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Use of visible and near-infrared reflectance spectroscopy models to determine soil erodibility factor (K) in an ecologically restored watershed / Qinghu Jiang in Remote sensing, vol 12 n° 18 (September-2 2020)
[article]
Titre : Use of visible and near-infrared reflectance spectroscopy models to determine soil erodibility factor (K) in an ecologically restored watershed Type de document : Article/Communication Auteurs : Qinghu Jiang, Auteur ; Yiyun Chen, Auteur ; Jialiang Hu, Auteur ; Feng Liu, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] bassin hydrographique
[Termes IGN] érosion
[Termes IGN] étalonnage de modèle
[Termes IGN] image proche infrarouge
[Termes IGN] image visible
[Termes IGN] réflectance spectrale
[Termes IGN] régression des moindres carrés partiels
[Termes IGN] sol arable
[Termes IGN] spectroscopie
[Termes IGN] surface cultivée
[Termes IGN] utilisation du solRésumé : (auteur) This study aimed to assess the ability of using visible and near-infrared reflectance (Vis–NIR) spectroscopy to quantify soil erodibility factor (K) rapidly in an ecologically restored watershed. To achieve this goal, we explored the performance and transferability of the developed spectral models in multiple land-use types: woodland, shrubland, terrace, and slope farmland (the first two types are natural land and the latter two are cultivated land). Subsequently, we developed an improved approach by combining spectral data with related topographic variables (i.e., elevation, watershed location, slope height, and normalized height) to estimate K. The results indicate that the calibrated spectral model using total samples could estimate K factor effectively (R2CV = 0.71, RMSECV = 0.0030 Mg h Mj−1 mm−1, and RPDCV = 1.84). When predicting K in the new samples, models performed well in natural land soils (R2P = 0.74, RPDP = 1.93) but failed in cultivated land soils (R2P = 0.24, RPDP = 0.99). Furthermore, the developed models showed low transferability between the natural and cultivated land datasets. The results also indicate that the combination of spectral data with topographic variables could slightly increase the accuracies of K estimation in total and natural land datasets but did not work for cultivated land samples. This study demonstrated that the Vis–NIR spectroscopy could be used as an effective method in predicting K. However, the predictability and transferability of the calibrated models were land-use type dependent. Our study also revealed that the coupling of spectrum and environmental variable is an effective improvement of K estimation in natural landscape region Numéro de notice : A2020-631 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12183103 Date de publication en ligne : 22/09/2020 En ligne : https://doi.org/10.3390/rs12183103 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96052
in Remote sensing > vol 12 n° 18 (September-2 2020) . - 16 p.[article]Ancient forest statistics provide centennial perspective over the status and dynamics of forest area in France / Timothée Audinot in Annals of Forest Science, vol 77 n° 3 (September 2020)
[article]
Titre : Ancient forest statistics provide centennial perspective over the status and dynamics of forest area in France Type de document : Article/Communication Auteurs : Timothée Audinot , Auteur ; Holger Wernsdörfer, Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2020 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] carte forestière
[Termes IGN] changement d'utilisation du sol
[Termes IGN] forêt de haute futaie
[Termes IGN] forêt privée
[Termes IGN] forêt publique
[Termes IGN] France (administrative)
[Termes IGN] politique forestière
[Termes IGN] surface forestière
[Termes IGN] taillis
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message: Centenary forest statistics informing major attributes of French forests were digitized, checked for consistency, and used to infer forest dynamics. Comparison to forest inventory data highlights increases in forest area and tree diversity, and substantial maturation of forests. Dataset access at https://doi.org/10.5281/zenodo.3739458
Context: The history of European forest dynamic remains fragmental. In France, the Daubrée statistics (1908) and agricultural statistics (1892, 1929) formed fundamental material to fill this gap.
Aims: Release, test, and summarize the digitalized dataset. Analyze long-term forest changes in forest area, composition, and structure.
Methods: Primary data on forest area across NUTS-3 geographic units, split by forest management and ownership categories and dominating tree species (Daubrée), were digitized and cross-compared. Centennial changes in forest attributes were assessed from modern forest inventory data.
Results: Cross-comparison revealed: (1) strong temporal consistency in forest changes over time, (2) systematic and interpretable biases in ownership/management categories between Daubrée and agricultural statistics. Strong shift from coppices to high forests, increased prevalence of private ownership, and constant proportion of broadleaf- and conifer-dominated forests were highlighted, with increased tree species diversity at country scale.
Conclusion: Ancient statistics are shown to play a major role in retrospective land-use and forest policy analysis.Numéro de notice : A2020-593 Affiliation des auteurs : LIF+Ext (2012-2019) Autre URL associée : vers HAL ouvert Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00987-5 Date de publication en ligne : 05/08/2020 En ligne : https://hal.science/hal-03317972v1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95928
in Annals of Forest Science > vol 77 n° 3 (September 2020) . - 24 p.[article]Assessing local trends in indicators of ecosystem services with a time series of forest resource maps / Matti Katila in Silva fennica, vol 54 n° 4 (September 2020)
[article]
Titre : Assessing local trends in indicators of ecosystem services with a time series of forest resource maps Type de document : Article/Communication Auteurs : Matti Katila, Auteur ; Tuomas Rajala, Auteur ; Annika S. Kangas, Auteur Année de publication : 2020 Article en page(s) : n° 10347 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte forestière
[Termes IGN] classification barycentrique
[Termes IGN] données de terrain
[Termes IGN] Finlande
[Termes IGN] image satellite
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] ressources forestières
[Termes IGN] série temporelle
[Termes IGN] service écosystémique
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Since the 1990’s, forest resource maps and small area estimates have been produced by combining national forest inventory (NFI) field plot data, optical satellite images and numerical map data using a non-parametric k-nearest neighbour method. In Finland, thematic maps of forest variables have been produced by the means of multi-source NFI (MS-NFI) for eight to ten times depending on the geographical area, but the resulting time series have not been systematically utilized. The objective of this study was to explore the possibilities of the time series for monitoring the key ecosystem condition indicators for forests. To this end, a contextual Mann-Kendall (CMK) test was applied to detect trends in time-series of two decades of thematic maps. The usefulness of the observed trends may depend both on the scale of the phenomena themselves and the uncertainties involved in the maps. Thus, several spatial scales were tested: the MS-NFI maps at 16 × 16 m2 pixel size and units of 240 × 240 m2, 1200 × 1200 m2 and 12 000 × 12 000 m2 aggregated from the MS-NFI map data. The CMK test detected areas of significant increasing trends of mean volume on both study sites and at various unit sizes except for the original thematic map pixel size. For other variables such as the mean volume of tree species groups, the proportion of broadleaved tree species and the stand age, significant trends were mostly found only for the largest unit size, 12 000 × 12 000 m2. The multiple testing corrections decreased the amount of significant p-values from the CMK test strongly. The study showed that significant trends can be detected enabling indicators of ecosystem services to be monitored from a time-series of satellite image-based thematic forest maps. Numéro de notice : A2020-791 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14214/sf.10347 Date de publication en ligne : 14/09/2020 En ligne : https://doi.org/10.14214/sf.10347 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96562
in Silva fennica > vol 54 n° 4 (September 2020) . - n° 10347[article]Combining optical and radar satellite image time series to map natural vegetation: savannas as an example / Maylis Lopes in Remote sensing in ecology and conservation, vol 6 n° 3 (September 2020)
[article]
Titre : Combining optical and radar satellite image time series to map natural vegetation: savannas as an example Type de document : Article/Communication Auteurs : Maylis Lopes, Auteur ; Pierre-Louis Frison , Auteur ; Sarah Durante, Auteur ; Henrike Schulte To Bühne, Auteur ; Audrey Ipavec, Auteur ; Vincent Lapeyre, Auteur ; Nathalie Pettorelli, Auteur Année de publication : 2020 Article en page(s) : pp 316 - 326 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aire protégée
[Termes IGN] Bénin
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de la végétation
[Termes IGN] écosystème
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] protection de l'environnement
[Termes IGN] protection de la biodiversité
[Termes IGN] savane
[Termes IGN] série temporelleRésumé : (auteur) Up-to-date land cover maps are important for biodiversity monitoring as they are central to habitat and ecosystem distribution assessments. Satellite remote sensing is a key technology for generating these maps. Until recently, land cover mapping has been limited to static approaches, which have primarily led to the production of either global maps at coarse spatial resolutions or geographically restricted maps at high spatial resolutions. The recent availability of optical (Sentinel-2) and radar (Sentinel-1) satellite image time series (SITS) which provide access to high spatial and very high temporal resolutions, is a game changer, offering opportunities to map land cover using both temporal and spatial information. These data moreover open interesting perspectives for land cover mapping based on data combination approach. However, the usefulness of combining dense time series (more than 30 images per year) and data combination approaches to map natural vegetation has so far not been assessed. To address this gap, this contribution tests the idea that the combined consideration of optical and radar data combination and time series analyses can significantly improve natural vegetation mapping in the Pendjari National Park, a Sahelian savanna protected area in Benin. Results highlight that the combination of Sentinel-1 and Sentinel-2 SITS performs as well as Sentinel-2 SITS alone in terms of classification accuracy. Land cover maps are however qualitatively better when considering the data combination approach. Our results also clearly show that the use of dense/hypertemporal optical time series significantly improves classification outcomes compared to using multitemporal only a few images per year) or monotemporal data. Altogether, this work thus demonstrates the ability of dense SITS to improve discrimination of natural vegetation types using information on their phenology, leading to more detailed and more reliable maps for environmental management. Numéro de notice : A2020-871 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : BIODIVERSITE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1002/rse2.139 Date de publication en ligne : 17/01/2020 En ligne : https://doi.org/10.1002/rse2.139 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99584
in Remote sensing in ecology and conservation > vol 6 n° 3 (September 2020) . - pp 316 - 326[article]Comparison of tree-based classification algorithms in mapping burned forest areas / Dilek Kucuk Matci in Geodetski vestnik, vol 64 n° 3 (September - November 2020)
[article]
Titre : Comparison of tree-based classification algorithms in mapping burned forest areas Type de document : Article/Communication Auteurs : Dilek Kucuk Matci, Auteur ; Resul Comert, Auteur ; Ugur Avdan, Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Slovène (slv) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] analyse d'image orientée objet
[Termes IGN] bassin méditerranéen
[Termes IGN] carte forestière
[Termes IGN] classification dirigée
[Termes IGN] classification par arbre de décision
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Landsat-8
[Termes IGN] incendie de forêt
[Termes IGN] matrice de confusion
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] Rotation Forest classification
[Termes IGN] Turquie
[Termes IGN] zone sinistréeRésumé : (auteur) In this study, we compared the performance of tree-based classification algorithms – Random Forest (RF), Rotation Forest (RotF), J48, The Alternating Decision Tree (ADTree), Forest by Penalising Attributes (Forest PA), Logical Analysis of Data Algorithm (LADTree) and Functional Trees (FT) – for mapping burned forest areas within the Mediterranean region in Turkey. Object-based image analysis (OBIA) was performed to pan-sharpened the Landsat 8 images. Four different burned areas, namely Kumluca, Adrasan, Anamur, and Alanya, were used as study areas. Kumluca, Anamur, and Alanya regions were used as training areas, and Adrasan region was used as the test area. Obtained results were evaluated with confusion matrix and statistically significant analysis. According to the results, FT and RotF produced more accurate results than other algorithms. Also, the results obtained with these algorithms are statistically significant. Numéro de notice : A2020-626 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.15292/geodetski-vestnik.2020.03.348-360 Date de publication en ligne : 23/08/2020 En ligne : https://doi.org/10.15292/geodetski-vestnik.2020.03.348-360 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96087
in Geodetski vestnik > vol 64 n° 3 (September - November 2020) . - 13 p.[article]Réservation
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