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International Journal of Remote Sensing Applications
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  This is an Open Access Journal Open Access journal
     ISSN (Print) 2226-4361 - ISSN (Online) 2226-4353
     Published by Science and Engineering Publishing Company Homepage  [47 journals]
  • Spatial Estimation of Wheat Yields from Landsat’s Visible, near
           Infrared and Thermal Reflectance Bands

    • Abstract: Spatial Estimation of Wheat Yields from Landsat’s Visible, near Infrared and Thermal Reflectance Bands
      Pages 134-143
      Author Potgieter, A.B.Power, B.Mclean, J.Davis, P.Rodriguez, D
      At a field level spatial crop yield patterns are mainly determined by spatially changing soil properties (e.g. soil moisture) in interaction with seasonal climate conditions and weather patterns at critical crop growth stages in the crop development. In this research we combined remote sensing technologies, local weather and canopy condition to describe spatial yield patterns of a 1400ha wheat field during the 2011 winter cropping season. More specifically, we determined the ability of remotely sensed derived indices, within the visible and thermal domains, to predict final harvested wheat yield at field scale. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different soil types. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, while crop canopy temperature was also measured. Satellite imagery Landsat TM 5 and 7 was obtained at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop water stress index (CSIws) at the location of each weather station. Field data was used to validate a crop stress index from satellite imagery. Yield data was acquired from the combine harvester at different locations in the field. We used visible and near-infrared bands to calculate the enhanced vegetation index (EVI). Thermal bands and EVI were used to derive a crop stress indices (CSIsat) as well as a moisture stress index (MSIsat), based on Moran’s trapezoid approach, at several times during the crop growth period. Weather station data were used to ground truth the satellite derived indices. Results showed that spatial variations in crop yield were related to a satellite derived canopy stress index (CSIsat) and a moisture stress index (MSIsat). At field level the canopy stress index (CSIws) calculated at midday was correlated to the CSIsat at late morning close to the time of Landsat satellite pass-over. Harvested yield was moderately correlated (R2 = 0.67) to CSIsat for a fix date across all fields. This relationship noticeably improved (adjusted R2 = 0.95), using both indices from all five dates across all fields during the crop growth period. Here we showed that satellite derived crop attributes (CSIsat and MSIsat) can account for most of the variability in actual crop yield and that they could be used to predict aggregated field scale wheat yields (deviation of +2.6%). The application and value of such an approach to the grains industry is also discussed.
      PubDate: 2014-09
  • Vegetation Activity in the Upper Oueme Basin (Benin, Africa) Studied from
           SPOT-VGT (2002-2012) According to Land Cover

    • Abstract: Vegetation Activity in the Upper Oueme Basin (Benin, Africa) Studied from SPOT-VGT (2002-2012) According to Land Cover
      Pages 121-133
      Author Sylvain BigotThao DoSylvie Gall
      Signs of climate change in West Africa over the last few decades are among the significant observed in the tropics, in particular the decrease in mean annual precipitation. Although such change has brought about new eco-climatic constraints on vegetation forms, it has not proven easy to determine interannual and intra-seasonal variations on a regional scale for major vegetation forms, whether natural or highly artificial as a result of human activities. The present study analyzes vegetation activity via a Normalized Difference Vegetation Index (NDVI) defined from ten-day SPOT-VGT data (one-km resolution, covering the period from 2002 to 2012) in the African Monsoon Multidisciplinary Analysis (AMMA) Program observation zone, located in the Upper Oueme River Basin in Benin. The statistical analysis is mainly based on a multifactor approach allowing approximately 54% of interannual NDVI variations to be accounted for. Results show that spatio-temporal NDVI variability in the River Basin is highly dependent on land use, be it forest, wooded savanna, farmland or areas undergoing conversion.
      PubDate: 2014-09
  • A Low-cost Unmanned Aerial System for Remote Sensing of Forested

    • Abstract: A Low-cost Unmanned Aerial System for Remote Sensing of Forested Landscapes
      Pages 113-120
      Author A.E. AkayM.G. WingJ. BurnettS. JohnsonJ. Session
      We developed a low-cost unmanned aerial system (UAS) for less than $1400 that is capable of capturing high-resolution imagery of landscapes. We accomplished this feat by making use of advances in open-source technology that are propelling small UAS applications for remote sensing. We describe the low-cost UAS that we developed, the process for assembling the aircraft, and the various components that are necessary for flight. We also describe software and piloting options that can support automated flight. In addition, we provide examples of high-resolution imagery that were captured of forest stands, buildings, and other features during a flight over a university campus in Turkey. We hope the descriptions and examples we provide will encourage researchers to develop and advance their own UAS for remote sensing applications. We anticipate that future years will bring more technological advancements that reduce the weight and size of high-resolution sensors and autopilot systems while increasing the reliability of UAS. It is also likely that the future will see small UAS as the primary means of collecting remotely sensed data for a variety of scientific, engineering, and resource management applications.
      PubDate: 2014-09
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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