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Wall-to-wall mapping of forest biomass and wood volume increment in Italy / Francesca Giannetti in Forests, vol 13 n° 12 (December 2022)  

Public [article]  inForests > vol 13 n° 12 (December 2022) . - n° 1989 Titre : Wall-to-wall mapping of forest biomass and wood volume increment in Italy Type de document : Article/Communication Auteurs : Francesca Giannetti, Auteur ; Gherardo Chirici, Auteur ; Elia Vangi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1989 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne [Termes IGN] carte thématique [Termes IGN] écosystème forestier [Termes IGN] forêt méditerranéenne [Termes IGN] gestion forestière [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Italie [Termes IGN] puits de carbone [Termes IGN] volume en bois [Vedettes matières IGN] Foresterie Résumé : (auteur) Several political initiatives aim to achieve net-zero emissions by the middle of the twenty-first century. In this context, forests are crucial as a carbon sink to store unavoidable emissions. Assessing the carbon sequestration potential of forest ecosystems is pivotal to the availability of accurate forest variable estimates for supporting international reporting and appropriate forest management strategies. Spatially explicit estimates are even more important for Mediterranean countries such as Italy, where the capacity of forests to act as sinks is decreasing due to climate change. This study aimed to develop a spatial approach to obtain high-resolution maps of Italian forest above-ground biomass (ITA-BIO) and current annual volume increment (ITA-CAI), based on remotely sensed and meteorological data. The ITA-BIO estimates were compared with those obtained with two available biomass maps developed in the framework of two international projects (i.e., the Joint Research Center and the European Space Agency biomass maps, namely, JRC-BIO and ESA-BIO). The estimates from ITA-BIO, JRC-BIO, ESA-BIO, and ITA-CAI were compared with the 2nd Italian NFI (INFC) official estimates at regional level (NUT2). The estimates from ITA-BIO are in good agreement with the INFC estimates (R2 = 0.95, mean difference = 3.8 t ha−1), while for JRC-BIO and ESA-BIO, the estimates show R2 of 0.90 and 0.70, respectively, and mean differences of 13.5 and of 21.8 t ha−1 with respect to the INFC estimates. ITA-CAI estimates are also in good agreement with the INFC estimates (R2 = 0.93), even if they tend to be slightly biased. The produced maps are hosted on a web-based forest resources management Decision Support System developed under the project AGRIDIGIT (ForestView) and represent a key element in supporting the new Green Deal in Italy, the European Forest Strategy 2030 and the Italian Forest Strategy. Numéro de notice : A2022-864 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.3390/f13121989 Date de publication en ligne : 24/11/2022 En ligne : https://doi.org/10.3390/f13121989 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102156 [article]

Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series / Gherardo Chirici in Annals of Forest Science, Vol 77 n° 2 (June 2020)  

Public [article]  inAnnals of Forest Science > Vol 77 n° 2 (June 2020) Titre : Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Giannetti, Auteur ; Erica Mazza, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] brûlis [Termes IGN] canopée [Termes IGN] coupe rase (sylviculture) [Termes IGN] dégradation du signal [Termes IGN] forêt méditerranéenne [Termes IGN] image Landsat [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] reconstruction du signal [Termes IGN] régénération (sylviculture) [Termes IGN] série temporelle [Termes IGN] taillis [Termes IGN] télémètre laser aéroporté Résumé : (auteur) Key message: This work analyses the rate of recovery of the spectral signal from clearcut areas of coppice Mediterranean forests using Landsat Time Series (LTS). The analysis revealed a more rapid rate of spectral signal recovery than what was found in previous investigations in boreal and temperate forests. Context: The rate of post-disturbance vegetation recovery is an important component of forest dynamics. Aims: In this study, we analyze the recovery of the spectral signal from forest clearcut areas in Mediterranean conditions when the coppice system of forest management is applied. Methods: We used LTS surface reflectance data (1999–2015). We generated an annual reference database of clearcuts using visual interpretation and local forest inventory data, and then derived the Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR) spectral trajectories for these clearcuts. From these spectral trajectories, we calculated the Years to Recovery or Y2R, the number of years it takes for a pixel to return to within a specified threshold (i.e., 70%, 80%, 90%, 100%) of its pre-disturbance value. Spectral recovery rates were then corroborated using measures of canopy height derived from airborne laser scanning (ALS) data. Results: The coppice system is associated with rapid recovery rates when compared to rates of recovery from seeds or seedlings in temperate and boreal forest conditions. We found that the Y2R derived from the spectral trajectories of post-clearcut NBR and NDVI provided similar characterizations of rapid recovery for the coppice system of forest management applied in our study area. The ALS measures of canopy height indicated that the Y2R metric accurately captured the rapid regeneration of coppice systems. Conclusion: The rapid rate of spectral recovery associated with the coppice system is 2–4 years, which contrasts with values reported in boreal and temperate forest environments, where spectral recovery was attained in approximately 10 years. NBR is an effective index for assessing rapid recovery in this forest system. Numéro de notice : A2020-293 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00936-2 Date de publication en ligne : 15/04/2020 En ligne : https://doi.org/10.1007/s13595-020-00936-2 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95123 [article]

Assessing forest windthrow damage using single-date, post-event airborne laser scanning data / Gherardo Chirici in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)  

Public [article]  inForestry, an international journal of forest research > vol 91 n° 1 (January 2018) . - pp 27 - 37 Titre : Assessing forest windthrow damage using single-date, post-event airborne laser scanning data Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Bottalico, Auteur ; Francesca Giannetti, Auteur ; Barbara Del Perugia, Auteur ; Davide Travaglini, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 27 - 37 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre urbain [Termes IGN] dommage matériel [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] peuplement forestier [Termes IGN] tempête [Termes IGN] Toscane (Italie) [Termes IGN] zone urbaine Résumé : (Auteur) One of many possible climate change effects in temperate areas is the increase of frequency and severity of windstorms; thus, fast and cost efficient new methods are needed to evaluate wind-induced damages in forests. We present a method for assessing windstorm damages in forest landscapes based on a two-stage sampling strategy using single-date, post-event airborne laser scanning (ALS) data. ALS data are used for delineating damaged forest stands and for an initial evaluation of the volume of fallen trees. The total volume of fallen trees is then estimated using a two-stage model-assisted approach, where variables from ALS are used as auxiliary information in the difference estimator. In the first stage, a sample of the delineated forest stands is selected, and in the second stage the within-stand damages are estimated by means of line intercept sampling (LIS). The proposed method produces maps of windthrown areas, estimates of forest damages in terms of the total volume of fallen trees, and the uncertainty of the estimates. A case study is presented for a large windstorm that struck the Tuscany Region of Italy the night of the 4th and the 5th of March 2015 and caused extensive damages to trees in both forest and urban areas. The pure field-based estimates from LIS and the ALS-based estimates of stand-level fallen wood were very similar. Our positive results demonstrate the utility of the single-date approach for a fast assessment of windthrow damages in forest stands which is especially useful when pre-event ALS data are not available. Numéro de notice : A2018-630 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx029 Date de publication en ligne : 06/07/2017 En ligne : https://doi.org/10.1093/forestry/cpx029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93215 [article]

Modeling Mediterranean forest structure using airborne laser scanning data / Francesca Bottalico in International journal of applied Earth observation and geoinformation, vol 57 (May 2017)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 57 (May 2017) . - pp 145 - 153 Titre : Modeling Mediterranean forest structure using airborne laser scanning data Type de document : Article/Communication Auteurs : Francesca Bottalico, Auteur ; Gherardo Chirici, Auteur ; Raffaello Giannini, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 145 - 153 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse comparative [Termes IGN] complexité [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt méditerranéenne [Termes IGN] intervalle de confiance [Termes IGN] Italie [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) The conservation of biological diversity is recognized as a fundamental component of sustainable development, and forests contribute greatly to its preservation. Structural complexity increases the potential biological diversity of a forest by creating multiple niches that can host a wide variety of species. To facilitate greater understanding of the contributions of forest structure to forest biological diversity, we modeled relationships between 14 forest structure variables and airborne laser scanning (ALS) data for two Italian study areas representing two common Mediterranean forests, conifer plantations and coppice oaks subjected to irregular intervals of unplanned and non-standard silvicultural interventions. The objectives were twofold: (i) to compare model prediction accuracies when using two types of ALS metrics, echo-based metrics and canopy height model (CHM)-based metrics, and (ii) to construct inferences in the form of confidence intervals for large area structural complexity parameters. Our results showed that the effects of the two study areas on accuracies were greater than the effects of the two types of ALS metrics. In particular, accuracies were less for the more complex study area in terms of species composition and forest structure. However, accuracies achieved using the echo-based metrics were only slightly greater than when using the CHM-based metrics, thus demonstrating that both options yield reliable and comparable results. Accuracies were greatest for dominant height (Hd) (R2 = 0.91; RMSE% = 8.2%) and mean height weighted by basal area (R2 = 0.83; RMSE% = 10.5%) when using the echo-based metrics, 99th percentile of the echo height distribution and interquantile distance. For the forested area, the generalized regression (GREG) estimate of mean Hd was similar to the simple random sampling (SRS) estimate, 15.5 m for GREG and 16.2 m SRS. Further, the GREG estimator with standard error of 0.10 m was considerable more precise than the SRS estimator with standard error of 0.69 m. Numéro de notice : A2017-369 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2016.12.013 En ligne : https://doi.org/10.1016/j.jag.2016.12.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85787 [article]

Statistical inference for forest structural diversity indices using airborne laser scanning data and the k-Nearest Neighbors technique / Matteo Mura in Remote sensing of environment, vol 186 (1 December 2016)  

Public [article]  inRemote sensing of environment > vol 186 (1 December 2016) . - pp 678 - 686 Titre : Statistical inference for forest structural diversity indices using airborne laser scanning data and the k-Nearest Neighbors technique Type de document : Article/Communication Auteurs : Matteo Mura, Auteur ; Ronald E. McRoberts, Auteur ; Gherardo Chirici, Auteur ; Marco Marchetti, Auteur Année de publication : 2016 Article en page(s) : pp 678 - 686 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] classification barycentrique [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] indice de diversité [Termes IGN] inférence statistique [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Italie [Termes IGN] optimisation (mathématiques) [Termes IGN] structure d'un peuplement forestier Résumé : (auteur) Forest structural diversity plays a major role for forest management, conservation and restoration and is recognized as a fundamental aspect of forest biodiversity. The assessment, maintenance and restoration of a diversified forest structure have become major foci in the effort to preserve forest ecosystems from loss of biological diversity. However, the assessment of forest biodiversity is difficult because it involves multiple components and is characterized using multiple variables. The objective of the study was to develop a methodological approach for predicting, mapping, and constructing a statistical inference for a multiple-variable index of forest structural diversity. The method included three key components: (i) use of the k-Nearest Neighbors (k-NN) technique, field plot data, and airborne laser scanning metrics to predict multiple forest structural diversity variables simultaneously, (ii) incorporation of multiple diversity variable predictions into a single index, and (iii) construction of a statistically rigorous inference for the population mean of the index. Three structural diversity variables were selected to illustrate the method: growing stock volume and the standard deviations of tree diameter at breast-height and tree height. Optimization of the k-NN technique produced mean relative deviations less in absolute value than 0.04 for predictions for each of the three structural diversity variables, R2 values between 0.50 and 0.66 which were in the range of values reported in the literature, and a confidence interval for the population mean of the index whose half-width was approximately 5% of the mean. Finally, the spatial pattern depicted in the resulting map of forest structural diversity for the study area contributed to validating the proposed method. Numéro de notice : A2016-769 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.09.010 En ligne : http://dx.doi.org/10.1016/j.rse.2016.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82419 [article]

Testing the applicability of BIOME-BGC to simulate beech gross primary production in Europe using a new continental weather dataset / Marta Chiesi in Annals of Forest Science, vol 73 n° 3 (September 2016)  

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A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data / Gherardo Chirici in Remote sensing of environment, vol 176 (April 2016)  

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Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data / Ronald E. McRoberts in Remote sensing of environment, vol 115 n° 12 (december 2011)  

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