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UID:pretalx-foss4g-2024-academic-track-3YCWGQ@talks.staging.osgeo.org
DTSTART;TZID=-03:20241204T140000
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DESCRIPTION:Tropical forests host half of Earth’s biodiversity (Dirzo & R
 aven\, 2003)\, 62% of global terrestrial vertebrate species (Pillay et al.
 \, 2022)\, and play a crucial role as a carbon sink (Mitchard\, 2018). Des
 pite their importance\, every year\, 3 to 4 million hectares of primary tr
 opical forests are lost\, mainly in Brazil\, Indonesia\, and the Democrati
 c Republic of Congo (DRC) (Hansen et al.\, 2013\; Seymour\, 2022)\, contri
 buting to 22% of total greenhouse gas (GHG) emissions worldwide along with
  agriculture\, forestry and other land use (AFOLU) (IPCC\, 2023).\n\nPreve
 nting deforestation requires understanding its root causes\, particularly 
 the capital availability to the farm sector. In many tropical countries\, 
 rural credit is available as loans at subsidized interest rates to improve
  agricultural production or support agricultural costs (Servo\, 2019). How
 ever\, these loans may be leading to more deforestation. Some studies have
  analyzed this issue on a municipal scale\, but few peer-reviewed studies 
 have linked rural credit to individual property-scale deforestation. Recen
 tly\, the NGO Greenpeace (Greenpeace\, 2024) and the Climate Policy Initia
 tive (Mourão et al.\, 2024) published two studies showing the relationshi
 p between rural credit and deforestation. Understanding this relationship 
 can improve public policies to prevent deforestation from happening even b
 efore it starts.\n\nMethods\nIn this study\, I used open data and FOSS4G t
 o quantify the amount of Rural Credit released to rural properties that co
 mmitted Deforestation. The datasets came from different open data sources.
  The Central Bank of Brazil provides data on rural credit on the SICOR Sys
 tem. The National Institute of Space Research (INPE) provides data on defo
 restation in the Terrabrasilis system. The Brazilian Forest Service provid
 ed data for each property's Rural Environmental Registry (CAR)\, providing
  their boundaries. The Brazilian Institute of Geography and Statistics (IB
 GE) provides data for administrative boundaries (state and municipality).\
 n\nUsing the Terra library in CRAN-R\,. I processed the data sets from thr
 ee states that contributed the most to deforestation: Rondônia\, Mato Gro
 sso\, and Pará. I used a Spatialite database and QGIS Geographic Informat
 ion System to check the results. The novelty here is that by using R scrip
 ts\, it was possible to rebuild the relational database from SICOR in a ge
 ospatial environment\, providing a reproducible environment. All steps are
  described below.\n\nFirst\, using R\, all the data needed for the analysi
 s was downloaded from their source and loaded into the R environment. The 
 second step\, still using R\, was to recreate the SICOR\, CAR\, and PRODES
  Deforestation tables and populate them into a Spatialite (SQLite) databas
 e. This step provides a valuable tool for monitoring by both environmental
  agencies and the banks that provide loans for rural credit.\n\nThe next s
 tep was to intersect the deforestation data with the CAR property boundari
 es\, calculating the amount of deforestation on each property using PRODES
  data between 2008 and 2023. Next\, the total number of loans between 2013
  and 2023 was identified for each property. All these steps were processed
  using the Terra library in R.\n\nResults\nIn 1992\, the Brazilian Parliam
 ent enacted Law 4\,829\, creating subsidies for rural credit\, known as Sa
 fra Plan. The interest rates of the Safra Plan have always been significan
 tly lower than those practiced in the market. In March 2019\, for example\
 , while the average interest rate on loans for non-rural purposes stood at
  31.6% per year\, rural credit was observed at 10.8% p.y. on market rates\
 , and even lower with controlled rates observing an average rate of 6.1% p
 .y.(Servo\, 2019) .\n\nThe results show that from 2013 to 2023\, more than
  BRL 17 billion was loaned to properties with some deforestation in these 
 three states (RO\, PA\, MT). Counting deforestation from August 2008 to Ju
 ly 2023\, 8197 km² is the total amount of clearing in properties that rec
 eived rural credit in those same three states\, representing 8.5% of all d
 eforestation for the period.
DTSTAMP:20260521T192710Z
LOCATION:Room I
SUMMARY:The relationship between rural credit and deforestation - George Po
 rto Ferreira
URL:https://talks.staging.osgeo.org/foss4g-2024-academic-track/talk/3YCWGQ/
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