scholarly journals GENERATING TIME SERIES OF MEDIUM-RESOLUTION TEMPERATURE VEGETATION DROUGHT INDEX IMAGES USING A KALMAN FILTER METHOD FOR SOIL MOISTURE CHANGE ANALYSIS

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 495-501
Author(s):  
H. Zhai ◽  
F. Huang ◽  
H. Qi ◽  
Y. Ren ◽  
R. Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Soil Moisture ◽  
Kalman Filter ◽  
Land Surface ◽  
Time Series Data ◽  
Series Data ◽  
Modis Data ◽  
Medium Resolution ◽  
Short Period

Abstract. Soil moisture is one of key environmental variables that affect vegetation cover and energy exchange between the land surface and the atmosphere. Satellite remote sensing technology can provide information for monitoring large-scale soil moisture dynamics quickly. The temperature vegetation dryness index (TVDI) acts as an effective indicator of inferring soil moisture status which is calculated according to the empirical parameterization of composed of the land surface temperature (LST) and the normalized difference vegetation index (NDVI) characteristic space. In this paper, the MODIS TVDI was calculated based on MODIS LST product (MOD11A2, 1 km) and NDVI data (derived from MOD09A1, 500m). Meanwhile, LST and NDVI from Landsat8 OLI images were estimated to obtain Landsat-based TVDI. Then, a Kalman filter algorithm was used to simulate TVDI time series data with 30m resolution and a revisit period of 8 days combining TVDI derived from Landsat and MODIS data. We selected the west of the Songnen Plain, China as the test area and high quality cloudy-free images during growing season (April to October) of 2018 as the input data. The predicted TVDI time series data of medium resolution not only improved the temporal resolution to capture the changes at fine scale within a short period, but also made up for the deficiency of low spatial resolution MODIS data. The results show that it is feasible to generate medium or high resolution TVDI time series data by applying different remote sensing data by Kalman filtering algorithm.

scholarly journals Freshwater-salt water interface dynamics during pumping tests

2019 ◽  
Author(s):  
Yongcheol Kim ◽  
Heesung Yoon ◽  
Soo-Hyung Lee
Keyword(s):  
Time Series ◽  
Coastal Aquifer ◽  
Time Series Data ◽  
Temporal Change ◽  
Salt Water ◽  
Series Data ◽  
Water Interface ◽  
Aquifer Management ◽  
Pumping Tests ◽  
Short Period

Freshwater-salt water interface (FSI) location is very important information for decision maker in managing coastal aquifer system, however, its temporal change have been hard to get using conventional method such as EC monitoring at one or several fixed depths, geophysical logging or remote sensing techniques. A FSI tracking device, which has density between freshwater and salt water and hence can moves up and down as the freshwater-salt water transition zone moves, is used to get a temporal change data for the interface during several different types of pumping tests, which were performed at coastal monitoring wells in Seocheon, middle west of Korean Peninsula. Four short period pumping tests, three long-period pumping tests, one step-drawdown test, one reverse step-drawdown test were performed at different pumping rate ranging 19.86 to 48.71 m3/d for different pumping period of 60 minutes to 2851 minutes. Time series data shows that the Interface-Egg rises up from -86.0 to -77.6 m amsl after 24-hours pumping and to -40.8 m amsl after 2-days pumping and freshwater lens thickness is getting thinner from 88.1 m to 78.4 m after 24-hours pumping and then 42.3 m after 2-days pumping. These salt water up-coning phenomena are supported by EC profiles which were logged before and after the whole pumping periods. Time series data tell us that salt water upconing in the pumping well happens quickly and recovers at a very slow rate which is about 1.5 cm/d at 3 months after stopping pumping. The time series data of groundwater head and the interface-Egg’s location also shows that there is a tidal influence between pumping periods. The FSI tracker is expected to be practically applied to coastal aquifer management preventing from salt water intrusion, especially at dynamically pumping area for agricultural and/or domestic water supply.

scholarly journals Spatial Pattern of Agricultural Productivity Trends in Malawi

2020 ◽  
Vol 12 (4) ◽  
pp. 1313
Author(s):  
Leah M. Mungai ◽  
Joseph P. Messina ◽  
Sieglinde Snapp
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Series Data ◽  
Agricultural Productivity ◽  
Household Survey ◽  
Maize Yield ◽  
Series Data ◽  
Maize Crop

This study aims to assess spatial patterns of Malawian agricultural productivity trends to elucidate the influence of weather and edaphic properties on Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) seasonal time series data over a decade (2006–2017). Spatially-located positive trends in the time series that can’t otherwise be accounted for are considered as evidence of farmer management and agricultural intensification. A second set of data provides further insights, using spatial distribution of farmer reported maize yield, inorganic and organic inputs use, and farmer reported soil quality information from the Malawi Integrated Household Survey (IHS3) and (IHS4), implemented between 2010–2011 and 2016–2017, respectively. Overall, remote-sensing identified areas of intensifying agriculture as not fully explained by biophysical drivers. Further, productivity trends for maize crop across Malawi show a decreasing trend over a decade (2006–2017). This is consistent with survey data, as national farmer reported yields showed low yields across Malawi, where 61% (2010–11) and 69% (2016–17) reported yields as being less than 1000 Kilograms/Hectare. Yields were markedly low in the southern region of Malawi, similar to remote sensing observations. Our generalized models provide contextual information for stakeholders on sustainability of productivity and can assist in targeting resources in needed areas. More in-depth research would improve detection of drivers of agricultural variability.

Short Period Oscillations in Acturus, Aldebaran, and Pollux

1988 ◽  
Vol 132 ◽  
pp. 291-294
Author(s):  
Peter H. Smith ◽  
Robert S. McMillan
Keyword(s):  
Time Series ◽  
Preliminary Analysis ◽  
Time Series Data ◽  
Careful Analysis ◽  
Series Data ◽  
Short Period ◽  
Stellar Velocity ◽  
Clean Algorithm ◽  
K Giants

A total of 48 nights of time series data have been obtained for the K giants: Arcturus, Pollux, and Aldebaran. A careful analysis of both single and multi–night sets using the earth's motion as a velocity calibrator has yielded stellar velocity time series accurate to ± 3 m/s per observation. Periodogram analyses of these sets have revealed the existence of oscillations with periods near 2.5 hrs and amplitudes of ± 5 m/s for both Pollux and Aldebaran, but not for Arcturus. Preliminary analysis of a 5-night set for Pollux using the CLEAN algorithm suggests at least three modes separated by about 35 microHertz.

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