Gustavo Larrea‐Gallegos
Biographic Data
| ID | 8952555 |
|---|---|
| NAME | Gustavo Larrea‐Gallegos |
| GIVEN NAMES | Gustavo |
| FAMILY NAME | Larrea‐Gallegos |
| SIGNATURE | GALLEGOS G L |
| AFFILIATIONS | Peruvian LCA Network, Department of Engineering Pontificia Universidad Católica del Perú Lima Peru |
| ORCID | 0000-0002-6283-7039 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Exploring machine learning techniques to predict deforestation to enhance the decision‐making of road construction projects
Land use changes (LUCs), which are defined as the modification in the use of land due to anthropogenic activities, are important sources of GHG emissions. In this context, understanding future trends of LUCs, such as deforestation, in a spatial manner is relevant. The main objective of this study is to generate a deforestation prediction model for a given period of time (i.e., 2002–2017 and 2010–2017) to estimate the potential carbon emissions as…
Applying the Technology Choice Model in Consequential Life Cycle Assessment
Demand for grapes to produce pisco in southern‐coastal Peru is expected to double by 2030. However, the appellation of this beverage confines the production and limits the space for agricultural expansion, leading to a situation in which potential competition for resources with established constraints is foreseen. Hence, the objective of this study is to understand the environmental impacts, focused on climate change and water consumption, linked…
No prominent works on this page.
Applying the Technology Choice Model in Consequential Life Cycle Assessment
Demand for grapes to produce pisco in southern‐coastal Peru is expected to double by 2030. However, the appellation of this beverage confines the production and limits the space for agricultural expansion, leading to a situation in which potential competition for resources with established constraints is foreseen. Hence, the objective of this study is to understand the environmental impacts, focused on climate change and water consumption, linked…
Exploring machine learning techniques to predict deforestation to enhance the decision‐making of road construction projects
Land use changes (LUCs), which are defined as the modification in the use of land due to anthropogenic activities, are important sources of GHG emissions. In this context, understanding future trends of LUCs, such as deforestation, in a spatial manner is relevant. The main objective of this study is to generate a deforestation prediction model for a given period of time (i.e., 2002–2017 and 2010–2017) to estimate the potential carbon emissions as…
Climate change (2 works) · Environmental Impact and Sustainability (2 works) · Geography (2 works) · Greenhouse gas (2 works) · Agricultural productivity (1 work) · Agriculture (1 work) · Agriculture Sustainability and Environmental Impact (1 work) · Amazon rainforest (1 work) · Civil engineering (1 work) · Computer Science (1 work)