ARIA (Automatic Risk Assessment) is a state-of-the-art platform with unprecedented ability to generate a fully automated sustainability report in just a few minutes. ARIA uses elements required to check the sustainability of palm plantations with a raft of innovation and years of experience of GRAS in sustainability risk assessment using cutting-edge remote sensing techniques.


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About ARIA

The expansion of palm plantations to tropical rainforest with high biodiversity and areas with high soil carbon stock such as peatlands and wetlands raises major environmental issues that must be addressed urgently.
Considering the ever-increasing commitment of industry for purchasing and using sustainable raw materials, there is a growing need for systems to monitor and claim zero-deforestation sourcing for palm oil.
Automated RIsk Assessment (ARIA) platform enables auditors to evaluate the sustainability risk of individual or group of farms in a user friendly and straight-forward procedure for palm plantations located in Indonesia and Malaysia which together supply more than 80% of palm production in the market. GRAS incorporated exclusive deforestation layers, satellite imagery time series, and other useful datasets to facilitate the identification of sustainability risks associated with palm for auditors in the certification process.


ISCC is a leading certification system in the EU renewable energy sector regulated by the RED II. The ISCC sustainability requirements for farms and plantations are laid down in the form of six principles. ARIA can be a great supplement to audit the ISCC Principle 1 and ISCC Principle 2 criterion regarding the protection of biodiverse and carbon-rich areas. It supports the decision-making process of auditors to assess and quantify environmental conditions of the farms that are going to be certified.


With ARIA, not only can one generate a fully automated and reliable sustainability report in just a few minutes, but our user-friendly and straight-forward platform facilitates users to generate reports for individual or group of farms with no expertise needed. Take a look at some of the distinct functionalities ARIA offers for conducting certification audits:

Automatic Risk Assessments

Users and auditors can use ARIA to create high quality, yet fully automated risk assessment reports within minutes.

Online management of reports and requests

Within your account in the ARIA platform, you can have access to all your reports and track the latest status of your assessment requests. Any reports that you create will be saved in your account with unlimited access.

Request for detailed assessments

Detailed analyses on field or plantation level allow the identification of deforestation with higher accuracy.
These can be requested from GRAS for a specific sourcing area and will be done using time series analysis and high resolution satellite imagery to exclude all the replanting activities from the detected potential deforestation. Detailed assessments enable users to have access to more information such as yield estimation, drought risk assessment and many more.

Online payment system

With the secure online payment there is no time and location constraints to use ARIA. It also helps to reduce carbon footprint with a completely paper-less billing and increases the efficiency of transactions.

Methodology of the automated risk assessment and reporting

For each plantation outline uploaded by the user, the system creates maps of carefully selected datasets, representing land-related ISCC criteria on potential deforestation since 2008, protected areas of high biodiversity, areas of high carbon stock and peatlands. Additional maps on waterbodies, slopes and fires within or in close vicinity of the plantation, as well as satellite images from different relevant points in time complement the report to support the risk evaluation in compliance with ISCC and RED requirements.

GRAS follows high quality standards in terms of data sources and algorithm development, especially for the content, source, quality, format and availability of the datasets. Advanced image processing methods and algorithms are used for the development of datasets to ensure a cost-efficient and high-performing provision of information with most recent updates available on time. The report is created in a automated system, ensuring easy-to-use handling and a timely provision of results with highest standards regarding data security.

Main criteria and additional datasets

Criteria for land use change

The potential deforestation and replanting datasets for Indonesia and Malaysia represent all tree cover removal since January 2008, which is the relevant cut-off-date for ISCC and RED II requirements. Based on optical and radar satellite data, and machine learning algorithms, GRAS produces accurate maps for the distinction of forest and plantation areas for the year 2007 in Indonesia and Malaysia. With this information, tree cover loss within plantation areas can be identified as replanting activities, whereas tree cover loss within forest areas can be identified as actual deforestation since 2008. This improvement of the dataset significantly increases the accuracy of potential deforestation information.

Criteria for land with high biodiversity value

To cover the ISCC criteria on areas with high biodiversity in the risk assessment approach and report, GRAS selected most relevant datasets representing the following topics:

  • Primary forests and other wooded land (ISCC criterion 7.1.2)
  • Highly biodiverse forest and other wooded land (ISCC criterion 7.1.3)
  • Designated nature protection areas (ISCC criterion 7.1.4)
  • Areas for the protection of rare, threatened or endangered species (ISCC criterion 7.1.5)
  • Grassland (ISCC criterion 7.1.6)

For each criterion, GRAS selected and processed relevant datasets according to the strict quality standards regarding accuracy, quality, relevance, regional coverage and source.

Criteria for land with high carbon stock

To identify areas with high carbon stock, GRAS includes datasets on: wetlands (ISCC criterion 7.1.7), continuously forested areas (ISCC criterion 7.1.8), and forested areas with 10-30% canopy cover (ISCC criterion 7.1.9)​
Wetlands are published by CIFOR (Center for International Forestry Research) for Tropical and Subtropical regions. Forest cover is differentiated into sparsely forested areas, with a canopy density between 10% and 30% and forest height of > 5 m, and the continuously forested areas with a canopy cover of > 30% and forest height of > 5 m, taking the ISCC/RED definition for forests into account.​

Criteria for peatland

Peatland areas for Indonesia and Malaysia are represented in the ARIA assessment and report by datasets provided by the Indonesian Ministry of Agriculture and CIFOR (Center for International Forestry Research), respectively. The map produced by CIFOR shows the distribution of peatland that covers the tropics and sub tropics, excluding small islands. It was mapped in 231 meters spatial resolution. Peat here is defined as any soil having at least 30 cm of decomposed or semi-decomposed organic material with at least 50% of organic matter. This corresponds to 29% of carbon content using 1.72 as the transformation factor from total organic carbon to organic matter.

Additional relevant criteria

The ARIA automatic assessment reports support companies and auditors in the individual risk evaluation of plantation outlines with additional information and maps on the topography, highlighting steep slopes and therefore the risk of soil erosion and degradation. Further, land cover maps, waterbodies and the occurrence of fires since 2008 are shown in the report to provide valuable information about the land history. Optical and radar satellite images from the observation period 2008-today complement the report and support the identification of land use change activities.

Interpretation of satellite images

GRAS has added various optical and radar satellite images to the report to support the verification of potential deforestation and potential replanting e.g., cloud-free Landsat satellite composites for the periods 2003-2007, 2008-2012, 2013-2017, and 2018-today, ALOS PALSAR satellite images for the years 2007 and 2018.

The correct interpretation of the satellite images available in the ARIA report provide users with the possibility to assess the risk of deforestation. The interpretation of colour, structure, comparison of the near surroundings, changes over time, etc, allows the detection of land cover changes over time e.g. deforestation, replanting.

The potential deforestation/replanting maps in the ARIA report assist in evaluating and identifying the need for further investigation. For instance, if the satellite images support the presence of a potential deforestation.


Deforestation and replanting activities

Potential deforestation

Tree cover loss is defined as the removal of tree cover due to a variety of factors. Tree cover is defined as all vegetation greater than 5 meters in height, and may take the form of forests or plantations across a range of canopy densities

Potential replanting

Potential replanting defines tree cover loss occurring after 1st January 2008 on areas that GRAS mapped as probable non-forested areas in the year 2007.

“Potential” means that the mapping of deforestation and replanting is done semi-automatically and was not manually checked by GRAS. A certain degree of uncertainty should be considered.

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