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ISSN: 2157-7617
Journal of Earth Science & Climatic Change
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Land Use/Cover and Vulnerability Mapping Through Remote Sensing and GIS In Astrakhan, Russia

Mukesh SB1,2,3*, Komal C2 and Alexander K2

11American Sentinel University, Colorado, USA

22Samara National Research University, Samara, Russia

33Bonn University, Bonn, Germany

*Corresponding Author:
Mukesh SB
American Sentinel University, Colorado, USA
Tel: 0123456789
E-mail: [email protected], [email protected]

Received date: July 22, 2016; Accepted date: January 11, 2017; Published date: January 18, 2017

Citation: Mukesh SB, Komal C, Alexander K (2017) Land Use/Cover and Vulnerability Mapping Through Remote Sensing and GIS In Astrakhan, Russia. J Earth Sci Clim Change 8:380. doi: 10.4172/2157-7617.1000380

Copyright: © 2017 Mukesh SB, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

The main aim of this research work is to identify natural and environmental vulnerability distribution in Astrakhan, Russia. This paper identifies, assess, and classify natural and environmental vulnerability using landscape pattern from multidisciplinary approach, based on remote sensing and Geographical Information System (GIS) techniques. A model was developed by following thematic layers: land use/cover, vegetation, geology, geomorphology, and soil in ArcGIS 10.3 software. According to numerical results vulnerability classified into five levels: low, reasonable, moderate, high and extreme vulnerability by mean of cluster principal. Results are shows that in natural vulnerability maximum area covered by moderate (54.62%) and environmental vulnerability concentrated by moderate (54.00%) vulnerability. So, study area has at medial level vulnerability. In the study area encroachment, population growth, industrialization and governmental polices for environmental protection are main cause for vulnerability. This study is helpful for decision making for eco-environmental recovering and rebuilding as well as predicting the future development.

Keywords

Geology; Natural and environmental vulnerability; Remote sensing; GIS; Vulnerability

Introduction

Astrakhan is a city in Russia, the capital of the Astrakhan region, located about 1,411 km southeast of Moscow. The city is an important railway hub, sea, and river port. The population of Astrakhan is about 532,000 in 2015, the area - 208 sq-km. Astrakhan fertile area (the Volga River delta) was the region of the Golden Horde and Khazaria states capitals. First written mentioning of Astrakhan settlement was made by travelers in the beginning of the 13th century. Mongol leader Tamerlane destroyed the town in 1395. In 1459-1556, it was the capital of Astrakhan Khanate. Archaeologists found the remains of it about 12 km from present Astrakhan. Tsar Ivan the Terrible Conquered Astrakhan Khanate and its capital in 1556. The town became the main Russian gate to Orient in the 17th century. It was the place where merchants from Armenia, Persia, India and other counties of the East met. The city stands on 11 islands of the Caspian depression, on the banks of the Volga River close to the area where it flows into the Caspian Sea. Astrakhan is the oldest economic and cultural center of the Lower Volga and the Caspian region. Often called the southern outpost of Russia and the Caspian capital, it is included in the list of historical Russian cities. Astrakhan has long been considered a multicultural city. Today, more than 100 nationalities of 14 confessions live here. The climate is semi-arid, dry, warm. In winter, rare precipitation falls as rain or snow, which usually melts quickly [1]. Summer is usually hot; the hottest month is July (average temperature: +25.6°C). Winters are mild, the coldest month - February (average temperature: -3.7°C). Astrakhan Airport offers regular flights to Moscow, Saint Petersburg, Sochi, and international flights to Aktau (Kazakhstan), Istanbul (Turkey).

Natural resources of the region include natural gas, oil, salt, gypsum. The industrial complex of Astrakhan, the economic center of the region, includes shipbuilding, pulp and paper industry, fish processing industry. The leading industries are fuel industry, mechanical engineering, power engineering, food industry. Astrakhan gas condensate field, the largest in the European part of Russia, is in the area. Astrakhan Gas Processing Plant produces gas for cars, diesel, and boiler fuel, Agric. Weight table to each unite in a thematic layer cultural lands make up more than 3.4 million hectares - the cultivation of tomatoes, peppers, aborigines, courgettis, cucumbers, carrots, beets, onions, cabbage and watermelons. Rice is traditionally grown along the Volga. The leading branch of livestock is sheep breeding. The region stretches for over 400 km in the form of a narrow stripe on both sides of the Volga-Aktyubinsk flood-lands. Flooded for a long time, the territory of the delta serves as spawning-ground for such fish as sturgeon, stellate sturgeon, white sturgeon, and others (Tables 1 and 2) [2].

Unit Pedogenesis/morphogenesis Relation Value
Stable Prevails pathogenesis 1
Intermediate Balance between pedogenesis and morphogenesis 2
Unstable Prevails morphogenesis 3

Table 1: Stability values of landscape units [13].

Thematic maps/classes Vulnerability grade levels
Land use/cover
Forest 1.8
Agriculture 1.5
Bare land 1
Mangroves 2
Settlements 3
Waterbody 0.5
Vegetation
Mangrove 2
River 0.5
Agriculture 1.5
Bare soil 1
Dunes 1.7
Forest 1.8
Urban area 3
Water 0.5
Ocean 0.5
Soil
Alluvial soil 3
Chestnut+Solonetz soil 1.9
Chestnut soil 1.6
Podzol 2
Sands 2.7
Ocean 0.5
Geomorphology
Costal trays 2
Dunes 1.7
River plains 2.5
River 0.5
Ocean 0.5
Urban area 3
Geology
Alluvial 2.5
Eluvium and deluvium of massive rocks 2
Eluvium of massive-crystal rocks and sandstones 1
Marine saline 2.6
Ocean 0.5
Lithspecs 3

Table 2: Weight table to each unite in a thematic layer.

Moreover, its landscape, climatic conditions, infrastructure, industrial situation, increasing population, less connectivity, forest and agriculture productions and so on are the main cause to identify natural and environmental vulnerability to make the balance in between physical factors (a diversity of natural processes), human activities (exploitation and development of the region) and economic processes [3]. So overall very high explorations of natural resources are the main cause of natural and environmental vulnerability study in the Astrakhan region, Russia [4].

Presently remote sensing and GIS techniques are the powerful tool to investigate, predict and forecast environmental change senior in a reliable, repetitive, non-invasive, rapid and cost effective way with considerable decision making strategies [5]. This research work use a new approach by integrating the above mention potential impacts for vulnerability assessment. Analysis can help to solve the multidisciplinary problems such as most or least vulnerable regions, their comparing in un-assessable and harsh climatic conditions [6]. In this research work we use geology, geomorphology, soil, bare land, vegetation, and land use scenarios for vulnerability assessment [7]. In this context, the main aim of this study is: (1) build a model of spatial distribution of natural and environmental vulnerability through remote sensing and GIS; (2) knowing the parameters used to obtain clarity of vulnerability; (3) knowing the level of vulnerability in different parts of the study area.

Presently remote sensing and GIS techniques are the powerful tool to investigate, predict and forecast environmental change senior in a reliable, repetitive, non-invasive, rapid and cost effective way with considerable decision making strategies [8]. This research work uses a new approach by integrating the above mention potential impacts for vulnerability assessment. Analysis can help to solve the multidisciplinary problems such as most or least vulnerable regions, their comparing, in un-assessable and harsh climatic conditions. In this research work we use geology, geomorphology, soil, vegetation and land use scenarios for vulnerability assessment [9]. In this context, the main aim of this study is: (1) build a model of spatial distribution of natural and environmental vulnerability through remote sensing and GIS; (2) knowing the parameters used to obtain clarity of vulnerability; (3) knowing the level of vulnerability in different parts of the study area [10].

Study Area

The study area is in the Astrakhan region, South-west part of Russia. Astrakhan is on the delta of Volga River, which is rich in sturgeon and exotic plants. The city lies on two banks of the Volga River, close to where it discharges into the Caspian Sea. The city coordinates are 46°21′N to 48°03′E (Figure 1).

earth-science-climatic-change-study-area-Astrakhan

Figure 1: Location map of the study area in Astrakhan, Russia.

Data and Methodology

Data

In this research work we used primary (satellite data) and secondary data such as ground truth for land use/cover classes and topographic sheets. The ground truth data were collected using Global Positioning System (GPS) for the year of 2007 and 2015 in the month of June to August for image analysis and classification accuracy. A selection of multi-sensor, multi-resolution and multi-temporal images was used in this study. The specific satellite images used were Landsat ETM+ (Enhanced Thematic Mapper plus) for 2000 and 2007, Landsat OLI (Operational Land Imager) for 2015, an image captured by a different type of sensors to know the changes in different dates [11].

Vulnerability concept

Vulnerability is a function of exposure, sensitivity and adaptive capacity. Where potential impacts are a function of exposure and sensitivity Therefore, vulnerability is a function of potential impacts and adaptive capacity. Where exposure components characterize the stressors and the entities under stress; Sensitivity components characterize the first order effects of the stresses, and adaptive capacity components characterize responses to the effects of the stresses. These measures can be quantitative (e.g., precipitation variability, distance to market) or qualitative (e.g., political party affiliation, environmental preservation ethic). Another slightly different view favored by the hazards and disasters research community is that adaptive capacity consists of two subcomponents: coping capacity and resilience. Coping capacity is the ability of people and places to endure the harm and resilience is the ability to bounce back after exposure to the harmful event, even if the people and places suffer considerable harm. In both cases, individuals and communities can take measures to increase their abilities to cope and bounce back; again depending on the physical, social, economic, spiritual and other resources they have or have access to [12].

Another basic issue for the evaluation a model is to assign weights to each factor according to its relative effects of factors considered on the vulnerability in a thematic layer. The analytic hierarchy process, a theory dealing with complex technological, economical and sociopolitical problems [13], is an appropriate method for deriving the weight assigned to each factor. The degree of membership within different levels of different indices was integrated using weight and the total degree of membership for different thematic layers was used to calculate the whole study area natural and environmental vulnerability. The application of subjective weightings on the one hand gives us some indication of how the relative importance of different factors might vary with context and can also tell us how sensitive vulnerability ratings are to perceptions of vulnerability in the expert community [14].

Data analysis

In this research work, we used multi-spectral and temporal data; both data were georeferenced based on topographical sheets with the help of ArcGIS 10.2 software. To improve the quality of research analysis we used different band ration, image enhancement techniques, principal component analysis and supervised classification.

Thematic maps (Figure 2) of geology, geomorphology, soil, wetland, vegetation, and land use/cover were prepared from Landsat ETM+ and OLI imageries. The weight of all landscape units based on [6,14] stability concept, where stability was classified per Table 1. The weights of a landscape unit indicate the importance of any factor in relation to others [10]. In natural vulnerability, all thematic layers give same weight but in environmental vulnerability all thematic layer was given different weight based on their sensitivity or effectiveness in the study area (Table 2) [15].

earth-science-climatic-change-Vegetation-soil-geomorphology

Figure 2: Vegetation, soil, geomorphology, geology and land use/cover map.

The degree of vulnerability for all units was range from 0 to 3. The vulnerability ranked as extreme, high, moderate, reasonable, and low vulnerability [15]. The weights of compensation indicate the importance of any factor in relation to others, as seen in the formula below for Natural Vulnerability map:

[(Theme 1) + (Theme 2) + (Theme 3) + (Theme 4) + (Theme 5)]/5

For Environmental Vulnerability, we use following formula:

1.1 X [Theme 1] + 0.1 X [Theme 2] + 0.1 X [Theme 3] + 0.1 X [Theme 4] + 0.1 X [Theme 5]

Where:

Theme 1: Geomorphology map.

Theme 2: Geology map.

Theme 3: Soil map.

Theme 4: Vegetation map.

Theme 5: Land use/cover map.

The results were distributed in following five vulnerability classes:

1. Low vulnerability: Less than 1.00

2. Reasonable vulnerability: 1.1 to 1.50

3. Moderate vulnerability: 1.51 to 2.00

4. High vulnerability: 2.1 to 2.50

5. Extreme vulnerability: Greater than to 2.51

Results

After assiging the risk value based on each specific data variable to each section of the land use/cover. The vulnerability ranges from 0.0 to 3. The vulnerability score were diveded into low, reasonable, moderate, high and extreme vulnerability (Figure 3).

earth-science-climatic-change-Natural-environmental-vulnerability-map

Figure 3: Natural and environmental vulnerability map.

Natural vulnerability

The map shows that maximum area is in safe zone as 54.62% area is in moderate vulnerability type and 33.56% area in reasonable vulnerability zone, which shows that around 85% area of the total study area is safe. 6.05% area goes in high vulnerability, Low vulnerability is 5.62% and extreme vulnerability is 0.15%. Low vulnerability is present in sea, river and water body areas and high vulnerability area is close to costal line and near to river basin. Vegetation area and close to river basin area are under the moderate vulnerability zone. Low vulnerability and sensible Vulnerability area are the most safe area in the study region,which is under the vegetation, bearland and wetland classes (Figure 3).

Environmental vulnerability

Around 54% area under the moderate vulnerability zone but high and extreme vulnerability is higher than natural vulnerability. Here 6.11% area is under high vulnerability and 0.15% under extreme vulnerability. Reasonable vulnerability is 7.03% and low vulnerability is 32.71%. Sensible vulnerability shows in bearland and some parts of vegetation and low vulnerability is present in sea, river and water bodies. Moderate vulnerability area covered a big part of the study area, which present in vegetation and costal line. High vulnerability is presenting in the river water area and extreme vulnerability is present in coastal line and close to river (Figure 3).

Discussion

Vulnerability maps demonstrate the great fragility of natural area, supported by the intense action of coastal processes and economic activities in the region. The activities of mining in the region create instability of natural resources [9]. In addition, with the excessive consumption of natural resources and the gradual increase in population, some prominent environmental problems need to be solved urgently. Among them, deforestation and forest degradation are the major environmental and ecological issues in the study area.

A substantial amount of forest has been lost due to the conversion of forest to farmlands, high grading, industrializations, and other logging practices due to market demand. Despite the high levels of current effort in forest conservation, degradation of forests caused by unsound exploitation is still a serious threat [12].

In addition, soil erosion has also seriously affected the sustainable development of the environment in the study area. Currently, this area is increasing at a rate of 100 km²/year. Deforestation is the chief cause of soil erosion and the adverse geology and climatic conditions intensify the erosion.

Moreover, the Astrakhan is one of the main unmanaged regions of Russia with economic decline and poor environmental awareness. Over the years, with population increase, demand for food, fuel and timber has exceeded local production levels, leading to an imbalance between humans and their environment. Inappropriate land use has generated a huge area of sloped farmland, vegetation destruction and soil loss, leading to gross deterioration of the environment.

An important goal of environmental assessment is to provide assistance to policy makers and practitioners in environmental protection. To protect and maintain the ecological environment in those areas, a population control policy might be needed and some regulations such as “convert slope farmland into forest or pasture” and laws (e.g. ‘Environmental Protection Act’, ‘Land Act’, ‘Forestry Act’, ‘Grassland Act’, etc.) could be established and implemented. Areas of higher ecological vulnerability should be protected over all others, for moderately vulnerable areas, integrated small watershed management should purposefully focus on sustainable utilization of natural resources, water and soil and sustainable protection of the environment.

In addition, it should develop ecological agriculture and industry combining traditional and modern practices to realize the coordinated development of both the environment and economy. In the areas immediately surrounding the Volga River, the importance of environmental protection should also be emphasized because of its significant geographical position. In addition to increasing vegetation coverage, enhancing the capacity for soil and water preservation and strengthening controls on nonpoint pollution, the establishment of special ecologically functional reserves, such as the river national wetland nature reserve, is a matter of priority. Human migration due to the water and industry project itself must also be noted. Ecological protection measures must be adopted to prevent soil erosion, prevent and control pollution, and to protect water, air and soil quality during emigrant movement and settlement within the study area.

However, strengthening environmental protection alone without alleviating socioeconomic and environmental ignorance can only be a temporary measure. Therefore, it is necessary to address the problems of socioeconomic and raise public environmental awareness as well as scientific understanding. Generally speaking, proper protection of the ecological environment of the study area would be significant not only for the protection of water resources, the ecological system and biodiversity in Astrakhan, but also for social progress, economic development and improvement in standards of living, national prosperity of the water source areas and the region at large.

Conclusions

As a result of the present analysis, we can say that vulnerability is the result of considerable changes in ecosystems and would lead to significant economic hazards. After this analysis we find following vulnerability results:

1. Natural and environmental vulnerability can be modelled by using Remote sensing and GIS techniques.

2. Maximum area covered by moderate vulnerability zone.

3. Natural and enviromental vulnerability is highely effected by bad climate conditions, less agriculture cover, land degradation and high socio-economic activities.

The vulnerability analysis is an indicator which show that where we are more or less uncertain. It helps in indicating how society and policy can have an important role to play in future development pathways.

Acknowledgement

This data work is financially supported by the Russian scientific Foundation, grant no. 14-31-00014 “Establishment of a Laboratory of Advanced Technology for Earth Remote Sensing”.

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