Resultados de búsqueda - "Sense data."

Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data por Fluet-Chouinard, E., Lehner, B., Rebelo, Lisa-Maria, Papa, F., Hamilton, S.K.

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A new multivariate agricultural drought composite index based on random forest algorithm and remote sensing data developed for Sahelian agrosystems por Hanade Houmma, I., Gadal, S., El Mansouri, L., Garba, M., Gbetkom, P.G., Mamane Barkawi, M.B., Hadria, R.

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Improving spatiotemporal groundwater estimates after natural disasters using remotely sensed data: a case study of the Indian Ocean Tsunami por Chinnasamy, Pennan, Sunde, M.G.

“…The analysis demonstrated the utility of remotely sensed data in predicting and assessing the impacts of natural disasters.…”
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Detection of bacterial wilt infection caused by Ralstonia solanacearum in potato (Solanum tuberosum L.) through multifractal analysis applied to remotely sensed data por Chavez, P., Yarleque, C., Loayza, H., Mares, V., Hancco, P., Priou, S., Marquez, M.P., Posadas, A., Zorogastua, P., Flexas, J., Quiróz, R.

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Using Remote Sensing Data in the Cloud to Monitor Climate Change in Senegal Regions Based on Seasonal Variables from 2000 to 2020.... por Alvarez, Cesar Ivan, Govind, Ajit

“…By evaluating correlations between vegetation, using NDVI, land surface temperature (LST), mean temperature, and precipitation from remote sensing data collected over the last 20 years (2000 to 2020) through Google Earth Engine, we have discovered a high negative correlation between NDVI and LST, a high positive correlation between NDVI and precipitation, and the lowest correlation between NDVI and mean temperature. …”
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Application of a method of analysis of remote sensing data obtained by targeting the estimated productivity in cane for quantifying panela NDVI (normalized difference vegetation index) por Rueda Calier, Fabio, Peñaranda Mallungo, Luis Alfonso, Velásquez Vargas, Wilmer Leonardo, Díaz Báez, Sergio Antonio

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Assessment and prediction of above-ground biomass in selectively logged forest concessions using field measurements and remote sensing data: Case study in South East Cameroon por Neba, G.A., Kanninen, M., Atyi, R.E., Sonwa, D.J.

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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. Site-level evaluation of the estimated CO2 fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r2 = 0.73 and 0.42 for 8 day GPP and NEE). …”
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EIA yield at scale project 2nd year Ph.D report (2024) on large scale yield gap estimation and characterization with multi-soruce remote sensing data: case study of rainfed wheat in Ethiopia

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Förtolkat digitalt data till skogsägarplan por Lundgren, Erik

“…This report is based on survey questions sent to five different organizations working with remote sensing data. Only two of these where willing to participate in this investigation. …”

Drought monitoring: Mali por Dembélé, Moctar, Koné, A., Amarnath, Giriraj, Zwart, Sander, Schmitter, Petra

“…The Mali Drought Monitoring System (MaliDMS) helps monitor drought onset, occurrence, duration, extent and severity based on WaPOR-derived and other high resolution remote-sensing data that are generated in near real time to enable a comprehensive assessment of drought conditions.…”
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Statistics from space: Next-generation agricultural production information for enhanced monitoring of food security in Mozambique: Project status update (H1 2023) por Koo, Jawoo

“…Objective: Produce and disseminate accurate crop production statistics data leveraging satellite remote sensing data for timely food policy decisions in Mozambique.…”
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Predicting high-magnitude, low-frequency crop losses using machine learning: An application to cereal crops in Ethiopia por Mann, Michael L., Malik, Arun S., Warner, James

“…In this paper we propose a new data fusion method combining remotely-sensed data with agricultural survey data that might address these limitations. …”
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Predicting high-magnitude, low-frequency crop losses using machine learning: An application to cereal crops in Ethiopia por Mann, Michael L., Warner, James, Malik, Arun S.

“…In this paper, we propose a new data fusion method—combining remotely sensed data with agricultural survey data—that might address these limitations. …”
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Real-time satellite data for natural resources management por Technical Centre for Agricultural and Rural Cooperation

“…John Stephenson and Jim Williams explain how weather satellite data reception systems are making remote sensing data more accessible for a variety of local applications.…”
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Irrigation: Remote control por Zwart, Sander J., Leclert, Lucie M.C., Bastiaanssen, Wim G.M.

“…Managers of the Office du Niger irrigation scheme in Mali are using remote sensing data to analyse the efficiency of the system without having to physically check the infrastructure. …”
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Modeling of Effective Leaf Area Index por Selin, Lina

“…The remote sensing data used were airborne laser scanning (ALS) data, Interferometric Synthetic Aperture Radar (InSAR) data from TanDEM-X, and stereo matched drone images. …”

Assessing the accuracy for area-based tree species classification using Sentinel-1 C-band SAR data por Udali, Alberto

“…The re-mote sensing data used were C-band Synthetic Aperture Radar (SAR) data from Sentinel-1. …”

Predicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model por Parmentier, I., Harrigan, R.J., Buermann, W., Mitchard, E.T.A., Saatchi, S., Malhi, Y., Bongers, F., Hawthorne, W.D., Leal, M.E., Lewis, S.L., Nusbaumer, L., Sheil, Douglas, Sosef, M.S.M., Affum-Baffoe, K., Bakayoko, A., Chuyong, G.B., Chatelain, C., Comiskey, J.A., Dauby, G., Doucet, J.L., Fauset, S., Gautier, L., Gillet, J.F., Kenfack, D., Kouamé, F.N., Kouassi, E.K., Kouka, L.A., Parren, M.P.E., Peh, K.S.H., Reitsma, J.M., Senterre, B., Sonke, B., Sunderland, Terry C.H., Swaine, M.D., Tchouto, M.G.P., Thomas, D., Valkenburg, J.L.C.H. van, Hardy, Olivier J.

“…Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns in tropical rain forest, West Africa and Atlantic Central Africa.…”
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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

“…The comparison of sensible heat flux measured from remotely sensed data and scintillometers provide accurate results. …”
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