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Special Issue "Land Surface Fluxes"

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A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 July 2009)

Special Issue Editors

Guest Editor
Prof. Dr. Assefa M. Melesse

Department of Earth and Environment, AHC-5-390, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA
Website | E-Mail
Fax: +1-305-348-3877.
Interests: watershed modelling; sediment dynamics, climate change, evapotranspiration and energy fluxes; system analysis; remote sensing hydrology
Guest Editor
Dr. Gabriel Senay

1. U.S. Geological Survey Earth Resources Observation & Science (EROS) Centre, 47914 252nd St, Garretson, SD 57030, USA
2. North Central Climate Science Centre (NC CSC), Colorado State University, Fort Collins, CO 80523-1499, USA
Website | E-Mail
Fax: +1-605-594-6925
Interests: remote sensing hydrology; evapotrpiration and soil moisture modeling; drought monitoring and food secruity; water use, quality and availability
Guest Editor
Dr. Mekonnen Gebremichael

Department of Civil and Environmental Engineering, University of Connecticut, 261 Glenbrook Rd., UNIT-2037, Storrs, CT 06269-2037, USA
Website | E-Mail
Fax: +1 860 486 2298
Interests: distributed watershed hydrologic modeling; water-energy-carbon fluxes coupling; land-atmosphere interaction; remote sensing applications in hydrology; hydrometeorology; hydroclimatology and ecohydrology; stochastic methods (spatial and temporal analyses); uncertainty analysis; non-linear dynamics (scaling issues)

Special Issue Information

Energy, water, carbon, and nitrogen (E-W-C-N) fluxes are all critical for humans and ecosystems and have strong links to climate. These fluxes have been perturbed by human activity throughout human history. However, these influences have accelerated in the past five decades or so, causing marked changes in regional and global climate. E-W-C-N fluxes show notable relationships and feedbacks. To quantify these fluxes at a larger spatial scale and establish the link among fluxes and their linkages to climate and hydrological dynamics, remote sensing approaches will be essential and practical.The Special Issue of Remote Sensing journal will publish those full research and high rated manuscripts addressing E-W-C-N fluxes using remote sensing data assimilation and modeling approaches. Flux and surface parameter estimation; evapotranspiration modeling and validation; carbon, methane and nitrogen fluxes from different ecosystems and in relation to field or watershed management options; remote sensing data assimilation and integration to landscape models; fluxes and climate dynamics; spatial and temporal dynamics of fluxes using new machine learning techniques (ANN, neurofuzzy, and others) will be accepted. --> Energy, water, carbon, and nitrogen (E-W-C-N) fluxes are all critical for humans and ecosystems and have strong links to climate. These fluxes have been perturbed by human activity throughout human history. However, these influences have accelerated in the past five decades or so, causing marked changes in regional and global climate. E-W-C-N fluxes show notable relationships and feedbacks. To quantify these fluxes at a larger spatial scale and establish the link among fluxes and their linkages to climate and hydrological dynamics, remote sensing approaches will be essential and practical.The Special Issue of Remote Sensing journal will publish those full research and high rated manuscripts addressing E-W-C-N fluxes using remote sensing data assimilation and modeling approaches. Flux and surface parameter estimation; evapotranspiration modeling and validation; carbon, methane and nitrogen fluxes from different ecosystems and in relation to field or watershed management options; remote sensing data assimilation and integration to landscape models; fluxes and climate dynamics; spatial and temporal dynamics of fluxes using new machine learning techniques (ANN, neurofuzzy, and others) will be accepted.

Keywords

  • water
  • carbonnitrogen and energy fluxes
  • soil moisture
  • albedo
  • emssivity
  • surface temperature
  • wetlands
  • latent heat flux
  • sensible heat flux

Published Papers (2 papers)

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Research

Open AccessArticle Mapping Latent Heat Flux in the Western Forest Covered Regions of Algeria Using Remote Sensing Data and a Spatialized Model
Remote Sens. 2009, 1(4), 795-817; doi:10.3390/rs1040795
Received: 31 August 2009 / Revised: 11 October 2009 / Accepted: 19 October 2009 / Published: 27 October 2009
Cited by 7 | PDF Full-text (866 KB) | HTML Full-text | XML Full-text
Abstract
The present paper reports on an investigation to monitor the drought status in Algerian forest covered areas with satellite Earth observations because ground data are scarce and hard to collect. The main goal of this study is to map surface energy fluxes with
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The present paper reports on an investigation to monitor the drought status in Algerian forest covered areas with satellite Earth observations because ground data are scarce and hard to collect. The main goal of this study is to map surface energy fluxes with remote sensing data, based on a simplified algorithm to solve the energy balance equation on each data pixel. Cultivated areas, forest cover and a large water surface were included in the investigated surfaces. The input parameters involve remotely sensed data in the visible, near infrared and thermal infrared. The surface energy fluxes are estimated by expressing the partitioning of energy available at the surface between the sensible heat flux (H) and the latent heat flux (LE) through the evaporative fraction (Λ) according to the S-SEBI (Simplified Surface Energy Balance Index) concept. The method is applicable under the assumptions of constant atmospheric conditions and sufficient wet and dry pixels over a Landsat 7 image. The results are analyzed and discussed considering instantaneous latent heat flux at the data acquisition time. The results confirm the relationships between albedo (r0), the surface temperature (T0) and the evaporative fraction. The method provides estimates of air temperature and LE close to reference measurements. The estimate of latent heat flux and other variables are comparable to those of previous studies. Their comparison with other methods shows reasonable agreement. This approach has demonstrated its simplicity and the fact that remote sensing data alone is sufficient; it could be very promising in areas where data are scarce and difficult to collect. Full article
(This article belongs to the Special Issue Land Surface Fluxes)
Open AccessArticle Modeling Net Ecosystem Exchange for Grassland in Central Kazakhstan by Combining Remote Sensing and Field Data
Remote Sens. 2009, 1(3), 159-183; doi:10.3390/rs1030159
Received: 1 June 2009 / Revised: 7 June 2009 / Accepted: 30 June 2009 / Published: 6 July 2009
Cited by 14 | PDF Full-text (331 KB) | HTML Full-text | XML Full-text
Abstract
Carbon sequestration was estimated in a semi-arid grassland region in Central Kazakhstan using an approach that integrates remote sensing, field measurements and meteorological data. Carbon fluxes for each pixel of 1 × 1 km were calculated as a product of photosynthetically active radiation
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Carbon sequestration was estimated in a semi-arid grassland region in Central Kazakhstan using an approach that integrates remote sensing, field measurements and meteorological data. Carbon fluxes for each pixel of 1 × 1 km were calculated as a product of photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (fPAR), the light use efficiency (LUE) and ecosystem respiration (Re). The PAR is obtained from a mathematical model incorporating Earth-Sun distance, solar inclination, solar elevation angle, geographical position and cloudiness information of localities. The fPAR was measured in field using hemispherical photography and was extrapolated to each pixel by combination with the Normalized Difference Vegetation Index (NDVI) obtained by the Vegetation instrument on board the Satellite Pour l’Observation de la Terra (SPOT) satellite. Gross Primary Production (GPP) of the aboveground and belowground vegetation of 14 sites along a 230 km west-east transect within the study region were determined at the peak of growing season in different land cover types and linearly related to the amount of PAR absorbed by vegetation (APAR). The product of this relationship is LUE = 0.61 and 0.97 g C/MJ APAR for short grassland and steppe, respectively. The Re is estimated using complex models driven by climatic data. Growing season carbon sequestration was calculated for the modelling year of 2004. Overall, the short grassland was a net carbon sink, whereas the steppe was carbon neutral. The evaluation of the modelled carbon sequestration against independent reference data sets proved high accuracy of the estimations. Full article
(This article belongs to the Special Issue Land Surface Fluxes)

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