NICFI’s satellite imagery of the global tropics now available in Earth Engine for analysis

NICFI’s satellite imagery of the global tropics now available in Earth Engine for analysis.

NICFI’s satellite imagery of the global tropics now available in Earth Engine for analysis

By Brian Sullivan, Sr. Program Manager, Google Earth Engine.

The Ganges River bisects two districts of the Rajaji National Park, alongside densely populated neighborhoods of Haridwar, India. June 2021. PlanetScope.

From its inception over 10 years ago. Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. This week. In partnership with Norway’s International Climate and Forest Initiative (NICFI). Kongsberg Satellite Services (KSAT). And Planet. We are proud to have launched new imagery that enables the Earth Engine community to tackle these challenges.

NICFI’s satellite imagery of the global tropics now available in Earth Engine for analysis

In September 2020, Norway’s Ministry of Climate. And Environment announced ~$43M of high-resolution tropical satellite monitoring to aid efforts in halting the destruction of the world’s rainforests. The cost of commercial satellite imagery has long prohibited many from employing it in their work. Expanding access to high resolution imagery enables greater use by academics, nonprofits, Indigenous communities, governments and forest managers. Journalists. And the private sector. The Planet Basemaps from the NICFI Tropical Forest program are now available in Google Earth Engine for analysis and monitoring related to forest conservation and restoration, climate change. Biodiversity, sustainable development. And more. (Learn how to get access.)

Google Earth Engine’s three interconnected pillars are perfectly aligned to enhance the opportunities provided with the NICFI Tropical Forest program.

Pillar 1: Data Catalog.


By adding NICFI Planet Basemaps to Google Earth Engine’s public data catalog of 700+ curated geospatial datasets, it provides unprecedented, high resolution (4.77m), deep time series (Dec 2015 to Aug 2020 biannual. Sept 2020 onward monthly). 4-band (RGB+NIR), coverage of 94 countries across the global tropics. No other corpus of broadly licensed, commercial. Analysis-ready imagery of this scope or scale exists today.

NICFI’s satellite imagery of the global tropics now available in Earth Engine for analysis

Pantropical coverage of NICFI program

Pillar 2: Geospatial Computation Platform.


Given the size of the data involved. About one petabyte. It is crucial to bring storage and processing together in one platform to enable global scale. Deep time series analysis. Similarly, as imagery resolution increases, so do the opportunities for finer granularity classifications. And object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Visual access to Planet’s tropical Basemaps have already begun to enable new forms of forestry verification and monitoring. But the next level of impacts will come from enabling new insights through analysis and new machine learning approaches.

Pillar 3: Collaborative Ecosystem.


Earth Engine’s roots began in academic forestry research, producing first of their kind public datasets like Global Forest Change. Funding from NICFI and others allowed nonprofits like World Resources Institute (WRI) to create policy and programmatic efforts like Global Forest Watch. Which in turn enabled journalists to share these insights with the world in a clear, actionable fashion. The ecosystem continued to grow as government and UN agencies furthered forestry research and developed operational workflows. And capacity building powered by Earth Engine. Now, new partnerships and engagements from the private sector are expanding the Earth Engine ecosystem as they look to build deforestation free supply chains, utilizing the power of markets to create a sustainable future.

The NICFI Tropical Forest program launch in Earth Engine brings a new class of global imagery under a purpose-driven license, combined with the latest satellite cloud computing and machine learning analysis platform. In an ever-evolving ecosystem of researchers. Nonprofits, journalists, and the private sector. Google is proud to continue to play a role in advancing partnerships and programs to enable insights and outcomes that reduce and reverse tropical forest loss.

Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT. Planet, and Google and learn how partners like United Nations Food & Agriculture are already using the data in Earth Engine.

NICFI’s satellite imagery of the global tropics now available in Earth Engine for analysis

Register for access at Planet’s NICFI page:

that also contains a program overview, FAQs, and terms of use. Planet also maintains a Developer Resource Center for Earth Enginehttps://earthtopomaps.com/after-school-this-teen-tracks-climate-change/
https://earthtopomaps.com/after-school-this-teen-tracks-climate-change/

Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. Similarly, as imagery resolution increases. So do the opportunities for finer granularity classifications and object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT, Planet.

From its inception over 10 years ago, Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. Similarly. As imagery resolution increases, so do the opportunities for finer granularity classifications and object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT.

Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. Similarly. As imagery resolution increases, so do the opportunities for finer granularity classifications and object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT.

Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. Similarly. As imagery resolution increases, so do the opportunities for finer granularity classifications and object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT.

Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. Similarly, as imagery resolution increases. So do the opportunities for finer granularity classifications and object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT, Planet.

From its inception over 10 years ago, Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. Similarly. As imagery resolution increases, so do the opportunities for finer granularity classifications and object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT.

Google Earth Engine’s mission has been to create a global-scale platform for Earth science data and analysis to further address the most pressing environmental and societal issues we face. Similarly. As imagery resolution increases, so do the opportunities for finer granularity classifications and object detection, but traditional pixel based methodologies fall short and new machine learning techniques are needed. Watch the launch announcement during the Global Forest Observations Initiative (GFOI) with KSAT.

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