Landscape vulnerability: concept and assessment

2019 ◽  
Author(s):  
Ivan Kesoretskikh ◽  
Sergey Zotov
Keyword(s):  
Vulnerability Assessment ◽  
Anthropogenic Impacts ◽  
Spatial Differentiation ◽  
Nature Management ◽  
Territorial Planning ◽  
Parameters Selection ◽  
Gis Environment ◽  
Kaliningrad Region ◽  
Local Levels ◽  
Selection Of

The monograph presents a methodology for assessing the vulnerability of landscapes to external influences. A comparative analysis of the concepts of "stability", "sensitivity", "vulnerability" in relation to natural complexes. An overview of existing methods for assessing the vulnerability of natural complexes is presented. The author's method of assessing the vulnerability of landscapes to anthropogenic impacts is described. The methodology is based on: selection and justification of criteria for assessing the vulnerability of landscapes; preparation of a parametric matrix and gradation of assessment criteria in accordance with the developed vulnerability classes; calculation of weighting factors of vulnerability assessment parameters; selection of optimal territorial operational unit for landscape vulnerability assessment. The method is implemented in the GIS environment "Assessment of vulnerability of landscapes of the Kaliningrad region to anthropogenic impacts", created by the authors using modern geoinformation products. The specificity of spatial differentiation of different landscapes in terms of vulnerability to anthropogenic impacts at the regional and local levels is revealed. It is stated that the use of the methodology for assessing the vulnerability of landscapes to anthropogenic impacts and its integration into the system of nature management will ensure a balanced account of geoecological features and environmental priorities in territorial planning. It is of interest to specialists in the field of rational nature management, environmental protection, spatial planning.

Application of geoinformation technologies for arranging a satellite monitoring system

2019 ◽  
Vol 943 (1) ◽  
pp. 110-118
Author(s):  
A.A. Kadochnikov
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Web Gis ◽  
Nature Management ◽  
Satellite Monitoring ◽  
Technological Support ◽  
Sensing Data ◽  
Territorial Planning ◽  
Operational Information

Today, remote sensing data are an important source of operational information about the environment for thematic GIS, this data can be used for the development of water, forestry and agriculture management, in the ecology and nature management, with territorial planning, etc. To solve the problem of ensuring the effective use of the space activities’results in the Krasnoyarsk Territory a United Regional Remote Sensing Center was created. On the basis of the Center, a new satellite receiving complex of FRC KSC SB RAS was put into operation. It is currently receiving satellite data from TERRA, AQUA, Suomi NPP and FENG-YUN satellites. Within the framework in cooperation with the Siberian Regional Center for Remote Sensing the Earth, an archive of satellite data from domestic Resource-P and Meteor-M2 satellites was created. The work considers some features of softwaredevelopment and technological support tools for loading, processing and publishing remote sensing data. The product is created in the service-oriented paradigm based on geoportal technologies and interactive web-cartography. The focus in this article is paid to the peculiarities of implementing the software components of the web GIS, the efficient processing and presentation of geospatial data.

scholarly journals Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1288
Author(s):  
Husam Musa Baalousha ◽  
Bassam Tawabini ◽  
Thomas D. Seers
Keyword(s):  
Fuzzy Logic ◽  
Numerical Model ◽  
Vulnerability Assessment ◽  
Anthropogenic Impacts ◽  
Groundwater Vulnerability ◽  
Vulnerability Mapping ◽  
Anthropogenic Contamination ◽  
Weighted Overlay ◽  
Vulnerability Maps

Vulnerability maps are useful for groundwater protection, water resources development, and land use management. The literature contains various approaches for intrinsic vulnerability assessment, and they mainly depend on hydrogeological settings and anthropogenic impacts. Most methods assign certain ratings and weights to each contributing factor to groundwater vulnerability. Fuzzy logic (FL) is an alternative artificial intelligence tool for overlay analysis, where spatial properties are fuzzified. Unlike the specific rating used in the weighted overlay-based vulnerability mapping methods, FL allows more flexibility through assigning a degree of contribution without specific boundaries for various classes. This study compares the results of DRASTIC vulnerability approach with the FL approach, applying both on Qatar aquifers. The comparison was checked and validated against a numerical model developed for the same study area, and the actual anthropogenic contamination load. Results show some similarities and differences between both approaches. While the coastal areas fall in the same category of high vulnerability in both cases, the FL approach shows greater variability than the DRASTIC approach and better matches with model results and contamination load. FL is probably better suited for vulnerability assessment than the weighted overlay methods.

scholarly journals Best Selection of Generative Adversarial Networks Hyper-Parameters using Genetic Algorithm

2020 ◽  
Author(s):  
Fajr Alarsan ◽  
Mamoon Younes
Keyword(s):  
Genetic Algorithm ◽  
Programming Language ◽  
Loss Function ◽  
Generative Adversarial Networks ◽  
Accuracy Function ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Adversarial Networks ◽  
Parameters Selection ◽  
Selection Of

Abstract Generative Adversarial Networks (GANs) are most popular generative frameworks that have achieved compelling performance. They follow an adversarial approach where two deep models generator and discriminator compete with each other In this paper, we propose a Generative Adversarial Network with best hyper-parameters selection to generate fake images for digits number 1 to 9 with generator and train discriminator to decide whereas the generated images are fake or true. Using Genetic Algorithm technique to adapt GAN hyper-parameters, the final method is named GANGA:Generative Adversarial Network with Genetic Algorithm. Anaconda environment with tensorflow library facilitates was used, python as programming language also used with needed libraries. The implementation was done using MNIST dataset to validate our work. The proposed method is to let Genetic algorithm to choose best values of hyper-parameters depending on minimizing a cost function such as a loss function or maximizing accuracy function. GA was used to select values of Learning rate, Batch normalization, Number of neurons and a parameter of Dropout layer.

scholarly journals DIFFERENCES IN ENVIRONMENTAL GOVERNANCE LEVELS IN THE SUSTAINABLE DEVELOPMENT OF RURAL AREAS OF THE WIELKOPOLSKIE VOIVODESHIP

2018 ◽  
Vol 47 (1) ◽  
pp. 21-28
Author(s):  
Małgorzata Dolata ◽  
Magdalena Jaworska ◽  
Magdalena Jaworska
Keyword(s):  
Rural Areas ◽  
Environmental Governance ◽  
Spatial Differentiation ◽  
Data Bank ◽  
Online Database ◽  
Local Data ◽  
The Sustainable Development ◽  
Central Statistical ◽  
Basic Source ◽  
Selection Of

The purpose of this paper is to assess the leveland spatial differentiation of selected environmental governanceparameters in the context of implementing the sustainabledevelopment concept in rural areas of the Wielkopolskievoivodeship districts in 2005 and 2015. The research procedurewas made up of three steps: review of the relevant literatureand selection of indicators to describe the environmentalgovernance topics; analyzing the changes in, and spatial differentiationof, specific environmental governance components;and ranking the districts. The basic source of data wasthe online database delivered by the Central Statistical Officein Warsaw, the Local Data Bank. As shown by the results,there is considerable spatial differentiation of specific environmentalgovernance components; however, when analyzedglobally, environmental governance proves to be a relativelynon-diversified process. In 2015, the highest sustainabilitylevels were recorded in rural areas of the following districts:Złotów, Kępno and Jarocin. In turn, the lowest levels werefound in Września, Wągrowiec and Śrem districts.

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