Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Marxan MPA-planning× | Oceaan-kleur chlo-a× | |
|---|---|---|
| Vakgebied | Oceanografie | Oceanografie |
| Familie | Process / pipeline | Process / pipeline |
| Jaar van ontstaan≠ | 2000 | 1978 |
| Grondlegger≠ | Ian Ball | Remote Sensing Community |
| Type≠ | optimization-algorithm | bio-optical |
| Oorspronkelijke bron≠ | Possingham, H. P., Ball, I., & Andelman, S. (2000). Mathematical methods for identifying representative reserve networks. In S. Ferson & M. Burgman (Eds.), Quantitative Methods for Conservation Biology (pp. 291-306). Springer-Verlag. link ↗ | Gordon, H. R., & Morel, A. Y. (1983). Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. Springer-Verlag. link ↗ |
| Aliassen | Marxan, Marxan with Zones | Chlorophyll-a Retrieval, Ocean Productivity Monitoring |
| Verwant | 3 | 3 |
| Samenvatting≠ | Marxan is a decision-support system that uses optimization algorithms to design cost-effective marine protected area (MPA) networks that achieve conservation targets while minimizing socioeconomic costs. Developed by Ian Ball and Hugh Possingham in 2000, Marxan has become the global standard tool for systematic conservation planning in marine environments. The software enables planners to explore trade-offs between conservation effectiveness and economic feasibility. | Ocean color remote sensing is the primary global method for retrieving seawater chlorophyll-a concentrations and phytoplankton productivity from satellite sensors. Based on bio-optical principles established in the 1970s, ocean color algorithms convert satellite spectral reflectance measurements into estimates of chlorophyll-a pigment concentration. This method enables global-scale, real-time monitoring of oceanic primary productivity and plankton dynamics. |
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