scholarly journals Theoretical Evaluation of Water Cloud Model Vegetation Parameters

2019 ◽  
Vol 11 (8) ◽  
pp. 894 ◽  
Author(s):  
Park ◽  
Jung ◽  
Cho ◽  
Moon ◽  
Han
Keyword(s):  
Cloud Model ◽  
Orientation Distribution ◽  
Theoretical Evaluation ◽  
Vegetation Water Content ◽  
Water Cloud ◽  
Vegetation Parameters ◽  
Vegetation Water ◽  
The Relationship ◽  
Optimal Set ◽  
Theoretical Scattering

The advantage of implementing the Water Cloud Model (WCM) is in being able to express complex scattering characteristics in a vegetated area with simple bulk vegetation descriptors. However, there has been a lack of understanding or consensus about the optimal set of vegetation descriptors. In this paper, the original and improved expressions of WCM are evaluated and the optimal vegetation descriptors are presented by examining the relationship between WCM vegetation parameters and the theoretical scattering model predictions. In addition, the condition-specific regression relationship between bulk vegetation descriptors and theoretical scattering and attenuation coefficients, expressed by the A and B parameters in the WCM, is analyzed in relation to the shape, size, and orientation distribution of the scatterer. Furthermore, the influence of radar observation conditions on the parameterization of the WCM is presented. The results show that the particle moisture content and the vegetation water content can be the optimal vegetation descriptors, denoted by the V1 and V2 variables in the WCM, respectively.

scholarly journals Retrieval of High-Resolution Soil Moisture through Combination of Sentinel-1 and Sentinel-2 Data

2020 ◽  
Vol 12 (14) ◽  
pp. 2303 ◽  
Author(s):  
Chunfeng Ma ◽  
Xin Li ◽  
Matthew F. McCabe
Keyword(s):  
Surface Roughness ◽  
Soil Moisture ◽  
High Resolution ◽  
Water Content ◽  
Cloud Model ◽  
Cosmic Ray ◽  
Vegetation Water Content ◽  
Water Cloud ◽  
Vegetation Water ◽  
Sentinel 2

Estimating soil moisture based on synthetic aperture radar (SAR) data remains challenging due to the influences of vegetation and surface roughness. Here we present an algorithm that simultaneously retrieves soil moisture, surface roughness and vegetation water content by jointly using high-resolution Sentinel-1 SAR and Sentinel-2 multispectral imagery, with an application directed towards the provision of information at the precision agricultural scale. Sentinel-2-derived vegetation water indices are investigated and used to quantify the backscatter resulting from the vegetation canopy. The proposed algorithm then inverts the water cloud model to simultaneously estimate soil moisture and surface roughness by minimizing a cost function constructed by model simulations and SAR observations. To examine the performance of VV- and VH-polarized backscatters on soil moisture retrievals, three retrieval schemes are explored: a single channel algorithm using VV (SCA-VV) and VH (SCA-VH) polarizations and a dual channel algorithm using both VV and VH polarizations (DCA-VVVH). An evaluation of the approach using a combination of a cosmic-ray soil moisture observing system (COSMOS) and Soil Climate Analysis Network measurements over Nebraska shows that the SCA-VV scheme yields good agreement at both the COSMOS footprint and single-site scales. The features of the algorithms that have the most impact on the retrieval accuracy include the vegetation water content estimation scheme, parameters of the water cloud model and the specification of initial ranges of soil moisture and roughness, all of which are comprehensively analyzed and discussed. Through careful consideration and selection of these factors, we demonstrate that the proposed SCA-VV approach can provide reasonable soil moisture retrievals, with RMSE ranging from 0.039 to 0.078 m3/m3 and R2 ranging from 0.472 to 0.665, highlighting the utility of SAR for application at the precision agricultural scale.

scholarly journals Estimation of water cloud model vegetation parameters using a genetic algorithm

2012 ◽  
Vol 57 (4) ◽  
pp. 776-789 ◽  
Author(s):  
Kamal Kumar ◽  
K.S. Hari Prasad ◽  
M.K. Arora
Keyword(s):  
Genetic Algorithm ◽  
Cloud Model ◽  
Water Cloud ◽  
Vegetation Parameters

scholarly journals Global Sensitivity Analysis of a Water Cloud Model toward Soil Moisture Retrieval over Vegetated Agricultural Fields

2021 ◽  
Vol 13 (19) ◽  
pp. 3889
Author(s):  
Chunfeng Ma ◽  
Shuguo Wang ◽  
Zebin Zhao ◽  
Hanqing Ma
Keyword(s):  
Sensitivity Analysis ◽  
Surface Roughness ◽  
Soil Moisture ◽  
Cloud Model ◽  
Incidence Angle ◽  
Agricultural Field ◽  
Estimation Of Parameters ◽  
Spatiotemporal Resolution ◽  
Water Cloud ◽  
Vegetation Parameters

The release of high-spatiotemporal-resolution Sentinel-1 Synthetic Aperture Radar (SAR) data to the public has provided an unprecedented opportunity to map soil moisture at watershed and agricultural field scales. However, the existing retrieval algorithms fail to derive soil moisture with expected accuracy. Insufficient understanding of the effects of soil and vegetation parameters on the backscatters is an important reason for this failure. To this end, we present a Sensitivity Analysis (SA) to quantify the effects of parameters on the dual-polarized backscatters of Sentinel-1 based on a Water Cloud Model (WCM) and multiple global SA methods. The identification of the incidence angle and polarization of Sentinel-1 and the description scheme of vegetation parameters (A, B and α) in WCM are especially emphasized in this analysis towards an optimal estimation of parameters. Multiple SA methods derive identical parameter importance ranks, indicating that a highly reasonable and reliable SA is performed. Comparison between two existing vegetation description schemes shows that the scheme using Vegetation Water Content (VWC) outperforms the scheme combing particle moisture content and VWC. Surface roughness, soil moisture, VWC, and B, are most sensitive on the backscatters. Variation of parameter sensitivity indices with incidence angle at different polarizations indicates that VV- and VH- polarized backscatters at small incidence angles are the optimal options for soil moisture and surface roughness estimation, respectively, while VV-polarized backscatter at larger incidence angles is well-suited for VWC and B estimation and HH-polarized backscatter is well suited for roughness estimation. This analysis improves the understanding of the effects of vegetated surface parameters on multi-angle and multi-polarized backscatters of Sentinel-1 SAR, informing improvement in SAR-based soil moisture retrieval.

Optical Remote Sensing of Vegetation Water Content

2018 ◽  
pp. 183-200
Author(s):  
Colombo Roberto ◽  
Busetto Lorenzo ◽  
Meroni Michele ◽  
Rossini Micol ◽  
Panigada Cinzia
Keyword(s):  
Remote Sensing ◽  
Water Content ◽  
Optical Remote Sensing ◽  
Vegetation Water Content ◽  
Vegetation Water

scholarly journals USO DO SOLO E DEGRADAÇÃO AMBIENTAL: estudo de caso da bacia do Mata Fome em Belém, Pará

2017 ◽  
Vol 2 (7) ◽  
pp. 162
Author(s):  
Marcos Jonatas Damasceno da Silva ◽  
Luziane Mesquita da Luz
Keyword(s):  
Urban Space ◽  
Environmental Degradation ◽  
Health Risks ◽  
Urban Areas ◽  
Satellite Image ◽  
Land Uses ◽  
Vegetation Water ◽  
The Relationship ◽  
Soil Changes

São diversos os problemas presentes nos espaços das cidades brasileiras, principalmente nos grandes espaços urbanos. Um desses problemas é a degradação do meio ambiente decorrente de intervenções não planejadas nesses espaços. Nesse sentido, este trabalho tem o propósito de analisar a relação entre a produção do espaço urbano, que atribui diferentes usos ao solo e a degradação do meio ambiente na Bacia do Mata Fome em Belém, Pará. Além disso, foi realizado um mapeamento do uso do solo da área de estudo, onde foi utilizada a imagem do satélite Ikonos de 2006. Os resultados deste trabalho evidenciaram que a produção do espaço urbano na Bacia do Mata Fome e os diversos usos do solo, provocaram degradação ambiental, por desencadearem a destruição da cobertura vegetal, poluição da água e do solo, mudanças na topografia dos terrenos, inundações, riscos à saúde, entre outros danos.Palavras-chave: Meio ambiente; Urbanização; Bacia hidrográfica; Poluição.USE OF SOIL AND ENVIRONMENTAL DEGRADATION: a case study of Mata Fome basin in Belém, ParáABSTRACTThere are several problems present in the spaces of brazilian cities, especially in large urban areas. One such problem is the degradation of the environment due to unplanned interventions in these spaces. In this sense, this work aims to analyze the relationship between the production of urban space that assigns different uses to soil and environmental degradation in the Mata Fome Watershed in Belém, Pará. In addition, we carried out a mapping of the use of soil of the study area where the satellite image Ikonos 2006. The results of this study indicated that the production of urban space in Mata Fome Watershed and various land uses, caused environmental degradation was used to trigger the destruction of vegetation, water pollution and soil changes in the topography of the land, floods, health risks and other damage.Keywords: Environment; Urbanization; Hydrographic watershed; Pollution.USO DEL SUELO Y DEGRADACIÓN AMBIENTAL: estudio del caso de la cuenca del Mata Fome en Belém, ParáRESUMEN Hay varios problemas presentes en los espacios de las ciudades brasileñas, especialmente en las grandes áreas urbanas. Uno de estos problemas es la degradación del medio ambiente debido a las intervenciones no planificadas en estos espacios. En este sentido, este trabajo tiene como objetivo analizar la relación entre la producción del espacio urbano, que asigna a los diferentes usos del suelo y la degradación del medio ambiente en la Cuenca del Mata Fome en Belém, Pará. Además, se realizó un mapeo del uso del suelo de la zona de estudio, donde la imagen de satélite Ikonos 2006. Los resultados de este estudio indicaron que la producción del espacio urbano en la Cuenca del Mata Fome y diversos usos de la tierra causado la degradación ambiental se utilizó para desencadenar la destrucción de la vegetación, la contaminación del agua y los cambios de suelo en la topografía del terreno, inundaciones, riesgos para la salud, y otros daños.Palabras clave: Medio ambiente; Urbanización; Cuenca hidrográfica; Contaminación.

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