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Nature Environmental Protection, 2020, 1(2); doi: 10.38007/NEP.2020.010204.

Animal Comfort Studies in Natural Environment Reserves Integrating RS and GIS

Author(s)

Firuz Suleymanov

Corresponding Author:
Firuz Suleymanov
Affiliation(s)

Department of Agriculture, University of Ioannina, Kostakii Campus, 47100 Arta, Greece

Abstract

Animals are an important part of the natural ecosystem, man's closest friend, an important source of wealth for human society, and a key factor in maintaining ecological balance and the harmonious development of human society. The composition of a fauna includes species composition, relative abundance and species diversity. In order to study the response of faunal communities to environmental change, it is necessary to first understand the species diversity of these communities, to observe the temporal dynamics of species composition and species richness, and to analyse the changing factors affecting the diversity of disturbed communities. The main objective of this paper is to develop a study of animal amenity in natural environmental reserves using RS and GIS techniques. In this paper, seven factors were selected to determine the influence of each natural factor and the parameters of the factors using the frequency of occurrence of animal trace points, to establish a suitable evaluation system using hierarchical analysis, and to evaluate the suitability of the protected areas before and after respectively. The impact on animal habitats is analysed by comparing the approximate distribution of damaged areas using classification. In this paper, the road factor evaluation of suitable areas for animals in nature reserves was graded and statistical analysis of the area was carried out to obtain statistics on the area of suitable areas for animals in nature reserves based on the road factor. The results show that 56.34% of the total area of the reserve is suitable for animals based on the road factor, 14.75% is sub-suitable and 28.91% is unsuitable.

Keywords

Remote Sensing, Geographic Information Systems, Natural Environment Reserves, Animal Comfort

Cite This Paper

Firuz Suleymanov. Animal Comfort Studies in Natural Environment Reserves Integrating RS and GIS. Nature Environmental Protection (2020), Vol. 1, Issue 2: 27-37. https://doi.org/10.38007/NEP.2020.010204.

References

[1] Busra Tegin, Eduin E. Hernandez, Stefano Rini, Tolga M. Duman. Straggler Mitigation Through Unequal Error Protection for Distributed Approximate Matrix Multiplication. IEEE J. Sel. Areas Commun. (2020) 40(2): 468-483.

[2] Astha Chawla, Animesh Singh, Prakhar Agrawal, Bijaya Ketan Panigrahi, Bhavesh R. Bhalja, Kolin Paul. Denial-of-Service Attacks Pre-Emptive and Detection Framework for Synchrophasor Based Wide Area Protection Applications. IEEE Syst. J. (2020). 16(1): 1570-1581. 

[3] Vivek Kumar Singh, Manimaran Govindarasu. A Cyber-Physical Anomaly Detection for Wide-Area Protection Using Machine Learning. IEEE Trans. Smart Grid. (2020) 12(4): 3514-3526. 

[4] Tamara Becejac, Crystal Eppinger, Aditya Ashok, Urmila Agrawal, James O'Brien. PRIME: A Real-Time Cyber-Physical Systems Testbed: from Wide-Area Monitoring, Protection, and Control Prototyping to Operator Training and Beyond. IET Cyper-Phys. Syst.: Theory & Appl. (2020) 5(2): 186-195. https://doi.org/10.1049/iet-cps.2019.0049

[5] Mahdi Haghifam, M. Nikhil Krishnan, Ashish Khisti, Xiaoqing Zhu, Wai-Tian Tan, John G. Apostolopoulos. On Streaming Codes With Unequal Error Protection. IEEE J. Sel. Areas Inf. Theory. (2020) 2(4): 1165-1179.

[6] Bokka Krishna Chaitanya, Anamika Yadav, Mohammad Pazoki. Wide Area Monitoring and Protection of Microgrid with DGs Using Modular Artificial Neural Networks. Neural Comput. Appl. (2018) 32(7): 2125-2139. https://doi.org/10.1007/s00521-018-3750-4

[7] Shalini, Subhransu Ranjan Samantaray. A Differential Voltage-Based Wide-Area Backup Protection Scheme for Transmission Network. IEEE Syst. J. (2020) 16(1): 520-530. 

[8] Sima Ghafoori, Ahmad Shalbaf. Predicting Conversion from MCI to AD by Integration of Rs-Fmri and Clinical Information Using 3D-Convolutional Neural Network. Int. J. Comput. Assist. Radiol. Surg. (2020) 17(7): 1245-1255. 

[9] Mateusz Marcisz, Margrethe Gaardløs, Krzysztof K. Bojarski, Till Siebenmorgen, Martin Zacharias, Sergey A. Samsonov. Explicit Solvent Repulsive Scaling Replica Exchange Molecular Dynamics (RS-REMD) in Molecular Modeling of Protein-Glycosaminoglycan Complexes. J. Comput. Chem. (2020) 43(24): 1633-1640. https://doi.org/10.1002/jcc.26965

[10] Niklas Sülzner, Julia Haberhauer, Christof Hättig, Arnim Hellweg. Prediction of Acid Pka Values in the Solvent Acetone Based on COSMO-RS. J. Comput. Chem. (2020) 43(15): 1011-1022. https://doi.org/10.1002/jcc.26864

[11] Leonel Mera-Jiménez, John F. Ochoa-Gómez. Volume Reduction Techniques for the Classification of Independent Components of rs-fMRI Data: A Study with Convolutional Neural Networks. Neuroinformatics. (2020) 20(1): 73-90. 

[12] Savita Soma, Mahesh V. Sonth, Sanjaykumar C. Gowre. Design of Two-Dimensional Photonic Crystal Based Ultra Compact Optical RS Flip-Flop. Photonic Netw. Commun. (2020) 43(2): 109-115. 

[13] Arjun BS, Alekya B, Hari RS, Vikas V, Anita Mahadevan, Hardik J. Pandya. Electromechanical Characterization of Human Brain Tissues: A Potential Biomarker for Tumor Delineation. IEEE Trans. Biomed. Eng. (2020) 69(11): 3484-3493. 

[14] Kamal Rsetam, Zhenwei Cao, Zhihong Man. Design of Robust Terminal Sliding Mode Control for Underactuated Flexible Joint Robot. IEEE Trans. Syst. Man Cybern. Syst. (2020) 52(7): 4272-4285. 

[15] Kevin Weinberger, Alaa Alameer Ahmad, Aydin Sezgin, Alessio Zappone. Synergistic Benefits in IRS- and RS-Enabled C-RAN With Energy-Efficient Clustering. IEEE Trans. Wirel. Commun. (2020) 21(10): 8459-8475. 

[16] Hyunwoo Cho, Hong-Yeop Song, Jae-Min Ahn, Deok Won Lim. Some New RS-coded Orthogonal Modulation Schemes for Future GNSS. ICT Express. (2020) 7(4): 530-534. 

[17] Akhilesh Yadav, Poonam Jindal, Devaraju Basappa. Design and Implementation of RS(450, 406) Decoder: Forward Error Correction by Reed Solomon Decoding. Int. J. Embed. Real Time Commun. (2020) Syst. 12(1): 19-43. 

[18] Banu Yetkin Ekren. A Multi-Objective Optimisation Study for the Design of An AVS/RS Warehouse. Int. J. Prod. Res. (2020) 59(4): 1107-1126. https://doi.org/10.10 80/00207543.202 0.17 20927