An approach for comparing agricultural development to societal visions

There is broad agreement that agriculture has to become more sustainable in order to provide enough affordable, healthy food at minimal environmental and social costs. But what is “more sustainable”? More often than not, different stakeholders have opposing opinions on what a more sustainable future should look like. This normative dimension is rarely explicitly addressed in sustainability assessments. In this study, we present an approach to assess the sustainability of agricultural development that explicitly accounts for the normative dimension by comparing observed development with various societal visions. We illustrate the approach by analyzing farm- and landscape-scale development as well as sustainability outcomes in a Swiss case study landscape. Observed changes were juxtaposed with desired changes by Avenir Suisse, a liberal think tank representing free-market interests; the Swiss Farmers Association, representing a conservative force; and Landwirtschaft mit Zukunft, an exponent of the Swiss agroecological movement. Overall, the observed developments aligned most closely with desired developments of the liberal think-tank (72%). Farmer interviews revealed that in the case study area farms increased in size (+ 57%) and became more specialized and more productive (+ 223%) over the past 20 years. In addition, interpretation of aerial photographs indicated that farming became more rationalized at the landscape level, with increasing field sizes (+ 34%) and removal of solitary field trees (− 18%). The case study example highlights the varying degrees to which current developments in agriculture align with societal visions. By using societal visions as benchmarks to track the progress of agricultural development, while explicitly addressing their narratives and respective systems of values and norms, this approach offers opportunities to inform also the wider public on the extent to which current developments are consistent with different visions. This could help identify mismatches between desired and actual development and pave the way for designing new policies.

Late Quaternary Marine Terraces and Tectonic Uplift Rates of the Broader Neapolis Area (SE Peloponnese, Greece)

Marine terraces are geomorphic markers largely used to estimate past sea-level positions and surface deformation rates in studies focused on climate and tectonic processes worldwide. This paper aims to investigate the role of tectonic processes in the late Quaternary evolution of the coastal landscape of the broader Neapolis area by assessing long-term vertical deformation rates. To document and estimate coastal uplift, marine terraces are used in conjunction with Optically Stimulated Luminescence (OSL) dating and correlation to late Quaternary eustatic sea-level variations. The study area is located in SE Peloponnese in a tectonically active region. Geodynamic processes in the area are related to the active subduction of the African lithosphere beneath the Eurasian plate. A series of 10 well preserved uplifted marine terraces with inner edges ranging in elevation from 8 ± 2 m to 192 ± 2 m above m.s.l. have been documented, indicating a significant coastal uplift of the study area. Marine terraces have been identified and mapped using topographic maps (at a scale of 1:5000), aerial photographs, and a 2 m resolution Digital Elevation Model (DEM), supported by extensive field observations. OSL dating of selected samples from two of the terraces allowed us to correlate them with late Pleistocene Marine Isotope Stage (MIS) sea-level highstands and to estimate the long-term uplift rate. Based on the findings of the above approach, a long-term uplift rate of 0.36 ± 0.11 mm a−1 over the last 401 ± 10 ka has been suggested for the study area. The spatially uniform uplift of the broader Neapolis area is driven by the active subduction of the African lithosphere beneath the Eurasian plate since the study area is situated very close (~90 km) to the active margin of the Hellenic subduction zone.

Inventory and classification of the post Little Ice Age glacial lakes in Svalbard

Rapid changes of glacial lakes are among the most visible indicators of global warming in glacierized areas around the world. The general trend is that the area and number of glacial lakes increase significantly in high mountain areas and polar latitudes. However, there is a lack of knowledge about the current state of glacial lakes in the High Arctic. This study aims to address this issue by providing the first glacial lake inventory from Svalbard, with focus on the genesis and evolution of glacial lakes since the end of the Little Ice Age. We use aerial photographs and topographic data from 1936 to 2012 and satellite imagery from 2013 to 2020. The inventory includes the development of 566 glacial lakes (total area of 145.91 km2) that were in direct contact with glaciers in 2008–2012. From the 1990s to the end of the 2000s, the total glacial lake area increased by nearly a factor of six. A decrease in the number of lakes between 2012 and 2020 is related to two main processes: the drainage of 197 lakes and the merger of smaller reservoirs into larger ones. The changes of glacial lakes show how climate change in the High Arctic affect proglacial geomorphology by enhanced formation of glacial lakes, leading to higher risks associated with glacier lake outburst floods in Svalbard.

Human vs. Machine, the Eyes Have It. Assessment of Stemphylium Leaf Blight on Onion Using Aerial Photographs from an NIR Camera

Aerial surveillance could be a useful tool for early detection and quantification of plant diseases, however, there are often confounding effects of other types of plant stress. Stemphylium leaf blight (SLB), caused by the fungus Stemphylium vesicarium, is a damaging foliar disease of onion. Studies were conducted to determine if near-infrared photographic images could be used to accurately assess SLB severity in onion research trials in the Holland Marsh in Ontario, Canada. The site was selected for its uniform soil and level topography. Aerial photographs were taken in 2015 and 2016 using an Xnite-Canon SX230NDVI with a near-infrared filter, mounted on a modified Cine Star—8 MK Heavy Lift RTF octocopter UAV. Images were taken at 15–20 m above the ground, providing an average of 0.5 cm/pixel and a field of view of 15 × 20 m. Photography and ground assessments of disease were carried out on the same day. NDVI (normalized difference vegetation index), green NDVI, chlorophyll index and plant senescence reflective index (PSRI) were calculated from the images. There were differences in SLB incidence and severity in the field plots and differences in the vegetative indices among the treatments, but there were no correlations between disease assessments and any of the indices.

UAV survey of sand knolls in the Tsasucheysky Bor Nature Reserve

The paper examines development of sand knolls under the influence of climatic and anthropogenic factors in Southern Zabaykalye within the territory of Tsasucheysky Bor nature reserve. The sand knolls were studied on-site with instruments and aerial surveying. Grain size distribution of the soil cover was studied. The floristic composition of the sand knolls represented by motley grass-grasses and herbs-grasses steppe communities with varying degrees of projective cover was investigated. The analysis of the field survey data from an unmanned aerial vehicle (UAV) made it possible to obtain the main morphometric parameters of the sand knolls, and overlaying aerial photographs on historic satellite images allowed to trace how they changed in time. The studies showed that the movement of the studied sand knolls with time as Aeolian formations under the influence of wind erosion is unlikely, as the sand knolls are currently mostly covered by steppe vegetation, and only about 20% of the areas are bare. The analysis of satellite images and aerial photographs showed that over the last twenty years the sand knolls had not moved or changed their size.

Evaluating critiques of evidence of historically heterogeneous structure and mixed-severity fires across dry-forest landscapes of the western USA

The structure and role of fire in historical dry forests, ponderosa pine (Pinus ponderosa) and dry mixed-conifer forests, of the western USA, have been debated for 25 years, leaving two theories. The first, that these forests were relatively uniform, low in tree density and dominated by low- to moderate-severity fires was recently reviewed, including a critique of opposing evidence. The second, that these forests historically had heterogeneous structure and a mixture of fire severities, has had several published reviews. Here, as authors in part of the second theory, we critically examined evidence in the first theory’s new review, which presented 37 critiques of the second theory. We examined evidence for and against each critique, including evidence presented or omitted. We found that a large body of published evidence against the first theory and supporting the second theory, presented in 10 published rebuttals and 25 other published papers, by us and other scientists, was omitted and not reviewed. We reviewed omitted evidence here. Omitted evidence was extensive, and included direct observations by early scientists, maps in early forest atlases, early newspaper accounts and photographs, early aerial photographs, seven paleo-charcoal reconstructions, ≥18 tree-ring reconstructions, eight land-survey reconstructions, and an analysis of forest-inventory age data. This large body of omitted published research provides compelling evidence supporting the second theory, that historical dry forests were heterogeneous in structure and had a mixture of fire severities, including high-severity fire. The first theory is rejected by this large body of omitted evidence.

A Study on the Usability of Open Spatial Data for Road Network-Based Analysis – Using Openstreetmap as an Example

For several years GIS software users could use for any purpose a dataset being to some extent an alternative to both products offered by commercial providers and official databases. It is OpenStreetMap (OSM for short) – a worldwide spatial dataset, created and edited by interested individuals and available for use by anyone with no limitations. It is built on the basis of data recorded with consumer grade GPS receivers, obtained through vectorization of aerial photographs and from other usable sources, including even sketches made in the field. The collected information is stored in a central database, the content of which is not only presented on the website as a digital map, but also offered for download as vector data. Such data can be used for, among other things, performing various analyses based on road networks, of which the most frequently used is the function of determining the optimal route connecting selected locations. The results of such analyses can only be considered reliable if the data used are of adequate quality. As the OSM database is built by enthusiasts, no plans for its systematic development are formulated and there are no built-in quality control mechanisms. Therefore, the paper proposes methods and tools to verify the usefulness of the data collected so far, as well as to correct detected errors. It focuses on the following categories of geographic data quality: location accuracy, topological consistency and temporal validity. In addition, a problem with determining the length of individual road network segments was noticed, related to data acquisition methods and ways of recording the shape of lines. Therefore, in order to carry out the so-called route calibration, it was suggested to use kilometer and hectometer posts used in transportation networks, the locations of which are successively added to the OSM database. BADANIE UŻYTECZNOŚCI OTWARTYCH DANYCH PRZESTRZENNYCH DO ANALIZ OPARTYCH NA SIECIACH DROGOWYCH – NA PRZYKŁADZIE OPENSTREETMAP Od kilkunastu już lat użytkownicy oprogramowania GIS mogą używać do dowolnych celów zbioru danych będącego do pewnego stopnia alternatywą zarówno dla produktów oferowanych przez dostawców komercyjnych, jak i urzędowych baz danych. Jest nim OpenStreetMap (w skrócie OSM) – obejmujący cały świat zbiór danych przestrzennych, tworzony i edytowany przez zainteresowane osoby i dostępny do stosowania przez każdego chętnego bez żadnych ograniczeń. Budowany jest na podstawie danych rejestrowanych turystycznymi odbiornikami GPS, pozyskiwanych poprzez wektoryzację zdjęć lotniczych oraz pochodzących z innych nadających się do wykorzystania źródeł, w tym nawet szkiców wykonywanych w terenie. Zgromadzona GEOINFORMATICA POLONICA 20: 2021 DOI 10.4467/21995923GP.21.007.14978 informacja zapisywana jest w centralnej bazie danych, której zawartość jest nie tylko prezentowana na stronie internetowej w postaci cyfrowej mapy, lecz również oferowana do pobrania jako dane wektorowe. Takie dane mogą mieć zastosowanie między innymi do przeprowadzania różnorodnych analiz bazujących na sieciach drogowych, z których najczęściej wykorzystywana jest funkcja wyznaczania optymalnej trasy łączącej wybrane lokalizacje. Wyniki takich analiz można uznać za wiarygodne tylko wtedy, gdy użyte w nich dane będą się charakteryzować odpowiednią jakością. Ponieważ baza danych OSM budowana jest przez pasjonatów, nie są formułowane żadne plany jej systematycznego rozwoju oraz brak jest wbudowanych mechanizmów kontroli jakości. Dlatego w artykule zaproponowano metody i narzędzia, które pozwolą na weryfikację przydatności zgromadzonych do tej pory danych, jak również na poprawę wykrytych błędów. Skupiono się na następujących kategoriach jakości danych geograficznych: dokładności położenia, spójności topologicznej oraz ważności czasowej. Dodatkowo dostrzeżono problem z wyznaczaniem długości poszczególnych obiektów sieci drogowej, związany z metodami pozyskiwania danych i sposobami rejestracji kształtu linii. W związku z tym do przeprowadzenia tak zwanej kalibracji trasy zasugerowano użycie stosowanych w sieciach transportowych słupków kilometrowych i hektometrowych, których lokalizacje są sukcesywnie wprowadzane do bazy danych OSM.

Changes in Alpine Butterfly Communities during the Last 40 Years

Our work aims to assess how butterfly communities in the Italian Maritime Alps changed over the past 40 years, in parallel with altitudinal shifts occurring in plant communities. In 2019, we sampled butterflies at 7 grassland sites, between 1300–1900 m, previously investigated in 2009 and 1978, by semi-quantitative linear transects. Fine-scale temperature and precipitation data elaborated by optimal interpolation techniques were used to quantify climate changes. The changes in the vegetation cover and main habitat alterations were assessed by inspection of aerial photographs (1978–2018/1978–2006–2015). The vegetation structure showed a marked decrease of grassland habitats and an increase of woods (1978–2009). Plant physiognomy has remained stable in recent years (2009–2019) with some local exceptions due to geomorphic disturbance. We observed butterfly ‘species substitution’ indicating a general loss in the more specialised and a general gain in more tolerant elements. We did not observe any decrease in species richness, but rather a change in guild compositions, with (i) an overall increased abundance in some widespread and common lowland species and (ii) the disappearance (or strong decrease) of some alpine (high elevation) species, so that ‘resilience’ could be just delusive. Changes in butterfly community composition were consistent with predicted impacts of local warming.

Improving a neural network model for semantic segmentation of images of monitored objects in aerial photographs

This paper considers a model of the neural network for semantically segmenting the images of monitored objects on aerial photographs. Unmanned aerial vehicles monitor objects by analyzing (processing) aerial photographs and video streams. The results of aerial photography are processed by the operator in a manual mode; however, there are objective difficulties associated with the operator's handling a large number of aerial photographs, which is why it is advisable to automate this process. Analysis of the models showed that to perform the task of semantic segmentation of images of monitored objects on aerial photographs, the U-Net model (Germany), which is a convolutional neural network, is most suitable as a basic model. This model has been improved by using a wavelet layer and the optimal values of the model training parameters: speed (step) ‒ 0.001, the number of epochs ‒ 60, the optimization algorithm ‒ Adam. The training was conducted by a set of segmented images acquired from aerial photographs (with a resolution of 6,000×4,000 pixels) by the Image Labeler software in the mathematical programming environment MATLAB R2020b (USA). As a result, a new model for semantically segmenting the images of monitored objects on aerial photographs with the proposed name U-NetWavelet was built. The effectiveness of the improved model was investigated using an example of processing 80 aerial photographs. The accuracy, sensitivity, and segmentation error were selected as the main indicators of the model's efficiency. The use of a modified wavelet layer has made it possible to adapt the size of an aerial photograph to the parameters of the input layer of the neural network, to improve the efficiency of image segmentation in aerial photographs; the application of a convolutional neural network has allowed this process to be automatic.