SDG 2 Data Pathfinder

Through Sustainable Development Goal (SDG) 2, Zero Hunger, the UN proposes to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture by 2030.

Nearly one in 10 people globally were exposed to severe levels of food insecurity in 2019, according to the United Nations (UN). The vulnerabilities and inadequacies of global food systems are expected to further intensify over the coming years.

Through Sustainable Development Goal (SDG) 2, Zero Hunger, the UN proposes to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture by 2030. A critical aspect of this goal is monitoring food production and implementing agricultural practices that increase production while also maintaining ecosystems and strengthening the capacity for adaptation to climate change, extreme weather, drought, flooding, invasive species, and other disasters. NASA Earth observations are an integral component in providing data necessary to assess progress towards achieving these goals.

This false-color Landsat 8 Operational Land Imager (OLI) image acquired on December 26, 2018, highlights the patchwork of flooded rice fields along the Sacramento and Feather Rivers in California, USA. Inundated fields are shown in dark blue; vegetation is bright green. A series of raised levees form the grid pattern between the fields. This image was acquired using a combination of shortwave infrared, near infrared, and visible light (bands 6-5-4). Image: NASA Earth Observatory.

SDG Goals are divided into broad Targets that are further divided into Indicators used to track progress toward accomplishing the Targets. NASA collects and analyzes data about our home planet applicable to agriculture and food production and makes these data fully and openly available to anyone. These data are helping us develop a better understanding of the connections between food production and land cover, soil moisture, evapotranspiration, the water cycle, temperature, and weather.

NASA helps develop tools to address food security and works with decision-makers and data users to tailor these tools to specific locations and user needs. These efforts help address issues like water management for irrigation, crop-type identification and land use, coastal and lake water quality monitoring, drought preparedness, and famine early warnings. Much of this work is carried out and supported fully or in part by the agency's Applied Sciences Program, which works with individuals and institutions worldwide to inform decision-making, enhance quality of life, and strengthen our economy. The Applied Sciences Program co-leads the international Earth Observations for Sustainable Development Goals initiative launched by the Group on Earth Observations. The initiative advances global knowledge about effective ways that Earth observations and geospatial information can support the SDGs.

The data and resources in this Pathfinder are specifically related to SDG 2 Targets 2.1, 2.3, and 2.4 (described below). Additional information about NASA data and products related to agriculture, water resources, and similar topics is available in the Agriculture and Water Resources Data Pathfinder.

SDG Goal 2: End hunger, achieve food security and improved nutrition, and promote sustainable agriculture

Target 2.1: By 2030, end hunger and ensure access by all people, in particular the poor and people in vulnerable situations, including infants, to safe, nutritious, and sufficient food all year round.
Nearly 85% of Mexico is facing drought conditions as of April 15, 2021. This image shows Evaporative Stress Index (ESI) data for the country, with brown colors indicating drier conditions. ESI incorporates leaf area index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA's Aqua and Terra satellites with observations of land surface temperatures from NOAA satellites and observations. The observations are used to estimate the amount of water evaporating from the land surface and from the leaves of plants. Image: NASA Earth Observatory; Landsat Image Gallery.
Target 2.3: By 2030, double the agricultural productivity and incomes of small-scale food producers, in particular women, indigenous peoples, family farmers, pastoralists, and fishers, including through secure and equal access to land, other productive resources and inputs, knowledge, financial services, markets and opportunities for value addition and non-farm employment.
Target 2.4: By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding, and other disasters and that progressively improve land and soil quality.

The NASA datasets listed in the following sections help measure progress toward meeting the above SDG 2 Targets by providing Earth observations that aid in monitoring the food insecurity of vulnerable populations, tracking agricultural production related to incomes of small-scale food producers, and monitoring environmental impacts to soil, water, fertilizer and pesticide pollution, and biodiversity. While not designed to be a complete list of all salient resources available through NASA's Earth science collection, the following information about NASA data, products, and services will help you chart a path to finding the information you need to help address SDG 2 Targets.

Please visit the Earthdata Forum, where you can interact with other users and NASA subject matter experts on a variety of Earth science research and applications topics.

Tools for Data Access and Visualization

Earthdata Search | Panoply | Giovanni | Worldview | AppEEARS | Soil Moisture Visualizer | MODIS/VIIRS Subsetting Tools Suite

Earthdata Search

Earthdata Search is NASA's EOSDIS tool for searching and discovering data in the EOSDIS collection as well as U.S and international agencies across the Earth science disciplines.

Users (including those without specific knowledge of the data) can search for and read about data collections, search for data files by date and spatial area, preview browse images, and download or submit requests for data files, with customization for select data collections.


In the project area, for some datasets, users can customize granules. Users can reformat the data and output as HDF, NetCDF, ASCII, KML, or a GeoTIFF and can choose from a variety of projection options. Data can be subset to obtain only the bands that are needed.



HDF and NetCDF files can be viewed in Panoply, a cross-platform application that plots geo-referenced and other arrays. Panoply offers additional functionality, such as slicing and plotting arrays, combining arrays, and exporting plots and animations.


Giovanni is an online environment for the display and analysis of geophysical parameters. There are many options for analysis. The following are the more popular ones:

  • Time-averaged maps are a simple way to observe the variability of data values over a region of interest.
  • Map animations are a means to observe spatial patterns and detect unusual events over time.
  • Area-averaged time series are used to display the value of a data variable that has been averaged from all the data values acquired for a selected region for each time step.
  • Histogram plots are used to display the distribution of values of a data variable in a selected region and time interval.

For more detailed tutorials:


NASA's Worldview visualization application visualization application provides the capability to interactively browse over 950 global, full-resolution satellite imagery layers and then download the underlying data. Many of the available imagery layers are updated within three hours of observation, essentially showing Earth as it looks "right now." This supports time-critical application areas such as wildfire management, air quality measurements, and flood monitoring. Imagery in Worldview is provided by NASA's Global Imagery Browse Services (GIBS). Worldview also includes nine geostationary imagery layers from GOES-East, GOES-West, and Himawari-8 available at ten minute increments for the last 30 days. These layers include Red Visible, which can be used for analyzing daytime clouds, fog, insolation, and winds; Clean Infrared, which provides cloud top temperature and information about precipitation; and Air Mass RGB, which enables visualization of specific air mass types (e.g., dry air, moist air, etc.). These full disk hemispheric views allow for almost real-time viewing of changes occurring around most of the world.



AppEEARS at LP DAAC offers a simple and efficient way to access and transform geospatial data from a variety of federal data archives. AppEEARS enables users to subset geospatial datasets using spatial, temporal, and band/layer parameters. Two types of sample requests are available: point samples for geographic coordinates and area samples for spatial areas via vector polygons.

Performing Area Extractions

After requesting an area extraction, users are taken to the Extract Area Sample page where they specify a series of parameters that are used to extract data for the areas of interest.

Spatial Subsetting

Define the region of interest in one of three ways:

  • Upload a vector polygon file in shapefile format (a single file with multiple features or multipart single features can be uploaded). The .shp, .shx, .dbf, or .prj files must be zipped into a file folder to upload.
  • Upload a vector polygon file in GeoJSON format (users can upload a single file with multiple features or multipart single features).
  • Draw a polygon on the map by clicking on the Bounding box or Polygon icons (single feature only).

Select the date range for the time period of interest.

Specify the range of dates for which data are desired for extraction by entering a start and end date (MM-DD-YYYY) or by clicking on the Calendar icon and selecting dates a start and end date in the calendar.

Adding Data Layers

Enter the product short name (e.g., MOD09A1, ECO3ETPTJPL), keywords from the product long name, a spatial resolution, a temporal extent, or a temporal resolution into the search bar. A list of available products matching the query will be generated. Select the layer(s) of interest to add to the Selected layers list. Layers from multiple products can be added to a single request. Be sure to read the list of available products available through AppEEARS.


Selecting Output Options

Two output file formats are available:

  • GeoTIFF
  • NetCDF4

If GeoTIFF is selected, one GeoTIFF will be created for each feature in the input vector polygon file for each layer by observation. If NetCDF4 is selected, outputs will be grouped into .nc files by product and by feature.


Interacting with Results

From the Explore Requests page, click the View icon to view and interact with results. This will take users to the View Area Sample page.

The Layer Stats plot provides time series boxplots for all of the sample data for a given feature, data layer, and observation. Each input feature is renamed with a unique AppEEARS ID (AID). If the feature contains attribute table information, users can view the feature attribute table data by clicking on the Information icon to the right of the Feature dropdown. To view statistics from different features or layers, select a different aid from the Feature dropdown and/or a different layer of interest from the Layer dropdown.


Please see the AppEEARS documentation to learn more about downloading the output as GeoTIFF or NetCDF4 files.

Soil Moisture Visualizer

ORNL DAAC developed a Soil Moisture Visualizer tool (read about it at Soil Moisture Data Sets Become Fertile Ground for Applications) that integrates a variety of different soil moisture datasets over North America. The visualization tool incorporates in-situ, airborne, and remote sensing data into one easy-to-use platform. This integration helps to validate and calibrate the data and provides spatial and temporal data continuity. It also facilitates exploratory analysis and data discovery for different groups of users. The Soil Moisture Visualizer offers the capability to geographically subset and download time series data in .csv format. For more information on the available datasets and use of the visualizer, view the Soil Moisture Visualizer Guide.

To use the visualizer, select a dataset of interest under Data. Depending on the dataset chosen, the visualizer provides the included latitude/longitude or an actual site location name and relative time frames of data collection. Upon selecting a parameter, the tool displays a time series with available datasets. All measurements are volumetric soil moisture. Surface soil moisture is the daily average of measurements at 0-5 cm depth and root zone soil moisture (RZSM) is the daily average of measurements at 0-100 cm depth. The visualizer also provides data sources for download.

The Soil Moisture Visualizer allows users to compare soil moisture measurements from multiple sources at the same location. In this screenshot, Level 4 Root Zone Soil Moisture (L4 RZSM) data acquired by NASA’s Soil Moisture Active Passive (SMAP) satellite are shown with data from in situ sensors across the 9-kilometer Equal-Area Scalable Earth (EASE) grid cell encompassing the Tonzi Ranch Fluxnet site in the Sierra Nevada foothills of California, USA. Daily precipitation values for the site (purple spikes) are also provided for reference. Image: NASA ORNL DAAC.

MODIS/VIIRS Subsetting Tools Suite

ORNL DAAC also has several tools for subsetting data from the MODIS and VIIRS instruments:

  • With the Global Subset Tool, users can request a subset for any location on Earth that are as GeoTiff and in text format, including interactive time-series plots and more. Users specify a site by entering the site's geographic coordinates and the area surrounding that site, from one pixel up to 201 x 201 km. From the available datasets, users can specify a date and then select from MODIS Sinusoidal Projection or Geographic Lat/Long. You will need to register for an Earthdata Login to request data.
  • With the Fixed Sites Subsets Tool, users can download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products. The goal of the Fixed Sites Subsets Tool is to prepare summaries of selected data products for the community to characterize field sites. It includes sites from networks such as National Ecological Observatory Network, Forest Global Earth Observatory network, Phenology Camera network, and Long Term Ecological Research Network.
  • With the Web Service, users can retrieve subset data (in real-time) for any location, time period, and area programmatically using a REST web service. Web service client and libraries are available in multiple programming languages, allowing integration of subsets into a workflow.

Top image: The Global Subsets Tool enables users to download available products for any location on Earth. Bottom image: The Fixed Sites Subsets Tool provides spatial subsets for established field sites for site characterization and validation of models and remote sensing products. Image: NASA ORNL DAAC.

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Other Resources

NASA Applied Sciences Resources

Professor Matt Hansen is using commercial small satellite imagery to map winter wheat extent in Punjab, Pakistan. The project is incorporating field measurements to validate crop maps. Image: NASA Harvest.

NASA's Applied Sciences Agriculture Program Area promotes the use of Earth observations to strengthen food security, support market stability, and protect human livelihoods. NASA Harvest, which is managed under the Agriculture Program Area, is a multidisciplinary consortium commissioned by NASA and led by the University of Maryland to enhance the use of satellite data in decision making related to food security and agriculture both domestically and globally. NASA Harvest has prioritized three impact areas: agricultural land use, agricultural sustainability, and agricultural productivity, and aims to improve each of these areas as well as the methods and products that provide actionable information and insight about them from farm to global scales. Together with partners in the U.S. and around the world, they help bolster food security, improve agricultural resilience, and reduce price volatility for vulnerable communities.

NASA's Applied Sciences Water Resources Application Area supports partnerships and applied research to discover, develop, and demonstrate new practical uses for NASA's Earth observations by the water resources management community. They work with a wide range of partners in the U.S. and around the world to find innovative solutions as shifts in land use, changing climates, and growing populations stress water supplies. The Water Resources Applications Area also supports the NASA Western Water Applications Office (WWAO), which works closely with water resource management partners in the Western U.S., and NASA Harvest, which engages with both domestic and international partners in the agricultural sector.

NASA's Applied Sciences Program supports two additional food security-related initiatives:

  • The Group on Earth Observations Global Agricultural Monitoring (GEOGLAM) Crop Monitor For Early Warning provides monthly transparent, multi-source, consensus assessments of crop growing conditions, status, and agro-climatic conditions that are likely to impact production in countries vulnerable to food insecurity. These assessments help strengthen agricultural, humanitarian intervention, and food security decision making and policy implementations.
  • The Drought Severity Evaluation Tool (DSET) was developed as part of NASA's Navajo Nation Drought Project. A collaborative effort of WWAO, the Navajo Nation Department of Water Resources, and the Desert Research Institute, DSET improves drought reporting and monitoring in the Navajo Nation, which covers an area in northern Arizona, southern Utah, and northern New Mexico roughly the size of the U.S. state of West Virginia.

NASA's Applied Remote Sensing Training (ARSET) program, which is part of the Applied Sciences Capacity Building Program Area, trains people to use Earth-observing data for environmental management and decision-making. ARSET training programs relevant to this SDG are:

Other NASA Assets

Annual total harvested crop area from the Carbon Fluxes from Global Agricultural Production and Consumption, 2005-2011 dataset. Darker green indicates a larger total annual harvested crop area in km2/year. Credit: NASA ORNL DAAC.

Data collections and resources relevant to this SDG are available through ORNL DAAC:

  • The Global Database of Soil Respiration Data provides soil respiration measurements that encompass the flux of autotrophically- and heterotrophically-generated CO2 from the soil to the atmosphere.
  • The Carbon Fluxes from Global Agricultural Production and Consumption dataset, which is part of NASA's Carbon Monitoring System (CMS), provides global estimates of carbon fluxes associated with annual crop NPP and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange derived from these carbon fluxes.
  • The NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) campaign is focused on observations of root zone soil moisture and net ecosystem exchange of CO2 over a variety of North American biomes across several seasons.
  • The Soil Moisture Visualizer harmonizes surface and root zone soil moisture datasets that are in diverse native data formats and encompass a range of spatial footprints, soil depths, and measurement frequencies.

Monitoring Drought using NASA Earth Observation Data is a story map from NASA’s ArcGIS DAAC Collaboration. The story map incorporates NASA Earth observations from multiple NASA programs into one thematic GIS web map. Analysis of these datasets provides a means to monitor in near real-time conditions leading to and resulting from drought as well as how humans may be affected. Datasets in the story map include precipitation, soil moisture, vegetation surface reflectance, evaporative stress, normalized difference vegetation index (NDVI), and population density.

The NASA-funded Methane Source Finder project mapped potential sources of methane in the state of California and developed new technologies to make remote sensing data of methane emissions readily available. Additional funding for this effort was provided by the California Air Resources Board, the California Energy Commission, the National Institute of Standards and Technology, Rocky Mountain Institute, and the University of Arizona. Read more about this effort at From Cow Manure to Landfills: Mapping Methane in California.

External Resources

Map of near-term acute food insecurity from July to September 2021 from the Famine Early Warning System Network (FEWS NET). Colors indicate food insecurity levels: Yellow = stressed; Orange = crisis; Red = emergency. Image: FEWS NET.

Several external tools consolidate food security and agriculture information at the U.S. national level and at the global level:

  • The Famine Early Warning System Network, which was created in 1985 by USAID, provides early warning and analysis on acute food insecurity. Analysts and specialists in 22 field offices work with U.S. government science agencies, national government ministries, international agencies, and non-governmental organizations to produce forward-looking reports on more than 36 of the world’s most food-insecure countries.
  • NOAA's National Integrated Drought Integration System provides drought-related information and resources and also has a suite of data, maps, and tools for exploring drought across the U.S.
  • The European Commission's European Drought Observatory provides drought-related information across Europe. The site contains data-based maps of indicators, tools for visualizing and analyzing the information, and reports of specific regional droughts.
  • The GEOGLAM Global Rangelands and Pasture Productivity Map is an online geospatial tool that provides information derived from Earth observations about the state and condition of global rangelands.

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Find the Data

Deforestation for agriculture and livestock production contributes to land degradation. These datasets will provide information on land surface reflectance and land cover.
These datasets provide information on changes to vegetation based on greenness (or vegetation indices_, gross primary productivity, evapotranspiration, and evaporative stress index.
Rain and snow provide the water upon which agriculture depends. This can be direct, through rainfall or snowpack on agricultural fields, or indirect, through water reserves in lakes, reservoirs, and groundwater that are used for irrigation.
SEDAC includes a number of data collections relevant to food security and agriculture.
Fresh, clean water is needed for agricultural production while fresh or salt water within a balanced, healthy ecosystem is critical for aquaculture
Last Updated
Feb 11, 2021