The impact of Russia-Ukraine conflict on global food security

Global Food Security, Journal Year: 2022, Volume and Issue: 36, P. 100661 - 100661

Published: Dec. 9, 2022

Language: Английский

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Challenges and opportunities in remote sensing-based crop monitoring: a review

National Science Review, Journal Year: 2022, Volume and Issue: 10(4)

Published: Dec. 19, 2022

Abstract Building a more resilient food system for sustainable development and reducing uncertainty in global markets both require concurrent near-real-time reliable crop information decision making. Satellite-driven monitoring has become main method to derive at local, regional, scales by revealing the spatial temporal dimensions of growth status production. However, there is lack quantitative, objective, robust methods ensure reliability information, which reduces applicability leads uncertain undesirable consequences. In this paper, we review recent progress identify challenges opportunities future efforts. We find that satellite-derived metrics do not fully capture determinants production quantitatively interpret status; latter can be advanced integrating effective new onboard sensors. have identified ground data accessibility negative effects knowledge-based analyses are two essential issues reduce decisions on security. Crowdsourcing one solution overcome restrictions ground-truth accessibility. argue user participation complete process could improve information. Encouraging users obtain from multiple sources prevent unconscious biases. Finally, need avoid conflicts interest publishing publicly available

Language: Английский

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Environmental and human health at risk – Scenarios to achieve the Farm to Fork 50% pesticide reduction goals

Environment International, Journal Year: 2022, Volume and Issue: 165, P. 107296 - 107296

Published: May 11, 2022

The recently released Farm to Fork Strategy of the European Union sets, for first time, pesticide reduction goals at EU level: 50% in overall use and risk chemical pesticides a more hazardous pesticides. However, there is little guidance provided as how achieve these targets. In this study, we compiled characteristics all 230 EU-approved, synthetic, open-field active substances (AS) used herbicides, fungicides insecticides, explored potential seven Fork-inspired scenarios goals. were based on recommended AS application rates, type, soil persistence, presence candidate substitution list, hazard humans ecosystems. All have been found cause negative effects or ecosystems depending exposure levels. This despite incomplete profiles several AS. 'No data available' situations are often observed same endpoints specific organisms. results indicate that only severe restrictions, such allowing low-hazard substances, will result targeted reductions. Over half considered top however, actions depend still be defined EC priority areas action plans, also other recent related strategies. Broader scenario implications (on productivity, biodiversity economy) response farmers restrictions should those plans define effective actions. Our emphasize need re-evaluation approved their representative uses, call open access AS, crop region-specific refine assess

Language: Английский

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A review of regional and Global scale Land Use/Land Cover (LULC) mapping products generated from satellite remote sensing

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2023, Volume and Issue: 206, P. 311 - 334

Published: Nov. 28, 2023

Language: Английский

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Development of a 10-m resolution maize and soybean map over China: Matching satellite-based crop classification with sample-based area estimation

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 294, P. 113623 - 113623

Published: May 17, 2023

Language: Английский

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Quantifying war-induced crop losses in Ukraine in near real time to strengthen local and global food security

Food Policy, Journal Year: 2023, Volume and Issue: 115, P. 102418 - 102418

Published: Feb. 1, 2023

Language: Английский

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Application of precision agriculture technologies in Central Europe-review

Journal of Agriculture and Food Research, Journal Year: 2024, Volume and Issue: 15, P. 101048 - 101048

Published: Feb. 15, 2024

Precision agriculture (PA) relies on a large amount of precise data about given area and allows that to be used in accordance with agronomic practices. It offers farmers greater control over existing processes, from crop placement soil conditions chemical use. On the other hand, applying precision livestock solutions these expanding systems is way bring animals closer producers minimize waste costs. In Europe, has emerged as new help increase quantity quality agricultural production while using fewer inputs. The spatial temporal variability application PA implications site-specific are documented this article. objective review article provide an overview Central European countries (Poland, Czech Republic, Austria, Slovakia, Slovenia, Germany, Hungary) identified through systematic literature (SLR). analyses revealed rapid development automation agriculture, demand for skilled workers will continue technology open up areas well AgriTech startups future. Currently, there Germany Republic who leaders use technologies. However, requires further research more accurate information constantly evolving.

Language: Английский

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CROPGRIDS: a global geo-referenced dataset of 173 crops

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: April 22, 2024

Abstract CROPGRIDS is a comprehensive global geo-referenced dataset providing area information for 173 crops the year 2020, at resolution of 0.05° (about 5.6 km equator). It represents major update Monfreda et al . (2008) (hereafter MRF), most widely used geospatial previously available, covering 175 with reference 2000 10 spatial resolution. builds on originally provided in MRF and expands it using 27 selected published gridded datasets, subnational data 52 countries obtained from National Statistical Offices, 2020 national-level statistics FAOSTAT, more recent harvested crop (physical) areas regional, national, levels. The advance current state knowledge distribution crops, useful inputs modelling studies sustainability analyses relevant to national international processes.

Language: Английский

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A 30 m annual cropland dataset of China from 1986 to 2021

Earth system science data, Journal Year: 2024, Volume and Issue: 16(5), P. 2297 - 2316

Published: May 6, 2024

Abstract. Accurate, detailed, and up-to-date information on cropland extent is crucial for provisioning food security environmental sustainability. However, because of the complexity agricultural landscapes lack sufficient training samples, it remains challenging to monitor dynamics at high spatial temporal resolutions across large geographical extents, especially regions where land use changing dramatically. Here we developed a cost-effective annual mapping framework that integrated time-series Landsat satellite imagery, automated sample generation, as well machine learning change detection techniques. We implemented proposed scheme cloud computing platform Google Earth Engine generated novel dataset China's 30 m resolution (namely CACD). Results demonstrated our approach was capable tracking dynamic changes in different zones. The pixel-wise F1 scores maps CACD were 0.79 ± 0.02 0.81, respectively. Further cross-product comparisons, including accuracy assessment, correlations with statistics, details, highlighted precision robustness compared other datasets. According estimation, from 1986 2021, total area expanded by 300 km2 (1.79 %), which underwent an increase before 2002 but general decline between 2015, slight recovery afterward. Cropland expansion concentrated northwest while eastern, central, southern experienced substantial loss. In addition, observed 419 342 (17.57 %) croplands abandoned least once during study period. consistent, high-resolution data can support progress toward sustainable production various research applications. full archive freely available https://doi.org/10.5281/zenodo.7936885 (Tu et al., 2023a).

Language: Английский

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Crop Type Mapping from Optical and Radar Time Series Using Attention-Based Deep Learning

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(22), P. 4668 - 4668

Published: Nov. 19, 2021

Crop maps are key inputs for crop inventory production and yield estimation can inform the implementation of effective farm management practices. Producing these at detailed scales requires exhaustive field surveys that be laborious, time-consuming, expensive to replicate. With a growing archive remote sensing data, there enormous opportunities exploit dense satellite image time series (SITS), temporal sequences images over same area. Generally, type mapping relies on single-sensor is solved with help traditional learning algorithms such as random forests or support vector machines. Nowadays, deep techniques have brought significant improvements by leveraging information in both spatial dimensions, which relevant studies. The concurrent availability Sentinel-1 (synthetic aperture radar) Sentinel-2 (optical) data offers great opportunity utilize them jointly; however, optimizing their synergy has been understudied techniques. In this work, we analyze compare three fusion strategies (input, layer, decision levels) identify best strategy optimizes optical-radar classification performance. They applied recent architecture, notably, pixel-set encoder–temporal attention encoder (PSE-TAE) developed specifically object-based SITS based self-attention mechanisms. Experiments carried out Brittany, northwest France, series. Input layer-level competitively achieved overall F-score surpassing decision-level 2%. On per-class basis, increased accuracy dominant classes, whereas improves up 13% minority classes. Against baseline, multi-sensor identified types more accurately: example, input-level outperformed 3% 9% F-score, respectively. We also conducted experiments showed importance early under high cloud cover condition.

Language: Английский

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