Lisboa, Sà Nogueira Mauricio Grinand, Clovis Betbeder, Julie Montfort, Frédérique Blanc, Lilian
The fragmented and complex landscape in the Miombo landscape makes it a challenge to map and disentangle the various forest change drivers (FCD) associated with these changes and relate them to other underlying drivers. To overcome these challenges, we developed a method to spatially disentangle the drivers of deforestation (smallholder and commerc...
Vallet, Ameline Dupuy, Stéphane Verlynde, Matthieu Gaetano, Raffaele
Land Use and Land Cover (LULC) maps are important tools for environmental planning and social-ecological modeling, as they provide critical information for evaluating risks, managing natural resources, and facilitating effective decision-making. This study aimed to generate a very high spatial resolution (0.5 m) and detailed (21 classes) LULC map f...
Capliez, Emmanuel Ienco, Dino Gaetano, Raffaele Baghdadi, Nicolas Hadj Salah, Adrien Le Goff, Matthieu Chouteau, Florient
With the huge variety of Earth observation satellite missions available nowadays, the collection of multisensor remote sensing information depicting the same geographical area has become systematic in practice, paving the way to the further breakthroughs in automatic land cover mapping with the aim to support decision makers in a variety of land ma...
Castro Alvarado, Enzo Bégué, Agnès Leroux, Louise Gaetano, Raffaele
Non-active agricultural land (NAAL) mapping in West Africa is essential to accurately assess agricultural systems and its contribution to food security and agro-ecological sustainability of current practices, and yet the available mapping methodologies are not adapted to the environmental and cropping conditions encountered when addressing tropical...
Ienco, Dino Gaetano, Raffaele Interdonato, Roberto
In this work, we present a new semi-supervised learning framework to cope with satellite image time series (SITS) classification in a data paucity scenario, considering extreme low levels of supervision. The proposed methodology, referred as SITS (Semi-Supervised Satellite Image Time Series classification method), is based on temporal convolutional...
Reiner, Florian Brandt, Martin Tong, Xiaoye Skole, David Kariryaa, Ankit Ciais, Philippe Davies, Andrew Hiernaux, Pierre Chave, Jérôme Mugabowindekwe, Maurice
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The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-res...
Lu, Tingting Brandt, Martin Tong, Xiaoye Hiernaux, Pierre Leroux, Louise Ndao, Babacar Fensholt, Rasmus
Multi-purpose Faidherbia albida trees represent a vital component of agroforestry parklands in West Africa as they provide resources (fodder for livestock, fruits and firewood) and support water lifting and nutrient recycling for cropping. Faidherbia albida trees are characterized by their inverse phenology, growing leaf flowers and pods during the...
Lelong, Camille Herimandimby, Hasina
Hereby presented data consists of a land use / land cover map of an 84 km2 part of the Vavatenina district, in the Analanjirofo Region of the east coast of Madagascar, where the landscape is dominated by woody vegetation. This map was obtained by processing very high spatial resolution multispectral images acquired by the Pleiades satellite sensor ...
Luciano, Ana Cláudia dos Santos Campagnuci, Bruna Cristina Gama Le Maire, Guerric
Remote sensing techniques can help estimate large sugarcane areas in order to support sustainable planning and management for the sugarcane industry, as well as in the context of environmental monitoring. In this study, four generalized space-time classifiers of high-resolution satellite images were tested in São Paulo State (SP) in order to map ou...
Censi, Alessandro Michele Ienco, Dino Gbodjo, Yawogan Jean Eudes Pensa, Ruggero Gaetano Interdonato, Roberto Gaetano, Raffaele
Satellite image time series (SITS) collected by modern Earth Observation (EO) systems represent a valuable source of information that supports several tasks related to the monitoring of the Earth surface dynamics over large areas. A main challenge is then to design methods able to leverage the complementarity between the temporal dynamics and the s...