# Developersearthengine Discoveries Spider (`getdataforme/developersearthengine-discoveries-spider`) Actor Automate data extraction from Google Earth Engine datasets with customizable parameters, receiving structured JSON output. Ideal for environmental research and analysis, offering scalable performance and user-friendly setup via Apify Store.... - **URL**: https://apify.com/getdataforme/developersearthengine-discoveries-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Automation, Lead generation, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README --- ## Developersearthengine Discoveries Spider ### Introduction The Developersearthengine Discoveries Spider is a powerful web scraping tool designed to extract valuable data from the Google Earth Engine datasets. It enables users to gather insights on various environmental and climate-related topics by automating the collection of structured information. ### Features - **Automated Data Extraction**: Seamlessly scrape data from specified URLs. - **Customizable Input Parameters**: Tailor the spider's behavior with configurable settings. - **High-Quality Output**: Receive well-structured JSON output for easy analysis. - **Scalable Performance**: Efficiently handle multiple requests and large datasets. - **User-Friendly Setup**: Simple configuration process via Apify Store. ### Input Parameters | Parameter | Type | Required | Description | Example | |------------|---------|----------|-----------------------------------------------------------------------------|----------------------------------------------| | Urls | array | No | The URLs for the spider to scrape. Must be valid HTTP/HTTPS links. | `["https://developers.google.com/earth-engine/datasets/tags/soil"]` | | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "Urls": [ "https://developers.google.com/earth-engine/datasets/tags/soil" ], "item_limit": 10 } ```` #### Output JSON ```json [ { "Title": "BLM AIM TerrADat TerrestrialAIM Point v1", "Brief": "Since 2011, the Bureau of Land Management (BLM) has collected field information to inform land health through its Assessment Inventory and Monitoring (AIM) strategy. To date, more than 6,000 terrestrial AIM field plots have been collected over BLM lands.", "Image": "https://developers.google.com/earth-engine/datasets/images/BLM/BLM_AIM_v1_TerrADat_TerrestrialAIM_sample.png", "Tags": ["blm", "ecosystems", "hydrology", "range", "soil", "table"], "Description (info link)": "https://developers.google.com/earth-engine/datasets/catalog/BLM_AIM_v1_TerrADat_TerrestrialAIM", "actor_id": "nA8se5TqGIG1TcCnU", "run_id": "6F0QWDXofsm0i2vVd" }, { "Title": "FLDAS: Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System", "Brief": "The FLDAS dataset (McNally et al. 2017), was designed to assist with food security assessments in data-sparse, developing country settings.", "Image": "https://developers.google.com/earth_engine/datasets/images/NASA/NASA_FLDAS_NOAH01_C_GL_M_V001_sample.png", "Tags": ["climate", "cryosphere", "evapotranspiration", "humidity", "ldas", "monthly"], "Description (info link)": "https://developers.google.com/earth-engine/datasets/catalog/NASA_FLDAS_NOAH01_C_GL_M_V001", "actor_id": "nA8se5TqGIG1TcCnU", "run_id": "6F0QWDXofsm0i2vVd" }, { "Title": "GLDAS-2.1: Global Land Data Assimilation System", "Brief": "NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components.", "Image": "https://developers.google.com/earth_engine/datasets/images/NASA/NASA_GLDAS_V021_NOAH_G025_T3H_sample.png", "Tags": ["3-hourly", "climate", "cryosphere", "evaporation", "forcing", "geophysical"], "Description (info link)": "https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V021_NOAH_G025_T3H", "actor_id": "nA8se5TqGIG1TcCnU", "run_id": "6F0QWDXofsm0i2vVd" } ] ``` ### Use Cases - **Market Research and Analysis**: Extract data for competitive analysis in environmental sectors. - **Competitive Intelligence**: Monitor competitors' activities related to Earth Engine datasets. - **Price Monitoring**: Track changes in dataset offerings or pricing models. - **Content Aggregation**: Compile information from various sources into a single repository. - **Academic Research**: Gather data for studies on climate change and land use. - **Business Automation**: Automate the collection of environmental data for operational insights. ### Installation and Usage 1. Search for "Developersearthengine Discoveries Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The output is a JSON array containing objects with the following fields: - **Title**: The title of the dataset or discovery. - **Brief**: A brief description of the dataset. - **Image**: URL to an image representing the dataset. - **Tags**: An array of tags associated with the dataset. - **Description (info link)**: A link to more detailed information about the dataset. - **actor\_id**: The ID of the actor that performed the extraction. - **run\_id**: The ID of the specific run. ### Rate Limiting and Best Practices To ensure optimal performance, adhere to these best practices: - Avoid setting a very high `item_limit` unless necessary, as it may lead to longer processing times. - Use valid and accessible URLs in the `Urls` parameter to prevent errors. - Monitor the actor's progress and logs for any issues during execution. ### Error Handling The spider includes error handling mechanisms to manage common issues such as invalid URLs or network timeouts. If an error occurs, it will be logged, and you can review these logs to diagnose and resolve the issue. ### Limitations and Considerations - The actor is designed to scrape publicly accessible data; ensure compliance with terms of service for any target websites. - Performance may vary based on server load and internet speed. - Customization beyond provided parameters requires additional development work. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Contact Us](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "Urls": [ "https://developers.google.com/earth-engine/datasets/tags/soil" ], "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/developersearthengine-discoveries-spider").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("getdataforme/developersearthengine-discoveries-spider").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call getdataforme/developersearthengine-discoveries-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/developersearthengine-discoveries-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Developersearthengine Discoveries Spider", "description": "Automate data extraction from Google Earth Engine datasets with customizable parameters, receiving structured JSON output. Ideal for environmental research and analysis, offering scalable performance and user-friendly setup via Apify Store....", "version": "0.0", "x-build-id": "wpMb1bFOVikwMmyjI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~developersearthengine-discoveries-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-developersearthengine-discoveries-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~developersearthengine-discoveries-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-developersearthengine-discoveries-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~developersearthengine-discoveries-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-developersearthengine-discoveries-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://developers.google.com/earth-engine/datasets/tags/soil" ], "items": { "type": "string" } }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```