Search Results - Sense data.

Groundwater storage and depletion trends in Tamil Nadu State, India by Chinnasamy, Pennan, Agoramoorthy, G.

“…Hence this study has used remote sensing data from NASA’s Gravity Recovery and Climate Experiment and the Global Land Data Assimilation Systems to assess the total change in groundwater storage across the state of Tamil Nadu over a period of 11 years, from 2002 to 2012. …”
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Estimación de rendimientos de trigo a partir de datos espectrales para el partido de Junín, provincia de Buenos Aires by Melilli, Maria Paula

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Operational global actual evapotranspiration: development, evaluation, and dissemination by Senay, Gabriel B., Kagone, Stefanie, Velpuri, Naga Manohar

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Do hydrologic rigor and technological advance tell us more or less about transboundary water management? by Giordano, Mark, Suhardiman, Diana, Peterson-Perlman, J.

“…Strict hydrologic definitions of basins coupled with technological advances including the use of remote sensing and geographic information systems have given us more accurate and detailed knowledge than ever before about the scale and extent of transboundary waters. …”
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Post-Fire Effects in Wetland Environments: Landscape Assessment of Plant Coverage and Soil Recovery in the Paraná River Delta Marshes, Argentina by Salvia, María Mercedes, Ceballos, Dario Sebastian, Grings, Francisco Matias, Karszenbaum, Haydee, Kandus, Patricia

“…The objective of this paper was to study fire severity in terms of fire effect on vegetation cover and soil properties, and the recovery of those properties after one growing season, using optical remote sensing techniques and fieldwork data. To this aim, we performed unsupervised classification of Landsat TM imagery and conducted vegetation censuses and soil sampling in November 2008 and May 2009. …”
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Comportamiento de la vegetación en planicies inundables : impacto del anegamiento y los cambios en el uso del suelo by Figueroa Schibber, Evelyn

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Synergy of Sentinel-1 and Sentinel-2 Time Series for Cloud-Free Vegetation Water Content Mapping with Multi-Output Gaussian Processes by Caballero, Gabriel, Pezzola, Nestor Alejandro, Winschel, Cristina Ines, Sanchez Angonova, Paolo Andres, Casella, Alejandra An, Orden, Luciano, Salinero-Delgado, Matías, Reyes-Muñoz, Pablo, Berger, Katja, Delegido, Jesús, Verrelst, Jochem

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Characterizing degradation of palm swamp peatlands from space and on the ground: An exploratory study in the Peruvian Amazon by Hergoualc'h, Kristell, Gutiérrez Vélez, Victor Hugo, Menton, Mary, Verchot, Louis V.

“…Results also showed that data from both active and passive remote sensing sensors are important for the mapping of dense PS degradation. …”
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Daily river discharge estimates by merging satellite optical sensors and radar altimetry through artificial neural network by Tarpanelli, A., Santi, E., Tourian, M.J., Filippucci, P., Amarnath, Giriraj, Brocca, L.

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Regional monitoring of Fall Armyworm (FAW) using early warning systems by 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.

“…For validation, we first employed the FAO Fall Armyworm Monitoring and Early Warning System (FAMEWS) mobile app data from Kenya, and then subsequently conducted field validation campaigns in Zimbabwe, Kenya, and Tanzania. …”
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Resource book on springshed management in the Indian Himalayan Region: guidelines for policy makers and development practitioners by Rathod, Roshan, Kumar, Manish, Mukherji, Aditi, Sikka, Alok, Satapathy, K. K., Mishra, A., Goel, S., Khan, M.

Subjects: “…data management…”
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Relación entre índices de sequía usando datos meteorológicos y satelitales, en la estepa magallánica seca (Patagonia) by Paredes, Paula Natalia, Maglione, Dora, Sandoval, Marisa, Soto, Julio, Bonfili, Oscar, Humano, Gervasio

Subjects: “…Weather Data…”
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Análisis de la estructura y funcionamiento de los bosques de la región chaqueña mediante sensores remotos by Ferraina, Antonella

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Food system innovations and digital technologies to foster productivity growth and rural transformation by Benfica, Rui, Chambers, Judith A., Koo, Jawoo, Nin-Pratt, Alejandro, Falck-Zepeda, José B., Stads, Gert-Jan, Arndt, Channing

“…Given their transformative potential and the urgency of developing the enabling R&D and policy trajectories required for impact, we highlight genome editing bio-innovations, specifically CRISPR-Cas9, to address sustainable agricultural growth; and digital technologies, including remote sensing, connected sensors, artificial intelligence, digital advisory services, digital financial services, and e-commerce, to help guide the operations and decision-making of farmers, traders, and policymakers in agricultural value chains. …”
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Detection of banana plants and their major diseases through aerial images and machine learning methods: A case study in DR Congo and Republic of Benin by Gómez Selvaraj, Michael, Vergara, Alejandro, Montenegro, Frank, Alonso Ruiz, Henry, Safari, Nancy, Raymaekers, Dries, Ocimati, Walter, Ntamwira, Jules Bagula, Tits, Laurent, Omondi, Bonaventure Aman Oduor, Blomme, Guy

“…Front-line remote sensing tools, coupled with machine learning (ML), have a significant role in crop monitoring and disease surveillance. …”
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Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research by Yebra, Marta, Scortechini, Gianluca, Adeline, Karine, Aktepe, Nursema, Beget, Maria Eugenia, Boer, Matthias, Brown, Tegan, Chuvieco, Emilio, De Bella, Carlos M., Forsyth, Greg, Granda, Elena

“…In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. …”
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Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change by Parkes, Ben, Higginbottom, Thomas P., Hufkens, Koen, Ceballos, Francisco, Kramer, Berber, Foster, Timothy

“…Gridded weather datasets, derived from combinations of in situ gauges, remote sensing, and climate models, provide a solution to fill this gap, and have been widely used to evaluate climate impacts on agriculture in data-scarce regions worldwide. …”
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Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies by Dembélé, M., Ceperley, N., Zwart, Sander J., Salvadore, E., Mariethoz, G., Schaefli, B.

“…Four distinct multivariate calibration strategies (basin-average, pixel-wise, spatial bias-accounting and spatial bias-insensitive) using actual evaporation and streamflow are implemented, resulting in 48 scenarios whose results are compared with a benchmark model calibrated solely with streamflow data. A process-diagnostic approach is adopted to evaluate the model responses with in-situ data of streamflow and independent remotely sensed data of soil moisture from ESA-CCI and terrestrial water storage from GRACE. …”
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Land use and land cover classification using phenological variability from MODIS vegetation in the Upper Pangani River Basin, eastern Africa by Kiptala, J.K., Mohamed, Y., Mul, Marloes L., Cheema, Muhammad Jehanzeb Masud, Zaag, P. van der

“…The overall Kappa coefficient of 0.85 also showed good agreement between the LULC and the ground data. The land suitability classification based on FAO-SYS framework for the various LULC types were also consistent with the derived classification results. …”
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Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral mat... by Gumma, Murali K., Thenkabail, Prasad S., Muralikrishna.I.V., Velpuri, Naga Manohar, Gangadhara Rao, Parthasaradhi, Dheeravath, Venkateswarlu, Biradar, Chandrashekhar M., Acharya, Sreedhar, Gaur, Anju

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