42 Results Found

Abstract: Lookup-table (LUT)-based radiative transfer model inversion is considered a physically-sound and robust method to retrieve biophysical parameters from Earth observation data but regularization strategies are needed to mitigate the d...

Hyperspectral cameras onboard unmanned aerial vehicles (UAVs) have recently emerged for monitoring crop traits at the sub-field scale. Different physical, statistical, and hybrid methods for crop trait retrieval have been developed. However, spectra...

The upcoming satellite mission EnMAP offers the opportunity to retrieve information on the seasonal development of vegetation parameters on a regional scale based on hyperspectral data. This study aims to investigate whether an analysis method for th...

Look-up table (LUT)-based canopy reflectance models are considered robust methods to estimate vegetation attributes from remotely sensed data. However, the LUT inversion approach is sensitive to measurements and model uncertainties, which raise the i...

The need for an efficient and standard technique for optimal spectral sampling of hyperspectral data during the inversion of canopy reflectance models has been the subject of many studies. The objective of this study was to investigate the utility of...

Grassland aboveground biomass (AGB) is a crucial indicator when studying the carbon sink of grassland ecosystems. The exploration of the grassland AGB inversion method with viable reproducibility is significant for promoting the practicability and ef...

Leaf pigment contents, such as chlorophylls a and b content (C ${}_{ab}$ ) or carotenoid content (Car), and the leaf area index (LAI) are recognized indicators of plants’ and forests’ health status that can be estimated through hyperspectral image...

The leaf chlorophyll content (LCC) is a critical index to characterize crop growth conditions, photosynthetic capacity, and physiological status. Its dynamic change characteristics are of great significance for monitoring crop growth conditions and u...

An analytical radiative transfer (RT) model for remote sensing reflectance that includes the bidirectional reflectance distribution function (BRDF) is described. The model, called ZTT (Zaneveld-Twardowski-Tonizzo), is based on the restatement of the...

Key leaf functional traits, such as chlorophyll and carotenoids content (C_ab and C_xc), equivalent water thickness (EWT), and leaf mass per area (LMA), are essential to the characterization and monitoring of ecosystem function. Spectroscopy provides a...

Accurate and rapid estimation of the leaf area index (LAI) is essential for assessing crop growth and nutritional status, guiding farm management, and providing valuable phenotyping data for plant breeding. Compared to the tedious and time-consuming...

Leaf area index (LAI) is one of the key biophysical parameters in crop structure. The accurate quantitative estimation of crop LAI is essential to verify crop growth and health. The PROSAIL radiative transfer model (RTM) is one of the most establishe...

Look-up table (LUT) based method is a popular and effective way for inverse halftoning. However, it still has very large development space to improve the reconstructed color image quality for color halftone images, because most of the existing color...

Despite the potential implications of a cropland canopy water content (CCWC) thematic product, no global remotely sensed CCWC product is currently generated. The successful launch of the Landsat-8 Operational Land Imager (OLI) in 2012, Sentinel-2A Mu...

Automated, image based methods for the retrieval of vegetation biophysical and biochemical variables are often hampered by the lack of a priori knowledge about land cover and phenology, which makes the retrieval a highly underdetermined problem. This...

Vegetation biophysical parameter retrieval is an important earth remote sensing system application. In this paper, we studied the potential impact of the addition of new spectral bands in the red edge region in future Landsat satellites on agroecosys...

Leaf chlorophyll content (LCC) is a pivotal parameter in the monitoring of agriculture and carbon cycle modeling at regional and global scales. ENVISAT MERIS and Sentinel-3 OLCI data are suitable for use in the global monitoring of LCC because of the...

The hardware of the matrix inversion architecture using QR decomposition with Givens Rotations (GR) and a back substitution (BS) block is required for many signal processing algorithms. However, the hardware of the GR algorithm requires the implement...

Leaf chlorophyll content (LCC) significantly correlates with crop growth conditions, nitrogen content, yield, etc. It is a crucial indicator for elucidating the senescence process of plants and can reflect their growth and nutrition status. This stud...

Background/Objectives: The objective of this study is to explore potential correlations between prostate volume, LUTS, and IIEF, with a particular emphasis on the relationship between prostate dimensions—width, height, and length—and both...

Random number generation is essential in many application domains, including high-energy physics simulations. Implementing Monte Carlo methods that generate samples following a desired probability distribution is particularly challenging on hardware...

Background: Lower urinary tract (LUT) symptoms are reported in more than 80% of patients with multiple sclerosis (MS), most commonly an overactive bladder (OAB). The relationship between brain white matter (WM) changes in MS and OAB symptoms is poorl...

Leaf area index (LAI) plays an important role in models of climate, hydrology, and ecosystem productivity. The physical model-based inversion method is a practical approach for large-scale LAI inversion. However, the ill-posed inversion problem, due...

Near-real-time, high-spatial-resolution leaf area index (LAI) maps would enable producers to monitor crop health and growth status, improving agricultural practices such as fertiliser and water management. LAI retrieval methods are numerous and can b...

An accurate inversion of the fraction of absorbed photosynthetically active radiation (FPAR) based on remote sensing data is particularly important for understanding global climate change. At present, there are relatively few studies focusing on the...

The leaf area index (LAI), a key parameter used to characterize the structure and function of the vegetation canopy, is crucial to simulations of the carbon, nitrogen, and water cycles of Earth’s system. In this paper, a neural network (NN) met...

In this paper, we introduce a refined three-stage inversion algorithm (TSIA) for forest height estimation using polarimetric interferometric synthetic aperture radar (PolInSAR). Specifically, the iterative extraction of the boundary of the coherence...

With increasing demands in real-time or near real-time remotely sensed imagery applications in such as military deployments, quick response to terrorist attacks and disaster rescue, the on-board geometric calibration problem has attracted the attenti...

Lattice-based post-quantum cryptography relies on fast polynomial multiplication. The Number-Theoretic Transform (NTT) is the key operation that enables this acceleration. To provide high throughput and low latency while keeping the area overhead sma...

This paper proposes a combined approach comprising a set of methods for the high-precision mapping of soil moisture in a study area located in Jiangsu Province of China, based on the Chinese C-band synthetic aperture radar data of GF-3 and high spati...

Radiation transform models such as PROSAIL are widely used for crop canopy reflectance simulation and biophysical parameter inversion. The PROSAIL model basically assumes that the canopy is turbid homogenous media with a bare soil background. However...

A physically based algorithm is used for automatic processing of MERIS level 1B full resolution data. The algorithm is originally used with input variables for optimization with different sensors (i.e. channel recalibration and weighting), aquatic re...

Radiative transfer models predicting the bidirectional reflectance factor (BRF) of leaf canopies are powerful tools that relate biophysical parameters such as leaf area index (LAI), fractional vegetation cover fV and the fraction of photosyntheticall...

An extended Fourier approach was presented to improve the retrieved leaf area index (LAI_r) of herbaceous vegetation in a time series from an alpine wetland. The retrieval was performed from the Aqua MODIS 8-day composite surface reflectance product (...

In recent years, China has developed and launched several satellites with high spatial resolutions, such as the resources satellite No. 3 (ZY-3) with a multi-spectral camera (MUX) and 5.8 m spatial resolution, the satellite GaoFen No. 1 (GF-1) with a...

The estimation of aboveground biomass (AGB), an important indicator of grassland production, is crucial for evaluating livestock carrying capacity, understanding the response and feedback to climate change, and achieving sustainable development. Most...

This paper presents a comprehensive review of digital floating-point arithmetic algorithms that utilize Taylor series expansion in combination with mantissa-region division techniques, and it further demonstrates their generalization and applicabilit...

The leaf area index (LAI) is a key crop biophysical variable influencing many vegetation processes. Spatial LAI estimates are essential to develop and improve spatial modeling tools to monitor vegetation conditions at large regional scales. Numerous...

The Advanced Geostationary Radiation Imager (AGRI) is one of the primary payloads aboard the FY-4A geostationary meteorological satellite, which can provide high-frequency, wide coverage, and multiple spectral channel observations for China and surro...

In the modern era of the Internet of Things (IoT), especially with the rapid development of quantum computers, the implementation of postquantum cryptography algorithms in numerous terminals allows them to defend against potential future quantum atta...

As one of the most important greenhouse gases, water vapor plays a vital role in various weather and climate processes. In recent years, a near-infrared ratio technique based on satellite images has become a research hotspot in the field of precipita...

Mapping and monitoring of Arctic vegetation biochemical and biophysical properties is gaining importance as global climate change is disproportionately affecting this region. Previous studies using remote sensing to model Arctic vegetation biochemica...