02470naa a2200289 a 450000100080000000500110000800800410001902200200006002400280008010000180010824501060012626000090023250004160024152013150065765000130197265000140198565000190199965300110201865300110202965300140204065300100205465300190206470000170208370000150210070000160211577300490213110599632019-08-02       2019    bl uuuu     u00u1 u    #d  aEISSN 2072-42927 a10.3390/rs111518012DOI1 aTISCORNIA, G.  aCan we Monitor Height of Native Grasslands in Uruguay with Earth Observation?.h[electronic resource]  c2019  aArticle history: Received: 4 June 2019 / Accepted: 30 July 2019 / Published: 1 August 2019. (This article belongs to the Special Issue Advances of Remote Sensing in Pasture Management). This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).  aABSTRACT. In countries where livestock production based on native grasslands is an important economic activity, information on structural characteristics of forage is essential to support national policies and decisions at the farm level. Remote sensing is a good option for quantifying large areas in a relative short time, with low cost and with the possibility of analyzing annual evolution. This work aims at contributing to improve grazing management, by evaluating the ability of remote sensing information to estimate forage height, as an estimator of available biomass. Field data (forage height) of 20 commercial paddocks under grazing conditions (322 samples), and their relation to MODIS data (FPAR, LAI, MIR, NIR, Red, NDVI and EVI) were analyzed. Correlations between remote sensing information and field measurements were low, probably due to the extremely large variability found within each paddock for field observations (CV: Around 75%) and much lower when considering satellite information (MODIS: CV: 4%?6% and Landsat:CV: 12%). Despite this, the red band showed some potential (with significant correlation coefficient values in 41% of the paddocks) and justifies further exploration. Additional work is needed to find a remote sensing method that can be used to monitor grasslands height.  aFORRAJES  aGANADERIA  aTELEDETECCIÓN  aCAMPOS  aFORAGE  aLIVESTOCK  aMODIS  aREMOTE SENSING1 aBAETHGEN, W.1 aRUGGIA, A.1 aCECCATO, P.  tRemote Sensing, 2019, 11, 1801. OPEN ACCESS.