Resultados de búsqueda - Sense data.

High-frequency monitoring enables machine learning–based forecasting of acute child malnutrition for early warning por Constenla-Villoslada, Susana, Liu, Yanyan, McBride, Linden, Ouma, Clinton, Mutanda, Nelson, Barrett, Christopher B.

“…Advances in computational methods, and the growing availability of near-real time remote sensing data, suggest that big data approaches might help meet this need. …”
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Time Series Application for Evapotranspiration and NDVI in Ucayali, Peru and Acre, Brazil por Galati, Valerie

“…This app utilizes the capabilities of Google Earth Engine to easily pull, visualize, and plot remotely sensed data in a user-friendly application. Users can choose from preloaded spatial data, draw a shape, or upload their own data to visualize and plot time series within an area of interest. …”
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Complementarity of two rice mapping approaches: characterizing strata mapped by hypertemporal MODIS and rice paddy identification using multitemporal SAR por Asilo, Sonia, de Bie, Kees, Skidmore, Andrew, Nelson, Andrew, Barbieri, Massimo, Maunahan, Aileen

“…We demonstrate the use of MODIS data for rice-based system characterization and X-band SAR data from TerraSAR-X and CosmoSkyMed for the identification and detailed mapping of rice areas and flooding/transplanting dates. …”
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FarMoRe – A tool for monitoring and reporting GHG mitigation results in rice production por Trang, Vu Hong, Nelson, Katherine, Yen, Bui Tan, Cuong, Ong Quoc, Tran, Nguyen Bao, Quyet, Vu Manh

“…Additionally, FarMoRe data can be used to validate aggregated data collected from other sources and remote sensing technologies. …”
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Ghana Feed the Future Harmonized Dataset por International Food Policy Research Institute

“…Moreover, the provision of household GPS coordinates (offset for confidentiality purposes) allows users to match data at different levels. This work combines multi-topic household and community socioeconomic and agricultural surveys with biophysical datasets from multiple sources, including remote sensing, for a thorough comparison of different phenomena. …”
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Automated cropland mapping of continental Africa using Google Earth Engine cloud computing por Xiong, Jun, Thenkabail, Prasad S., Gumma, Murali K., Teluguntla, P., Poehnelt, J., Congalton, Russell, Yadav, K., Thau, D.

“…The automation of agricultural mapping using satellite-derived remotely sensed data remains a challenge in Africa because of the heterogeneous and fragmental landscape, complex crop cycles, and limited access to local knowledge. …”
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Development and adaptation of RIICE tool for Cote d'Ivoire por Mathieu, Renaud, Dossou-Yoyo, Eliott, Holecz, Francisco, Murusegan, Deiveegan, Quicho, Emma, Satapathy, Sushree, Akpoffo, Marius, Gatti, Luca, Ouedraogo, Mathieu

“…The study leveraged multi-source remote sensing data, including Sentinel-1, Sentinel-2, PlanetScope, and SAOCOM, to improve the accuracy of rice area detection and yield predictions. …”
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Analys av säsongsvariationer vid skattning av skogliga variabler med InSAR teknik por Sjödin, Edward

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Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms por Tramontana, Gianluca, Jung, Martin, Schwalm, Christopher R., Ichii, Kazuhito, Camps-Valls, Gustau, Ráduly, Botond, Reichstein, Markus, Arain, M. Altaf, Cescatti, Alessandro, Kiely, Gerard, Merbold, Lutz, Serrano-Ortiz, Penelope, Sickert, Sven, Wolf, Sebastian, Papale, Dario

“…We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. …”
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Skattningar av ståndortsindex – med flygburen laserskanning, allmänt tillgänglig information eller skördarmätningar? por Larsson, Karl

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Hydrological modeling of large river basins: how much is enough? por Johnston, Robyn M., Smakhtin, Vladimir U.

“…Initiatives are needed to improve the quantity and quality of data for model input, calibration and validation, both traditional hydrological monitoring (improved networks, expansion of automated systems) and new methods for data collection (remote sensing, crowd-sourcing and community based observations). …”
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Assessment of Large Scale Land Cover Change Classifications and Drivers of Deforestation in Indonesia por Wijaya, A., Sugardiman, R., Budiharto, Tosiani, A., Murdiyarso, Daniel, Verchot, Louis V.

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Skattningar i gallringsskog med hjälp av flygburen laserskanning por Sjödin, Martin

“…This master’s thesis is a remote sensing study of an area-based method used to detect forest in need of thinning by use of laser data and field samples. …”
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Better Potato for a Better Life: Reducing Food Insecurity and Dependence on Cereals in Amhara Oromia, Tigray and SNNP regions of Ethiopia por International Potato Center

“…Unmanned Aerial Vehicle (UAV)-based remote sensing technology is a game changer in the gathering of agricultural statistics data. …”
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A New Framework for Vegetation Productivity Dynamics Assessment in Patagonia: Rangeland Functional Archetypes por Sello, Mario Eugenio, Maddio, Rafael Adrian, Hurtado, Santiago Ignacio, Castillo, Daniel Alejandro, Perri, Daiana Vanesa, Bruzzone, Octavio Augusto, Easdale, Marcos Horacio

“…In turn, most methods used to evaluate rangelands focus on data obtained from field measurements and vegetation classifications based on remote sensing data. …”
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Active in situ and passive airborne fluorescence measurements for water stress detection on a fescue field por Moya, I., Loayza, H., López, M.L., Sánchez, J.M., Goulas, Y., Ounis, A., Quiróz, R., Calera, A.

“…Notwithstanding, the results from airborne remote sensing are not as precise as in situ active data.…”
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CGIAR Excellence in Agronomy Initiative por CGIAR Excellence in Agronomy Initiative

“…EiA is supported by the CGIAR Big Data Platform and will combine big data analytics, new sensing technologies, geospatial decision tools, and farming systems research to come up with scalable agronomic innovations for agricultural development. …”
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Enhancing sustainable intensification in Ethiopia through landscape restoration interventions: The sustainable intensification assessment framework approach por Adimassu, Zenebe, Tibebe, Degefie, Tamene, Lulseged, Abera, Wuletawu, Ayehu, Getachew Tesfaye

“…Remote Sensing and Geographical Information System (GIS) techniques were used to analyze satellite images while SPSS (V. 26) package was used to analyze primary survey data. …”
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BIHS Harmonized Dataset por International Food Policy Research Institute

“…Moreover, the provision of household GIS coordinates (offset for confidentiality purposes) allows users to match data at different levels. This work combines multi-topic household and community socio-economic and agricultural surveys with biophysical datasets from multiple sources, including remote sensing, for a thorough comparison of different phenomena. …”
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Water productivity monitoring: Ethiopia por Tadesse, Mulugeta, Muleta, D., Schmitter, Petra, Dembélé, Moctar

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