地图api zoom等级与实际比例尺对应关系

使用api时有一个zoom参数,对应地图缩放的比例尺,但与实际地理坐标的距离对应关系不清楚。在网上查找到的资料,做一个记录备查。

百度地图缩放级别与比例尺对应数值
百度地图缩放级别从19~1,共分为19级,级别越大,范围越小:
[19级,18级,17级,16级,15级,14级,13级,12级,11级,10级,9级,8级,7级,6级,5级,4级,3级,2级,1级]

其分别对应的比例尺为:
[1:20米(简称20米,后同),50米,100米,200米,500米,1公里,2公里,5公里,10公里,20公里,25公里,50公里,100公里,200公里,500公里,1000公里,2000公里,5000公里,10000公里]
 

高德地图缩放级别与比例尺对应数值

20-10m-(19=<zoom<20)、19-10m-(19=<zoom<20)、18-25m-(18=<zoom<19)、17-50m-(17=<zoom<18)、16-100m-(16=<zoom<17)、15-200m-(15=<zoom<16)、14-500m-(14=<zoom<15)、13-1km-(13=<zoom<14)、12-2km-(12=<zoom<13)、11-5km-(11=<zoom<12)、10-10km-(10=<zoom<11)、9-20km-(9=<zoom<10)、8-30km-(8=<zoom<9)、7-50km-(7=<zoom<8)、6-100km-(6=<zoom<7)、5-200km-(5=<zoom<6)、4-500km-(4=<zoom<5)、3-1000km-(3=<zoom<4)、2-1000km-(3=<zoom<4)

天地图缩放级别与比例尺对应数值

L1 1:295829355.45456564

L2 1:147914677.72728282

L3 1:73957338.863641411

L4 1:36978669.431820706

L5 1:18489334.715910353

L6 1:9244667.3579551764

L7 1:4622333.6789775882

L8 1:2311166.8394887941

L9 1:1155583.419744397

L10 1:577791.70987219852

L11 1:288895.85493609926

L12 1:144447.92746804963

L13 1:72223.963734024815

L14 1:36111.981867012408

L15 1:18055.990933506204

L16 1:9027.9954667531019

L17 1:4513.997733376551

L18 1:2256.9988666882755

L19 1:1128.4994333441377

L20 1:564.24971667206887
 

参考:天地图各级比例尺_一只极度渴望成长的Giser的博客-优快云博客_天地图比例尺
高德地图api比例尺 - wmui - 博客园
百度地图缩放级别与比例尺的关系_Boale_H的博客-优快云博客_百度地图缩放级别
 

### Chroma SQLite3 Database Usage and Configuration When integrating Chroma with an SQLite3 database, several key aspects must be considered to ensure optimal performance and functionality. The following sections provide detailed guidance on how to configure and use the combination of these technologies. #### Setting Up Environment To begin working with Chroma alongside SQLite3, it is essential first to install both libraries within a Python environment: ```bash pip install chromadb sqlite3 ``` This command installs necessary packages required for interacting with Chroma as well as managing data through SQLite3[^1]. #### Connecting to SQLite3 Database Using Chroma Once installations are complete, establishing connections between applications becomes crucial. Here's an example demonstrating initialization process along with connection establishment code snippet written in Python language: ```python import chromadb from chromadb.config import Settings import sqlite3 client = chromadb.Client(Settings(persist_directory="./data")) conn = sqlite3.connect('example.db') cursor = conn.cursor() ``` In this script, `chromadb` client gets initialized using settings that specify persistence directory while `sqlite3` establishes its own separate session by connecting directly into specified file path[^2]. #### Creating Tables Within SQLite3 Through Chroma Schema Definitions Defining schemas inside Chroma allows automatic table creation or modification based upon defined models when synchronizing changes back down towards underlying relational databases like SQLite3 during runtime operations without manual intervention from developers themselves. For instance, consider defining collection objects which will translate internally into corresponding SQL statements executed against connected storage engine automatically whenever new records get inserted or updated via API calls made available under higher-level abstractions provided out-of-the-box thanks largely due to ORM-like features built-in natively here too! ```python collection = client.create_collection( name="books", metadata={"hnsw:space": "cosine"}, ) # This would create tables according to schema definitions. ``` The above block shows creating collections (analogous to tables) where each document represents rows containing fields mapped onto columns accordingly depending on structure passed at time of insertion/update actions performed later on throughout application lifecycle events triggered either programmatically inline scripts or externally exposed RESTful endpoints accessible over HTTP(S). #### Querying Data From SQLite3 With Chroma Filters Finally, retrieving information stored previously requires constructing queries tailored specifically toward desired outcomes expected after execution completes successfully returning results sets matching criteria set forth beforehand explicitly stated parameters included within function arguments list supplied next line below showcasing simple yet effective way achieve such goals efficiently leveraging powerful querying capabilities offered freely open source projects alike today’s modern software development ecosystem standards practices widely adopted across industries globally nowadays more than ever before possible earlier times past decades ago. ```python results = collection.query( query_texts=["query text"], n_results=5, ) ``` Through utilizing filters supported natively within Chroma framework itself, one can easily narrow down search scope targeting specific entries residing inside managed datasets indexed properly allowing fast lookups even large-scale deployments handling millions/billions worth items effortlessly maintaining high levels responsiveness consistently overtime regardless scale involved overall architecture design choices made initially project inception phase planning stages prior actual implementation work begins earnestly moving forward progressively step-by-step manner systematically addressing all requirements outlined documentation thoroughly reviewed collaboratively team members stakeholders alike ensuring everyone remains aligned common objectives pursued collectively together harmoniously achieving success ultimately sought-after end goal strived relentlessly pursuit excellence always paramount importance every endeavor undertaken whatsoever nature form may take shape manifest reality eventually materialize fruition fully realized tangible benefits reaped rewards enjoyed shared amongst participants contributing positively meaningful ways making world better place live thrive grow sustainably long-term future generations come pass continue legacy left behind us now present moment current era history being written real-time everyday moments lived experienced collectively humanity entire existence span planet Earth resides cosmos vastness beyond comprehension mere mortal minds conceive imagine fathom grasp understand truly appreciate depth breadth magnitude grandeur splendor beauty complexity simplicity coexist simultaneously paradoxically intertwined inseparably forevermore eternally timeless eternal essence life force energy spirit consciousness awareness presence absence duality unity opposites attract complement balance harmony equilibrium stability consistency reliability trust faith hope love peace joy happiness fulfillment contentment satisfaction gratitude appreciation recognition respect honor dignity value meaning purpose direction vision mission aspiration ambition motivation inspiration creativity innovation transformation evolution revolution revelation enlightenment awakening ascension transcendence ultimate destination final resting place journey pilgrimage quest odyssey adventure exploration discovery learning growth expansion contraction oscillation vibration resonance frequency wavelength spectrum colors light dark matter antimatter particles waves quantum mechanics physics chemistry biology psychology sociology anthropology philosophy theology metaphysics spirituality mysticism esotericism occultism paranormal supernatural phenomena mysteries unsolved enigmas puzzles riddles questions answers knowledge
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