Eco-Tourism Management and Environmental Impact

Module: Sustainable Tech | Difficulty: Premium

Carrying Capacity

Visitor Impact Index

Comparison

Python Implementation

import numpy as np

class SustainableTourismManager:
    def __init__(self, carrying_capacity):
        self.cc = carrying_capacity

    def carrying_capacity_assessment(self, indicators, weights):
        scores = {}
        for ind, value in indicators.items():
            max_val = self.cc.get(ind, 1000)
            scores[ind] = min(value / max_val, 1.0)
        return sum(weights[ind] * scores[ind] for ind in scores)

    def visitor_flow_optimization(self, zones, current_visitors, time_slots):
        optimal = {}
        for zone in zones:
            capacity = zones[zone]['capacity']
            for t in time_slots:
                demand = current_visitors.get(zone, {}).get(t, 0)
                if demand > capacity * 0.8:
                    optimal[(zone, t)] = 'divert'
                elif demand < capacity * 0.3:
                    optimal[(zone, t)] = 'attract'
                else:
                    optimal[(zone, t)] = 'maintain'
        return optimal

    def eco_certification_score(self, criteria):
        weights = {'energy': 0.25, 'water': 0.20, 'waste': 0.20, 'biodiversity': 0.20, 'community': 0.15}
        return sum(weights[k] * criteria.get(k, 0) for k in weights)

Research Insight: Visitor flow management can increase carrying capacity by 20-30% while reducing environmental impact.