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Age-dependence of stand biomass in managed boreal forests based on the Finnish National Forest Inventory data / Anna Repo in Forest ecology and management, vol 498 (15 October 2021)  

Public [article]  inForest ecology and management > vol 498 (15 October 2021) . - n° 119507 Titre : Age-dependence of stand biomass in managed boreal forests based on the Finnish National Forest Inventory data Type de document : Article/Communication Auteurs : Anna Repo, Auteur ; Tuomas Rajala, Auteur ; Helena M. Henttonen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 119507 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bilan du carbone [Termes IGN] biomasse [Termes IGN] changement climatique [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] gestion forestière [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modélisation de la forêt [Termes IGN] puits de carbone [Termes IGN] tourbière [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Information on carbon stocks and the rate of carbon accumulation is needed to harness the climate change mitigation potential of boreal forests. While previous studies have revealed general patterns and mechanisms for age-dependence of stand biomass, simple stand-level models that address the age-biomass relationship on average in managed boreal forests in different environmental conditions are largely missing. We developed models for the relationship between stand age and biomass by forest types on peatlands and mineral soils across climate zones in managed forests in Finland based on National Forest Inventory measurements from 1996 to 2018. In addition, we analyzed at which rate biomass accumulates when managed forest ages in different growth conditions. In northern Finland the maximum biomass change rate was one third, and the maximum biomass stock less than half of the corresponding values in sub-xeric heath forests on minerals soils in southern Finland. On drained peatlands the maximum biomass growth rate was approximately half, and on undrained peatlands one third of the maximum growth rate on mineral soils. On most fertile sites on mineral soils the maximum biomasses were three times larger than on the poorest sites. Correspondingly, the maximum biomass stock change rates were almost eight times faster on most fertile sites. In the example cases presented, the highest annual biomass change rates were achieved in young forests on average at the stand ages of 7–32 years, whereas the 95% of the maximum stock were reached on average in stands of 63–147 years. At the age of highest biomass growth rate stands contained 27–59% of the maximum biomass stocks. The developed models can be used in practical applications such as accounting of biogenic carbon in life-cycle assessments, mapping carbon, or creating simple predictions of biomass stock development in regions, or estimating the mitigation potential of afforestation and reforestation or estimating the magnitude of carbon offsets projects. Numéro de notice : A2021-659 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119507 date de publication en ligne : 30/07/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119507 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98398 [article]

Application of feature selection methods and machine learning algorithms for saltmarsh biomass estimation using Worldview-2 imagery / Sikdar M. M. Rasel in Geocarto international, vol 36 n° 10 ([01/06/2021])  

Public [article]  inGeocarto international > vol 36 n° 10 [01/06/2021] . - pp 1075-1099 Titre : Application of feature selection methods and machine learning algorithms for saltmarsh biomass estimation using Worldview-2 imagery Type de document : Article/Communication Auteurs : Sikdar M. M. Rasel, Auteur ; Hsing-Chung Chang, Auteur ; Timothy J. Ralph, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1075-1099 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] bande spectrale [Termes IGN] biomasse [Termes IGN] classification par forêts aléatoires [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image multibande [Termes IGN] image Worldview [Termes IGN] marais salé [Termes IGN] modèle de simulation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] régression [Termes IGN] variable Résumé : (Auteur) Assessing large scale plant productivity of coastal marshes is essential to understand the resilience of these systems to climate change. Two machine learning approaches, random forest (RF) and support vector machine (SVM) regression were tested to estimate biomass of a common saltmarshes species, salt couch grass (Sporobolus virginicus). Reflectance and vegetation indices derived from 8 bands of Worldview-2 multispectral data were used for four experiments to develop the biomass model. These four experiments were, Experiment-1: 8 bands of Worldview-2 image, Experiment-2: Possible combination of all bands of Worldview-2 for Normalized Difference Vegetation Index (NDVI) type vegetation indices, Experiment-3: Combination of bands and vegetation indices, Experiment-4: Selected variables derived from experiment-3 using variable selection methods. The main objectives of this study are (i) to recommend an affordable low cost data source to predict biomass of a common saltmarshes species, (ii) to suggest a variable selection method suitable for multispectral data, (iii) to assess the performance of RF and SVM for the biomass prediction model. Cross-validation of parameter optimizations for SVM showed that optimized parameter of ɛ-SVR failed to provide a reliable prediction. Hence, ν-SVR was used for the SVM model. Among the different variable selection methods, recursive feature elimination (RFE) selected a minimum number of variables (only 4) with an RMSE of 0.211 (kg/m2). Experiment-4 (only selected bands) provided the best results for both of the machine learning regression methods, RF (R2= 0.72, RMSE= 0.166 kg/m2) and SVR (R2= 0.66, RMSE = 0.200 kg/m2) to predict biomass. When a 10-fold cross validation of the RF model was compared with a 10-fold cross validation of SVR, a significant difference (p = Numéro de notice : A2021-367 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1624988 date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1624988 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97729 [article]

Identifying the effects of chronic saltwater intrusion in coastal floodplain swamps using remote sensing / Elliott White Jr in Remote sensing of environment, vol 258 (June 2021)  

Public [article]  inRemote sensing of environment > vol 258 (June 2021) . - n° 112385 Titre : Identifying the effects of chronic saltwater intrusion in coastal floodplain swamps using remote sensing Type de document : Article/Communication Auteurs : Elliott White Jr, Auteur ; David Kaplan, Auteur Année de publication : 2021 Article en page(s) : n° 112385 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] eau de mer [Termes IGN] Enhanced vegetation index [Termes IGN] Floride (Etats-Unis) [Termes IGN] littoral [Termes IGN] Louisiane (Etats-Unis) [Termes IGN] marais [Termes IGN] Mexique (golfe du) [Termes IGN] montée du niveau de la mer [Termes IGN] salinité [Termes IGN] série temporelle Résumé : (auteur) Coastal floodplain swamps (CFS) are an important part of the coastal wetland mosaic, however they are threatened due to accelerated rates of sea level rise and saltwater intrusion (SWI). While remote sensing-based detection of wholesale coastal ecosystem shifts (i.e., from forest to marsh) are relatively straightforward, assessments of chronic, low-level SWI into CFS using remote sensing have yet to be developed and can provide a critical early-warning signal of ecosystem deterioration. In this study, we developed nine ecologically-based hypotheses to test whether remote sensing data could be used to reliably detect the presence of CFS experiencing SWI. Hypotheses were motivated by field- and literature-based understanding of the phenological and vegetative dynamics of CFS experiencing SWI relative to unimpacted, control systems. Hypotheses were organized into two primary groups: those that analyzed differences in summary measures (e.g., median and distribution) between SWI-impacted and unimpacted control sites and those that examined timeseries trends (e.g., sign and magnitude of slope). The enhanced vegetation index (EVI) was used as a proxy for production/biomass and was generated using MODIS surface reflectance data spanning 2000 to 2018. Experimental sites (n = 8) were selected from an existing network of long-term monitoring sites and included 4 pairs of impacted/non-impacted CFS across the northern Gulf of Mexico from Texas to Florida. The four best-supported hypotheses (81% across all sties) all used summary statistics, indicating that there were significant differences in the EVI of CFS experiencing chronic, low-level SWI compared to controls. These hypotheses were tested using data across a large and diverse region, supporting their implementation by researchers and managers seeking to identify CFS undergoing the first phases of SWI. In contrast, hypotheses that assessed CFS change over time were poorly supported, likely due to the slow and variable pace of ecological change, relatively short remote sensing data record, and/or specific site histories. Overall, these results show that remote sensing data can be used to identify differences in CFS vegetation associated with long-term, low-level SWI, but further methodological advancements are needed to reliably detect the temporal transition process. Numéro de notice : A2021-444 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112385 date de publication en ligne : 12/03/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112385 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97851 [article]

A GIS- and AHP-based approach to map fire risk: a case study of Kuan Kreng peat swamp forest, Thailand / Narissara Nuthammachot in Geocarto international, vol 36 n° 2 ([01/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 212 - 225 Titre : A GIS- and AHP-based approach to map fire risk: a case study of Kuan Kreng peat swamp forest, Thailand Type de document : Article/Communication Auteurs : Narissara Nuthammachot, Auteur ; Dimitris Stratoulias, Auteur Année de publication : 2021 Article en page(s) : pp 212 - 225 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] cartographie des risques [Termes IGN] climat [Termes IGN] forêt marécageuse [Termes IGN] historique des données [Termes IGN] incendie de forêt [Termes IGN] outil d'aide à la décision [Termes IGN] prévention des risques [Termes IGN] processus d'analyse hiérarchique [Termes IGN] Thaïlande [Termes IGN] tourbière Résumé : (auteur) Forest fires are abrupt transformations of the natural ecosystem and management authorities are required to take preventive measures to tackle fire events. Geographic information system (GIS) is a powerful tool for providing information with a spatial context and analytical hierarchy process (AHP) is a well-established technique for multiple criteria decision making. In this study, GIS and AHP are combined to analyse seven fire-related factors related to climate, topography and human influence. Fire risk for a peat swamp forested area in Kuan Kreng, Nakorn Sri Thammarat province, Thailand is estimated in five categories. 705 historic fire events from 2006 to 2017 are used to validate our approach. 82% of the historic fire incidents occurred within the highest fire risk class categories while only a few omission errors were recorded. The combined approach of GIS and AHP techniques can yield useful fire risk maps, which can consequently be used for future planning and management of fire prone areas. Numéro de notice : A2021-083 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1611946 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1611946 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96832 [article]

Drought propagation and its impact on groundwater hydrology of wetlands: a case study on the Doode Bemde nature reserve (Belgium) / Buruk Kitachew Wossenyeleh in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 21 n° 1 (January 2021) . - pp 39 - 51 Titre : Drought propagation and its impact on groundwater hydrology of wetlands: a case study on the Doode Bemde nature reserve (Belgium) Type de document : Article/Communication Auteurs : Buruk Kitachew Wossenyeleh, Auteur ; Kaleb Asnake Worku, Auteur ; Boud Verbeiren, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 39 - 51 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Belgique [Termes IGN] carte hydrographique [Termes IGN] données météorologiques [Termes IGN] eau souterraine [Termes IGN] hydrogéologie [Termes IGN] réserve naturelle [Termes IGN] sécheresse [Termes IGN] surveillance hydrologique [Termes IGN] zone humide Résumé : (auteur) Drought can be described as a temporary decrease in water availability over a significant period that affects both surface and groundwater resources. Droughts propagate through the hydrological cycle and may impact vulnerable ecosystems. This paper investigates drought propagation in the hydrological cycle, focusing on assessing its impact on a groundwater-fed wetland ecosystem. Meteorological drought indices were used to analyze meteorological drought severity. Moreover, a method for assessing groundwater drought and its propagation in the aquifer was developed and applied. Groundwater drought was analyzed using the variable threshold method. Furthermore, meteorological drought and groundwater drought on recharge were compared to investigate drought propagation in the hydrological cycle. This research is carried out in the Doode Bemde wetland in central Belgium. The results of this research show that droughts are attenuated in the groundwater system. The number and severity of drought events on groundwater discharge were smaller than for groundwater recharge. However, the onset of both drought events occurred at the same time, indicating a quick response of the groundwater system to hydrological stresses. In addition, drought propagation in the hydrological cycle indicated that not all meteorological droughts result in groundwater drought. Furthermore, this drought propagation effect was observed in the wetland. Numéro de notice : A2021-133 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/nhess-21-39-2021 date de publication en ligne : 08/01/2021 En ligne : https://doi.org/10.5194/nhess-21-39-2021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96994 [article]

Polarimetric Synthetic Aperture Radar / Irena Hajnsek (2021)  

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Boreal peatland forests: ditch network maintenance effort and water protection in a forest rotation framework / Jenny Miettinen in Canadian Journal of Forest Research, vol 50 n° 10 (October 2020)  

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Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data / Yaotong Cai in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)  

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Uncertainty of forested wetland maps derived from aerial photography / Stephen P. Prisley in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)  

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Wide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 / Dirk Hoekman in Remote sensing, vol 12 n° 19 (October 2020)  

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Long time-series remote sensing analysis of the periodic cycle evolution of the inlets and ebb-tidal delta of Xincun Lagoon, Hainan Island, China / Huaguo Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)  

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Using spectral indices to estimate water content and GPP in sphagnum moss and other peatland vegetation / Kirsten J. Lees in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)  

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Profitability of growing Scots pine on cutaway peatlands / Lasse Aro in Silva fennica, vol 54 n° 3 (June 2020)  

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Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database / Collin Homer in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

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A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions / Shahryar K. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

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