By Committee on the Earth System Science for Decisions About Human Welfare: Contributions of Remote Sensing, Geographical Sciences Committee, Board on Earth Sciences and Resources, Division on Earth and Life Studies, National Research Council, Visit Amazon's
Land distant sensing: using space-based satellite tv for pc applied sciences to procure details on environmental variables comparable to land-use and land-covering mixture with different varieties of info provides info on adjustments within the Earth's floor and surroundings which are serious for forecasting and responding to human welfare concerns, reminiscent of ailment outbreaks, nutrition shortages, and floods.
This e-book summarizes a workshop at the strength contributions of remotely sensed info to land-use and land-cover switch and how one can use actual, organic, temporal, and social features of specific destinations to help judgements approximately human welfare. The discussions desirous about human health and wellbeing and nutrition safeguard, features of human welfare during which remotely-sensed environmental stipulations play a key function. Examples illustrating the probabilities for using distant sensing for societal profit are incorporated through the file. as a result of workshop, 3 topics have been pointed out that, if fostered, may support discover the potential of the appliance of land distant sensing to judgements approximately human welfare: (1) integration of spatial info on environmental stipulations derived from distant sensing with socioeconomic information; (2) verbal exchange among distant sensing scientists and choice makers to figure out potent use of land distant sensing info for human welfare matters; and (3) acquisition and entry to long term environmental facts and improvement of means to interpret those facts.
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Additional info for COntributions of land remote sensing for decisions about food security and human health
Applications for Human Health Infectious diseases affecting humans and animals in the tropics have spatially and seasonally varying impacts that can be studied using satellite data. There are two different ways to conduct research involving remotely sensed data in human health studies: using process-based and pattern-based models. Both are useful and important. Process-based or mechanistic models that simulate the underlying biological processes of disease transmission and spread are applied to foretell the future and predict the outcome of different land use, environmental, or policy scenarios.
Remotely sensed data are used to fill in the gaps in groundbased observations, as the routine monitoring of rainfall, vegetation, crops, and market prices is made more meaningful by assembling information on how households access food and income. Remotely sensed data are used to develop vegetation index imagery to identify changes in seasonal landscape that could indicate drought (Hutchinson, 1991). Below are some of the tools used by FEWS NET to measure and analyze conditions in Africa: • The Normalized Difference Vegetation Index (NDVI) calculates the amount of vegetation in a given area by measuring the difference between near-infrared and red light, since chlorophyll in leaves absorbs red light but reflects infrared.
2. There are few in situ ground truth data accompanying remote sensing technology, which will inhibit the use of the technology. In situ data are needed to verify analyses of data derived from remote sensing and to collect other data that cannot be detected remotely. 3. Health research professionals are not typically trained to use the tools required to analyze remotely sensed data. 4. Privacy concerns inhibit the sharing of health data by the health care community. In particular, lack of locational information on disease cases inhibits spatial analyses using remote sensing.
COntributions of land remote sensing for decisions about food security and human health by Committee on the Earth System Science for Decisions About Human Welfare: Contributions of Remote Sensing, Geographical Sciences Committee, Board on Earth Sciences and Resources, Division on Earth and Life Studies, National Research Council, Visit Amazon's