Search Results - Sense data.

Diagnosing irrigation performance and water productivity through satellite remote sensing and secondary data in a large irrigation system of Pakistan by Ahmad, M.D., Turral, Hugh, Nazeer A.

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Surface runoff estimation over heterogeneous canal commands applying medium resolution remote sensing data with the SCS-CN method by Jayakody, Priyantha, Gamage, M.S.D.Nilantha

“…The widely accepted SCS curve number method was employed to calculate surface runoff, using a combination of remotely-sensed land use/land cover and hydrometrological data in the Punjab canal command areas. …”
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Diagnosing irrigation performance and water productivity through satellite remote sensing and secondary data in a large irrigation system of Pakistan by Ahmad, Mobin-ud-Din, Turral, Hugh, Nazeer, Aamir

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Using remote sensing data for water depletion assessment at administrative and Irrigation-system levels: case study of the Ferghana Province of Uzbekistan by Chemin, Yann H., Platonov, Alexander, Ul-Hassan, Mehmood, Abdullaev, Iskandar

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

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Comparing evapotranspiration estimates from satellites, hydrological models and field data by Kite, G.W., Droogers, Peter

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Semi-automated methods for mapping wetlands using Landsat ETM+ and SRTM data by Islam, Aminul, Thenkabail, Prasad S., Kulawardhana, Wasantha, Alankara, Ranjith, Gunasinghe, Sarath, Edussuriya, C., Gunawardana, A.

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Evaluation of Nigerian agricultural production data by Hatzenbuehler, Patrick L., Abbott, Philip C., Abdoulaye, Tahirou

Subjects: “…data quality…”
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Evaluation of different methods for delineation of wetlands in Limpopo River Basin using Landsat ETM + and SRTM data by Kulawardhana, Wasantha, Thenkabail, Prasad S., Masiyandima, Mutsa, Biradar, Chandrashekhar M., Vithanage, Jagath, Finlayson, C. Max, Gunasinghe, Sarath, Alankara, Ranjith

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Machine learning and big data techniques for satellite-based rice phenology by Aguilar-Ariza, Andrés

“…To cope with this challenge, studies have found practical applications on mapping rice using remote sensing techniques. This study attempts to implement a methodology aimed at monitoring rice phenology using optical satellite data. …”
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Training Manual for UAV Data Utilization Workshop: Train-the-Trainer Program by Dubovyk, Olena, Robson, Benjamin A., Andersen, Gidske L.

Subjects: “…remote sensing…”
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Mapping rice areas of South Asia using MODIS multitemporal data by Gumma, Murali Krishna

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Growing period and drought early warning in Africa using satellite data by Henricksen, B.L., Durkin, J.W.

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The spatial data and knowledge gateways at the International Water Management Institute (IWMI) by Thenkabail, Prasad S., Biradar, Chandrashekhar M., Noojipady, Praveen, Islam, Aminul, Velpuri, Naga Manohar, Vithanage, Jagath, Kulawardhana, Wasantha, Jie, Li Yuan, Venkateswarlu, Dheeravath, Gunasinghe, Sarath, Alankara, Ranjith

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Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data by Wessels, Konrad, Mathieu, Renaud, Knox, Nichola, Main, Russell, Naidoo, Laven, Steenkamp, Karen

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Fourier analysis of historical NOAA time series data to estimate bimodal agriculture by Canisius, F., Turral, Hugh, David, S.

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

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Combining remotely sensed and survey data to better understand linkages between urbanization and child nutrition: Case study from Burkina Faso by Haile, Beliyou, Guo, Zhe, Arndt, Channing, Ahn, Hee Eun

“…Instead of relying on a binary urban-rural classification available in the DHS data, we construct two continuous indicators of urbanization based on remotely sensed data ‒ the size of urban area within 10 kilometers radius around the DHS cluster (urban extent) and the distance between the child’s DHS cluster and the boundary of the nearest urban settlement (remoteness).…”
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Crop Monitoring Using Smartphone Based Near-Surface Remote Sensing: Ground Pictures of Wheat and Auxiliary Data from Northern India by International Food Policy Research Institute, Ghent University, University of Manchester

“…We, therefore, foresee that these data will ?nd applications in crop modeling, remote sensing validation and machine learning-based crop assessment.…”
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Integrating remote sensing census and weather data for an assessment of rice yield water consumption and water productivity in the Indo-Gangetic river basin by Cai, X.L., Sharma, Bharat R.

“…This article presents a simplified approach tomap rice (Oryza sativa L.) water consumption, yield, and water productivity (WP) in the Indo-Gangetic Basin (IGB) by combining remotely sensed imagery, national census and meteorological data. …”
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