Clément Mallet

Institut national de l’information géographique et forestière | IGN · LaSTIG lab

Shape vectorization is a key stage of the digitization of large-scale historical maps, especially city maps that exhibit complex and valuable details. Having access to digitized buildings, building blocks, street networks and other geographic content opens numerous new approaches for historical studies such as change tracking, morphological analysi...

Land cover maps are a pivotal element in a wide range of Earth Observation (EO) applications. However, annotating large datasets to develop supervised systems for remote sensing (RS) semantic segmentation is costly and time-consuming. Unsupervised Domain Adaption (UDA) could tackle these issues by adapting a model trained on a source domain, where...

The HYEP project (ANR HYEP 14-CE22-0016-01 Hyperspectral imagery for Environmental urban Planning - Mobility and Urban Systems Programme - 2014) confirmed the interest of a global approach to the urban environment by remote sensing and in particular by using hyperspectral imaging (HI). The interest of hyperspectral images lies in the range of infor...

Land-use/land-cover (LULC) maps describe the Earth’s surface with discrete classes at a specific spatial resolution. The chosen classes and resolution highly depend on peculiar uses, making it mandatory to develop methods to adapt these characteristics for a large range of applications. Recently, a convolutional neural network (CNN)-based method wa...

We propose a new deep learning-based method for estimating the occupancy of vegetation strata from airborne 3D LiDAR point clouds. Our model predicts rasterized occupancy maps for three vegetation strata corresponding to lower, medium, and higher cover. Our weakly-supervised training scheme allows our network to only be supervised with vegetation o...

Capturing the global topology of an image is essential for proposing an accurate segmentation of its domain. However, most of existing segmentation methods do not preserve the initial topology of the given input, which is detrimental for numerous downstream object-based tasks. This is all the more true for deep learning models which most work at lo...

Sentinel-2 satellites provide dense image time series exhibiting high spectral, spatial and temporal resolutions. These images are in particular of utter interest for Land-Cover (LC) mapping at large scales. LC maps can now be computed on a yearly basis at the scale of a country with efficient supervised classifiers, assuming suitable training data...

The analysis of the multi-layer structure of wild forests is an important challenge of automated large-scale forestry. While modern aerial LiDARs offer geometric information across all vegetation layers, most datasets and methods focus only on the segmentation and reconstruction of the top of canopy. We release WildForest3D, which consists of 29 st...

We propose a new deep learning-based method for estimating the occupancy of vegetation strata from 3D point clouds captured from an aerial platform. Our model predicts rasterized occupancy maps for three vegetation strata: lower, medium, and higher strata. Our training scheme allows our network to only being supervized with values aggregated over c...

We propose a new deep learning-based method for estimating the occupancy of vegetation strata from 3D point clouds captured from an aerial platform. Our model predicts rasterized occupancy maps for three vegetation strata: lower, medium, and higher strata. Our training scheme allows our network to only being supervized with values aggregated over c...

Most contemporary supervised image segmentation methods do not preserve the initial topology of the given input (like the closeness of the contours). One can generally remark that edge points have been inserted or removed when the binary prediction and the ground truth are compared. This can be critical when accurate localization of multiple interc...

In this paper, we propose an operational solution for the yearly classification of crop parcels at national scale (namely France) for Land Parcel Identification System updating, under the Common Agricultural Policy (CAP) umbrella. Our pipeline is based on the ι2 open-source framework and fed with both time series of Sentinel-1 radar and Sentinel-2...

Label noise is known to negatively impact the performance of classification algorithms. In this paper, we develop a model robust to label noise that uses both labelled and unlabelled samples. In particular, we propose a novel algorithm to optimize the model parameters that scales efficiently w.r.t. the number of training samples. Our contribution r...

Maps have been a unique source of knowledge for centuries. Such historical documents provide invaluable information for analyzing the complex spatial transformation of landscapes over important time frames. This is particularly true for urban areas that encompass multiple interleaved research domains (social sciences, economy, etc.). The large amou...

This paper presents the final results of the ICDAR 2021 Competition on Historical Map Segmentation (MapSeg), encouraging research on a series of historical atlases of Paris, France, drawn at 1/5000 scale between 1894 and 1937. The competition featured three tasks, awarded separately. Task 1 consists in detecting building blocks and was won by the L...

Dense time series of optical satellite imagery describing vegetation activity provide essential information for the efficient and regular monitoring of vegetation. Nevertheless, the temporal resolution of optical sensors is strongly affected by cloud cover, resulting in significant missing information. The use of complementary acquisitions, such as...

One key factor to exhaustive vegetation monitoring lies in the dense temporal sampling of the measurements. Areas subject to multiple human interventions, such as grasslands, are particularly concerned. A Recurrent Neural Network multi-sensor regression approach (SenRVM), relying on the systematic acquisitions of Sentinel-1 SAR satellite, has been...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

City modeling consists in building a semantic generalized model of the surface of urban objects. These could be seen as a special case of Boundary representation surfaces. Most modeling methods focus on 3D buildings with Very High Resolution overhead data (images and/or 3D point clouds). The literature abundantly addresses 3D mesh processing but fr...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

We report key elements and figures related to the proceedings of the 2021 edition of the XXIVth ISPRS Congress. Similarly to 2020, the COVID-19 pandemic caused global travel challenges and restrictions for the first half of 2021. Consequently, the physical Congress re-scheduled from June 2020 to July 2021 was again postponed to June 2022, still in...

This paper presents the final results of the ICDAR 2021 Competition on Historical Map Segmentation (MapSeg), encouraging research on a series of historical atlases of Paris, France, drawn at 1/5000 scale between 1894 and 1937. The competition featured three tasks, awarded separately. Task~1 consists in detecting building blocks and was won by the L...

The digitization of historical maps enables the study of ancient, fragile, unique, and hardly accessible information sources. Main map features can be retrieved and tracked through the time for subsequent thematic analysis. The goal of this work is the vectorization step, i.e., the extraction of vector shapes of the objects of interest from raster...

CORINE Land-Cover (CLC) and its by-products are considered as a reference baseline for land-cover mapping over Europe and subsequent applications. CLC is currently tediously produced each six years from both the visual interpretation and the automatic analysis of a large amount of remote sensing images. Observing that various European countries reg...

The digitization of historical maps enables the study of ancient, fragile, unique, and hardly accessible information sources. Main map features can be retrieved and tracked through the time for subsequent thematic analysis. The goal of this work is the vectorization step, i.e., the extraction of vector shapes of the objects of interest from raster...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

Time series of optical and Synthetic Aperture RADAR (SAR) images provide complementary knowledge about the cover and use of the Earth surface since they exhibit information of distinct physical nature. They have proved to be particularly relevant for monitoring large areas with high temporal dynamics and related to significant ecosystem services. G...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

Sentinel-2 satellites provide dense image time series exhibiting high spectral, spatial and temporal resolution. These images are in particular of utter interest to map Land-Cover (LC) at large scale. LC maps can now be computed on a yearly basis at the scale of a country with efficient supervised classifiers, assuming suitable training data are av...

Many land-cover products have been made available for a large range of end-users over the last ten years, even at global scales. In particular, remote sensing data analysis has proved to be the most feasible solution for automation purposes, at multiple spatial scales. However, current solutions are not sufficient for designing better products, ada...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

In order to reach the goal of reliably solving Earth monitoring tasks, automated and efficient machine learning methods are necessary for large-scale scene analysis and interpretation. A typical bottleneck of supervised learning approaches is the availability of accurate (manually) labeled training data, which is particularly important to train sta...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes occurred since the mid 20th century. They provide a relatively dense temporal sampling of the territories with a very high spatial resolution. Thus, they offer time series data which can answer a large variety of long-...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

We report key elements and figures related to the proceedings of the 2020 edition of the XXIVth ISPRS Congress. The COVID-19 pandemic causes global travel challenges and restrictions for the full year 2020. Consequently, the Congress planned in June 2020 in Nice (France) was postponed to July 2021. Papers were already submitted and the review proce...

Time series of optical and Synthetic Aperture RADAR (SAR) images provide complementary knowledge about the cover and use of the Earth surface since they exhibit information of distinct physical nature. They have proved to be particularly relevant for monitoring large areas with high temporal dynamics and related to significant ecosystem services. G...

En los últimos quince años, los sistemas de información geográfica se han convertido en un elemento central de las aplicaciones que se ocupan de cuestiones de ordenación del territorio.Este tercer volumen describe la implementación de varias aplicaciones relacionadas con la ordenación del uso de la tierra en QGIS (Quantum Geographic Information Sys...

Este libro inicia la serie Utilización del QGIS en la teledetección, cuyo objetivo es facilitar la apropiación y el uso operativo del QGIS (Quantum Geographic Information System) en el campo de la teledetección.Este volumen define el principio del funcionamiento del QGIS y las librerías fundamentales más utilizadas en el procesamiento de imágenes y...

La agricultura y la silvicultura son áreas fuertemente comprometidas con el uso de datos espaciales, que son esenciales para restaurar la variabilidad espacial y temporal de las condiciones de la superficie. Un muy buen conocimiento de estos entornos es fundamental tanto desde el punto de vista económico como medioambiental. En este contexto, el us...

En un contexto de cambios globales fuertemente vinculados (climáticos y antropogénicos), la comprensión y cuantificación de la dinámica y los riesgos de los recursos hídricos es esencial para los administradores.Este cuarto volumen de la serie muestra la presentación y práctica de QGIS y sus bibliotecas de aplicaciones que se ocupan de problemas de...

The papers in this special section focus on the technology of urban remote sending. The rapid growth and the multiple changes of the urban environments pose unique challenges to cities across the globe. Due to the high rates of urbanization on our planet, it is often argued that the future of humanity will be decided in cities. This means that inno...

The automatic generation of three-dimensional (3D) building models from geospatial data is now a standard procedure. An abundance of literature covers the last two decades, and several solutions are now available. However, urban areas are very complex environments. Inevitably, practitioners still have to visually assess, at a city-scale, the correc...

The generation of 3D building models from Very High Resolution geospatial data is now an automatized procedure. However , urban areas are very complex and practitioners still have to visually assess the correctness of these models and detect reconstruction errors. We proposed an approach for automatically evaluating the quality of 3D building model...

The generation of 3D building models from Very High Resolution geospatial data is now an automatized procedure. However, urban areas are very complex and practitioners still have to visually assess the correctness of these models and detect reconstruction errors. We proposed an approach for automatically evaluating the quality of 3D building models...

Permanent Grasslands (PG) are heterogeneous environments with high spatial and temporal dynamics, subject to increasing environmental challenges. This study aims to identify requirements, key constraining factors and solutions for robust and complete detection of Mowing Events. Remote sensing is a powerful tool to monitor and investigate Near-Real-...

The automatic modeling of urban scenes in 3D from geospatial data has been studied for more than thirty years. However, the output models still have to undergo a tedious task of correction at city scale. In this work, we propose an approach for automatically evaluating the quality of 3D building models. A taxonomy of potential errors is first propo...

The automatic modeling of urban scenes in 3D from geospatial data has been studied for more than thirty years. However, the output models still have to undergo a tedious task of correction at city scale. In this work, we propose an approach for automatically evaluating the quality of 3D building models. A taxonomy of potential errors is first propo...

More and more countries have digitised or are currently digitising their archives of aerial images. They are a unique and relatively unexplored means to chronicle land-cover information over the past 100 years with very high spatial resolution. Such data provide a relatively dense temporal sampling of the territories. 3D information can even be ret...