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Introduction
Xiaopo does research in Remote Sensing, Water Science and Soil Science. Their most recent publication is 'Spatial Up-Scaling Correction for Leaf Area Index Based on the Fractal Theory'.
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Publications
Publications (27)
Above-ground biomass (AGB) of rice is crucial for monitoring growth and predicting yields. While deep learning algorithms, like deep convolutional neural networks (DCNNs), show compelling performance in estimating crop parameters, gathering sufficient ground-truth samples for model training poses a significant challenge, leading to the "small sampl...
Land Surface Temperature (LST) is widely used as a crucial parameter to monitor the energy exchange and cycle processes over the globe. Constructing seamless LST datasets with high accuracy is crucial to study its influence on climate. However, existing remote sensing methods for estimating LST are inevitably limited by cloud contaminations, leadin...
A R T I C L E I N F O Edited by Jing M. Chen Keywords: Outgoing longwave radiation (OLR) Radiation transfer simulation Multi-Dimensional matrix MAPping (MDMAP) Polynomial regression Moderate resolution imaging Spectroradiometer (MODIS) Cloud and Earth's radiant energy system (CERES) A B S T R A C T Outgoing Longwave Radiation (OLR) is an important...
The challenges of utilizing the 250-m resolution thermal infrared (TIR) data obtained from the Medium Resolution Spectral Imager-II (MERSI-II) onboard the Chinese Fengyun-3D (FY-3D) satellite are bowtie effect and non-uniform brightness stripe noise. While previous solutions have addressed these issues separately, this manuscript introduced a more...
Accurate retrieval of ice surface temperature (IST) over the Arctic ice-water mixture zone (IWMZ) is significantly essential for monitoring the change of the polar sea ice environment. Previous researchers have focused on evaluating the accuracy of IST retrieval in pack ice regions, possibly on account of the availability of in situ measurement dat...
Land surface temperature (LST) is a crucial parameter needed to study the thermal environment in urban areas. Currently, it can be restored from thermal infrared (TIR) measurements based on various LST retrieval algorithms. But the expected urban LST retrieval accuracy of <1 K is difficult to achieve because knowledge is lacking on how to correct t...
Land surface temperature (LST) is a pivotal parameter in many study areas. At present, numerous algorithms are available to retrieve accurate LST from different satellite thermal infrared (TIR) observations. However, rare studies focus on simultaneous LST and land surface emissivity (LSE) retrieval from the TIR measurements of MERSI-II onboard Chin...
Land surface temperature (LST) is an essential input for modeling the processes of energy exchange and balance of the earth's surface. Thermal infrared (TIR) remote sensing is considered to be the most efficient way to obtain accurate LST, both regionally and globally. Currently, many LST retrieval algorithms have been developed, including the up-t...
Ice/snow surface temperature (I/SST) is an essential parameter in many research fields such as the climate change, energy and matter balance of the South pole regions. Currently, many algorithms have been developed for various satellite observations to derive the I/SST. However, rare studies focus on accurate I/SST retrieval from the observations o...
Accurate estimations of daily mean land surface temperature (LST) are important for investigating the urban heat island effect, land-atmosphere energy exchanges, and global climate change. Moderate Resolution Imaging Spectroradiometer (MODIS) sensors can provide up to four instantaneous LSTs of a single day across the world. However, numerous studi...
Land surface temperature (LST) is a key parameter for many fields of study. Currently, LST retrieved from satellite thermal infrared (TIR) measurements is attainable with an accuracy of about 1 K for most natural flat surfaces. However, over urban areas, TIR measurements are influenced by 3-D structures and their radiation that could degrade the pe...
Land surface temperature (LST) is an important parameter of the Earth surface. However, there are still some factors influencing the urban LST retrieval accuracy but have not been well addressed in existing LST retrieval algorithms: (1) the adjacency effect in the thermal infrared (TIR) spectral region; (2) the impact of the three-dimensional struc...
Land surface temperature (LST) is an important parameter in many research fields. Many algorithms have been developed to retrieve LST from satellite thermal infrared (TIR) measurements; of these, the most widely used are the split window (SW) and temperature–emissivity separation (TES) methods. However, the performance of the SW and TES methods can...
Sensor-observed energy from adjacent pixels, known as the adjacency effect, influences land surface reflectivity retrieval accuracy in optical remote sensing. As the spatial resolution of thermal infrared (TIR) images increases, the adjacency effect may influence land surface temperature (LST) retrieval accuracy in TIR remote sensing. However, to o...
The scaling effect correction of retrieved parameters is an essential and difficult issue in analysis and application of remote sensing information. Based on fractal theory, this paper developed a scaling transfer model to correct the scaling effect of the leaf area index (LAI) estimated from coarse spatial resolution image. As the key parameter of...
This paper proposes a scaling transfer model based on fractal theory to retrieve the leaf area index (LAI) at different spatial resolutions and to evaluate the scaling bias on the LAI retrieved from coarse resolution images. The LAI scaling transfer model was developed by establishing the double logarithmic linear relationship between the scale n (...
Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on...
The spatio-temporal distribution and variation of soil moisture content have a significant impact on soil temperature, heat balance between land and atmosphere and atmospheric circulation. Hence, it is of great significance to monitor the soil moisture content dynamically at a large scale and to acquire its continuous change during a certain period...
We report here on the relationship between titanium abundance and its spectral features on the Moon, using 36 craters exposed in Sinus Iridum, a landing site for China's Lunar Exploration Program. Six absorption parameters (Full Wave at Half Maximum (FWHM), absorption depth (D), absorption position (λ), absorption area (A), absorption asymmetry (S)...
In the paper, we developed a novel method of soil moisture estimation in vegetated area base on the simulation result of Cupid model[1], and it was found that LAI and land surface temperture (Ts) appeared in logarithmic relation rather than linear traditionally TVDI (Temperature Vegetation Dryness Index) assumed. Then the soil moisture in vegetated...
