Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Upangaji wa Eneo Lililohifadhiwa Baharini (MPA) kwa Kutumia Marxan× | Klorofili-a ya Rangi ya Bahari× | |
|---|---|---|
| Nyanja | Oseanografia | Oseanografia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2000 | 1978 |
| Mwanzilishi≠ | Ian Ball | Remote Sensing Community |
| Aina≠ | optimization-algorithm | bio-optical |
| Chanzo asilia≠ | 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 ↗ |
| Majina mbadala | Marxan, Marxan with Zones | Chlorophyll-a Retrieval, Ocean Productivity Monitoring |
| Zinazohusiana | 3 | 3 |
| Muhtasari≠ | 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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