Aug 2026· Statistical Journal of the IAOS· 0 citations· 10 references
Abstract
The World Programme for the Census of Agriculture 2030 (WCA 2030) marks a paradigm shift in how countries design and implement agricultural censuses. It explicitly encourages the integration of Earth Observation (EO) and geospatial data to enhance efficiency, accuracy, and comparability. This paper presents a methodological synthesis of how EO can be embedded across the census cycle—from the preparation of geospatial reference layers and georeferencing of holdings to validation and area estimation. Drawing on lessons from FAO's EOSTAT programme, the UN Handbook of Remote Sensing for Agricultural Statistics, and innovative examples such as Brazilian Institute of Geography and Statistics's (IBGE) AI-based parcel delineation in Brazil, this article illustrates practical pathways for operationalization. The analysis emphasizes institutional readiness, quality assurance, and emerging AI-based approaches that enable scalable, cost-effective census operations aligned with WCA 2030 standards.
This systematic review synthesizes literature published in 2019–2026, identified through Scopus, Web of Science, and supplementary searches, to examine applications, multimodal data integration, and decision support in precision agriculture.
César de Oliveira Ferreira Silva· AI and Precision Agriculture· 0 citations
Geospatial analyses are becoming fundamentally important on a global scale for the sake of sustainability. The overall objective of this research is to analyze geospatial data, using images from Landsat 2, 5, 7, and 8 satellites from 1975 to 2020, based on changes in land use, and from Sentinel-3B OLCI (Ocean Land Colo...
Isadora Cezar Caino, Julia Scopel, Julia Almeida et al.· Revista de Arquitetura IMED· 0 citations
Geomorphological studies conducted by the Geological Survey of Brazil (SGB-CPRM) have evolved since the 1970s, with significant methodological advances over the past two decades in institutional projects. In this context, multiscale mapping of landform patterns has become established as a fundamental approach to terrai...
Maria Adelaide Maia, M. Dantas, A. Lacerda et al.· Journal of the Geological Su...· 0 citations
This study presents an AI-assisted geospatial framework for farmland suitability assessment in the Omo sub-basin of Ethiopia, within the Sustainable Land Management Program (SLMP). Leveraging Google Earth Engine (GEE), twelve key biophysical variables were extracted from multi-temporal satellite data and processed usin...
Kueshi Sémanou Dahan, G. Gebre, Mohammedawel Jeneto Mohammed et al.· Journal of Environmental Man...· 0 citations
In the context of growing international recognition of geospatial information as a strategic driver of evidence-based decision-making, digital transformation, and sustainable development, robust assessment frameworks are essential for guiding the development of National Spatial Data Infrastructures (NSDIs). This paper...
Alla Manga, A. Diaw, Johannes Van Geertsom et al.· ISPRS International Journal...· 1 citation
It is argued that future progress depends less on incremental accuracy gains than on reproducible multi-source workflows, explicit uncertainty, trustworthy and explainable geospatial artificial intelligence, privacy-preserving governance, interoperable standards and evaluation in the institutions that ultimately use th...
Yashvardhan Singh, Divya Singh, Sakshi Shukla et al.· Advances in Research· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
