Search results for " remote sensing data"

showing 2 items of 2 documents

Remote sensing and climate data as a key for understanding fasciolosis transmission in the Andes: review and update of an ongoing interdisciplinary p…

2006

Fasciolosis caused by Fasciola hepatica in various South American countries located on the slopes of the Andes has been recognized as an important public health problem. However, the importance of this zoonotic hepatic parasite was neglected until the last decade. Countries such as Peru and Bolivia are considered to be hyperendemic areas for human and animal fasciolosis, and other countries such as Chile, Ecuador, Colombia and Venezuela are also affected. At the beginning of the 1990s a multidisciplinary project was launched with the aim to shed light on the problems related to this parasitic disease in the Northern Bolivian Altiplano. A few years later, a geographic information system (GIS…

FascioliasisHealth (social science)Geographic information systemAdvanced very-high-resolution radiometerGeography Planning and DevelopmentMedicine (miscellaneous)lcsh:G1-922Risk Assessmentfasciolosis geographic information system climatic forecast indices remote sensing data Andes.Normalized Difference Vegetation IndexTropical climatemedicineAnimalsHumansFasciolosisRemote sensinggeographyTropical Climategeography.geographical_feature_categorybusiness.industryHealth PolicyFasciola hepaticaSouth Americamedicine.diseaseRemote sensing (archaeology)Epidemiological MonitoringGeographic Information SystemsInterdisciplinary CommunicationEpidemiological MonitoringbusinessMountain rangelcsh:Geography (General)Environmental MonitoringProgram EvaluationGeospatial Health
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Farm-Scale Crop Yield Prediction from Multi-Temporal Data Using Deep Hybrid Neural Networks

2021

Farm-scale crop yield prediction is a natural development of sustainable agriculture, producing a rich amount of food without depleting and polluting environmental resources. Recent studies on crop yield production are limited to regional-scale predictions. The regional-scale crop yield predictions usually face challenges in capturing local yield variations based on farm management decisions and the condition of the field. For this research, we identified the need to create a large and reusable farm-scale crop yield production dataset, which could provide precise farm-scale ground-truth prediction targets. Therefore, we utilise multi-temporal data, such as Sentinel-2 satellite images, weath…

hybrid neural networkSVDP::Landbruks- og Fiskerifag: 900::Landbruksfag: 910farm-scale crop yield prediction; deep learning; hybrid neural network; convolutional neural network; recurrent neural network; Sentinel-2 satellite remote sensing datadeep learningconvolutional neural networkSentinel-2 satellite remote sensing datarecurrent neural networkAgriculturefarm-scale crop yield predictionAgronomy and Crop ScienceAgronomy
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