Land Use and Land Cover Change Associated with Coffee Production in Amazonas, Peru

Land use and land cover change (LULC) driven by agricultural expansion has become a major environmental challenge in tropical regions, particularly in coffee-producing landscapes, where economic growth often conflicts with forest conservation. This study integrates multi-temporal land cover analysis and future scenario modeling to assess LULC dynamics associated with coffee expansion in the district of Ocumal, in the Amazona Peru. Land cover classes were identified using a Random Forest classification approach applied to Landsat imagery from 2000, 2010, and 2020 processed in Google Earth Engine (GEE), while future scenarios for 2030 and 2040 were simulated using the MOLUSCE plugin in QGIS 2.18. Cross-tabulation matrices and annual rates of change were calculated using IDRISI SELVA 17.0. The results show increases of 12.6% and 7.4% in coffee crop area during 2000–2010 and 2010–2020, respectively, alongside a significant reduction in forest and grassland cover (−5.06% and −2.10% during 2010–2020), mainly driven by agricultural expansion facilitated by transportation infrastructure and market accessibility. This study contributes to the international literature by providing empirical evidence from the Peruvian Amazon on the long-term impacts of coffee expansion on land use and land cover, supporting land-use planning and sustainable agriculture in tropical regions.

Authors

Institutions

Publication Details

Journal
Land
Published
2026-02-25
DOI
https://doi.org/10.3390/land15030368
Primary Topic
Coffee research and impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Land Use and Land Cover Change Associated with Coffee Production in Amazonas, Peru

Omer Cruz, Einstein Bravo Campos, Fredy Velayarce-Vallejos, Lenin Quiñones Huatangari et al.
Land
Coffee research and impacts
article

Land Use and Land Cover Change Associated with Coffee Production in Amazonas, Peru

Omer Cruz, Einstein Bravo Campos, Fredy Velayarce-Vallejos, Lenin Quiñones Huatangari, Cleyton Francisco Chavez Cruz, Einstein Sánchez Bardales, River Chávez Santos
article en

Abstract

Land use and land cover change (LULC) driven by agricultural expansion has become a major environmental challenge in tropical regions, particularly in coffee-producing landscapes, where economic growth often conflicts with forest conservation. This study integrates multi-temporal land cover analysis and future scenario modeling to assess LULC dynamics associated with coffee expansion in the district of Ocumal, in the Amazona Peru. Land cover classes were identified using a Random Forest classification approach applied to Landsat imagery from 2000, 2010, and 2020 processed in Google Earth Engine (GEE), while future scenarios for 2030 and 2040 were simulated using the MOLUSCE plugin in QGIS 2.18. Cross-tabulation matrices and annual rates of change were calculated using IDRISI SELVA 17.0. The results show increases of 12.6% and 7.4% in coffee crop area during 2000–2010 and 2010–2020, respectively, alongside a significant reduction in forest and grassland cover (−5.06% and −2.10% during 2010–2020), mainly driven by agricultural expansion facilitated by transportation infrastructure and market accessibility. This study contributes to the international literature by providing empirical evidence from the Peruvian Amazon on the long-term impacts of coffee expansion on land use and land cover, supporting land-use planning and sustainable agriculture in tropical regions.

LandVol. 15(3)
National University Toribio Rodríguez de Mendoza (PE)
Zero hunger
Openalex Percentile: Top 41%
Coffee research and impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.