Search results for "Vegetation"

2018

The Radar Vegetation Index (RVI) is a well-established microwave metric of vegetation cover. The index utilizes measured linear scattering intensities from co- and cross-polarization and is normalized to ideally range from 0 to 1, increasing with vegetation cover. At long wavelengths (L-band) microwave scattering does not only contain information coming from vegetation scattering, but also from soil scattering (moisture & roughness) and therefore the standard formulation of RVI needs to be revised. Using global level SMAP L-band radar data, we illustrate that RVI runs up to 1.2, due to the pre-factor in the standard formulation not being adjusted to the scattering mechanisms at these lo…

Estimation of evapotranspiration using SVAT models and surface IR temperature

1995

Soil Vegetation Atmosphere Transfer (SVAT) models have been implemented to estimate energy and mass fluxes between soil, vegetation and atmosphere of various ecosystems. They can also simulate remote sensing data and in particular thermal infrared surface temperature. Usually, these models are simple, but they use realistic descriptions of radiative, turbulent and water transfers. These include description of stomatal control of transpiration fluxes. Some studies have shown that such models may be used to derive evapotranspiration from surface temperature, using inversion procedures. In this study, inversion of two different SVAT models are compared.

Hydrological drivers of wetland vegetation community distribution within Everglades National Park, Florida

2010

The influence of hydrological dynamics on vegetation distribution and the structuring of wetland environments is of growing interest as wetlands are modified by human action and the increasing threat from climate change. Hydrological properties have long been considered a driving force in structuring wetland communities. We link hydrological dynamics with vegetation distribution across Everglades National Park (ENP) using two publicly available datasets to study the probability structure of the frequency, duration, and depth of inundation events along with their relationship to vegetation distribution. This study is among the first to show hydrologic structuring of vegetation communities at…

Radiance-based NIRv as a proxy for GPP of corn and soybean

2020

Abstract Substantial uncertainty exists in daily and sub-daily gross primary production (GPP) estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that near-infrared radiance of vegetation (NIRv,Rad), defined as the product of observed NIR radiance and normalized difference vegetation index, can accurately estimate corn and soybean GPP at daily and half-hourly time scales, benchmarked with multi-year tower-based GPP at three sites with different environmental and irrigation conditions. Overall, NIRv,Rad explains 84% and 78% variations of half-hourly GPP for corn and soybean, respectively, outperforming NIR reflectance of vegetation (NIRv,Ref), enhanced vege…

Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review

2020

Abstract Green fractional vegetation cover ( f c ) is an important phenotypic factor in the fields of agriculture, forestry, and ecology. Spatially explicit monitoring of f c via relative vegetation abundance (RA) algorithms, especially those based on scaled maximum/minimum vegetation index (VI) values, has been widely investigated in remote sensing research. Although many studies have explored the effectiveness of RA algorithms over the past 30 years, a literature review summarizing the corresponding theoretical background, issues, current state-of-the-art techniques, challenges, and prospects has not yet been published. The overall objective of the present study was to accomplish a compre…

PHYSICS-based retrieval of scattering albedo and vegetation optical depth using multi-sensor data integration

2017

Vegetation optical depth and scattering albedo are crucial parameters within the widely used τ-ω model for passive microwave remote sensing of vegetation and soil. A multi-sensor data integration approach using ICESat lidar vegetation heights and SMAP radar as well as radiometer data enables a direct retrieval of the two parameters on a physics-derived basis. The crucial step within the retrieval methodology is the calculus of the vegetation scattering coefficient KS, where one exact and three approximated solutions are provided. It is shown that, when using the assumption of a randomly oriented volume, the backscatter measurements of the radar provide a sufficient first order estimate and …

SMOS-IC : a revised SMOS product based on a new effective scattering albedo and soil roughness parameterization

2017

International audience; This study presents a new SMOS (Soil Moisture and Ocean Salinity) soil moisture (SM) product based on a different scattering albedo and soil roughness parameterization: the SMOS-IC (SMOS INRA-CESBIO) data set. In this study, several parameterizations of the vegetation and soil roughness parameters (co, H-R and N-RP, P = H, V) were tested and the retrieved SM was compared against in situ observations obtained from the International Soil Moisture Network (ISMN). Firstly, values of omega = 0.10, H-R = 0.4 and N-RP = -1 (P = H, V) were found globally. Secondly, a calibration of these parameters was obtained for the different land cover categories of the International Geo…

Comparison of cloud-reconstruction methods for time series of composite NDVI data

2010

Land cover change can be assessed from ground measurements or remotely sensed data. As regards remotely sensed data, such as NDVI (Normalized Difference Vegetation Index) parameter, the presence of atmospherically contaminated data in the time series introduces some noise that may blur the change analysis. Several methods have already been developed to reconstruct NDVI time series, although most methods have been dedicated to reconstruction of acquired time series, while publicly available databases are usually composited over time. This paper presents the IDR (iterative Interpolation for Data Reconstruction) method, a new method designed to approximate the upper envelope of the NDVI time s…

Short-Term Vegetation Recovery after a Grassland Fire in Lithuania: The Effects of Fire Severity, Slope Position and Aspect

2016

In Lithuania, fire is frequently used by farmers as a tool to remove dry grass, improve soil nutrient status and help soil tilling. However, little is known about the ecological impacts of these fires, including vegetation recovery. The objective of this work is to study the impacts of a spring grassland fire on vegetation recuperation on an east-facing (A) and a west-facing slope (B), considering fire severity and slope position, 10, 17, 31 and 46 days after the fire. Because of their effects on fire behaviour, aspect, steepness and heterogeneity of topography favoured higher fire severity on slope B than on slope A. Three different slope positions were identified on slope A – flat top, mi…

Assessing and Modeling Soil Detachment Capacity by Overland Flow in Forest and Woodland of Northern Iran

2020

Land use has significant effects on the erosion process, since it influences the soil detachment capacity by causing an overland flow (Dc). The effects of different land uses on the rill detachment capacity have not been explained in depth, and the hydraulic parameters providing accurate estimates of this soil property have not been completely identified. This study quantifies Dc at low flow rates in woodland and forestland, compared to two other land uses (cropland and grassland), in the Saravan watershed (Northern Iran), and develops prediction models of Dc and rill erodibility (Kr). Dc was measured on undisturbed soil samples, collected in the four land uses, and characterized in terms o…