Page 20 - Transitioning Turfgrass
P. 20
TRANSITIONING TURFGRASS
Cropper K., Munshaw G., Barrett M., 2017. Optimum Sea- different management practices on botanical composition,
sonal Mowing Heights for Smooth Crabgrass Reduction in quality, colour and growth of urban lawns. Urban Forestry &
Tall Fescue Lawns. HortTechnology. 27(1): 73-77. Urban Greening. 26: 178-183.
Cushnahan T., Yule I.J., Pullanagari R.R., Grafton M.C.E., Leasure J.K, 1949. Determining the species composition of
2016. Identifying grass species using hyperspectral sensing. swards. Agronomy Journal. 41: 204-206.
In: Integrated nutrient and water management for sustain-
able farming. (Eds. Currie L.D., Singh R.) Massey University, Macolino S., Pignata G., Giolo M., Richardson M.D., 2014.
Palmerston North, New Zealand. 14 pages. Species Succession and Turf Quality of Tall Fescue and Ken-
tucky Bluegrass Mixtures as Affected By Mowing Height.
Dalponte M., Bruzzone L., Gianelle D., 2012. Tree species Crop Science 54: 1220–1226.
classification in the Southern Alps based on the fusion of very
high geometrical resolution multispectral/hyperspectral im- Malenovsky Z., Mishra K.B., Zemek F., Rascher U., Nedbal
ages and LiDAR data. Remote Sensing of Environment 123: L., 2009. Scientific and technical challenges in remote sens-
258–270. ing of plant canopy reflectance and fluorescence. Journal of
Experimental Botany 60: 2987–3004.
Dalponte M., Bruzzone L., Vescovo L., Gianelle D., 2009.
The role of spectral resolution and classifier complexity in Monteiro S.T., Uto K., Kosugi Y., Oda K., Lino Y., Saito G.,
the analysis of hyperspectral images of forest areas. Remote 2008. Hyperspectral image classification of grass species
Sensing of Environment 113: 2345–2355. in northeast Japan. In IGARSS 2008-2008 IEEE Interna-
tional Geoscience and Remote Sensing Symposium (Vol. 4,
Drusch M., Moreno J., Del Bello U., Franco R., Goulas Y., pp. IV-399).
Huth A., Kraft S., Middleton E.M., Miglietta F., Mohammed
G., Nebdal L., Rascher U., Schuttemeyer D., Verhoef W., R Development Core Team, 2015. R: A language and envi-
2017. The FLuorescence EXplorer Mission Concept—ESA’s ronment for statistical computing.
Earth Explorer 8. IEEE Trans. Geoscience and Remote Sens- Rascher U., Nichol C.J., Small C., Hendricks L., 2017. Mon-
ing 55: 1273–1284. itoring spatiotemporal dynamics of photosynthesis with a
Dunn J., Diesburg K., 2004. Turf management in the transi- portable hyperspectral imaging system. Photogrammetic
tion zone. John Wiley & Sons. Engineering and Remote Sensing 73: 45–56.
Earlywine D.T., Smeda R.J., Teuton T.C., Sams C.E., Xiong Sakowska K., MacArthur A., Gianelle D., Dalponte M., Al-
X., 2010. Evaluation of oriental mustard (Brassica juncea) berti G., Gioli B., Miglietta F., Pitacco A., Meggio F., Fava F.,
seed meal for weed suppression in turf. Weed technology 24: Julitta T., Rossini M., Rocchini D., Vescovo L., 2019. Assessing
440-445. Across-Scale Optical Diversity and Productivity Relationships
in Grasslands of the Italian Alps. Remote Sensing 11: 614.
Fang S., Tang W., Peng Y., Gong Y., Dai C., Chai R., Liu K.,
2016. Remote Estimation of Vegetation Fraction and Flow- Salehi H., Khosh-Khui M., 2004. Turf Monoculture Cool-
er Fraction in Oilseed Rape with Unmanned Aerial Vehicle Cool and Cool-Warm Season Seed Mixture Establish-
Data. Remote Sensing 8: 416. mentand Growth Responses. Hort Science. 39(7): 1732-1735.
Galvão L.S., Epiphanio J.C.N., Breunig F.M., Formaggio Vyas D., Krishnayya N.S.R., Manjunath K.R., Ray S.S.,
A.R., 2011. 17 Crop Type Discrimination Using Hyperspectral Panigrahy S., 2011. Evaluation of classifiers for processing
Data. Hyperspectral remote sensing of vegetation 397. Hyperion (EO-1) data of tropical vegetation. International
Journal of Applied Earth Observation and Geoinformation
Ghasemloo N., Mobasheri M.R., Rezaei Y., 2011. Vegetation 13: 228–235.
Species Determination Using Spectral Characteristics and
Artificial Neural Network (SCANN). Journal of Agricultural Xiao X.M., Zhang Q., Braswell B., et al., 2004. Modelling
Science and Technology 13: 1223-1232. gross primary production of temperate deciduous broadleaf
forest using satellite images and climate data. Remote Sens-
Gough L., Osenberg C.W., Gross K.L., Collins S.L., 2000. ing of Environment 91: 256–70.
Fertilization effects on species density and primary productivity
in several herbaceous plant communities. Oikos. 89: 428–439. Xu X., Gu X., Song X., Li C., Huang W., 2011. Assessing rice
chlorophyll content with vegetation indices from hyperspec-
Knot P., Hrabe F., Hejduk S., Skladanka J., Kvasnovsky M., tral data. Computer and Computing Technologies in Agricul-
Hodulikova L., Caslavova I., Horky P., 2017. The impacts of ture IV, Springer, Boston.
16