A5077275845- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Sugarcane Cultivation and Processing
- Conservation, Biodiversity, and Resource Management
- Remote-Sensing Image Classification
- Remote Sensing and LiDAR Applications
- Smart Agriculture and AI
- Spectroscopy and Chemometric Analyses
- Biofuel production and bioconversion
- Rural Development and Agriculture
- Agricultural Innovations and Practices
- Agriculture, Land Use, Rural Development
- Geography and Environmental Studies
- Hydrology and Drought Analysis
- Plant Water Relations and Carbon Dynamics
- Geochemistry and Geologic Mapping
- Soil and Land Suitability Analysis
- Satellite Image Processing and Photogrammetry
- Agriculture and Rural Development Research
- Remote Sensing and Land Use
- Climate variability and models
- Leaf Properties and Growth Measurement
- Water-Energy-Food Nexus Studies
- Rangeland Management and Livestock Ecology
- Advanced Database Systems and Queries
Food and Agriculture Organization of the United Nations
2025
UCLouvain
2021-2024
Life Science Institute
2023
University of Copenhagen
2022
National Institute for Space Research
2017-2021
Universidade Estadual de Campinas (UNICAMP)
2009-2018
Brazilian Center for Research in Energy and Materials
2013-2016
Laboratório Nacional de Ciência e Tecnologia do Bioetanol
2014
Sugarcane ethanol has been produced in Brazil since the early 20th century, but production increased mid‐1970s aiming at substituting 20% of gasoline. Despite an increase 2000s stable 2008. This paper presents a review main developments achieved and future challenges. The sector had positive economic environmental results through technological development, as result research development by private companies strong public support. yield steadily positively impacted costs, primarily due to...
Tropical forests regulate the global water and carbon cycles also host most of world’s biodiversity. Despite their importance, they are hard to survey due location, extent, particularly, cloud coverage. Clouds hinder spatial radiometric correction satellite imagery diminishing useful area on each image, making it difficult monitor land change. For this reason, our purpose is identify detection algorithm best suited for Amazon rainforest Sentinel–2 images. To achieve this, we tested four...
Recently, remote sensing image time series analysis has being widely used to investigate the dynamics of environments over time. Many studies have combined with machine learning methods improve land use and cover change mapping. In order support analysis, analysis-ready data (ARD) collections been modeled organized as multidimensional cubes. Data cubes can be defined sets associated spatially aligned pixels. Based on lessons learned in research project e-Sensing, related national demands for...
Abstract The Brazilian Amazon has the highest concentration of indigenous peoples in world. Recently, government sent a bill to Congress regulate commercial mining lands. This work analyzes risks proposed Amazonian and their To evaluate possible impact new bill, we consider all license requests registered Brazil’s National Mining Agency that overlap lands as potential areas future. existing cover 176 000 km 2 lands, factor 3000 more than area current illegal mining. Considering only these...
Abstract This paper presents a dataset of yearly land use and cover classification maps for Mato Grosso State, Brazil, from 2001 to 2017. is one the world’s fast moving agricultural frontiers. To ensure multi-year compatibility, work uses MODIS sensor analysis-ready products an innovative method that applies machine learning techniques classify satellite image time series. The provide information about crop pasture expansion over natural vegetation, as well spatially explicit estimates...
This study investigates the main threats related to environmental degradation that affect Amazonian Indigenous Lands (ILs). Through a cluster analysis, we group ILs according set of common occur within and outside their limits. The results show most 383 are affected internally by combination different threats, namely: deforestation, forest degradation, fires, mining, croplands, pastures, roads. However, multiple relatively severe mainly located in arc deforestation Roraima state. loss...
The preference for simple explanations, known as the parsimony principle, has long guided development of scientific theories, hypotheses, and models. Yet recent years have seen a number successes in employing highly complex models ...
The extensive amount of Earth observation satellite images available brings opportunities and challenges for land mapping in global regional scales. These large datasets have motivated the use image time series analysis coupled with machine learning techniques to produce cover class maps. To be successful, these methods need good quality training samples, which are most important factor determining accuracy results. For this reason, samples control noise. In paper, we propose a method assess...
Amazonian Indigenous Lands (ILs) are human-environment systems facing a multitude of environmental threats. Yet, the resulting vulnerability these to date unknown. We adopt theoretical framework IPCC assess Brazilian Amazon ILs for two periods (2001–2010 and 2011–2019) overall (2001–2019). Vulnerability is deemed function exposure (EX), sensitivity (SE) adaptive capacity (AC) system Sensitivity (threats within IL) in IL's buffer zones) indicators changes forest cover, economic activities,...
Cropland mapping in smallholder landscapes is challenged by complex and fragmented landscapes, labor-intensive unmechanized land management causing high within-field variability, rapid dynamics shifting cultivation systems, substantial proportions of short-term fallows. To overcome these challenges, we here present a large-area framework to identify active cropland fallows for the 2020/2021 growing season at 4.77 m spatial resolution. Our study focuses on Northern Mozambique, an area...
Demand for agricultural exports in Brazil has stimulated the expansion of crop production and cattle raising, which caused environmental impacts. In response, developed public policies such as new Forest Code (FC) supply chain arrangements Soy Cattle Moratoriums. This paper analyzes effectiveness these policies, considering trajectories state Mato Grosso three years: 2005 (pre-moratorium before FC), 2010 (post-moratorium FC) 2017 post-new FC). Our analysis uses a detailed land use change...
Methods for crop phenology detection using time series analysis have provided accurate information large agricultural areas in shorter processing times, which can be useful agronomic management and supply chain monitoring. Given the dynamics Brazilian Cerrado, with alternating type plantings, successions, rotations, as well climate practices variation between harvest periods, these methods detecting subtle land use cover changes at farm field scales, improving thematic classifications near...
Cropland mapping in smallholder landscapes is challenged by complex and fragmented landscapes, labor-intensive unmechanized land management causing high within-field variability, rapid dynamics shifting cultivation systems, substantial proportions of short-term fallows. To overcome these challenges, we here present a large-area framework to identify active cropland fallows for the 2020/2021 growing season at 4.77 m spatial resolution. Our study focuses on Northern Mozambique, an area...
Considerando que algumas investigações sobre o tema aquecimento global utilizam longas séries temporais de temperatura uma questão deve ser levantada é relativa a influência possíveis concentrações fontes calor urbano os postos meteorológicos possam estar submetidos. O primeiro passo para responder essa verificar se, em mesma região, ocorrem tendências concomitantes elevação nos dados diversas localidades, possivelmente ligadas fenômenos escala global. Entretanto, se tiver seu início...
Abstract. Currently, the overwhelming amount of Earth Observation data demands new solutions regarding processing and storage. To reduce time spent in searching, downloading pre-processing data, remote Sensing community is coming to an agreement on minimum corrections satellite images must convey order reach broadest range applications. Satellite imagery meeting such criteria (which usually include atmospheric, radiometric topographic corrections) are generically called Analysis Ready Data...