A5055961154- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Remote Sensing and Land Use
- Remote Sensing and LiDAR Applications
- X-ray Diffraction in Crystallography
- Crystallization and Solubility Studies
- Smart Agriculture and AI
- Remote-Sensing Image Classification
- Plant Water Relations and Carbon Dynamics
- Geographic Information Systems Studies
- Species Distribution and Climate Change
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Cryospheric studies and observations
- Flood Risk Assessment and Management
- Climate variability and models
- Spectroscopy and Chemometric Analyses
- Science and Climate Studies
- Plant Ecology and Soil Science
- Meteorological Phenomena and Simulations
- Atmospheric and Environmental Gas Dynamics
- Urban Heat Island Mitigation
- Ocean Waves and Remote Sensing
- Geophysics and Gravity Measurements
- Oceanographic and Atmospheric Processes
- Global Trade and Competitiveness
UCLouvain
2012-2024
Crop area extent estimates and crop type maps provide crucial information for agricultural monitoring management. Remote sensing imagery in general and, more specifically, high temporal spatial resolution data as the ones which will be available with upcoming systems, such Sentinel-2, constitute a major asset this kind of application. The goal paper is to assess what state-of-the-art supervised classification methods can applied multi-temporal optical produce accurate at global scale. Five...
The convergence of new EO data flows, methodological developments and cloud computing infrastructure calls for a paradigm shift in operational agriculture monitoring. Copernicus Sentinel-2 mission providing systematic 5-day revisit cycle free access opens completely avenue near real-time crop specific monitoring at parcel level over large countries. This research investigated the feasibility to propose methods develop an open source system able generate, national scale, cloud-free...
Abstract. Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global data sets presently fall short of user needs providing detailed spatial thematic information that consistently mapped over time easily transferable to requirements models. In 2009, European Space Agency launched Climate Change Initiative (CCI), (LC_CCI) as 1 13 essential climate variables targeted for research development. The LC_CCI was implemented...
Abstract. Land-use and land-cover change (LULCC) impacts local energy water balance contributes on global scale to a net carbon emission the atmosphere. The newly released annual ESA CCI (climate initiative) land cover maps provide continuous changes at 300 m resolution from 1992 2015, can be used in surface models (LSMs) simulate LULCC effects stocks budgets. Here we investigate absolute areas gross different plant functional types (PFTs) derived products. results are compared with other...
Land cover is one of the essential climate variables ESA Climate Change Initiative (CCI). In this context, Cover CCI (LC CCI) project aims at building global land maps suitable for modeling based on Earth observation by satellite sensors. The challenge to generate a set successive that are both accurate and consistent over time. To do so, operational methods automated classification optical images investigated. proposed approach consists locally trained using an selection training samples...
Abstract. The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme generate CDRs addressing range essential variables (ECVs) from satellite data. Here, we review nature, mathematics, practicalities, communication Earth observations. This paper argues that derived satellite-based observation (EO) should include rigorous support application...
Cropland mapping relies heavily on field data for algorithm calibration, making it, in many cases, applicable only at the campaign scale. While recently launched Sentinel-2 satellite will be able to deliver time series over large regions, it not really compatible with current approach or available situ data. This research introduces a generic methodology annual cropland along season high spatial resolution use of globally baseline land cover and no need The is based cropland-specific...
The exploitation of new high revisit frequency satellite observations is an important opportunity for agricultural applications. Sentinel-2 Agriculture project S2Agri (http://www.esa-sen2agri.org/SitePages/Home.aspx) designed to develop, demonstrate and facilitate the time series contribution EO component agriculture monitoring many systems across globe. In framework this project, article studies construction a dynamic cropland mask. This mask consists binary...
Abstract. Improving systematic observations of land cover, as an Essential Climate Variable, should contribute to a better understanding the global climate system and thus improve our ability predict climatic change. The aim this paper is bring cover closer meeting needs science. First, consultation mechanisms were established with modeling community identify its specific requirements in terms satellite-based products. This assessment highlighted characterization, accuracy products, well...
Accurate maps of surface water extent are paramount importance for management, satellite data processing and climate modeling. Several bodies based on remote sensing have been released during the last decade. Nonetheless, none has a truly (90 ∘ N/90 S) global coverage while being thoroughly validated. This paper describes global, spatially-complete (void-free) accurate mask inland/ocean 2000–2012 period, built in framework European Space Agency (ESA) Climate Change Initiative (CCI). map...
Accurate and timely information on the global cropland extent is critical for food security monitoring, water management earth system modeling. Principally, it allows analyzing satellite image time-series to assess crop conditions permits isolation of agricultural component focus impacts various climatic scenarios. However, despite its importance, accurate spatial extent, mapping with remote sensing imagery remains a major challenge. Following an exhaustive identification collection existing...
Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity regional to global agriculture in terms of resolution (10–20 meter), revisit frequency (five days) coverage (global). In this context, European Space Agency launched 2014 “Sentinel2 Agriculture” project, which aims prepare exploitation through development open source...
Abstract. Essential Climate Variables were listed by the Global Observing System as critical information to further understand climate system and support modelling. The European Space Agency launched its Change Initiative in order provide an adequate response set of requirements for long-term satellite-based products climate. Within this program, CCI Land Cover project aims at revisiting all algorithms required generation global land cover that are stable consistent over time, while also...
Time series of vegetation indices (VIs) obtained by remote sensing are widely used to study phenology on regional and global scales. The aim the is design a method produce reference data set describing seasonal inter-annual variability land-surface scale. Specific constraints inherent in such set: (1) high diversity types heterogeneous conditions observation, (2) near-daily resolution needed follow rapid changes phenology, (3) time depict baseline cycle must be long enough representative...
Abstract Monitoring land cover over large areas on a yearly basis is challenging. The spatial and temporal consistency of an object-based change detection algorithm was tested through multi-year application the forest Borneo, using SPOT-VEGETATION time series from 2000 to 2008. Continuous thresholds allowed tuning according specific requirements in terms omission commission errors. accuracy method assessed ROC (relative operating characteristics) curves, which were found useful evaluate...
Abstract. Global land cover is a key variable in the earth system with feedbacks on climate, biodiversity and natural resources. However, global land-cover datasets presently fall short of user needs providing detailed spatial thematic information that consistently mapped over time easily transferable to requirements models. In 2009, European Space Agency launched Climate Change Initiative (CCI), (LC_CCI) as one thirteen Essential Variables targeted for research development. The LC_CCI was...