scholarly journals Characterizing Spatio-Temporal Dynamics of Urbanization in China Using Time Series of DMSP/OLS Night Light Data

2014 ◽  
Vol 6 (8) ◽  
pp. 7708-7731 ◽  
Author(s):  
Tao Xu ◽  
Ting Ma ◽  
Chenghu Zhou ◽  
Yuke Zhou
Keyword(s):  
Time Series ◽  
Temporal Dynamics ◽  
Spatio Temporal ◽  
Urbanization In China

scholarly journals Learning from satellite observations: increased understanding of catchment processes through stepwise model improvement

2021 ◽  
Vol 25 (2) ◽  
pp. 957-982 ◽  
Author(s):  
Petra Hulsman ◽  
Hubert H. G. Savenije ◽  
Markus Hrachowitz
Keyword(s):  
Time Series ◽  
Spatial Patterns ◽  
Temporal Dynamics ◽  
Water Storage ◽  
Remotely Sensed ◽  
Satellite Observations ◽  
Model Structure ◽  
Total Water ◽  
Groundwater Reservoir ◽  
Spatio Temporal

Abstract. Satellite observations can provide valuable information for a better understanding of hydrological processes and thus serve as valuable tools for model structure development and improvement. While model calibration and evaluation have in recent years started to make increasing use of spatial, mostly remotely sensed information, model structural development largely remains to rely on discharge observations at basin outlets only. Due to the ill-posed inverse nature and the related equifinality issues in the modelling process, this frequently results in poor representations of the spatio-temporal heterogeneity of system-internal processes, in particular for large river basins. The objective of this study is thus to explore the value of remotely sensed, gridded data to improve our understanding of the processes underlying this heterogeneity and, as a consequence, their quantitative representation in models through a stepwise adaptation of model structures and parameters. For this purpose, a distributed, process-based hydrological model was developed for the study region, the poorly gauged Luangwa River basin. As a first step, this benchmark model was calibrated to discharge data only and, in a post-calibration evaluation procedure, tested for its ability to simultaneously reproduce (1) the basin-average temporal dynamics of remotely sensed evaporation and total water storage anomalies and (2) their temporally averaged spatial patterns. This allowed for the diagnosis of model structural deficiencies in reproducing these temporal dynamics and spatial patterns. Subsequently, the model structure was adapted in a stepwise procedure, testing five additional alternative process hypotheses that could potentially better describe the observed dynamics and pattern. These included, on the one hand, the addition and testing of alternative formulations of groundwater upwelling into wetlands as a function of the water storage and, on the other hand, alternative spatial discretizations of the groundwater reservoir. Similar to the benchmark, each alternative model hypothesis was, in a next step, calibrated to discharge only and tested against its ability to reproduce the observed spatio-temporal pattern in evaporation and water storage anomalies. In a final step, all models were re-calibrated to discharge, evaporation and water storage anomalies simultaneously. The results indicated that (1) the benchmark model (Model A) could reproduce the time series of observed discharge, basin-average evaporation and total water storage reasonably well. In contrast, it poorly represented time series of evaporation in wetland-dominated areas as well as the spatial pattern of evaporation and total water storage. (2) Stepwise adjustment of the model structure (Models B–F) suggested that Model F, allowing for upwelling groundwater from a distributed representation of the groundwater reservoir and (3) simultaneously calibrating the model with respect to multiple variables, i.e. discharge, evaporation and total water storage anomalies, provided the best representation of all these variables with respect to their temporal dynamics and spatial patterns, except for the basin-average temporal dynamics in the total water storage anomalies. It was shown that satellite-based evaporation and total water storage anomaly data are not only valuable for multi-criteria calibration, but can also play an important role in improving our understanding of hydrological processes through the diagnosis of model deficiencies and stepwise model structural improvement.

scholarly journals Predicting Spatio-temporal Time Series Using Dimension Reduced Local States

2019 ◽  
Vol 30 (3) ◽  
pp. 713-735 ◽  
Author(s):  
Jonas Isensee ◽  
George Datseris ◽  
Ulrich Parlitz
Keyword(s):  
Time Series ◽  
Principle Component Analysis ◽  
Temporal Dynamics ◽  
Time Series Prediction ◽  
Noisy Data ◽  
Nearest Neighbour ◽  
Reduction Techniques ◽  
Spatio Temporal ◽  
Delay Coordinates ◽  
Dimension Reduction Techniques

Abstract We present a method for both cross-estimation and iterated time series prediction of spatio-temporal dynamics based on local modelling and dimension reduction techniques. Assuming homogeneity of the underlying dynamics, we construct delay coordinates of local states and then further reduce their dimensionality through Principle Component Analysis. The prediction uses nearest neighbour methods in the space of dimension reduced states to either cross-estimate or iteratively predict the future of a given frame. The effectiveness of this approach is shown for (noisy) data from a (cubic) Barkley model, the Bueno-Orovio–Cherry–Fenton model, and the Kuramoto–Sivashinsky model.

scholarly journals Evaluation of Using Sentinel-1 and -2 Time-Series to Identify Winter Land Use in Agricultural Landscapes

2018 ◽  
Vol 11 (1) ◽  
pp. 37 ◽  
Author(s):  
Julien Denize ◽  
Laurence Hubert-Moy ◽  
Julie Betbeder ◽  
Samuel Corgne ◽  
Jacques Baudry ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Cover ◽  
Temporal Dynamics ◽  
Agricultural Practices ◽  
Agricultural Landscapes ◽  
Support Vector ◽  
Kappa Index ◽  
Spatio Temporal ◽  
Agricultural Areas

Monitoring vegetation cover during winter is a major environmental and scientific issue in agricultural areas. From an environmental viewpoint, the presence and type of vegetation cover in winter influences the transport of pollutants to water resources. From a methodological viewpoint, characterizing spatio-temporal dynamics of land cover and land use at the field scale is challenging due to the diversity of farming strategies and practices in winter. The objective of this study was to evaluate the respective advantages of Sentinel optical and SAR time-series to identify land use in winter. To this end, Sentinel-1 and -2 time-series were classified using Support Vector Machine and Random Forest algorithms in a 130 km² agricultural area. From the classification, the Sentinel-2 time-series identified winter land use more accurately (overall accuracy (OA) = 75%, Kappa index = 0.70) than that of Sentinel-1 (OA = 70%, Kappa = 0.66) but a combination of the Sentinel-1 and -2 time-series was the most accurate (OA = 81%, Kappa = 0.77). Our study outlines the effectiveness of Sentinel-1 and -2 for identify land use in winter, which can help to change agricultural practices.

Spatio-temporal dynamics of phytoplankton and primary production in Lake Tanganyika using a MODIS based bio-optical time series

2010 ◽  
Vol 114 (4) ◽  
pp. 772-780 ◽  
Author(s):  
N. Bergamino ◽  
S. Horion ◽  
S. Stenuite ◽  
Y. Cornet ◽  
S. Loiselle ◽  
...  
Keyword(s):  
Time Series ◽  
Primary Production ◽  
Lake Tanganyika ◽  
Temporal Dynamics ◽  
Spatio Temporal ◽  
Optical Time

Measuring spatio-temporal dynamics of impervious surface in Guangzhou, China, from 1988 to 2015, using time-series Landsat imagery

2018 ◽  
Vol 627 ◽  
pp. 264-281 ◽  
Author(s):  
Jianhui Xu ◽  
Yi Zhao ◽  
Kaiwen Zhong ◽  
Feifei Zhang ◽  
Xulong Liu ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Dynamics ◽  
Landsat Imagery ◽  
Impervious Surface ◽  
Spatio Temporal

scholarly journals Multi-scale event synchronization analysis for unravelling climate processes: A wavelet-based approach

2017 ◽  
Author(s):  
Ankit Agarwal ◽  
Norbert Marwan ◽  
Maheswaran Rathinasamy ◽  
Bruno Merz ◽  
Jürgen Kurths
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Time Scale ◽  
Temporal Dynamics ◽  
Multiple Scales ◽  
Nonlinear Interactions ◽  
Reference Time ◽  
Multi Scale ◽  
Spatio Temporal ◽  
Different Time Scales

Abstract. The temporal dynamics of climate processes are spread across different time scales and, as such, the study of these processes only at one selected time scale might not reveal the complete mechanisms and interactions within and between the (sub-) processes. For capturing the nonlinear interactions between climatic events, the method of event synchronization has found increasing attention recently. The main drawback with the present estimation of event synchronization is its restriction to analyse the time series at one reference time scale only. The study of event synchronization at multiple scales would be of great interest to comprehend the dynamics of the investigated climate processes. In this paper, wavelet based multi-scale event synchronization (MSES) method is proposed by combining the wavelet transform and event synchronization. Wavelets are used extensively to comprehend multi-scale processes and the dynamics of processes across various time scales. The proposed method allows the study of spatio-temporal patterns across different time scales. The method is tested on synthetic and real-world time series in order to check its replicability and applicability. The results indicate that MSES is able to capture relationships that exist between processes at different time scales.

scholarly journals Exploring the Spatio-Temporal Dynamics of Winter Rape on the Middle Reaches of Yangtze River Valley Using Time-Series MODIS Data

2020 ◽  
Vol 12 (2) ◽  
pp. 466 ◽  
Author(s):  
Jianbin Tao ◽  
Wenbin Wu ◽  
Wenbin Liu ◽  
Meng Xu
Keyword(s):  
Time Series ◽  
Yangtze River ◽  
Temporal Dynamics ◽  
International Market ◽  
Yangtze River Valley ◽  
River Valley ◽  
Winter Rape ◽  
Domestic Production ◽  
Modis Data ◽  
Spatio Temporal

Rapeseed is an important oil product in China. China’s current soybean trade issues with major soybean producing countries have caused a large decline in soybean import since 2017. This may bring the increasing needs of rapeseed import, which would have an impact on domestic production. However, our knowledge on the effects of international rapeseed trade on domestic production remains unknown. It is thus important to understand the pattern of rapeseed in China under this scenario, as it may provide necessary information for all relevant stakeholders. With this goal, this study aims to investigate the spatial and temporal patterns of winter rape in China’s major winter rape production region, the Middle Reaches of the Yangtze River Valley (MYR), during 2003–2015 using time-series Moderate Resolution Imaging Spectroradiometer (MODIS) data. A decision tree according to the difference in enhanced vegetation index (EVI) profiles of land-cover types was built to extract winter rape. The results show that there is an essential decrease in both the number and density of winter rape patches under the opening global rapeseed market. There are significant hotspots of winter rape gain and loss, within which the loss dominated the trend. The significant cost advantage of rapeseed in the international market may largely reduce the domestic cultivation in China through telecoupling effects. Understanding the spatio-temporal dynamics of winter rape on the MYR has significant economic and policy implications and can provide great supports for the agricultural production, policy-making, and oil products trade in the international market.

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