhomme, Marc; Chuine, Isabelle; Davi, Hendrik; Delzon, Sylvain; Duchêne, Eric; Legave, Jean Michel; Raynal, Hélène; Pichot, Christian; Van Leeuwen, Cornelis; Perpheclim Team

2015-04-01

Phenology is a bio-indicator of climate evolutions. Measurements of phenological stages on perennial species provide actually significant illustrations and assessments of the impact of climate change. Phenology is also one of the main key characteristics of the capacity of adaptation of perennial species, generating questions about their consequences on plant growth and development or on fruit quality. Predicting phenology evolution and adaptative capacities of perennial species need to override three main methodological limitations: 1) existing observations and associated databases are scattered and sometimes incomplete, rendering difficult implementation of multi-site study of genotype-environment interaction analyses; 2) there are not common protocols to observe phenological stages; 3) access to generic phenological models platforms is still very limited. In this context, the PERPHECLIM project, which is funded by the Adapting Agriculture and Forestry to Climate Change Meta-Program (ACCAF) from INRA (French National Institute of Agronomic Research), has the objective to develop the necessary infrastructure at INRA level (observatories, information system, modeling tools) to enable partners to study the phenology of various perennial species (grapevine, fruit trees and forest trees). Currently the PERPHECLIM project involves 27 research units in France. The main activities currently developed are: define protocols and observation forms to observe phenology for various species of interest for the project; organizing observation training; develop generic modeling solutions to simulate phenology (Phenological Modelling Platform and modelling platform solutions); support in building research projects at national and international level; develop environment/genotype observation networks for fruit trees species; develop an information system managing data and documentation concerning phenology. Finally, PERPHECLIM project aims to build strong collaborations with public

Characterizing Cropland Phenology in Major Grain Production Areas of Russia, Ukraine, and Kazakhstan by the Synergistic Use of Passive Microwave and Visible to Near Infrared Data

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Woubet G. Alemu

2016-12-01

Full Text Available We demonstrate the synergistic use of surface air temperature retrieved from AMSR-E (Advanced Microwave Scanning Radiometer on Earth observing satellite and two vegetation indices (VIs from the shorter wavelengths of MODIS (MODerate resolution Imaging Spectroradiometer to characterize cropland phenology in the major grain production areas of Northern Eurasia from 2003–2010. We selected 49 AMSR-E pixels across Ukraine, Russia, and Kazakhstan, based on MODIS land cover percentage data. AMSR-E air temperature growing degree-days (GDD captures the weekly, monthly, and seasonal oscillations, and well correlated with station GDD. A convex quadratic (CxQ model that linked thermal time measured as growing degree-days to accumulated growing degree-days (AGDD was fitted to each pixel’s time series yielding high coefficients of determination (0.88 ≤ r2 ≤ 0.98. Deviations of observed GDD from the CxQ model predicted GDD by site corresponded to peak VI for negative residuals (period of higher latent heat flux and low VI at beginning and end of growing season for positive residuals (periods of higher sensible heat flux. Modeled thermal time to peak, i.e., AGDD at peak GDD, showed a strong inverse linear trend with respect to latitude with r2 of 0.92 for Russia and Kazakhstan and 0.81 for Ukraine. MODIS VIs tracked similar seasonal responses in time and space and were highly correlated across the growing season with r2 > 0.95. Sites at lower latitude (≤49°N that grow winter and spring grains showed either a bimodal growing season or a shorter unimodal winter growing season with substantial inter-annual variability, whereas sites at higher latitude (≥56°N where spring grains are cultivated exhibited shorter, unimodal growing seasons. Sites between these extremes exhibited longer unimodal growing seasons. At some sites there were shifts between unimodal and bimodal patterns over the study period. Regional heat waves that devastated grain production

Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests.

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Migliavacca, Mirco; Reichstein, Markus; Richardson, Andrew D; Mahecha, Miguel D; Cremonese, Edoardo; Delpierre, Nicolas; Galvagno, Marta; Law, Beverly E; Wohlfahrt, Georg; Black, T Andrew; Carvalhais, Nuno; Ceccherini, Guido; Chen, Jiquan; Gobron, Nadine; Koffi, Ernest; Munger, J William; Perez-Priego, Oscar; Robustelli, Monica; Tomelleri, Enrico; Cescatti, Alessandro

2015-01-01

Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration (RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error (RMSE) and a 6% increase in the modeling efficiency (EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy. © 2014 John Wiley & Sons

Global Navigation Satellite System (GNSS) Rapid Clock Product Summary from NASA CDDIS

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National Aeronautics and Space Administration — This derived product set consists of Global Navigation Satellite System Rapid Clock Product Summary from the NASA Crustal Dynamics Data Information System (CDDIS)....

The USA National Phenology Network; taking the pulse of our planet

Science.gov (United States)

Weltzin, Jake F.

2011-01-01

People have tracked phenology for centuries and for the most practical reasons: it helped them know when to hunt and fish, when to plant and harvest crops, and when to navigate waterways. Now phenology is being used as a tool to assess climate change and its effects on both natural and modified ecosystems. How is the timing of events in plant and animal life cycles, like flowering or migration, responding to climate change? And how are those responses, in turn, affecting people and ecosystems? The USA National Phenology Network (the Network) is working to answer these questions for science and society by promoting a broad understanding of plant and animal phenology and their relationship to environmental change. The Network is a consortium of organizations and individuals that collect, share, and use phenology data, models, and related information to enable scientists, resource managers, and the public to adapt in response to changing climates and environments. In addition, the Network encourages people of all ages and backgrounds to observe and record phenology as a way to discover and explore the nature and pace of our dynamic world. The National Coordinating Office (NCO) of the Network is a resource center that facilitates and encourages widespread collection, integration, and sharing of phenology data and related information (for example, meteorological and hydrological data). The NCO develops and promotes standardized methods for field data collection and maintains several online user interfaces for data upload and download, as well as data exploration, visualization, and analysis. The NCO also facilitates basic and applied research related to phenology, the development of decision-support tools for resource managers and planners, and the design of educational and outreach materials

Continental-scale patterns of Cecropia reproductive phenology: evidence from herbarium specimens.

Science.gov (United States)

Zalamea, Paul-Camilo; Munoz, François; Stevenson, Pablo R; Paine, C E Timothy; Sarmiento, Carolina; Sabatier, Daniel; Heuret, Patrick

2011-08-22

Plant phenology is concerned with the timing of recurring biological events. Though phenology has traditionally been studied using intensive surveys of a local flora, results from such surveys are difficult to generalize to broader spatial scales. In this study, contrastingly, we assembled a continental-scale dataset of herbarium specimens for the emblematic genus of Neotropical pioneer trees, Cecropia, and applied Fourier spectral and cospectral analyses to investigate the reproductive phenology of 35 species. We detected significant annual, sub-annual and continuous patterns, and discuss the variation in patterns within and among climatic regions. Although previous studies have suggested that pioneer species generally produce flowers continually throughout the year, we found that at least one third of Cecropia species are characterized by clear annual flowering behaviour. We further investigated the relationships between phenology and climate seasonality, showing strong associations between phenology and seasonal variations in precipitation and temperature. We also verified our results against field survey data gathered from the literature. Our findings indicate that herbarium material is a reliable resource for use in the investigation of large-scale patterns in plant phenology, offering a promising complement to local intensive field studies.

Impact of warming climate and cultivar change on maize phenology in the last three decades in North China Plain

Science.gov (United States)

Xiao, Dengpan; Qi, Yongqing; Shen, Yanjun; Tao, Fulu; Moiwo, Juana P.; Liu, Jianfeng; Wang, Rede; Zhang, He; Liu, Fengshan

2016-05-01

As climate change could significantly influence crop phenology and subsequent crop yield, adaptation is a critical mitigation process of the vulnerability of crop growth and production to climate change. Thus, to ensure crop production and food security, there is the need for research on the natural (shifts in crop growth periods) and artificial (shifts in crop cultivars) modes of crop adaptation to climate change. In this study, field observations in 18 stations in North China Plain (NCP) are used in combination with Agricultural Production Systems Simulator (APSIM)-Maize model to analyze the trends in summer maize phenology in relation to climate change and cultivar shift in 1981-2008. Apparent warming in most of the investigated stations causes early flowering and maturity and consequently shortens reproductive growth stage. However, APSIM-Maize model run for four representative stations suggests that cultivar shift delays maturity and thereby prolongs reproductive growth (flowering to maturity) stage by 2.4-3.7 day per decade (d 10a-1). The study suggests a gradual adaptation of maize production process to ongoing climate change in NCP via shifts in high thermal cultivars and phenological processes. It is concluded that cultivation of maize cultivars with longer growth periods and higher thermal requirements could mitigate the negative effects of warming climate on crop production and food security in the NCP study area and beyond.

Topography-mediated controls on local vegetation phenology estimated from MODIS vegetation index

Science.gov (United States)

Taehee Hwang; Conghe Song; James Vose; Lawrence Band

2011-01-01

Forest canopy phenology is an important constraint on annual water and carbon budgets, and responds to regional interannual climate variation. In steep terrain, there are complex spatial variations in phenology due to topographic influences on microclimate, community composition, and available soil moisture. In this study, we investigate spatial patterns of phenology...

Temporal patterns of vegetation phenology and their responses to climate change in mid-latitude grasslands of the Northern Hemisphere

Science.gov (United States)

Ren, S.; Chen, X.; Qin, Q.; Zhang, Y.; Wu, Z.

2017-12-01

Grassland ecosystem is greatly sensitive to regional and global climate changes. In this study, the start (SOS) and end (EOS) date of growing season were extracted from NDVI data (1981 2014) across the mid-latitude (30°N 55°N) grasslands of Northern Hemisphere. We first validated their accuracy by ground observed phenological data and phenological metrics derived from gross primary production (GPP) data. And then, main climatic factors influencing the temporal patterns of SOS/EOS were explored by means of gridded meteorological data and partial correlation analysis. Based on the results of above statistical analysis, the similarities and differences of spring and autumn phenological responses to climate change among North American grasslands, Mid-West Asian grasslands, and Mongolian grasslands were analyzed. The main results and conclusions are as follows. First, a significant positive correlation was found between SOS/EOS and observed green-up/brown-off date (PSOS/EOS (PSOS/EOS can reflect temporal dynamics of terrestrial vegetation phenology. Second, SOS in Mid-West Asian grasslands showed a significant advancing trend (0.22 days/year, PSOS in North American grasslands and Mongolian grasslands was not significant. EOS in North American grasslands (0.31 dyas/year, PSOS/EOS inter-annual fluctuations and hydrothermal factors showed that a significant negative correlation was found between SOS and the pre-season temperature in 41.6% of pixels (PSOS and pre-season rainfall/snowfall in 14.6%/19.0% of pixels (PSOS and EOS are mainly affected by pre-season temperature and pre-season rainfall.

Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Realtime and Research Products and Applications

Science.gov (United States)

Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guojon

2004-01-01

Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25 deg latitude-longitude resolution over the latitude range from 50 deg N-50 deg S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

The remote sensing of ocean primary productivity - Use of a new data compilation to test satellite algorithms

Science.gov (United States)

Balch, William; Evans, Robert; Brown, Jim; Feldman, Gene; Mcclain, Charles; Esaias, Wayne

1992-01-01

Global pigment and primary productivity algorithms based on a new data compilation of over 12,000 stations occupied mostly in the Northern Hemisphere, from the late 1950s to 1988, were tested. The results showed high variability of the fraction of total pigment contributed by chlorophyll, which is required for subsequent predictions of primary productivity. Two models, which predict pigment concentration normalized to an attenuation length of euphotic depth, were checked against 2,800 vertical profiles of pigments. Phaeopigments consistently showed maxima at about one optical depth below the chlorophyll maxima. CZCS data coincident with the sea truth data were also checked. A regression of satellite-derived pigment vs ship-derived pigment had a coefficient of determination. The satellite underestimated the true pigment concentration in mesotrophic and oligotrophic waters and overestimated the pigment concentration in eutrophic waters. The error in the satellite estimate showed no trends with time between 1978 and 1986.

Nonlinear Variations of Net Primary Productivity and Its Relationship with Climate and Vegetation Phenology, China

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Jian Yang

2017-09-01

Full Text Available Net primary productivity (NPP is an important component of the terrestrial carbon cycle. In this study, NPP was estimated based on two models and Moderate Resolution Imaging Spaectroradiometer (MODIS data. The spatiotemporal patterns of NPP and the correlations with climate factors and vegetation phenology were then analyzed. Our results showed that NPP derived from MODIS performed well in China. Spatially, NPP decreased from the southeast toward the northwest. Temporally, NPP showed a nonlinear increasing trend at a national scale, but the magnitude became slow after 2004. At a regional scale, NPP in Northern China and the Tibetan Plateau showed a nonlinear increasing trend, while the NPP decreased in most areas of Southern China. The decreases in NPP were more than offset by the increases. At the biome level, all vegetation types displayed an increasing trend, except for shrub and evergreen broad forests (EBF. Moreover, a turning point year occurred for all vegetation types, except for EBF. Generally, climatic factors and Length of Season were all positively correlated with the NPP, while the relationships were much more diverse at a regional level. The direct effect of solar radiation on the NPP was larger (0.31 than precipitation (0.25 and temperature (0.07. Our results indicated that China could mitigate climate warming at a regional and/or global scale to some extent during the time period of 2001–2014.

Atmospheric mechanisms governing the spatial and temporal variability of phenological phases in central Europe

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Scheifinger, Helfried; Menzel, Annette; Koch, Elisabeth; Peter, Christian; Ahas, Rein

2002-11-01

A data set of 17 phenological phases from Germany, Austria, Switzerland and Slovenia spanning the time period from 1951 to 1998 has been made available for analysis together with a gridded temperature data set (1° × 1° grid) and the North Atlantic Oscillation (NAO) index time series. The disturbances of the westerlies constitute the main atmospheric source for the temporal variability of phenological events in Europe. The trend, the standard deviation and the discontinuity of the phenological time series at the end of the 1980s can, to a great extent, be explained by the NAO. A number of factors modulate the influence of the NAO in time and space. The seasonal northward shift of the westerlies overlaps with the sequence of phenological spring phases, thereby gradually reducing its influence on the temporal variability of phenological events with progression of spring (temporal loss of influence). This temporal process is reflected by a pronounced decrease in trend and standard deviation values and common variability with the NAO with increasing year-day. The reduced influence of the NAO with increasing distance from the Atlantic coast is not only apparent in studies based on the data set of the International Phenological Gardens, but also in the data set of this study with a smaller spatial extent (large-scale loss of influence). The common variance between phenological and NAO time series displays a discontinuous drop from the European Atlantic coast towards the Alps. On a local and regional scale, mountainous terrain reduces the influence of the large-scale atmospheric flow from the Atlantic via a proposed decoupling mechanism. Valleys in mountainous terrain have the inclination to harbour temperature inversions over extended periods of time during the cold season, which isolate the valley climate from the large-scale atmospheric flow at higher altitudes. Most phenological stations reside at valley bottoms and are thus largely decoupled in their temporal

Response of vegetation phenology to urbanization in the conterminous United States

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Li, Xuecao [Department of Geological and Atmospheric Sciences, Iowa State University, Ames IA 50011 USA; Zhou, Yuyu [Department of Geological and Atmospheric Sciences, Iowa State University, Ames IA 50011 USA; Asrar, Ghassem R. [Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park MD 20740 USA; Mao, Jiafu [Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge TN 37831 USA; Li, Xiaoma [Department of Geological and Atmospheric Sciences, Iowa State University, Ames IA 50011 USA; Li, Wenyu [Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084 China

2016-12-18

The influence of urbanization on vegetation phenology is gaining considerable attention due to its implications for human health, cycling of carbon and other nutrients in Earth system. In this study, we examined the relationship between change in vegetation phenology and urban size, an indicator of urbanization, for the conterminous United States. We studied more than 4500 urban clusters of varying size to determine the impact of urbanization on plant phenology, with the aids of remotely sensed observations since 2003–2012. We found that phenology cycle (changes in vegetation greenness) in rural areas starts earlier (start of season, SOS) and ends later (end of season, EOS), resulting in a longer growing season length (GSL), when compared to the respective surrounding urban areas. The average difference of GSL between urban and rural areas over all vegetation types, considered in this study, is about 9 days. Also, the extended GSL in urban area is consistent among different climate zones in the United States, whereas their magnitudes are varying across regions. We found that a tenfold increase in urban size could result in an earlier SOS of about 1.3 days and a later EOS of around 2.4 days. As a result, the GSL could be extended by approximately 3.6 days with a range of 1.6–6.5 days for 25th ~ 75th quantiles, with a median value of about 2.1 days. For different vegetation types, the phenology response to urbanization, as defined by GSL, ranges from 1 to 4 days. The quantitative relationship between phenology and urbanization is of great use for developing improved models of vegetation phenology dynamics under future urbanization, and for developing change indicators to assess the impacts of urbanization on vegetation phenology.

Volcview: A Web-Based Platform for Satellite Monitoring of Volcanic Activity and Eruption Response

Science.gov (United States)

Schneider, D. J.; Randall, M.; Parker, T.

2014-12-01

The U.S. Geological Survey (USGS), in cooperation with University and State partners, operates five volcano observatories that employ specialized software packages and computer systems to process and display real-time data coming from in-situ geophysical sensors and from near-real-time satellite sources. However, access to these systems both inside and from outside the observatory offices are limited in some cases by factors such as software cost, network security, and bandwidth. Thus, a variety of Internet-based tools have been developed by the USGS Volcano Science Center to: 1) Improve accessibility to data sources for staff scientists across volcano monitoring disciplines; 2) Allow access for observatory partners and for after-hours, on-call duty scientists; 3) Provide situational awareness for emergency managers and the general public. Herein we describe VolcView (volcview.wr.usgs.gov), a freely available, web-based platform for display and analysis of near-real-time satellite data. Initial geographic coverage is of the volcanoes in Alaska, the Russian Far East, and the Commonwealth of the Northern Mariana Islands. Coverage of other volcanoes in the United States will be added in the future. Near-real-time satellite data from NOAA, NASA and JMA satellite systems are processed to create image products for detection of elevated surface temperatures and volcanic ash and SO2 clouds. VolcView uses HTML5 and the canvas element to provide image overlays (volcano location and alert status, annotation, and location information) and image products that can be queried to provide data values, location and measurement capabilities. Use over the past year during the eruptions of Pavlof, Veniaminof, and Cleveland volcanoes in Alaska by the Alaska Volcano Observatory, the National Weather Service, and the U.S. Air Force has reinforced the utility of shared situational awareness and has guided further development. These include overlay of volcanic cloud trajectory and

Evaluation of Satellite Precipitation Products with Rain Gauge Data at Different Scales: Implications for Hydrological Applications

Directory of Open Access Journals (Sweden)

Ruifang Guo

2016-07-01

Full Text Available Rain gauge and satellite-retrieved data have been widely used in basin-scale hydrological applications. While rain gauges provide accurate measurements that are generally unevenly distributed in space, satellites offer spatially regular observations and common error prone retrieval. Comparative evaluation of gauge-based and satellite-based data is necessary in hydrological studies, as precipitation is the most important input in basin-scale water balance. This study uses quality-controlled rain gauge data and prevailing satellite products (Tropical Rainfall Measuring Mission (TRMM 3B43, 3B42 and 3B42RT to examine the consistency and discrepancies between them at different scales. Rain gauges and TRMM products were available in the Poyang Lake Basin, China, from 1998 to 2007 (3B42RT: 2000–2007. Our results show that the performance of TRMM products generally increases with increasing spatial scale. At both the monthly and annual scales, the accuracy is highest for TRMM 3B43, with 3B42 second and 3B42RT third. TRMM products generally overestimate precipitation because of a high frequency and degree of overestimation in light and moderate rain cases. At the daily scale, the accuracy is relatively low between TRMM 3B42 and 3B42RT. Meanwhile, the performances of TRMM 3B42 and 3B42RT are highly variable in different seasons. At both the basin and pixel scales, TRMM 3B43 and 3B42 exhibit significant discrepancies from July to September, performing worst in September. For TRMM 3B42RT, all statistical indices fluctuate and are low throughout the year, performing worst in July at the pixel scale and January at the basin scale. Furthermore, the spatial distributions of the statistical indices of TRMM 3B43 and 3B42 performed well, while TRMM 3B42RT displayed a poor performance.

Reproductivity and phenology of argan (argania spinosa (L.) skeels) a rare tree endemic to the west of algeria

International Nuclear Information System (INIS)

Benaouf, Z.; Arabi, Z.; Miloudi, A.; Souidi, Z.

2015-01-01

Argania spinosa in its ecological interest is threefold: forest, forage and fruit (oil production). The regeneration of the argan tree, it is important to know the phenology of this species. The study of phenology helps to know precisely the periods of activity of vegetation for productivity measures (Embryogenesis of the pollen grain, pollen deposition, pollen adhesion, fluorescence microscopy of pollen tube growth and Pollen grain size). Our results on the study of the phenology of two taxa of Argania spinosa (Mascara taxa and Mostaganem taxa), Regarding the phenological behavior of the argan under the effect of environmental conditions, we can mention that some argan trees (of Oggaz and one of Stidia) are early trees bloom twice a year in October and in spring, the author trees are late trees manifest activity during periods of the year. Begin to bloom from February until spring, this period is characterized by the breakdown of flower buds and the appearance of flowers on the twigs of the previous year and those of the current year; the fall of their ripe fruit takes place in Jun of the following year. Argan trees wore two generations of fruit, fruit knotted this season and last season tied fruit maturing. The length of the cycle is detected 9 and 16 months, we believe that a time synchronization in the evolution of physiological behavior argan trees of the two stations with 90 percentage. (author)

Comparison of total column ozone obtained by the IASI-MetOp satellite with ground-based and OMI satellite observations in the southern tropics and subtropics

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A. M. Toihir

2015-09-01

Full Text Available This paper presents comparison results of the total column ozone (TCO data product over 13 southern tropical and subtropical sites recorded from the Infrared Atmospheric Sounder Interferometer (IASI onboard the EUMETSAT (European organization for the exploitation of METeorological SATellite MetOp (Meteorological Operational satellite program satellite. TCO monthly averages obtained from IASI between June 2008 and December 2012 are compared with collocated TCO measurements from the Ozone Monitoring Instrument (OMI on the OMI/Aura satellite and the Dobson and SAOZ (Système d'Analyse par Observation Zénithale ground-based instruments. The results show that IASI displays a positive bias with an average less than 2 % with respect to OMI and Dobson observations, but exhibits a negative bias compared to SAOZ over Bauru with a bias around 2.63 %. There is a good agreement between IASI and the other instruments, especially from 15° S southward where a correlation coefficient higher than 0.87 is found. IASI exhibits a seasonal dependence, with an upward trend in autumn and a downward trend during spring, especially before September 2010. After September 2010, the autumn seasonal bias is considerably reduced due to changes made to the retrieval algorithm of the IASI level 2 (L2 product. The L2 product released after August (L2 O3 version 5 (v5 matches TCO from the other instruments better compared to version 4 (v4, which was released between June 2008 and August 2010. IASI bias error recorded from September 2010 is estimated to be at 1.5 % with respect to OMI and less than ±1 % with respect to the other ground-based instruments. Thus, the improvement made by O3 L2 version 5 (v5 product compared with version 4 (v4, allows IASI TCO products to be used with confidence to study the distribution and interannual variability of total ozone in the southern tropics and subtropics.

Alteration of Hormonal Levels in a Rootless Epiphytic Bromeliad in Different Phenological Phases.

Science.gov (United States)

Mercier; Endres

1999-11-01

Major changes in indole-3-acetic acid (IAA) and cytokinin (CK) levels occur at different phenological phases of Tillandsia recurvata shoots. This epiphytic rootless bromeliad was chosen as suitable material for hormonal analysis because CK synthesis is restricted to the shoots, thus avoiding problems in the interpretation of results caused by translocation and interconversion of CK forms between roots and leaves encountered in plants with both organs. Young plants of T. recurvata have weak apical dominance because side shoots appeared early in development, and branch growth was correlated with a strong increase in the level of zeatin. The flowering phase was characterized by a significant increase in free base CKs, zeatin, and isopentenyladenine compared with the levels found in adult vegetative shoots. In contrast, both free-base CKs declined in the fruiting phenological phase, and the IAA level increased dramatically. It was concluded that in phases characterized by intense organ formation, such as in the juvenile and flowering stages, there was an enhancement of CK content, mainly caused by zeatin, leading to a lower IAA/CK ratio. Higher ratios were correlated with phases that showed no organogenesis, such as adult and fruiting phenologies.

The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

Science.gov (United States)

Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

2017-04-01

We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse

A Satellite-Based Sunshine Duration Climate Data Record for Europe and Africa

Directory of Open Access Journals (Sweden)

Steffen Kothe

2017-05-01

Full Text Available Besides 2 m - temperature and precipitation, sunshine duration is one of the most important and commonly used parameter in climatology, with measured time series of partly more than 100 years in length. EUMETSAT’s Satellite Application Facility on Climate Monitoring (CM SAF presents a climate data record for daily and monthly sunshine duration (SDU for Europe and Africa. Basis for the advanced retrieval is a highly resolved satellite product of the direct solar radiation from measurements by Meteosat satellites 2 to 10. The data record covers the time period 1983 to 2015 with a spatial resolution of 0.05° × 0.05°. The comparison against ground-based data shows high agreement but also some regional differences. Sunshine duration is overestimated by the satellite-based data in many regions, compared to surface data. In West and Central Africa, low clouds seem to be the reason for a stronger overestimation of sunshine duration in this region (up to 20% for monthly sums. For most stations, the overestimation is low, with a bias below 7.5 h for monthly sums and below 0.4 h for daily sums. A high correlation of 0.91 for daily SDU and 0.96 for monthly SDU also proved the high agreement with station data. As SDU is based on a stable and homogeneous climate data record of more than 30 years length, it is highly suitable for climate applications, such as trend estimates.

Minding the gaps: new insights into R&D management and operational transitions of NOAA satellite products

Science.gov (United States)

Colton, Marie C.; Powell, Alfred M.; Jordan, Gretchen; Mote, Jonathon; Hage, Jerald; Frank, Donald

2004-10-01

The NESDIS Center for Satellite Applications and Research (STAR), formerly ORA, Office of Research and Applications, consists of three research and applications divisions that encompass satellite meteorology, oceanography, climatology, and cooperative research with academic institutions. With such a wide background of talent, and a charter to develop operational algorithms and applications, STAR scientists develop satellite-derived land, ice, ocean, and atmospheric environmental data products in support of all of NOAA"s mission goals. In addition, in close association with the Joint Center for Satellite Data Assimilation, STAR scientists actively work with the numerical modeling communities of NOAA, NASA, and DOD to support the development of new methods for assimilation of satellite data. In this new era of observations from many new satellite instruments, STAR aims to effectively integrate these data into multi-platform data products for utilization by the forecast and applications communities. Much of our work is conducted in close partnerships with other agencies, academic institutes, and industry. In order to support the nearly 400 current satellite-derived products for various users on a routine basis from our sister operations office, and to evolve to future systems requires an ongoing strategic planning approach that maps research and development activities from NOAA goals to user requirements. Since R&D accomplishments are not necessarily amenable to precise schedules, appropriate motivators and measures of scientific progress must be developed to assure that the product development cycle remains aligned with the other engineering segments of a satellite program. This article presents the status and results of this comprehensive effort to chart a course from the present set of operational satellites to the future.

Phenological adaptations in Ficus tikoua exhibit convergence with unrelated extra-tropical fig trees.

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Ting-Ting Zhao

Full Text Available Flowering phenology is central to the ecology and evolution of most flowering plants. In highly-specific nursery pollination systems, such as that involving fig trees (Ficus species and fig wasps (Agaonidae, any mismatch in timing has serious consequences because the plants must balance seed production with maintenance of their pollinator populations. Most fig trees are found in tropical or subtropical habitats, but the dioecious Chinese Ficus tikoua has a more northerly distribution. We monitored how its fruiting phenology has adapted in response to a highly seasonal environment. Male trees (where fig wasps reproduce had one to three crops annually, whereas many seed-producing female trees produced only one fig crop. The timing of release of Ceratosolen fig wasps from male figs in late May and June was synchronized with the presence of receptive figs on female trees, at a time when there were few receptive figs on male trees, thereby ensuring seed set while allowing remnant pollinator populations to persist. F. tikoua phenology has converged with those of other (unrelated northern Ficus species, but there are differences. Unlike F. carica in Europe, all F. tikoua male figs contain male flowers, and unlike F. pumila in China, but like F. carica, it is the second annual generation of adult wasps that pollinate female figs. The phenologies of all three temperate fig trees generate annual bottlenecks in the size of pollinator populations and for female F. tikoua also a shortage of fig wasps that results in many figs failing to be pollinated.

Comparison between satellite precipitation product and observation rain gauges in the Red-Thai Binh River Basin

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Lakshmi, V.; Le, M. H.; Sutton, J. R. P.; Bui, D. D.; Bolten, J. D.

2017-12-01

The Red-ThaiBinh River is the second largest river in Vietnam in terms of economic impact and is home to around 29 million people. The river has been facing challenges for water resources allocation, which require reliable and routine hydrological assessments. However, hydrological analysis is difficult due to insufficient spatial coverage by rain gauges. Satellite-based precipitation estimates are a promising alternative with high-resolution in both time and space. This study aims at investigating the uncertainties in satellite-based precipitation product TRMM 3B42 v7.0 by comparing them against in-situ measurements over the Red-ThaiBinh River basin. The TRMM 3B42 v7.0 are assessed in terms of seasonal, monthly and daily variations over a 17-year period (1998 - 2014). Preliminary results indicate that at a daily scale, except for low Mean Bias Error (MBE), satellite based rainfall product has weak relationship with ground observation data, indicating by average performance of 0.326 and -0.485 for correlation coefficient and Nash Sutcliffe Efficiency (NSE), respectively. At monthly scale, we observe that the TRMM 3B42 v7.0 has higher correlation with the correlation increased significantly to 0.863 and NSE of 0.522. By analyzing wet season (May - October) and dry season (November - April) separately we find that the correlation between the TRMM 3B42 v7.0 with ground observations were higher for wet season than the dry season.

Phenological observations on shrubs to predict weed emergence in turf

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Masin, Roberta; Zuin, Maria Clara; Zanin, Giuseppe

2005-09-01

Phenology is the study of periodic biological events. If we can find easily recognizable events in common plants that precede or coincide with weed emergences, these plants could be used as indicators. Weed seedlings are usually difficult to detect in turf, so the use of phenological indicators may provide an alternative approach to predict the time when a weed appears and consequently guide management decisions. A study was undertaken to determine whether the phenological phases of some plants could serve as reliable indicators of time of weed emergence in turf. The phenology of six shrubs (Crataegus monogyna Jacq., Forsythia viridissima Lindl., Sambucus nigra L., Syringa vulgaris L., Rosa multiflora Thunb., Ziziphus jujuba Miller) and a perennial herbaceous plant [Cynodon dactylon (L.) Pers.] was observed and the emergence dynamics of four annual weed species [Digitaria sanguinalis (L.) Scop., Eleusine indica (L.) Gaertner, Setaria glauca (L.) Beauv., Setaria viridis (L.) Beauv.] were studied from 1999 to 2004 in northern Italy. A correlation between certain events and weed emergence was verified. S. vulgaris and F. viridissima appear to be the best indicators: there is a quite close correspondence between the appearance of D. sanguinalis and lilac flowering and between the beginning of emergence of E. indica and the end of lilac flowering; emergences of S. glauca and S. viridis were predicted well in relation to the end of forsythia flowering. Base temperatures and starting dates required to calculate the heat unit sums to reach and complete the flowering phase of the indicators were calculated using two different methods and the resultant cumulative growing degree days were compared.

Assessing the impact of extreme air temperature on fruit trees by modeling weather dependent phenology with variety-specific thermal requirements

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Alfieri, Silvia Maria; De Lorenzi, Francesca; Missere, Daniele; Buscaroli, Claudio; Menenti, Massimo

2013-04-01

Extremely high and extremely low temperature may have a terminal impact on the productivity of fruit tree if occurring at critical phases of development. Notorious examples are frost during flowering or extremely high temperature during fruit setting. The dates of occurrence of such critical phenological stages depend on the weather history from the start of the yearly development cycle in late autumn, thus the impact of climate extremes can only be evaluated correctly if the phenological development is modeled taking into account the weather history of the specific year being evaluated. Climate change impact may lead to a shift in timing of phenological stages and change in the duration of vegetative and reproductive phases. A changing climate can also exhibit a greater climatic variability producing quite large changes in the frequency of extreme climatic events. We propose a two-stage approach to evaluate the impact of predicted future climate on the productivity of fruit trees. The phenological development is modeled using phase - specific thermal times and variety specific thermal requirements for several cultivars of pear, apricot and peach. These requirements were estimated using phenological observations over several years in Emilia Romagna region and scientific literature. We calculated the dates of start and end of rest completion, bud swell, flowering, fruit setting and ripening stages , from late autumn through late summer. Then phase-specific minimum and maximum cardinal temperature were evaluated for present and future climate to estimate how frequently they occur during any critically sensitive phenological phase. This analysis has been done for past climate (1961 - 1990) and fifty realizations of a year representative of future climate (2021 - 2050). A delay in rest completion of about 10-20 days has been predicted for future climate for most of the cultivars. On the other hand the predicted rise in air temperature causes an earlier development of