Conditioning a Hydrologic Model Using Patterns of Remotely Sensed Land Surface Temperature

2018 ◽  
Vol 54 (4) ◽  
pp. 2976-2998 ◽  
Author(s):  
Matthias Zink ◽  
Juliane Mai ◽  
Matthias Cuntz ◽  
Luis Samaniego
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remotely Sensed ◽  
Hydrologic Model

scholarly journals Urban Irrigation Suppresses Land Surface Temperature and Changes the Hydrologic Regime in Semi-Arid Regions

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1563 ◽  
Author(s):  
Bryant Reyes ◽  
Terri Hogue ◽  
Reed Maxwell
Keyword(s):  
Surface Temperature ◽  
Water Use ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remotely Sensed ◽  
Hydrologic Model ◽  
Hydrologic Regime ◽  
Surface Temperatures ◽  
Land Surface Temperatures ◽  
Semi Arid

Outdoor water use for irrigation constitutes a substantial urban water flux yet its impact on the land surface remains poorly quantified. This study analyzes the impact of irrigation on land surface temperatures and the hydrologic regime of a large, semi-arid urban metropolis. Using remotely sensed products, municipal water use data, and simulations with a coupled land surface-hydrologic model we find significant impacts on both land surface temperatures and the hydrologic dynamics of the study domain, Los Angeles, CA. The analysis of remotely sensed land surface temperature finds a decrease of up to 3.2 ± 0.02 K between low and high irrigation areas of similar land cover. These temperature differences, caused by a human-induced flux, are on par with estimates of the urban heat island effect and regional warming trends; simulations are able to capture this difference but underestimate absolute values throughout. Assessment of change in irrigation volume and timing through simulations show that irrigation timing has a small impact (<±2%) on evapotranspiration and runoff. Furthermore, relatively low irrigation volumes push the semi-arid urban environment into a sub-humid regime.

scholarly journals A Review of Reconstructing Remotely Sensed Land Surface Temperature under Cloudy Conditions

2021 ◽  
Vol 13 (14) ◽  
pp. 2838
Author(s):  
Yaping Mo ◽  
Yongming Xu ◽  
Huijuan Chen ◽  
Shanyou Zhu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spatial Scales ◽  
Remotely Sensed ◽  
Urban Heat Islands ◽  
Reconstruction Algorithms ◽  
Gap Filling ◽  
Practical Applications ◽  
Data Gaps

Land surface temperature (LST) is an important environmental parameter in climate change, urban heat islands, drought, public health, and other fields. Thermal infrared (TIR) remote sensing is the main method used to obtain LST information over large spatial scales. However, cloud cover results in many data gaps in remotely sensed LST datasets, greatly limiting their practical applications. Many studies have sought to fill these data gaps and reconstruct cloud-free LST datasets over the last few decades. This paper reviews the progress of LST reconstruction research. A bibliometric analysis is conducted to provide a brief overview of the papers published in this field. The existing reconstruction algorithms can be grouped into five categories: spatial gap-filling methods, temporal gap-filling methods, spatiotemporal gap-filling methods, multi-source fusion-based gap-filling methods, and surface energy balance-based gap-filling methods. The principles, advantages, and limitations of these methods are described and discussed. The applications of these methods are also outlined. In addition, the validation of filled LST values’ cloudy pixels is an important concern in LST reconstruction. The different validation methods applied for reconstructed LST datasets are also reviewed herein. Finally, prospects for future developments in LST reconstruction are provided.

scholarly journals Temporal Variations and Associated Remotely Sensed Environmental Variables of Dengue Fever in Chitwan District, Nepal

2018 ◽  
Vol 7 (7) ◽  
pp. 275 ◽  
Author(s):  
Bipin Acharya ◽  
Chunxiang Cao ◽  
Min Xu ◽  
Laxman Khanal ◽  
Shahid Naeem ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Dengue Fever ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Environmental Variables ◽  
Vegetation Index ◽  
Generalized Additive Model ◽  
Additive Model ◽  
Remotely Sensed ◽  
Cross Correlation Analysis

Dengue fever is one of the leading public health problems of tropical and subtropical countries across the world. Transmission dynamics of dengue fever is largely affected by meteorological and environmental factors, and its temporal pattern generally peaks in hot-wet periods of the year. Despite this continuously growing problem, the temporal dynamics of dengue fever and associated potential environmental risk factors are not documented in Nepal. The aim of this study was to fill this research gap by utilizing epidemiological and earth observation data in Chitwan district, one of the frequent dengue outbreak areas of Nepal. We used laboratory confirmed monthly dengue cases as a dependent variable and a set of remotely sensed meteorological and environmental variables as explanatory factors to describe their temporal relationship. Descriptive statistics, cross correlation analysis, and the Poisson generalized additive model were used for this purpose. Results revealed that dengue fever is significantly associated with satellite estimated precipitation, normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI) synchronously and with different lag periods. However, the associations were weak and insignificant with immediate daytime land surface temperature (dLST) and nighttime land surface temperature (nLST), but were significant after 4–5 months. Conclusively, the selected Poisson generalized additive model based on the precipitation, dLST, and NDVI explained the largest variation in monthly distribution of dengue fever with minimum Akaike’s Information Criterion (AIC) and maximum R-squared. The best fit model further significantly improved after including delayed effects in the model. The predicted cases were reasonably accurate based on the comparison of 10-fold cross validation and observed cases. The lagged association found in this study could be useful for the development of remote sensing-based early warning forecasts of dengue fever.

Remotely sensed retrieval of Local Climate Zones and their linkages to land surface temperature in Harare metropolitan city, Zimbabwe

Urban Climate ◽  
2019 ◽  
Vol 27 ◽  
pp. 259-271 ◽  
Author(s):  
Terence Darlington Mushore ◽  
Timothy Dube ◽  
Moven Manjowe ◽  
Wester Gumindoga ◽  
Abel Chemura ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remotely Sensed ◽  
Climate Zones ◽  
Local Climate ◽  
Metropolitan City ◽  
Local Climate Zones
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