This present study Analytical Hierarchy Processes (AHP) techniques, PVI and SVI indices were applied, calculate and identified the physical and socio-economic, cultural, historical and environment criterion and sub-parameters (05 major criteria and 22 sub-parameters) based on the evaluation of tourism potential ability of each parameter and its scenic beauty for a selected site of Ganpatipule beach in Ratnagiri District, Maharashtra (India) most significant importance to tourism. AHP-OS software was used to calculating pairwise comparisons matrix and determine the weight of selected criterion and parameters. The physical of vulnerability index (PVI) and socio-economic vulnerability index (SVI) calculating the physical computation of consistency ratio, CR=CI/RI (CR=0.07) the socio-economic computation of consistency ratio, CR = 0.08 values identified study area tourism potential is relevant. The PVI and SVI classes i.e. very highly coastal tourism potential to low coastal tourism potential are identified to the coastal area natural potential site. GIS-based Arc 10.3; Global Mapper (2011) the software was used to analyze beach potential in the study area. The AHP techniques are most applicable for in this study area for coastal tourism planning, management and development of local level.
Tourism is one of the energetic and 1, 2 most vital fast-developing prime industry 3, 4. Tourism activities are a major role in economic development at the national to the local level. These activities are directly affected by the environment and human societies. Hence, proper need coastal management and planning in tourism sectors is significant to the sustainable development 5. The world tourism industry total financial involvement of travel and tourism to GDP global 2006-2019 is 9258 billion U.S. dollars and it’s also a favorable economic environment world GDP is +3.6 % (UNWTO, 2019). Most coastal scenic beauty and coastal tourism potential are important resources of coastal tourism 6 development. Nature-based coastal tourism is the asset of the nation 7. The tourist destination is created job opportunities surrounding area and ultimately income level have increased the at global to the local level. Coastal morphological landscape 8 is a major natural attraction of the tourist. Geotourism is the major principles are nature-based tourism these are major reasons the tourism sector is developed in all over the world 9. Several researchers have been scientifically carried out the studies for tourism potential identification using Analytical Hierarchical Process (AHP) for coastal tourism development. AHP methods identified the potential sites, coastal tourism, and scenic beauty of beach for tourism development. Hence, the research area has been marked on AHP techniques for coastal tourism development in Ganpatipule beach. The criteria and sub-parameter like beach sand color, coastal slope, and an aerial view of the beach; beach sunset, sunrise view, adjacent land use and man-made attraction, festival, religious activities, historical attraction etc. are used for identification coastal tourism potential and its scenic beauty of the study area. Suryawanshi and Ranyewale 10, Mani Murali 11, Pralong and Reynard 12, Suryawanshi 13 have used the different criteria and parameter value, namely the scenic, scientific, historical, cultural and economic value for identification potential tourism sites. Some of the researchers have used similar parameters like as beach water clarity, the size of the area, coastal slope (%), adjacent land use, seas, lakes, streams, integrity 14, 15, 16, 17, 18, demarcated criterion such as scenery, wildlife, topography, ease of access, society uniqueness in Surat Thani have Province, Thailand. Tourism potential evaluation criteria aesthetic and artistic value, pursuit value, civilizing-past value, systematic value, biodiversity, the mass of tourism destination, sightseeing seasonality, linkages among new visitors site, prospective user-friendliness, the remoteness from visitor attractions to the town center, lodging excellence, cookery excellence and service labour excellence etc have been used for assessment tourism potential. Therefore, scientific, physical and socioeconomic criteria and sub-parameters are selected in the present’s research for identification of tourism potential.
AHP advance techniques were applied for the identification of tourism potential within the research area. The majority of the researchers into the revision of tourism potential have used recent scientific GIS (Geographical Information System) base multi-criterion (MCE) method. These AHP and GIS techniques have been practiced via a variety of researchers in different physical areas of India 19, 20, 21. The GIS and RS technique using satellite images are used as an appropriate apparatus for identifying of tourism potential sites and its scenic beauty 15, 17, 22, 23. Moreover, to Study evolution tourism potential, satellite image has been used by Mani Murali 11.
Further, Analytical Hierarchy Processes, techniques widely used for the tourism development sector and its various uses like identification tourism potential sites, scenic beauty, tourism site suitability and so on. Analytical Hierarchy Processes determine the weight of influence into definite tourism potential use pairwise comparisons of the parameters as per research area importance to determine the rank and criteria for identification of tourism potential using the OS AHP software. Saaty 24 was used the AHP technique can evaluate the complexities with their significant important. The present research mentions the process to the identification of tourism potential and its scenic beauty the standard physical and socioeconomic criteria and sub-parameters of the Ganpatipule beach in Ratnagiri district in Maharashtra (India) by applying GIS-based geoprocessing system software ARC drawing component in ARC GIS 9.3 and Global Mapper (2013). The study area selected all standard criteria and sub-parameter of tourism potential were computed statistics to evaluate the uniqueness of different tourism potential parameter for research and progress of coastal tourism.
Ganpatipule beach is the part of Ratnagiri (Tahsil) district in the western coast of Maharashtra and covered by ‘Kokan region’. The geographical extension of the study area is 170 8’ 0’’North to 170 9’ 30’’North latitude and 730 16’ 0’’East to 730 17’ 0’’East longitude (Figure 1). The study area beach is an entire north-south narrow strip, low coastal land plain height below 100 meters. The atmosphere of the research area is characterized as a result of warm summer from the coastal area day and night temperature variation is little change between 17°C to 35°C in March to May. The annual rainfall distribution in a wet period from June to September is 4589 mm. Ganpatipule surrounding area having rich flora and fauna with there is the coconut and mangrove trees it’s a very small village, including a total of 304 household families’ resident. Mostly all villager main spoke language is Marathi and kokani. Ganapatipule village sex ratio is 826 lower than the state of Maharashtra (929). The literacy rate Ganapatipule is 92.42% and the total population of this village is 1236, out of this population 667 were engaged in work activities. Rice is a major crop production from this villager (Census of India 2011). Beach side have the 400 years old ’Swayambhu’ Ganpati been the main attraction of tourist, mostly tourist visited in “Gauri Ganpati “and “Magh Chaturthi” festivals time.
The current research is a scientific review of existing literature on identification tourism potential studies of the Ganpatipule coastline with emphasis on coastal Ratnagiri district. Basically to identified the tourism potential sites of Ganpatipule beach mainly physical and socio-economic criteria and sub-parameters like beach scenic value, beach scientific investigated value, historical and cultural value, hospitality and tourism value and assessment of beach environment value have been assessed based on literature review using GIS-based and OS AHP software techniques approach. The identifications of study area location Ganpatipule beach were approved, using the Survey of India (SOI) toposheet on a 1:50,000 scale. The Maharashtra Maritime Board data and Census of Ratnagiri district data (2001 and 2011) were used for evaluating the specific appropriate beach potential scenic value of selected each criterion and parameter and investigation of beach morphology (Table 1).
The fieldwork was carried out in the direction of gathering the information adjacent beach physical landscape features and artificial features between the assist of global positioning system (GPS). The Google image data are overloaded, process, and analyze in ARC GIS 9.3 and Global. Saaty 24, 25 introduced the AHP method to resolve the complex judgment -making problems. For that reason, present research AHP techniques have been used for the identification tourism potential with based coastal vulnerability index (CVI) taking equally physical (PVI) and socioeconomic (SVI) criteria and sub-parameters into consideration (Figure 2).
Coastal morphological Physical characteristics are most significant for tourism planning, management and development. Cetin and Sevik 16, Brilha 14, Li Lin and Pussella 17, Mani Murali 11, Pralong and Reynard 12 Suryawanshi and Ranyewale 26 You-jun and Zheng-xin 18 have used the physical and socio-economic, cultural and historical with environment assessment parameter (five major criteria and 22 sub-parameter) namely, beach morphology (BM), landscape features (LF), beach sand colour (BSC), beach sunrise and sunset view (BSV), and beach water clarity (BWC) size of the area (SA), coastal slope (%) (CS), adjacent land use (ALU), seas, lakes, streams (SLS), Integrity (I) for identification tourism potential and its scenic beauty. Further, Botero 27, Hoang 28, Mamun and Mitra 12, 29, You-Jun and Zheng-Xian 18, has used the standard socioeconomic criteria and sub-parameters including historical attraction (HA), cultural attraction (CA), tourism activity duration (TAD), tourist visitors intensity (TVI), accessibility/connectivity (A/C), the distance from tourist location (DTL), accommodation (A), beach security/protection (BC/P), Pollution(P), beach management (BM), erosion risk (ER) and beach cleanness(BC) for identification of coastal tourism potential using AHP techniques. These parameters influence the potential of the morphological site. Therefore, these parameters are considered for identification tourism potential and its scenic beauty 30 for tourism planning, management and development based on literature survey, field survey and local morphological condition of the beach. The selected physical and socioeconomic criteria and sub-parameters mention all these parameters about the inherent capacity of the coastal site for tourism suitability (Table 2).
The morphology of coast is formed by exogenetic and endogenous processes. The rocky cliff coast and wave-cut platform at risk for tourist activities on the beach, but the soft sand and Open/ barren land beach is more suitable for tourism activities. Thus, the present study of sea coast morphology enables to identify the coastal areas is suitable for tourism activities.
The coastal landscape features such as a surrounding mountain, valley sites, and water bodies increase the beach, scenic value which is an engage in recreation and significant function in tourism and support in favor of visitor’s natural attractive morphological sites.
Tourists always visited a white /golden sand shore than a bright one. Ganpatipule beach, characterized is natural tourism potential scenic sites, white sand beaches with fine and smooth sand. It is the outstanding nature-based attraction of tourism with high tourism potential.
The peaceful environment is the input attractions of tourist resting on the sunlight beach. It’s the positive impact on basically coasting tourism their from the cultural community with various festivals therefore such coast site promoted to accommodation planning, developing new tourist attractions. Form the study area beach sunrise and sunset view was assigned ranks 4 according to the weight of significance values high tourism potential.
The tourist greatest ideal on beach priority 31 or coastal tourist preference is coast water clarity. The statement about the Brazilian Tourism Ministry sun and coast sightseeing as tourism behavior related pursuit on the coast suitable to the transparent beach water clarity with a peaceful environment. Therefore beach water excellence is one of the significant factors in favor of the choice of tourist beach, as a result of community strength situation consequently with the purpose of tourists can choose which coast to visit 32. Thus, present study beach water quality is transparent for tourism developers.
3.4. Beach Scientific Investigates Value (BSIV)The sizes of the beach are important elements related to tourism activities, i.e. overnight tourist capacity, hotels, the hospitality tourism, assessment of beach environment, it is essential to promote tourism development with maintaining the peaceful environment and pollution free of the scenic area 33. Therefore, the size of the area 0.75 ha- 0.50 ha with moderate size considered as the criterion for identification of tourism potential in the research area.
Coastal slope analysis is significant physical features for site suitability of tourism. The gentle slope is more potential for a tourist attraction than the steep slope. The present research, ASTER data database of sea coast elevations > 1 (1.30) has been used to identify the coastal slope. This data is obtained from the Maharashtra Maritime Board, India and the coastal slope of the entire research area. The gentle slope is more suitable for coastal tourism activities and base criterion in tourism development. The slope layer is classified four categories based the ranking criteria (Table 2) Which is low; moderate, high and steep. Therefore, a region with moderate slopes > 1 (1.30) 34 was considered as the criterion for identifying risk to tourism activities towards an ocean of in the study area
Terrain utilize is the most significant aspect of the tourist attraction for the environmental assessment, progress of land use in the present condition all over the humankind 1, 35. Therefore, GIS-based techniques ARC GIS 9.3 was used in this study to evaluate the marshy/swampland, the mixed crop with built-up, paddy field, mangroves, Scrub vegetation, social forestry, plantation, forest land use of tourism.
Sea, lake or island and the stream is a characterized by nature-based physical setting on the border of land and sea present off white or golden sand beaches, scenic beauty, variety of plants or biodiversity, delta free coast morphology with natural environment etc. 36. This research attempts to evaluate the potentiality of sustainable sightseeing in Ganpatipule sea adjacent location of tourism development.
The scientific value of the morphological sites was based on integrity, natural rarity and representatives of the local morphological sites. Both natural and anthropogenic factors a positive and negative effect on the coast 12, 14. The present beach is intact, it’s suitable for tourism development and planning.
3.5. Historical and Cultural Value (HCV)The Role of historical attraction of tourism development is important including historical port, temple, churches, home of a famous person, monuments, In this study area, Keshavsut birthplace was the famous attraction of tourists from Malgund.
The cultural activities, engage in recreation a dominant function in the growth of the tourism industry, i.e. performing arts, visual arts, folk festival, the cultural tradition of a local people, food, shopping places, accommodations, architecture, handicrafts, theatres etc. Thus the present study area cultural is very rich.
The morphological and cultural heritage factors determined the suitability tourism potential sites. It is a huge attraction of tourist in the study area due to the rich natural and artistic tradition site in support of the increase of coastal tourism. Tourists visiting proportion yearly is >200–300 days per year given study area.
The scenic beauty with rich natural and cultural heritage location 37 with good services and facilities available to tourist they prefer or choice or selected to this destination for tourism. The tourist visitor’s intensity depends on the season, festivals and cultural events. The present study area tourist visiting intensity is major in the Ganesh Chaturthi and festivals.
3.6. Hospitality of Tourism Value (HTV)Road networks, including state road, sea face road, railway station and airport are essential to the development of beach tourism 11, 38 and high tourism potential sites. The present study area shows positive indicators, i.e. moderate accessibility with good accessibility for tourism development 13.
The distance from road, city, transportation, hotel, medical, hospital, police station, railway station, airport, restaurant, parking accommodation, etc. to the tourist location plays a key role in tourism development. The study areas highly suitable for tourism were mostly located 39 in the shoreline are < 1km.
The tourist prefers to visit any tourism destination that essential the availability of good accommodation facilities with better food with additional entertainment and communication services and facilities Besides, sport, accommodation sites of sunset and sunrise aerial viewpoint location, game reserves, parks, swimming tank should be assisted in the development of their potentials. In this area good accommodation facilities are available.
Beach protection is essential to strict control visitors’ overnight flow, tourism activities and it’s related all services and facilities, natural environmental security is more significant for a peaceful and ecological environment of scenic area 33. In this study area, beach security is no maintained properly.
Tourism is the most significant source of economic development. Relative to land-use changes in tourism sectors, various ecological and natural resources issues, i.e. water, air, noise, land pollution and problems appear in the seacoast area. Therefore, coastal zone management is required intended for the growth of sustainable tourism in the research area.
Nobre 40 has been focused on Integrated Coastal Zone Management (ICZM) programs, including protection of coastal resources (CZM, USA, 1993-1995), management of coastal development, safety of beach dunes, bluffs and stony coast and terms of public admission to the beach (CZM, USA, 1995-1997) for coastal management. Therefore, the present area needs to implement the coastal zone management policy and conserve the morphological site.
The physical, climatic and geological hazard is affected on sea coast due to damaged natural tourism potential of sites 41. Moreover, these coastal areas are highly populated and their erosion risks to infrastructure are high and prone to more erosion. Therefore, coastal management 42 and protection are needed and reduced the erosion risk to infrastructure for tourism development.
The beach cleanness is the nearly everyone important reason in support of coastal choice 43. Ganpatipule beach is an extremely beautiful destination used for local and national tourists for to a large extent of the year. Here attempt to improve the beach cleanness and maintain the coastal tourism potential and its scenic beauty.
Prof. Thomas L. Saaty (1970) introduces the Analytical Hierarchy Process (AHP) method which is mostly used for solving composite problems connected to group judgment making. Several researchers have been used to AHP. Therefore, AHP has been used for identification of tourism potential and its scenic beauty in the present study. This method is processed following steps for identification of tourism potential criteria and sub parameter: (1) determination of ranks, (2) pairwise comparison matrixes, (3) normalization of pairwise comparison matrix, (4) calculation of weights and influence (5).
Kennell 37, Chen 44, Gaikwad and Bhagat 45, Ghamgosar 1, Gumusay 10, Bozic and Mani Murali 11, Truong and Jang 46, Zolekar and Bhagat 20, Zolekar 21 its scholar have been used multi-criteria decision-making and pairwise comparison matrix. Literature review, field survey, Maharashtra Maritime Board quantitative and qualitative data have been mostly used for determination of ranks to the criteria and sub-parameters selected for identification of tourism potential and its scenic beauty. The scores were assigned to the criteria and sub-criteria from 1 to 4 i.e. low (1), Moderate (2), High (3) and Very high (4) (Table 2, Table 3 and Table 4) which is the prime score to indicate the potential site.
Further, researchers in the field of tourism potential 47 and scenic beauty have assigned scores to the criteria and parameter on the basis of coastal tourism potential site 1 to 9 (Table 4). The researcher has been assigned the score for sub- criterion and parameter (Table 5 and Table 6) and calculated by score or weight value of each physical, i.e. coastal slope (%), size of the area, Seas, Lakes, Streams, landscape features, integrity, beach water Clarity, beach sunset sunrise view, adjacent Land use, beach morphology 11, 12, 14, 16, 17, 26 and socioeconomic, cultural and historical with environment criterion and sub parameter (Table 5 and Table 6) i.e. erosion risk (ER), beach management (BM), beach cleanliness (BC), beach security/protection (BC/P), accessibility/connectivity (A/C), tourism activity duration (TAD), cultural activities, historical attraction (HA), pollution (P), accommodation (A),distance from tourist location(DTL),tourist visitors intensity(TVI) 12, 18, 28, 41 were assigned, as per nine point scale factors in Business Performance Management Singapore (BPMSG’s), AHP-Online Systems –AHP-OS software used to determine and calculate the weights or score.
Saaty (1980) has been suggested pairwise comparison matrix (PCM) to compute the weights for calculation of the influence of criterion to express the relative significant between each two criteria. The Field survey and literature analysis were used for arrangement of conclusion between two criteria and the pairwise comparison matrix (PCM) was arranged (Table 5 and Table 6). The pairwise comparison matrix (PCM) helps to identify the relationship between the criterion relative to the identification of tourism potential and its scenic beauty in the present study. The criterion principles in PCM were divided as a result of the total of the column to locate the cell values in normalized pairwise comparison matrix (Table 7 and Table 9) 11, 15, 19, 48.
The calculating normalized matrix of selected criterion and sub Parameter and find out each weight of criterion and sub Parameter 11 were used the following normalized matrix calculating equation 1 (Table 7 and Table 9).
(1) |
= Normalized Matrix.
= Weight of each criterion.
= Sum of each criterion
Further, the normalized matrix percentage weight of each criterion was calculating sum/final influence selected criterion and sub Parameter and dividing all the cell values from the sum of the respective columns in the pairwise comparison matrix used (Table 8 and Table 10) the following percentage weight calculating equation 2.
(2) |
= Percentage weight of each criterion.
= Sum/final influence.
n = Number of criterion/parameter.
Consistency ratio (CR) was used the scaling method and its priorities in hierarchical structures 24 (AHP). Basically consistency ratio (3) a result was calculated by consistency index value (CI) dividing the random index value (RI) as follows (Equation 3),
(3) |
Here, the consistency index (CI) can be expressed as [1,10,11,24,37,44,46,49,50,51] Equation 4),
(4) |
Saaty 24, 25 expressed that consistency ratio (CR) of a value of 0.10 or less is considered relevant or accepts its means that is a significant priority if consistency ratio (CR) of a value of > 0.10 or < 0.1 it’s not relevant or rejects or error, its means not significant then calculating AHP sequence (Table 12) 11, 52.
The physical vulnerability index (PVI) calculating was used 11, 52, 53 the following equation (5),
(5) |
Here, Weight of each physical parameter and vulnerability score of each variable. The socioeconomic vulnerability index (SIV) was calculated as follows equation (6),
(6) |
A Researcher has used the Coastal vulnerability index (CVI) as follows equation (7), considering that both physical and socioeconomic factors have equal contribution to coastal vulnerability.
(7) |
The geographical study of a selected site of Ganpatipule beach in Ratnagiri district, Maharashtra (India) were using multi-criteria the Analytical Hierarchy Processes (AHP) 24 method for identifying the potential of coastal tourism and its scenic beauty. These are the resulting weights for the 05 major criteria and 22 sub-parameter (10 physical and 12 socio-economic, cultural and historical with environment Parameter) based on pairwise comparisons and normalized matrix (Figure 7, Figure 8, Figure 9, Figure 10). The researcher was (equations 3) for the calculating the physical computation of consistency ratio, CR=0.07), (equations 4) CI= 0.10 and RI (1.49) (Table 11) and find out the socioeconomic computation of consistency ratio, CR = 0.08, CI= 0.12 and RI=1.48 values results. The researcher measures the evaluation of the consistency ratio 24 was using the CR ≤ 0.10 (physical variables 0.07 ≤ 0.10 and socioeconomic variables 0.08 ≤ 0.10) its mean physical variable consistency ratio is 0.07 is less than ≤ 0.10 and socioeconomic variables 0.08 less than ≤ 0.10 (Table 13). Therefore the geographical study of a selected site of Ganpatipule Beach in Ratnagiri District, Maharashtra (India) it’s the potential of coastal tourism and scenic beauty is most relevant and significant. Therefore the Ganpatipule beach site has been more applicable and suitable for tourism planning and development.
The Physical vulnerability index (PVI) estimated and find out variables result. The physical criterion and sub-parameter value PVI is the base of priority rank. These physical variables are showing the priority rank, first, three priority ranks are beach morphology (BM) (1), beach sand colour (BSC) (2) and adjacent land use (ALU) (3) then beach sunset and sunrise view (BV) (4), beach water clarity (BWC)(5), integrity(I)(6), sea lake, stream (SLS) (7), landscape features (LF)(8), size of the area (SA) (9) and coastal slope(CS) ranks is 10 its means risk to sunbathing because the slope is not gentle along the coastline (Table14).
Here, socioeconomic vulnerability index (SVI) calculating the variables result and socioeconomic, cultural and historical with environment criterion and sub-parameter value SVI is the base of priority rank. These socioeconomic variables are showing the priority rank, first, three priority ranks the distance from tourist location (DTL) (1), accommodation (A)(2), and tourist visitors intensity(TVI)(3)then Pollution(P)(4), historical attraction (HA)(5), cultural attraction (CA)(6), tourism activities duration (TAD)(7), accessibility/ connectivity (A/C)(8), and beach Security /protection (BC/P), ranks is 09, beach management (BM) 10 is expressed that absent of management and also beach cleanliness (BC)(11) is fair it’s not maintained properly. Here to highlight that Ganpatipule beach area erosion risk (ER) (12) is the major issues (Table 15).
4.3. Classification of the Tourism PotentialThe classification of the tourism potential to base of the physical vulnerability index (PVI) and socioeconomic vulnerability index (SVI) these as follows:
The beach water clarity (BWC), integrity (I), sea lake, stream (SLS), landscape features (LF), size of the area and coastal slope all these physical variables have the low tourism potential and socio-economic variables namely historical attraction (HA), cultural attraction (CA), tourism activities duration (TAD), accessibility/ connectivity (A/C), and beach Security/protection (BC/P), beach management (BM), beach cleanliness (BC), and erosion risk (ER) low tourism potential for tourism development and management. Therefore the government level and local level planning and management are most important in this tourism sector.
The beach sand color (BSC) and adjacent land use (ALU) then beach sunset and sunrise view (BV) these physical variables have the moderate tourism potential and socioeconomic variables, i.e. tourist visitors intensity (TVI) and Pollution (P) were coming into these categories. Its means infrastructures facilities and tourism, coastal action plan policy implementation needed
The hospitality of Ganpatipule beach, e.g. the distance from tourist location (DTL) and accommodation (A) is good; it is significant factors for tourism development.
The beach morphology of Ganpatipule beach is naturally highly attractive and the nature base tourism place. Therefore, this beach has high coastal tourism potential and scenic beauty.
The ARC GIS 9.3, Global Mapper (2013), OS AHP free software and Microsoft excel (2007) based evaluation technique, i.e., AHP, analysis, is most applicable to identifying tourism potential and its scenic beauty in the study area.The study was conducted using 05 major criteria and 22 subparameter criteria related to the physical parameter, i.e., beach morphology (BM), landscape features (LF), beach sand colour (BSC), beach sunrise and sunset view (BSV), and beach water clarity (BWC) size of the area (SA), coastal slope (%) (CS), adjacent land uses (ALU), Seas, Lakes, Streams (SLS), Integrity (I) are observed to identified tourism potential. However, socio-economic variables are most important factors i.e. historical attraction (HA), cultural attraction (CA), tourism activities duration (TAD), tourist visitors intensity (TVI), accessibility and connectivity (A/C), the distance from tourist location (DTL), accommodation (A), beach security and protection (BC/P), Pollution(P), beach management (BM),erosion risk (ER) and beach cleanness (BC) Weights of criteria were calculated using PCM and scores were assigned based on field survey and literature survey. The PVI and SVI index shows that the tourism potential with attractive natural scenic beauty in this study area. Some criteria show the environment assessment potential value is low. Therefore need to maintain the coastal area and conserve the coastal morphology for tourism planning and management of the local area
I thank you to a colleague from my department Mr. Ravindra Gaikwad, Prof. (Dr.) Vijay Bhagat, Dr. Zolekar Rajendra and my dear student Mr. (Dr.) Nanabahu Kudnar in favor of their precious assist and idea with moral sustain throughout this research. AHP-Online Systems –AHP-OS software thanked for free access to the software. Critical review and positive remarks from the anonymous reviewers meaningfully upgraded the final paper.
The author state no conflict of interest.
AHP: Analytical Hierarchy Process; SOI: Survey of India.
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[25] | Saaty, T.L., “Principles of the Analytic Hierarchy Process,” Expert Judgment and Expert Systems Edited by J. Mumpower et, (35)1-47, 1987. | ||
In article | View Article | ||
[26] | Suryawanshi, R. S., and Ranyewale, S. K., “Tourism Potential of Geomorphosites: A Comparative Assessment of Selected Beach Sites in Malvan Tahsil, Sindhudurg Coast of Maharashtra (India),” Transactions, 40(2), 285-292, 2018. | ||
In article | |||
[27] | Botero, C., Pereira, C., Anfuso, G., Cervantes, O., Williams, A. T., Silva, C. P., and Manjarres, A., “Recreational parameters as an assessment tool for beach quality”, Journal of Coastal Research, (70), 556-562, 2014. | ||
In article | View Article | ||
[28] | Hoang, H. T. T., Truong, Q. H., and Nguyen, A. T., “Multicriteria Evaluation of Tourism Potential in the Central Highlands of Vietnam : Combining Geographic Information System (GIS), Analytic Hierarchy Process (AHP) and Principal Component Analysis (PCA)”, Sustainability (MDPI), 1–20, 2018. | ||
In article | View Article | ||
[29] | Mamun, A. Al. and Mitra, S., “A Methodology for Assessing Tourism Potential: Case Study Murshidabad District, West Bengal, India, International Journal of Scientific and Research Publications, 2(9), 1-8, 2012. | ||
In article | |||
[30] | Mooser, A., and Anfuso, G., “Management Implications for the Most Attractive Scenic Sites along the Andalusia Coast (SW Spain),” Sustainability(MDPI), 1-26, 2018. | ||
In article | View Article | ||
[31] | Botero, C., Anfuso, G., Williams, A. T., Zielinski, S., da Silva, C. P., Cervantes, O., and Cabrera, J.A., (2013), “Reasons for beach choice: European and Caribbean perspectives,” Journal of Coastal Research, 65(1), 2013. | ||
In article | View Article | ||
[32] | Cristiano, C., Carla, L., and Anfuso, G.,”Coastal scenic evaluation at Santa Catarina ( Brazil ): Implications for coastal management Coastal scenic evaluation at Santa”, Ocean & Coastal Management · 146–157,2018. | ||
In article | View Article | ||
[33] | Lin, S., Lu, J., and Fan, Y., “An Ecological Early Warning Indicator System for Environmental Protection of Scenic Areas,” Sustainability(MDPI), 1-15,2019. | ||
In article | View Article | ||
[34] | Kumar, T. S., Mahendra, R. S., Nayak, S., Radhakrishnan, K., Sahu, K. C., Kumar, T. S., and Sahu, K. C., “Coastal Vulnerability Assessment for Orissa State, East Coast of India Coastal Vulnerability Assessment for Orissa State, East Coast of India”, Journal of Coastal Research, (263), 523-534, 2010. | ||
In article | View Article | ||
[35] | Duke, J. M., and Aull-hyde, R.,”Identifying public preferences for land preservation using the analytic hierarchy process”, Ecological Economics, 42, 131–145, 2002. | ||
In article | View Article | ||
[36] | Hajra, R., “Formulation of Methodological Approach for Sustainable Tourism Using “STC” Criteria : A Case Study of Sagar Island, India,” International Journal Of Innovative Research & Development, 3(1), 305-309, 2016. | ||
In article | |||
[37] | Bozic, S., Vujicic, M., & Kennell, J., “Sun, Sea and Shrines : Application of Analytic Hierarchy Process (AHP) to Assess the Attractiveness of Six Cultural Heritage Sites in Phuket (Thailand),” Geographica Pannonica, 22(2), 121-138, 2018. | ||
In article | View Article | ||
[38] | Pareta, L., “Remote Sensing And Gis Based Site Suitability Analysis For Tourism Development,” International Journal of Advanced Research in Engineering and Applied Sciences, 2(5), 43-58, 2013. | ||
In article | |||
[39] | Wanyonyi, J. W., Imwati, A., and Boitt, M., “GIS In Analysis of potential Sites For Ecotourism – A Case Study of Kwale County,” Journal of Environmental Science, Toxicology and Food Technology, 10(10), 43-49, 2016. | ||
In article | View Article | ||
[40] | Nobre, A. M., “Scientific approaches to address challenges in coastal management, “Marine Ecology Progress Series, 434(1), 279-289, 2011. | ||
In article | View Article | ||
[41] | Bagdanavi, I., Kelp, L., Galinien, J., and Soomere, T., ”Index based multi-criteria approach to Coastal risk assessment,’’ Journal of Coastal Conservation, 23,785-800, 2019. | ||
In article | View Article | ||
[42] | Pranzini, E., “Ocean & Coastal Management Evaluation of the scenic value of 100 beaches in Cuba : Implications for coastal tourism management”, Ocean and Coastal Management, 142, 173-185, 2017. | ||
In article | View Article | ||
[43] | Williams, A. T., Micallef, A., and Anfuso, G., “Andalusia, Spain : An Assessment of Coastal Scenery ,” Landscape Research, 37-41, 2012. | ||
In article | View Article | ||
[44] | Chen, C., “Applying the Analytical Hierarchy Process (AHP) Approach to Convention Site Selection” Journal of Travel Research, 45, 167-174, 2006. | ||
In article | View Article | ||
[45] | Gaikwad R D., and Bhagat V.S., “Multi-criteria watershed prioritizationof Kas Basin in Maharashtra (India): AHP and influence approaches,” Hydrospatial Analysis, 1(1), 41-61, 2017. | ||
In article | View Article | ||
[46] | Truong, H., and Jang, W., “Evaluating the Competition of Marine Tourism Industry Among Major Countries in Southeast Asia Using AHP Method,” American Journal of Environmental and Resource Economics,4(3), 104-109, 2019. | ||
In article | View Article | ||
[47] | Gholami, S., Assayesh, H., and Alipour-nakhi, A., “The Study of Tourism Geography in Rural Areas of Noushahr City of Mazandaran Province (Iran) - the Case of Balade Kojour Vill“, Agricultural and Natural Resources, 7(3), 341-346, 2010. | ||
In article | |||
[48] | Taylor, F. A., Hoffman, D., “Personnel evaluation with AHP,” Management Decision Ketcham, A. F., and, 679-685, 2014. | ||
In article | View Article | ||
[49] | Saaty, T. L., ”How to make a decision : The Analytic Hierarchy Process,” European Journal of Operational Research, 48, 9-26, 1990. | ||
In article | View Article | ||
[50] | Saaty, T. L., “Priority setting in complex problems,” IEEE Transactions on Engineering Management, 30(3), 140-, 1983. | ||
In article | View Article | ||
[51] | Wind, Y., and Saaty, T. L., “Marketing Applications of the Analytic Hierarchy Process,” Management Sciences, 641-657, 1980. | ||
In article | View Article | ||
[52] | Rocha, C., Antunes, C., and Catita, C., “Coastal Vulnerability Assessment Due to Sea Level Rise : The Case Study of the Atlantic Coast of Mainland Portugal,” Water(MDPI), 1-25, 2020. | ||
In article | View Article | ||
[53] | Duriyapong, F., and Nakhapakorn, K., “Coastal vulnerability assessment : a case study of Samut Sakhon coastal zone,” Songklanakarin Journal Sciences and Technology, 33(4), 469-476, 2011. | ||
In article | |||
Published with license by Science and Education Publishing, Copyright © 2021 Sanjay B. Navale, Rajendra S. Suryawanshi and Vijay S. Bhagat
This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
[1] | Ghamgosar, M., “Multicriteria Decision Making Based on Analytical Hierarchy Process (AHP) in GIS for Tourism,” Middle-East Journal of Scientific Research, 10 (4, 501-507, 2011. | ||
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[23] | Rutherford, J., Kobryn, H., and Newsome, D., “Current Issues in Tourism A case study in the evaluation of geotourism potential through geographic information systems : application in a geology-rich island tourism hotspot,” Current Issues in Tourism, 37-41, 2014. | ||
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[24] | Saaty, T.L., “A scaling method for priorities in hierarchical structures. Journal of mathematical psychology, 15(3), 234-281, 1977. | ||
In article | View Article | ||
[25] | Saaty, T.L., “Principles of the Analytic Hierarchy Process,” Expert Judgment and Expert Systems Edited by J. Mumpower et, (35)1-47, 1987. | ||
In article | View Article | ||
[26] | Suryawanshi, R. S., and Ranyewale, S. K., “Tourism Potential of Geomorphosites: A Comparative Assessment of Selected Beach Sites in Malvan Tahsil, Sindhudurg Coast of Maharashtra (India),” Transactions, 40(2), 285-292, 2018. | ||
In article | |||
[27] | Botero, C., Pereira, C., Anfuso, G., Cervantes, O., Williams, A. T., Silva, C. P., and Manjarres, A., “Recreational parameters as an assessment tool for beach quality”, Journal of Coastal Research, (70), 556-562, 2014. | ||
In article | View Article | ||
[28] | Hoang, H. T. T., Truong, Q. H., and Nguyen, A. T., “Multicriteria Evaluation of Tourism Potential in the Central Highlands of Vietnam : Combining Geographic Information System (GIS), Analytic Hierarchy Process (AHP) and Principal Component Analysis (PCA)”, Sustainability (MDPI), 1–20, 2018. | ||
In article | View Article | ||
[29] | Mamun, A. Al. and Mitra, S., “A Methodology for Assessing Tourism Potential: Case Study Murshidabad District, West Bengal, India, International Journal of Scientific and Research Publications, 2(9), 1-8, 2012. | ||
In article | |||
[30] | Mooser, A., and Anfuso, G., “Management Implications for the Most Attractive Scenic Sites along the Andalusia Coast (SW Spain),” Sustainability(MDPI), 1-26, 2018. | ||
In article | View Article | ||
[31] | Botero, C., Anfuso, G., Williams, A. T., Zielinski, S., da Silva, C. P., Cervantes, O., and Cabrera, J.A., (2013), “Reasons for beach choice: European and Caribbean perspectives,” Journal of Coastal Research, 65(1), 2013. | ||
In article | View Article | ||
[32] | Cristiano, C., Carla, L., and Anfuso, G.,”Coastal scenic evaluation at Santa Catarina ( Brazil ): Implications for coastal management Coastal scenic evaluation at Santa”, Ocean & Coastal Management · 146–157,2018. | ||
In article | View Article | ||
[33] | Lin, S., Lu, J., and Fan, Y., “An Ecological Early Warning Indicator System for Environmental Protection of Scenic Areas,” Sustainability(MDPI), 1-15,2019. | ||
In article | View Article | ||
[34] | Kumar, T. S., Mahendra, R. S., Nayak, S., Radhakrishnan, K., Sahu, K. C., Kumar, T. S., and Sahu, K. C., “Coastal Vulnerability Assessment for Orissa State, East Coast of India Coastal Vulnerability Assessment for Orissa State, East Coast of India”, Journal of Coastal Research, (263), 523-534, 2010. | ||
In article | View Article | ||
[35] | Duke, J. M., and Aull-hyde, R.,”Identifying public preferences for land preservation using the analytic hierarchy process”, Ecological Economics, 42, 131–145, 2002. | ||
In article | View Article | ||
[36] | Hajra, R., “Formulation of Methodological Approach for Sustainable Tourism Using “STC” Criteria : A Case Study of Sagar Island, India,” International Journal Of Innovative Research & Development, 3(1), 305-309, 2016. | ||
In article | |||
[37] | Bozic, S., Vujicic, M., & Kennell, J., “Sun, Sea and Shrines : Application of Analytic Hierarchy Process (AHP) to Assess the Attractiveness of Six Cultural Heritage Sites in Phuket (Thailand),” Geographica Pannonica, 22(2), 121-138, 2018. | ||
In article | View Article | ||
[38] | Pareta, L., “Remote Sensing And Gis Based Site Suitability Analysis For Tourism Development,” International Journal of Advanced Research in Engineering and Applied Sciences, 2(5), 43-58, 2013. | ||
In article | |||
[39] | Wanyonyi, J. W., Imwati, A., and Boitt, M., “GIS In Analysis of potential Sites For Ecotourism – A Case Study of Kwale County,” Journal of Environmental Science, Toxicology and Food Technology, 10(10), 43-49, 2016. | ||
In article | View Article | ||
[40] | Nobre, A. M., “Scientific approaches to address challenges in coastal management, “Marine Ecology Progress Series, 434(1), 279-289, 2011. | ||
In article | View Article | ||
[41] | Bagdanavi, I., Kelp, L., Galinien, J., and Soomere, T., ”Index based multi-criteria approach to Coastal risk assessment,’’ Journal of Coastal Conservation, 23,785-800, 2019. | ||
In article | View Article | ||
[42] | Pranzini, E., “Ocean & Coastal Management Evaluation of the scenic value of 100 beaches in Cuba : Implications for coastal tourism management”, Ocean and Coastal Management, 142, 173-185, 2017. | ||
In article | View Article | ||
[43] | Williams, A. T., Micallef, A., and Anfuso, G., “Andalusia, Spain : An Assessment of Coastal Scenery ,” Landscape Research, 37-41, 2012. | ||
In article | View Article | ||
[44] | Chen, C., “Applying the Analytical Hierarchy Process (AHP) Approach to Convention Site Selection” Journal of Travel Research, 45, 167-174, 2006. | ||
In article | View Article | ||
[45] | Gaikwad R D., and Bhagat V.S., “Multi-criteria watershed prioritizationof Kas Basin in Maharashtra (India): AHP and influence approaches,” Hydrospatial Analysis, 1(1), 41-61, 2017. | ||
In article | View Article | ||
[46] | Truong, H., and Jang, W., “Evaluating the Competition of Marine Tourism Industry Among Major Countries in Southeast Asia Using AHP Method,” American Journal of Environmental and Resource Economics,4(3), 104-109, 2019. | ||
In article | View Article | ||
[47] | Gholami, S., Assayesh, H., and Alipour-nakhi, A., “The Study of Tourism Geography in Rural Areas of Noushahr City of Mazandaran Province (Iran) - the Case of Balade Kojour Vill“, Agricultural and Natural Resources, 7(3), 341-346, 2010. | ||
In article | |||
[48] | Taylor, F. A., Hoffman, D., “Personnel evaluation with AHP,” Management Decision Ketcham, A. F., and, 679-685, 2014. | ||
In article | View Article | ||
[49] | Saaty, T. L., ”How to make a decision : The Analytic Hierarchy Process,” European Journal of Operational Research, 48, 9-26, 1990. | ||
In article | View Article | ||
[50] | Saaty, T. L., “Priority setting in complex problems,” IEEE Transactions on Engineering Management, 30(3), 140-, 1983. | ||
In article | View Article | ||
[51] | Wind, Y., and Saaty, T. L., “Marketing Applications of the Analytic Hierarchy Process,” Management Sciences, 641-657, 1980. | ||
In article | View Article | ||
[52] | Rocha, C., Antunes, C., and Catita, C., “Coastal Vulnerability Assessment Due to Sea Level Rise : The Case Study of the Atlantic Coast of Mainland Portugal,” Water(MDPI), 1-25, 2020. | ||
In article | View Article | ||
[53] | Duriyapong, F., and Nakhapakorn, K., “Coastal vulnerability assessment : a case study of Samut Sakhon coastal zone,” Songklanakarin Journal Sciences and Technology, 33(4), 469-476, 2011. | ||
In article | |||