Xiaodong Huang

Xiaodong Huang

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38
Publications
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Introduction
Skills and Expertise

Publications

Publications (38)
Article
Full-text available
Soil moisture content (SMC) is an indispensable basic element for crop growth and development in agricultural production. Obtaining accurate information on SMC in real time over large agricultural areas has important guiding significance for crop yield estimation and production management. In this study, the paper reports on the retrieval of SMC fr...
Article
Full-text available
Soil moisture content (SMC) is a significant factor affecting crop growth and development. However, SMC estimation, based on synthetic aperture radar (SAR), is influenced by a variety of surface parameters, such as vegetation cover and surface roughness. As a result, determining the SMC across agricultural areas (e.g., wheat fields) remotely (i.e.,...
Article
Full-text available
Rice false smut (RFS), caused by Ustilaginoidea virens, is a significant grain disease in rice that can lead to reduced yield and quality. In order to obtain spatiotemporal change information, multitemporal hyperspectral UAV data were used in this study to determine the sensitive wavebands for RFS identification, 665–685 and 705–880 nm. Then, two m...
Article
Accurate knowledge of the distribution, breadth and change in agricultural activity is important to food security and the related trade and policy mechanisms. Routine observations afforded by spaceborne Synthetic Aperture Radar (SAR) allows for high-fidelity monitoring of agricultural parameters at the field scale. Here we evaluate the approach to...
Article
Full-text available
Soil moisture is vital for the crop growth and directly affects the crop yield. Conventional SAR based soil moisture monitoring is often influenced by vegetation cover and surface roughness. Machine-learning methods are not constrained by physical parameters and have high nonlinear fitting capabilities. In this study, machine-learning methods were...
Article
Full-text available
Abstract Irrigated rice requires intense water management under typical agronomic practices. Cost effective tools to improve the efficiency and assessment of water use is a key need for industry and resource managers to scale ecosystem services. In this research we advance model‐based decomposition and machine learning to map inundated rice using t...
Article
Full-text available
Crop area mapping is important for tracking agricultural production and supporting food security. Spaceborne approaches using synthetic aperture radar (SAR) now allow for mapping crop area at moderate spatial and temporal resolutions. Multi-frequency SAR data is highly useful for crop monitoring because backscatter response from vegetation canopies...
Article
Full-text available
Abstract Synthetic Aperture Radar (SAR) data are well‐suited for change detection over agricultural fields, owing to high spatiotemporal resolution and sensitivity to soil and vegetation. The goal of this work is to evaluate the science algorithm for the NASA ISRO SAR (NISAR) Cropland Area product using data collected by NASA's airborne Uninhabited...
Article
Full-text available
Soil moisture is a key indicator to assess cropland drought and irrigation status as well as forecast production. Compared with the optical data which are obscured by the crop canopy cover, the Synthetic Aperture Radar (SAR) is an efficient tool to detect the surface soil moisture under the vegetation cover due to its strong penetration capability....
Article
Full-text available
Soil moisture (Mv) estimation and monitoring over agricultural areas using Synthetic Aperture Radar (SAR) are often affected by vegetation cover during the growing season. Volume scattering and vegetation attenuation can complicate the received SAR backscatter signal when microwave interacts with the vegetation canopy. To address the existing probl...
Article
Planned satellite launches will provide open access and operational L-band radar data streams at space-time resolutions not previously available. To further prepare, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) platform was used to observe cropland sites across the southern United States to support the development of L-band (24...
Article
Full-text available
Chlorophyll is an essential pigment for photosynthesis in crops, and leaf chlorophyll content can be used as an indicator for crop growth status and help guide nitrogen fertilizer applications. Estimating crop chlorophyll content plays an important role in precision agriculture. In this study, a variable, rate of change in reflectance between wavel...
Article
Full-text available
Numerous studies have examined the changes in streamflow in the Mekong River Basin (MRB) using observations and hydrological modeling; however, there is a lack of integrated modeling studies that explicitly simulate the natural and human-induced changes in flood dynamics over the entire basin. Here we simulate the river-floodplain-reservoir inundat...
Article
Full-text available
Annual crop inventory information is important for many agriculture applications and government statistics. The synergistic use of multi-temporal polarimetric synthetic aperture radar (SAR) and available multispectral remote sensing data can reduce the temporal gaps and provide the spectral and polarimetric information of the crops, which is effect...
Article
The polarimetric Synthetic Aperture Radar (PolSAR) signal contains more parameters than single or dual polarized SAR when using a scattering matrix to characterize targets. The increased information content of PolSAR provides more potential inputs for machine learning and classification applications; however, polarimetric parameters tend to be simp...
Article
Full-text available
Surface soil moisture (SSM) retrieval over agricultural fields using synthetic aperture radar (SAR) data is often obstructed by the vegetation effects on the backscattering during the growing season. This paper reports the retrieval of SSM from RADARSAT-2 SAR data that were acquired over wheat and soybean fields throughout the 2015 (April to Octobe...
Article
Full-text available
Recent conflict along the border of Bangladesh and Myanmar has amplified a food security crisis and access to the region remains challenging. Moderate-resolution satellite remote sensing offers an approach to complement more traditional food insecurity hot spot assessment across Rakhine, Myanmar; however, conflict creates unique signals that are no...
Article
Full-text available
Up-to-date spatial information on ground movements and land use is useful for emergency management of coastal regions. Time series InSAR techniques have proven to be effective tools for providing the former; however, InSAR results alone cannot be used to characterize the relationship between movements and land use. The focus of this study is to eva...
Article
Agriculture is an important sector in Canada, and annual crop inventories are required in many agricultural applications. Multi-temporal polarimetric synthetic aperture radar (SAR) data have great potential in crop classification due to its less dependency on weather condition. This study, for the first time, investigated the effects of the Minimum...
Article
Full-text available
Synthetic Aperture Radar (SAR), as an active sensor transmitting long wavelengths, has the advantages of working day and night and without rain or cloud disturbance. It is further able to sense the geometric structure of forests more than passive optical sensors, making it a valuable tool for mapping forest Above Ground Biomass (AGB). This paper st...
Article
Several studies have taken advantage of polarimetric synthetic aperture radar (PolSAR) to monitor forest disturbance caused by wildfire given its higher sensitivity to forest structure compared to single polarization SAR. This letter explores the capability of a simple volume scattering model (SVSM) to characterize burned forested area caused by wi...
Article
Full-text available
Crop type inventory and within season estimates at moderate (<30 m) resolution have been elusive in many regions due to the lack of temporal frequency, clouds, and restrictive data policies. New opportunities exist from the operational fusion of Landsat-8 Operational Land Imager (OLI), Sentinel-2 (A & B), and Sentinel-1 (A & B) which provide more f...
Article
Increasing studies have been conducted to investigate the potential of polarimetric synthetic aperture radar (SAR) in crop growth monitoring due to the capability of penetrating the clouds, haze, light rain, and vegetation canopy. This study investigated the sensitivity of 16 parameters derived from C-band Radarsat-2 polarimetric SAR data to crop h...
Article
Information on crop phenological development stages such as emergence, flowering, fruiting, maturing and senescence is essential for crop production surveillance and yield prediction. It has long been related to optical spectral signatures such as the Normalized Difference Vegetation Index (NDVI) or spectral shifts in the red-edge range. In recent...
Article
This paper presents a novel method of multi-temporal land cover classification based on the polarization signature (PS). Additionally, the temporal change of the scattering mechanism of crops and other land cover classes is analyzed based on the PS. Firstly, the scattering mechanisms of corn, soybean, wheat, forest and urban over time are analyzed....
Article
In this letter, we attempt to improve existing model-based decomposition methods to estimate the soil moisture for C-band RADARSAT-2 data. An adaptive two-component decomposition (ATCD) is developed that considers the surface and volume scattering caused by the soil and crop canopy, respectively. The surface scattering adopted is an X-Bragg scatter...
Article
Many research studies have investigated surface parameter inversion for bare soils. This paper attempts to take into account the agricultural fields with crop residues and fields under low vegetation cover in addition to bare soil fields. An integrated surface parameter inversion scheme (ISPIS) is proposed to invert surface parameters in these agri...
Article
A simplified adaptive volume scattering model (SAVSM) for RADARSAT-2 polarimetric synthetic aperture radar (PolSAR), based on the nth power sine and cosine functions, is developed to characterize the changes in crop phenology within the growing season. A threecomponent model-based decomposition (TCMD) with SAVSM is also implemented with the non-neg...
Article
Full-text available
This paper proposes an automated water body detection method to delineate detailed water bodies from high-resolution satellite images. It consists of three steps: a) coarse water mask detection from optical imagery using unsupervised classification; b) water mask refinement using backscatter value from synthetic aperture radar (SAR) images; and c)...
Conference Paper
In this paper, we proposed an Integrated Four-component Model-based Decomposition (IFMD) based on multi-look covariance matrix integrating the selective de-orientate and the generalized volume scattering. Firstly, a generalized volume scattering model (GVSM) is adopted to substitute the volume scattering of Freeman Decomposition. Then, the Cross Po...
Conference Paper
In the PC cluster environment, parallel algorithms can significantly improve the efficiency of remote sensing image processing. The remote sensing dataset is the raster data stored by order of band, therefore, it is feasible to assign executable tasks to some computing nodes by band and complete the processing tasks together through communicating e...

Projects

Projects (4)
Project
develop soil moisture retrieval algortihm for NISAR mission
Project
Dear Colleagues, Accurate and timely information of crop growth is essential to precision farming and sustainable agricultural production. Remote sensing data acquired by different platforms (e.g., satellite, airborne, UAV and ground) have been increasingly used to capture crop growth at various spatial and temporal scales. More recently, many newly developed sensors and data acquisition technologies have been developed to further enhance the capability of remote sensing in supporting crop growth monitoring and yield prediction. Multispectral imageries with red-edge bands, hyperspectral imageries and synthetic aperture radar imageries have become commonly available, providing unprecedented data support to stimulate innovation for crop monitoring. When combined with new data processing algorithms (e.g., machine learning and big data architecture) and high-performance computers, the power of remote technology has been unleashed. Given the improvement of advanced sensor technologies, the early detection of crop stress and the quantitation impacts on crop yield remain challenging. This special issue calls for innovative research in using remote sensing and other cutting-edge technologies such as data fusion and artificial intelligence to tackle the issues facing the modern field crop production. The topics include but are not limited to the following: Site-management zone delineation in precision agriculture Crop biophysical and biochemical parameter (e.g., LAI/fAPAR, leaf chlorophyll and leaf nitrogen) retrieval Crop biomass and yield estimation Crop logging detection Crop stress (e.g., nutrient, pests, diseases, drought, and heat stress) monitoring Crop progress (e.g., sowing, flowering, and harvest) detection In-season crop types classification Sustainable agricultural practices Deadline for manuscript submissions: 30 June 2022. https://www.mdpi.com/journal/remotesensing/special_issues/Crop_Growth_Monitoring
Project
Here we test some of the science algorithms to be used for NASA-ISRO SAR (NISAR) mission's ecosystem products by applying the approach to data available from platforms such as Sentinel-1 and UAVSAR (source data, simulated data and dithered data). NISAR's estimated launch date is early 2023.