Esri 2020 Global Land Cover: A Comprehensive Overview

Understanding the Earth's surface is crucial for various applications, ranging from environmental monitoring to urban planning. The Esri 2020 Global Land Cover dataset provides a detailed snapshot of land cover types across the globe, offering valuable insights for researchers, policymakers, and businesses alike. This article delves into the intricacies of the Esri 2020 Global Land Cover data, exploring its creation, applications, and significance.

What is Esri 2020 Global Land Cover?

The Esri 2020 Global Land Cover is a high-resolution dataset that classifies the Earth's surface into different land cover types. Land cover refers to the physical material on the Earth's surface, such as forests, grasslands, water bodies, and urban areas. This dataset is created using deep learning techniques applied to satellite imagery, specifically Sentinel-2 imagery, which offers a spatial resolution of 10 meters. This high resolution allows for detailed mapping and analysis of land cover patterns.

Esri, a leading company in geographic information system (GIS) technology, produces this dataset. The Esri 2020 Global Land Cover is part of a broader effort to provide comprehensive and up-to-date geospatial data for various applications. The dataset is updated regularly, with newer versions incorporating the latest satellite imagery and improved classification algorithms.

The primary purpose of the Esri 2020 Global Land Cover is to provide a consistent and accurate representation of land cover types worldwide. This information can be used for a wide range of applications, including:

Environmental Monitoring: Tracking changes in forest cover, monitoring deforestation rates, and assessing the impact of climate change on vegetation.
Urban Planning: Identifying suitable locations for new developments, assessing the environmental impact of urban expansion, and managing urban green spaces.
Agriculture: Monitoring crop health, estimating crop yields, and managing irrigation systems.
Disaster Management: Assessing the vulnerability of different areas to natural disasters, such as floods and wildfires, and planning for emergency response.
Conservation: Identifying priority areas for conservation, monitoring the effectiveness of conservation efforts, and managing protected areas.

The Esri 2020 Global Land Cover dataset is freely available to the public, making it a valuable resource for researchers, policymakers, and anyone interested in understanding the Earth's surface. The dataset can be accessed through Esri's ArcGIS platform, as well as through other data portals and APIs.

How is the Data Created?

The creation of the Esri 2020 Global Land Cover dataset involves a sophisticated process that combines satellite imagery, deep learning algorithms, and expert knowledge. The process can be broken down into several key steps:

Data Acquisition: The primary data source for the Esri 2020 Global Land Cover is Sentinel-2 satellite imagery. Sentinel-2 is a constellation of two satellites operated by the European Space Agency (ESA) as part of the Copernicus program. These satellites provide high-resolution multispectral imagery of the Earth's surface, with a spatial resolution of 10 meters for most bands. The imagery is acquired regularly, providing frequent updates on land cover conditions.
Data Preprocessing: The acquired satellite imagery undergoes several preprocessing steps to ensure its quality and accuracy. These steps include:
- Atmospheric Correction: Removing the effects of atmospheric scattering and absorption to obtain accurate surface reflectance values.
- Geometric Correction: Correcting for distortions in the imagery caused by the satellite's viewing angle and the Earth's curvature.
- Cloud Masking: Identifying and removing clouds and cloud shadows from the imagery.
Deep Learning Model Training: A deep learning model is trained to classify the preprocessed satellite imagery into different land cover types. The model is trained using a large dataset of labeled examples, where each example consists of a satellite image and the corresponding land cover type. The training data is collected from various sources, including existing land cover maps, field surveys, and expert knowledge.
Land Cover Classification: The trained deep learning model is applied to the preprocessed satellite imagery to classify each pixel into one of the land cover classes. The model outputs a probability for each class, and the class with the highest probability is assigned to the pixel.
Post-processing and Accuracy Assessment: The initial classification results are refined through post-processing techniques to improve their accuracy and consistency. These techniques include:
- Filtering: Removing noise and outliers from the classification results.
- Smoothing: Reducing the spatial variability of the classification results.
- Consistency Checking: Ensuring that the classification results are consistent with other data sources, such as elevation data and existing land cover maps.
The accuracy of the final land cover map is assessed using a validation dataset, which consists of independent observations of land cover types. The accuracy assessment provides an estimate of the overall accuracy of the map, as well as the accuracy for each individual land cover class.

Land Cover Classes

The Esri 2020 Global Land Cover dataset classifies the Earth's surface into ten different land cover classes. These classes are designed to be broad enough to capture the major types of land cover, while also being specific enough to be useful for a wide range of applications. The ten land cover classes are:

Water: This class includes all areas covered by water, such as oceans, lakes, rivers, and reservoirs.
Trees: This class includes all areas covered by trees, including forests, woodlands, and orchards. Trees are defined as woody vegetation taller than 3 meters.
Shrubland: This class includes areas dominated by shrubs, which are woody vegetation less than 3 meters tall. Shrubland is often found in arid and semi-arid regions.
Herbaceous: This class includes areas dominated by herbaceous vegetation, such as grasses, forbs, and sedges. Herbaceous vegetation is typically found in grasslands, meadows, and pastures.
Barren: This class includes areas with little or no vegetation, such as deserts, sand dunes, and exposed rock. Barren areas are typically found in arid and semi-arid regions.
Built-up: This class includes areas covered by buildings, roads, and other artificial structures. Built-up areas are typically found in urban and suburban areas.
Snow/Ice: This class includes areas covered by snow or ice, such as glaciers, ice sheets, and snow-covered mountains. This class is dynamic and changes with the seasons.
Cloud: This class identifies areas where the land cover is obscured by clouds. While efforts are made to minimize cloud cover, some areas may still be affected.
Rangeland: This class includes land where the dominant vegetation is suitable for grazing or browsing. It encompasses grasslands, shrublands, and savannas used for livestock grazing.
Permanent Wetland: This class includes areas where the soil is permanently saturated with water, supporting vegetation adapted to wet conditions. Examples include swamps, marshes, and bogs.

These classes provide a comprehensive overview of the Earth's land cover and can be used for a wide range of applications. The accuracy and consistency of the Esri 2020 Global Land Cover dataset make it a valuable resource for researchers, policymakers, and anyone interested in understanding the Earth's surface.

Applications of Esri 2020 Global Land Cover

The Esri 2020 Global Land Cover data has a wide array of applications across various fields, providing valuable insights for decision-making and research. Here are some key areas where this dataset proves invaluable:

Environmental Monitoring and Conservation:

The Esri 2020 Global Land Cover is instrumental in monitoring changes in land cover over time. This is crucial for tracking deforestation rates, assessing the impact of climate change on vegetation, and monitoring the spread of invasive species. Conservation organizations can use the data to identify priority areas for conservation, monitor the effectiveness of conservation efforts, and manage protected areas. For example, changes in forest cover can be detected and analyzed to understand the drivers of deforestation and develop strategies to mitigate its impact. Similarly, the data can be used to monitor the health of ecosystems and identify areas that are vulnerable to degradation.
Urban Planning and Management:
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Urban planners can leverage the Esri 2020 Global Land Cover to identify suitable locations for new developments, assess the environmental impact of urban expansion, and manage urban green spaces. The data can be used to analyze the distribution of land cover types within urban areas, identify areas that are lacking in green space, and plan for the development of new parks and recreational areas. Additionally, the data can be used to assess the impact of urban development on water resources, air quality, and biodiversity. By understanding the spatial distribution of land cover types, urban planners can make more informed decisions about land use and development.
Agriculture and Food Security:

In the agricultural sector, the Esri 2020 Global Land Cover supports monitoring crop health, estimating crop yields, and managing irrigation systems. The data can be used to identify areas where crops are stressed due to drought, pests, or diseases. This information can be used to target interventions, such as irrigation or pest control, to improve crop yields. Additionally, the data can be used to estimate the total area of land under cultivation and to monitor changes in agricultural land use over time. This information is essential for ensuring food security and managing agricultural resources sustainably.
Disaster Management and Risk Assessment:

The dataset is also valuable for assessing the vulnerability of different areas to natural disasters, such as floods and wildfires, and planning for emergency response. The data can be used to identify areas that are at high risk of flooding due to their proximity to rivers or low-lying terrain. Similarly, the data can be used to identify areas that are at high risk of wildfires due to their vegetation type and proximity to ignition sources. This information can be used to develop disaster preparedness plans and to allocate resources for emergency response. For example, evacuation routes can be planned based on the spatial distribution of land cover types, and emergency responders can be equipped with the information they need to navigate affected areas.
Climate Change Research:

Esri's land cover data plays a vital role in climate change research by providing a baseline for monitoring changes in vegetation cover, snow and ice extent, and other land surface characteristics. These changes can be used to assess the impact of climate change on ecosystems and to develop strategies for mitigating its effects. The data can also be used to model the exchange of carbon dioxide between the atmosphere and the land surface, which is essential for understanding the global carbon cycle. By providing a comprehensive and up-to-date picture of land cover, the Esri 2020 Global Land Cover dataset contributes to our understanding of the complex interactions between the Earth's climate and its land surface.

Accessing the Data

Accessing the Esri 2020 Global Land Cover dataset is straightforward, thanks to Esri's commitment to making geospatial data accessible to a wide audience. Here are the primary ways to access the data:

ArcGIS Online:

The most direct way to access the Esri 2020 Global Land Cover is through ArcGIS Online, Esri's cloud-based mapping and analysis platform. The dataset is hosted as a tile layer, which means that it is pre-rendered into a series of images that can be quickly displayed in a web browser or GIS application. To access the data, simply search for "Esri 2020 Global Land Cover" in the ArcGIS Online content library. Once you have found the dataset, you can add it to your map and start exploring the data.
ArcGIS Living Atlas of the World:

The Esri 2020 Global Land Cover is also part of the ArcGIS Living Atlas of the World, a curated collection of geospatial data and maps from around the globe. The Living Atlas provides access to a wide range of authoritative data, including imagery, base maps, and thematic maps. The Esri 2020 Global Land Cover can be found in the Living Atlas by searching for "land cover" or browsing the environmental layers. The Living Atlas provides a convenient way to discover and access the data, as well as other related datasets.
ArcGIS Pro:

If you are using ArcGIS Pro, Esri's desktop GIS software, you can access the Esri 2020 Global Land Cover directly from within the application. Simply connect to ArcGIS Online or the ArcGIS Living Atlas and search for the dataset. Once you have found the dataset, you can add it to your map and start working with the data. ArcGIS Pro provides a powerful set of tools for analyzing and visualizing the data, as well as for creating custom maps and applications.
APIs and Web Services:

For developers, Esri provides APIs and web services that allow you to access the Esri 2020 Global Land Cover programmatically. These APIs and web services can be used to integrate the data into your own applications or to perform custom analyses. The APIs are available in a variety of programming languages, including Python, JavaScript, and .NET. The web services provide access to the data in a variety of formats, including GeoJSON, KML, and Shapefile.

By offering multiple access points, Esri ensures that users with different needs and technical capabilities can easily access and utilize the Esri 2020 Global Land Cover dataset. Whether you are a researcher, a policymaker, or a developer, you can find a way to access the data that meets your needs.

Conclusion

The Esri 2020 Global Land Cover dataset is a valuable resource for understanding the Earth's surface and its changes over time. With its high resolution, comprehensive classification scheme, and wide range of applications, this dataset provides insights for environmental monitoring, urban planning, agriculture, disaster management, and climate change research. By making the data freely available and accessible through various platforms, Esri empowers researchers, policymakers, and businesses to make informed decisions and address some of the world's most pressing challenges. The Esri 2020 Global Land Cover stands as a testament to the power of geospatial technology in advancing our understanding of the planet and promoting sustainable development.