Latest news with #GoogleEarthEngine
Agriland
08-06-2025
- Business
- Agriland
New data shows wheat could lose half its best land by 2100
The Food and Agriculture Organization of the United Nations (FAO) has upgraded its innovative geospatial app with a new indicator which has provided data showing that several major crops – including wheat and beans – could lose half their best land by 2100. Designed for policymakers, technicians, and project designers, the Adaptation, Biodiversity, and Carbon Mapping Tool (ABC-Map) app offers an initial screening of the climate-related risks, essential biodiversity indicators, and carbon reduction potential of a selected project. It is an open-source satellite imagery app, based on Google Earth Engine, with information from global datasets. Following its upgrade, ABC-Map now features a new indicator that provides information on the suitability of major crops in evolving climate scenarios to the end of the century. FAO senior natural resources (Climate Change) officer Martial Bernoux said the new information could help ensure our capacity to cope with climate change and its impacts on land in the long-term. 'Given the increasingly erratic weather and extreme events – including droughts, extreme heat, and floods – farmers, policymakers, and technicians need to know if the crops, investments, or projects they are considering will work or if they need to adjust and consider other crops or more adaptation measures instead,' Bernoux said. 'Our ABC-Map tool can now better assist them with these considerations, further reinforcing climate resilience.' Concerning data for wheat and other crops The new indicator, developed by FAO, incorporates data from a study by French fintech start-up Finres, commissioned by the International Fund for Agricultural Development (IFAD) and funded by the French Development Agency (AFD). The study – 'Have crops already reached peak suitability: assessing global climatic suitability decreases for crop cultivation' – uses a new method to assess crop suitability in varied climate scenarios. It concludes that five out of nine major staple and cash crops – including wheat, coffee, beans, cassava, and plantain – are already losing optimal growing conditions, and some could lose half their optimal suitable land by 2100. In particular, the study's researchers suggest that coffee production in some of the major coffee-growing regions could decline sharply by 2100. They say beans and wheat could experience significant losses, especially in regions such as North America and Europe. Maize and rice, however, could initially find more suitable areas for cultivation, the researchers suggest, but this situation could reverse by the end of the century under high-emission scenarios. How does it work? The ABC-Map geospatial app features indicators in three sections: adaptation, biodiversity, and carbon. This new indicator expands the scope of the adaptation section, which previously displayed only data on past trends in a given area, including past temperature and rainfall. Now, the new indicator also adds information on future trends. A user inputs a location, then selects a crop from 30 options, including coffee, maize, and wheat. The tool then displays the suitability of the selected crops for land in that area, for time periods stretching to 2100, providing a crop suitability score for two different climate emission scenarios. Also planned for this year, according to the FAO, is an indicator with information on livestock heat stress and another for crop water requirements, which would estimate expected rainfall and potential irrigation needs. Strengthening national capacity ABC-Map is one of the technical tools in the COP28 Agriculture, Food, and Climate National Action Toolkit, which aims to help governments develop and implement policy measures on climate action and agri-food system transformation. The app was launched last year during an expert panel on the Food and Agriculture for Sustainable Transformation (FAST) Partnership, at the Global Forum for Food and Agriculture in Berlin, Germany. The tool helps users better understand the synergies and trade-offs among the three pressing and interlinked challenges of climate change mitigation, adaptation, and countering biodiversity loss in the context of safeguarding agriculture and food security. It promotes holistic environmental actions in agriculture.
India Today
02-06-2025
- Climate
- India Today
Maps: Satellite data reveals extent of Assam floods
The flood situation in Assam's Brahmaputra valley remained severe on Monday, with water levels continuing to rise across several regions, according to officials. Satellite imagery and flood-mapping data analysed by India Today's OSINT team using Sentinel-1 SAR (Synthetic Aperture Radar) data revealed that large areas of land were submerged under the same methodology, the composite overview imagery showed extensive inundation across key districts in Assam, including Nalbari, Guwahati, Nagaon, Silchar, Golaghat and Kamrup. Isolated flood signatures were also detected across nearly 19-20 districts, including Dhemaji, Dibrugarh, Darrang, Biswanath, Tinsukia, Karbi Anglong, Karbi Anglong West, Kamrup, Hojai, Sonitpur, Charaideo, Sivasagar, Majuli and In Assam's Kamrup Metropolitan district, flooding was primarily observed along the floodplains of the Digaru river. Satellite imagery indicated severe inundation in key urban zones, particularly in the Garchuk and Boragaon localities of Guwahati. Blue shades represent flooding in Kamrup. A similar pattern emerged in the satellite imagery of Nagaon district, where floodwaters were concentrated along the floodplains of the Kapili river. Significant inundation was detected near Kaziranga National Park, as well as in the areas of Barhampur, Barafuti and Kampur Google Earth Engine (GEE), we processed Sentinel-1 SAR datasets to perform time-series analysis of flood dynamics. By comparing radar data from the pre-monsoon and monsoon periods, we identified changes in surface water coverage that allowed us to detect newly-flooded zones. The use of SAR data, which can penetrate cloud cover and heavy rain, allowed consistent monitoring even during peak weather conditions. This approach enabled clear visualization of flood extent across Assam's impacted this analysis, we utilised pre-flooding (April 16 to May 7) and intra-flooding (May 31 to June 1) remote sensing datasets to conduct a differential assessment of surface water extent. By analysing temporal variations in satellite imagery, we were able to highlight flood-affected zones with enhanced spatial India Meteorological Department (IMD) has issued a red alert for Assam and Meghalaya, warning the states of heavy to very heavy rainfall in the coming week. Similar alerts have been issued for Nagaland, Mizoram, Manipur and Tripura, which are also expected to receive intense Watch IN THIS STORY#Assam
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Business Standard
29-04-2025
- Business Standard
MP first state to launch AI-based real-time forest alert system: Officials
Madhya Pradesh has become the first state to implement an AI-based real-time alert system on a pilot basis for active forest management using satellite images, mobile feedback, and machine learning, an official said on Tuesday. The Artificial Intelligence system will enable the forest department to detect land encroachment, land use change, and forest degradation. "Madhya Pradesh has become the first state in the country to implement an AI-based real-time forest alert system. This historic step has been taken towards active forest management in the state. This system works with the help of satellite images, mobile feedback and machine learning," the official said. This system is being implemented as a pilot project in five sensitive forest divisions including Shivpuri, Guna, Vidisha, Burhanpur and Khandwa, which have reported several encroachment and tree felling incidents. It will be implemented at the state level, the official added. He said that based on Google Earth Engine, the AI alert system analyses multi-temporal satellite data and identifies land use changes using a custom AI model. Every possible change is sent to the field staff through a mobile app so that they can confirm it by visiting the site. Guna Divisional Forest Officer (DFO) Akshay Rathore, who conceptualised the AI system for forest management, said this is the first time the forest department has combined satellite, AI, and field feedback in a continuous cycle, which improves itself over time. The system is implemented under the leadership and institutional support of the Head of Forest Force (HoFF), Aseem Shrivastava, and Additional Principal Chief Forest Conservator of IT B.S. Annigeri. "This system empowers forest staff to monitor and take immediate action. Alert generation and feedback process includes initial alert generation using Google Earth Engine to compare satellite images of three dates, identify changes in crops, wasteland, construction etc," Rathore said. An official stated that each alert includes over 20 features, such as polygon alerts triggered by notable pixel changes, field verification for mobile app alerts, and uploads by field staff, including GPS-tagged photos, voice notes, and comments. It also involves data enrichment with indexes like NDVI, SAVI, EVI, and SAR attributes. The new process involves live monitoring on the Divisional Forest Officer's dashboard, showing real-time alerts categorised by beat and field posts, with filters for date, density, and area. Alerts will be sent to a mobile app for field staff to take on-site action. The app will enable submission of survey data, including images, GPS, and voice recordings, and incorporate features like geo-fencing and distance measurement, the official said.
