Research Article
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Year 2023, Volume: 10 Issue: 4, 39 - 47, 26.12.2023

Foram Jadeja Kauresh Vachhrajani Manik H. Kalubarme

https://doi.org/10.30897/ijegeo.1344777

Abstract

References

  • Aburas, M. M., Abdullah, S. H., Ramli, M. F., Ashaari, Z. H. (2015). Measuring Land Cover Change in Seremban, Malaysia Using NDVI Index. Procedia Environmental Sciences, 30, 238–243. https://doi.org/10.1016/j.proenv.2015.10.043
  • Anand, A., Singh, S. K., Kanga, S. (2018). Estimating the change in forest cover density and predicting NDVI for west Singhbhum using linear regression. Int. J. Environ. Rehabil. Conserv, 9, 193-203. https://doi.org/10.31786/09756272.18.9.1.125
  • Artis, D. A., Carnahan, W. H. (1982). Survey of emissivity variability in thermography of urban areas. Remote sensing of Environment, 12(4), 313-329.
  • Avdan, U., Jovanovska, G. (2016). Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. Journal of sensors, 2016.
  • Bendib, A., Dridi, H., Kalla, M. I. (2017). Contribution of Landsat 8 data for the estimation of land surface temperature in Batna city, Eastern Algeria. Geocarto International, 32(5), 503–513. https://doi.org/10.1080/10106049.2016.1156167
  • Chandrasekar, K. (2016). Geo-spatial meteorological products for Agricultural drought assessment. NRSC User Interaction Meet- PPT.
  • Entezari, A., Amir Ahmadi, A., Aliabadi, K., Khosravian, M., Ebrahimi, M. (2016). Monitoring Land Surface Temperature and Evaluating Change Detection Land Use (Case Study: Parishan Lake Basin). Hydrogeomorphology, 2(8), 113-139.
  • Esetlili, M. T. , Bektas Balcik, F. , Balik Sanli, F. , Kalkan, K. , Ustuner, M. , Goksel, C. , Gazioğlu, C. Kurucu, Y. (2018). Comparison of Object and Pixel-Based Classifications For Mapping Crops Using Rapideye Imagery: A Case Study Of Menemen Plain, Turkey. International Journal of Environment and Geoinformatics, 5(2), 231-243. https://doi.org/10 30897/ijegeo.442002
  • Faisal, A. Al, Kafy, A. Al., Al Rakib, A., Akter, K. S., Jahir, D. M. A., Sikdar, M. S., Ashrafi, T. J., Mallik, S., Rahman, M. M. (2021). Assessing and predicting land use/land cover, land surface temperature and urban thermal field variance index using Landsat imagery for Dhaka Metropolitan area. Environmental Challenges, 4, 100192. https://doi.org/10.1016/j.envc.2021.100192
  • Forkuo, E. K., Frimpong, A. (2012). Analysis of forest cover change detection. International journal of remote sensing applications, 2(4), 82-92. https://www.researchgate.net/publication/269222395
  • Khorrami, B., Gunduz, O., Patel, N., Ghouzlane, S., Najjar, M. (2019). Land surface temperature anomalies in response to changes in forest cover. International Journal of Engineering and Geosciences, 4(3), 149-156. https://doi.org/10.26833/ijeg.549944
  • Liu, L., Zhang, Y. (2011). Urban heat island analysis using the Landsat TM data and ASTER data: A case study in Hong Kong. Remote sensing, 3(7), 1535-1552. https://doi.org/10.3390/rs3071535
  • Malik, M. M., Tali, J. A., Nusrath, A. (2017). Spatio-Temporal Changes of Forest Cover in Baramulla District. Journal of Remote Sensing & GIS, 8(3).
  • Markham, B. L., Barker, J. L. (1985). Spectral characterization of the Landsat Thematic Mapper sensors. International Journal of Remote Sensing, 6(5), 697-716.
  • Naim, M. N. H., Kafy, A. A. (2021). Assessment of urban thermal field variance index and defining the relationship between land cover and surface temperature in Chattogram city: A remote sensing and statistical approach. Environmental Challenges, 4(April), 100107.
  • Nath, B. (2014). Quantitative Assessment of Forest Cover Change of a Part of Bandarban Hill Tracts Using NDVI Techniques. Journal of Geosciences and Geomatics, 2(1), 21–27. https://doi.org/10.12691/jgg-2-1-4
  • Omar, P. J., Kumar, V. (2021). Land surface temperature retrieval from TIRS data and its relationship with land surface indices. Arabian Journal of Geosciences, 14(18), 1-14.
  • Peng, S. S., Piao, S., Zeng, Z., Ciais, P., Zhou, L., Li, L. Z., ... Zeng, H. (2014). Afforestation in China cools local land surface temperature. Proceedings of the National Academy of Sciences, 111(8), 2915-2919.
  • Renard, F., Alonso, L., Fitts, Y., Hadjiosif, A., Comby, J. (2019). Evaluation of the effect of urban redevelopment on surface urban heat islands. Remote Sensing, 11(3). https://doi.org/10.3390/rs11030299 Rouse Jr, J. W., Haas, R. H., Schell, J. A., Deering, D. W. (1973). Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation (No. NASA-CR-132982).
  • Sarkar, S., Bandyopadhyay, J., Giri, S. (2021). Spatio-Temporal analysis of forest conversion in contrasting LULC and vegetation extraction using spatial information southern part of Jangalmahal, West Bengal, India. Int J Appl Res 2021;7(4):247-254. DOI: 10.22271/allresearch.2021.v7.i4d.8501
  • Sinha, S., Pandey, P. C., Sharma, L. K., Nathawat, M. S., Kumar, P., Kanga, S. (2014). Remote estimation of land surface temperature for different LULC features of a moist deciduous tropical forest region. Remote sensing applications in environmental research, 57-68.
  • Sutariya, S., Hirapara, A., Meherbanali, M., Tiwari, M., Sıngh, V. Kalubarme, M. (2021). Soil Moisture Estimation using Sentinel-1 SAR Data and Land Surface Temperature in Panchmahal District, Gujarat State. International Journal of Environment and Geoinformatics, 8(1), 65-77. https://doi.org/10.30897/ijegeo.777434
  • Tarpley, J. D., Schneider, S. R., Money, R. L. (1984). Global vegetation indices from the NOAA-7 meteorological satellite. Journal of Climate and Applied Meteorology, 491-494.
  • Tepanosyan, G., Muradyan, V., Hovsepyan, A., Pinigin, G., Medvedev, A., Asmaryan, S. (2021). Studying spatial-temporal changes and relationship of land cover and surface Urban Heat Island derived through remote sensing in Yerevan, Armenia. Building and Environment, 187, 107390.
  • van Leeuwen, T. T., Frank, A. J., Jin, Y., Smyth, P., Goulden, M. L., van der Werf, G. R., Randerson, J. T. (2011). Optimal use of land surface temperature data to detect changes in tropical forest cover. Journal of Geophysical Research: Biogeosciences, 116(G2). https://doi.org/10.1029/2010JG001488
  • Weng, Q., Lu, D., Schubring, J. (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote sensing of Environment, 89(4), 467-483.
  • Yismaw, A., Gedif, B., Addisu, S., Zewudu, F. (2014). Forest cover change detection using remote sensing and GIS in Banja district, Amhara region, Ethiopia. International Journal of Environmental Monitoring and Analysis, 2(6), 354.

Assessment of Spatio-Temporal changes of Forest Cover using Remote Sensing techniques in Pavagadh Region, Gujarat State

Year 2023, Volume: 10 Issue: 4, 39 - 47, 26.12.2023

Foram Jadeja Kauresh Vachhrajani Manik H. Kalubarme

https://doi.org/10.30897/ijegeo.1344777

Abstract

For effective forest management, it is essential to consider forest patterns and periodic changes in forest cover. Several spectral vegetation indices derived from multi-temporal Remote Sensing data are useful to track the changes over time. The major objective of this study was to monitor the changes in forest cover during the past three decades in the Pavagadh area of Panchmahal district, Gujarat State, India. Various indices like Normalized Difference Vegetation Index (NDVI), Land Surface Temperature, and Urban Thermal Field Variance Index (UTFVI) with the Ecological Evaluation Index were analyzed for assessment of Spatio-temporal changes in the forest cover. Multi-temporal Landsat-TM and OLI sensor data for the years 1991, 2001, 2011, and 2021 were utilized covering the study area. The results indicated that the total forest cover area has gradually increased from 1991 to 2021 and the total forest area has doubled during this period of 30 years. The comparative study of NDVI and Land Surface Temperature map brings out a significant fact that in the areas where moderate and dense forest cover is present, the Land Surface Temperature was lower as compared to areas with poor vegetation cover. This indicates that there is an inverse relationship between forest cover distribution and Land Surface Temperature. However, the Ecological evaluation index shows that the forest vegetation quality is gradually improving to normal conditions with the excellent category and UTFVI value (< 0) in reference to the year 1991.

Keywords

Forest cover change Land Surface Temperature NDVI UTFVI Ecological Evaluation Index

References

  • Aburas, M. M., Abdullah, S. H., Ramli, M. F., Ashaari, Z. H. (2015). Measuring Land Cover Change in Seremban, Malaysia Using NDVI Index. Procedia Environmental Sciences, 30, 238–243. https://doi.org/10.1016/j.proenv.2015.10.043
  • Anand, A., Singh, S. K., Kanga, S. (2018). Estimating the change in forest cover density and predicting NDVI for west Singhbhum using linear regression. Int. J. Environ. Rehabil. Conserv, 9, 193-203. https://doi.org/10.31786/09756272.18.9.1.125
  • Artis, D. A., Carnahan, W. H. (1982). Survey of emissivity variability in thermography of urban areas. Remote sensing of Environment, 12(4), 313-329.
  • Avdan, U., Jovanovska, G. (2016). Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. Journal of sensors, 2016.
  • Bendib, A., Dridi, H., Kalla, M. I. (2017). Contribution of Landsat 8 data for the estimation of land surface temperature in Batna city, Eastern Algeria. Geocarto International, 32(5), 503–513. https://doi.org/10.1080/10106049.2016.1156167
  • Chandrasekar, K. (2016). Geo-spatial meteorological products for Agricultural drought assessment. NRSC User Interaction Meet- PPT.
  • Entezari, A., Amir Ahmadi, A., Aliabadi, K., Khosravian, M., Ebrahimi, M. (2016). Monitoring Land Surface Temperature and Evaluating Change Detection Land Use (Case Study: Parishan Lake Basin). Hydrogeomorphology, 2(8), 113-139.
  • Esetlili, M. T. , Bektas Balcik, F. , Balik Sanli, F. , Kalkan, K. , Ustuner, M. , Goksel, C. , Gazioğlu, C. Kurucu, Y. (2018). Comparison of Object and Pixel-Based Classifications For Mapping Crops Using Rapideye Imagery: A Case Study Of Menemen Plain, Turkey. International Journal of Environment and Geoinformatics, 5(2), 231-243. https://doi.org/10 30897/ijegeo.442002
  • Faisal, A. Al, Kafy, A. Al., Al Rakib, A., Akter, K. S., Jahir, D. M. A., Sikdar, M. S., Ashrafi, T. J., Mallik, S., Rahman, M. M. (2021). Assessing and predicting land use/land cover, land surface temperature and urban thermal field variance index using Landsat imagery for Dhaka Metropolitan area. Environmental Challenges, 4, 100192. https://doi.org/10.1016/j.envc.2021.100192
  • Forkuo, E. K., Frimpong, A. (2012). Analysis of forest cover change detection. International journal of remote sensing applications, 2(4), 82-92. https://www.researchgate.net/publication/269222395
  • Khorrami, B., Gunduz, O., Patel, N., Ghouzlane, S., Najjar, M. (2019). Land surface temperature anomalies in response to changes in forest cover. International Journal of Engineering and Geosciences, 4(3), 149-156. https://doi.org/10.26833/ijeg.549944
  • Liu, L., Zhang, Y. (2011). Urban heat island analysis using the Landsat TM data and ASTER data: A case study in Hong Kong. Remote sensing, 3(7), 1535-1552. https://doi.org/10.3390/rs3071535
  • Malik, M. M., Tali, J. A., Nusrath, A. (2017). Spatio-Temporal Changes of Forest Cover in Baramulla District. Journal of Remote Sensing & GIS, 8(3).
  • Markham, B. L., Barker, J. L. (1985). Spectral characterization of the Landsat Thematic Mapper sensors. International Journal of Remote Sensing, 6(5), 697-716.
  • Naim, M. N. H., Kafy, A. A. (2021). Assessment of urban thermal field variance index and defining the relationship between land cover and surface temperature in Chattogram city: A remote sensing and statistical approach. Environmental Challenges, 4(April), 100107.
  • Nath, B. (2014). Quantitative Assessment of Forest Cover Change of a Part of Bandarban Hill Tracts Using NDVI Techniques. Journal of Geosciences and Geomatics, 2(1), 21–27. https://doi.org/10.12691/jgg-2-1-4
  • Omar, P. J., Kumar, V. (2021). Land surface temperature retrieval from TIRS data and its relationship with land surface indices. Arabian Journal of Geosciences, 14(18), 1-14.
  • Peng, S. S., Piao, S., Zeng, Z., Ciais, P., Zhou, L., Li, L. Z., ... Zeng, H. (2014). Afforestation in China cools local land surface temperature. Proceedings of the National Academy of Sciences, 111(8), 2915-2919.
  • Renard, F., Alonso, L., Fitts, Y., Hadjiosif, A., Comby, J. (2019). Evaluation of the effect of urban redevelopment on surface urban heat islands. Remote Sensing, 11(3). https://doi.org/10.3390/rs11030299 Rouse Jr, J. W., Haas, R. H., Schell, J. A., Deering, D. W. (1973). Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation (No. NASA-CR-132982).
  • Sarkar, S., Bandyopadhyay, J., Giri, S. (2021). Spatio-Temporal analysis of forest conversion in contrasting LULC and vegetation extraction using spatial information southern part of Jangalmahal, West Bengal, India. Int J Appl Res 2021;7(4):247-254. DOI: 10.22271/allresearch.2021.v7.i4d.8501
  • Sinha, S., Pandey, P. C., Sharma, L. K., Nathawat, M. S., Kumar, P., Kanga, S. (2014). Remote estimation of land surface temperature for different LULC features of a moist deciduous tropical forest region. Remote sensing applications in environmental research, 57-68.
  • Sutariya, S., Hirapara, A., Meherbanali, M., Tiwari, M., Sıngh, V. Kalubarme, M. (2021). Soil Moisture Estimation using Sentinel-1 SAR Data and Land Surface Temperature in Panchmahal District, Gujarat State. International Journal of Environment and Geoinformatics, 8(1), 65-77. https://doi.org/10.30897/ijegeo.777434
  • Tarpley, J. D., Schneider, S. R., Money, R. L. (1984). Global vegetation indices from the NOAA-7 meteorological satellite. Journal of Climate and Applied Meteorology, 491-494.
  • Tepanosyan, G., Muradyan, V., Hovsepyan, A., Pinigin, G., Medvedev, A., Asmaryan, S. (2021). Studying spatial-temporal changes and relationship of land cover and surface Urban Heat Island derived through remote sensing in Yerevan, Armenia. Building and Environment, 187, 107390.
  • van Leeuwen, T. T., Frank, A. J., Jin, Y., Smyth, P., Goulden, M. L., van der Werf, G. R., Randerson, J. T. (2011). Optimal use of land surface temperature data to detect changes in tropical forest cover. Journal of Geophysical Research: Biogeosciences, 116(G2). https://doi.org/10.1029/2010JG001488
  • Weng, Q., Lu, D., Schubring, J. (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote sensing of Environment, 89(4), 467-483.
  • Yismaw, A., Gedif, B., Addisu, S., Zewudu, F. (2014). Forest cover change detection using remote sensing and GIS in Banja district, Amhara region, Ethiopia. International Journal of Environmental Monitoring and Analysis, 2(6), 354.
There are 27 citations in total.

Details

Primary Language English
Subjects Physical Geography and Environmental Geology (Other)
Journal Section Research Articles
Authors

Foram Jadeja 0000-0002-6609-8560

Kauresh Vachhrajani This is me 0000-0002-6840-4752

Manik H. Kalubarme This is me 0000-0002-0977-7671

Early Pub Date November 25, 2023
Publication Date December 26, 2023
Published in Issue Year 2023 Volume: 10 Issue: 4

Cite

APA Jadeja, F., Vachhrajani, K., & H. Kalubarme, M. (2023). Assessment of Spatio-Temporal changes of Forest Cover using Remote Sensing techniques in Pavagadh Region, Gujarat State. International Journal of Environment and Geoinformatics, 10(4), 39-47. https://doi.org/10.30897/ijegeo.1344777

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