Landscape Change Analysis Research Articles

Landsat images and GIS techniques as key tools for historical analysis of landscape change and fragmentation

Monitoring and evaluation of landscape fragmentation is important in numerous research areas, such as natural resource protection and management, sustainable development, and climate change. One of the main challenges in image classification is the intricate selection of parameters, as the optimal combination significantly affects the accuracy and reliability of the final results. This research aimed to analyze landscape change and fragmentation in northwestern Peru. We utilized accurate land cover and land use (LULC) maps derived from Landsat imagery using Google Earth Engine (GEE) and ArcGIS software. For this, we identified the best dataset based on its highest overall accuracy, and kappa index; then we performed an analysis of variance (ANOVA) to assess the differences in accuracies among the datasets, finally, we obtained the LULC and fragmentation maps and analyzed them. We generated 31 datasets resulting from the combination of spectral bands, indices of vegetation, water, soil and clusters. Our analysis revealed that dataset 19, incorporating spectral bands along with water and soil indices, emerged as the optimal choice. Regarding the number of trees utilized in classification, we determined that using between 10 and 400 decision trees in Random Forest classification doesn't significantly affect overall accuracy or the Kappa index, but we observed a slight cumulative increase in accuracy metrics when using 100 decision trees. Additionally, between 1989 and 2023, the categories Artificial surfaces, Agricultural areas, and Scrub/ Herbaceous vegetation exhibit a positive rate of change, while the categories Forest and Open spaces with little or no vegetation display a decreasing trend. Consequently, the areas of patches and perforated have expanded in terms of area units, contributing to a reduction in forested areas (Core 3) due to fragmentation. As a result, forested areas smaller than 500 acres (Core 1 and 2) have increased. Finally, our research provides a methodological framework for image classification and assessment of landscape change and fragmentation, crucial information for decision makers in a current agricultural zone of northwestern Peru.

Support vector machine-based spatiotemporal land use land cover change analysis in a complex urban and rural landscape of Akaki river catchment, a Suburb of Addis Ababa, Ethiopia

Intense level of land use land cover (LULC) changes has been observed in Sub-Saharan Africa, particularly in the central highlands of Ethiopia, due to rapid population growth and urbanization process. However, quantifying and identifying the rural-urban landscape changes are challenging. In this study, LULC changes during the years 1984, 1990, 2000, 2010, and 2021 have been analyzed using satellite imageries and Support Vector Machine (SVM) algorithms in a heterogenous rural and urban landscape of the Akaki river catchment, central highlands of Ethiopia. The LULC change drivers were evaluated by applying LULC thematic change analysis combined with key informants’ interviews. Seven LULCs that include: Built-up area (BTA), Cropland (CL), Grassland (GL), Waterbody (WB), Plantation Forest (PF), Woodland (WL), and Bareland (BL) were detected. The result shows that 51.3 % of the catchment area has been transformed into other land uses. BTA increased by 24.7 % while GL and WL reduced by 18.1 % and 5.9 % respectively. Large areas of CL (61 %) and GL (22 %) were changed into an urban landscape. The spatial and non-spatial analysis revealed that the major spatiotemporal LULC change drivers between 1984 and 2005 were land use policy and legislation change and the Eucalyptus tree plantation campaign. Whereas, low-cost housing programs, informal settlers, market opportunity, and real estate development were the main drivers for the LULC changes between 2006 and 2021. The study also found the key informant observation and SVM image classification results are aligned and therefore, we found the SVM-based classifications are suited for such complex rural-urban landscape change and pattern analysis. The outcome of this research can contribute to improving land use policy, its management, and public understanding of the LULC dynamics and its implications.

Change Detection Analysis Using Drone-Based Photogrammetry for Long-Term Archaeological Site Erosion Monitoring

This paper presents a rapid, cost-effective, and non-specialist approach to long-term archaeological site monitoring that is repeatable and affordable. Advances in unmanned aerial vehicle (UAV)-based photogrammetry allow for the creation of multi-temporal three-dimensional (3D) models that permit accurate and in-depth analysis and quantification of landscape change through time. This paper presents a case study of aerial-based photogrammetric datasets using UAVs (i.e., drones) to conduct change detection analysis for monitoring continued erosion threatening an Indigenous buffalo jump in Alberta, Canada. The results demonstrate which areas of the site experienced the most significant change over a period of four years. By bridging gaps between traditional field survey and satellite-scale observations of impacts to large archaeological site complexes, UAV monitoring programs may become increasingly important as anthropogenic climate change continues to threaten heritage sites in Canada.

Land Use Changes in the Southeastern United States: Quantitative Changes, Drivers, and Expected Environmental Impacts

Land use change analysis provides valuable information for landscape monitoring, managing, and prioritizing large area conservation practices. There has been significant interest in the southeastern United States (SEUS) due to substantial land change from various economic activities since the 1940s. This study uses quantitative data from the Economic Research Service (ERS) for landscape change analysis, addressing land change among five major land types for twelve states in the SEUS from 1945 to 2012. The study also conducted a literature review using the PSALSAR framework to identify significant drivers related to land type changes from research articles within the region. The analysis showed how each land type changed over the period for each state in the time period and the percentage change for the primary drivers related to land use change. The literature review identified significant drivers of land use and land cover change (LULCC) within the SEUS. The associated drivers were categorized into natural and artificial drivers, then further subdivided into eight categories related to land type changes in the region. A schematic diagram was developed to show land type changes that impacted environmental changes from various studies in the SEUS. The results concluded that Forest land accounted for 12% change and agricultural land for 20%; population growth in the region is an average of 2.59% annually. It also concluded that the need for research to understand past land use trends, direction and magnitude of land cover changes is essential. Significant drivers such as urban expansion and agriculture are critical to the impending use of land in the region; their impacts are attributed to environmental changes in the region and must be monitored.

Spatiotemporal Dynamics of Landscape Transformation in Western Balkans’ Metropolitan Areas

Human-caused landscape transformation represents a danger to conserving the Earth’s natural habitats. Landscape fragmentation (LF) caused by transportation infrastructure and urban development poses a threat to human and environmental health by increasing traffic noise and pollution, reducing the size and viability of wildlife populations, facilitating the spread of invasive species, and reducing the recreational qualities of the landscape. It is especially noticeable in the metropolitan areas of developing countries due to rapid and unsupervised urban sprawl. In this context, this study aims to protect natural landscapes and biodiversity, promoting forms of sustainable development. To exemplify our aim, we bring a spatio-temporal analysis of landscape change comparing three metropolitan areas in the Western Balkans (WB). First, we compare the land use land cover (LULC) changes in Tirana (Albania), Skopje (North Macedonia), and Sarajevo (Bosnia and Herzegovina). The comparison was based on the Urban Atlas (UA) data of 2012 and 2018. The analysis was performed on two levels, at the metropolitan and urban spatial scales. Apart from descriptive statistics about the changes in surface area and patch counts, we used effective mesh size (meff) as a landscape metric to quantify the LF level. Our results show that each city has faced significant LULC change between 2012 and 2018, with a dominant increase in artificial surfaces. Furthermore, the cumulative natural surface area reduction is followed by increased landscape patch counts, indicating an increased LF at both levels. This study enhances public awareness about the landscape transformation trends in the developing metropolitan regions of WB. The respective administrative bodies at both local and central levels are invited to consider our results and adopt proper measurements to reduce the adverse consequences of subsequent spatial development decisions.

Research on the Change in Public Art Landscape Pattern Based on Deep Learning

With the limited design level of urban external space and place environment, however, the city image design and public art design play an important role in urban development, which leads to the lack of rational understanding that vague urban style is the effective implementation. In this article, a deep learning model is proposed to study the changes in public art landscape pattern in urban space, and it is constantly found that the changes in urban spatial layout have an impact on urban development. Firstly, the landscape index was analyzed effectively, and the Markov model was used to predict land use change, which provided a theoretical basis for the analysis of urban landscape change. Then the GeoSOS-FLUS model based on deep learning is used to make up for the lack of diversity of land use types by using the suitability probability calculation module of ANN and the adaptive inertia and competition mechanism, and the competition between different land use types is introduced. The experimental results show that the GeoSOS-FLUS framework based on deep learning model has good prediction effect and application ability.

Analysis of Landscape Change and Its Driving Mechanism in Chagan Lake National Nature Reserve

Lake ecosystems play an important role in regional ecological security and the sustainable development of the economy and society. In order to study the evolution of landscape patterns and the main driving forces in the Chagan Lake Nature Reserve in recent years, we used landscape type data from 2005, 2010, 2015, and 2019 to study the characteristics of the regional landscape’s structural changes. At the same time, the spatial heterogeneity of the driving factors of landscape change was analyzed using the spatial analysis method, and the driving mechanism of landscape change was quantitatively analyzed. The results showed that: (1) from 2005 to 2019, the area of cultivated land, marshland, and water bodies increased, while the area of grassland and the area of bare land decreased. (2) The dominant patch types in the study area formed good connectivity, and the degree of landscape fragmentation increased. (3) In the past 15 years, there has been spatial heterogeneity in the regression coefficients of different driving factors of landscape change: the area with a greater influence of the elevation factor was in the south; the regression coefficient of precipitation showed the spatial distribution characteristics of highs in the west and lows in the east; the gross domestic product had a greater impact on the east and the south; the spatial variation of grain yield was mainly reflected in the southeast and northwest regions; the fishery yield gradually changed from high in the southeast and low in the northwest to the distribution characteristic of decreasing from the east to the southwest; the lake fluorine content showed a distribution pattern that gradually changed from high in the southeast and low in the northwest to high in the middle and low in the north and south; the distribution pattern of the distance to oil production changed from north to southeast to south to north; the distance to the road changed from high in the east and low in the west to the opposite spatial distribution pattern. (4) The interaction of precipitation and lake fluoride content with other factors showed a strong driving effect, which had a significant impact on the landscape change of Chagan Lake Nature Reserve. Since the study area is located in a typical fluorine-rich geochemical environment, human activities, such as the expansion of irrigation areas around Chagan Lake and groundwater exploitation, have accelerated the dissolution of fluorine-containing minerals, promoted the enrichment process of fluorine in Chagan Lake, and enhanced the explanatory power of lake fluorine content in terms of landscape changes. At the same time, the increase in precipitation during the study period is beneficial to the growth of vegetation and the storage of water in lakes, which promotes changes in landscape types such as grasslands and areas of water.

Temporal and Spatial Analysis of Urban Landscape Change: The Case of Burdur, Turkey

Bu araştırmada, 2012 ve 2018 arazi kullanım/arazi örtüsü (AKAÖ) haritaları kullanılarak Burdur İli Merkez İlçesi'nde peyzaj değişiklikleri incelenmiştir. Veri analizinde ArcMap 10.8 ve FRAGSTATSTM 4.2 yazılımlarından faydalanılmıştır. AKAÖ üzerindeki değişiklikler Sınıf Alanı (CA), Parça Sayısı (NP), Parça Yoğunluğu (PD), Peyzajın Oranı (PLAND) ve Ortalama Parça Büyüklüğü (AREA_MN) metrikleri kullanılarak belirlenmiştir. 2012 ve 2018 yılları arasında maden/inşaat/kullanılmayan araziler en büyük artışı (%122,34) göstermişken, en büyük azalış (%19,68) sulak alanlarda meydana gelmiştir. AKAÖ sınıfları arasında en büyük dönüşüm (7.016,07 ha) tarımsal alanlar ile doğal/yarı doğal alanlar arasında olmuştur. Endüstriyel/ticari alanlarda ve sulak alanlarda parçalanma artmış, tarımsal alanlarda ve doğal/yarı doğal alanlarda ise parçalanma azalmıştır. Sonuç olarak, 6 yıl gibi kısa bir sürede meydana gelen peyzaj değişimleri önemli soru işaretlerini gündeme getirmektedir. Bu değişiklikler hiç şüphesiz ekosistem hizmetlerini ve ekolojik süreçleri olumsuz etkileyecektir. Ekosistem hizmetleri ve ekolojik süreçlerin aksamaması için gerekli önlemler alınmalıdır. Burdur kenti için geniş kapsamlı bir kentsel yeşil altyapı stratejisi ve planının hazırlanması bu yolda önemli bir adım olacaktır.

A new C & I for sustainable forest management

According to the biophysical area, the government has set the land use of forest areas to be managed for specific management purposes. The implication is that the Criteria and Indicators (C&I) of sustainable forest management are arranged fractionally, based on the forest area’s function. This study aims to analyze the effectiveness of the application of C&I for sustainable forest management in conservation forests in the upstream area of the Jeneberang watershed in Gowa Regency. Field observations, interviews, focus group discussions, workshops, and documentation study conducted to collect primary and secondary data. The analysis conducted by the research were (1) Socio-Economic, (2) Landscape Change, (3) Activity-Based Management and (4) Policy Analysis. The results found the application of C&I of sustainable forest management based on forest function is ineffective because the forest area is an inseparable landscape unit, so the management unit should not be separated. Therefore, forest areas’ land use should be reconstructed based on the function of forest area (fractional) to “landscape-based watershed landscape”. C & I in measuring sustainable forest management performance should also be hierarchically structured interconnected input, outputs, outcomes, and impact indicators.

Remote Sensing-Based Analysis of Urban Landscape Change in the City of Bucharest, Romania

The paper investigates the urban landscape changes for the last 50 years in Bucharest, the capital city of Romania. Bucharest shows a complex structural transformation driven by the socialist urban policy, followed by an intensive real-estate market development. Our analysis is based on a diachronic set of high-resolution satellite imagery: declassified CORONA KH-4B from 1968, SPOT-1 from 1989, and multisensor stacked layers from Sentinel-1 SAR together with Sentinel-2MSI from 2018. Three different datasets of land cover/use are extracted for the reference years. Each dataset reveals its own urban structure pattern. The first one illustrates a radiography of the city in the second part of the 20th century, where rural patterns meet the modern ones, while the second one reveals the frame of a city in a full process of transformation with multiple constructions sites, based on the socialist model. The third one presents an image of a cosmopolitan city during an expansion process, with a high degree of landscape heterogeneity. All the datasets are included in a built-up change analysis in order to map and assess the spatial transformations of the city pattern over 5 decades. In order to quantify and map the changes, the Built-up Change Index (BCI) is introduced. The results highlight a particular situation linked to the policy development visions for each decade, with major changes of about 50% for different built-up classes. The GIS analysis illustrates two major landscape transformations: from the old semirural structures with houses surrounded by gardens from 1968, to a compact pattern with large districts of blocks of flats in 1989, and a contemporary city defined by an uncontrolled urban sprawl process in 2018.

Divide et Disperda: Thirty Years of Fragmentation and Impacts on the Eco-Mosaic in the Case Study of the Metropolitan City of Naples

Nowadays, anthropic pressures are continuously transforming the landscape mosaic, leading to issues related to habitat fragmentation and the loss of ecosystem functions. In this study, a landscape-change analysis over the 1990–2018 timeframe of the case study area of Metropolitan City of Naples (MCN) (southern Italy) was performed to evaluate trends, causes, and results of the landscape transformations. We preliminary performed a spatial–temporal fragmentation-expansion analysis in the MCN through the landscape expansion index (LEI), and subsequently determined the impacts on the eco-mosaic. The multitemporal analysis (1990–2018) highlighted an urban expansion in the MCN. The LEI analysis depicted a dual tendency in the increased fragmenting of the MCN’s eco-mosaic. The urban landscape has compacted in the hollow areas, and in the meantime there has been a sprawling expansion of the urban fabric. The most impacted land-use category was “Agricultural areas”, of which 57.42 km2 have been lost in 28 years, with negative impacts on ecological connectivity. Finally, we investigated the relationship between the increase and type of landscape fragmentation and the demographic flows over time. We found that the areas affected by demographic growth were the same ones characterized by an edge expansion of the urban patterns. Conversely, where there has been a demographic decrease, an infilling behavior of urban fabric has been noted. This study highlights a possible correlation between the expansion type of the urban fabric and the demographic flows in a region as a main driver. The outcome of 30-year transformations is the actual ecological network in which Core Areas, Buffer Zones, and Primary Connections covered 35.3%, 11.1%, and 39.6%, respectively, of the total surface of the MCN, covering an overall area of 1008.4 km2.

Using Landscape Change Analysis and Stakeholder Perspective to Identify Driving Forces of Human–Wildlife Interactions

Human–wildlife interactions (HWI) were frequent in the post-socialist period in the mountain range of Central European countries where forest habitats suffered transitions into built-up areas. Such is the case of the Upper Prahova Valley from Romania. In our study, we hypothesized that the increasing number of HWI after 1990 could be a potential consequence of woodland loss. The goal of our study was to analyse the effects of landscape changes on HWI. The study consists of the next steps: (i) applying 450 questionnaires to local stakeholders (both citizens and tourists) in order to collect data regarding HWI temporal occurrences and potential triggering factors; (ii) investigating the relation between the two variables through the Canonical Correspondence Analysis (CCA); (iii) modelling the landscape spatial changes between 1990 and 2018 for identifying areas with forest loss; (iv) overlapping the distribution of both the households affected by HWI and areas with loss of forested ecosystems. The local stakeholders indicate that the problematic species are the brown bear (Ursus arctos), the wild boar (Sus scrofa), the red fox (Vulpes vulpes) and the grey wolf (Canis lupus). The number of animal–human interactions recorded an upward trend between 1990 and 2018, and the most significant driving factors were the regulation of hunting practices, the loss of habitats, and artificial feeding. The landscape change analysis reveals that between 1990 and 2018, the forest habitats were replaced by built-up areas primarily on the outskirts of settlements, these areas coinciding with frequent HWI. The results are valid for both forest ecosystems conservation in the region, wildlife management, and human infrastructures durable spatial planning.

Agricultural Landscape Change Analysis: A Case Study of Bornova District in Izmir Province

Amaç: Bu çalışma ile İzmir ili Bornova ilçesinde 2012 ve 2016 yılları arasında meydana gelen alan kullanım/arazi örtüsü değişimlerinin tarımsal peyzajın değişimini nasıl etkilediğini ortaya koymak amaçlanmıştır.Materyal ve Metot: Çalışmada 2012 yılına ait RapidEye ve 2016 yılına ait Landsat 8 OLI uydu görüntüleri kullanılmıştır. Araştırma alanının alan kullanım/arazi örtüsü ile tarımsal peyzaj değişiminin analiz edilmesinde Sınıf Alanı (CA), Peyzajın Oranı (PLAND), Ortalama Leke Büyüklüğü (AREA_MN), Bağlantılılık İndeksi (CONNECT), Leke Sayısı (NP), Peyzaj Şekil İndeksi (LSI), Alan Ağırlıklı Ortalama Leke Büyüklüğü (AREA_AM) ve Ortalama Öklid En Yakın Komşu Mesafesi (ENN_MN) olmak üzere sekiz adet peyzaj metriğinden yararlanılmıştır. Alan kullanım/arazi örtüsü değişimlerinin belirlenmesinde ArcGIS 10.1 yazılımı, peyzaj metriklerine yönelik analizler için ise FRAGSTATS 4.2 yazılımı kullanılmıştır.Bulgular: Çalışma sonucunda tarımsal alanların 3113 hektardan 3121 hektara artış gösterdiği tespit edilmiştir. Tarım alanlarının yoğun olduğu bölgelerde yeni tarım alanlarının açılması ile tarım alanlarının genişlediği, diğer yerlerdeki büyük lekeler halindeki tarım alanlarının ise diğer alan kullanımlarına dönüşmesi nedeniyle küçülme eğilimi gösterdiği belirlenmiştir. Sonuç: Alan kullanım/arazi örtüsü değişimlerinin ve değişim eğilimlerinin ne yönde olduğunun tespit edilmesi, arazi üzerindeki baskıların azaltılması, doğal kaynaklardan optimum fayda sağlanması ve sürdürülebilir planlama stratejilerinin oluşturulması açısından önem arz etmektedir. Bu çalışma ile alan kullanım/arazi örtüsü değişimlerinin peyzaj metrikleri ile değerlendirilmesinin, değişimlerin izlenmesinde kullanılabilecek bir yöntem olduğu ortaya konulmuştur.

How to consider history in landscape ecology: patterns, processes, and pathways

ContextLandscape ecology early on developed the awareness that central objects of investigation are not stable over time and therefore the historical dimension must be included, or at least considered.ObjectivesThis paper considers the importance of history in landscape ecology in terms of its impact on patterns and processes and proposes to complement these with the notion of pathways in order to provide a comprehensive analysis of landscape change.MethodsWe develop a conceptual framework distinguishing between legacy effects, which include pattern and processes, and path dependence, with a focus of development pathways and we illustrate these perspectives by empirical examples.ResultsCombined short- to long-lasting imprints and legacies of historical patterns and processes reveal how present patterns and processes are in various ways influenced by legacies of the past. The focus on inherent dynamics of development pathways sheds light on the process of change itself, and its trajectories, and reveals the role of event chains and institutional reproduction.ConclusionsUnderstanding patterns, processes, and pathways over time, allows a more complete analysis of landscape change, and forms the base to preserve vital ecosystem services of both human-made and natural landscapes for the future.

Analysis of climate and landscape change through the Pennsylvanian and Permian Monongahela and Dunkard Groups, Southeastern Ohio, USA

Paleosols and ichnofossils of the Late Pennsylvanian to Early Permian Monongahela and Dunkard groups of southeastern Ohio provide significant paleoenvironmental and paleoclimatic data related to the Late Paleozoic climatic transition. Forty paleosol profiles from three outcrops in southeastern Ohio were investigated. Methods included the description of paleosol profiles in the field and the analysis of thin sections. Clay mineralogy and bulk geochemistry were used to assess weathering processes and paleoprecipitation. Results, such as the distribution, abundance, and size of physical features including slickensides, pedogenic carbonates, and rhizoliths suggest erratic fluctuations between mildly seasonal wet environments and strongly seasonal dry environments throughout the studied section which are supported by oscillations in calculated paleoprecipitation values. Paleosols of the Monongahela Group are interpreted as mildly to strongly seasonal, wet to wet-dry, sparsely to heavily vegetated fen, dry woodland, clastic marsh, early successional vegetation, and brakeland ecosystems forming on proximal to distal floodplain and shoreline lacustrine environments. Paleosols of the Lower Dunkard Group are interpreted as a mildly to strongly seasonal, wet to wet-dry, sparsely to heavily vegetated, clastic marsh, early successional vegetation, and brakeland ecosystems forming on proximal to distal floodplain and distal levee environments. Variability in climate has profound effects on paleolandscapes. By investigating changes in paleosols through episodes of climatic transition, we can better understand the impact these changes have on soils and soil ecosystems of the past and future.

Decline and Passive Restoration of Forest Vegetation Around the Yeocheon Industrial Complex of Southern Korea

This study was carried out to clarify the vegetation decline due to air pollutants emitted in the process of industrial activities and the passive restoration of the vegetation due to socioeconomic changes after economic growth. To achieve this goal, we investigated the spatial distribution of vegetation, differences in species composition and diversity among vegetation types different in damage degree, vegetation dynamics, the age structure and annual ring growth of two dominant plant species, and the landscape change that occurred in this area over the last 50 years. Plant communities tended to be spatially distributed in the order of grassland, shrubland (dominated by Styrax japonicus Siebold and Zucc. community), and forests (dominated by Pinus thunbergii Parl. and Pinus densiflora Siebold and Zucc. communities), with increasing distance from the pollution source. The result of stand ordination based on vegetation data reflected the trend of such a spatial distribution. Species richness evaluated based on the species rank dominance curve was the highest in shrubland and the lowest in grassland; species richness in forests was intermediate. The size class distribution of woody plant species in four plant communities composing three vegetation types showed the possibility of them being replaced by forest in the late successional stage. However, the density of successor trees was relatively low, whereas the density of shrubby plants, which are resilient to air pollution, was very high. The age class distribution of a dominant species forming shrubland and pine forest showed that most of them were recruited after industrialization in this area. The period when young individuals in both vegetation types were recruited corresponded to the period when the annual ring growth of the pine trees that survived air pollution was reduced. An analysis of the landscape change in this area indicated that coniferous forest and agricultural field decreased greatly, whereas industrial area, residential area, mixed forest, and broadleaved forest showed increasing trends since construction of the industrial complex. As a result, the decrease in coniferous forest is usually due to vegetation decline and partially to succession, as the pine trees dominating the forest are not only sensitive to air pollution but are also shade-intolerant. The increase in mixed and broadleaved forests reflects vegetation decline or succession. Vegetation decline progressed for about 30 years after the construction of the industrial complex; it has begun to be restored passively since then, although the change has been slow. These results are in line with the environmental Kuznets curve hypothesis that environmental degradation increases in the early stages of economic growth to a certain point, and, after a turning point, economic development leads to environmental improvements—thus, there is an inverted U-shaped relationship between economic growth and environmental degradation.

THE CHANGE OF NATURAL LANDSCAPE IN PALANGA CITY (LITHUANIA)

The paper presents the comparative analysis of the Palanga city landscape change during the period between 2008 and 2019. For this analysis, the land fund statistics of the Republic of Lithuania, which had been grouped into a relatively natural and anthropogenic landscape, were used. Landscape change is graphically shown in the figures. Lithuanian and foreign scientific literature and legal acts were analyzed for the fulfillment of the work. The Palanga city landscape analysis of the current situation was done. During the analysis the Palanga city statistics were compared with the data of Klaipeda County and the Republic of Lithuania. Landscape structure maintenance is the subject important and relevant to this day, as the landscape shapes the country's culture and is the component of natural and cultural heritage contributing to the quality of life and it consolidates Lithuanian identity, uniqueness in Europe and the world. The topic is actual because it is necessary to analyze landscape change in Palanga in order to evaluate and preserve the components of natural landscape in Lithuanian resort. The analysis showed that during the analyzed period the Palanga city natural landscape area 46.34 ha or 1.39 percent. The increase of the natural landscape area was determined by the development of water bodies and wetland areas.

Integrated Landscape Change Analysis of Protected Areas and their Surrounding Landscapes: Application in the Brazilian Cerrado

Remote sensing tools have been long used to monitor landscape dynamics inside and around protected areas. Hereto, scientists have largely relied on land use and land cover (LULC) data to derive indicators for monitoring these dynamics, but these metrics do not capture changes in the state of vegetation surfaces that may compromise the ecological integrity of conservation areas’ landscapes. Here, we introduce a methodology that combines LULC change estimates with three Normalized Difference Vegetation Index-based proxy indicators of vegetation productivity, phenology, and structural change. We illustrate the utility of this methodology through a regional and local analysis of the landscape dynamics in the Cerrado Biome in Brazil in 2001 and 2016. Despite relatively little natural vegetation loss inside core protected areas and their legal buffer zones, the different indicators revealed significant LULC conversions from natural vegetation to farming land, general productivity loss, homogenization of natural forests, significant agricultural expansion, and a general increase in productivity. These results suggest an overall degradation of habitats and intensification of land use in the studied conservation area network, highlighting serious conservation inefficiencies in this region and stressing the importance of integrated landscape change analyses to provide complementary indicators of ecologically-relevant dynamics in these key conservation areas.

Measuring landscape change, lot by lot: Greening activity in response to a vacant land reuse program

Urban vacancy is a persistent problem in many cities across the U.S. and globally. Vacant land greening helps improve neighborhood conditions and initiatives that transfer vacant lots to neighborhood residents can return benefits to where they are most needed. We examined one such initiative, the Chicago Large Lot Program, which allows property owners in high-vacancy areas to purchase 1–2 city-owned vacant lots on their block for $1 each. We developed a fine-scale landscape change analysis based on a visual assessment of aerial and street-level imagery. Our assessment, which included 20 different aspects of land/tree cover and condition/care, was applied to 424 lots purchased in two areas of the city one year before and after purchase. Among the significant changes we observed was an 8% increase of lots with gardens, and while there was a 16% reduction of lots with mature trees, it was accompanied by a similar increase in the proportion of mature trees in “good condition.” Also, nearly a third of the lots showed signs of appropriation for use and/or stewardship prior to purchase, a process known as “blotting.” We found that transfer of ownership to residents through the Large Lot Program was followed by improved condition and care regardless of prior blotting, but the non-blotted lots had bigger improvements in condition and care after purchase than the blotted lots. Changes associated with vacant land greening have both social and ecological implications, and we discuss our findings with respect to urban greening strategies and future research.

Urban Landscape Change Analysis Using Local Climate Zones and Object-Based Classification in the Salt Lake Metro Region, Utah, USA

Urban areas globally are vulnerable to warming climate trends exacerbated by their growing populations and heat island effects. The Local Climate Zone (LCZ) typology has become a popular framework for characterizing urban microclimates in different regions using various classification methods, including a widely adopted pixel-based protocol by the World Urban Database and Access Portal Tools (WUDAPT) Project. However, few studies to date have explored the potential of object-based image analysis (OBIA) to facilitate classification of LCZs given their inherent complexity, and few studies have further used the LCZ framework to analyze land cover changes in urban areas over time. This study classified LCZs in the Salt Lake Metro Region, Utah, USA for 1993 and 2017 using a supervised object-based analysis of Landsat satellite imagery and assessed their change during this time frame. The overall accuracy, measured for the most recent classification period (2017), was equal to 64% across 12 LCZs, with most of the error resulting from similarities among highly developed LCZs and non-developed classes with sparse or low-stature vegetation. The observed 1993–2017 changes in LCZs indicated a regional tendency towards primarily suburban, open low-rise development, and large low-rise and paved classes. However, despite the potential for local cooling with landscape transitions likely to increase vegetation cover and irrigation compared to pre-development conditions, summer averages of Landsat-derived top-of-atmosphere brightness temperatures showed a pronounced warming between 1992–1994 and 2016–2018 across the study region, with a 0.1–2.9 °C increase among individual LCZs. Our results indicate that future applications of LCZs towards urban change analyses should develop a stronger understanding of LCZ microclimate sensitivity to changes in size and configuration of urban neighborhoods and regions. Furthermore, while OBIA is promising for capturing the heterogeneous and multi-scale nature of LCZs, its applications could be strengthened by adopting more generalizable approaches for LCZ-relevant segmentation and validation, and by incorporating active remote sensing data to account for the 3D complexity of urban areas.