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A novel cotton mapping index combining Sentinel-1 SAR and Sentinel-2 multispectral imagery / Lan Xun in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > Vol 181 (November 2021) . - pp 148 - 166 Titre : A novel cotton mapping index combining Sentinel-1 SAR and Sentinel-2 multispectral imagery Type de document : Article/Communication Auteurs : Lan Xun, Auteur ; Jiahua Zhang, Auteur ; Dan Cao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 148 - 166 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie automatique [Termes IGN] Chine [Termes IGN] coefficient de rétrodiffusion [Termes IGN] distribution spatiale [Termes IGN] Etats-Unis [Termes IGN] Gossypium (genre) [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de végétation [Termes IGN] polarisation [Termes IGN] réflectance spectrale [Termes IGN] série temporelle Résumé : (auteur) Cotton is an important cash crop in the world, as the main source of natural and renewable fiber for textiles. Accurate and timely monitoring of the cotton distribution is crucial for cotton cultivation management and international trade. However, most of the previous researches on cotton identification using remotely sensed images are highly dependent on training samples, and the collection of samples is time-consuming and expensive. To overcome this limitation, a new index, termed as Cotton Mapping Index (CMI), was developed in this study for automatic cotton mapping using time series of Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 Multispectral Instrument (MSI) satellite data. Four sites in the United States (U.S.) and four sites in China were selected to develop and assess the performance of the CMI. The spectral characteristics derived from Sentinel-2 and backscattering coefficients derived from Sentinel-1 for cotton and non-cotton crops during the cotton growth period were analyzed. Considering the phenology differences of crops in different regions, the features at an adaptive window were adopted to construct the CMI. The results showed that at the peak greenness period, the multiplication of red-edge 1 and red-edge 2 band for cotton samples were much larger than those for non-cotton samples, whereas the spectral angle at the red band as well as the absolute values of backscattering coefficients in vertical transmit and vertical receive (VV) polarization for cotton samples were much smaller than those for non-cotton samples. Based on these findings, the CMI was developed to identify cotton cultivated area within the cropland area. The overall accuracy of classification results for the sites in the U.S. was higher than 81.20%, and the mean relative error for the sites in Xinjiang of China was 26.69%. The CMI, which incorporated optical and radar features, had a better performance than the indices using optical features solely. The advantage of the CMI over supervised classifiers (i.e., k-nearest neighbors, support vector machine and random forest) is that no training samples are required. Moreover, the cotton distribution map can be obtained before the harvest using the CMI. These results indicated the potential of the CMI for cotton mapping. The applicability of CMI in other regions with different cropping systems and crop types needs to be further assessed in the future study. Numéro de notice : A2021-775 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.021 Date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98836 [article]

Variation in plant–soil interactions among temperate forest herbs / Jared J. Beck in Plant ecology, vol 222 n° 11 (November 2021)  

Public [article]  inPlant ecology > vol 222 n° 11 (November 2021) . - pp 1225 - 1238 Titre : Variation in plant–soil interactions among temperate forest herbs Type de document : Article/Communication Auteurs : Jared J. Beck, Auteur Année de publication : 2021 Article en page(s) : pp 1225 - 1238 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] croissance végétale [Termes IGN] forêt tempérée [Termes IGN] herbe [Termes IGN] phytoécologie [Termes IGN] relations plante - sol [Termes IGN] Wisconsin (Etats-Unis) [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Antagonistic interactions between plants and soil biota promote species diversity in many plant communities but little is known about how these plant–soil interactions influence herbaceous species in temperate forests. To assess the potential for soil biota to affect the growth of forest herbs, I conducted a greenhouse experiment in which seedlings of nine focal herb species common in Wisconsin (USA) forests were grown in soil derived from conspecific and heterospecific plants. This soil origin treatment was crossed with a subsequent treatment in which half of the soils were pasteurized to eliminate soil biota. The presence and origin of soil biota had variable effects on plant growth among the nine focal species. Thalictrum dioicum, Elymus hystrix, and Solidago flexicaulis growth were inhibited by the presence of soil biota in unpasteurized soils. Thalictrum dioicum seedlings grown in conspecific, unpasteurized soil accumulated 30% less biomass than seedlings grown in heterospecific, unpasteurized soil indicating that host-specific effects of microbial pathogens restrict seedling growth. Similarly, E. hystrix seedlings were 11% smaller in conspecific-trained soils. The remaining herb species showed no significant response to experimental treatments manipulating soil biota. These variable growth responses highlight the potential for differences in plant–soil interactions among plant species to influence local plant distributions and community dynamics. Janzen–Connell effects, like those observed in T. dioicum and E. hystrix, could promote coexistence among certain species and contribute to high local plant diversity in temperate forest understories. Numéro de notice : A2021-730 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s11258-021-01173-x Date de publication en ligne : 23/08/2021 En ligne : https://doi.org/10.1007/s11258-021-01173-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98674 [article]

Modeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps / Batistin Bour in Forest ecology and management, vol 502 (15 december 2021)  

Public [article]  inForest ecology and management > vol 502 (15 december 2021) . - n° 119697 Titre : Modeling post-logging height growth of black spruce-dominated boreal forests by combining airborne LiDAR and time since harvest maps Type de document : Article/Communication Auteurs : Batistin Bour, Auteur ; Victor Danneyrolles, Auteur ; Yan Boucher, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119697 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] carte forestière [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt boréale [Termes IGN] forêt de production [Termes IGN] gestion forestière [Termes IGN] hauteur des arbres [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] Picea mariana [Termes IGN] productivité [Termes IGN] Québec (Canada) [Termes IGN] récolte de bois [Termes IGN] semis de points Résumé : (auteur) Increase in forest disturbance due to land use as well as climate change has led to an expansion of young forests worldwide, which drives global carbon dynamics and timber allocation. This study presents a method that combines a single airborne LiDAR acquisition and time since harvest maps to model height growth of post-logged black spruce-dominated forests in a 1700 km2 eastern Canadian boreal landscape. We developed a random forest model in which forest height at a 20 m × 20 m pixel resolution is a function of stand age, combined with environmental variables (e.g., slope, site moisture, surface deposit). Our results highlight the model's strong predictive power: least-square regression between predicted and observed height of our validation dataset was very close to the 1:1 relation and strongly supported by validation metrics (R2 = 0.74; relative RMSE = 19%). Environmental variables thus allowed to accurately predict forest productivity with a high spatial resolution (20 m × 20 m pixels) and predicted forest height growth in the first 50 years after logging ranged between 16 and 27 cm·year−1 across the whole study area, with a mean of 20.5 cm·year−1. The spatial patterns of potential height growth were strongly linked to the effect of topographical variables, with better growth rates on mesic slopes compared to poorly drained soils. Such models could have key implications in forest management, for example to maintain forest ecosystem services by adjusting the harvesting rates depending on forest productivity across the landscapes. Numéro de notice : A2021-708 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2021.119697 Date de publication en ligne : 25/09/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119697 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98819 [article]

Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery / Camile Sothe in Geocarto international, Vol 36 n° 19 ([18/10/2021])  

Public [article]  inGeocarto international > Vol 36 n° 19 [18/10/2021] . - pp 2241 - 2259 Titre : Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery Type de document : Article/Communication Auteurs : Camile Sothe, Auteur ; Claudia Maria de Almeida, Auteur ; Marcos Benedito Schimalski, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2241 - 2259 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] Brésil [Termes IGN] délimitation [Termes IGN] forêt tropicale [Termes IGN] houppier [Termes IGN] identification de plantes [Termes IGN] image à très haute résolution [Termes IGN] image Worldview [Termes IGN] méthode heuristique [Termes IGN] orthoimage [Termes IGN] segmentation d'image Résumé : (auteur) In the case of tree species delineation with very high spatial resolution (VHR) images, is desirable that each segment corresponds to one individual tree crown (ITC). However, in order to have a segmentation algorithm that generates segments matching to ITCs, its parameters ought to be properly tuned. Aiming to avoid time-consuming trial-and-error procedures associated with this task, some initiatives for the automatic search of segmentation parameters have been developed, such as metaheuristic methods. The objective of this work was to test the automatic tuning of segmentation parameters of three segmentation algorithms for the delineation of ITCs belonging to a native endangered species in a subtropical forest area, comparing this method with the traditional trial-and-error approach. Two datasets (WorldView-2 and an orthoimage) and three segmentation algorithms (multiresolution, mean-shift and graph-based) were tested. For the automatic approach, a hybrid metaheuristic method was applied to accomplish the automatic search of parameters for the segmentation algorithms, while for the trial-and-error, a visual assessment was conducted for each set of parameters tested. Four supervised metrics were used to assess the quality of the segmentation results for the optimization approach and for the final set of parameters chosen in the trial-and-error approach. Results showed that none of the algorithms, datasets or approaches differ too much. The evaluation metrics values were lower, indicating that the reference ITCs polygons matched with the segmentation results. Despite the similar results, the automatic tuning of segmentation parameters proved to be a feasible alternative to reduce the subjectivity and the human effort in the choice of segmentation parameters as compared to the trial-and error approach. Numéro de notice : A2021-765 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1690056 Date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1690056 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98810 [article]

A vector-based method for drainage network analysis based on LiDAR data / Fangzheng Lyu in Computers & geosciences, vol 156 (November 2021)  

Public [article]  inComputers & geosciences > vol 156 (November 2021) Titre : A vector-based method for drainage network analysis based on LiDAR data Type de document : Article/Communication Auteurs : Fangzheng Lyu, Auteur ; Xinlin Ma, Auteur ; et al., Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse vectorielle [Termes IGN] Caroline du Nord (Etats-Unis) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] interpolation spatiale [Termes IGN] modèle numérique de surface [Termes IGN] réseau hydrographique [Termes IGN] semis de points Résumé : (auteur) Drainage network analysis is fundamental to understanding the characteristics of surface hydrology. Based on elevation data, drainage network analysis is often used to extract key hydrological features like drainage networks and streamlines. Limited by raster-based data models, conventional drainage network algorithms typically allow water to flow in 4 or 8 directions (surrounding grids) from a raster grid. To resolve this limitation, this paper describes a new vector-based method for drainage network analysis that allows water to flow in any direction around each location. The method is enabled by rapid advances in Light Detection and Ranging (LiDAR) remote sensing and high-performance computing. The drainage network analysis is conducted using a high-density point cloud instead of Digital Elevation Models (DEMs) at coarse resolutions. Our computational experiments show that the vector-based method can better capture water flows without limiting the number of directions due to imprecise DEMs. Our case study applies the method to Rowan County watershed, North Carolina in the US. After comparing the drainage networks and streamlines detected with corresponding reference data from US Geological Survey generated from the Geonet software, we find that the new method performs well in capturing the characteristics of water flows on landscape surfaces in order to form an accurate drainage network. Numéro de notice : A2021-755 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104892 Date de publication en ligne : 24/07/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98733 [article]

Impact of travel time uncertainties on modeling of spatial accessibility: a comparison of street data sources / Yan Lin in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)  

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Integration of heterogeneous terrain data into Discrete Global Grid Systems / Mingke Li in Cartography and Geographic Information Science, vol 48 n° 6 (October 2021)  

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Evaluating the potential of cybercartography in facilitating indigenous self-determination: A case study with the Hupačasath first nation / Dexter Robson in Cartographica, vol 56 n° 3 (Fall 2021)  

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Using LiDAR and Random Forest to improve deer habitat models in a managed forest landscape / Colin S. Shanley in Forest ecology and management, vol 499 (1 November 2021)  

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GIS-based logic scoring of preference method for urban densification suitability analysis / Shuoge Shen in Computers, Environment and Urban Systems, vol 89 (September 2021)  

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GIS models for vulnerability of coastal erosion assessment in a tropical protected area / Luís Russo Vieira in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)  

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Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data / Laura Elena Cué La Rosa in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)  

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A multiagent systems with Petri Net approach for simulation of urban traffic networks / Mauricio Flores Geronimo in Computers, Environment and Urban Systems, vol 89 (September 2021)  

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Shore zone classification from ICESat-2 data over Saint Lawrence Island / Huan Xie in Marine geodesy, vol 44 n° 5 (September 2021)  

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Monitoring forest disturbance using time-series MODIS NDVI in Michoacán, Mexico / Yao Gao in Geocarto international, Vol 36 n° 15 ([10/08/2021])  

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