134 lines
4.3 KiB
Python
134 lines
4.3 KiB
Python
import geopandas as gpd
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import numpy as np
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from datetime import datetime, timedelta
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import json
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import random
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def simulate_river_flow(hours=336):
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"""模拟河流径流数据
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使用简单的正弦函数加随机波动来模拟径流变化
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"""
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# 基础流量(立方米/秒)
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base_flow = random.uniform(50, 200)
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# 生成时间序列数据
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time_steps = np.linspace(0, 2 * np.pi, hours)
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# 使用正弦函数生成周期性变化
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flow = base_flow + base_flow * 0.3 * np.sin(time_steps)
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# 添加随机波动
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flow += np.random.normal(0, base_flow * 0.1, hours)
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return flow.clip(min=0) # 确保流量非负
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def flow_to_color(flow, min_flow, max_flow):
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"""根据径流量生成颜色
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低流量 (0-30%): 深蓝 [0, 0, 180, 255]
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中等流量 (30-65%): 绿色过渡 [0, 180, 0, 255]
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高流量 (65-100%): 深红 [180, 0, 0, 255]
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"""
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# 将流量归一化到0-1区间
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normalized_flow = (flow - min_flow) / (max_flow - min_flow)
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transition_point = 0.7 # 70%处开始第一次过渡
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if normalized_flow < transition_point:
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# 从蓝色过渡到绿色 (0-70%)
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ratio = normalized_flow / transition_point # 将0-0.3映射到0-1
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red = 0
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green = int(180 * ratio)
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blue = int(180 * (1 - ratio))
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else:
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# 从绿色过渡到红色 (70%-100%)
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ratio = (normalized_flow - transition_point) / (
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1 - transition_point
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) # 将0.3-1映射到0-1
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red = int(180 * ratio)
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green = int(180 * (1 - ratio))
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blue = 0
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return [red, green, blue, 255] # RGBA格式
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def create_czml(geojson_path, output_path, year=2024, month=6, day=1, hours=168):
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# 读取GeoJSON数据
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gdf = gpd.read_file(geojson_path)
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# 设置时间范围
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start_time = datetime(year, month, day, 0, 0, 0)
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# 创建CZML文档
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czml = [
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{
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"id": "document",
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"name": "River Network Visualization",
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"version": "1.0",
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"clock": {
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"interval": f"{start_time.isoformat()}Z/{(start_time + timedelta(hours=hours)).isoformat()}Z",
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"currentTime": f"{start_time.isoformat()}Z",
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"multiplier": 3600, # 1小时/秒
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},
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}
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]
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# 为每条河流生成数据
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for idx, row in gdf.iterrows():
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# 模拟径流数据
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flow_data = simulate_river_flow(hours)
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min_flow = flow_data.min()
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max_flow = flow_data.max()
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# 提取坐标
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coords = []
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if row.geometry.type == "MultiLineString":
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for line in row.geometry.geoms:
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coords.extend([[x, y, 0] for x, y in line.coords])
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# 创建每个时间点的颜色数据
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color_property = []
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for hour in range(hours):
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current_time = start_time + timedelta(hours=hour)
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color = flow_to_color(flow_data[hour], min_flow, max_flow)
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color_property.append(
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{
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"interval": f"{current_time.isoformat()}Z/{(current_time + timedelta(hours=1)).isoformat()}Z",
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"rgba": color,
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}
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)
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# 创建河流对象
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river = {
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"id": f"river_{row['Index']}",
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"name": f"River {row['Index']}",
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"polyline": {
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"positions": {
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"cartographicDegrees": [
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coord for point in coords for coord in point
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]
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},
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"material": {"solidColor": {"color": color_property}},
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"width": 3,
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"clampToGround": True, # 贴地显示
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"classificationType": "BOTH", # 同时在地形和3D切片上显示
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"zIndex": 1, # 控制叠加顺序
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"distanceDisplayCondition": {
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"nearFar": [0, 1000000] # 显示距离范围（米）
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},
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"heightReference": "CLAMP_TO_GROUND", # 确保贴地
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},
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}
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czml.append(river)
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# 保存CZML文件
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with open(output_path, "w") as f:
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json.dump(czml, f, indent=2)
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if __name__ == "__main__":
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# 使用示例
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geojson_path = "input/1.geojson"
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czml_output = "output/rivers.czml"
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create_czml(geojson_path, czml_output, hours=168)
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