Using RS/GIS for spatiotemporal ecological vulnerability analysis based on DPSIR framework in the Republic of Tatarstan, Russia

doi:10.1016/j.ecoinf.2021.101490

Ecological Informatics

Volume 67, March 2022, 101490

https://doi.org/10.1016/j.ecoinf.2021.101490 Get rights and content

Highlights

•
Develop EVI based on satellite, socio-economic and demographic data.
•
Used remote sensing, GIS, GPS and DIP techniques for EVI analysis.
•
Analysis all indicators under DPSIR framework with AHP weight method.
•
Identify spatiotemporal changes in ecological vulnerability and their cause.
•
Suggestion for sustainable development and protection of eco-environment.

Abstract

The republic of Tatarstan is one of the most growing state in Russia in terms of industrialization and modernization with various natural disasters and intense human activities which brought dramatic changes in the ecological process and then led to serious ecological vulnerability. Therefore this research work proposed an analytical framework based on remote sensing (RS), geographical information system (GIS), and analytical hierarchy process (AHP) for spatiotemporal ecological vulnerability analysis at pixel level from 2010 to 2020 and developed a driver-pressure-state-impact-response (DPSIR) framework based on 23 indicators by the AHP weight method to compute ecological vulnerability index (EVI). Further, EVI was classified into five levels based on natural breaks in ArcGIS software as potential, slight, light, moderate, and heavy levels. All 23 indicators were generated from different remote sensing and socio-economic data, processed through digital image processing techniques in terms of removing errors, projection, standardization, and results were saved in GIS format. Results indicate that from 2010 to 2020, EVI was continuously increased from 0.419 to 0.429, and its changes associated with regional vulnerability events and their impact in the region. The moderate level EVI was covering the highest area in all three years with very few changes and continuously increasing. Results also indicate that higher human-socio-economic activities and pressure on natural resources increased ecological vulnerability. This research work is useful to identify main causes and responsible indicators for ecological vulnerability as well as suitable for real-time EVI mapping, monitoring at any scale and region.

Introduction

The ecological vulnerability index (EVI) represents a weak environment, which is at risk of damage due to disturbance in natural and man-made/artificial resources (Ji and Cui, 2021; Yajun and Lifang, 2020; Yang and Song, 2021). The risk of damage condition can easily understand by the vulnerability concept, where vulnerability means “the degree to which a system is susceptible to or unable to cope with adverse effects” (McCarthy, 2001). Broadly vulnerability has three parts: exposure, sensitivity, and adaptive capacity (Gupta et al., 2020; Swami and Parthasarathy, 2021). The adaptive capacity can also divide into two parts: coping adaptive capacity and resilience adaptive capacity based on the 4th assessment of IPCC. But now this was replaced by the 5th assessment report of IPCC to consider just sensitivity and adaptive capacity for assessing vulnerability. In the present time where fast development, new infrastructure, modernization create challenges to make a balance situation between ecology and economy. Governments are more focused on economic growth in place of ecological conservation and avoid sustainable development. Therefore economic development and ecosystem conservation are the two most important parameters to achieve in sustainable development plans (Huiling and Dan, 2020; Peng and Deng, 2021; Surya et al., 2020). However, a higher rate of human-socio-economic activities and climate change is the main factor for accumulative and extension of ecological vulnerability (Saha et al., 2021; Xu et al., 2021). At present, ecological vulnerability analyses is an essential part of sustainable development plans and at the same time protect natural resources for their subsequently utilization by the future generations. It also helps to avoid misuse of land and promote proper utilization of natural resources (Jogo and Hassan, 2010; Qin and Leung, 2021; Xie et al., 2020). This attracts researchers for indictors-based ecological vulnerability study with the concern of “socio-ecological” parameters (Lata et al., 2021; Praharaj et al., 2018).

EVI assessment is the most important study for proper eco-environmental management and sustainable development of a site-specific area (Basu and Das, 2021; Boori et al., 2021). It's a great help if study, ecological vulnerability patterns, and transformation with its levels and change mechanisms addressed (Zhu and Song, 2021). Some site-specific studies through remote sensing and GIS technology have been done in Russia for ecological vulnerability assessment such as greenness, peninsula study, social, social-ecological, biodiversity, wildlife, oil spill sensitivity, community resilience, city, wetland, coastline, reservoirs, etc. (Alessa et al., 2008; Carroll and Miquelle, 2006; Depellegrin and Pereira, 2016; Forbes, 2007; Kuenzer et al., 2019; Walker et al., 2009). But these studies were failure to consider special characteristics, complicities, and variations of regional indicators as well as their appropriate background or context for EVI assessment (Choudhary et al., 2021). Therefore the main aim of this study was to develop a new model, which considers the maximum possible site-specific indicators relevant to human-socio-economic-ecological characteristics and provide an accurate real-time ecological vulnerability index. Based on previous experts' knowledge and skills, this research work used the driver-pressure-state-impact-response (DPSIR) framework for a complete and qualitative EVI assessment. All indicators were identified at grid level, integrated with the AHP weight method under the DPSIR framework, and resulted EVI was quantified at grid level for the whole study area.

Thus the main objectives of this research work were:

1.
Identify most suitable regional relevant ecological vulnerability indicators under DPSIR framework;
2.
Assign a weight to vulnerability indicators using AHP;
3.
Identify spatiotemporal changes in ecological vulnerability index at grid level;
4.
Suggestion for sustainable development and at the same time protection of eco-environment.

Section snippets

Study area

The Republic of Tatarstan is situated in the center of the East European plain, approximately 800 km east of Moscow, Russia (Fig. 1). It lies in between the biggest European river Volga and Kama River and extended till the Ural Mountains in east and joint of European and Asian Russia. Tatarstan has a 3.8 million population and covers 67,800 km² areas, which means bigger than Belgium and Netherlands and equal to Ireland. The main natural resource of Tatarstan is oil, natural gas, gypsum,

Method

All standardized indicators created in RS/GIS were combined by using a raster calculate module in ArcGIS software to produce EVI maps for the study area. Fig. 2 illustrate all methodological steps, which was used in this research work.

Ecological vulnerability index assessment

Fig. 3 represent ecological vulnerability index maps of the study area for the years 2010, 2015, and 2020. EVI distribution maps clearly associated with local vulnerability events and their impacts. The extreme cold weather with the fast-developing speed in the region was the main cause of changes in the ecological situation in the Republic of Tatarstan, Russia. The population in the study area has been continuously increasing, which also increases industrialization, new infrastructure,

Discussion

There were a lot of changes in ecological vulnerability from 2010 to 2020 spatially in the north part of the study area and close to Kazan city. The government was trying to protect the environment with sustainable development and implant new policies. Kazan has been the third most visited tourist place in Russia and the total population of Tatarstan has been continuously increasing. Therefore higher human-socio-economic activities and investments for modernization, EVI was increasing. The FIFA

Conclusions

This research work analyzed spatiotemporal ecological vulnerability analysis in Tatarstan Russia from 2010 to 2020 under the DPSIR framework. Results indicate that a moderate level of EVI was dominated all the time, which is an alarming situation. The north part of the study area has a higher level of ecological vulnerability, while the south part of the study has a lower level of vulnerability. As north part have higher human-socio-economic activities due to higher industrialization,

Declaration of Competing Interest

The authors declare no conflict of interest.

Acknowledgments

The research was supported by the Ministry of Science and Higher Education of the Russian Federation (Grant # 0777-2020-0017) and, was partially funded by RFBR, project number # 20-51-05008.

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Using RS/GIS for spatiotemporal ecological vulnerability analysis based on DPSIR framework in the Republic of Tatarstan, Russia

Highlights

Abstract

Introduction

Section snippets

Study area

Method

Ecological vulnerability index assessment

Discussion

Conclusions

Declaration of Competing Interest

Acknowledgments

Environ. Challen.

Remote Sens. Appl.

Mar. Pollut. Bull.

Ecol. Indic.

J. Environ. Manag.

Sustain. Comput.

Ecol. Econ.

Expert Syst. Appl.

J. Arid Environ.

Ecol. Indic.

Ecol. Indic.

Sci. Total Environ.

J. Clean. Prod.

Losing the plot: environmental problems and livelihood strife in developing rural Ethiopia—Suri Agropastoralism vs. state resource use

The Arctic water resource vulnerability index: an integrated assessment tool for community resilience and vulnerability with respect to freshwater

Environ. Manag.

The weight of interaction of mining activities: groundwater in environmental impact assessment using fuzzy analytical hierarchy process (FAHP)

Environ. Earth Sci.

Comparing implementations of global and local indicators of spatial association

Test

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J. Comput. Opt.

Spatial viability analysis of Amur tiger Panthera tigris altaica in the Russian Far East: the role of protected areas and landscape matrix in population persistence

J. Appl. Ecol.

Land evaluation and sustainable development of ecotourism in the Garhwal Himalayan region using geospatial technology and analytical hierarchy process

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Environ. Chem. Lett.

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