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UID:pretalx-foss4g-2024-academic-track-CUVPXC@talks.staging.osgeo.org
DTSTART;TZID=-03:20241204T150000
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DESCRIPTION:Most historical sources\, available in multiple formats (e.g.\,
  tabular and analog data)\, contain valuable geographic information. This 
 data can be transformed to generate both quantitative and qualitative insi
 ghts\, enabling the creation of digital maps and unlocking significant pot
 ential for scientific analysis. However\, the use of historical data prese
 nts several challenges: 1. Sources need to be digitized\; 2. Collections a
 re often spread across multiple archives\; 3. Metadata is often unavailabl
 e\; 4. Standardizing diverse sources and quantitatively reconstructing dat
 a from various periods is difficult\; 5. The reliability of historical dat
 a can be uncertain\; 6. There is limited spatial resolution\; and 7. Inacc
 uracies and text legibility issues are common. These challenges underscore
  the need for novel methodologies aimed at enhancing the quality and quant
 ity of such sources. This paper presents the findings of the exploratory p
 roject AgroecoDecipher (2022.09372.PTDC) dedicated to extracting a compreh
 ensive database from historical textual records and analogue map files to 
 trace agroecological patterns. Employing an exploratory methodology ground
 ed in artificial intelligence (AI) and Geographic Information Systems (GIS
 )\, the projected solutions include the establish-ment of routines based o
 n AI tools that combines GIS\, machine learning (ML)\, and Large Language 
 Models (LLMs). Approxi-mately 271 survey books from the 1950s were digitiz
 ed at the municipal level\, with a total sheet count exceeding 42\,000. Ad
 di-tionally\, more than 100 analogue maps were digitized\, processed\, and
  vectorized\, resulting in a detailed geodatabase map ar-chive. The result
 s are promising and demonstrate that the integration of AI and geospatial 
 tools has proven essential in trans-forming raw historical data.
DTSTAMP:20260513T160921Z
LOCATION:Room II
SUMMARY:The Use of GeoAI Techniques for Gathering\, Storing\, and Analyzing
  Historical Agroecological Data - Cláudia M. Viana
URL:https://talks.staging.osgeo.org/foss4g-2024-academic-track/talk/CUVPXC/
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