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Unmanned aerial vehicles (UAVs), commonly known as drones, present a cost-effective solution for the swift collection of data from vast and remote areas that are otherwise difficult to access. The Mediterranean Basin, known for being a hotspot for plant biodiversity, hosts several habitats and taxa of significant naturalistic value. However, many of these areas are often inaccessible to botanists, making exploration and research challenging. The aim of this paper is to involve the utilization of drone surveys and open-source software for botanical research. Our primary goal is to show the effectiveness of these tools in the field and demonstrate their practical application in Natura 2000 sites. The protected area chosen for this research is Rocca di Novara, situated in northeastern Sicily. Thanks to our drone investigations, we were able to capture images of a mountainside that is inaccessible to humans. This allowed us to observe the habitat of some species in detail. One of the most fascinating discoveries was the reappearance of Saxifraga callosa subsp. australis, which had not been confirmed in this area for over 140 years. Using drones for botanical research can boost field research, making monitoring easier and more cost-effective over time, especially in Natura 2000 sites. [ABSTRACT FROM AUTHOR]

Passive acoustic monitoring (PAM) through acoustic recorder units (ARUs) shows promise in detecting early landscape changes linked to functional and structural patterns, including species richness, acoustic diversity, community interactions, and human-induced threats. However, current approaches primarily rely on supervised methods, which require prior knowledge of collected datasets. This reliance poses challenges due to the large volumes of ARU data. In this work, we propose a non-supervised framework using autoencoders to extract soundscape features. We applied this framework to a dataset from Colombian landscapes captured by 31 audiomoth recorders. Our method generates clusters based on autoencoder features and represents cluster information with prototype spectrograms using centroid features and the decoder part of the neural network. Our analysis provides valuable insights into the distribution and temporal patterns of various sound compositions within the study area. By utilizing autoencoders, we identify significant soundscape patterns characterized by recurring and intense sound types across multiple frequency ranges. This comprehensive understanding of the study area's soundscape allows us to pinpoint crucial sound sources and gain deeper insights into its acoustic environment. Our results encourage further exploration of unsupervised algorithms in soundscape analysis as a promising alternative path for understanding and monitoring environmental changes. [ABSTRACT FROM AUTHOR]

For 10 years, a group of specialists from the department of physical geography and cartography has been exploring the territories of national parks consistently using information technology tools, improving their use in combination with ground test landscape surveys. This article reflects the experience of such scientific and applied development in relation to the territory of Slobozhansky National Nature Park. The purpose of this development is to improve the existing technologies of complex interpretation of geodata for the design and monitoring of the territory in their systematic combination with the methods of online mapping and in-depth meaningful interpretation for the scientific support of the organization of the territory and the administration of the national parks. This article covers currently known and possible scientific approaches and measures that rely on scientific and applied measures used by the national parks administration in management processes. The most recent issues highlighted in this article compared to the previous published works of the authors are the formulation of the trinity paradigm of the process of creating a landscape model of the territory. A set of individual tasks is defined, the consistent implementation of which ensures the achievement of the goal: selection of appropriate types, scales and optical ranges of remote sensing, taking into account the landscape conditions inherent in the location of the territory of the national park; development, on these grounds, of the technology of thematic landscape mapping, geoecological assessment and control of results on test areas of the terrain; peculiarities of drawing legends of applied landscape maps using GIS technologies; making corrections and additions to the existing defining documents of projects of the national park organization and developing recommendations for their improvement; design of the monitoring system of Slobozhansky National Nature Park. In the paradigm of applied landscape research, the national park should be designed based on the trinity of remote sensing and human intelligence: a) the technical level of providing remote sensing; b) taking into account the ambiguity of the optical image of the area depending on the purpose of geodata interpretation; c) tasks that are also solved ambiguously: the selection of certain ranges and scales of soundings, the selection of test areas and even the compilation of legends of a large-scale landscape map. The specified ambiguity is manifested in the variability of constructions and creates the subjectivity of applied landscape research. Methodological basis. The system-structural approach is manifested in the identification and identification of those spatial connections between visually significant and hidden from direct observation properties (mainly water-heat balance indicators) of the landscape, which change in an ambiguous dependence on regional background indicators, therefore must be taken into account in design and monitoring. Scientific results. In addition to theoretical generalizations, the article briefly presents the implementation of the highlighted approach in the study of landscapes of the Slobozhansky National Nature Park.

Unmanned aerial vehicles (UAVs), commonly known as drones, present a cost-effective solution for the swift collection of data from vast and remote areas that are otherwise difficult to access. The Mediterranean Basin, known for being a hotspot for plant biodiversity, hosts several habitats and taxa of significant naturalistic value. However, many of these areas are often inaccessible to botanists, making exploration and research challenging. The aim of this paper is to involve the utilization of drone surveys and open-source software for botanical research. Our primary goal is to show the effectiveness of these tools in the field and demonstrate their practical application in Natura 2000 sites. The protected area chosen for this research is Rocca di Novara, situated in northeastern Sicily. Thanks to our drone investigations, we were able to capture images of a mountainside that is inaccessible to humans. This allowed us to observe the habitat of some species in detail. One of the most fascinating discoveries was the reappearance of Saxifraga callosa subsp. australis, which had not been confirmed in this area for over 140 years. Using drones for botanical research can boost field research, making monitoring easier and more cost-effective over time, especially in Natura 2000 sites.

Passive acoustic monitoring (PAM) through acoustic recorder units (ARUs) shows promise in detecting early landscape changes linked to functional and structural patterns, including species richness, acoustic diversity, community interactions, and human-induced threats. However, current approaches primarily rely on supervised methods, which require prior knowledge of collected datasets. This reliance poses challenges due to the large volumes of ARU data. In this work, we propose a non-supervised framework using autoencoders to extract soundscape features. We applied this framework to a dataset from Colombian landscapes captured by 31 audiomoth recorders. Our method generates clusters based on autoencoder features and represents cluster information with prototype spectrograms using centroid features and the decoder part of the neural network. Our analysis provides valuable insights into the distribution and temporal patterns of various sound compositions within the study area. By utilizing autoencoders, we identify significant soundscape patterns characterized by recurring and intense sound types across multiple frequency ranges. This comprehensive understanding of the study area’s soundscape allows us to pinpoint crucial sound sources and gain deeper insights into its acoustic environment. Our results encourage further exploration of unsupervised algorithms in soundscape analysis as a promising alternative path for understanding and monitoring environmental changes.

For 10 years, a group of specialists from the department of physical geography and cartography has been exploring the territories of national parks consistently using information technology tools, improving their use in combination with ground test landscape surveys. This article reflects the experience of such scientific and applied development in relation to the territory of Slobozhansky National Nature Park. The purpose of this development is to improve the existing technologies of complex interpretation of geodata for the design and monitoring of the territory in their systematic combination with the methods of online mapping and indepth meaningful interpretation for the scientific support of the organization of the territory and the administration of the national parks. This article covers currently known and possible scientific approaches and measures that rely on scientific and applied measures used by the national parks administration in management processes. The most recent issues highlighted in this article compared to the previous published works of the authors are the formulation of the trinity paradigm of the process of creating a landscape model of the territory. A set of individual tasks is defined, the consistent implementation of which ensures the achievement of the goal: selection of appropriate types, scales and optical ranges of remote sensing, taking into account the landscape conditions inherent in the location of the territory of the national park; development, on these grounds, of the technology of thematic landscape mapping, geoecological assessment and control of results on test areas of the terrain; peculiarities of drawing legends of applied landscape maps using GIS technologies; making corrections and additions to the existing defining documents of projects of the national park organization and developing recommendations for their improvement; design of the monitoring system of Slobozhansky National Nature Park. In the paradigm of applied landscape research, the national park should be designed based on the trinity of remote sensing and human intelligence: a) the technical level of providing remote sensing; b) taking into account the ambiguity of the optical image of the area depending on the purpose of geodata interpretation; c) tasks that are also solved ambiguously: the selection of certain ranges and scales of soundings, the selection of test areas and even the compilation of legends of a large-scale landscape map. The specified ambiguity is manifested in the variability of constructions and creates the subjectivity of applied landscape research. Methodological basis. The system-structural approach is manifested in the identification and identification of those spatial connections between visually significant and hidden from direct observation properties (mainly water-heat balance indicators) of the landscape, which change in an ambiguous dependence on regional background indicators, therefore must be taken into account in design and monitoring. Scientific results. In addition to theoretical generalizations, the article briefly presents the implementation of the highlighted approach in the study of landscapes of the Slobozhansky National Nature Park. [ABSTRACT FROM AUTHOR]

The need for reliable landscape-scale monitoring of forest disturbance has grown with increased policy and regulatory attention to promoting the climate benefits of forests. Change detection algorithms based on satellite imagery can address this need but are largely untested for the forest types and disturbance regimes of the US Northeast, including management practices common in northern hardwoods and mixed hardwood-conifer forests. This study ground-truthed the "off-the-shelf" outputs of three satellite-based change detection algorithms using detailed harvest records and maps covering 43,000 ha of working forests in northeastern New York. [ABSTRACT FROM AUTHOR]

Traditional landscape photographs reaching back until the second half of the nineteenth century represent a valuable image source for the study of long-term landscape change. Due to the oblique perspective and the lack of geographical reference, landscape photographs are hardly used for quantitative research. In this study, oblique landscape photographs from the Norwegian landscape monitoring program are georeferenced using the WSL Monoplotting Tool with the aim of evaluating the accuracy of point and polygon features. In addition, the study shows how the resolution of the chosen digital terrain model and other factors affect accuracy. Points mapped on the landscape photograph had a mean displacement of 1.52 m from their location on a corresponding aerial photograph, while mapped areas deviated on average 5.6% in size. The resolution of the DTM, the placement of GCPs and the angle of incidence were identified as relevant factors to achieve accurate geospatial data. An example on forest expansion at the abandoned mountain farm Flysetra in Mid-Norway demonstrates how repeat photography facilitates the georectification process in the absence of reliable ground control points (GCPs) in very old photographs. [ABSTRACT FROM AUTHOR]

Ecosystem monitoring is fundamental to our understanding of how ecosystem change is impacting our natural resources and is vital for developing evidence‐based policy and management. However, the different types of ecosystem monitoring, along with their recommended applications, are often poorly understood and contentious. Varying definitions and strict adherence to a specific monitoring type can inhibit effective ecosystem monitoring, leading to poor program development, implementation and outcomes. In an effort to develop a more consistent and clear understanding of ecosystem monitoring programs, we here review the main types of monitoring and recommend the widespread adoption of three classifications of monitoring, namely, targeted, surveillance and landscape monitoring. Landscape monitoring is conducted over large areas, provides spatial data, and enables questions relating to where and when ecosystem change is occurring to be addressed. Surveillance monitoring uses standardised field methods to inform on what is changing in our environments and the direction and magnitude of that change, whilst targeted monitoring is designed around testable hypotheses over defined areas and is the best approach for determining the causes of ecosystem change. The classification system is flexible and can incorporate different interests, objectives, targets and characteristics as well as different spatial scales and temporal frequencies, while also providing valuable structure and consistency across distinct ecosystem monitoring programs. To support our argument, we examine the ability of each monitoring type to inform on six key types of questions that are routinely posed for ecosystem monitoring programs, such as where and when change is occurring, what is the magnitude of change, and how can the change be managed? As we demonstrate, each type of ecosystem monitoring has its own strengths and weaknesses, which should be carefully considered relative to the desired results. Using this scheme, scientists and land managers can design programs best suited to their needs. Finally, we assert that for our most serious environmental challenges, it is essential that we include information from each of these monitoring scales to inform on all facets of ecosystem change, and this is best achieved through close collaboration between the scales. With a renewed understanding of the importance of each monitoring type, along with greater commitment to monitor cooperatively, we will be well placed to address some of our greatest environmental challenges. [ABSTRACT FROM AUTHOR]

Road-based citizen science surveys are increasingly used for long-term monitoring of wildlife, including amphibians, over large spatial scales. However, how representative such data are when compared to the actual species distribution remains unclear. Spatial biases in site selection or road network coverage by volunteers could skew results towards more urbanised areas and consequently produce incorrect or partial trend estimations at regional or national scales. Our objective was to compare and verify potential spatial biases of road-based data using distribution datasets of different origins. We used as a case study the common toad (Bufo bufo), a fast-declining species and the main amphibian targeted by conservation action on roads in Europe. We used Maxent models to compare road survey data obtained from the 35 year-long "Toads on Roads" project in Great Britain with models using national-scale toad distribution records as well as with models using randomly generated points on roads. Distribution models that used data collected by volunteers on roads produced similar results to those obtained from overall species distribution, indicating the lack of selection bias and high spatial coverage of volunteer-collected data on roads. Toads were generally absent from mountainous areas and, despite the high availability of potential recorders, showed nearly complete absence of road-based records in large urban areas. This is probably the first study that comparatively evaluates species distribution models created using datasets of different origin in order to verify the influence of potential spatial bias of data collected by volunteers on roads. Large-scale declines of widespread amphibians have been demonstrated using data collected on roads and our results indicate that such data are representative and certainly comparable to other existing datasets. We show that for countries with high road network coverage, such as Great Britain, road-based data collected by volunteers represent a robust dataset and a critical citizen science contribution to conservation. [ABSTRACT FROM AUTHOR]

Natural areas are tracts of land with little or no evidence of past human influence and designated for research, education, and conservation. Many sites were selected to represent high-quality examples of both common and rare plant association groups. However, the extent to which natural areas characterize regional environmental conditions or gradients important for measuring and understanding the effects of climate change has not been examined. We compared the current collection of natural areas in Oregon and Washington to the broader natural ecosystems found in the region using four ecological parameters derived from existing datasets: forest structure, dominant tree species, vegetation formation classes, and elevation. We evaluated these data sets at both the regional and ecosystem scales and looked at the influence of land ownership in representing these parameters. Our results suggest that the Pacific Northwest natural areas network is well representative of all four parameters at the regional level. There were some gaps in representation at the ecoregion scale and across some land ownerships. Results from this study further support using natural areas for monitoring long-term climate change effects in the Pacific Northwest. [ABSTRACT FROM AUTHOR]

Abstract Repeat photography is an efficient method for documenting long-term landscape changes. So far, the usage of repeat photographs for quantitative analyses is limited to approaches based on manual classification. In this paper, we demonstrate the application of a convolutional neural network (CNN) for the automatic detection and classification of woody regrowth vegetation in repeat landscape photographs. We also tested if the classification results based on the automatic approach can be used for quantifying changes in woody vegetation cover between image pairs. The CNN was trained with 50 × 50 pixel tiles of woody vegetation and non-woody vegetation. We then tested the classifier on 17 pairs of repeat photographs to assess the model performance on unseen data. Results show that the CNN performed well in differentiating woody vegetation from non-woody vegetation (accuracy = 87.7%), but accuracy varied strongly between individual images. The very similar appearance of woody vegetation and herbaceous species in photographs made this a much more challenging task compared to the classification of vegetation as a single class (accuracy = 95.2%). In this regard, image quality was identified as one important factor influencing classification accuracy. Although the automatic classification provided good individual results on most of the 34 test photographs, change statistics based on the automatic approach deviated from actual changes. Nevertheless, the automatic approach was capable of identifying clear trends in increasing or decreasing woody vegetation in repeat photographs. Generally, the use of repeat photography in landscape monitoring represents a significant added value to other quantitative data retrieved from remote sensing and field measurements. Moreover, these photographs are able to raise awareness on landscape change among policy makers and public as well as they provide clear feedback on the effects of land management. Graphical abstract Unlabelled Image Highlights • The convolutional neural network is able to detect woody vegetation in photographs. • Image quality is an important factor for discriminating between vegetation types. • The automatic approach is capable of identifying trends in woody vegetation regrowth. • Manual classification provides most accurate results in change detection. • Repeat photography is a powerful tool for communicating landscape changes. [ABSTRACT FROM AUTHOR]

In savannas, mapping grazing resources and indicators of land degradation is important for assessing ecosystem conditions and informing grazing and land management decisions. We investigated the effects of classifiers and used time series imagery—images acquired within and across seasons—on the accuracy of plant species maps. The study site was a grazed savanna in southern Kenya. We used Sentinel-2 multi-spectral imagery due to its high spatial (10−20 m) and temporal (five days) resolution with support vector machine (SVM) and random forest (RF) classifiers. The species mapped were important for grazing livestock and wildlife (three grass species), indicators of land degradation (one tree genus and one invasive shrub), and a fig tree species. The results show that increasing the number of images, including dry season imagery, results in improved classification accuracy regardless of the classifier (average increase in overall accuracy (OA) = 0.1632). SVM consistently outperformed RF, and the most accurate model and was SVM with a radial kernel using imagery from both wet and dry seasons (OA = 0.8217). Maps showed that seasonal grazing areas provide functionally different grazing opportunities and have different vegetation characteristics that are critical to a landscape’s ability to support large populations of both livestock and wildlife. This study highlights the potential of multi-spectral satellite imagery for species-level mapping of savannas.

Abstract There are more than 580 natural areas in Oregon and Washington managed by 20 federal, state, local, and private agencies and organizations. This natural areas network is unparalleled in its representation of the diverse ecosystems found in the Pacific Northwest, and could prove useful for monitoring long‐term ecological responses to climate change. Our objectives were to (1) evaluate potential effects of climate change on these natural areas and (2) develop strategies for selecting and prioritizing sites for long‐term monitoring. Bioclimatic and Random Forest modeling were used to identify subsets of natural areas to prioritize for long‐term monitoring efforts based on the current and projected (2020s, 2050s, 2080s) outputs from 13 future climate models. Projection consensus suggest some of the largest effects of climate change on natural areas may be the result of a substantial range increase in suitable climate for warmer‐adapted forest types coupled with a reduction in habitat for cooler‐adapted forest types. We identify four strategies that could be used for prioritizing sites and help manage and protect biodiversity in the Pacific Northwest, especially given uncertainty over climate change effects.

Maintaining the long-term sustainability of human and natural systems across agricultural landscapes requires an integrated, systematic monitoring system that can track crop productivity and the impacts of agricultural intensification on natural resources. This study presents the design and practical implementation of a monitoring framework that combines satellite observations with ground-based biophysical measurements and household surveys to provide metrics on ecosystem services and agricultural production at multiple spatial scales, reaching from individual households and plots owned by smallholder farmers to 100-km landscapes. We developed a set of protocols for monitoring and analyzing ecological and agricultural household parameters within two 10 × 10-km landscapes in Rwanda, including soil fertility, crop yield, water availability, and fuelwood sustainability. Initial results suggest providing households that rely on rainfall for crop irrigation with timely climate information and improved technical inputs pre-harvest could help increase crop productivity in the short term. The value of the monitoring system is discussed as an effective tool for establishing a baseline of ecosystem services and agriculture before further change in land use and climate, identifying limitations in crop production and soil fertility, and evaluating food security, economic development, and environmental sustainability goals set forth by the Rwandan government. [ABSTRACT FROM AUTHOR]

There are more than 580 natural areas in Oregon and Washington managed by 20 federal, state, local, and private agencies and organizations. This natural areas network is unparalleled in its representation of the diverse ecosystems found in the Pacific Northwest, and could prove useful for monitoring long-term ecological responses to climate change. Our objectives were to (1) evaluate potential effects of climate change on these natural areas and (2) develop strategies for selecting and prioritizing sites for long-term monitoring. Bioclimatic and Random Forest modeling were used to identify subsets of natural areas to prioritize for long-term monitoring efforts based on the current and projected (2020s, 2050s, 2080s) outputs from 13 future climate models. Projection consensus suggest some of the largest effects of climate change on natural areas may be the result of a substantial range increase in suitable climate for warmer-adapted forest types coupled with a reduction in habitat for cooler-adapted forest types. We identify four strategies that could be used for prioritizing sites and help manage and protect biodiversity in the Pacific Northwest, especially given uncertainty over climate change effects. [ABSTRACT FROM AUTHOR]

The subordinated position of soil in the geosystem allows it to be used as an indicator of the landscape balance. Examples where soil plays such an indicative role are presented in this paper. The theory of the “geochemical landscape” has been used as the theoretical-methodological basis. Soil properties indicating direction, intensity and quality of matter migration in the landscape have been discussed (profile environment, pH, redox, quantitative and qualitative humus properties). The indicative role of soil in the monitoring of “sustainable landscape” has also been characterized. According to the authors, three models of this landscape can be created: natural, rural and urban sustainable landscapes.

Changes in land use and land cover reflect anthropogenic effects in areas with a long history of human occupation, such as Mediterranean regions. To understand the landscape dynamics of a semi-arid Mediterranean ecosystem in Chile, we evaluated land-cover trajectories and their effects on landscape spatial patterns over a period of 36 years (1975–2011). We used landscape metrics combined with surveys of landowners to distinguish the main drivers of landscape change. General results indicated that changes in forest area followed both natural (64%) and human-induced (36%) trajectories. At the landscape level, fragmentation for all forest cover types increased, whereas at the class level, fragmentation of Native Forest decreased. The landscape changed from a homogeneous mosaic dominated by grazing and agriculture to a more heterogeneous environment, where natural cover had become more dominant. Thus, the use of a landscape ecology approach together with field information improved our understanding of the spatiotemporal dynamics in this landscape. This study is one of the first to assess landscape dynamics of the Mediterranean semi-arid region of Chile. This is important because it aids decision-making for biodiversity conservation in a global hotspot and land-use planning. [ABSTRACT FROM AUTHOR]

An important level of biodiversity, alongside the diversity of genes and species, is the diversity of ecosystems and landscapes. In this contribution an indicator system is proposed to measure natural diversity (relief, soils, waters), cultural diversity (main land use classes, diversity of land use, ecotones, connectivity) and anthropogenic impacts (fragmentation, hemeroby, protection). The contribution gives an overview of various indicators on landscape diversity and heterogeneity currently used in Germany and Europe. Based on these indicators a complementary system, is presented. The indicators introduced here are derived from regular evaluations of the digital basis landscape model (Basic DLM) of the Authoritative Topographic-Cartographic Information System (ATKIS), the digital land cover model for Germany (LBM-DE) as well as other supplementary data such as the mapping of potential natural vegetation. With the proposed indicators it is possible to estimate cumulative land-use change and its impact on the environmental status and biodiversity, so that existing indicator systems are supplemented with meaningful additional information. Investigations have shown that indicators on forest fragmentation, hemeroby or ecotones can be derived from official geodata. As such geodata is regularly updated, trends in indicator values can be quickly identified. Large regional differences in the distribution of the proposed indicators have been confirmed, thereby revealing deficits and identifying those regions with a high potential for biodiversity. The indicators will be successively integrated into the web-based land-use monitor ( http://www.ioer-monitor.de ), which is freely available for public use. [ABSTRACT FROM AUTHOR]

This study explores the concept of pasture, looking at how people classify it and the features that determine how an image is classified. The analysis is based on two parallel studies that used the same image material. The first study was a web-based survey in which respondents were asked to make a pairwise comparison of the images they felt best corresponded to pasture. The second study used eye-tracking to investigate the elements viewed by respondents as they considered the degree to which images corresponded to pasture. It is found that the respondents had clear and mostly similar concepts of pasture and that they apply these consistently when categorising pasture. [ABSTRACT FROM AUTHOR]

Measures to mitigate the risk of pesticide entry into aquatic ecosystems are becoming increasingly more important in the management of hot spots of pesticide transfer; such management, for example, is required by the European Union's directive for the sustainable use of pesticides (2009/128/EC). Measures beyond those currently stipulated for pesticide product authorization may be needed. A concise compilation of the appropriate measures for users (that are primarily farmers but also, e.g., regulators and farm extension services) and a guide for practically identifying these measures at the catchment scale is currently not available. Therefore, a proposal was developed for a guide focusing on the most important diffuse entry pathways (spray drift and runoff). Based on a survey of exposure-relevant landscape parameters (i.e., the riparian buffer strip width, riparian vegetation type, density of ground vegetation cover, coverage of the water body with aquatic macrophytes, field slope, and existence of concentrated flow paths), a set of risk mitigation measures focusing on the specific situation of pollution of a water body catchment can be identified. The user can then choose risk mitigation measures to implement, assisted by evaluations of their efficiency in reducing pesticide entry, feasibility, and expected acceptability to farmers. Currently, 12 landscape-related measures and 6 application-related measures are included. The present guide presents a step toward the practical implementation of risk mitigation measures for reducing pesticide entry in aquatic ecosystems. Integr Environ Assess Manag 2014;10:286-298. © 2013 SETAC [ABSTRACT FROM AUTHOR]

Today landscape change monitoring becomes important in the field of sustainable development planning. Real changes of landscape have to be observed in a large scale (not smaller than 1:10,000) in order to avoid generalization of small landscape elements. In such a scale it is rational to perform the monitoring in sample areas that would be enough statistically abundant. The paper offers an original method of distributing the landscape sample areas in Lithuanian territory, differing from most methods based on random choose of sample areas though thorough analysis of the analogous methods abroad was performed. The work was sponsored by the Environmental Agency at the Lithuanian Ministry of Environment. In accordance to the spread of different natural landscape types (like clayey plains, morainic hills, sandy plains, etc.), a set of 100 sample areas (2.5 km2 each) was distributed in Lithuanian territory. To increase the sample area number in smaller landscape types (spit, coastal sandy plain, delta), some proportional corrections were made. Thus, the largest number of the sample areas was assigned to the most spread clayey plains (22), the smallest number – to sandy coastal plain (3). In order to find a concrete place for each sample area inside the landscape type a computer program was employed and the highest representation principle applied. Several tens of thousands possible positions of the sample areas were tested in order to find the best in representing land cover structure. This was achieved by calculating relative remoteness of tested samples’ land cover structure from the respective landscape type structure, further selecting the most patchy samples. Selecting the position of a sample area was also influenced by the buffer capacity (resistance to the chemical impact) of landscape, mostly concentrating on the areas with less buffer capacity (more sensitive to chemical pollution). Santrauka Tvariajai pletrai planuoti tampa aktualia kraštovaizdžio kaitos stebesena. Realūs kraštovaizdžio pokyčiai Lietuvos mastu turi būti fiksuojami stambiuoju masteliu (ne smulkesniu nei 1:10 000), vengiant nepageidautino smulkiu kraštovaizdžio elementu generalizavimo. Tokiu masteliu racionalu būtu pokyčiu stebejimus atlikti etalonuose, ju skaičius turetu būti statistiškai patikimas. Pateikiama originali kraštovaizdžio monitoringo etalonu išdestymo Lietuvos teritorijoje metodika. Darbas buvo atliktas remiant Aplinkos apsaugos agentūrai prie Lietuvos aplinkos ministerijos. Metodika parengta atsižvelgiant ir i užsienio šaliu patirti. Pagal kraštovaizdžio tipu paplitima proporcingai buvo išdalyta 100 2,5 km2 ploto etalonu, papildomai koreguojant (padidinant) etalonu skaičiu mažai paplitu‐siuose kraštovaizdžio tipuose (nerijoje, pajūrio lygumoje, deltoje). Taigi daugiausia etalonu (22) buvo skirta plačiausiai paplitusioms molingosioms lygumoms, mažiausiai (3) – pajūrio lygumai. Etalonams konkrečios vietos buvo parenkamos kompiuterine programa ir vadovautasi didžiausio reprezentatyvumo principu. Kiekvieno kraštovaizdžio tipo buvo išbandyta nuo keliu šimtu iki keliasdešimties tūkstančiu galimu etalonu padečiu, nustatyta pagal žemes dangos struktūra reprezentuojančios geriausiai. Etalonu vietu parinkimas buvo siejamas ir su kraštovaizdžio buferiškumo cheminei taršai arealais, daugiau koncentruojant mažesnio buferiškumo (jautresniuose cheminei taršai) plotuose. Резюме В настоящее время мониторинг изменений ландшафта становится актуальным для планировки сбалансированного развития. Реальные изменения ландшафта в Литве должны быть прослеживаемы в крупном масштабе (не мельче чем 1:10.000) во избежание нежелательной генерализации мелких структурных элементов ландшафта. В таком масштабе рационально осуществлять наблюдения на специально выделенных эталонных территориях, число которых должно быть статистически достаточным. В статье приведена методика расположения названных эталонов на территории Литвы. Работа выполнена при поддержке Агентства по охране окружающей среды при Министерстве окружающей среды. Методика разработана с учетом опыта зарубежных стран. С учетом распределения ландшафтных типов пропорционально было поделено сто эталонов площадью 2,5 км2 каждый. Дополнительно корректировалось (увеличивалось) число эталонов в мало распространенных ландшафтных типах (на косе, приморской равнине, в дельте). Наибольшее число эталонов (22) было отдано глинистым (наиболее распространенным) равнинам, а наименьшее (3) – приморской равнине. С целью подбоpa для эталонов конкретных мест была применена компьютерная программа, а также следовали принципу наивысшей репрезентативности. В каждом ландшафтном типе было испробовано от нескольких сот до нескольких десятков тысяч возможных положений эталонов с целью определить лучшее положение по репрезентативности земельно покровной структуры. Подбор мест для эталонов был осуществлен с учетом сопротивляемости ландшафта химическому загрязнению. Больше эталонов размещалось в наименее устойчивых ареалах. First Publish Online: 10 Feb 2011 Reikšminiai žodžiai: kraštovaizdžio monitoringas, stebėsenos etalonai, didžiausio atstovavimo principas, žemės dangos struktūra, gamtiniai kraštovaizdžio tipai. Ключевые слова: мониторинг ландшафта, эталонные ареалы, принцип наивысшей репрезентативности, структура земельного покрова, природные типы ландшафта

One of the landscape dynamics that has attracted significant interest, both from the scientific community and, more recently, from the broader population, is landscape fragmentation. Landscape fragmentation has come to the forefront since it impacts ecological systems and human ac-tivities. From landscape ecology to the theory of perception, multiple disci-plines have dealt with the concept and measurement of landscape fragmen-tation and its impacts on habitats and societies. Landscape fragmentation, which is one of the most widespread landscape processes, has been stud-ied in both conservation biology and landscape ecology disciplines. Quanti-tative indicators capable of measuring landscape patterns and changes are used to examine landscape fragmentation and assess the impact on the environment and biodiversity. In addition, qualitative indicators are used to measure the social dimension and perception of landscape fragmentation by humans (with little connection to ecological processes). The present study takes a pragmatic approach to integrate existing con-cepts and methodologies of landscape fragmentation assessment and ex-amine the feasibility of creating a comprehensive indicator that combines the strengths of these different perspectives. In this article, we summarize and analyze the current assessments used to study landscape fragmenta-tion. We report the strengths, limitations, successes and challenges of the quantitative and perceptive approaches and provide an insight into the pos-sibilities and potential of combining these approaches into one assessment. Based on the existing literature and pioneering integrative approaches, we conclude that it is convenient and feasible to design an indicator of land-scape fragmentation. This indicator would be informative of changes in the landscape pattern and meaningful for land planners and society as a whole. Such an indicator, however, should be constrained in scope to focus on people and our unique perception of scale, visual fragmentation, and human societal context and cultural background. A combination of both approaches would maximize the significance and utility of a landscape fragmentation indicator. Landscape ecology methodologies have proved to be useful in develop-ing indicators of landscape patterns. There are difficulties, however, which are inherent in the measurement methods and the interpretation of the meaning that landscape fragmentation indices have for species living in the landscape. These limitations require researchers to be very concise regard-ing the targeted species, the elements considered to cause the fragmenta-tion of their habitat and the scale at which this habitat should be studied. The exact definition of which elements are involved in landscape fragmentation and the degree to which they contribute to the perception and the discrimi-nation of groups of people that share similar views and opinions regarding a given landscape fragmentation pattern are issues that can be addressed by disciplines studying landscape perception, preferences and interactions within communities. At present, when integrative approaches combining landscape ecology indices and visual indicators have proved to be achiev-able, studies of the viability of particular indicators that are informative for specific landscape processes are important. Our future research will focus on the development of a suitable indicator of landscape fragmentation, which takes into account the aforementioned requirements and limitations. [ABSTRACT FROM AUTHOR]

Abstract: The European Landscape Convention (ELC) brings the social dimension of landscapes to the forefront of its definition of landscape. Landscape indicators need to take this requirement into account. Landscape fragmentation, which is one of the most widespread landscape processes in Europe, has been studied in both conservation biology and landscape ecology disciplines. Quantitative indicators capable of measuring landscape patterns and changes are used to examine landscape fragmentation and assess the impact on the environment and biodiversity. In addition, qualitative indicators are used to measure the social dimension and perception of landscape fragmentation by humans (with little connection to ecological processes). In this article, we summarize and analyze the current assessments used to study landscape fragmentation. We report the strengths, limitations, successes and challenges of the quantitative and perceptive approaches and provide insight into the possibilities and potential of combining these approaches into one assessment. Based on the existing literature and pioneering integrative approaches, we conclude that it is convenient and feasible to design an indicator of landscape fragmentation that is consistent with the ELC framework. This indicator would be informative of changes in the landscape pattern and meaningful for land planners and society as a whole. Such an indicator, however, should be constrained in scope to focus on people and our unique perception of scale, visual fragmentation, and human societal context and cultural background. [Copyright &y& Elsevier]

Abstract: The structure of a landscape is highly relevant for research and planning (such as fulfilling the requirements of the Water Framework Directive – WFD – and for implementation of comprehensive catchment planning). There is a high potential for restoration of linear landscape elements in most European landscapes. By implementing the WFD in Germany, the restoration of linear landscape elements could be a valuable measure, for example to reduce nutrient input into rivers. Despite this importance of landscape structures for water and nutrients fluxes, biodiversity and the appearance of a landscape, specific studies of the linear elements are rare for larger catchment areas. Existing studies are limited because they either use remote sensing data, which does not adequately differentiate all types of linear landscape elements, or they focus only on a specific type of linear element. To address these limitations, we developed a framework allowing comprehensive quantification of linear landscape elements for catchment areas, using publicly available biotope type data. We analysed the dependence of landscape structures on natural regions and regional soil characteristics. Three data sets (differing in biotopes, soil parameters and natural regions) were generated for the catchment area of the middle Mulde River (2700km2) in Germany, using overlay processes in geographic information systems (GIS), followed by statistical evaluation. The linear landscape components of the total catchment area are divided into roads (55%), flowing water (21%), tree rows (14%), avenues (5%), and hedges (2%). The occurrence of these landscape components varies regionally among natural units and different soil regions. For example, the mixed deciduous stands (3.5m/ha) are far more frequent in foothills (6m/ha) than in hill country (0.9m/ha). In contrast, fruit trees are more frequent in hill country (5.2m/ha) than in the cooler foothills (0.5m/ha). Some 70% of avenues, and 40% of tree rows, are discontinuous; in contrast, only 20% of hedges are discontinuous. Using our innovative framework, comprehensive information about landscape elements can now be obtained for regional applications. This approach can be applied to other regions and is highly relevant for landscape planning, erosion control, protection of waters and preservation of biotopes and species. [Copyright &y& Elsevier]

LANDFIRE is a large interagency project designed to provide nationwide spatial data for fire management applications. As part of the effort, many 2000 vintage Landsat Thematic Mapper and Enhanced Thematic Mapper plus data sets were used in conjunction with a large volume of field information to generate detailed vegetation type and structure data sets for the entire United States. In order to keep these data sets current and relevant to resource managers, there was strong need to develop an approach for updating these products. We are using three different approaches for these purposes. These include: 1) updating using Landsat-derived historic and current fire burn information derived from the Monitoring Trends in Burn Severity project; 2)~incorporating vegetation disturbance information derived from time series Landsat data analysis using the Vegetation Change Tracker; and 3) developing data products that capture subtle intra-state disturbance such as those related to insects and disease using either Landsat or the Moderate Resolution Imaging Spectroradiometer (MODIS). While no one single approach provides all of the land cover change and update information required, we believe that a combination of all three captures most of the disturbance conditions taking place that have relevance to the fire community. [ABSTRACT FROM PUBLISHER]

Rural landscapes are highly dynamic and their change impacts on a number of ecological processes such as the dynamics of biodiversity. Although a substantial amount of research has focused on quantifying these changes and their impact on biodiversity, most studies have focused on single dimensions of land use change. This lack of integration in land use change studies can be explained by the fact that data on the spatial, temporal, and ecological dimensions of land use are seldom available for the same geographical location. In this paper, the benefits of taking into account these three dimensions are illustrated with results derived from the Great Britain Countryside Surveys (CS), a large-scale monitoring programme designed to assess change in the extent and ecological condition of British habitats. The overview of CS results presented in this paper shows that (1) changes in land use composition will translate into a variety of spatial patterns; (2) the temporal stability of land use is often lower than can be expected; and (3) there can be large-scale shifts in the ecological condition of the land use types that form our rural landscapes. The benefits of integrated rural landscape studies are discussed in the context of other national monitoring programmes. [Copyright &y& Elsevier]

Abstract: Ecologists can be overwhelmed by the number of metrics available to quantify landscape structure. Clarification of interrelationships and redundancy is needed to guide metric selection and interpretation for the purpose of landscape monitoring. In this study we identified independent components of class- and landscape-level structure in multiple landscapes in each of three large and geographically disjunct study areas. We used FRAGSTATS and principal components analysis (PCA) to identify independent components of landscape structure, and cluster analysis to group the components. We then calculated the universality, strength, and consistency of the identified landscape structure components. At the class-level we identified 24 independent configuration components. Seven of these components were nearly universal and consistent in interpreted meaning. At the landscape-level there were 17 independent structure components. Eight of these components were universal and consistent. These results indicate that there are consistent combinations of metrics that universally describe the major attributes of landscape structure at the class- and landscape-levels. [Copyright &y& Elsevier]

Harmonisation of land-cover data relates to spatial data integration and therefore needs to consider the data concepts adopted and the spatial, temporal, semantic and quality aspects of the data. Differences in semantic concepts are often considered the key obstacle to data integration and interoperability. If the problem of harmonisation is limited to the variation in the semantic content of data expressed as differences in categorisation, then various approaches have been developed to address the methodological issues and for computing semantic similarity. Five Nordic class sets were selected for establishing correspondences between their semantic class contents using the parameterised land cover classification system (LCCS) as a reference system. Subsequently, semantic similarities between pair-wise classes were calculated using a module of LCCS. This article first examines the aspects of land-cover harmonisation and the LCCS methodologies for categorisation and semantic similarity. It then discusses the functioning of LCCS as a reference system in which the more or less corresponding class of the original Nordic classes was determined and the semantic similarity indices computed. Suggestions are provided for improvements in the LCCS methodology, both in establishing correspondences and for computing semantic similarity. Recommendations are given for the way forward in land-cover harmonisation and for measures to express the quality of harmonisation of the semantic contents of class sets at class set level and individual class level. [ABSTRACT FROM AUTHOR]

Worldwide, invasive weeds threaten agricultural, natural and urban ecosystems. In Australia's agricultural and grazing regions, invasive species often establish across extensive areas where weed management is hampered by an inability to detect the location and timing of an outbreak. In these vast landscapes, an effective detection and monitoring system is required to delineate the extent of the invasion and identify spatial and temporal factors associated with weed establishment and thickening. In this study, we utilize a time series of remote sensing imagery to detect the spatial and temporal patterns of Prickly Acacia ( Acacia nilotica) invasion in the Mitchell grass plains of North Queensland. We develop a spectral index from Landsat images which is applied to images from 1989 to 2004, in combination with a classification mask, to identify locations and monitor changes in Prickly Acacia density across 29 000 km2 of Mitchell grass plains. The approach identified spectral and temporal signatures consistent with Prickly Acacia infestation on 1.9% of this landscape. Field checking of results confirmed presence of the weed in previously unrecorded locations. The approach may be used to evaluate future spread, or outcomes of management strategies for Prickly Acacia in this landscape and could be employed to detect and monitor invasions in other extensive landscapes. [ABSTRACT FROM AUTHOR]

Abstract: A framework for landscape monitoring based on a functional approach is presented. Landscape monitoring is defined as regular, long-term surveillance of landscapes. Suitable monitoring resulting in the early recognition of crucial changes in the environment is a prerequisite if timely counteractions are to be carried out. Such monitoring provides spatially and temporally homogeneous data sets, and allows for adjustment to and validation of ecological models. The peculiarities of the framework presented are as follows. Landscape functions, and ecological conditions and processes are scrutinized from a strong human perspective. The procedure employs various methods based on models, balances, calculations and estimations. Thus, far-reaching data integration is possible, which allows for the drawing of conclusions which are important for human society. The landscape monitoring proposed also follows a differentiated scale-dependent approach (at local, sub-regional and regional levels) with a stepwise integration of data. Data sampling and analysis are organized according to a scale-dependent set of assumptions allowing a problem-oriented approach. The framework is exemplified by changes in soils in a small (16.1km2) floodplain in Saxony (Germany). The assessment proposed also takes into account historical data. Essential changes in soils have been established, e.g. losses in humus, deposition of soils by excavation matter and peat degradation. It was found that the percentage of arable land increased, and the groundwater level decreased in several areas. This finds expression in several physical and chemical parameters, e.g. in reduced field and sorption capacities. Therefore, the performances of soil protection functions and of production functions became worse. [Copyright &y& Elsevier]

Abstract: Landscape monitoring is a rapidly developing approach in the field of environmental science and management. In order to develop a sound landscape monitoring programme, key theoretical concepts and study objectives should be clearly stipulated, and the specific objects to be monitored, as well as the criteria for selecting study areas, hierarchical levels, and techniques of data collection and analysis should be identified. This paper describes the development and implementation of the Estonian monitoring programme for agricultural landscapes, conventional approaches for landscape monitoring, and by neighbourhood analysis, assesses how landscape features are covered by different complementary monitoring data and how the current pattern of monitoring networks represents the landscape features. A spatially explicit method of network design for monitoring and sampling strategies combines stratified and multi-scale agricultural landscape monitoring and uses neighbourhood analysis characterised by the nearest neighbourhood index and Ripley''s K-function. Data for landscape analysis are obtained from landscape monitoring (three sets) and other complementary environmental monitoring sets, such as biodiversity, forest, soil, and water monitoring (11 sets). It is shown that several monitoring sets follow an approach that aims to achieve national geographical coverage, representing various landscape types. Small sets having less than 50 stations are biased and the networks are not statistically significant. Proportional stratified sampling requires fewer sites for large homogenous inland landscape districts. The concept of agricultural landscape monitoring was tested in pilot areas. The chosen multi-scale object-based methods provide a good overview of the level of human pressure on different categories of agricultural land. Results of the monitoring showed that the species composition and abundance of bio-indicators was, to a great degree, determined by landscape structure. A systematic approach focused on landscape classes helps to integrate the monitoring set as a whole and to achieve a coherent and efficient layout of monitoring sets for Estonia. [Copyright &y& Elsevier]

Abstract: Biodiversity issues have gained importance in forestry as a result of the increased awareness of forest landscape changes, but still there is much to do before forest management meets reasonable goals for forest protection and renewal of biodiversity. In this work, we focus on boreal forest landscapes, using Finland as a case study, and taking advantage of a valuable database—the National Forest Inventory (NFI). We explore a multicriteria approach by using a predictive habitat suitability model for three-toed woodpecker (Picoides tridactylus) based on Weights-of-Evidence (WofE) and a combination of remote sensing and field data derived from the Multisource Finnish National Forest Inventory (MS-NFI). The WofE model is a quantitative method used for combining evidence to examine the support for a given hypothesis. WofE involves the estimation of a response variable (favourability for certain habitat occurrence) and a set of predictor variables (e.g. GIS layers containing environmental variables). WofE is based on a log-linear form of Bayes’ rule and uses the prior probability distribution and the likelihood of the data to generate a posterior probability distribution. Very few examples exist of WofE being used to predict the spatial distribution of species or communities using biophysical descriptors. This work explores WofE as a tool for rapid biodiversity assessment using georeferenced species information. Since the method is dependent of the indicator species used as a surrogate of biodiversity value it can be applied for assessing biodiversity conditions of both managed and protected areas to help decision-making concerning protection of valuable habitats. Thus, the map of habitat suitability, represented as a range of probabilities of occurrence, offers an objective framework for evaluating the outcomes of different scenarios. Similarly, an objective assessment of habitat suitability provides a rational basis for management decisions incorporating impact on species habitat. [Copyright &y& Elsevier]

Landscape ecology and landscape pattern analysis are important components of national-scale programs to identify trends in land cover change because: 1) Statistics on changes in land cover proportions are not spatial. A change matrix derived from GIS provides useful information, but it does not show the spatial form of change in the landscape. Landscape pattern metrics reveal spatial pattern. 2) A growing body of literature has shown that a change in landscape pattern might indicate important changes in ecological functions: forest connectivity and species movements, number and size of farm patches, effects on water quality. Spatial pattern is important in structuring ecological communities and in maintaining existence of competitors. Spatial pattern may be determined by disturbance and may in turn, determine how disturbances propagate through the system. 3) Sometimes landscape pattern may not significantly change, even though land cover proportions do change. Or, vice-versa, sometimes landscape pattern can significantly change, even though land cover proportions don’t significantly change. 4) Landscape pattern is an inherent and important part of describing landscapes: based on the literature, one of the most important descriptive characteristics of a landscape is its texture. The objectives of this paper are to: 1) Explain the importance of the role of landscape ecology and landscape pattern analysis in land cover change studies; 2) Review the literature that specifically incorporates landscape ecology into land cover change studies; and 3) List the theoretical and technical issues involved and suggest solutions for them. [ABSTRACT FROM AUTHOR]