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The farming-pastoral ecotone in Gansu Province, a crucial green barrier in northwestern China, faces a conflict between economic development and environmental fragility. Scientifically assessing the landscape ecological risks in this region is essential for developing an early warning system for ecological security and ensuring the sustainable management of regional ecosystems. This study systematically analyzes the dynamic evolution patterns and clustering characteristics of landscape ecological risk along the topographic gradient in the area, using Land-Use and Land-Cover Change (LUCC) data from five periods (each period representing 10 years) between 1980 and 2020, as well as Digital Elevation Model (DEM) data. Methods such as CA-Markov and the Topographic Position Index (TPI) were employed to assess these risks. Additionally, the study simulates the spatial distribution patterns of ecological risks in future years. The results reveal that from 1980 to 2020, the area of built-up land in the farming-pastoral ecotone of Gansu Province increased by approximately 82%, with roughly 21% of the expansion occurring at the expense of grasslands and 53% from arable land. Ecological risk in the study area exhibits a spatial distribution pattern characterized by lower risk in the southwest and higher risk in the northeast. Overall, ecological risk initially increased and then decreased. The area of high-risk zones has steadily decreased by approximately 50% since 2010, primarily in regions with low topographic gradients and high human activity. In other areas, high-risk levels are directly proportional to the topographic gradient, showing a high degree of spatial clustering. Consequently, land-use planning should be tailored to local conditions, and a long-term monitoring mechanism should be established. This study provides novel insights into the spatiotemporal changes in landscape ecological risk in ecologically vulnerable areas, focusing on topographic gradients. [ABSTRACT FROM AUTHOR]

Context: The tropical Andes have a long history of human land use, which has affected vegetation patterns especially at high elevations. However, reference patterns to quantify these effects are missing due to lacking data from mountain ranges unaffected by humans. Objectives: We compared landscape-scale patterns of forest distribution in the largest tropical Andean mountain range without high-elevation human occupancy, the Cordillera de Vilcabamba, and a nearby range with a long land-use history, the Cordillera de San Miguel, in Peru. Methods: We quantified topographical positions (exposition, slope, wetness index) of 12.5 × 12.5-m2 pixels with and without forest cover in 100-m elevational bands and compared the study regions. Results: In the undisturbed range (Vilcabamba), forest consistently occurred on steeper slopes than non-forest, differing little in other topographic metrics except a slight preference for the less sunny South- and West-facing slopes. In the disturbed range (San Miguel), forest showed little preference for any landscape position at elevations below 3500 m, but at higher elevations patterns were very clear: forest was more restricted to valley bottoms, as indicated consistently by higher topographic wetness and lower slope and topographic position indices, and to the less sunny South-facing slopes. Conclusions: Land-use has a strong influence on landscape-level forest distribution in this part of the tropical Andes. Similar effects are likely in other tropical mountains, although no reference areas are available in most of them. The patterns described here can support the use of remote sensing to detect minimally disturbed tropical alpine-treeline ecotones, which should be focal points for conservation and research. [ABSTRACT FROM AUTHOR]

Urban growth in Indonesia is accelerating, particularly in areas with complex geomorphological features. This study examines the spatiotemporal variations of built-up area expansion in the Yogyakarta Urban Region (YUR), a rapidly urbanizing area characterized by diverse landforms and significant development pressures. Using Landsat satellite imagery (2001–2022), the study employed the Landscape Expansion Index (LEI) to classify urban expansion types and the Topographic Position Index (TPI) to analyze geomorphological characteristics. The findings reveal that edge-expansion dominated upper slopes, contributing 69%, 75%, and 79% of built-up area growth in 2001–2008, 2008–2015, and 2015–2022, respectively. Simultaneously, the outlying expansion type has steadily increased, particularly in U-shaped valleys, which grew significantly from 51.35 ha (2001–2008) to 109.28 ha (2008–2015) and 219.14 ha (2015–2022), highlighting an escalating risk of urban sprawl. These findings highlight the need for targeted urban planning policies to monitor and control growth patterns in geomorphologically sensitive areas, reducing sprawl and promoting sustainable development. [ABSTRACT FROM AUTHOR]

The landform of the region highly influences the dynamics of the flood and plays a crucial role in directing the water flow, affecting the speed and volume of runoff. Assam, located in northeast India, experiences floods yearly due to adverse climatic conditions and complex terrain features. The objective of the present study is to understand the landform classification of Assam using the topographic position index (TPI) and geomorphon-based automated classification of landform (ACL) method and its spatial distribution with slope, geology, soil, LULC, and flood inundation. The ACL method shows that gentle slopes or flat areas occupy the maximum area ranging from 56.17 to 68.10% for TPI‐based slope position classes, and for geomorphon, slope feature occupies 20.61–25.39% of the total area. The spatial distribution of TPI and geomorphon-based landform classification was different because TPI compares the elevation of a point to the average elevation of its neighbourhood, while geomorphon classifies the landscape into predefined landform classes based on terrain shape and the spatial arrangement of elevation values. In both models, valleys are the most dominant landform class and are mainly present in the Central and Barak valley of Assam. The built-up areas and waterbodies on vulnerable landform classes increase their flood susceptibility. About 38.08% of the inundated area was found in wide valleys and 31% of the inundated area lies under flat landforms. The present study can be effective in land use planning, sustainable natural resource management, disaster risk management, and mitigation strategies. [ABSTRACT FROM AUTHOR]

This study scrutinizes interannual (2003–2023) variations in coastal upwelling along the Guangdong Province during summers (June–August) in the northeastern South China Sea (NESCS) by comprehensively applying the moderate-resolution imaging spectroradiometer (MODIS) remote sensing sea surface temperature (SST) and chlorophyll concentration (CHL) data and the model reanalysis product. The results show that SST and upwelling intensity in the sea area have significant (p < 0.05) rising trends in the last 21 years. The CHL shows an upward but insignificant trend, which is affected simultaneously by the rise in SST and the enhancement of upwelling. Further analysis reveals that the interannual variations in upwelling are robustly related to the wind fields' variations in the coastal region. A clockwise/counter-clockwise anomaly in the wind field centered on the NESCS facilitates alongshore/onshore winds near the Guangdong coast, which can strengthen/weaken coastal upwelling. Based on the correlation between wind field variations and large-scale climate factors, long-term variations in the upwelling intensity can be primarily predicted by the Oceanic Niño Index. [ABSTRACT FROM AUTHOR]

To explore relationships between spatial distributions of northern shrimp Pandalus eous and environmental factors along the coastline of Honshu Island in the Sea of Japan, we built delta-type two-step generalized additive models (delta-GAM) based on bottom trawl surveys conducted in 2013–2022. The models provide the first quantitative analysis of the species' habitat, showing that its distribution is associated with bottom sediment type, depth, slope and topographic position index (TPI) alongside the effects of year and region. From the delta-GAM response plots, species habitat preferences in the Sea of Japan were estimated as follows: seafloor deeper than 283 m; muddy rather than sandy bottoms; gently sloped to flat bottoms (<0.8° in slope); and valleys rather than ridges (TPI < 0.9). These results were reviewed in detail along with previously reported distribution records of northern shrimp. Standardized density (s-density) per fishing grid cell (10′ square latitude–longitude mesh) estimated from the delta-GAM results indicated that this species is widely distributed on the continental slope along the coast of Honshu Island. To test plausibility of the s-density analysis, we compared s-density per fishing grid cell with nominal CPUE (kg per haul) per fishing grid cell based on official logbook data from large offshore trawl fisheries. The two were generally positively correlated by year, and the delta-GAM results were assumed to be fairly robust. Finally, potential fishing grounds were explored based on the delta-GAM results. [ABSTRACT FROM AUTHOR]

Soil is one of the most important natural resources of any country, erosion process degrades the soil and leaves irreparable damage. The aim of this study is to estimate the rate of soil erosion and its relationship with landforms and lithology unites of Zonuzchay catchment in Marand county. In this study was used the modified global model of soil loss (RUSEL), geographic information system (GIS) and remote sensing (RS) to estimate the rate of soil erosion. To implement the model, rainfall erosivity factors (R), soil erodibility factor (K), slope length-gradient factor (LS), conservation practice factor (P) and cover management factor (C) in Arc GIS environment calculated and Then a soil erosion map was drawn in five class of hazard (very low, low, medium, high and very high). Topographic position index (TPI) was used to classify and map the landforms of the catchment. Then, the role of different landforms and lithology unites in relation to soil erosion rates was investigated by combining relevant maps. The results showed that the values of Average soil erosion is 1.71 tons per hectare per year. Valleys and deeply incised streams on heights and slopes (94.27 km2) and then Mountain tops and high ridges (89.21 km2) have the highest rate of erosion. In Zonuzchay catchment, soil erosion is mostly on the flysch type deposits, red and gray conglomerates with Marl layers and alluvial terraces. Investigation of regression relationships between (RUSLE) model factors and soil erosion of Zonuzchay catchment showed that the slope length-gradient factor (LS) has the greatest effect in calculating the rate of erosion of Zonuzchay catchment. [ABSTRACT FROM AUTHOR]

Hillslope elements and land cover types are primarily determining the spatial variability of soils in the hilly and mountainous landscape. Among the soil forming factors, topography strongly influences pedogenic process and governs the variability of soils in hilly and mountainous landscape. This study mainly focusses on characterizing soil quality parameters distribution based on the hillslope elements and soil–landscape units in the watershed. Digital terrain model (DTM)-derived topographic position index was used to delineate various hillslope elements. Land use/land cover map was generated using random forest machine learning technique. Hillslope elements, land use/land cover types and aspects were integrated in GIS environment to generate soil–landscape unit map of the watershed. Soil samples were collected based on various soil–landscape units to characterize soil quality parameters such as total carbon (TC) soil organic matter (SOM), total nitrogen (TN), aggregate stability (SAS) in the watershed. SOM ranged from 1.6% to 10.05% and higher estimated in shoulder (forest) followed by valley (agriculture) and toe slope (forest). TC and TN contents ranged from 0.93% to 5.84% and 0.11% to 0.38%, respectively. The C:N ratio ranged from 7.96% to 18.31% and high value was found in shoulder (forest) followed by valley (agriculture) and toe slope (forest). SAS under different hillslope elements in the area ranged from 0.0.552 to 0.615 indicating large spatial variation of soil quality parameters. The study indicates that in hilly and mountainous landscape, topography and land cover types have major role in determining soil quality. DTM-based soil–landscape units' delineation can be helpful to study soil quality variability and can be used to generate soil map for the hilly and mountainous watershed. The significance of this study lies in its potential to make substantial contributions to land use planning, sustainable land management and environmental conservation planning in the challenging and ecologically fragile and sensitive Himalayan region. [ABSTRACT FROM AUTHOR]

Copyright of Research of Soil & Water Conservation is the property of Institute of Soil & Water Conservation, Chinese Academy of Sciences & Ministry of Water Resources and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on the absolute dynamic topography data from the Copernicus Marine Environment Monitoring Service, this paper applies the Topographic Position Index to develop a new approach for mapping the anticyclonic eddies in the South China Sea (SCS). The results show that anticyclonic eddies are active in the deep basin of SCS, and the five selected parameters (number or frequency, lifetime, kinetic energy, amplitude, and area or radius) of anticyclonic eddies have a similar temporal variation and a similar spatial distribution pattern. (1) As for monthly variations, anticyclonic eddies are active in late spring and most active in summer. (2) The El Niño–Southern Oscillation had a stronger impact on the inter-annual variations of anticyclonic eddies in the SCS before 2013, resulting in a significant transition of inter-annual variations of these five parameters in around 2004. After 2013, most of these five parameters had a minimum in 2015 and a maximum in 2017. (3) Analyses show that the eddy activities in the SCS are significantly influenced by the monsoon wind and the western boundary current like Kuroshio. Therefore, the areas southwest of Taiwan Island and east of Vietnam are the two areas where the anticyclonic eddies are most active, with much larger eddy kinetic energy and much higher eddy amplitude. [ABSTRACT FROM AUTHOR]

Changes in topography, such as terrain elevation and slope, are an important source of landscape complexity influencing the ecology of animals, particularly in mountainous landscapes. In such landscapes animals navigate changes in elevation and slope in their daily movement. Despite the importance of topographic variation, studies of animal ecology in mountainous landscapes tend not to explicitly consider those effects on species detection. We deployed a broad‐extent, coarse resolution camera‐trapping system across a landscape with considerable complexity and quantified the influence of topographic variables on detection probability conditional on occurrence for multiple mammal species. Specifically, we examined the fine‐scale effects of terrain steepness and topographic position (i.e. ridges, mid‐slopes or valleys) on detection probability for 14 mammal species at camera‐traps. We found that detection probability increased on gently sloping terrain for six species and decreased on the steepest slopes sampled for three of these species and three additional species. Among four other mammal species, detection probability changed according to local topographic position though the directionality of these responses varied among these species. Several species, primarily meso‐carnivores as well as larger‐bodied species, like mule deer and black bears, were more detectable on gentle slopes than flat terrain. This pattern suggests that many species may use moderately steep terrain for the resources or heterogeneity they provide. Topographic position had comparatively less effect on species detection probabilities, suggesting that this variable does not have a strong effect on fine‐scale space use of animal species in mountainous regions. These relationships suggest that researchers should consider local terrain when siting camera traps in mountainous landscapes and analyzing survey data from such landscapes. Studies that compare the detection of mammal species at cameras deployed in close proximity will improve our understanding of fine‐scale topographic effects on mammal movement and detection. [ABSTRACT FROM AUTHOR]

In qualitative–quantitative assessment of geodiversity, geomorphology describes landscape forms suggesting specific locations as geosites. However, all digital elevation models (DEM) contain information only about altitude and coordinate systems, which are not enough data for inclusion assessments. To overcome this, researchers may transform altitude parameters into a range of different models such as slope, aspect, plan, and profile curvature. More complex models such as Geomorphon or Topographic Position Index (TPI) may be used to build visualizations of landscapes. All these models are rarely used together, but rather separately for specific purposes—for example, aspect may be used in soil science and agriculture, while slope is considered useful for geology and topography. Therefore, a qualitative–quantitative assessment of geodiversity has been developed to recognize possible geosite locations and simplify their search through field observation and further description. The Coromandel Peninsula have been chosen as an area of study due to landscape diversity formed by Miocene–Pleistocene volcanism which evolved on a basement of Jurassic Greywacke and has become surrounded and partially covered by Quaternary sediments. Hence, this research provides a comparison of six different models for geomorphological assessment. Models are based on DEM with surface irregularities in locations with distinct elevation differences, which can be considered geosites. These models have been separated according to their parameters of representations: numerical value and types of landscape. Numerical value (starting at 0, applied to the area of study) models are based on slope, ruggedness, roughness, and total curvature. Meanwhile, Geomorphon and TPI are landscape parameters, which define different types of relief ranging from stream valleys and hills to mountain ranges. However, using landscape parameters requires additional evaluation, unlike numerical value models. In conclusion, we describe six models used to calculate a range of values which can be used for geodiversity assessment, and to highlight potential geodiversity hotspots. Subsequently, all models are compared with each other to identify differences between them. Finally, we outline the advantages and shortcomings of the models for performing qualitative–quantitative assessments. [ABSTRACT FROM AUTHOR]

Predicting species geographic distributions is key to managing invasive species, conserving biodiversity, and understanding species' environmental requirements. Species distribution models (SDMs) commonly focus on climatic predictors, but other environmental factors can also be essential, particularly for species with specialized habitats defined by hydrologic, topographic, or edaphic conditions (e.g., riparian, wetland, alpine, coastal, serpentine). Here, we demonstrate a novel approach for capturing strong effects of both hydrologic and climatic predictors in SDMs for riparian plants, by merging analyses targeted at environmental drivers within riparian ecosystems and across the western USA (3.8 × 106 km2). We developed presence‐background SDMs from five algorithms for three invasive riparian trees (Tamarix ramossisima/chinensis [saltcedar], Elaeagnus angustifolia [Russian olive], and Ulmus pumila [Siberian elm]) and three native Populus spp. (cottonwoods). We used separate background datasets to develop models with different spatial scales of inference: (1) spatially filtered random points to represent available habitat across the study area and (2) target‐group points from Salix (willow) occurrences to represent available riparian habitat. Random‐background models captured hydrologic drivers of riparian tree distributions relative to the largely upland western USA, whereas Salix‐background models captured climatic drivers within the context of riparian ecosystems. Combining predictions from the two backgrounds identified hydrologically suitable habitats within climatically suitable regions, resulting in fewer false "absences" than either background alone, improving predictions over previous SDMs, and providing more complete information to guide management decisions. Surprisingly, the predicted habitat for U. pumila, a newly recognized riparian invader, was as or more extensive than Populus deltoides/fremontii, T. ramossisima/chinensis, and E. angustifolia, the most common riparian tree complexes in the western USA. Watersheds constituting 20% of U. pumila predicted habitat contained no occurrence records, indicating high risk of future and unrecognized invasions. Combining models from random and ecosystem‐specific target‐group backgrounds may improve SDMs for species from many specialized habitats, providing a method to link predicted distributions to localized geographic features while capturing broad‐scale climatic requirements. [ABSTRACT FROM AUTHOR]

The availability of high-resolution digital elevation models (DEM) and advancements in geospatial techniques enable a more accurate measure of slope position classes and classification of landforms using algorithms like topographic position index (TPI). In this study, TPI-based slope position classes are used for the identification of major relief features like ridges, and these are embedded with DEM-derived terrain slope to perform the topographic amplification-based classification of the North Eastern Region (NER) of India, according to the present European (Eurocode-8) and Italian seismic codes using GIS tools. They are classified into four topographic classes: T1, T2, T3, and T4. The relation of geological units, seismic site classification map, and land use land cover (LULC) classes with identified topographic classes for the study region are analyzed. The results reveal that ~ 25% of the study area is a potentially high amplification zone (T4 class; amplification factor of 1.4 as per Eurocode-8), primarily associated with dense and light vegetation type land cover. The Indian seismic recording station sites and the epicenters of past earthquake events in the region are classified based on the obtained topographic classification map. Approximately, 47% of earthquake events of large magnitudes and ~ 30% of strong motion network (SMN) station sites are in localities with potential topographic effects. The human settlements are predominantly found in places identified with no or minimal amplification zone (T1 class; amplification factor of 1). The presented topographic classification map of NER can assist the decision-makers and authorities to identify potentially high amplification areas considering seismic hazards and making choices for future infrastructural development. [ABSTRACT FROM AUTHOR]

Defining river networks from a digital elevation model (DEM) is a critical step in many hydrological studies. Most methods rely on analyses of flow accumulation based on a single drainage area threshold value. Landscape heterogeneity hinders the definition of drainage pixels by exceeding a threshold. In this study, we propose a method that automatically accounts for variable drainage density in the definition of river networks from relatively coarse DEMs by using the topographic position index (TPI) as an auxiliary variable, therefore calling it the Topographic Position-based Stream definition (TPS). We tested the TPS method with the 90 m resolution MERIT-DEM (Multi-Error-Removed Improved-Terrain DEM) in Brazil, applying it to three river basins with contrasting landforms and climates. The method improved drainage representation in all analysed regions. It successfully represented stream networks with intra-basin variable drainage density by using a single DEM and three parameters, showing potential for hydrological applications at multiple spatial scales. [ABSTRACT FROM AUTHOR]

Earth surface study or Geomorphology is one of the fundamental physical geographic studies. The ultimate result of the geomorphological study is shown as a map and many geomorphological researchers have been developing their geomorphology-mapping methodology over time. Recently, remote sensing methodologies have been developed rapidly in geographical studies, and attempts at geomorphological mapping by remote sensing method have also been made. Thus, in this study, landform classification, one of the geomorphological fundamental studies, was conducted based on “Topographic Position Index” and classified with “Weiss and Jennessy landform classification algorithm”, in the case of the Ulaanbaatar city. As the result of the study, the landform of the Ulaanbaatar city was classified into 6 typologies including Mountain tops high ridges, upper slopes mesas, Midslopes, Open slopes, Plains, and V shape valleys. Accurate classification of the landform is a basic geomorphological concept, and it is used as background information for engineering geomorphology. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With scant information available on domestic DEM quality and suitable evaluation methods, particularly in city regions, this study set out to evaluate and compare nine contemporary seamless DEM from different sources and spatial resolutions. The assessment focused on DEM accuracy, as well as determining the variation in data quality across several urban land cover types and slope classes. This was systematically determined against independent LiDAR-derived control points, co-registered reference grids, and resampled data from relevant land cover information. It showed that different sensor configurations and interpolation techniques directly relate to the unique ground cover and topographic variations as manifested by the particular digital surface model (DSM) or terrain model (DTM). An experimental photogrammetric DTM and SA National DEM compared very well with 'off-the-shelf' tri-stereo Elevation4™ and WorldDEM™ DTM products. Their good performance eluded to them being the least affected by land surface cover and gradient variations. The accuracy metrics produced by the AW3D30 DEM throughout were on average substantially higher than those calculated for both the National DEM and the SRTM-X DEM. Two local commercial versions, the older SADTM and more recent SUDEM, and lastly the ASTER GDEM2 in particular, yielded noticeably less accurate results that would restrain their usefulness. [ABSTRACT FROM AUTHOR]

The shallow landslides assessment is a hard task in territories featuring composite influence of natural and anthropic factors. In Liguria region (northwestern Italy), the landscape presents widespread human intervention prevalently represented by terraces. The assessment of predisposing factors in such landscape deserve a multidisciplinary approach. We implemented a classification methodology based on the Analytical Hierarchy Process. In GIS environment we overlaid several layers: (i) slope, (ii) land use, (iii) lithology, and (iv) aspect. Slope and aspect have been computed on a filtered (based on TPI) high-resolution DTM with the removal of terraces, in order to obtain the pristine slope pattern. Each spatial data was then reclassified according to the weighting procedures thus producing a landslide susceptibility map. This methodology represents a starting point for the correct assessment of shallow landslides occurrence, capable to generate a map, taking in account of the peculiar features of this extremely man-made territory. [ABSTRACT FROM AUTHOR]

Modern advances in cloud computing and machine-leaning algorithms are shifting the manner in which Earth-observation (EO) data are used for environmental monitoring, particularly as we settle into the era of free, open-access satellite data streams. Wetland delineation represents a particularly worthy application of this emerging research trend, since wetlands are an ecologically important yet chronically under-represented component of contemporary mapping and monitoring programs, particularly at the regional and national levels. Exploiting Google Earth Engine and R Statistical software, we developed a workflow for predicting the probability of wetland occurrence using a boosted regression tree machine-learning framework applied to digital topographic and EO data. Working in a 13,700 km2 study area in northern Alberta, our best models produced excellent results, with AUC (area under the receiver-operator characteristic curve) values of 0.898 and explained-deviance values of 0.708. Our results demonstrate the central role of high-quality topographic variables for modeling wetland distribution at regional scales. Including optical and/or radar variables into the workflow substantially improved model performance, though optical data performed slightly better. Converting our wetland probability-of-occurrence model into a binary Wet-Dry classification yielded an overall accuracy of 85%, which is virtually identical to that derived from the Alberta Merged Wetland Inventory (AMWI): the contemporary inventory used by the Government of Alberta. However, our workflow contains several key advantages over that used to produce the AMWI, and provides a scalable foundation for province-wide monitoring initiatives. [ABSTRACT FROM AUTHOR]

Small, seasonal pools and temporary ponds (<4.0 ha) are the most numerous and biologically diverse wetlands in many natural landscapes. Thus, accurate determination of their numbers and spatial characteristics is beneficial for conservation and management of biodiversity associated with these freshwater systems. We examined the utility of a topographic position index (TPI) landscape classification to identify and classify depressional wetlands. We also assessed relationships between topographic characteristics and ponded duration of known wetlands to allow hydrological characteristics to be extended to non-monitored locations in similar landscapes. Our results indicate that this approach was successful at identifying wetlands, but did have higher errors of commission (10%) than omission (5%). Additionally, the TPI procedure provided a reasonable means to correlate general ponded duration characteristics (long/short) with wetland topography. Although results varied by hydrologic class, permanent/long ponded duration wetlands were more often classified correctly (80%) than were short ponded duration wetlands (67%). However, classification results were improved to 100 and 75% for permanent/long and short ponded duration wetlands, respectively, by removing wetlands occurring on an abrupt marine terrace that erroneously inflated pond topographic characteristics. Our study presents an approach for evaluating wetland suitability for species or guilds that are associated with key habitat characteristics, such as hydroperiod. [ABSTRACT FROM AUTHOR]

Satellite-derived surface elevation models are an important resource for landscape archaeological studies. Digital elevation data is useful for classifying land features, characterizing terrain morphology, and discriminating the geomorphic context of archaeological phenomena. This paper shows how remotely sensed elevation data obtained from the Japan Aerospace Exploration Agency's Advanced Land Observing Satellite was integrated with local land system spatial data to digitally classify the topographic slope position of seven broad land classes. The motivation of our research was to employ an objective method that would allow researchers to geomorphometrically discriminate the topographic context of Aboriginal stone arrangements, an important archaeological site type in the Pilbara region of northwest Australia. The resulting digital terrain model demonstrates that stone arrangement sites are strongly correlated with upper topographic land features, a finding that contradicts previous site recordings and fundamentally changes our understanding of where stone arrangement sites are likely to have been constructed. The outcome of this research provides investigators with a stronger foundation for testing hypotheses and developing archaeological models. To some degree, our results also hint at the possible functions of stone arrangements, which have largely remained enigmatic to researchers. © 2017 The Authors. Archaeological Prospection Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Mountain ridges are valued by the Korean people as major and critical sources of natural resources and environment. Despite their recognised values, continuous exploitation and infrastructure development in forestlands have been causing large-scale degradation in mountains throughout the country. In response to this problem, our study supports recent efforts by the government to designate protection areas across the country. We build on the traditional classification of mountain ridges and apply a terrain-based spatial model to derive mountain ridge area boundaries. Based on the well-known mountain ridge system of the Korean peninsula, established in 1769, our approach was to select mountain ridgelines and boundaries using a terrain-based spatial model. The selected areas are generally located at high elevations with undulating terrain. They include a relatively large portion of ecologically important areas. A large portion of non-nationally owned forest is also found in the selected areas. Ecological importance and property rights would likely cause significant debate and conflicts among different social groups regarding designation of legally binding protection areas. Our model provides an explicit, scientific basis for the rigorous evaluation and area prioritisation as part of the protection area designation process. Application of our model can facilitate conversation on the country’s mountain ridge asset and public participation in the decision-making process. [ABSTRACT FROM PUBLISHER]

Mapping geomorphology in a mountainous terrain is very critical for understanding various land surface processes for their accurate quantification and prediction on different spatial and temporal scales. In the present study, geomorphological mapping was carried out in Ferozpora watershed of Jhelum using remotely sensed data supported by extensive field observations. Three approaches were adopted for mapping geomorphology of Ferozpora watershed. A geomorphological mapping model, Topographic Position Index (TPI), on Screen Image Interpretation (OSII) of satellite data and a hybrid approach utilizing information from TPI and OSII of satellite data were employed. Geomorphology of the area, mapped using the three approaches, was cross checked and verified with the ground data collected by extensively surveying the area and recording the geo-location of the geomorphological features using GPS. Overall, 12 different landforms were mapped which include Alluvial plains, Deeply incised streams, Glacial terrain, Highly dissected hills, Karewa, Fluvial landforms, Moderately dissected hills, Mountain ridges, River channel and U-shaped valleys. The study revealed that Hybrid approach, using inputs from TPI, OSII and field observations, is appropriate in mapping different geomorphological features in this topographically complex terrain with an overall accuracy of 91.53% as compared to TPI (45.56%) and OSII (77.82%) approaches. The study could be extrapolated to other parts of topographically complex Himalayan terrain so as to bring about a very high resolution geomorphological map of Himalayas which could aid policy makers, planners and earth scientists in better modelling the earth surface processes like soil erosion, landslides, hydrology, etc. in the region. [ABSTRACT FROM AUTHOR]

Hydrogeomorphic approaches to wetland classification use landform classes to distinguish wetland functionality at a regional scale. Space-borne radar technology enabled faster regional surveying of surface elevations to digital elevation models, which allowed for automated terrain attribute and landform classification using geographical information systems. Country-wide mapping of landforms remain a challenge though, because of the diversity of landscapes and non-exclusive attributes of each landform class. This article presents the approach, method and steps taken to calculate a country-wide data-set of landforms for wetland-type classification in South Africa, using a freely available Landform Tool. The Landform Tool primarily uses standard deviation from the average elevation, calculated for both small and large neighbourhood distances. The results were compared with 2820 random points, classified manually using Google Earth imagery and topographical maps, and showed a 43% accuracy within 50 m of the manually identified landform class. The Landform Tool tended to overestimate benches and valley floors, and underestimate the extent of the slope class, regardless of changes made in the neighbourhood settings or standard deviation settings. Though the data-set was acceptable as a general reference framework at national scale, improvements will be essential for fine-scale wetland delineation and classification. [ABSTRACT FROM PUBLISHER]

We present topographic slope positions of seismic stations within four independent networks (IGUT, IIEES, GSI, and BHRC) in Iran through integrated use of digital elevation models and GIS. Since topographic amplification factor (TAF) due to ground surface irregularity could be one of the reasons of earthquake wave amplification and unexpected damage of structures located on the top of ridges in many previous studies, the ridge stations in the study area are recognized using topographic position index (TPI) as a spatial-based scale-dependent approach that helps in classification of topographic positions. We also present the correlation between local topographic positions and V along with Voronoi tiles of two networks (IGUT and IIEES). The obtained results can be profitably used in seismology to establish homogeneous subnetworks based on Voronoi tiles with precise feedback and in the formulation of new ground motion prediction equations with respect to topographic position and topographic amplification factor. [ABSTRACT FROM AUTHOR]

Intense physical weathering engenders formation of scree cones at the foot of slopes dissected by couloirs. Combination of several geomorphic processes operating within the slope results in formation of cones of a polygenetic character (talus-alluvial cones, rockfall talus cones, or - in particular cases, talus-alluvial-avalanche cones). This study was aimed at determination of morphometric parameters characteristic for particular morphogenetic types of the cones in the Rybi Potok Valley in the High Tatra Mountains. For the purpose of the research, knowledge about the terrain and available cartographic materials (geological, geomorphological and topographical maps, LiDAR data) were employed. In the studied valley, 24 cones were selected and for each of them, morphogenetic types and morphometric parameters (surface, minimal and maximal height, roughness coefficient, Topographic Position Index) were determined. The correlations between different parameters enabled establishment and determination of the combination of morphometric parameters typical for the particular types of the cones. The impact of snow avalanches on one of the cones (at the mouth of Żleb Żandarmerii) was identified. This cone has morphometric parameters dissimilar to those of the other cones in the studied valley. It is the only cone in the valley which was classified as the avalanche cone. [ABSTRACT FROM AUTHOR]

The increase in geoheritage studies has secured recognition globally regarding the importance of abiotic natural features. Prominent in geoheritage screening practices follows a multicriteria assessment framework; however, the complexity of interest in values often causes decision making to overlook geoeducation, one of the primary facets of geosystem services. Auckland volcanic field in New Zealand stretches through the whole area of metropolitan Auckland, which helps preserve volcanic cones and their cultural heritage around its central business district (CBD). They are important sites for developing tourist activities. Geoeducation is becoming a significant factor for tourists and others visiting geomorphological features, but it cannot be achieved without sound planning. This paper investigates the use of big data (FlickR), Geopreservation Inventory, and Geographic Information System for identifying geoeducation capacity of tourist attractions. Through landform classification using the Topographic Position Index and integrated with geological and the inventory data, the underpromoted important geoeducation sites can be mapped and added to the spatial database Auckland Council uses for urban planning. The use of the Geoeducation Capacity Map can help resolve conflicts between the multiple objectives that a bicultural, metropolitan city council need to tackle in the planning of upgrading open spaces while battling of growing demand for land. [ABSTRACT FROM AUTHOR]

The use of topographic airborne LiDAR data has become an essential part of archaeological prospection, particularly as a tool for detecting archaeological features in the landscape. However, its use for landscape reconstruction and understanding archaeological sites in their environmental context is still underutilised. To this end, we took an innovative approach to using LiDAR data as a means of discovering, documenting, and interpreting agricultural land use systems by looking for significant environmental variation within a microregion. We combined information from LiDAR-derived DEM derivatives with archaeological, geological, and soil data. We introduced two methodological innovations. The first is the modified wetness index, which combines the LiDAR-derived precision with the accuracy of the effective field capacity of the soil to obtain a very realistic predictor of soil quality. The second is the modified landform classification, a combination of topographic position index and visual geomorphological analysis, which amalgamates two of the most important predictive variables for the distribution of plant species. Our approach is demonstrated by a case study focusing on early medieval settlements in the context of agricultural land use in the subalpine microregion of Bled (Slovenia). It revealed that early medieval settlers were drawn to light soils with high water retention capacity. Such soils were particularly suitable for the cultivation of barley, which is known to have been one of the most important staple crops of the period, especially in colder climate such as subalpine. Soils with lower water retention capacity were not colonized until the eleventh century, which may signify the transition at that time to a higher level of agricultural organisation and wheat as a staple cereal food. [ABSTRACT FROM AUTHOR]

In an era of significant growth in the availability of spatial data and continued advances in computing technologies, opportunities for new interpretations and solutions to the landscape research problems posed worldwide are emerging. This paper presents different possibilities of applying digital terrain model (DTM) data in research of various aspects of landscape. For this purpose, two different methods were proposed. The first was to identify a set of components of the Jelenia Góra city landscape character on the basis of the topographic position index and spatial distribution of land cover, while the second was to assess the landscape of Jelenia Góra city in terms of the possibility of adopting new elements, using the author's scenic absorptivity method. The results indicate the structure of the components of the landscape character of Jelenia Góra city together with its spatial distribution, which also allowed for the delineation of landscape units. The scenic absorptivity analysis showed that there are isolated areas within Jelenia Góra city that are capable of accommodating significant size elements that would not adversely affect the city landscape. In conclusion, DTM data are able to significantly improve research methods in landscape studies. [ABSTRACT FROM AUTHOR]

Based on Himawari-8 Sea Surface Temperature (SST) data and the semi-automatic Topographic Position Index (TPI)-based mapping method, this study maps the significant coastal upwelling in the northern South China Sea (NSCS). The results show that the Minnan coastal upwelling mainly occurs within 100 km off the south coast of Fujian; the Yuedong coastal upwelling appears to the east of Pearl River Estuary, limited to the area shallower than 40 m; and the Qiongdong coastal upwelling occurs most frequently in the area shallower than 75 m off the east coast of Hainan Island. Based on the results, this paper quantitatively describes the temporal and spatial variations of upwelling duration, influence area, upwelling SST anomaly, and chlorophyll-a (Chl-a) increase. Different coastal upwelling regions in the NSCS are significantly different in characteristics. The Qiongdong coastal upwelling has the longest duration and occurs most frequently, the Yuedong coastal upwelling has the largest influence area and Chl-a increase, and the Minnan coastal upwelling is quite strong in the NSCS. [ABSTRACT FROM AUTHOR]

Coastal upwelling is important for coastal ecosystems and the blue economy because of its large productivity and large potential for catching fish. However, coastal upwelling along the Taiwan east coast has received little attention from the research community. This study used five-year daily Himawari-8 geostationary satellite sea surface temperature data to map the coastal upwelling east of Taiwan during the summer monsoon season. We applied a semi-automatic image process technique based on the topographic position index for the quantitative upwelling mapping. The results show clear evidence of seasonal coastal upwelling along the entire Taiwan east coast, mainly under the influence of upwelling-favorable southwesterly/southerly winds. There are three broad upwelling centers along the Taiwan east coast: north, central, and south. The upwelling around the northern center has the longest upwelling season, lasting from May to September. The upwelling extents are larger between June and August during the height of the summer monsoon. [ABSTRACT FROM AUTHOR]

Many geoscientific computations are directly influenced by the resolution and accuracy of digital elevation models (DEMs). Therefore, knowledge about the accuracy of DEMs is essential to avoid misleading results. In this study, a comprehensive evaluation of the vertical accuracy of globally available DEMs from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Shuttle Radar Topography Mission (SRTM), Advanced Land Observing Satellite (ALOS) World 3D and TanDEM-X WorldDEM™ was conducted for a large region in Northern Chile. Additionally, several very high-resolution DEM datasets were derived from Satellite Pour l'Observation de la Terre (SPOT) 6/7 and Pléiades stereo satellite imagery for smaller areas. All datasets were evaluated with three reference datasets, namely elevation points from both Ice, Cloud, and land Elevation (ICESat) satellites, as well as very accurate high-resolution elevation data derived by unmanned aerial vehicle (UAV)-based photogrammetry and terrestrial laser scanning (TLS). The accuracy was also evaluated with regard to the existing relief by relating the accuracy results to slope, terrain ruggedness index (TRI) and topographic position index (TPI). For all datasets with global availability, the highest overall accuracies are reached by TanDEM-X WorldDEM™ and the lowest by ASTER Global DEM (GDEM). On the local scale, Pléiades DEMs showed a slightly higher accuracy as SPOT imagery. Generally, accuracy highly depends on topography and the error is rising up to four times for high resolution DEMs and up to eight times for low-resolution DEMs in steeply sloped terrain compared to flat landscapes. [ABSTRACT FROM AUTHOR]