Monitoring the urban green spaces and landscape fragmentation using remote sensing: a case study in Osmaniye,Turkey

Urban green spaces play a significant role in management of physical activity, psychological well-being, and public health of urban residents. With the expansion of urban areas in Turkey during the past decades, urban green spaces have been fragmented and dispersed causing impairment and environmental degradation. The purpose of this study is to model urban green space distribution by focusing on the landscape fragmentation in city of Osmaniye using remote sensing and geographic information system technology. Normalized difference vegetation index (NDVI) and urban landscape ratio (ULR) were used to assess the proximity and spatial arrangement of urban green spaces within the neighbor landscapes to quantify the urban land use effect. The geospatial analysis results showed that increase in total built-up area and population has significantly decreased the urban green space cover because of high levels of landscape fragmentation in urban city center. Also, due to high levels of landscape fragmentation, approximately 45% of the Osmaniye city is estimated to become urbanized by 2030. This study demonstrated the benefits of directional vegetation index application with geospatial analyses in characterizing the environmental quality for planning and management of urban green spaces. This approach could be used for determining the future urban land development scenarios correlating with regional planning procedures.     

Assessment of visual landscape quality using IKONOS imagery

The assessment of visual landscape quality is of importance to the management of urban woodlands. Satellite remote sensing may be used for this purpose as a substitute for traditional survey techniques that are both labour-intensive and time-consuming. This study examines the association between the quality of the perceived visual landscape in urban woodlands and texture measures extracted from IKONOS satellite data, which features 4-m spatial resolution and four spectral bands. The study was conducted in the woodlands of Istanbul (the most important element of urban mosaic) lying along both shores of the Bosporus Strait. The visual quality assessment applied in this study is based on the perceptual approach and was performed via a survey of expressed preferences. For this purpose, representative photographs of real scenery were used to elicit observers’ preferences. A slide show comprising 33 images was presented to a group of 153 volunteers (all undergraduate students), and they were asked to rate the visual quality of each on a 10-point scale (1 for very low visual quality, 10 for very high). Average visual quality scores were calculated for landscape. Texture measures were acquired using the two methods: pixel-based and object-based. Pixel-based texture measures were extracted from the first principle component (PC1) image. Object-based texture measures were extracted by using the original four bands. The association between image texture measures and perceived visual landscape quality was tested via Pearson’s correlation coefficient. The analysis found a strong linear association between image texture measures and visual quality. The highest correlation coefficient was calculated between standard deviation of gray levels (SDGL) (one of the pixel-based texture measures) and visual quality (r?=?0.82, P?<?0.05). The results showed that perceived visual quality of urban woodland landscapes can be estimated by using texture measures extracted from satellite data in combination with appropriate modelling techniques.     

Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, USA

This paper intended to examine the seasonal variations in the relationship between landscape pattern and land surface temperature based on a case study of Indianapolis, United States. The integration of remote sensing, GIS, and landscape ecology methods was used in this study. Four Terra's ASTER images were used to derive the landscape patterns and land surface temperatures (LST) in four seasons in the study area. The spatial and ecological characteristics of landscape patterns and LSTs were examined by the use of landscape metrics. The impact of each land use and land cover type on LST was analyzed based on the measurements of landscape metrics. The results show that the landscape and LST patterns in the winter were unique. The rest of three seasons apparently had more agreeable landscape and LST patterns. The spatial configuration of each LST zone conformed to that of each land use and land cover type with more than 50% of overlap in area for all seasons. This paper may provide useful information for urban planers and environmental managers for assessing and monitoring urban thermal environments as result of urbanization.     

Attributes of reliable long-term landscape-scale studies: Malpractice insurance for landscape ecologists

Monitoring long-term change in forested landscapes is an intimidating challenge with considerable practical, methodological, and theoretical limitations. Current field approaches used to assess vegetation change at the plot-to-stand scales and nationwide forest monitoring programs may not be appropriate at landscape scales. We emphasize that few vegetation monitoring programs (and, thus, study design models) are designed to detect spatial and temporal trends at landscape scales. Based primarily on advice from many sources, and trial and error, we identify 14 attributes of a reliable long-term landscape monitoring program: malpractice insurance for landscape ecologists. The attributes are to: secure long-term funding and commitment; develop flexible goals; refine objectives; pay adequate attention to information management; take an experimental approach to sampling design; obtain peer-review and statistical review of research proposals and publications; avoid bias in selection of long-term plot locations; insure adequate spatial replication; insure adequate temporal replication; synthesize retrospective, experimental, and related studies; blend theoretical and empirical models with the means to validate both; obtain periodic research program evaluation; integrate and synthesize with larger and smaller scale research, inventory, and monitoring programs; and develop an extensive outreach program. Using these 14 attributes as a guide, we describe one approach to assess the potential effect of global change on the vegetation of the Front Range of the Colorado Rockies. This self-evaluation helps identify strengthes and weaknesses in our program, and may serve the same role for other landscape ecologists in other programs.     

Automatic habitat classification methods based on satellite images: A practical assessment in the NW Iberia coastal mountains

Although remote sensing is increasingly in use for habitat mapping, traditional image classification methods tend to suffer shortcomings due to non-normality of spectral signatures, as well as overlapping and heterogeneity in radiometric responses of natural and semi natural vegetation. Methods using non-parametric classifiers and object-oriented analysis have been suggested as possible solutions for overcoming these limitations. In this paper, we aimed at evaluating the performance of some of these techniques for the European Natura 2000 network of protected areas habitats mapping. For this purpose, we tested different methods of supervised image classification in the Northern Mountains of Galicia, Spain, an area included in the Natura 2000 network, which is characterized by a highly heterogeneous landscape. Methods involved the use of maximum likelihood and nearest neighbour decision rules in per-pixel and per-object classification analyses on Landsat TM imagery. Per-object classifications were completed using the segment mean and segment means plus standard deviation feature spaces. The results showed the existence of significant differences in the accuracies for the different methodologies, their strengths and weaknesses and identified the most adequate approach for habitat mapping. Analyses pointed out that significant improvements in accuracy were achieved only under certain combinations of per-object analysis, non-parametric classifiers and high dimensionality feature space.     

An examination of the effect of landscape pattern, land surface temperature, and socioeconomic conditions on WNV dissemination in Chicago

This paper developed an approach by the synthesis of remote sensing, landscape metrics, and statistical methods to examine the effects of landscape pattern, land surface temperature, and socioeconomic conditions on the spread of West Nile virus (WNV) caused by mosquitoes and animal hosts in Chicago, USA. Land use/land cover and land surface temperature images were derived from Terra’s Advanced Spaceborne Thermal Emission and Reflection Radiometer imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns in the study area. The positive reports of mosquitoes and animal hosts for WNV in fall, 2001–2006, were collected from the Cook County Public Health Department. Forty-nine municipalities were found to have WNV-positive records in mosquitoes and animal hosts in fall 2004. Socioeconomic data were obtained from the 2000 US Census. Statistical analysis was applied to WNV data in fall 2004 to identify the relationship between potential predictors and WNV spread. As a result, landscape factors, such as landscape aggregation index and the urban areas and areas of grass and water, showed strong correlations with the WNV-positive records. Socioeconomic conditions, such as the population over 65 years old, also showed a strong correlation with WNV-positive records. Thermal conditions of water showed a less but still considerable correlation to WNV-positive records. This research offers an opportunity to explore the effects of landscape pattern, land surface temperature, and socioeconomic conditions on the spread of WNV caused by mosquitoes and animal hosts. Results can contribute to public health and environmental management in the study area.     

Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China

Remote sensing of local environmental conditions is not accessible if substrates are covered with vegetation. This study explored the relationship between vegetation spectra and karst eco-geo-environmental conditions. Hyperspectral remote sensing techniques showed that there were significant differences between spectral features of vegetation mainly distributed in karst and non-karst regions, and combination of 1,300- to 2,500-nm reflectance and 400- to 680-nm first-derivative spectra could delineate karst and non-karst vegetation groups. Canonical correspondence analysis (CCA) successfully assessed to what extent the variation of vegetation spectral features can be explained by associated eco-geo-environmental variables, and it was found that soil moisture and calcium carbonate contents had the most significant effects on vegetation spectral features in karst region. Our study indicates that vegetation spectra is tightly linked to eco-geo-environmental conditions and CCA is an effective means of studying the relationship between vegetation spectral features and eco-geo-environmental variables. Employing a combination of spectral and spatial analysis, it is anticipated that hyperspectral imagery can be used in interpreting or mapping eco-geo-environmental conditions covered with vegetation in karst region.     

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the “One Sensor at Different Scales” (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R ² of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.     

A comparison of two procedures to estimate three basic monitoring landscape metrics for monitoring

An interesting alternative to wall-to-wall mapping approaches for the estimation of landscape metrics is to use sampling. Sample-based approaches are cost-efficient, and measurement errors can be reduced considerably. The previous efforts of sample-based estimation of landscape metrics have mainly been focused on data collection methods, but in this study, we consider two estimation procedures. First, landscape metrics of interest are calculated separately for each sampled image and then the image values are averaged to obtain an estimate of the entire landscape (separated procedure, SP). Second, metric components are calculated in all sampled images and then the aggregated values are inserted into the landscape metric formulas (aggregated procedure, AP). The national land cover map (NLCM) of Sweden, reflecting the status of land cover in the year 2000, was used to provide population information to investigate the statistical performance of the estimation procedures. For this purpose, sampling simulation with a large number of replications was used. For all three landscape metrics, the second procedure (AP) produced a lower relative RMSE and bias than the first one (SP). A smaller sample unit size (50 ha) produced larger bias than a larger one (100 ha), whereas a smaller sample unit size produced a lower variance than a larger sample unit. The efficiency of a metric estimator is highly related to the degree of landscape fragmentation and the selected procedure. Incorporating information from all of the sampled images into a single one (aggregated procedure, AP) is one way to improve the statistical performance of estimators.     

Spatiotemporal changes of landscape pattern in response to deforestation in Northeastern Turkey: a case study in Rize

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzes spatial and temporal changes in land use and forest cover patterns in a typical mountain forest area in Rize Forest Enterprise of the Northeastern part of Turkey. The area is investigated by evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1984 and 2007 using GIS and FRAGSTATS. The quantative evidences presented here showed that there were drastic changes in the temporal and spatial dynamics of land use/forest cover. As an overall change between 1984 and 2007, there was a net decrease of 2.30% in total forested areas. On one hand, productive forest areas decreased 12,506 ha, on the other hand, degraded forest areas increased 14,805 ha. In examining the changes of crown closure and development stages of forest ecosystem during the study period, the forest stand area with medium crown closures increased. Regenerated area increased while the other development stages were left to grow to mature development stages in the period. These results regarding to crown closure and development stage showed that forest quality has increased but total forest areas decreased. This is partially due to out-migration of rural population in Rize and Cayeli towns. In terms of spatial configuration, analysis of the metrics revealed that landscape structure in Study area had changed substantially over the 23-year study period, resulting in fragmentation of the landscape as indicated by the large patch numbers and the smaller mean patch sizes due to heavy timber subtraction, illegal cutting, and uncontrolled stand treatments.     

Identification of Characteristic Regions and Representative Stations: A Study of Water Quality Variables in the Kattegat

Gradients in nutrient distributions and the effects of eutrophication are common features in most coastal marine areas. These structures occur in aquatic systems due to spatial differences in hydrography, nutrient loading and key biogeochemical processes. Two statistical methods, cluster analysis and probability mapping, have been used in the present study to determine characteristics and patterns in water quality variables. Combined, these two methods provide a useful tool to statistically determine spatial homogeneity and representativity of areas and stations. A case study is presented here in which water quality variables (salinity, dissolved inorganic nitrogen, dissolved inorganic phosphorus and chlorophyll) in surface waters of the Kattegat are analysed for the time period 1993-1997. It was found that morphology, the proximity to sources of nutrient loading from land, nutrient uptake and the infrequent water exchange between the Baltic Sea in the south and the Skagerrak in the north all contribute to create distinct regions of water quality. Regions with concentrations significantly different from the overall mean are identified. In addition to identification of regions with similar characteristics, representative stations (as well as not representative stations) for the respective regions were made. This type of information can be used to design new or revise old monitoring programs.     

Landscape changes as a factor affecting the course and consequences of extreme floods in the Otava river basin, Czech Republic

The paper presents the analysis of anthropogenical modifications of the landscape in relation to the course and consequences of floods. The research was conducted in the Otava river basin which represents the core zone of the extreme flood in August 2002 in Central Europe. The analysis was focused on the key indicators of landscape modification potentially affecting the runoff process - the long-term changes of land-use, changes of land cover structure, land drainage, historical shortening of the river network and the modifications of streams and floodplains. The information on intensity and spatial distribution of modifications was derived from different data sources - historical maps, available GIS data, remote sensing and field mapping. The results revealed a high level of spatial diversity of anthropogenical modifications in different parts of the river basin. The intensive modifications in most of indicators were concentrated in the lowland region of the river basin due to its agricultural use; however important changes were also recorded in the headwater region of the basin. The high spatial diversity of the modifications may result in their varying effect on the course and consequences of floods in different parts of the river basin. This effect is demonstrated by the cluster analysis based on the matrix of indicators of stream and floodplain modification, physiogeographical characteristics and geomorphological evidences of the flood in August 2002, derived from the individual thematic layers using GIS.     

Performance assessment of geospatial simulation models of land-use change—a landscape metric-based approach

Performance evaluation is a critical step when developing land-use and cover change (LUCC) models. The present study proposes a spatially explicit model performance evaluation method, adopting a landscape metric-based approach. To quantify GEOMOD model performance, a set of composition- and configuration-based landscape metrics including number of patches, edge density, mean Euclidean nearest neighbor distance, largest patch index, class area, landscape shape index, and splitting index were employed. The model takes advantage of three decision rules including neighborhood effect, persistence of change direction, and urbanization suitability values. According to the results, while class area, largest patch index, and splitting indices demonstrated insignificant differences between spatial pattern of ground truth and simulated layers, there was a considerable inconsistency between simulation results and real dataset in terms of the remaining metrics. Specifically, simulation outputs were simplistic and the model tended to underestimate number of developed patches by producing a more compact landscape. Landscape-metric-based performance evaluation produces more detailed information (compared to conventional indices such as the Kappa index and overall accuracy) on the model’s behavior in replicating spatial heterogeneity features of a landscape such as frequency, fragmentation, isolation, and density. Finally, as the main characteristic of the proposed method, landscape metrics employ the maximum potential of observed and simulated layers for a performance evaluation procedure, provide a basis for more robust interpretation of a calibration process, and also deepen modeler insight into the main strengths and pitfalls of a specific land-use change model when simulating a spatiotemporal phenomenon.     

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics

Bafa Lake Nature Park is one of Turkey’s most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural–natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.     

Monitoring structural assets of bi-species groves according to land use types: a case study from arid plains

This paper provides a framework for the managers to devise means to protect, restore, and maintain the remaining bi-species groves for sustainable management of fragile arid land ecosystem. At the moment, there is no information available about the structural and functional ecology of these dwindling remnants. The selection criteria for the classification of the groves are based on understanding the positive association between the two species, Prosopis cineraria and Salvadora oleoides, in terms of spatial pattern and morphological features. It was achieved by highlighting the attributes of the benchmark grove and classification of other groves in reference to it. The results clearly show that positive association in the groves is due to differences in the growth strategies of the two species in terms of above- and belowground biomass allocation and architecture. Most of the groves are in various stages of degradation, and anthropogenic interferences are the major determinant linked with the declining status of the groves. These activities affect the complimentary attributes of the bi-species groves, thus disturbing the characteristic structural features which contributed to the stability of this fragile landscape.     

Monitoring soil productive potential

Desertification involves the loss of soil productive potential, but a means of assessing and monitoring the progress of desertification on the soil has been elusive. Soil is so varied and complex that methods of assessing condition are too slow, tedious, and expensive for routine use. Moreover, differences in soil type can be confused with soil condition. This paper presents a structured method of assessing soil condition. This method is based on recognizing and classifying soil surface features and examining soil properties that reflect the status of the processes of erosion, infiltration, and nutrient cycling. Published in the form of a user manual, the method has the following three stages: (1) defining the geomorphic setting of the site, (2) recognizing patch/interpatch associations and the mode of erosion at the landscape scale, and (3) assessing soil surface condition ratings in quadrats sited within the landscape pattern patches. Stage 3 is achieved by observing each of 11 features in the field and classifying their status according to detailed fieldnotes and photographs. The method applies to a wide range of soil types and biogeographical regimes and has proven to be repeatable among observers and quickly transferred to new observers.     

Fate of coliforms and pathogenic parasite in four full-scale sewage treatment systems in India

Global positioning systems (GPS) are increasingly being used for habitat mapping because they provide spatially referenced data that can be used to characterize habitat structure across the landscape and document habitat change over time. We evaluated the accuracy of using a GPS for determining the size and location of habitat patches in a riverine environment. We simulated error attributable to a mapping-grade GPS receiver capable of achieving sub-meter accuracy onto discrete macrophyte bed and wood habitat patches (2 to 177 m(2)) that were digitized from an aerial photograph of the Laramie River, Wyoming, USA in a way that emulated field mapping. Patches with simulated error were compared to the original digitized patches. The accuracy in measuring habitat patches was affected most by patch size and less by patch shape and complexity. Perimeter length was consistently overestimated but was less biased for large, elongate patches with complex shapes. Patch area was slightly overestimated for small patches but was unbiased for large patches. Precision of area estimates was highest for large (>100 m(2)), elongate patches. Percent spatial overlap, a measure of the spatial accuracy of patch location, was low and variable for the smallest patches (2 to 5 m(2)). Mean percent spatial overlap was not related to patch shape but the precision of overlap was lower for small, elongate, and complex patches. Mapping habitat patches with a mapping-grade GPS can yield useful data, but research objectives will determine the acceptable amount of error and the smallest habitats that can be reliably measured.     

Determining recreational, scenic, and historical–cultural potentials of landscape features along a segment of the ancient Silk Road using factor analyzing

Generally, roads are structures connecting areas of special importance to each other (e.g., from urban areas to villages). In addition to functioning as transportation mediums, roads have aesthetic qualities by means of their recreational, scenic, and cultural functions. One of these unexplored roads, the Trabzon–Gümü?hane old state highway in the Northeast Turkey, the subject of this study, is quite unique for being a part of the historical Silk Road. The aim of the study is to determine the recreational, scenic, and cultural potentials of this road and to identify the landscape qualities based on these potentials. After dividing the road into three sections for comparison purposes, data gathered from basic digital maps obtained from The General Directorate of Rural Services (the governmental agency that is responsible for producing such digital maps) and field trips were entered into maps using geographic information system followed by creating demonstration films using photographs and video camera images of the natural and cultural characteristics of the area. Then, these films were evaluated by an expert team to identify the road’s recreational, scenic, and cultural potentials. The results of the evaluation process, the relationships between determined landscape characteristics for each function, and the contribution scores of different functions assigned for the artificial features were statistically analyzed. The analyses showed a very strong relationship between the sections and the contribution scores of the recreation and the scenic functions. The results of these analyses also revealed some landscape characteristics having high contribution values for all the functions. This, in turn, helped in determining a potential of the study area to become a greenway.