Search results for "Computers in Earth Science"

Near real-time estimation of Sea and Land surface temperature for MSG SEVIRI sensors

2020

Abstract Land and Sea Surface Temperatures (LST and SST) are both recognized as Essential Climate Variables, and are routinely retrieved by a wealth of satellites. However, for validated approaches, the latest data are usually not available to the general public. We offer to bridge this gap, by using Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI), with its 15 min temporal resolution. Here, we present generic algorithms for the retrieval of both LST and SST, valid for the SEVIRI instrument onboard MSG platforms 8–11, which we validate using hourly data of 4 ground stations and 11 buoys in Spain over the years 2015 to 2018. These validations show that …

Brown and green LAI mapping through spectral indices

2015

Abstract When crops senescence, leaves remain until they fall off or are harvested. Hence, leaf area index (LAI) stays high even when chlorophyll content degrades to zero. Current LAI approaches from remote sensing techniques are not optimized for estimating LAI of senescent vegetation. In this paper a two-step approach has been proposed to realize simultaneous LAI mapping over green and senescent croplands. The first step separates green from brown LAI by means of a newly proposed index, ‘Green Brown Vegetation Index (GBVI)’. This index exploits two shortwave infrared (SWIR) spectral bands centred at 2100 and 2000 nm, which fall right in the dry matter absorption regions, thereby providing…

Simultaneous retrieval of sugarcane variables from Sentinel-2 data using Bayesian regularized neural network

2023

Estimating soil moisture content under grassland with hyperspectral data using radiative transfer modelling and machine learning

2023

The monitoring of soil moisture content (SMC) at very high spatial resolution (10m) using unmanned aerial systems (UAS) is of high interest for precision agriculture and the validation of large scale SMC products. Data-driven approaches are the most common method to retrieve SMC with UAS-borne data at water limited sites over non-disturbed agricultural crops. A major disadvantage of data-driven algorithms is the limited transferability in space and time and the need of a high number of ground reference samples. Physically-based approaches are less dependent on the amount of samples and are transferable in space and time. This study explores the potential of (1) a hybrid method targeting the…

FluoCat: A cable-suspended multi-sensor system for the vegetation SIF Cal/Val monitoring and estimation of effective sunlit surface fluorescence

2023

Growing stock volume from multi-temporal landsat imagery through google earth engine

2019

Growing stock volume (GSV) is one of the most important variables for.forest management and is traditionally- estimated from ground measurements. These measurements are expensive and therefore sparse and hard to maintain in time on a regular basis. Remote sensing data combined with national forest inventories constitute a helpful tool to estimate and map forest attributes. However, most studies on GSV estimation from remote sensing data focus on small forest areas with a single or only a few species. The current study aims to map GSV in peninsular Spain, a rather large and very heterogeneous area. Around 50 000 wooded land plots from the Third Spanish National Forest Inventory (NFI3) were u…

A simple method to directly retrieve reference evapotranspiration from geostationary satellite images

2013

Abstract Application of FAO-56 methodology for the assessment of reference evapotranspiration, ET 0 , is challenging in areas of the world with sparse meteorological network stations. For this reason alternative procedures using remotely observed data have been proposed in the literature. In this work, a simplified version of the Makkink approach [J. Inst. Wat. Eng. 11: 277–288, 1957] was tested in a typical Mediterranean environment (Sicily, Italy). The implemented Makkink approach (MAK) uses remotely estimated solar radiation derived from Meteosat Second Generation (MSG) satellite data and in situ observations of air temperature to assess ET 0 at daily time scale. Alternatively, taking ad…

Estimating the phenological dynamics of irrigated rice leaf area index using the combination of PROSAIL and Gaussian Process Regression

2021

The growth of rice is a sequence of three different phenological phases. This sequence of change in rice phenology implies that the condition of the plant during the vegetative phase relates directly to the health of leaves functioning during the reproductive and ripening phases. As such, accurate monitoring is important towards understanding rice growth dynamics. Leaf Area Index (LAI) is an important indicator of rice yields and the availability of this information during key phenological phases can support more informed farming decisions. Satellite remote sensing has been adopted as a proxy to field measurements of LAI and with the launch of freely available high resolution Satellite imag…

Laboratory calibration and field measurement of land surface temperature and emissivity using thermal infrared multiband radiometers

2019

Accurate ground measurements of land surface temperature (LST) are necessary for validating satellite LST products. In order to provide reliable data, ground radiometers must be calibrated with reference to an international standard, and radiometric temperatures must be corrected for land surface emissivity. As opposed to water, land surface emissivity is not usually known for many ground covers, so an emissivity value has to be assumed, assigned from spectral emissivity libraries or measured for each land cover and spectral band considered. The aim of this study is to show the laboratory calibration and the methodology for simultaneous field measurements of LST and emissivity employed in t…

Comparative analysis of different techniques for spatial interpolation of rainfall data to create a serially complete monthly time series of precipit…

2011

Abstract The availability of good and reliable rainfall data is fundamental for most hydrological analyses and for the design and management of water resources systems. However, in practice, precipitation records often suffer from missing data values mainly due to malfunctioning of raingauge for specific time periods. This is an important issue in practical hydrology because it affects the continuity of rainfall data and ultimately influences the results of hydrologic studies which use rainfall as input. Many methods to estimate missing rainfall data have been proposed in literature and, among these, most are based on spatial interpolation algorithms. In this paper different spatial interpo…