Resultados de búsqueda - Sense data.

Remotely‐sensed primary productivity shows that domestic and native herbivores combined are overgrazing Patagonia por Oliva, Gabriel Esteban, Paredes, Paula Natalia, Ferrante, Daniela, Cepeda, Carla Tamara, Rabinovich, Jorge Eduardo

“…Overgrazing has degraded Patagonia, but sheep stocks decreased and gave way to mixed systems with cattle, goats and guanacos (native wild camelids). 2.The objective of this paper was to develop a method to estimate carrying capacity based on remotely sensed data, and to assess wild and domestic herbivore numbers in order to establish if grazing stocks have evolved to balance with carrying capacity. 3.Net Primary Productivity (NPP) MOD17/A3 images and field Aerial Net Primary Productivity (ANPP) data of 66 sites were linearly regressed (R2= 0.83, P<0.01), and the slope 0.236 used to convert MOD17/A3 NPP to ANPP. …”
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Remote sensing approach for spatial planning of land management interventions in West African savannas por Heiskanen, J., Liu, J., Valbuena, R., Aynekulu, Ermias, Packalen, P., Pellikka, P.

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Machine Learning-Driven Remote Sensing Applications for Agriculture in India—A Systematic Review por Pokhariyal, Shweta, Patel, N. R., Govind, Ajit

“…The advancement in remote sensing (RS) and machine learning (ML) has proven beneficial for farmers and policymakers in minimizing crop losses and optimizing resource utilization through valuable crop insights. …”
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Improved remote sensing methods to detect northern wild rice (Zizania palustris L.) por O’Shea, Kristen, LaRoe, Jillian, Vorster, Anthony, Young, Nicholas, Evangelista, Paul, Mayer, Timothy, Carver, Daniel, Simonson, Eli, Martin, Vanesa, Radomski, Paul, Knopik, Joshua, Kern, Anthony, Khoury, Colin K.

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A framework for disaggregating remote-sensing cropland into rainfed and irrigated classes at continental scale por Owusu, Afua, Kagone, S., Leh, Mansoor, Velpuri, Naga Manohar, Gumma, Murali K., Ghansah, Benjamin, Thilina-Prabhath, Paranamana, Akpoti, Komlavi, Mekonnen, Kirubel, Tinonetsana, Primrose, Mohammed, I.

“…Consequently, the approach outlined expands on the suite of remote sensing landcover products that can be used for agricultural water studies in Africa by enabling the extraction of irrigated and rainfed cropland data from landcover products that do not have disaggregated cropland classes.…”
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Use of remote sensing for linkage mapping and genomic prediction for common rust resistance in maize por Loladze, Alexander, Rodrigues, Francelino A., Petroli, Cesar D., Muñoz-Zavala, Carlos, Naranjo, Sergio, San Vicente García, Felix M., Gerard, Bruno G., Montesinos-Lopez, Osval A., Crossa, Jose, Martini, Johannes W.R.

“…Moreover, results of linkage mapping as well as of genomic prediction (GP), suggest that VS data was of a higher quality, indicated by higher −logp values in the linkage studies and higher predictive abilities for genomic prediction. …”
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Dissecting light sensing and metabolic pathways on the millimeter scale in high-altitude modern stromatolites por Alonso-Reyes, Daniel Gonzalo, Galván, Fátima Silvina, Irazoqui, Jose Matias, Amadio, Ariel, Tschoeke, Diogo, Thompson, Fabiano, Albarracín, Virginia Helena, Farias, María Eugenia

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Urgent flood hazard assessment using multi-sensor data in refugee hosting community settings: implications for immediate planning and design of anticipatory actions por Haile, Alemseged Tamiru, Bekele, T. W., Negash, E. D., Mekuria, Wolde, Ruckstuhl, Sandra

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The suitability of existing open data weather data for agro-meteo advisory [Ethiopia] por Ceccarelli, Tomaso, Wit, Allard de, Rob Lokers, Rob

“…Open data in the weather domain could address the information needs of agro-meteo farm advisory systems. …”
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Multivariate random forest prediction of poverty and malnutrition prevalence por Browne, Chris, Matteson, David S., McBride, Linden, Hu, Leiqiu, Liu, Yanyan, Sun, Ying, Wen, Jiaming, Barrett, Christopher B.

Materias: “…data…”
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A synergy cropland of China by fusing multiple existing maps and statistics por Lu, Miao, Wu, Wenbin, You, Liangzhi, Chen, Di, Zhang, Li, Yang, Peng, Tang, Huajun

Materias: “…data fusion…”
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Relationship between MODIS-NDVI data and wheat yield : a case study in northern Buenos Aires province, Argentina por Lopresti, Mariano Francisco, Di Bella, Carlos Marcelo, Degioanni, Américo José

“…In the first five years, an empirical model was calibrated and validated with field-observed wheat yields and MOD13q1 product-NDVI data, whereas in the other four years, the calibrated model was applied by means of yield maps and by comparing with official yields. …”
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Mapping irrigated areas using MODIS 250 meter time-series data: a study on Krishna river basin (India) por Gumma, Murali Krishna, Thenkabail, Prasad S., Nelson, Andrew

“…This paper describes an innovative remote sensing based vegetation phenological approach to map irrigated areas and then the differentiates the ground water irrigated areas from the surface water irrigated areas in the Krishna river basin (26,575,200 hectares) in India using MODIS 250 meter every 8-day near continuous time-series data for 2000–2001. …”
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“The future will be local.” Omställning Sverige – the transition towns movement in Sweden : from local communities to counter-hegemony? por Pühringer, Maria Franziska

Does climate-smart agriculture make economic sense to farmers? Yes, and there's more evidence than you think por Nowak, Andreea C., Rosenstock, Todd S., Namoi, Nictor, Lamanna, Christine, Steward, Peter R.

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Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium por Thenkabail, Prasad S., Biradar, Chandrashekhar M., Noojipady, P., Dheeravath, Venkateswarlu, Li, Yuan Jie, Velpuri, Naga Manohar, Gumma, Murali K., Gangalakunta, O.R.P., Turral, Hugh, Xueliang Cai, Vithanage, Jagath, Schull, M.A., Dutta, R.

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Vegetation phenology to partition groundwater- from surface water-irrigated areas using MODIS 250-m time-series data for the Krishna River basin por Gumma, Murali K., Thenkabail, Prasad S., Velpuri, Naga Manohar

“…Vegetation phonologies of nine distinct classes consisting of irrigated, rainfed, and other land-use classes were derived using MODIS 250-m near continuous time-series data that were tested and verified using groundtruth data, Google Earth very high resolution (sub-metre to 4 m) imagery, and state-level census data. …”
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Remote sensing as a monitoring tool for cropping area determination in smallholder agriculture in Tanzania and Uganda 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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Remote sensing as a monitoring tool for cropping area determination in smallholder agriculture in Tanzania and Uganda por Quiróz, R.

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Estimating Leaf Area Index of Wheat Using UAV-Hyperspectral Remote Sensing and Machine Learning por Rejith, Rajan G., Sahoo, Rabi N., Ranjan, Rajeev, Kondraju, Tarun, Bhandari, Amrita, Gakhar, Shalini

“…Accurate mapping of LAI from high-resolution hyperspectral UAV data using machine learning models facilitates near-real-time monitoring of crop health.…”
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