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Historical aerial images, captured by film cameras in the previous century, are valuable resources for quantifying Earth's surface and landscape changes over time. In the post-war period, these images were often acquired to create topographic maps, resulting in the acquisition of large-scale aerial photographs with stereo coverage. Photogrammetric techniques applied to these stereo images enable the extraction of 3D information to reconstruct digital surface models (DSMs) and orthoimages. Here, we present a highly automated photogrammetric approach for generating countrywide DSMs of Switzerland, at a 1 m resolution, from approximately 40,000 scanned aerial stereo images acquired between 1979 and 2006, with known exterior and interior orientation. We derived four countrywide DSMs for the epochs 1979–1985, 1985–1991, 1991–1998, and 1998–2006. From the DSMs, we generated corresponding countrywide vegetation height models (VHMs). We assessed the quality of the historical DSMs at the country scale and within six representative study sites, evaluating the vertical accuracy and the completeness of image-matching across different land cover types. Mean completeness ranged from 64 % for 'glacial and perpetual snow' to 98 % for 'sealed surfaces', with a value of 93 % for the 'closed forest' class. Across Switzerland, the median elevation accuracy of the historical DSMs compared with a reference digital terrain model (DTM) on sealed surface points ranged from 0.28 to 0.53 m, with a normalised median absolute deviation (NMAD) of around 1 m and a maximum root mean square error (RMSE) of 3.90 m. The same analysis between geodetic points and historical DSMs showed higher accuracies, with median values of ≤ 0.05 m and an NMAD < 1 m. The VHMs generated in this study enabled the detection of major changes in forest areas due to windstorm damage, forest dynamics, and growth. This work demonstrates the feasibility of generating accurate, very high-resolution DSM time series (spanning three decades) and VHMs from historical aerial images of the entire surface of Switzerland in a highly automated manner. The VHMs are already being used to estimate countrywide biomass changes. The countrywide DSMs and VHMs for the four epochs, along with auxiliary data, are available online at https://doi.org/10.16904/envidat.528 (Marty et al., 2024) and can be used to quantify long-term elevation changes and related processes across different surfaces. [ABSTRACT FROM AUTHOR]

Forest structure reflects the forest disturbance regime and can provide important information about the rate of human impact. A better understanding of the structural variability and large-scale dynamics of natural forests is crucial for 'close to nature' forest management planning. In this study, we developed a partly automated approach to assess the structure of potential primeval and managed beech forests in the Ukrainian Carpathians using WorldView-2 imagery. We analyzed the local (50 m x 50 m scale) canopy closure of these forests by extracting the canopy gaps and determined four forest structure types ranging from very closed to low density. The occurrence and frequencies of these structure types were significantly different in the primeval and managed beech forests. The four forest structure types were predicted and mapped using multinomial logistic regression based on the textural features derived from the original image bands and two vegetation indices. A 10-fold crossvalidation resulted in an overall accuracy of 83% and a kappa coefficient of 75%, with the highest agreement for the very closed structure type (87%) and the lowest agreement for the medium density and low density structure types (79%). The forest structure type maps can be helpful for planning management activities in beech forests. Key words: beech forests, structure types, canopy gap fraction, WorldView-2, Carpathian region. La structure forestiere reflete le regime de perturbation de la foret et peut fournir d'importantes informations au sujet du taux d'impact humain. Il est crucial d'avoir une meilleure comprehension de la variabilite structurale et de la dynamique a grande echelle des forets naturelles pour planifier une sylviculture dite ecologique. Dans cette etude, nous avons developpe une approche partiellement automatisee pour evaluer la structure des hetraies possiblement vierges ou amenagees dans les Carpates ukrainiennes a l'aide d'images du satellite WorldView-2. Nous avons analyse la fermeture du couvert forestier localement (echelle de 50 m x 50 m) en faisant abstraction des trouees dans le couvert et en determinant quatre types de structures forestieres allant de tres fermee a faible densite. L'occurrence et la frequence de ces types de structures etaient significativement differentes dans les hetraies vierges et amenagees. Les quatre types de structures forestieres ont ete predits et cartographies a l'aide de la regression logistique multinomiale sur la base des caracteristiques texturales derivees des bandes d'images originales et de deux indices de vegetation. Une validation croisee repetee a 10 fois a donne une precision globale de 83 % et un coefficient kappa de 75 %; la structure la plus fermee avait le taux de concordance le plus eleve (87 %) et les structures de densites moyenne et faible avait le taux de concordance le plus faible (79 %). Les cartes illustrant les types de structures forestieres peuvent etre utiles pour planifier les travaux sylvicoles dans les hetraies. [Traduit par la Redaction] Mots-cles: hetraies, types de structures, fraction de trouee, WorldView-2, region des Carpates., 1. Introduction Beech forests are a potentially natural vegetation type in European temperate forests and one of the dominant forest ecosystems in the Carpathian mountain region. In the Ukrainian Carpathians, [...]

Mangrove forests, as an essential component of the coastal zones in tropical and subtropical areas, provide a wide range of goods and ecosystem services that play a vital role in ecology. Mangroves are globally threatened, disappearing, and degraded. Consequently, knowledge on mangroves distribution and change is important for effective conservation and making protection policies. Developing remote sensing data and classification methods have proven to be suitable tools for mapping mangrove forests over a regional scale. Here, we scrutinized and compared the performance of pixel-based and object-based methods under Support Vector Machine (SVM) and Random Forest (RF) algorithms in mapping a mangrove ecosystem into four main classes (Mangrove tree, mudflat, water, and sand spit) using resampled and fused Sentinel-2 images. Additionally, landscape metrics were used to identify the differences between spatial patterns obtained from different classification methods. Results showed that pixel-based classifications were influ-enced heavily by the effect of salt and pepper noise, whereas in object-based classifications, boundaries of land use land cover (LULC) polygons were smoother and visually more appealing. Object-based classifications, with an excellent level of kappa, distinguished mudflat and sand spit from each other and from mangrove better than the pixel-based classifications which obtained a fair-to-good level of kappa. RF and SVM performed differently under comparable circumstances. The results of landscape metrics comparison presented that the classification methods can be affected on quantifying area and size metrics. Although the results supported the idea that fused Sentinel images may provide better results in mangrove LULC classification, further research needs to develop and evaluate various image fusion approaches to make use of all Sentinel's fine resolution images. Our results on the mapping of mangrove ecosystems can contribute to the improvement of management and conservation strategies for these ecosystems being impacted by human activities. [ABSTRACT FROM AUTHOR]

Current technical advances in the field of digital photogrammetry demonstrate the great potential of automatic image matching for deriving dense surface measurements of the forest canopy. In contrast to airborne laser scanning (ALS), aerial stereo images are updated more regularly by national or regional mapping agencies in several countries. Frequently, ALS-based terrain models (DTMs) are available, and thus photogrammetric canopy heights can be derived. However, currently, there is little knowledge as to how accurately forest attributes can be modeled using the aerial stereo images acquired by these official, regular aerial surveys, especially for mixed forests in central Europe. Thus, a photogrammetric point cloud derived from UltraCamX stereo images in combination with an ALS-DTM and a classification of coniferous and deciduous tree regions (based on ortho-images) was used to create a stratified estimation of timber volume and basal area in a mixed forest in Germany. Suitable models were derived at the plot level using explanatory variables from the photogrammetric point cloud (which was normalized using an ALS-DTM). The prior stratification of conifer- and deciduous-dominated field plots slightly improved the estimation accuracy. The results verify that stereo images can be an alternative to ALS data for modeling key forest attributes, even in mixed central European forests with complex structure. Resume: Les avancees technologiques actuelles dans le domaine de la photogrammetrie numerique demontrent le fort potentiel du recalage automatique d'images pour deriver des mesures de la surface dense du couvert forestier. Contrairement au balayage laser aeroporte (BLA), les images stereoscopiques aeriennes sont mises a jour plus regulierement par des organismes nationaux ou regionaux de cartographie dans plusieurs pays. Les modeles numeriques de terrain fondes sur le BLA (MNT-BLA) sont souvent disponibles et les hauteurs photogrammetriques du couvert forestier peuvent etre ainsi derivees. Toutefois, il existe actuellement peu de connaissances quant a la precision des attributs forestiers pouvant etre modelises a l'aide d'images stereoscopiques aeriennes acquises regulierement par ces releves aeriens officiels, en particulier pour les forets melangees de l'Europe centrale. Ainsi, un nuage photogrammetrique de points (derive d'images stereoscopiques UltraCamX), combine a un MNT-BLA et une classification des regions occupees par des coniferes ou des feuillus etablie a l'aide d'orthoimages, a ete utilise pour obtenir une estimation stratifiee du volume de bois et de la surface terriere dans une foret melangee en Allemagne. Des modeles appropries ont ete obtenus a l'echelle de la placette a l'aide de variables explicatives tirees du nuage photogramme-trique de points qui avait ete normalise a l'aide du MNT-BLA. La stratification a priori des placettes dominees par des coniferes ou par des feuillus a legerement ameliore la precision de l'estimation. Les resultats confirment que les images stereoscopiques peuvent remplacer les donnees obtenues par BLA pour modeliser les attributs cles de la foret, meme dans les forets melangees a structure complexe de l'Europe centrale. [Traduit par la Redaction], Introduction The requirements for national and regional forest inventories have changed in recent decades, along with the methods of data acquisition involved. Timber volume and basal area are forest attributes [...]

Essential forest ecosystem services can be assessed by better understanding the diversity of vegetation, specifically those of Mediterranean region. A species level classification of maquis would be useful in understanding vegetation structure and dynamics, which would be an indicator of degradation or succession in the region. Although remote sensing was regularly used for classification in the region, maquis are simply represented as one to three categories based on density or height. To fill this gap, we test the capability of Sentinel-2 imagery, together with selected ancillary variables, for an accurate mapping of the dominant maquis formations. We applied Recursive Feature Selection procedure and used a Random Forest classifier. The algorithm is tested using ground truth collected from site and reached 78% and 93% overall accuracy at species level and physiognomic level, respectively. Our results suggest species level characterization of dominant maquis is possible with Sentinel-2 spatial resolution. [ABSTRACT FROM AUTHOR]