GSCI rose to 547.05 Index Points on September 9, 2025, up 0.11% from the previous day. Over the past month, GSCI's price has risen 1.77%, and is up 8.49% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. GSCI Commodity Index - values, historical data, forecasts and news - updated on September of 2025.

Graph and download economic data for Global Price Index of All Commodities (PALLFNFINDEXQ) from Q1 2003 to Q2 2025 about World, commodities, price index, indexes, and price.

Gold rose to 3,654.27 USD/t.oz on September 10, 2025, up 0.75% from the previous day. Over the past month, Gold's price has risen 9.31%, and is up 45.48% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on September of 2025.

Crude Oil rose to 63.22 USD/Bbl on September 10, 2025, up 0.95% from the previous day. Over the past month, Crude Oil's price has fallen 1.15%, and is down 6.07% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on September of 2025.

CRB Index rose to 371.77 Index Points on September 9, 2025, up 0.26% from the previous day. Over the past month, CRB Index's price has risen 1.84%, and is up 18.09% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on September of 2025.

Graph and download economic data for Producer Price Index by Commodity: All Commodities (PPIACO) from Jan 1913 to Aug 2025 about commodities, PPI, inflation, price index, indexes, price, and USA.

Between January 1971 and May 2025, gold had average annual returns of **** percent, which was only slightly more than the return of commodities, with an annual average of around eight percent. The annual return of gold was over ** percent in 2024. What is the total global demand for gold? The global demand for gold remains robust owing to its historical importance, financial stability, and cultural appeal. During economic uncertainty, investors look for a safe haven, while emerging markets fuel jewelry demand. A distinct contrast transpired during COVID-19, when the global demand for gold experienced a sharp decline in 2020 owing to a reduction in consumer spending. However, the subsequent years saw an increase in demand for the precious metal. How much gold is produced worldwide? The production of gold depends mainly on geological formations, market demand, and the cost of production. These factors have a significant impact on the discovery, extraction, and economic viability of gold mining operations worldwide. In 2024, the worldwide production of gold was expected to reach *** million ounces, and it is anticipated that the rate of growth will increase as exploration technologies improve, gold prices rise, and mining practices improve.

This dataset contains detailed records of India’s principal commodity-wise exports to various countries from 2017–18 to 2022–23 (skipping 2020–21 due to COVID-related data gaps). The data is structured annually and provides insights into:

Exported commodity names Destination countries Export quantity Export value (in USD million) Measurement units

These records are sourced from https://www.data.gov.in/ and are valuable for analysts, researchers, and policymakers studying international trade trends, market demand, and sector-wise export performance.

📁 Files Included File Name Year Format Principal_Commodity_wise_export_201718.csv 2017–18 CSV Principal_Commodity_wise_export_201819.csv 2018–19 CSV Principal_Commodity_wise_export_201920.csv 2019–20 CSV Principal_Commodity_wise_export_202122.csv 2021–22 CSV Principal_Commodity_wise_export_202223.csv 2022–23 CSV

📌 Columns Each file includes the following columns: COMMODITY – Name of the exported product COUNTRY – Country to which the product was exported UNIT – Unit of measurement (e.g., KGS, NOS, LITRES) QUANTITY – Total exported quantity VALUE (US$ Million) – Export value in USD millions

💡 Use Cases Time-series analysis of export performance Identifying high-value export commodities Understanding trade relationships with countries Policy and strategy development for boosting exports Comparative analysis across years and regions

📊 Sample Questions You Can Explore What are the top 10 exported commodities from India over the last 5 years? How has India's export value to the USA evolved since 2017? Are there any emerging markets for Indian goods? What commodities saw a decline in exports after COVID-19?

The price of gold per troy ounce increased considerably between 1990 and 2025, despite some fluctuations. A troy ounce is the international common unit of weight used for precious metals and is approximately **** grams. At the end of 2024, a troy ounce of gold cost ******* U.S. dollars. As of * June 2025, it increased considerably to ******** U.S. dollars. Price of – additional information In 2000, the price of gold was at its lowest since 1990, with a troy ounce of gold costing ***** U.S. dollars in that year. Since then, gold prices have been rising and after the economic crisis of 2008, the price of gold rose at higher rates than ever before as the market began to see gold as an increasingly good investment. History has shown, gold is seen as a good investment in times of uncertainty because it can or is thought to function as a good store of value against a declining currency as well as providing protection against inflation. However, unlike other commodities, once gold is mined it does not get used up like other commodities (for example, such as gasoline). So while gold may be a good investment at times, the supply demand argument does not apply to gold. Nonetheless, the demand for gold has been mostly consistent.

Silver rose to 41.05 USD/t.oz on September 10, 2025, up 0.41% from the previous day. Over the past month, Silver's price has risen 9.11%, and is up 43.16% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Silver - values, historical data, forecasts and news - updated on September of 2025.

Copper fell to 4.50 USD/Lbs on September 9, 2025, down 0.02% from the previous day. Over the past month, Copper's price has risen 1.40%, and is up 11.18% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Copper - values, historical data, forecasts and news - updated on September of 2025.

In 2025, the price of platinum is forecast to hover around ***** U.S. dollars per troy ounce. Meanwhile, the cost of per troy ounce of gold is expected to amount to ***** U.S. dollars. Precious metals Precious metals are counted among the most valuable commodities worldwide. The most well known such metals are gold, silver and the platinum group metals. A precious metal can be used as an industrial commodity or as an investment. The major areas of application include the following sectors: technology, car-making, industrial manufacturing and jewelry making. Furthermore, gold and silver are used as coinage metals, and gold reserves are held by the central banks of many countries worldwide in order to store value or for use as a redemption medium. The idea behind this procedure is that gold reserves will help secure and stabilize the countries’ respective currencies. At ***** tons, the United States is the country with the most extensive stock of gold. It is kept in an underground vault at the New York Federal Reserve Bank. Russia, the United States, Canada, South Africa and China are the main producers of precious metals. Silver is the most abundant of the metals, followed by gold and palladium. Barrick Gold is the world’s largest gold mining company. The Toronto-based firm produced some **** million ounces of gold in 2020. The leading silver producers include Mexico-based Fresnillo, Poland’s KGHM Polska Miedž and the mining giant Glencore. Anglo Platinum and Impala are the key mining companies to produce platinum group metals. In 2023, Silver prices are expected to settle at around **** U.S. dollars per troy ounce. It is expected to remain the precious metal with the lowest value per ounce. The price of gold is forecast to drop to around ***** U.S. dollars per ounce, making it the most expensive precious metal in 2023.

Aluminum fell to 2,620.15 USD/T on September 10, 2025, down 0.35% from the previous day. Over the past month, Aluminum's price has risen 1.38%, and is up 10.53% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Aluminum - values, historical data, forecasts and news - updated on September of 2025.

Overview \r The March edition of Agricultural commodities contains ABARES' latest outlook for Australia's key agricultural commodities to 2021-22. \r The outlook will be an important focal point at the conference and underpin many presentations delivered by ABARES speakers at the conference. \r The report provides updated commodity forecasts, as well as articles on the EU sheep meat industry; farm performance of broadacre and dairy farms; productivity in Australia's broadacre and dairy industries; and disaggregating farm performance by size. \r \r Key Issues \r Commodity forecasts \r • The gross value of farm production is forecast to increase by 8.3 per cent to a record $63.8 billion in 2016-17 before easing by 3.9 per cent to a forecast $61.3 billion in 2017-18. Despite the forecast decline, the gross value of farm production in 2017-18 would be 17.3 per cent higher than the average of $52.3 billion over the five years to 2015-16 in nominal terms. \r • The gross value of livestock production is forecast to increase by around 4.4 per cent to $31.2 billion in 2017-18, following a forecast decrease of 2.6 per cent in 2016-17. If this forecast is realised, the gross value of livestock production in 2017-18 would be around 28 per cent higher than the average of $24.4 billion over the five years to 2015-16 in nominal terms. \r • The gross value of crop production is forecast to decrease by 11.3 per cent to $30 billion in 2017-18, after a forecast increase of 20.2 per cent in 2016-17. The decrease follows record production of wheat and barley in 2016-17, which resulted from favourable seasonal conditions during winter and spring. If this forecast is realised, the gross value of crop production in 2017-18 would be around 8 per cent higher than the average of $27.9 billion over the five years to 2015-16 in nominal terms. \r • In 2021-22 the gross value of farm production is projected to be around $59.6 billion (in 2016-17 dollars), 8.6 per cent higher than the average of $54.9 billion over the five years to 2015-16 (also in 2016-17 dollars). In 2021-22 the gross value of crop production is projected to be around $29.0 billion and the gross value of livestock production is projected to be around $30.6 billion (in 2016-17 dollars). \r • Export earnings from farm commodities are forecast to be around $48.7 billion in 2017-18, higher than the forecast $47.7 billion in 2016-17. \r • The agricultural commodities for which export earnings are forecast to rise in 2017-18 are beef and veal (up 1 per cent), wool (10 per cent), dairy products (11 per cent), sugar (10 per cent), cotton (35 per cent), wine (5 per cent), lamb (3 per cent), live feeder/slaughter cattle (4 per cent), rock lobster (6 per cent) and mutton (1 per cent). \r • Forecast increases in 2017-18 are expected to be partly offset by expected declines in export earnings for wheat (down 9 per cent), coarse grains (11 per cent), canola (6 per cent) and chickpeas (42 per cent). \r • In Australian dollar terms, export prices of wool, dairy products, sugar, wine, lamb, barley, canola, rock lobster and mutton are forecast to increase in 2017-18. Export prices for cotton and chickpeas are forecast to fall. Prices for beef and veal, wheat and live feeder/slaughter cattle are forecast to remain around the same as in 2016-17. \r • In 2021-22 the value of farm exports is projected to be around $46.6 billion (in 2016-17 dollars), 8 per cent higher than the average of $43.1 billion over the five years to 2015-16 in real terms. \r • The value of crop exports is projected to be $24.9 billion (in 2016-17 dollars) in 2021-22, 7 per cent higher than the average of $23.2 billion over the five years to 2015-16 in real terms. The value of livestock exports is projected to be $21.8 billion (in 2016-17 dollars) in 2021-22, 10 per cent higher than the average of $19.8 billion over the five years to 2015-16 in real terms. \r • Export earnings for fisheries products are forecast to increase by 2.3 per cent in 2017-18 to $1.5 billion, after decreasing by a forecast 3.4 per cent in 2016-17. \r \r Economic assumptions underlying this set of commodity forecasts \r \r In preparing this set of agricultural commodity forecasts: • World economic growth is assumed to be 3.3 per cent in 2017 and 3.4 per cent in 2018. Growth is expected to rise further to around 3.5 per cent in 2019 before declining to 3.4 per cent in 2021 and 3.3 per cent in 2022. \r • Economic growth in Australia is assumed to average 2.8 per cent in 2017-18. Over the medium term to 2021-22, economic growth is assumed to average around 3 per cent. \r • The Australian dollar is assumed to average US73 cents in 2017-18, slightly lower than the forecast average of US75 cents in 2016-17. It is assumed to appreciate slightly over the medium term, reaching US74 cents towards 2021-22. \r \r Articles on agricultural issues \r The EU sheep meat industry \r • The European Union is one of the world's largest consumers of sheep meat. Imports are controlled by import quotas and prohibitive out-of-quota tariffs. \r • Australia is the second largest exporter to the European Union, behind New Zealand, although its allocated quota is just 8 per cent that of New Zealand's. \r • As a high value market for sheep meat, expanding sheep meat exports to the European Union would benefit the Australian industry. However, until the trade outcomes of Brexit are known, opportunities for Australian sheep meat exporters are uncertain. \r \r Farm performance: broadacre and dairy farms, 2014-15 to 2016-17 \r • In 2016-17 farm cash income for Australian broadacre farms is projected to average $216,000 a farm, the highest recorded in the past 20 years. \r • Record broadacre farm cash incomes this year are the result of near record winter grain production in most regions and good prices for beef cattle, sheep, lamb and wool. \r • Average farm cash income is projected to increase for broadacre farms in all states except Tasmania in 2016-17. \r • Farm cash income for dairy farms is projected to decline by 17 per cent nationally to an average of $105,000 a farm in 2016-17, reflecting lower average farmgate milk prices and reduced milk production. \r \r Productivity in Australia's broadacre and dairy industries \r • From 1977-78 to 2014-15, productivity in the broadacre industries averaged 1.1 per cent a year as a result of declining input use (down 1 per cent a year) and modest output growth (up 0.1 per cent a year). \r • In the dairy industry, productivity growth averaged 1.5 per cent a year between 1978-79 and 2014-15. This reflected average annual growth of 1.3 per cent in output and an average annual decline of 0.2 per cent in input use. \r \r Disaggregating farm performance by size \r • The largest 10 per cent of broadacre farms produced 46 per cent of total output, while the smallest 50 per cent of farms produced 12 per cent of total output. \r • The average rate of return, including capital appreciation, generated by the largest 10 per cent of broadacre farms was 8.2 per cent, while the smallest 10 per cent generated average returns of -2.8 per cent. \r • The largest 10 per cent of broadacre farms had the lowest average equity ratio of all farms (79 per cent), while the smallest 10 per cent of farms had the highest average equity ratio (97 per cent). \r

Background

Human-induced land use change (LUC), driven by activities such as forestry, logging, and the production of agricultural commodities (e.g. fruits, nuts, and meat) significantly impacts the Global Commons, encompassing the climate system, ice sheets, land biosphere, oceans, and the ozone layer. The convertion of natural forests into areas dedicated to these activities lead to disrupted ecosystems (Foley et al. 2005), severely degraded biodiversity (Newbold et al. 2015), and the release of substantial amounts of greenhouse gases (GHGs) into the atmosphere (Hong et al. 2021), further exacerbating climate change and ocean acidification (Doney et al. 2009). The expansion of the agricultural frontier is identified as the predominant direct cause of deforestation globally, with other industries like timber and mining also playing significant roles (Curtis et al. 2018). To achieve global climate targets, forestry, and other land use GHG emissions must decrease along a nonlinear trajectory and reach carbon neutrality by 2050 (Rockström et al. 2017). However, to successfully address this road map, improving our understanding of deforestation drivers is urgently needed.

Summary

This dataset is the result of data processing performed to estimate the extent to which commodities and other agricultural products have replaced forests, while mapping the CO2 emission impact making use of the best available spatially explicit data. Results are reported globally for 52 products at national level, as well as agroecological and thermal zones (FAO & IIASA) and a 50km cell vector grid.

In order to detect spatially-explicit deforestation drivers, the current extent of commodities and agricultural products was overlapped with global annual tree cover loss in the 10-year period from 2014 to 2023. Carbon stocks in the deforested areas were then assumed to have been emmited into the atmosphere. Recent, detailed crop and pasture maps for relevant commodities were used whenever available, and coarser resolution datasets were used as supplements when needed. Operations were performed in Google Earth Engine.

Datasets used

Forest and biomass carbon distribution

The Global Forest Change dataset (Hansen et al., 2013) is used to estimate deforestation between 2014 and 2023. This tree cover loss dataset measures the first instance of complete removal of tree cover canopy at a 30-meter resolution for all woody vegetation over 5 meters in height.

The WCMC Above and Below Ground Biomass Carbon Density (Soto-Navarro et al., 2020), for reference year 2010 at 300m pixel, is overlapped with resulting deforested areas pixels to dermine the biomass carbon present in the areas before deforestation.

Generalized deforestation drivers

Tree cover loss by dominant driver (Curtis et al., 2022) in 2023 is used to determine wide categories of deforestation drivers (commodities, shifting agriculture, forestry, wildfire and urbanization). Pixels indicating deforestation in the Global Forest Change dataset (Hansen et al., 2013) that overlap the commodities and shifting agriculture pixels from this dataset (Curtis et al., 2022) have their drivers further detailed with the data sources listed in the below.

EarthStat pasture areas layer (Ramankutty et al., 2008) is used to identify areas for which specific livestock categories are to be defined. The project provides pasture areas for reference year 2000 at ~10km resolution.

Detailed deforestation drivers

The Group on Earth Observations Global Agricultural Monitoring (GEOGLAM) commodity distibution layer (Becker-Reshef et al., 2023) is used to identify specific commodities (winter wheat, spring wheat, maize, rice and soybean) to deforestation pixels pertaining to the "commodities" class. The ressource provides commodity distribution mapping at 5km pixel resolution. Values are provided as percentage of pixel area occupied by given crop.

The Spatial Production Allocation Model (SPAM) physical area layer (You et al., 2014) for reference year 2020 is used to detail drivers pertaining to the "shifting agriculture" class. The dataset covers 46 crops and crop groups at ~9km pixel resolution. Values are provided as percentage of pixel area occupied by given crop or crop group.

The Gridded Livestock of the World (GLW3) (Gilbert et al., 2022) is used to determine which species (cattle, goat, sheep or horse) of livestock is raised in areas identified as pasture in the EarthStat layer and pertaining to the "commodities" class. The project provides livestock distribution for reference year 2015 at ~9km resolution. Values are provided as number of individuals located within the pixel. Values were converted into percentage of pixel area covered by grazing field for given species based on species density thresholds.

Data processing

Most of data processing takes place in Google Earth Engine, with scripts redacted in javascript. In summary, two strategies were implemented:

Proportional driver distribution strategy: When deforestation pixels (Hansen et al., 2013) overlapped with pixels from at least one of the detailed deforestation drivers data sources, the driver describe in the latter were associated with that deforested area. Whenever more than one of these data sources had non-null pixels overlapping the area, a proportional distribution was assumed (i.e. if SPAM indicated 100% of the area to be covered by cowpea crops, GEOGLAM 100% by maize, and GLW3 100% by cattle grazing fields, the pixel is assumed to have 33.3% of its deforested area associated with each of these drivers).

Main driver strategy: When deforestation pixels did not overlap with any non-null pixels from any of the detailed drivers sources, the pixel is assumed to have the entirety of its deforested area associated with one single main driver resulting from a crop-livestock mosaic. The mosaic is created by taking the highest value from each of the crop or livestock distribution rasters, and then assigning the raster category to be the new pixel value, ultimately creating a category raster layer containing the main crop, crop group or livestock species occupying that pixel area. Null or zero values in this mosaic are filled-in by nearest neighbour analysis, to a limit of 20 pixels expansion. This was enough to ensure that all deforestation pixels had at least one detailed driver with which it could be associated. The logic behind this operation resides in the fact that the deforestation layer (Hansen et al., 2013) has a larger temporal coverage (with the more recent data point being the reference year 2023), while the detailed driver layers can be as old as reference year 2015. This means we're assuming the main deforestation drivers continued to expand their limits to neighbouring areas during the years for which no data is available.

Resulting rasters from both strategies are put together and a zonal statistics operation is performed in order to populate the vector grid cells.

Files

This repository contains the following files:

deforested_area_by_LUC_driver_2014_2023.CSV contains the deforested area (hectares) and the corresponding driver in each grid cell (idenfied by the id field) in each year, in CSV text format.

carbon_emissions_by_LUC_driver_2014_2023.CSV contains the carbon emitted (Mg CO2 eq.) and the corresponding driver in each grid cell (idenfied by the id field) in each year, in CSV text format.

spatial_grid.gpkg contains the raw 50km cell grid, with identification of country (iso3 and name fields), region, and FAO agroecological zone (zone field) and thermal zone (thermal field), in Geopackage format. In order to visualize the data in a map, the user will need to join one of the csv files to this geopackage file by basing the join on the 'id' field.

summary_showcase.png is an image showcasing maps created using the database, as well as a diagram showing the datasets used to create the final dataset.

How to cite

Iablonovski, G.; Berthet, E. C.; Roberts, S. (2024). Yearly CO2 emissions from anthropogenic land use change by main driver (2014-2023) [Data set]. Zenodo. https://zenodo.org/doi/10.5281/zenodo.13308514

Authors and contact

Authors: Guilherme Iablonovski*, Etienne Charles Berthet, Sophie Roberts

*Corresponding author: Guilherme Iablonovski (guilherme.iablonovski@unsdsn.org)

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Platinum rose to 1,378.80 USD/t.oz on September 10, 2025, up 0.48% from the previous day. Over the past month, Platinum's price has risen 3.57%, and is up 44.23% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Platinum - values, historical data, forecasts and news - updated on September of 2025.

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This statistic depicts the average annual prices for copper from 2014 through 2026*. In 2024, the average price for copper stood at 9,142 nominal U.S. dollars per metric ton.