IEEE Geoscience and Remote Sensing Magazine - March 2021 - 230

[279]	N. Virlet, K. Sabermanesh, P. Sadeghi-Tehran, and M. J. Hawkesford, " Field Scanalyzer: An automated robotic field phenotyping platform for detailed crop monitoring, " Funct. Plant Biol.,
vol. 44, no. 1, pp. 143-153, 2017. doi: 10.1071/FP16163.
[280]	M. Friedli, N. Kirchgessner, C. Grieder, F. Liebisch, M. Mannale,
and A. Walter, " Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species
under field conditions, " Plant Methods, J. Art., vol. 12, no. 1, p. 9,
Jan. 29, 2016. doi: 10.1186/s13007-016-0109-7.
[281]	C. Zhang and J. M. Kovacs, " The application of small unmanned
aerial systems for precision agriculture: A review, " Precis. Agr., vol.
13, no. 6, pp. 693-712, 2012. doi: 10.1007/s11119-012-9274-5.
[282]	F. H. Holman, A. B. Riche, M. Castle, M. J. Wooster, and M.
J. Hawkesford, " Radiometric calibration of 'commercial off the
shelf' cameras for UAV-based high-resolution temporal crop
phenotyping of reflectance and NDVI, " Remote Sens., vol. 11,
no. 14, p. 1657, 2019. doi: 10.3390/rs11141657.
[283]	F. Holman, A. Riche, A. Michalski, M. Castle, M. Wooster, and
M. Hawkesford, " High throughput field phenotyping of wheat
plant height and growth rate in field plot trials using UAV based
remote sensing, " Remote Sens., vol. 8, no. 12, p. 1031, 2016. doi:
10.3390/rs8121031.
[284]	X. Jin, J. Ma, Z. Wen, and K. Song, " Estimation of maize residue
cover using Landsat-8 OLI image spectral information and textural features, " Remote Sens., vol. 7, no. 11, pp. 14,559-14,575,
2015. doi: 10.3390/rs71114559.
[285]	W. Koppe et al., " Rice monitoring with multi-temporal and
dual-polarimetric TerraSAR-X data, " Int. J. Appl. Earth Observ.
Geoinform., vol. 21, pp. 568-576, Apr. 2013. doi: 10.1016/j.
jag.2012.07.016.
[286]	I. M. Johnstone and M. Raimondo, " Periodic boxcar deconvolution and diophantine approximation, " Ann. Statist., vol. 32, no.
5, pp. 1781-1804, 2004. doi: 10.1214/009053604000000391.
[287]	J.-S. Lee and E. Pottier, Polarimetric Radar Imaging: From Basics to
Applications. Boca Raton, FL: CRC, 2017.
[288]	Y. Sheng and D. E. Alsdorf, " Automated georeferencing and
orthorectification of Amazon basin-wide SAR mosaics using
SRTM DEM data, " IEEE Trans. Geosci. Remote Sens., vol. 43, no.
8, pp. 1929-1940, 2005. doi: 10.1109/TGRS.2005.852160.
[289]	M. Brown, K. De Beurs, and M. Marshall, " Global phenological response to climate change in crop areas using satellite remote sensing of vegetation, humidity and temperature over 26
years, " Remote Sens. Environ., vol. 126, pp. 174-183, Nov. 2012.
doi: 10.1016/j.rse.2012.08.009.
[290]	I. Becker-Reshef et al., " Monitoring global croplands with
coarse resolution earth observations: The Global Agriculture
Monitoring (GLAM) project, " Remote Sens., vol. 2, no. 6, pp.
1589-1609, 2010. doi: 10.3390/rs2061589.
[291]	X.-P. Song et al., " National-scale soybean mapping and area estimation in the United States using medium resolution satellite
imagery and field survey, " Remote Sens. Environ., vol. 190, pp.
383-395, Mar. 2017. doi: 10.1016/j.rse.2017.01.008.
[292]	C. M. Biradar et al., " A global map of rainfed cropland areas
(GMRCA) at the end of last millennium using remote sensing, "
Int. J. Appl. Earth Observ. Geoinform., vol. 11, no. 2, pp. 114-129,
2009. doi: 10.1016/j.jag.2008.11.002.

230

[293]	N. Yang et al., " Large-scale crop mapping based on machine
learning and parallel computation with grids, " Remote Sens.,
vol. 11, no. 12, p. 1500, 2019. doi: 10.3390/rs11121500.
[294]	B. D. Wardlow and S. L. Egbert, " Large-area crop mapping using
time-series MODIS 250 m NDVI data: An assessment for the US
Central Great Plains, " Remote Sens. Environ., vol. 112, no. 3, pp.
1096-1116, 2008. doi: 10.1016/j.rse.2007.07.019.
[295]	J. Dong et al., " Tracking the dynamics of paddy rice planting
area in 1986-2010 through time series Landsat images and
phenology-based algorithms, " Remote Sens. Environ., vol. 160,
pp. 99-113, Apr. 2015. doi: 10.1016/j.rse.2015.01.004.
[296]	R . A. Geerken, " An algorithm to classify and monitor seasonal
variations in vegetation phenologies and their inter-annual
change, " ISPRS J. Photogram. Remote Sens., vol. 64, no. 4, pp.
422-431, 2009. doi: 10.1016/j.isprsjprs.2009.03.001.
[297]	Y. Shao, R. S. Lunetta, B. Wheeler, J. S. Iiames, and J. B. Campbell, " An evaluation of time-series smoothing algorithms for
land-cover classifications using MODIS-NDVI multi-temporal
data, " Remote Sens. Environ., vol. 174, pp. 258-265, Mar. 2016.
doi: 10.1016/j.rse.2015.12.023.
[298]	R . Azar, P. Villa, D. Stroppiana, A. Crema, M. Boschetti, and
P. A. Brivio, " Assessing in-season crop classification performance using satellite data: A test case in Northern Italy, " Eur.
J. Remote Sens., vol. 49, no. 1, pp. 361-380, 2016. doi: 10.5721/
EuJRS20164920.
[299]	P. Villa, D. Stroppiana, G. Fontanelli, R. Azar, and P. A. Brivio,
" In-season mapping of crop type with optical and X-band SAR
data: A classification tree approach using synoptic seasonal features, " Remote Sens., vol. 7, no. 10, pp. 12,859-12,886, 2015. doi:
10.3390/rs71012859.
[300]	C. Gómez, J. C. White, and M. A. Wulder, " Optical remotely
sensed time series data for land cover classification: A review, "
ISPRS J. Photogram. Remote Sens., vol. 116, pp. 55-72, June 2016.
doi: 10.1016/j.isprsjprs.2016.03.008.
[301]	F. Waldner et al., " Towards a set of agrosystem-specific cropland mapping methods to address the global cropland diversity, " Int. J. Remote Sens., vol. 37, no. 14, pp. 3196-3231, 2016.
doi: 10.1080/01431161.2016.1194545.
[302]	S. Skakun et al., " Early season large-area winter crop mapping
using MODIS NDVI data, growing degree days information and
a Gaussian mixture model, " Remote Sens. Environ., vol. 195, pp.
244-258, 2017. doi: 10.1016/j.rse.2017.04.026.
[303]	A. Bouvet and T. Le Toan, " Use of ENVISAT/ASAR wide-swath
data for timely rice fields mapping in the Mekong River Delta, "
Remote Sens. Environ., vol. 115, no. 4, pp. 1090-1101, 2011. doi:
10.1016/j.rse.2010.12.014.
[304]	I. Choudhury and M. Chakraborty, " SAR signature investigation of rice crop using RADARSAT data, " Int. J. Remote Sens., vol.
27, no. 3, pp. 519-534, 2006. doi: 10.1080/01431160500239172.
[305]	Y. Oguro, Y. Suga, S. Takeuchi, M. Ogawa, T. Konishi, and K.
Tsuchiya, " Comparison of SAR and optical sensor data for monitoring of rice plant around Hiroshima, " Adv. Space Res., vol. 28,
no. 1, pp. 195-200, 2001. doi: 10.1016/S0273-1177(01)00345-3.
[306]	Y. Shao et al., " Rice monitoring and production estimation using
multitemporal RADARSAT, " Remote Sens. Environ., vol. 76, no. 3,
pp. 310-325, 2001. doi: 10.1016/S0034-4257(00)00212-1.
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

MARCH 2021
IEEE Geoscience and Remote Sensing Magazine - March 2021

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - March 2021
