02742naa a2200337 a 450000100080000000500110000800800410001902400510006010000220011124501150013326000090024852016950025765000210195265000150197365000190198865000290200765000250203665000160206165000180207765000250209565300360212065300280215665300280218470000190221270000190223170000180225070000190226870000160228770000220230377300790232520935882018-07-26       2018    bl uuuu     u00u1 u    #d7 ahttps://doi.org/10.1109/LGRS.2017.27891202DOI1 aSANCHES, I. D. A.  aCampo Verde databasebseeking to improve agricultural remote sensing of tropical areas.h[electronic resource]  c2018  aAbstract: In tropical/subtropical regions, the favorable climate associated with the use of agricultural technologies, such as no tillage, minimum cultivation, irrigation, early varieties, desiccants, ?owering inducing, and crop rotation, makes agriculture highly dynamic. In this letter, we present the Campo Verde agricultural database. The purpose of creating and sharing these data is to foster advancement of remote sensing technology in areas of tropical agriculture, primarily the development and testingof methods for croprecognition andagriculturalmapping. Campo Verde is a municipality of Mato Grosso state, localized in the Cerrado (Brazilian Savanna) biome, in central west Brazil. Soybean, maize, and cotton are the primary crops cultivated in this region. Double cropping systems are widely adopted in this area. There is also livestock and forestry production. Our database provides the land-use classes for 513 ?elds by month for one Brazilian crop year (between October 2015 and July 2016). This information was gathered during two ?eld campaigns in Campo Verde (December 2015 and May 2016) and by visual interpretation of a time series of Landsat-8/Operational Land Imager (OLI) images using an experienced interpreter. A set of 14 preprocessed synthetic aperture radar Sentinel-1 and 15 Landsat-8/OLI mosaic images is also made available. It is important to promote the use of radar data for tropical agricultural applications, especially because the use of optical remote sensing in these regions is hindered by the high frequency of cloud cover. To demonstrate the utility of our database, results of an experiment conducted using the Sentinel-1 data set are presented.  aDigital database  aMonitoring  aRemote sensing  aSynthetic aperture radar  aTropical agriculture  aAgricultura  aBase de Dados  aSensoriamento Remoto  aAgricultural mapping/monitoring  aDouble cropping systems  aFree available database1 aFEITOSA, R. Q.1 aDIAZ, P. M. A.1 aSOARES, M. D.1 aLUIZ, A. J. B.1 aSCHULTZ, B.1 aMAURANO, L. E. P.  tIEEE Geoscience and Remote Sensing Lettersgv. 15, n. 3, p. 369-373, 2018.