Resultados de búsqueda - "algorithm"

Estimation of maize foliar temperature and stomatal conductance as indicators of water stress based on optical and thermal imagery acquired using an Unmanned Aerial Vehicle (UAV) p... por Brewer, K., Clulow, A.D., Sibanda, M., Gokool, S., Odindi, J., Mutanga, O., Naiken, V., Chimonyo, Vimbayi Grace Petrova, Mabhaudhi, Tafadzwanashe

“…Considering these developments, we evaluated the utility of optical and thermal infrared UAV imagery, in combination with a random forest machine-learning algorithm, to estimate the maize foliar temperature and stomatal conductance as indicators of potential crop water stress and moisture content over the entire phenological cycle. …”
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Assessing Sumatran Peat Vulnerability to Fire under Various Condition of ENSO Phases Using Machine Learning Approaches por Prasetyo, L.B., Setiawan, Y., Condro, A.A., Kustiyo, K., Putra, E.I., Hayati, N., Wijayanto, A.K., Ramadhi, A., Murdiyarso, D.

“…We found that the ensemble model performed better compared to a single algorithm for depicting fire vulnerability within Sumatran peatlands. …”
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Envirome-wide associations enhance multi-year genome-based prediction of historical wheat breeding data por Costa Neto, Germano, Crespo-Herrera, Leonardo A., Fradgley, Nick, Gardner, Keith A., Bentley, Alison R., Dreisigacker, Susanne, Fritsche-Neto, Roberto, Montesinos López, Osval A., Crossa, José

“…We propose that the EPA effectively serves as a “reinforcement learner” algorithm capable of uncovering the effect of seasonality over the reaction-norms, with the benefits of better forecasting the similarities between past and future trialing sites. …”
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Cloud-based crop type mapping for Nandi County, Kenya por Guo, Zhe

“…The pixel-level machine learning classification algorithm requires high-quality crop-type ground truth data to integrate corresponding satellite images as training samples to train the machine learning classifier. …”
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Regional monitoring of Fall Armyworm (FAW) using early warning systems por Buchaillot, Maria Luisa, Cairns, Jill E., Hamadziripi, Esnath, Wilson, Kenneth, Hughes, David, Chelal, John, McCloskey, Peter, Kehs, Annalyse, Clinton, Nicholas, Araus, José Luis, Kefauver, Shawn C.

“…Here, we developed and tested a Sentinel 2 a+b satellite-based monitoring algorithm based on optimized first-derivative NDVI time series analysis using Google Earth Engine. …”
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Predicting climate-driven changes in reservoir inflows and hydropower in Côte d'Ivoire using machine learning modeling por Obahoundje, Salomon, Diedhiou, A., Akpoti, Komlavi, Kouassi, K. L., Ofosu, E. A., Kouame, D. G. M.

“…To simulate inflow to reservoir and energy generation, the Random Forest (RF), a machine-learning algorithm allowing fewer input variables was applied. …”
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Spatiotemporal variability of soil moisture over Ethiopia and its teleconnections with remote and local drivers por Jimma, Tamirat B, Demissie, Teferi, Diro, Gulilat T, Ture, Kassahun, Terefe, Tadesse, Solomon, Dawit

“…An empirical orthogonal function (EOF) and KMeans clustering algorithm have been employed to classify the large domain into homogeneous zones. …”
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Defining a target population of environments in Africa for Brachiaria sp. and Guinea grass breeding por Mora, Brayan, Jauregui, Rosa Noemi, Llanos Herrera, Lizeth, Peters, Michael, Van Der Hoek, Rein, Notenbaert, An

“…Subsequently, environmental clusters were generated in the target countries using the classic clustering algorithm K-Means. This method groups pixels (areas of 5 km2) considering the principal components generated through EOF. …”
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Near infrared spectroscopy for cooking time classification of cassava genotypes por Bandeira e Sousa, M., Morales, C. F. G., Mbanjo, E., Egesi, C., Oliveira, E.J.

“…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …”
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Hydrological parametrization through remote sensing in the Volta Basin West Africa por Hafeez, M., Andreini, Marc, Liebe, Jens R., Friesen, J., Marx, A., Giesen, Nick van de

“…Evapotranspiration - The Surface Energy Balance Algorithm for Land (SEBAL) was used to calculate sensible heat flux and evapotranspiration through the energy balance. …”
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OrchardQuant-3D: Combining drone and LiDAR to perform scalable 3D phenotyping for characterising key canopy and floral traits in fruit orchards por Xia, Yunpeng, Li, Hanghang, Zhang, Fanhang, Sun, Gang, Qi, Kaijie, Jackson, Robert, Pinheiro, Felipe, Liu, Xiaoman, Mu, Yue, Zhang, Shaoling, Deakin, Greg, Whitfield, E. Charles, Tao, Shutian, Zhou, Ji

“…We first built a data fusion algorithm to register 3D point clouds collected by both drones (for colour signals) and Light Detection And Ranging (LiDAR, for precise spatial properties), reconstructing high-quality 3D orchard models at different growth stages. …”
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Advancements in satellite observations of inland and coastal waters: building towards a global validation network por Avouris, D. M., Maciel, F., Sharp, S. L., Craig, S. E., Dekker, A. G., Di Vittorio, C. A., Gardner, J. R., Goldsmith, E., Gossn, J. I., Greb, S. R., Grunert, B. K., Gurlin, D., Jampani, Mahesh, Khan, R. M., Lowin, B., McKinna, L., Mouw, C. B., Ogashawara, I., Calle, S. R., Salls, W., Sánchez-Cabeza, J.-A., Schaeffer, B., Seegers, B. N., Silander, J., Smail, E. A., Wang, M., Werdell, J.

“…Finally, we provide considerations for future field campaigns to improve coordination with remote sensing data collection and ensure that field data is well suited for use in model or algorithm development.…”
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Estimating actual evapotranspiration through remote sensing techniques to improve agricultural water management: A case study in the transboundary Olifants Catchment in the Limpopo... por Ahmad, Mobin-ud-Din, Magagula, Thulani F., Love, David, Kongo, V., Mul, Marloes L., Kinoti, Jeniffer

“…This paper describes a case study that uses a remote sensing technique, the Surface Energy Balance Algorithm for Land (SEBAL) to assess actual evapotranspiration across a range of land uses in the middle part of the Olifants Basin in South Africa. …”
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Predicting rice yield losses caused by multispecies weed competition por Flórez, J.A., Fischer, Albert J., Ramírez, Héctor V., Duque E., Myriam Cristina

“…Yield loss prediction enables the economic analysis of weed control, providing a basis for strategic use of herbicides and diversified weed management, but site differences restrict predictions to the environments for which the models are calibrated. We developed an algorithm for predicting rice yield losses based on early assessments of multispecies weed infestations emerging in successive flushes within variable crop stands. …”
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Effect of temperature on the phenology of Chilo partellus (Swinhoe) (Lepidoptera, Crambidae); simulation and visualization of the potential future distribution of C. partellus in A... por Khadioli, N., Tonnang, Henri E.Z., Muchugu, E., Ong'amo, G., Achia, Thomas, Kipchirchir, I., Kroschel, Jürgen, Le Ru, B.

“…Several non-linear models were fitted to the data to model development time, mortality and reproduction of the insect species. Cohort updating algorithm and rate summation approach were stochastically used for simulating age and stage structure populations and generate life-table parameters. …”
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New data-driven estimation of terrestrial CO2 fluxes in Asia using a standardized database of eddy covariance measurements, remote sensing data, and support vector regression por Ichii, Kazuhito, Ueyama, Masahito, Masayuki Kondo, Saigusa, Nobuko, Kim, Joon, Alberto, Ma. Carmelita R., Ardö, Jonas, Euskirchen, Eugenie S., Minseok Kang, Hirano, Takashi, Joiner, Joanna, Kobayashi, Hideki, Belelli Marchesini, Luca, Merbold, Lutz, Miyata, Akira, Saitoh, Taku M., Takagi, Kentaro, Varlagin, Andrej, Bret-Harte, Marion Syndonia, Kenzo Kitamura, Kosugi, Yoshiko, Ayumi Kotani, Kumar, K., Li, Shenggong, Machimura, Takashi, Yojiro Matsuura, Yasuko Mizoguchi, Takeshi Ohta, Mukherjee, Sandipan, Yuji Yanagi, Yasuda, Yukio, Yiping, Zhang, Fenghua Zhao

“…Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. …”
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Anticipated climate and land-cover changes reveal refuge areas for Borneo's orang-utans por Struebig, M., Fischer, M., Gaveau, D.L.A., Meijaard, E., Wich, S., Gonner, C., Skyes, R., Wilting, A., Kramer-Schadt, S.

“…We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. …”
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Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests por Besnard, H., Carvalhais, N., Arain, M.A., Black, A., Brede, B., Buchmann, Nina, Chen, J., Clevers, J.G.P.W., Dutrieux, L.P., Gans, F., Herold, M., Jung, M., Kosugi, Y., Knohl, A., Law, B.E., Paul-Limoges, E., Lohila, A., Merbold, Lutz, Roupsard, O., Valentini, R., Wolf, S., Zhang, X., Reichstein, Markus

“…The resulting data-driven model integrates interannual and seasonal variations of climate and vegetation by using Landsat and climate data at each site. The presented LSTM algorithm was able to effectively describe the overall seasonal variability (Nash-Sutcliffe efficiency, NSE = 0.66) and across-site (NSE = 0.42) variations in NEE, while it had less success in predicting specific seasonal and interannual anomalies (NSE = 0.07). …”
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Predicting potential distribution and identifying priority areas for conservation of the Yellow-tailed Woolly Monkey (Lagothrix flavicauda) in Peru por Guzman, Betty K., Cotrina Sánchez, Alexander, Allauja Salazar, Elvis E., Olivera Tarifeño, Christian M., Ramos Sandoval, Jhonny D., Hoyos Cerna, Marlon Y., Barboza Castillo, Elgar, Torres Guzmán, Cristóbal, Oliva Cruz, Manuel

“…Therefore, in this study we modeled the potential distribution area of this species in Peru, the model was generated using the MaxEnt algorithm, along with 80 georeferenced occurrence records and 28 environmental variables. …”
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Selection of a suitable probability model for the analysis of biochemical data from soil por Rossi, Maria Sol, Mon, Rodolfo, Irurtia, Carlos Bernardino

“…Multivariate time series analysis was used to study the behavior of soil enzyme activities. A time series algorithm was used to study the biochemical profile of the soil subjected to three cycles of agriculture with the ts library in the R environment under Debian GNU/Linux system. …”
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