---

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

{
  "Urls": [
    "https://developers.google.com/earth-engine/datasets/tags/soil"
  ],
  "item_limit": 10
}

Output 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

We're here to help you get the most out of this Actor!