Monitoring zmian użytkowania i pokrycia terenu oraz ich wpływu na parametry klimatyczne przy użyciu teledetekcji i GIS: studium przypadku w Dolinie Dolny Dibang, Arunachal Pradesh, Indie
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RIS BIB ENDNOTEData publikacji: 19.11.2024
Geoinformatica Polonica, 2024, Vol. 23 (2024), s. 59 - 75
https://doi.org/10.4467/21995923GP.24.005.20472Autorzy
Monitoring Land Use Land Cover Change and Its Impact on Climatic Parameters Using Remote Sensing and GIS: A Case Study of Lower Dibang Valley, Arunachal Pradesh, India
The changes in the socio-dynamics and the pattern of occurrences of natural hazards both at larger and regional scales have been influenced by the alterations in the Land use land cover change (LULCC) modifications. The LULCC of Lower Dibang valley of Arunachal Pradesh is investigated using contemporary tools of Remote sensing and Geographic Information system. A temporal analysis is done for the years viz, 2009, 2014, and 2021 using USGS Landsat satellite images. To determine the change in LULCC support vector machine a supervised classification method is used and is cross checked with Google Earth points for achieving accuracy and the temporal analysis is done by comparing each images pixel by pixel. The findings show that between 2009 and 2021, the region had significant changes in land cover in the following areas: forest area (–8%), rangeland/scrubland (–6%), barren land/bare soil/open rocks (–1%), agricultural (-2%), and water body/river (–1%). It was observed that lowland and higher altitude regions saw the majority of the LULCC alterations. In the seven tehsils of the Lower Dibang Valley of Arunachal Pradesh, which are located at varying elevations and slopes, the effects of LULC changes on climatic and environmental variables such as latent/sensible heat flow, temperature, precipitation, and specific humidity have been evaluated independently. This research paper’s methodology and results section includes a full explanation of the procedures followed and the outcomes.
The authors are thankful to all the reviewers for their valuable comments and suggestions which have helped for the overall improvement of the quality of the research paper.
1. Rawart, J.S., Biswas, V., Kumar, M. Changes in land use/cover using geospatial techniques: A case study of Ramnagar town area, district Nainital, Uttarakhand, India. Egypt J Remote Sens Space Sci., 2013; volume 16, pp. 111–117.
2. Kumar, M., Arup, D., Richa, S., Supratik, S. Change detection analysis using multi-temporal satellite data of Poba reserve forest, Assam and Arunachal Pradesh. Int. J. GeomatGeosci. 2014; volume 4, pp. 517–527.
3. Lambin, E.F., Turner, B.L., Geist, H.J., Agbola, S.M., Angelsen, A., Bruce, J.W., Coomes, O.T., Dirzo, R., Fischer, G., Folke, C. The causes of land-use and land-cover change: Moving beyond the myths. Glob. Environ Chang, 2011, volume 11, pp. 261–269.
4. Al-Kafy, A., Saha, M., Al-Faisal, A., Rahaman, Z., Rahman, M.T., Liu, D., Fatteh, M.A., Rakib, A.A., Al-Doubari, A.E., Rahaman, S.N., Hasan, M.Z., Ahasan, M.A.K. Predicting the impact of land use/land cover changes on seasonal urban thermal characteristics using maching learning algorithms. Build Environ (https://doi.org/10.1016/j.buildenv.2022.109066), 2022; volume 217.
5. Ritse, V., Basumatary, H., Kulnu, A.S., Dutta, G., Phukan, M.M., Hazarika, N. Monitoring land use land cover changes in the Eastern Himalayan landscape of Nagaland, Northeast India. Environ Monit Assess. 2020; volume 192(11), pp. 1–17.
6. Emiru, B., Ashfare, H., Fenta, A.A., Hishe, H., Gebremedhin, M.A., Wahed, H.G., Solomon, N. Land use land cover changes along topographic gradients in Hugumburda national forest priority area, Northern Ethiopia. Remote SensApplSoc Environ, 2018, volume 13, pp. 61–6.
7. Sankhala, S., Singh, B. Evaluation of urban sprawl and land use/land cover change using remote sensing and GIS techniques: A case study of Jaipur City, India. Int. J. Emerg. TechnolAdvEng. 2014; volume 4, pp. 66–72.
8. Hegazy, I.R., Mosbeh, R.K. Monitoring urban growth and land use change detection with GIS and remote sensing technique in Daqahlia governorate Egypt. Int. J. Sustain Built Environ, 2015; volume 4, pp. 117–124.
9. Chomitz, K.M., Kamari, K. The domestic benefits of tropical forests. World Bank Res Obs. 1998; volume 13, pp. 13–35.
10. Bruijnzeel, L.A. Hydrological functions of tropical forests: Not seeing the soil for the trees? AgricEcosyst Environ. 2004, volume 104, pp. 185–228.
11. Cheruto, M.C., Kauti, M.K., Kisangau, P.D., Kariuki, P. Assessment of land use and land cover change using GIS and remote sensing techniques: A case study of Makueni County, Kenya. J Remote Sens GIS. 2016; volume 5, pp. 175.
12. Al-Kafy, A., Al-Faisal, A., Rakib, A.A., Fattah, M.A., Rahaman, Z.A., Sattar, G.S. Impact of vegetation cover loss on surface temperature and carbon emission in a fastest growing cities, Cumilla, Bangladesh. Build Environ (https://doi.org/j.buildenv.2021.108573). 2022b; volume 208.
13. Minale, A.S. Retrospective analysis of land cover and use dynamics in GilgelAbbay Watershed using GIS and remote sensing technique, Northwestern Ethiopia. Int. J. Geosci. 2013, volume 4, pp. 1003–1008.
14. Meshesha, T.W., Tripathi, S.K., Khare, D.M. Analyses of land use and land cover change dynamics using GIS and remote sensing during 1984 and 2015 in the Beressa Watershed Northern Central Highland of Ethiopia. Model Earth Syst. Environ. 2016; volume 2, pp. 1–12.
15. Adeel, M. Methodology for identifying urban growth potential using land use and population data: A case study of Islamabad Zone IV. Procedia Environ Sci. 2010; volume 2, pp. 32–41.
16. Rawart, J.S., Kumar, M. Monitoring land use/cover change using remote sensing and GIS techniques: A case of Hawallbagh block, district Almora, Utterkland, India. Egypt J. Remote Sens Space Sci. 2015, volume 18, pp. 77–84.
17. Weng, Q. A remote sensing-GIS evaluation of urban expansion and its impacts on the temperature in the Zhujiang Delta, China. Int. J. Remote Sens. 2011; volume 22, 1999–2014.
18. Hassan, Z., Rabia, S., Sheikh, A., Amir, H.M., Neelam, A., Amna, B., Summra, E. Dynamics of land use and land cover change (LULCC) using geospatial techniques: A case study of Islamabad Pakistan. Springer Plus. 2016; volume 5, pp. 812.
19. Liang, S., Fang, H., Morisette, J.T., Chen, M., Shuey, C.J., Walthall, C.L., Daughtry, C.S. Atmospheric correction of Landsat ETM+ Land surface imagery. II. Validation and applications. IEEE Trans Geosci Remote Sens. 2022; volume 4, pp. 2736–2746.
20. Ayele, G.T., Demessie, S.S., Mengistu, K.T., Tilahun, S.A., Melesse, A.M. Multitemporal land use/land cover change detection for the Batena Watershed, Rift Valley Lakes Basin, Ethiopia. In: Landscape Dynamics, Soils and Hydrological Processes in Varied Climates; Springer: Berlin, Germany, 2016; pp. 51–72.
21. Lambin, E.F., Geist, H.J. Global land-use and land-cover change: What have we learned so far. Glob Chang Newsl. 2001; volume 46, pp. 27–30.
22. Woldeamlak, B. Land covers dynamics since the 1950s in Chemoga Watershed, Blue Nile Basin, Ethiopia. Mt Res Dev. 2002; volume 22, pp. 263–269.
23. Manandhar, R., Odeh, I.O., Ancev, T. Improving the accuracy of land use and land cover classification of Landsat data using post-classification enhancement. Remote Sensing. 2009; volume 1(3), pp. 330–344.
24. Alshari, E.A., Gawali, B.W. Development of classification system for LULC using remote sensing and GIS. Global Transitions Proceedings. 2021, volume 2(1), pp. 8–17.
25. Negi, V.S., Pathalk, R., Rawal, R.S., Bhatta, I.D., Sharma, S. Long term ecological monitoring of forest ecosystems in Indian Himalayan region: Criteria and indicator approach. Ecol Indic. 2019; volume 102, pp. 374–381.
26. Nath, A.J., Kumar, R., Devi, N.B., Rocky, P., Giri, K., Sahoo, U.K., Bajpai, R.K., Sahu, N., Pandey, R. Agroforestry land suitability analysis in the eastern Himalayan region. Environ Chall (doi: 10.1016/j.envc.2021.100199), 2021.
27. Singh, S.L., Sahoo, U.K., Gogoi, A., Kenye, A. Effect of land use changes on carbon stock dynamics in major land use sectors of Mizoram, Northeast India. J Environ Prot. 2018; volume 9, pp. 1262–1285.
28. Sahoo, U.K., Singh, S.L., Gogoi, A., Kenye, A., Sahoo, S.S. Active and passive soil organic carbon pools as affected by different land use types in Mizoram, Northeast India. PLoS One. 2019; volume 14(7).
29. Ahirwal, J., Nath, A., Brahma, B., Deb, S., Sahoo, U.K., Nath, A.J. Pattern and driving factors of biomass carbon and soil organic carbon stock in the Indian Himalayan region. Sci. Total Environ. 2021; volume 770.
30. Thong, P., Pebam, R., Sahoo, U.K. A geospatial approach to understand the dynamics of shifting cultivation in Champhai district of Mizoram. North-east India. J. Indian Soc Remote Sensdoi, 2018.
31. Thong, P., Sahoo, U.K., Pebam, R., Thangjam, U. Spatial and temporal dynamices of shifting cultivation in Manipur, Northeast India based on time-series satellite data. Remote Sens Appl Soc Environ. 2019a; volume 14, pp. 126–137.
32. Thong, P., Sahoo, U.K., Pebam, R., Thangjam, U. Changing trends of shifting cultivations and its drivers in Champhai, Northeast India. Ind. J. Hill Farm. 2019b; volume 32(1), pp. 1–4.
33. Gogoi, A., Sahoo, U.K. Impact of anthropogenic disturbances on species diversity and vegetation structure of a lowland tropical rainforest of eastern Himalaya, India. J. Mount Sci. 2018; volume 15(11), pp. 2453–2465.
34. CBD Conference of Parties to Convention on Biological Diversity. Fourteenth Meeting Item 21 of the Provisional Agenda. Sharm EI-Sheikh, Egypt, November 2018, pp. 17–29.
35. Gogoi, A., Ahirwal,, J., Sahoo, U.K. Plant biodiversity and carbon sequestration potential of the planted forest in Brahmaputra flood plains. J. Environ Manage (10.1016/j.envman.2020.111671), 2021.
36. Deka, J., Tripathi, O.P., Khan, M.L., Srivastava, V.K. Study on land-use and land-cover change dynamics in eastern Arunachal Pradesh, NE India using remote sensing and GIS. Trop Ecol. 2019; volume 60, pp. 199–208.
37. Areendran, G., Raj, K., Majumdar, S., Joshi, R., Puri, K. Land use land cover mapping of Mouling National Park in Arunachal Pradesh, India using geospatial tools. International J. Science Environment. 2018; volume 7(2), pp. 696–705.
38. Sahoo, U.K., Tripathi, O.P., Nath, A.J., Deb, S., Das, D.J., Gupta, A., Devi, N.B., Chaturvedi, S.S., Singh, S.L., Kumar, A., Tiwari, B.K. Quantifying tree diversity, carbon stocks and sequestration potential for diverse land-uses in northeast India. Front Env. Sci. (https://doi.org/10.3389/fenvs.2021.724950), 2021.
39. Bordoloi, R., Das, B., Tripathi, O.P., Sahoo, U.K., Nath, A.J., Deb, S., Das, D.J., Gupta, A., Devi, N.B., Chaturvedi, S.S., Tiwari, B.K., Paul, A., Tajo, L. Satellite based integrated approaches to modeling spatial carbon stock and carbon sequestration potential of different land uses of northeast India. Environ Sust Indic (https://doi.org/100166, https://doi.org/10.1016/j.indic.2021.100166). 2022, volume 13:
40. Deb, D., Jamatia, M., Debbarma, J., Ahirwal, J., Deb, S., Sahoo, U.K. Evaluating the role of community-managed forest in carbon sequestration and climate change mitigation of Tripura, India. Air Water Soil Pollut (https://doi.org/10.1007/s11270-021-05133-z). 2021, volume 232, pp. 166.
41. Congallton, R.G., Green, K. Assessing accuracy of remote sensed data. Remote Sensing Environment. 1999, volume 37, pp. 35–46.
42. Sari, H., Ozsahin, E. Spatiotemporal change in the LULC (Landuse/Landcover) characteristics of Tekirdag Province based on the CORINE (Thrace, Türkiye). Fresenius Environ Bull. 2016, volume 25, pp. 4694–4707.
43. Ikiel, C., Dutucu, A.A., Ustaoglu, B., Kilic, D.E. Land use and land cover (LULC) classifcation using Spot-5 image in the Adapazari Plain and its surroundings, Türkiye. TOJSAT Online J. Sci. Technol. 2012; volume 2, pp. 37–42.
44. Yilmaz, Y.A., Sen, O.L., Turuncoglu, U.U. Modeling the hydroclimatic efects of local land use and land cover changes on the water budget in the upper Euphrates – Tigris basin. J. Hydrol. (https://doi.org/10.1016/j.jhydrol.2019.06.074). 2019; volume 576, pp. 596–609.
45. Xie, Q., Sun, Q. Monitoring the spatial variation of aerosol optical depth and its correlation with land use/land cover in Wuhan, China: a perspective of urban planning. Int. J. Environ Res Public Health (https://doi.org/10.3390/ijerph18031132). 2021, volume 18, pp. 1–18.
46. Kharol, S.K., Kaskaoutis, D.G., Badarinath, K.V.S. Influence of land use/land cover (LULC) changes on atmospheric dynamics over the arid region of Rajasthan state, India. J. Arid Environ (https://doi.org/10.1016/j.jaridenv.2012.09.006). 2013, volume 88, pp. 90–101.
47. Liou, Y.A., Kar, S.K. Evapotranspiration estimation with remote sensing and various surface energy balance algorithms-a review. Energies (https://doi.org/10.3390/en7052821). 2014; volume 7, pp. 2821–2849.
48. Xie, Q., Sun, Q. Monitoring the spatial variation of aerosol optical depth and its correlation with land use/land cover in Wuhan, China: a perspective of urban planning. Int. J. Environ Res Public Health (https://doi.org/10.3390/ijerph18031132). 2021; volume 18, pp. 1–18.
49. Achugbu, I.C., Olufayo, A.A., Balogun, I.A. Modeling the spatiotemporal response of dew point temperature, air temperaturę and rainfall to land use land cover change over West Africa. Model Earth Syst. Environ (https://doi.org/10.1007/s40808-021-01094-8). 2022; volume 8, pp. 173–198.
50. Zadbagher, E., Becek, K., Berberoglu, S. Modeling land use/land cover change using remote sensing and geographic information systems: case study of the Seyhan Basin, Türkiye. Environ Monit Assess (https://doi.org/10.1007/ s10661-018-6877-y). 2018; volume 190, pp. 494.
51. Karimi, P., Bastiaanssen, W.G.M. Spatial evapotranspiration, rainfall and land use data in water accounting – part 1: review of the accuracy of the remote sensing data. Hydrol. Earth Syst. Sci. (https://doi.org/10.5194/hess-19-507-2015). 2015; volume 19, pp. 507–532.
52. Zhang, Y., Balzter, H., Wu, X. Spatial-temporal patterns of urban anthropogenic heat discharge in Fuzhou, China, observed from sensible heat fux using Landsat TM/ETM+ data. Int. J. Remote Sens (https://doi.org/10.1080/01431161.2012.718465). 2013; volume 34, pp. 1459–1477.
53. Wang, X.G., Wang, W., Huang, D., Yong, B., Chen, X. Modifying SEBAL model based on the trapezoidal relationship between land surface temperature and vegetation index for actual evapotranspiration estimation. Remote Sens (https://doi.org/10.3390/rs60x000x). 2014; volume 6, pp. 5909–5937.
Informacje: Geoinformatica Polonica, 2024, Vol. 23 (2024), s. 59 - 75
Typ artykułu: Oryginalny artykuł naukowy
Tytuły:
Dr. M. S. Sheshgiri College of Engineering and Technology
Indie
Sreenidhi Institute of Science and Technology
Hyderabad Telangana-501301, Indie
Mizoram University
Indie
Capacity Building Commission, DOP&T
Indie
Mizoram University
Indie
Biodiversity Research Centre,
Mizoram University
Indie
Publikacja: 19.11.2024
Status artykułu: Otwarte
Licencja: CC BY
Udział procentowy autorów:
Informacje o konflikcie interesów:
Korekty artykułu:
-Języki publikacji:
Angielski