scholarly journals Landscape Sustainability Evaluation of Ecologically Fragile Areas Based on Boltzmann Entropy

2020 ◽  
Vol 9 (2) ◽  
pp. 77 ◽  
Author(s):  
Jingyi Xu ◽  
Xiaoying Liang ◽  
Hai Chen
Keyword(s):  
Configurational Entropy ◽  
Remote Sensing Data ◽  
Quantitative Relationship ◽  
Field Investigation ◽  
Shaanxi Province ◽  
Landscape Sustainability ◽  
Boltzmann Entropy ◽  
Digital Elevation ◽  
Elevation Model ◽  
Evaluation Matrix

From the perspective of landscape, it is important to evaluate the landscape sustainability of ecologically fragile areas and explore temporal and spatial evolution laws to promote their sustainable development. Presently, most studies on the analysis of landscape Boltzmann entropy (also called configurational entropy) are based on a single landscape, and most of these studies are theoretical discussions. However, there are few case studies on landscape ecology. The main objectives of this paper are to explore a quantitative relationship between Boltzmann entropy and landscape sustainability, to propose a method for evaluating landscape sustainability based on Boltzmann entropy, and to evaluate the sustainability of diverse landscapes in Mizhi County, Shaanxi Province, China. This article uses digital elevation model (DEM) data with a spatial resolution of 30 m in Mizhi County. The remote sensing data on Mizhi County from 2000 were obtained by the Landsat Enhanced Thematic Mapper (ETM) + sensor, and the high-resolution image of Mizhi County from 2015 was obtained by the Gaofen-1 satellite. In this article, the subbasins are taken as the evaluation unit, and the Boltzmann entropy of Mizhi County is calculated based on the experts’ scoring of landscape sustainability in the study area. Through the analysis of landscape sustainability results from 216 subbasins in Mizhi County in 2000 and 2015, the following conclusions are drawn: (1) the evaluation matrix proposed in this paper is effective, and the Boltzmann entropy obtained by this method can directly reflect the level of landscape sustainability; (2) during the research period, the landscape sustainability of Mizhi County showed a good trend overall, especially the three townships of Taozhen, Shadian, and Shigou, which were significantly improved, and these findings were consistent with the field investigation; (3) on the spatial level, the landscape sustainability of mid-eastern Mizhi County is relatively poor compared to that in other regions, but the sustainability is also slowly increasing.

scholarly journals Multi-Aspect Analysis of Object-Oriented Landslide Detection Based on an Extended Set of LiDAR-Derived Terrain Features

2019 ◽  
Vol 8 (8) ◽  
pp. 321 ◽  
Author(s):  
Kamila Pawłuszek ◽  
Sylwia Marczak ◽  
Andrzej Borkowski ◽  
Paolo Tarolli
Keyword(s):  
Laser Scanning ◽  
Remote Sensing Data ◽  
Field Investigation ◽  
Kappa Index ◽  
Object Based ◽  
Digital Elevation ◽  
Forested Areas ◽  
Scanning Lidar ◽  
Elevation Model ◽  
Agricultural Areas

Landslide identification is a fundamental step enabling the assessment of landslide susceptibility and determining the associated risks. Landslide identification by conventional methods is often time-consuming, therefore alternative techniques, including automatic approaches based on remote sensing data, have captured the interest among researchers in recent decades. By providing a highly detailed digital elevation model (DEM), airborne laser scanning (LiDAR) allows effective landslide identification, especially in forested areas. In the present study, object-based image analysis (OBIA) was applied to landslide detection by utilizing LiDAR-derived data. In contrast to previous investigations, our analysis was performed on forested and agricultural areas, where cultivation pressure has degraded specific landslide geomorphology. A diverse variety of aspects that influence OBIA accuracy in landslide detection have been considered: DEM resolution, segmentation scale, and feature selection. Finally, using DEM delivered layers and OBIA, landslide was identified with an overall accuracy (OA) of 85% and a kappa index (KIA) equal to 0.60, which illustrates the effectiveness of the proposed approach. In the end, a field investigation was performed in order to evaluate the results achieved by applying an automatic OBIA approach. The advantages and challenges of automatic approaches for landslide identification for various land use were also discussed. Final remarks underline that effective landslide detection in forested areas could be achieved while this is still challenging in agricultural areas.

New methodical approaches to mapping of geosystems (by the example of Baikalian Siberia’s geosystems)

2018 ◽  
Vol 937 (7) ◽  
pp. 23-34 ◽  
Author(s):  
I.N. Vladimirov
Keyword(s):  
Global Climate ◽  
Remote Sensing Data ◽  
Field Research ◽  
Scientific Basis ◽  
Nature Management ◽  
Climate Data ◽  
Structural Dynamic ◽  
Digital Elevation ◽  
North Asia ◽  
Elevation Model

The article considers a new approach to landscape mapping based on the synthesis of remote sensing data of high and medium spatial resolution, a digital elevation model, maps of various thematic contents, a set of global climate data, and materials of field research. The map of the Baikalian’s Siberia geosystems is based on the principles of the multistage regional-typological and structural-dynamic classification of geosystems proposed by Academician V.B. Sochava. The structure of the geosystems of the Baikalian Siberia is characterized by great complexity, both in the set of natural complexes and in the degree of their contrast. The regional classification range covers the geosystems inherent in different subcontinents of Asia and reflects their interpenetration, being a unique landscape-situational example of Siberian nature within North Asia. The map of the geosystems of the Baikalian Siberia reflects the main structural and dynamic diversity of geosystems in the region in the systems of their geographic and genetic spatial structures. These landscape cartographic studies fit into a single system of geographic forecasting and create a new fundamental scientific basis for developing recommendations for optimizing nature management in the Baikal region within the framework of implementing state environmental policy.

Estimating the ice thickness of the Müller Ice Cap using an inversion of the shallow ice approximation

2021 ◽  
Author(s):  
Ann-Sofie Priergaard Zinck ◽  
Aslak Grinsted
Keyword(s):  
Remote Sensing Data ◽  
The Arctic ◽  
Ice Thickness ◽  
Potential Contribution ◽  
Mean Squared Errors ◽  
Ice Caps ◽  
Ice Cap ◽  
Regression Parameters ◽  
Digital Elevation ◽  
Elevation Model

<p><span>The ice thickness of the Müller Ice Cap, Arctic Canada, is estimated using regression parameters obtained from an inversion of the shallow ice approximation by the use of a single Operation IceBridge flight line in combination with the glacier outline, surface slope, and elevation. The model is compared with an iterative inverse method of estimating the bedrock topography using PISM as a forward model. In both models the surface elevation is given by the Arctic Digital Elevation Model. The root mean squared errors of the ice thickness on the ice cap is 131 m and 139 m for the shallow ice inversion and the PISM model, respectively. Including the outlet glaciers increases the root mean squared errors to 136 m and 396 m, respectively. </span></p><p><span>The simplicity of the shallow ice inversion model, combined with the good results and the fact that only remote sensing data is needed, means that there is a possibility of applying this model in a global glacier thickness estimate by using the Randolph Glacier Inventory. Most global glacier estimates only provide the volume and not the ice thickness of the glaciers. Hence, global ice thickness models is of great importance in quantifying the potential contribution of sea level rise from the glaciers and ice caps around the globe. </span></p>

scholarly journals A Probabilistic Assessment of Soil Erosion Susceptibility in a Head Catchment of the Jemma Basin, Ethiopian Highlands

Geosciences ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 248 ◽  
Author(s):  
Mariaelena Cama ◽  
Calogero Schillaci ◽  
Jan Kropáček ◽  
Volker Hochschild ◽  
Alberto Bosino ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Remote Sensing Data ◽  
Gully Erosion ◽  
Entropy Model ◽  
Global Issues ◽  
Susceptibility Maps ◽  
Digital Elevation ◽  
Elevation Model ◽  
Color Composite

Soil erosion represents one of the most important global issues with serious effects on agriculture and water quality, especially in developing countries, such as Ethiopia, where rapid population growth and climatic changes affect widely mountainous areas. The Meskay catchment is a head catchment of the Jemma Basin draining into the Blue Nile (Central Ethiopia) and is characterized by high relief energy. Thus, it is exposed to high degradation dynamics, especially in the lower parts of the catchment. In this study, we aim at the geomorphological assessment of soil erosion susceptibilities. First, a geomorphological map was generated based on remote sensing observations. In particular, we mapped three categories of landforms related to (i) sheet erosion, (ii) gully erosion, and (iii) badlands using a high-resolution digital elevation model (DEM). The map was validated by a detailed field survey. Subsequently, we used the three categories as dependent variables in a probabilistic modelling approach to derive the spatial distribution of the specific process susceptibilities. In this study we applied the maximum entropy model (MaxEnt). The independent variables were derived from a set of spatial attributes describing the lithology, terrain, and land cover based on remote sensing data and DEMs. As a result, we produced three separate susceptibility maps for sheet and gully erosion as well as badlands. The resulting susceptibility maps showed good to excellent prediction performance. Moreover, to explore the mutual overlap of the three susceptibility maps, we generated a combined map as a color composite where each color represents one component of water erosion. The latter map yields useful information for land-use managers and planning purposes.

scholarly journals CREATION OF GIS-RESOURCES FOR PHYSIOGRAPHIC ZONING OF THE TRANSBOUNDARY RUSSIAN-MONGOLIAN TERRITORY

2021 ◽  
Vol 26 (2) ◽  
pp. 91-102
Author(s):  
Andrew N. Beshentsev ◽  
◽  
Alexander A. Ayurzhanaev ◽  
Bator V. Sodnomov ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Statistical Research ◽  
Active Biomass ◽  
Sensing Data ◽  
Digital Elevation ◽  
Geographical Regions ◽  
Elevation Model ◽  
Geographical Characteristics

The article is aimed at the development of methodological foundations for the creation of geoin-formation resources of transboundary territories based on cartographic materials and remote sensing data, as well as physical and geographical zoning of the transboundary Russian-Mongolian territory. The methodological basis of the study is cartographic and statistical research methods, geoinformation technology, as well as processing and analysis of remote sensing data. As a result, the study deter-mines the features of geoinformation resources, presents their characteristics, develops a classification and substantiates their integrating value in making interstate territorial decisions. The article gives the physical and geographical characteristics of the territory, determines the scale of mapping, establishes the basic units of geoinformation mapping and modeling, creates the coverage of the basin division, and proposes a scheme for creating basic geoinformation resources for the physical and geographical zoning of the territory. Based on the analysis of the digital elevation model, the territory was zoned according to the morphometric parameters of the relief. As a result of processing and analysis of Landsat images at different times, the territory was zoned in terms of the amount of photosynthetically active biomass (NDVI). As a result of zoning, 6 physical-geographical regions and 33 physical-geographical areas were identified.

scholarly journals Impact of sea level rise and shoreline changes in the tropical island ecosystem of Andaman and Nicobar region, India

2021 ◽  
Author(s):  
mageswaran thangaraj ◽  
Sachithanandam V ◽  
Sridhar R ◽  
Manik Mahapatra ◽  
R Purvaja ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sea Level Rise ◽  
Sea Level ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Andaman Island ◽  
Shoreline Changes ◽  
Digital Elevation ◽  
Analysis System ◽  
Elevation Model

Abstract We report here a four decades of shoreline changes and possible sea level rise (SLR) impact on landuse/landcover (LULC) in Little Andaman Island by using remote sensing (RS) and GIS techniques. A total of six remote sensing data sets covering years between 1976 and 2018 were used to understand the shoreline changes. Moreover, a Digital Shoreline Analysis System (DSAS) was used to estimate short- and long- term shoreline changes from ArcGIS environment. Besides, the Island vulnerability due to SLR was studied through using digital elevation model (DEM). As a result of Sumatra earthquake (2004), the results were showed a significant variation in shorline upliftment and subsidence. The land subsidence was noticed in the range of 1042-3077 ha with sea level rise between 1 and 5 m. Hence, we conclude that Little Andaman Island is vulnerable to SLR and overwhelm low elvation coastal zone.

scholarly journals Quantitative Analysis of Different Environmental Factor Impacts on Land Cover in Nisos Elafonisos, Crete, Greece

2020 ◽  
Vol 17 (18) ◽  
pp. 6437
Author(s):  
Mohamed Elhag ◽  
Silvena Boteva
Keyword(s):  
Land Use ◽  
Environmental Factors ◽  
Land Cover ◽  
Remote Sensing Data ◽  
Mediterranean Ecosystems ◽  
Land Use Land Cover ◽  
Routine Work ◽  
Digital Elevation ◽  
Elevation Model ◽  
Sentinel 2

Land Cover monitoring is an essential task for a better understanding of the ecosystem’s dynamicity and complexity. The availability of Remote Sensing data improved the Land Use Land Cover mapping as it is routine work in ecosystem management. The complexity of the Mediterranean ecosystems involves a complexity of the surrounding environmental factors. An attempt to quantitatively investigate the interdependencies between land covers and affected environmental factors was conducted in Nisos Elafonisos to represent diverse and fragile coastal Mediterranean ecosystems. Sentinel-2 (MSI) sensor and ASTER Digital Elevation Model (DEM) data were used to classify the LULC as well as to draw different vegetation conditions over the designated study area. DEM derivatives were conducted and incorporated. The developed methodology is intended to assess the land use land cover for different practices under the present environmental condition of Nisos Elafonisos. Supervised classification resulted in six different land cover clusters and was tested against three different environmental clusters. The findings of the current research pointed out that the environmental variables are independent and there is a vertical distribution of the vegetation according to altitude.

Geoinformation mapping of landscapes on the example of the Primorskiy Ridge (Baikal region)

2020 ◽  
Vol 954 (12) ◽  
pp. 20-30
Author(s):  
Yu.V. Vanteeva ◽  
Е.А. Rasputina ◽  
S.V. Solodyankina
Keyword(s):  
Digital Elevation Model ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Topographic Wetness Index ◽  
Space Images ◽  
Topographic Position Index ◽  
Digital Elevation ◽  
Different Seasons ◽  
Position Index ◽  
Elevation Model

The authors present the results of geoinformation mapping the Primorskiy Ridge landscapes using Landsat 8 satellite images, the digital elevation model SRTM and the factor-dynamic classification of geosystems. At the first stage, the remote sensing data for different seasons were classified using the ISODATA method. Then, using the digital elevation model, the landforms were classified basing upon the topographic position index. According to combining the classification parameters of one of the space images and digital elevation model, each polygon is automatically assigned to a certain preliminary type of landscapes using boolean expressions. Legend adjustments were made basing upon the fieldwork materials. As a result, a digital landscape map of the southern part of the Primorsky Ridge was created; it reflects the landscape structure at the level of facies groups and contains attributive information about the landform, altitude, slope and aspect, topographic wetness index. The analysis of the landscape pattern showed a high fragmentation of landscape polygons, formed due to overlay operations, which indicates the need for generalization of landscape contours.

scholarly journals Glacier mass balance over the central Nyainqentanglha Range during recent decades derived from remote-sensing data

2019 ◽  
Vol 65 (251) ◽  
pp. 422-439 ◽  
Author(s):  
KUNPENG WU ◽  
SHIYIN LIU ◽  
ZONGLI JIANG ◽  
JUNLI XU ◽  
JUNFENG WEI
Keyword(s):  
Mass Balance ◽  
Remote Sensing Data ◽  
Shuttle Radar Topography Mission ◽  
Topographic Maps ◽  
Glacier Mass Balance ◽  
Glacier Area ◽  
Ice Surface ◽  
Digital Elevation ◽  
Elevation Changes ◽  
Elevation Model

ABSTRACTTo obtain information on changes in glacier mass balance in the central Nyainqentanglha Range, a comprehensive study was carried out based on digital-elevation models derived from the 1968 topographic maps, the Shuttle Radar Topography Mission DEM (2000) and TerraSAR-X/TanDEM-X (2013). Glacier area changes between 1968 and 2016 were derived from topographic maps and Landsat OLI images. This showed the area contained 715 glaciers, with an area of 1713.42 ± 51.82 km2, in 2016. Ice cover has been shrinking by 0.68 ± 0.05% a−1 since 1968. The glacier area covered by debris accounted for 11.9% of the total and decreased in the SE–NW directions. Using digital elevation model differencing and differential synthetic aperture radar interferometry, a significant mass loss of 0.46 ± 0.10 m w.e. a−1 has been recorded since 1968; mass losses accelerated from 0.42 ± 0.20 m w.e. a−1 to 0.60 ± 0.20 m w.e. a−1 between 1968–2000 and 2000–2013, with thinning noticeably greater on the debris-covered ice than the clean ice. Surface-elevation changes can be influenced by ice cliffs, as well as debris cover and land- or lake-terminating glaciers. Changes showed spatial and temporal heterogeneity and a substantial correlation with climate warming and decreased precipitation.

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