2015 USDA Food Desert areas for Florida defined by 2010 US Census tract. Based on LILATract_1And10 field census data. Developed by the USDA Economic Research Service (ERS) as part of the Food Access Research Atlas.This service is intended for use with popups or at very large scales.This data layer is part of Florida’s Roadmap to Living Healthy web map produced by the Florida Department of Agriculture and Consumer Services (FDACS), Division of Food, Nutrition and Wellness (DFNW).For technical assistance, contact the Florida's Roadmap to Healthy Living Administrator

Presents a spatial overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility. Created by the USDA. Data as of 2011-2015 5 yr period averages. Metadata and current information available at: https://www.ers.usda.gov/data-products/food-access-research-atlas

Dataset is an overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility. This dataset provides food access data for populations within census tracts; and offers census-tract-level data on food access that can be used for community planning or research purposes.Data from USDA Economic Research Service (ERS) Food Access Research Atlas, 2019. Last updated 4/27/2021.See also USDA map service at https://gisportal.ers.usda.gov/server/rest/services/FARA/FARA_2019/MapServer.

The Food Access Research Atlas presents a spatial overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility, provides food access data for populations within census tracts, and offers census-tract-level data on food access that can be downloaded for community planning or research purposes.

Data pulled from the USDA Food Research Atlas for 2019 Census Tracts designated as food deserts

Dataset is an overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility. This dataset provides food access data for populations within census tracts; and offers census-tract-level data on food access that can be used for community planning or research purposes.Data from USDA Economic Research Service (ERS) Food Access Research Atlas, 2019. Last updated 4/27/2021.See also USDA map service at https://gisportal.ers.usda.gov/server/rest/services/FARA/FARA_2019/MapServer.

Contains a list of grocery stores which was used by the city to calculate the estimates of Chicagoans living in food deserts in 2011. Data in this file can be cross-referenced with the city's business license data (http://bit.ly/sMFZdN).

Contains a list of grocery stores which was used by the city to calculate the estimates of Chicagoans living in food deserts in 2011. Data in this file can be cross-referenced with the city's business license data (http://bit.ly/sMFZdN).

After analyzing the map, there are some spatial concerns that need to be addressed. Most of the city has a trend of low median household income, and the least poor being in the central part of the city. The neighborhood of Jefferson in the eastern part of Denver is evidence of a food desert, as well as in the Lakeside suburb and Westwood (“Planting Seeds in Food Deserts: Neighborhood Gardens, Produce in Corner Stores” 2014) . One thing that really stood out to me was the lack of grocery stores in the eastern part of Denver, just bordering Aurora. This area is a food desert, and the average income of the area is below average. The wealthier neighborhoods are granted more sufficient access just near this part of Denver. We also see quality access to food towards the center of the city in the areas with lower income. The further we move outwards, the more and more the grocery stores start spreading out from a cluster form. From analyzing the map, it seems like living on the outskirts of Denver is where the lower income households will struggle with access to food

There are some very wealthy neighborhoods, specifically along Colorado Boulevard, where there are a lot of high quality grocery stores. This extensive street only has grocery stores located in the wealthy part of it. If we look north, towards the interstate, we see absolutely none located along Colorado Blvd. It is clear that the grocery stores were placed in the central part of Colorado Blvd, as opposed to the northern and southern parts where the average income is much lower. I believe this to be concrete evidence of a biased towards socioeconomic status.sources: “Planting Seeds in Food Deserts: Neighborhood Gardens, Produce in Corner Stores.” 2014. Accessed April 30. http://www.denverpost.com/news/ci_14906833.

“USDA Economic Research Service - Food Access Research Atlas.” 2014. Accessed April 30. http://www.ers.usda.gov/data-products/food-access-research-atlas#.U2A99le0RPW.

United States Department of Agriculture Economic Research Service’s Food Access Research Atlas maps census tracts that are considered to be both low income and low access. The Atlas provides different ways to understand characteristics that can contribute to food deserts, including income level, distance to supermarkets, and vehicle access. The low access and distance measure extracted from the Food Access Research Atlas, and displayed on the Maryland Food System Map, is low income and low access measured at ½ mile and 10 miles. The Food Access Research Atlas defines this measure as being a low-income census tract with at least 500 people or 33 percent of the population living more than ½ mile (urban areas) or more than 10 miles (rural areas) from the nearest supermarket. A low-income census tract is defined as a having either a poverty rate of 42 percent or more, or a median family income less than 80 percent of the State-wide median family income; or a tract in a metropolitan area with a median family income less than 80 percent of the surrounding metropolitan area medium family income. A census tract is urban if its geographic centroid is in an area with more than 2,500 people. All other tracts are rural.

Data source: United States Department of Agriculture, Economic Research Service

Date: 2013

The food access data displayed in this theme are quantitative measures that illustrate the accessibility of nutritious, affordable, and culturally appropriate food in Florida’s communities. Food consumption is often influenced by the food environment and barriers that may inhibit an individual’s ability to make healthful food choices. In addition, food access has been studied as a contributing factor in diet and health outcomes. The Florida Department of Agriculture and Consumer Services has used the most current food access data from trusted sources, such as the U.S. Department of Agriculture, Centers for Disease Control and Prevention, Florida Department of Children and Families, Feeding Florida, Nielsen, and The Reinvestment Fund to build this visualization. The food access data listed in Florida’s Roadmap to Living Healthy includes important layers, such as nutrition programs, food banks, food deserts, retail market locations, Supplemental Nutrition Assistance Program (SNAP) statistics), low supermarket access areas, farmers’ markets, and limited service restaurants along with other vital statistics. This unique categorization of food access data can be used to better identify the specific food access needs of individual communities in Florida, and allow government agencies, nonprofit organizations, and other organizations to identify gaps so they may begin to improve access to those communities.

This map shows where food stores are located across California with gray dots. Along with that, the red indicates the income of the area. The dark red indicates areas with higher poverty rates and, and the lighter area indicates the places with lower poverty rates. When you first look at the graph it looks like California has a lot of food sources in most of the areas people live in. However, there is more to California's food sources when you take a closer look. The blue indicates poverty rates. (The darker blue means higher poverty rates, and the lighter blue mean lower poverty rates). And the blue and green dots indicate whether the food source is a grocery store or not. The red means it is not a food source and is a convenience store, and the green means it is a food source. As you can see there are way more red dots than green, meaning there are more convenience stores compared to regular grocery stores. A lot of the areas that only have red dots mean that that area is a food desert. That means they have no good quality fresh produce near them. Now let's take a closer look at some towns.

Measure and Map Access to Grocery StoresFrom the perspective of the people living in each neighborhoodHow do people in your city get to the grocery store? The answer to that question depends on the person and where they live. This web map helps answer the question in this app.Some live in cities and stop by a grocery store within a short walk or bike ride of home or work. Others live in areas where car ownership is more prevalent, and so they drive to a store. Some do not own a vehicle, and rely on a friend or public transit. Others rely on grocery delivery for their needs. And, many live in rural areas far from town, so a trip to a grocery store is an infrequent event involving a long drive.This map from Esri shows which areas are within a ten minute walk or ten minute drive of a grocery store in the United States and Puerto Rico. Darker color indicates access to more stores. The chart shows how many people can walk to a grocery store if they wanted to or needed to.It is estimated that 20% of U.S. population live within a 10 minute walk of a grocery store, and 92% of the population live within a 10 minute drive of a grocery store.Look up your city to see how the numbers change as you move around the map. Or, draw a neighborhood boundary on the map to get numbers for that area.Every census block is scored with a count of walkable and drivable stores nearby, making this a map suitable for a dashboard for any city, or any of the 50 states, DC and Puerto Rico. Two colorful layers visualize this definition of access, one for walkable access (suitable for looking at a city neighborhood by neighborhood) and one for drivable access (suitable for looking across a city, county, region or state).On the walkable layer, shades of green define areas within a ten minute walk of one or more grocery stores. The colors become more intense and trend to a blue-green color for the busiest neighborhoods, such as downtown San Francisco. As you zoom in, a layer of Census block points visualizes the local population with or without walkable access.As you zoom out to see the entire city, the map adds a light blue - to dark blue layer, showing which parts of the region fall within ten minutes' drive of one or more grocery stores. As a result, the map is useful at all scales, from national to regional, state and local levels. It becomes easier to spot grocery stores that sit within a highly populated area, and grocery stores that sit in a shopping center far away from populated areas. This view of a city begins to hint at the question: how many people have each type of access to grocery stores? And, what if they are unable to walk a mile regularly, or don't own a car?How to Use This MapUse this map to introduce the concepts of access to grocery stores in your city or town. This is the kind of map where people will want to look up their home or work address to validate what the map is saying.The map was built with that use in mind. Many maps of access use straight-line, as-the-crow-flies distance, which ignores real-world barriers to walkability like rivers, lakes, interstates and other characteristics of the built environment. Block analysis using a network data set and Origin-Destination analysis factors these barriers in, resulting in a more realistic depiction of access.There is data behind the map, which can be summarized to show how many people have walkable access to local grocery stores. The map includes a feature layer of population in Census block points, which are visible when you zoom in far enough. This feature layer can be plugged into an app like this one that summarizes the population with/without walkable or drivable access.Lastly, this map can serve as backdrop to other community resources, like food banks, farmers markets (example), and transit (example). Add a transit layer to immediately gauge its impact on the population's grocery access. You can also use this map to see how it relates to communities of concern. Add a layer of any block group or tract demographics, such as Percent Senior Population (examples), or Percent of Households with Access to 0 Vehicles (examples).The map is a useful visual and analytic resource for helping community leaders, business and government leaders see their town from the perspective of its residents, and begin asking questions about how their community could be improved.Data sourcesPopulation data is from the 2010 U.S. Census blocks. Each census block has a count of stores within a 10 minute walk, and a count of stores within a ten minute drive. Census blocks known to be unpopulated are given a score of 0. The layer is available as a hosted feature layer.Grocery store locations are from SafeGraph, reflecting what was in the data as of October 2020. Access to the layer was obtained from the SafeGraph offering in ArcGIS Marketplace. For this project, ArcGIS StreetMap Premium was used for the street network in the origin-destination analysis work, because it already has the necessary attributes on each street segment to identify which streets are considered walkable, and supports a wide variety of driving parameters.The walkable access layer and drivable access layers are rasters, whose colors were chosen to allow the drivable access layer to serve as backdrop to the walkable access layer. Alternative versions of these layers are available. These pairs use different colors but are otherwise identical in content.Data PreparationArcGIS Network Analyst was used to set up a network street layer for analysis. ArcGIS StreetMap Premium was installed to a local hard drive and selected in the Origin-Destination workflow as the network data source. This allows the origins (Census block centroids) and destinations (SafeGraph grocery stores) to be connected to that network, to allow origin-destination analysis.The Census blocks layer contains the centroid of each Census block. The data allows a simple popup to be created. This layer's block figures can be summarized further, to tract, county and state levels.The SafeGraph grocery store locations were created by querying the SafeGraph source layer based on primary NAICS code. After connecting to the layer in ArcGIS Pro, a definition query was set to only show records with NAICS code 445110 as an initial screening. The layer was exported to a local disk drive for further definition query refinement, to eliminate any records that were obviously not grocery stores. The final layer used in the analysis had approximately 53,600 records. In this map, this layer is included as a vector tile layer.MethodologyEvery census block in the U.S. was assigned two access scores, whose numbers are simply how many grocery stores are within a 10 minute walk and a 10 minute drive of that census block. Every census block has a score of 0 (no stores), 1, 2 or more stores. The count of accessible stores was determined using Origin-Destination Analysis in ArcGIS Network Analyst, in ArcGIS Pro. A set of Tools in this ArcGIS Pro package allow a similar analysis to be conducted for any city or other area. The Tools step through the data prep and analysis steps. Download the Pro package, open it and substitute your own layers for Origins and Destinations. Parcel centroids are a suggested option for Origins, for example. Origin-Destination analysis was configured, using ArcGIS StreetMap Premium as the network data source. Census block centroids with population greater than zero were used as the Origins, and grocery store locations were used as the Destinations. A cutoff of 10 minutes was used with the Walk Time option. Only one restriction was applied to the street network: Walkable, which means Interstates and other non-walkable street segments were treated appropriately. You see the results in the map: wherever freeway overpasses and underpasses are present near a grocery store, the walkable area extends across/through that pass, but not along the freeway.A cutoff of 10 minutes was used with the Drive Time option. The default restrictions were applied to the street network, which means a typical vehicle's access to all types of roads was factored in.The results for each analysis were captured in the Lines layer, which shows which origins are within the cutoff of each destination over the street network, given the assumptions about that network (walking, or driving a vehicle).The Lines layer was then summarized by census block ID to capture the Maximum value of the Destination_Rank field. A census block within 10 minutes of 3 stores would have 3 records in the Lines layer, but only one value in the summarized table, with a MAX_Destination_Rank field value of 3. This is the number of stores accessible to that census block in the 10 minutes measured, for walking and driving. These data were joined to the block centroids layer and given unique names. At this point, all blocks with zero population or null values in the MAX_Destination_Rank fields were given a store count of 0, to help the next step.Walkable and Drivable areas are calculated into a raster layer, using Nearest Neighbor geoprocessing tool on the count of stores within a 10 minute walk, and a count of stores within a ten minute drive, respectively. This tool uses a 200 meter grid and interpolates the values between each census block. A census tracts layer containing all water polygons "erased" from the census tract boundaries was used as an environment setting, to help constrain interpolation into/across bodies of water. The same layer use used to "shoreline" the Nearest Neighbor results, to eliminate any interpolation into the ocean or Great Lakes. This helped but was not perfect.Notes and LimitationsThe map provides a baseline for discussing access to grocery stores in a city. It does not presume local population has the desire or means to walk or drive to obtain groceries. It does not take elevation gain or loss into account. It does not factor time of day nor weather, seasons, or other variables that affect a

This layer shows which parts of the United States and Puerto Rico fall within ten minutes" walk of one or more grocery stores. It is estimated that 20% of U.S. population live within a 10 minute walk of a grocery store, and 92% of the population live within a 10 minute drive of a grocery store. The layer is suitable for looking at access at a neighborhood scale. When you add this layer to your web map, along with the drivable access layer and the SafeGraph grocery store layer, it becomes easier to spot grocery stores that sit within a highly populated area, and grocery stores that sit in a shopping center far away from populated areas. Add the Census block points layer to show a popup with the count of stores within 10 minutes" walk and drive. This view of a city begins to hint at the question: how many people have each type of access to grocery stores? And, what if they are unable to walk a mile regularly, or don"t own a car? How to Use This Layer in a Web MapUse this layer in a web map to introduce the concepts of access to grocery stores in your city or town. This is the kind of map where people will want to look up their home or work address to validate what the map is saying. See this example web map which you can use in your projects, storymaps, apps and dashboards. The layer was built with that use in mind. Many maps of access use straight-line, as-the-crow-flies distance, which ignores real-world barriers to walkability like rivers, lakes, interstates and other characteristics of the built environment. Block analysis using a network data set and Origin-Destination analysis factors these barriers in, resulting in a more realistic depiction of access. Lastly, this layer can serve as backdrop to other community resources, like food banks, farmers markets (example), and transit (example). Add a transit layer to immediately gauge its impact on the population"s grocery access. You can also use this map to see how it relates to communities of concern. Add a layer of any block group or tract demographics, such as Percent Senior Population (examples), or Percent of Households with Access to 0 Vehicles (examples). The layer is a useful visual resource for helping community leaders, business and government leaders see their town from the perspective of its residents, and begin asking questions about how their community could be improved. Data sourcesPopulation data is from the 2010 U.S. Census blocks. Each census block has a count of stores within a 10 minute walk, and a count of stores within a ten minute drive. Census blocks known to be unpopulated are given a score of 0. The layer is available as a hosted feature layer. Grocery store locations are from SafeGraph, reflecting what was in the data as of October 2020. Access to the layer was obtained from the SafeGraph offering in ArcGIS Marketplace. For this project, ArcGIS StreetMap Premium was used for the street network in the origin-destination analysis work, because it already has the necessary attributes on each street segment to identify which streets are considered walkable, and supports a wide variety of driving parameters. The walkable access layer and drivable access layers are rasters, whose colors were chosen to allow the drivable access layer to serve as backdrop to the walkable access layer. Data PreparationArcGIS Network Analyst was used to set up a network street layer for analysis. ArcGIS StreetMap Premium was installed to a local hard drive and selected in the Origin-Destination workflow as the network data source. This allows the origins (Census block centroids) and destinations (SafeGraph grocery stores) to be connected to that network, to allow origin-destination analysis. The Census blocks layer contains the centroid of each Census block. The data allows a simple popup to be created. This layer"s block figures can be summarized further, to tract, county and state levels. The SafeGraph grocery store locations were created by querying the SafeGraph source layer based on primary NAICS code. After connecting to the layer in ArcGIS Pro, a definition query was set to only show records with NAICS code 445110 as an initial screening. The layer was exported to a local disk drive for further definition query refinement, to eliminate any records that were obviously not grocery stores. The final layer used in the analysis had approximately 53,600 records. In this map, this layer is included as a vector tile layer. Methodology Every census block in the U.S. was assigned two access scores, whose numbers are simply how many grocery stores are within a 10 minute walk and a 10 minute drive of that census block. Every census block has a score of 0 (no stores), 1, 2 or more stores. The count of accessible stores was determined using Origin-Destination Analysis in ArcGIS Network Analyst, in ArcGIS Pro. A set of Tools in this ArcGIS Pro package allow a similar analysis to be conducted for any city or other area. The Tools step through the data prep and analysis steps. Download the Pro package, open it and substitute your own layers for Origins and Destinations. Parcel centroids are a suggested option for Origins, for example. Origin-Destination analysis was configured, using ArcGIS StreetMap Premium as the network data source. Census block centroids with population greater than zero were used as the Origins, and grocery store locations were used as the Destinations. A cutoff of 10 minutes was used with the Walk Time option. Only one restriction was applied to the street network: Walkable, which means Interstates and other non-walkable street segments were treated appropriately. You see the results in the map: wherever freeway overpasses and underpasses are present near a grocery store, the walkable area extends across/through that pass, but not along the freeway. A cutoff of 10 minutes was used with the Drive Time option. The default restrictions were applied to the street network, which means a typical vehicle"s access to all types of roads was factored in. The results for each analysis were captured in the Lines layer, which shows which origins are within the cutoff of each destination over the street network, given the assumptions about that network (walking, or driving a vehicle). The Lines layer was then summarized by census block ID to capture the Maximum value of the Destination_Rank field. A census block within 10 minutes of 3 stores would have 3 records in the Lines layer, but only one value in the summarized table, with a MAX_Destination_Rank field value of 3. This is the number of stores accessible to that census block in the 10 minutes measured, for walking and driving. These data were joined to the block centroids layer and given unique names. At this point, all blocks with zero population or null values in the MAX_Destination_Rank fields were given a store count of 0, to help the next step. Walkable and Drivable areas are calculated into a raster layer, using Nearest Neighbor geoprocessing tool on the count of stores within a 10 minute walk, and a count of stores within a ten minute drive, respectively. This tool uses a 200 meter grid and interpolates the values between each census block. A census tracts layer containing all water polygons "erased" from the census tract boundaries was used as an environment setting, to help constrain interpolation into/across bodies of water. The same layer use used to "shoreline" the Nearest Neighbor results, to eliminate any interpolation into the ocean or Great Lakes. This helped but was not perfect. Notes and LimitationsThe map provides a baseline for discussing access to grocery stores in a city. It does not presume local population has the desire or means to walk or drive to obtain groceries. It does not take elevation gain or loss into account. It does not factor time of day nor weather, seasons, or other variables that affect a person"s commute choices. Walking and driving are just two ways people get to a grocery store. Some people ride a bike, others take public transit, have groceries delivered, or rely on a friend with a vehicle. Thank you to Melinda Morang on the Network Analyst team for guidance and suggestions at key moments along the way; to Emily Meriam for reviewing the previous version of this map and creating new color palettes and marker symbols specific to this project. Additional ReadingThe methods by which access to food is measured and reported have improved in the past decade or so, as has the uses of such measurements. Some relevant papers and articles are provided below as a starting point. Measuring Food Insecurity Using the Food Abundance Index: Implications for Economic, Health and Social Well-BeingHow to Identify Food Deserts: Measuring Physical and Economic Access to Supermarkets in King County, WashingtonAccess to Affordable and Nutritious Food: Measuring and Understanding Food Deserts and Their ConsequencesDifferent Measures of Food Access Inform Different SolutionsThe time cost of access to food – Distance to the grocery store as measured in minutes

Desert Locust Monitoring, Forecasting and Assessment in Africa and Southwest Asia. Covering Ethiopia, Kenya, Somalia, Pakistan, Yemen, India, Nepal and Afghanistan. A research team RSCROP led by Prof. Huang Wenjiang and Prof. Dong Yingying of the ‘Digital Earth Science Platform’ Project in CASEarth has tracked the migration path of the Desert Locust and make a detailed analysis on the possibility of the Desert Locust invasion of China. Integrated with multi-source Earth Observation data, e.g. meteorological data, field data, and remote sensing data (such as GF series in China, MODIS and Landsat series in US, Sentinel series in EU), and self-developed models and algorithms for Desert Locust monitoring and forecasting, the research team constructed the ‘Vegetation pests and diseases monitoring and forecasting system’, which could regularly release thematical maps and reports on Desert Locust. The Desert Locust has ravaged the Horn of Africa and Southwest Asia, posing serious threats on agricultural production and food security of the inflicted regions. The Food and Agriculture Organization of the United Nations（FAO）has issued a worldwide Desert Locust warning, calling for joint efforts from multiple countries in prevention and control of the pest to ensure food security and regional stability.

United States - Producer Price Index by Commodity: Processed Foods and Feeds: Ice Cream and Frozen Desserts (DISCONTINUED) was 294.93900 Index 1982=100 in August of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Processed Foods and Feeds: Ice Cream and Frozen Desserts (DISCONTINUED) reached a record high of 294.93900 in August of 2025 and a record low of 58.60000 in May of 1975. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Processed Foods and Feeds: Ice Cream and Frozen Desserts (DISCONTINUED) - last updated from the United States Federal Reserve on October of 2025.

A food desert is defined as having limited access to supermarkets, grocery stores or a source of healthy/affordable food. This indicator displays tracts having low food access at 1 mile for urban areas and 10 miles for rural areas. If the tract scores a 1, then there is low food access and if it scores a 0, then low food access is not identified. The Food Access Research Atlas, available from the USDA, offers valuable insights into food access indicators for low-income and other census tracts. Users can access various measures of supermarket accessibility and obtain data on food access for specific populations within census tracts. This interactive tool allows users to create maps showcasing food access indicators and compare data from different years, such as 2019 and previous measurements from 2015. Moreover, the atlas provides valuable census-tract-level data on food access, which can be downloaded for community planning and research purposes. To explore the Food Access Research Atlas and access its data,Visit: https://www.ers.usda.gov/data-products/food-access-research-atlas/download-the-data/

United States - Producer Price Index by Commodity: Processed Foods and Feeds: Wines, Dessert, Effervescent, and Wine Coolers was 131.31000 Index Dec 2011=100 in August of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Processed Foods and Feeds: Wines, Dessert, Effervescent, and Wine Coolers reached a record high of 132.95900 in March of 2025 and a record low of 100.00000 in January of 2012. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Processed Foods and Feeds: Wines, Dessert, Effervescent, and Wine Coolers - last updated from the United States Federal Reserve on October of 2025.

Desert Locust Monitoring, Forecasting and Assessment in Africa and Southwest Asia. Covering India. A research team RSCROP led by Prof. Huang Wenjiang and Prof. Dong Yingying of the ‘Digital Earth Science Platform’ Project in CASEarth has tracked the migration path of the Desert Locust and make a detailed analysis on the possibility of the Desert Locust invasion of China. Integrated with multi-source Earth Observation data, e.g. meteorological data, field data, and remote sensing data (such as GF series in China, MODIS and Landsat series in US, Sentinel series in EU), and self-developed models and algorithms for Desert Locust monitoring and forecasting, the research team constructed the ‘Vegetation pests and diseases monitoring and forecasting system’, which could regularly release thematical maps and reports on Desert Locust. The Desert Locust has ravaged the Horn of Africa and Southwest Asia, posing serious threats on agricultural production and food security of the inflicted regions. The Food and Agriculture Organization of the United Nations（FAO）has issued a worldwide Desert Locust warning, calling for joint efforts from multiple countries in prevention and control of the pest to ensure food security and regional stability.

Map and data for the Food Base LA Food Systems Dashboard. This map contains 2020 Census Tracts for Los Angeles County, and a variety of other boundaries to support data analysis and exploration: the county itself, its 88 cities plus unincorporated cities, county statistical areas (CSA), county service planning areas (SPA), county supervisorial districts, LA Times neighborhoods, and City of Los Angeles Council Districts. Point data include L.A. County Department of Public Health Restaurant and Market Inventory and Inspection data (quarterly data for 2023-2025) and CalFresh (USDA SNAP) food retailer and restaurant meals locations. Datasets are time series when available, and organized by groups: Food Assistance and Benefits, Retail Food Outlets, Food Deserts, Resident Health, Resident Demographics, Neighborhood Characteristics, Green and Garden Spaces, and Schools.