Assessment of the success of canopy cover revegetation of former coal mine lands with Forest Canopy Density (FCD) Model in Kutai Kartanegara, East Kalimantan
Abstract
Coal mining plays a vital role in Indonesia's economic growth. However, these activities negatively impact the environment. To minimize this, the Indonesian government requires ex-mining land to be reclaimed, with one of the success criteria being canopy cover. Until now, there has been no measurable method that can determine the success rate of canopy cover on reclaimed land. This research was conducted to develop a measurement method based on remote sensing data using the Forest Canopy Density (FCD) Model, which is applied in Company X, Kutai Kertanegara. The FCD Model consisted of four biophysical indices, including AVI, BSI, SI, and TI, obtained from Landsat 8 OLI TIRS imagery from 2013–2021. The Kolmogorov-Smirnov normality test was performed before testing the relationship between FCD values and canopy cover using linear regression to obtain the canopy cover success value based on the FCD value. The FCD showed an increasing trend yearly, especially in the first two years after planting. Regression analysis showed a strong relationship between FCD values and canopy cover values, with R2=0.775, and revealed that 75.35 is the FCD value threshold for a successful canopy cover in the reclamation area. This study shows that the FCD approach can be applied to determine the success rate of reclamation in post-mining areas.
References
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Azizi, Z., Najafi, A., & Sohrabi, H. (2008). Forest Canopy Density Estimating , Using Satellite Images. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 4. https://doi.org/10.13140/2.1.2953.6967
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Frazer, G.W., Canham, C.D., Lertzman, K.P. (1999): Gap Light Analyzer (GLA): Imaging software to extract canopy structure and gap light transmission indices from truecolour fisheye photographs, users manual and program documentation. 36 pp. Simon Fraser University, Burnaby, British Columbia, and the Institute of Ecosystem Studies, Millbrook, New York
Frouz, J., Dvorščík, P., Vávrová, A., Doušová, O., Kadochová, Š., & Matějíček, L. (2015). Development of canopy cover and woody vegetation biomass on reclaimed and unreclaimed post-mining sites. Ecological Engineering, 84, 233–239. https://doi.org/10.1016/j.ecoleng.2015.09.027
Godinho, S., Gil, A., Guiomar, N., Neves, N., & Pinto-Correia, T. (2016). A remote sensing-based approach to estimating montado canopy density using the FCD model: a contribution to identifying HNV farmlands in southern Portugal. Agroforestry Systems, 90(1), 23–34. https://doi.org/10.1007/s10457-014-9769-3
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
Jain, P., Ahmed, R., Rehman, S., & Sajjad, H. (2020). Detecting disturbed forest tracts in the Sariska Tiger Reserve, India, using forest canopy density and fragmentation models. Modeling Earth Systems and Environment, 6(3), 1373–1385. https://doi.org/10.1007/s40808-020-00755-4
Krisnawati, H., Varis, E., Kallio, M., Kanninen, M. (2011). Paraserianthes falcataria (L.) Nielsen Ecology , silviculture and productivity. Center for International Forestry Research : Bogor.
Kurniawan, Ali. R; Surono, W. (2013). Model Reklamasi Tambang Rakyat Berwawasan Lingkungan : Tinjauan Atas Reklamasi Lahan Bekas Tambang Batu Apung Ijobalit, Kabupaten Lombok Timur, Propinsi Nusa Tenggara Barat. Jurnal Teknologi Mineral Dan Batubara, 9(September), 165–174.
Liu, Y., Zhou, W., Yan, K., Guan, Y., & Wang, J. (2022). Identification of the disturbed range of coal mining activities: A new land surface phenology perspective. Ecological Indicators, 143(August), 109375. https://doi.org/10.1016/j.ecolind.2022.109375
Mohsin, M., Zhu, Q., Naseem, S., Sarfraz, M., & Ivascu, L. (2021). Economic Growth , Social Interaction , and Public Health : An Application of Semi-Quantitative Mathematical Approach. Processes, 9(972).
Mondal, I., Thakur, S., Juliev, M., & Kumar De, T. (2021). Comparative analysis of forest canopy mapping methods for the Sundarban biosphere reserve, West Bengal, India. Environment, Development and Sustainability, 23(10), 15157–15182. https://doi.org/10.1007/s10668-021-01291-6
Pemerintah Indonesia. 2018. Keputusan Menteri ESDM Nomor No.1827K/30/MEM/2018 tentang Pedoman Pelaksanaan Kaidah Teknik Pertambangan Yang Baik Pemerintah Indonesia. Sekretariat Negara. Jakarta
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Pratiwi, Narendra, B. H., & Mulyanto, B. (2020). Soil properties improvement and use of adaptive plants for land rehabilitation of post tin mining closure in Bangka Island, Indonesia. Biodiversitas, 21(2), 505–511. https://doi.org/10.13057/biodiv/d210211
Rikimaru, A., & Miyatake, S. (2002). Development of Forest Canopy Density Mapping and Monitoring Model using Indices of Vegetation , Bare soil and Shadow. Geospatial World, Acrs, 1–6. www.gisdevelopment.net
Rikimaru, A., 1996. Landsat TM data processing guide for forest canopy density mapping and monitoring model. In: International Tropical Timber Organization (ITTO) workshop on utilization of remote sensing in site assessment and planning for rehabilitation of logged-over forest, Bangkok, Thailand, pp. 1–8
Tichý, L. (2016). Field test of canopy cover estimation by hemispherical photographs taken with a smartphone. Journal of Vegetation Science, 27(2), 427–435. https://doi.org/10.1111/jvs.12350
Tiwary, R. K. (2001). Environmental impact of coal mining on water regime and its management. Water, Air, and Soil Pollution, 132(1–2), 185–199. https://doi.org/10.1023/A:1012083519667
WCA. Coal facts,Coal contribution, https://www.worldcoal.org/coal-facts/coalscontribution/, 2022
Welles, J. M., & Cohen, S. (1996). Canopy structure measurement by gap fraction analysis using commercial instrumentation. Journal of Experimental Botany, 47(302), 1335–1342. https://doi.org/10.1093/jxb/47.9.1335
Xiao, W., Deng, X., He, T., & Chen, W. (2020). Mapping annual land disturbance and reclamation in a surface coal mining region using google earth engine and the landtrendr algorithm: A case study of the shengli coalfield in Inner Mongolia, China. Remote Sensing, 12(10). https://doi.org/10.3390/rs12101612
Xiao, W., Deng, X., He, T., & Guo, J. (2023). Using POI and time series Landsat data to identify and rebuilt surface mining, vegetation disturbance and land reclamation process based on Google Earth Engine. Journal of Environmental Management, 327, 116920. https://doi.org/10.1016/j.jenvman.2022.116920
Zulkarnain., Joy, B., Tuhpawana, P., Prawira, I. (2014). Soil Erosion Assessment of The Post-Coal Mining Site in Kutai Kartanagera District, East Kalimantan Province. International Journal of Science and Engineering, 7(2), 130–136. https://doi.org/10.12777/ijse.7.2.130-136
Authors
RosikinR., PrasetyoL. B. and HermawanR. (2023) “Assessment of the success of canopy cover revegetation of former coal mine lands with Forest Canopy Density (FCD) Model in Kutai Kartanegara, East Kalimantan”, Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management). Bogor, ID, 13(4), pp. 574-585. doi: 10.29244/jpsl.13.4.574-585.
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