Toward “all weather,” long record, and real-time land surface temperature retrievals from microwave satellite observations

2016 ◽  
Vol 121 (10) ◽  
pp. 5699-5717 ◽  
Author(s):  
C. Prigent ◽  
C. Jimenez ◽  
F. Aires
Keyword(s):  
Surface Temperature ◽  
Real Time ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Satellite Observations

scholarly journals Land Surface Temperature Retrieval from Passive Microwave Satellite Observations: State-of-the-Art and Future Directions

2020 ◽  
Vol 12 (16) ◽  
pp. 2573
Author(s):  
Si-Bo Duan ◽  
Xiao-Jing Han ◽  
Cheng Huang ◽  
Zhao-Liang Li ◽  
Hua Wu ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Important Variable ◽  
Satellite Observations ◽  
Passive Microwave ◽  
Empirical Methods ◽  
Physically Based ◽  
Temperature Retrieval ◽  
Semi Empirical

Land surface temperature (LST) is an important variable in the physics of land–surface processes controlling the heat and water fluxes over the interface between the Earth’s surface and the atmosphere. Space-borne remote sensing provides the only feasible way for acquiring high-precision LST at temporal and spatial domain over the entire globe. Passive microwave (PMW) satellite observations have the capability to penetrate through clouds and can provide data under both clear and cloud conditions. Nonetheless, compared with thermal infrared data, PMW data suffer from lower spatial resolution and LST retrieval accuracy. Various methods for estimating LST from PMW satellite observations were proposed in the past few decades. This paper provides an extensive overview of these methods. We first present the theoretical basis for retrieving LST from PMW observations and then review the existing LST retrieval methods. These methods are mainly categorized into four types, i.e., empirical methods, semi-empirical methods, physically-based methods, and neural network methods. Advantages, limitations, and assumptions associated with each method are discussed. Prospects for future development to improve the performance of LST retrieval methods from PMW satellite observations are also recommended.

scholarly journals Assessment of agricultural drought in Morocco based on a composite of the Vegetation Health Index (VHI) and Standardized Precipitation Evapotranspiration Index (SPEI)

2021 ◽  
Vol 314 ◽  
pp. 04003
Author(s):  
Sara Moutia ◽  
Mohamed Sinan ◽  
Brahim Lekhlif
Keyword(s):  
Surface Temperature ◽  
Real Time ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Agricultural Drought ◽  
Health Index ◽  
Spatial Coverage ◽  
Vegetation Health ◽  
Vegetation Health Index

According to IPCC, Morocco is a highly vulnerable country to extreme climate events, especially droughts; this will affect different socioeconomic sectors, mainly the agriculture sector. Droughts are controlled by the variability of precipitation and evapotranspiration but also not neglecting the effect of land surface conditions such as land surface temperature. In this present study, the remote sense observations MODIS Normalized Difference Vegetation Index (NDVI) and CMSAF Land Surface Temperature (LST) were used for calculating the Vegetation Health Index (VHI). The main advantage of remote sensing products is that they are reasonably efficient in terms of temporal and spatial coverage, and they are useful for the monitoring and assessment of drought in the near real-time. Furthermore, ERA5 Reanalysis-based SPEI is calculated. The goal of this study is to assess the spatial and temporal patterns of drought, this study offers the composite of SPEI and VHI drought monitoring obtained by plotting maps and graphs to show the monthly and annual variability of drought for the period 2000–2015 over the whole of Morocco. This monitoring can be used as a near real-time warning system in a changing climate.

Near-real time retrievals of land surface temperature within the MODIS Rapid Response System

2007 ◽  
Vol 106 (3) ◽  
pp. 326-336 ◽  
Author(s):  
A.C.T. Pinheiro ◽  
J. Descloitres ◽  
J.L. Privette ◽  
J. Susskind ◽  
L. Iredell ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Real Time ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Rapid Response ◽  
Rapid Response System ◽  
Response System
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