<aside> <img src="/icons/tablet_green.svg" alt="/icons/tablet_green.svg" width="40px" /> TABLE OF CONTENTS

• Introduction
• Getting Started
• Creating a New Project
• Screening Project Results
• Underlying Datasets </aside>

The following datasets are used with the NbS Screening Tool, either to perform the land cover eligibility checks or for the carbon potential calculations:

• Space Intelligence's Global Harmonised Layers (30m resolution) screening-grade dataset, which includes present day land cover (2024), present day forest carbon stock in tC/ha (2024) and historical deforestation (2011-2023). The dataset is built from a smart combination and post-processing of 18 open datasets, which Space Intelligence has built and continues to update to provide a reliable, consistent and globally available dataset. Within the NbS Screening Tool, the dataset is used for the land cover eligibility and historical deforestation check, and for deriving existing forest carbon stock values.
• Growth curve parameters (Robinson et al, 2025) for aboveground live carbon in naturally regrowing forests; this dataset is used within the ARR module for ex-ante predictions of tree growth and carbon removals potential.
• Tropical and Subtropical Wetlands Distribution dataset (Gumbricht et al., 2017); shows distribution of wetland, peatland and peat depth covering the tropics and subtropics at 231m resolution. Within the NbS Screening Tool, this dataset is used to assess percentage of peatland and/or tidal wetland vegetation within user-uploaded project boundaries.
• Deforestation risk maps (ha/pixel/year), either:
  • Official or preliminary coarse resolution (100m) risk maps from Verra, where available; or
  • Space Intelligence risk maps (10m resolution), derived from our in-house jurisdictional Forest Cover Benchmark Maps.

Deforestation risk maps are only used within the REDD module, for historical forest cover eligibility checks across the relevant Historical Reference Period, assessment of deforestation risk within user-uploaded project boundaries, and to estimate carbon emissions avoidance potential (in combination with present day forest carbon stock derived from our Global Harmonised Layers dataset).

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The following datasets are used within the NbS Screening Tool Pro, to assess project durability risk:

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• Temperature Extremes (Copernicus Climate Change Service, Climate Data Store, 2021):

CMIP6 provides climate projections under three Shared Socioeconomic Pathways, using BCC-CSM2-MR model output with a 1981-2010 reference period, selected for its performance in representing temperature extremes. Within the NbS Screening Tool Pro, this dataset is used to compute warm spell days (TC90p), the percentage of days in a year where daily maximum temperature exceeds the 90th percentile of the reference period.

• Flooding (ISIMIP2b flood depth simulations (Inter-Sectoral Impact Model Intercomparison Project, phase 2b):

Multi-model ensemble output across 12 Global Hydrological Model/Global Climate Model (GHM/GCM) combinations (3 GHMs by 4 GCMs), under three Representative Concentration Pathways (RCP2.6, RCP6.0 and RCP8.5), with a historical baseline of 1971-2005. Within the NbS Screening Tool Pro, this dataset is used to compute the frequency of flooding (flood depth greater than 0m) in the 5 years before and after a target year.

• Sea Level Rise (IPCC AR6 sea level projections (Garner et al., 2021)):

Projections that classify pixels as inundated or unchanged (binary mask) relative to a 2025 baseline. Used to estimate projected coastal inundation area in ha.

• Extreme Weather Events (Copernicus Climate Change Service, Climate Data Store, 2021):

Climate forcing data using HadGEM3-GC31-LL model output, with a 1981-2010 reference period. Within the NbS Screening Tool Pro, this dataset is used to compute the frequency of extreme wind days, defined as days where daily-mean wind speed exceeds the local 98th percentile threshold (p98) of the reference period.

• Fire Prevalence (Copernicus Land Monitoring Service):

CLMS burnt area data (Copernicus Land Monitoring Service); maps burn scars, surfaces sufficiently affected by fire to show significant change in vegetation cover (destruction or loss of green material) and in the ground surface (temporarily darker due to ash), over the period 2021-2025. Within the NbS Screening Tool Pro, this dataset is used to compute fire return rate, calculated by summing the number of fires detected each month and dividing by the number of years in the period.

• Anthropogenic (Space Intelligence Global Harmonised Layers):

Historical deforestation risk in the project  area and a 10km buffer is calculated from Space Intelligence’s Global Harmonised Layers dataset, detailed earlier in this guide.