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Soil temperature is one of the essential variables governing the land atmosphere interaction. In this study, we proposed a statistical algorithm to retrieve the surface soil temperature from AMSR-E brightness temperature (TB) observations. The algorithm was developed based on the regression relationship between AMSR-E TB and corresponding in situ soil temperature observed at the Naqu network in the...
The commonly applied triangular method was used to estimate regional evapotranspiration(ET). Based on the parameters of land surface, the applicability of NDVI-land surface temperature(NDVI-LST) and NDVI-albedo triangular methods were validated using the landsat7 data and the Heihe Watershed Allied Telemetry Experimental Research(HiWATER) observed data. Considering the affecting of soil moisture and...
As a close proxy of the GOES-R Advanced Baseline Imager (ABI) instrument, the on-board 16-band Advanced Himawari Imager (AHI) brings an unprecedented opportunity to exercise the ABI algorithms developed for GOES-R in the STAR Algorithm Processing Framework (SAPF). STAR has been collaborating with JMA and NASA since AHI's post launch checkout and has been acquiring the full resolution AHI data form...
Significant changes have occurred in permafrost and seasonally frozen soils in the Tibetan Plateau (TP) during the last few decades, with potential influence on regional climate, hydrological and ecosystem processes. Land surface temperature (LST) is closely associated with surface energy balance, thus is a critical parameter affecting the frozen soil thermodynamics. Satellite remote sensing provides...
Surface soil moisture (SSM) is a significant variable in various fields of science. This paper aims to analyze and improve a SSM retrieval model to apply it to estimate SSM at the regional scale. Firstly, the model parameters were been analyzed. The rotation angle was transformed into exponential form and the ellipse center horizontal coordinate was decreased for the improved SSM retrieval model....
This paper analyzes the influence of the anomalous temperature occurred at the near surface boundary layer of the atmosphere on the land surface temperature (LST) retrieval with the generalized split-window algorithm (GSW). The coefficients in the GSW algorithm corresponding to a series of overlapping ranging of the mean emissivity, the atmospheric water vapor content, and the LST are derived using...
An algorithm has been developed for retrieving instantaneous microwave land surface emissivity using brightness temperature and precipitable water vapor data. Unlike previous algorithms, the new technique does not need infrared land surface temperature as the input data, and overcomes the limitation of previous algorithms under cloudy conditions. Compared with the values from physical retrieval algorithm,...
Land surface temperature (LST) plays a crucial role in energy balance of the earth system. Retrieving LST from the lunar can outperform artificial earth satellite. But there are no datasets acquired for earth observation from the lunar, yet. In order to obtain the thermal infrared images of the earth, used for LST retrieval, from the lunar, it is necessary to calculate the land surface thermal infrared...
Northeast China, one of the most important grain producing regions in China, is vulnerable to drought. Timely, accurate and effective drought monitoring in the region is very essential to secure its output grain production. In this paper, the temporal and spatial distribution of drought in Northeast China was analyzed based on the TVDI. Also the drought change trend from 2001–2013 in Northeast China...
Water vapor plays an important roles in the Earth's energy and water cycles. Compared to optical remote sensing, microwave remote sensing has the advantage to acquire information of atmosphere under cloudy condition. Up to now, there is no published reliable total precipitable water product over land from AMSR2 due to effect of high land surface emissivity in microwave band. In this study, an improved...
The systemic validation works were carried out at a watershed scale based on the ground-based observation data of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER). Three validation strategies, scaling-up, spatial representation analysis, footprint analysis were used based on different data acquirement techniques. Some studies were performed and four types of remote sensing products...
The quantification of forest Gross Primary Productivity (GPP) has been the focus of many scientific studies (e.g. carbon cycle, climate change, etc.). Current remote sensing-based models (i.e., the MODIS MOD_17 model), rely on the accurate meteorological data, specific vegetation parameter, the applicability and explicability of remote sensing data. In this study, the original MODIS GPP products were...
Airborne TIR remote sensing can obtain land surface temperature (LST) with high spatial resolution. However, the swath width of airborne stripes is usually limited. Therefore, it is necessary to generate the LSTs for a large area through temporal normalization of LSTs derived from different stripes. By selecting an agricultural oasis as the study area, this study compares the diurnal temperature cycle...
Soil Moisture and Ocean Salinity (SMOS) is the first L-band passive microwave mission dedicated to soil moisture (SM) monitoring but has coarse resolution. SMOS SM was downscaled by Back propagation neural network (BPNN) and MODIS LST and EVI, and was evaluated by intensive 56 stations in-situ obtained from the mesoscale Tibetan Plateau Soil Moisture/Temperature Monitoring Network (SMTMN) during 2010–2012...
Soil moisture derived from the SMAP passive microwave radiometers has a spatial resolution of 36km. In the case of applications of weather, catchment hydrology and agriculture there is a requirement of high spatial resolution. In this paper we present an innovative method to downscale passive soil moisture retrievals using vegetation index and surface temperature.
In this study, a single-channel parametric model (SC-PM) algorithm were used to produce 300m LST product from HJ-1B IRS data. The NCEP atmospheric profiles and a parametric model were used for atmospheric correction. In order to improve the accuracy of the land surface emissivity (LSE), the 1km ASTER Global Emissivity Dataset (GED) and self-developed 5-day 1km vegetation cover product were used for...
For some strong earthquakes, thermal anomaly occurs before the event, however not definitely. In this study, time series of MODIS Land Surface Temperature (LST) products have been processed and analyzed to locate possible anomalous variations prior to the Lushan (20 April 2013) earthquakes. In order to exclude the seasonal or annual effects from the LST variations, also to avoid the rainy and cloudy...
Land degradation is one of most serious socio-ecological problems in Northeast Asia dryland regions (NADR), which requires reliable assessments on degree and extent of land degradation. This paper aims (1) to assess the applicability of Rainfall Use Efficiency (RUE) and Precipitation Marginal Response (PMR) in monitoring land degradation in NADR, and (2) to analyze natural factors for land degradation...
In this paper, an approach for oil contaminated wastewater recognition is presented. By analyzing the relationship between thermal and multispectral characteristics of clean water and oil contaminated wastewater. The Oil Contaminated Wastewater Index (OCWI) was then developed to extract the oil contaminated wastewater. Results show that remote sensing can be of great help in tracking the oil contaminated...
This study compares VIIRS LST with ground in-situ observations from Baseline Surface Radiation Network (BSRN) and Global Monitoring Division (GMD) baseline observatories. The validation results present a close agreement between satellite estimation and ground observations with the accuracy about −0.4 K and −0.7 K, precision of 2.1 and 1.8 over BSRN CAB site and GOB site, respectively. A precision...
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