Centre dedocumentation
scientifique

Mapping global flying aircraft activities using Landsat 8 and cloud computing / Fen Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 184 (February 2022) . - pp 19 - 30 Titre : Mapping global flying aircraft activities using Landsat 8 and cloud computing Type de document : Article/Communication Auteurs : Fen Zhao, Auteur ; Lang Xia, Auteur ; Arve Kylling, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 19 - 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] aviation civile [Termes IGN] cartographie thématique [Termes IGN] climat [Termes IGN] détection d'objet [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] informatique en nuage [Termes IGN] navigation aérienne [Termes IGN] trafic aérien [Termes IGN] transport aérien Résumé : (auteur) Satellite-based remote sensing might provide a potential way for monitoring the global flight activities and their environment impacts, while the remote sensing community pays less attention on it. In this study, we presented a flying aircraft detection algorithm which effectively handles the noise on Landsat 8 OLI cirrus band caused by energetic particles in the South Atlantic Anomaly region, and a new framework based on cloud infrastructure was proposed to map global flying aircraft activities from 2013 to 2020 using Landsat 8 Operational Land Imager (OLI) data. Validation was performed for 254 scenes recorded for various cloudy and surface conditions and vapor contents. The overall percentages of false alarms and omissions for these validation images were 5.37% and 7.80%, respectively. Limited to the resolution of Landsat data, cloud, the size and flight altitude of the aircraft, 42.99% flying aircraft were undetected compared with the FlightRadar24. Instead of using the Google Earth Engine, we employed more flexible cloud computing techniques, Google Cloud Storage and Google Calculation Engine, to construct our framework for the larger volume data. A total of 1.94 million Landsat images were analyzed to obtain the activities maps, and the results showed that globally flying aircraft increased by 25.85% from 2014 to 2019 (the year 2013 was excluded for the low coverage of Landsat scenes), with an annual rate of 4.31%. In 2020, flying aircraft were reduced by 40% compared with 2019 due to the influence of COVID-19 and traveling restrictions, and Europe was the most severely affected by COVID-19, with an 84.59% decline of flying aircraft in April 2020. This study provides a unique long-term supplement to monitor aviation activities and their climate impact. Numéro de notice : A2022-090 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.12.003 Date de publication en ligne : 15/12/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.12.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99506 [article]

Improving LSMA for impervious surface estimation in an urban area / Jin Wang in European journal of remote sensing, vol 55 n° 1 (January 2022)  

Public [article]  inEuropean journal of remote sensing > vol 55 n° 1 (January 2022) . - pp 37 - 51 Titre : Improving LSMA for impervious surface estimation in an urban area Type de document : Article/Communication Auteurs : Jin Wang, Auteur ; Yaolong Zhao, Auteur ; Yingchun Fu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 37 - 51 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] classification et arbre de régression [Termes IGN] image Landsat-OLI [Termes IGN] régression [Termes IGN] signature spectrale [Termes IGN] surface imperméable [Termes IGN] Yunnan (Chine) [Termes IGN] zone urbaine Résumé : (auteur) Linear spectral mixture analysis (LSMA) and regression analysis are the two most conventionally used methods to estimate impervious surfaces at the subpixel scale in an urban area. However, LSMA lacks the sensitivity to pixel brightness, which leads to inter variability of endmembers and affects the ability to distinguish features with a similar spectral signature. This research aims to develop LSMA aided by a regression analysis model to estimate impervious surfaces with higher accuracy. A spectral angle mapping (SAM) based regression analysis model is introduced to reduce errors. Based on high-resolution images and field survey data, the SAM-based regression analysis can estimate non-impervious surface and high-impervious surface densities with high accuracy, while less accurate in impervious surfaces with low/medium density. In contrast, LSMA is able to estimate low/medium-density impervious surfaces with higher accuracy. We propose an improved approach by integrating the two methods, regression analysis aided LSMA, for impervious surface estimation. The proposed method increases the overall accuracy of the impervious surface estimation to 85.24%, which is significantly greater than that of the conventional methods. Numéro de notice : A2022-098 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2021.2018666 Date de publication en ligne : 05/01/2022 En ligne : https://doi.org/10.1080/22797254.2021.2018666 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99548 [article]

Landsat-based monitoring of southern pine beetle infestation severity and severity change in a temperate mixed forest / Ran Meng in Remote sensing of environment, vol 269 (February 2022)  

Public [article]  inRemote sensing of environment > vol 269 (February 2022) . - n° 112847 Titre : Landsat-based monitoring of southern pine beetle infestation severity and severity change in a temperate mixed forest Type de document : Article/Communication Auteurs : Ran Meng, Auteur ; Renjie Gao, Auteur ; Feng Zhao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] dépérissement [Termes IGN] forêt tempérée [Termes IGN] image Landsat-8 [Termes IGN] insecte nuisible [Termes IGN] mortalité [Termes IGN] peuplement mélangé [Termes IGN] Scolytinae [Termes IGN] signature spectrale [Termes IGN] surveillance forestière [Termes IGN] xylophage Résumé : (auteur) The recent northward expansion of Southern Pine Beetle (SPB) outbreaks associated with warming winters has caused extensive tree mortality in temperate pine forests, significantly affecting forest dynamics, structure, and functioning. Spatially-explicit early warning and detection of SPB-induced tree mortality is critical for timely and sustainable forest management practices. The unique contributions of remote sensing technologies to mapping the location, extent, and severity of beetle outbreaks, as well as assisting in analyzing the potential drivers for outbreak predictions, have been well recognized. However, little is known about the performance of moderate resolution satellite multispectral imagery for early warning and detection of SPB-induced tree mortality. Thus, we conducted this study, as the first attempt, to capture the spatial-temporal patterns of SPB infestation severity at the regional scale and to understand the underlying environmental drivers in a spatially-explicit manner. First, we explored the spectral signatures of SPB-killed trees based on 30-m plot measurements and Landsat-8 imagery. Then, to improve detection accuracy for areas with low-moderate SPB infestation severity, we added spectral-temporal anomaly information in the form of a linear trend of the spectral index trajectory to a previously developed approach. The best overall accuracy increased from 84.7% to 90.1% and the best Macro F1 value increased from 0.832 to 0.900. Next, we compared the performances of spectral indices in mapping SPB infestation severity (i.e., % red stage within the 30-m grid cell). The results showed that the combination of Normalized Difference Moisture Index and Tasseled Cap Greenness had the best performance for mapping SPB infestation severity (2016: R2 = 0.754; RSME = 15.7; 2017: R2 = 0.787; RSME = 12.4). Finally, we found that climatic and landscape variables can explain the detected patterns of SPB infestation from 2014 to 2017 in our study area (R2 = 0.751; RSME = 9.67), providing valuable insights on possible predictors for early warning of SPB infestation. Specifically, in our study area, winter dew point temperature was found to be one of the most important predictors, followed by SPB infestation locations in the previous year, canopy cover of host species, elevation, and slope. In the context of continued global warming, our study not only provides a novel framework for efficient, spatially-explicit, and quantitative measurements of forest damage induced by SPB infestation over large scales, but also uncovers opportunities to predict future SPB outbreaks and take precautions against it. Numéro de notice : A2022-096 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112847 Date de publication en ligne : 15/12/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112847 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99538 [article]

Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([06/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 2 [06/01/2022] . - pp 526 - 542 Titre : Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa Type de document : Article/Communication Auteurs : Mangana Rampheri, Auteur ; Timothy Dube, Auteur ; Inos Dhau, Auteur Année de publication : 2022 Article en page(s) : pp 526 - 542 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique du sud (état) [Termes IGN] arbre (flore) [Termes IGN] bande spectrale [Termes IGN] biodiversité végétale [Termes IGN] conservation de la flore [Termes IGN] détection de changement [Termes IGN] espèce végétale [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] indice de végétation [Termes IGN] régression [Termes IGN] réserve naturelle Résumé : (auteur) We use remotely sensed data to estimate species diversity in Blouberg Nature Reserve (BNR) in the Limpopo province, South Africa to understand the state of biodiversity since communities’ involvement in conservation initiatives. To achieve this objective, Landsat series data collected before and after community involvement in biodiversity conservation were used in conjunction with selected diversity indices i.e., Shannon-Wiener Index (H’) and Simpson Index (D). Thirty 15 m × 15 m field plots were selected and all trees within each plot were identified, with the help of Botanists. Further, we applied regression analysis to determine the relationship between satellite derived tree species diversity and field observations. The results of the study demonstrated a significant (p  Numéro de notice : A2022-052 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1080/10106049.2020.1723717 Date de publication en ligne : 16/04/2020 En ligne : https://doi.org/10.1080/10106049.2020.1723717 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99443 [article]

Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region / Paulo Victor N. Araújo in Natural Hazards and Earth System Sciences, vol 21 n° 11 (November 2021)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 21 n° 11 (November 2021) . - pp 3353 - 3366 Titre : Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region Type de document : Article/Communication Auteurs : Paulo Victor N. Araújo, Auteur ; Venerando E. Amaro, Auteur ; Leonlene S. Aguiar, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3353 - 3366 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Brésil [Termes IGN] carte thématique [Termes IGN] cartographie des risques [Termes IGN] changement climatique [Termes IGN] données lidar [Termes IGN] estuaire [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-OLI [Termes IGN] image Radarsat [Termes IGN] marée océanique [Termes IGN] modèle numérique de surface [Termes IGN] montée du niveau de la mer [Termes IGN] risque naturel [Termes IGN] submersion marine [Termes IGN] zone inondable [Termes IGN] zone semi-aride Résumé : (auteur) Previous studies on tidal flood mapping are mostly through continental- and/or global-scale approaches. Moreover, the few works on local-scale perception are concentrated in Europe, Asia, and North America. Here, we present a case study approaching a tidal flood risk mapping application in the face of climate change scenarios in a region with a strong environmental and social appeal. The study site is an estuarine cut in the Brazilian semi-arid region, covering part of two state conservation units, which has been suffering severe consequences from tidal flooding in recent years. In this case study, we used high-geodetic-precision data (lidar DEM), together with robust tidal return period statistics and data from current sea level rise scenarios. We found that approximately 327.60 km2 of the estuary is under tidal flood risk and in need of mitigation measures. This case study can serve as a basis for future management actions, as well as a model for applying risk mapping in other coastal areas. Numéro de notice : A2021-127 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.5194/nhess-21-3353-2021 Date de publication en ligne : 09/11/2021 En ligne : https://doi.org/10.5194/nhess-21-3353-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99321 [article]

Field scale wheat LAI retrieval from multispectral Sentinel 2A-MSI and LandSat 8-OLI imagery: effect of atmospheric correction, image resolutions and inversion techniques / Rajkumar Dhakar in Geocarto international, vol 36 n° 18 ([04/10/2021])  

Permalink

Spectral reflectance estimation of UAS multispectral imagery using satellite cross-calibration method / Saket Gowravaram in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

Permalink

Development of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)  

Permalink

The real potential of current passive satellite data to map aboveground biomass in tropical forests / Nidhi Jha in Remote sensing in ecology and conservation, vol 7 n° 3 (September 2021)  

Permalink

Spatiotemporal analysis of urban heat island intensification in the city of Minneapolis-St. Paul and Chicago metropolitan areas using Landsat data from 1984 to 2016 / Mbongowo J. Mbuh in Geocarto international, vol 36 n° 14 ([01/08/2021])  

Permalink

Detecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)  

Permalink

Evaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data / Asadollah Mirasi in Geocarto international, vol 36 n° 12 ([01/07/2021])  

Permalink

Multi-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images / Yanyan Gao in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

Permalink

Rapid ecosystem change at the southern limit of the Canadian Arctic, Torngat Mountains National Park / Emma L. Davis in Remote sensing, vol 13 n° 11 (June-1 2021)  

Permalink

The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries / Nagihan Aslan in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)  

Permalink