The Trajectories of Perennial Crops Cover Change in Relationship with Forest Cover Change in Bao Lam District, Lam Dong Province
Main Article Content
Abstract
Abstract: The expansion of perennial crops area plays an important role for supporting the human livelihood in the Central Highlands, so have negative impacts on deforestation and sustainable development. Remote sensing and GIS were used to analyze the trajectories of perennial crops cover change in relationship with deforestation. The Logistic regression models were used to analyze proximate reasons and spatial changing determinants of main land cover changes for the period 2004-2016 of Bảo Lâm district. The result show that the perennial crops changes are indicator for deforestation in Bảo Lâm district with high deforestation rate 0,8% per year caused by the expansion of annual crops, blind area and the expansion of perennial crops. The facile accessed forest and suitable forest area for perennial crops have more destroyed. The trajectories of perennial crops and forest cover changes are important scientific towards sustainable development.
Keywords:
Remote sensing, perennial crops, forest cover change.
References
[1] Cục Thống kê tỉnh Lâm Đồng; Niên giám thống kê tỉnh Lâm Đồng năm 2015– các huyện thị. 2015, Lâm Đồng: Nxb. Thống kê.
[2] DeFries, R.S., et al., Deforestation driven by urban population growth and agricultural trade in the twenty-first century. Nature Geoscience, 2010. 3.
[3] Lambin, E.F. and P. Meyfroidt. Global land use change, economic globalization, and the looming land scarcity. in National Academy of Sciences of the United States of America. 2011.
[4] FAO, Global Forest Resources Assessment. 2010: Rome.
[5] Doutriaux, S., Geisler, C., Shively, G.,, Competing for coffee space: development-induced displacement in the Central Highlands of Vietnam. Rural Sociology, 2008. 73(4): p. 528–554.
[6] Ziegler, A.D., et al., Environmental Consequences of the Demise in Swidden Cultivation in Montane Mainland Southeast Asia: Hydrology and Geomorphology. Human Ecology, 2009. 37(3): p. 361-373.
[7] Meyfroidt, P. and E.F. Lambin, The causes of the reforestation in Vietnam. Land Use Policy, 2008a. 25(2): p. 182-197.
[8] UN-REDD Vietnam; Final report on Forest Ecological Stratification in Vietnam. 2011: Hanoi.
[9] Thảo, L.B., Việt Nam lãnh thổ và các vùng Địa lý. 1998, Hà Nội: Nxb Thế giới.
[10] Ban phân vùng địa lý tự nhiên; UB Kế hoạch và kỹ thuật nhà nước; Phân vùng địa lý tự nhiên Việt Nam. 1971: Hà Nội.
[11] Meyfroidt, P., T.P. Vu, and V.A. Hoang, Trajectories of deforestation, coffee expansion and displacement of shifting cultivation in the Central Highlands of Vietnam. Global Environmental Change, 2013. 23(5): p. 1187-1198.
[12] Ha, D.T. and G. Shively, Coffee Boom, Coffee Bust and Smallholder Response in Vietnam’s Central Highlands. Review of Development Economics, 2008. 12(2): p. 312-326.
[13] Agergaard, J., N. Fold, and K.V. Gough, Global–local interactions: socioeconomic and spatial dynamics in Vietnam's coffee frontier. Geographical Journal, 2009. 175(2): p. 133-145.
[14] Mukashema, A., A. Veldkamp, and A. Vrieling, Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network. International Journal of Applied Earth Observation and Geoinformation, 2014. 33: p. 331-340.
[15] Cordero‐Sancho, S. and S.A. Sader, Spectral analysis and classification accuracy of coffee crops using Landsat and a topographic‐ environmental model. International Journal of Remote Sensing, 2007. 28(7): p. 1577-1593.
[16] Bock, M., et al., Object-oriented methods for habitat mapping at multiple scales – Case studies from Northern Germany and Wye Downs, UK. Journal for Nature Conservation, 2005(13): p. 75-89.
[17] Dehvari A. and H.R. J, Comparison of object-based and pixel based infrared airborne image classification methods using DEM thematic layer. Journal of Geography and Regional Planning, 2009. 2: p. 86-96.
[18] Willhauck, G., Comparison of object oriented classification techniques and standard image analysis for the use of change detection between SPOT multispectral satellite images and aerial photos. International Archives of Photogrammetry and Remote Sensing, 2000. 33: p. 214-221.
[19] Gaurav K. P. and P.K. G, Comparison of Advanced Pixel Based (ANN and SVM) and Object-Oriented Classification Approaches Using Landsat-7 Etm+ Data. International Journal of Engineering and Technology, 2010. 2: p. 245-51.
[20] Matinfar H.R., et al., Comparisons of Object-Oriented and Pixel-Based Classification of Land Use/Land Cover Types Based on Lansadsat7, Etm+ Spectral Bands (Case Study: Arid Region of Iran). American-Eurasian J. Agriculture & Environment, Science, 2007. 2: p. 448-56.
[21] Yan G., et al., Comparison of pixel-based and object-oriented image classification approaches a case study in a coal fire area, Wuda, Inner Mongolia,China. International Journal of Remote Sensing, 2006. 27: p. 4039-55.
[22] Zhou, Z., et al., Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost. PLOS ONE, 2015. 10(11): p. e0142069.
[23] Long, J.A., et al., Object-oriented crop classification using multitemporal ETM+ SLC-off imagery and random forest. GIScience & Remote Sensing, 2013. 50(4): p. 418-436.
[24] Schultz, B., et al., Self-Guided Segmentation and Classification of Multi-Temporal Landsat 8 Images for Crop Type Mapping in Southeastern Brazil. Remote Sensing, 2015. 7(11).
[25] Pham, V.C., et al., The conversion of agricultural land in the peri-urban areas of Hanoi (Vietnam): patterns in space and time. Journal of Land Use Science, 2015. 10(2): p. 224-242.
[26] Cox, D.R., The Regression Analysis of Binary Sequences. Journal of the Royal Statistical Society. Series B (Methodological), 1958. 20(2): p. 215-242.
[27] Walker, S.H. and D.B. Duncan, Estimation of the Probability of an Event as a Function of Several Independent Variables. Biometrika, 1967. 54(1/2): p. 167-179.
[28] Müller, D., et al., Lost in transition: determinants of post-socialist cropland abandonment in Romania. Journal of Land Use Science, 2009. 4
(1-2): p. 109-129.
[2] DeFries, R.S., et al., Deforestation driven by urban population growth and agricultural trade in the twenty-first century. Nature Geoscience, 2010. 3.
[3] Lambin, E.F. and P. Meyfroidt. Global land use change, economic globalization, and the looming land scarcity. in National Academy of Sciences of the United States of America. 2011.
[4] FAO, Global Forest Resources Assessment. 2010: Rome.
[5] Doutriaux, S., Geisler, C., Shively, G.,, Competing for coffee space: development-induced displacement in the Central Highlands of Vietnam. Rural Sociology, 2008. 73(4): p. 528–554.
[6] Ziegler, A.D., et al., Environmental Consequences of the Demise in Swidden Cultivation in Montane Mainland Southeast Asia: Hydrology and Geomorphology. Human Ecology, 2009. 37(3): p. 361-373.
[7] Meyfroidt, P. and E.F. Lambin, The causes of the reforestation in Vietnam. Land Use Policy, 2008a. 25(2): p. 182-197.
[8] UN-REDD Vietnam; Final report on Forest Ecological Stratification in Vietnam. 2011: Hanoi.
[9] Thảo, L.B., Việt Nam lãnh thổ và các vùng Địa lý. 1998, Hà Nội: Nxb Thế giới.
[10] Ban phân vùng địa lý tự nhiên; UB Kế hoạch và kỹ thuật nhà nước; Phân vùng địa lý tự nhiên Việt Nam. 1971: Hà Nội.
[11] Meyfroidt, P., T.P. Vu, and V.A. Hoang, Trajectories of deforestation, coffee expansion and displacement of shifting cultivation in the Central Highlands of Vietnam. Global Environmental Change, 2013. 23(5): p. 1187-1198.
[12] Ha, D.T. and G. Shively, Coffee Boom, Coffee Bust and Smallholder Response in Vietnam’s Central Highlands. Review of Development Economics, 2008. 12(2): p. 312-326.
[13] Agergaard, J., N. Fold, and K.V. Gough, Global–local interactions: socioeconomic and spatial dynamics in Vietnam's coffee frontier. Geographical Journal, 2009. 175(2): p. 133-145.
[14] Mukashema, A., A. Veldkamp, and A. Vrieling, Automated high resolution mapping of coffee in Rwanda using an expert Bayesian network. International Journal of Applied Earth Observation and Geoinformation, 2014. 33: p. 331-340.
[15] Cordero‐Sancho, S. and S.A. Sader, Spectral analysis and classification accuracy of coffee crops using Landsat and a topographic‐ environmental model. International Journal of Remote Sensing, 2007. 28(7): p. 1577-1593.
[16] Bock, M., et al., Object-oriented methods for habitat mapping at multiple scales – Case studies from Northern Germany and Wye Downs, UK. Journal for Nature Conservation, 2005(13): p. 75-89.
[17] Dehvari A. and H.R. J, Comparison of object-based and pixel based infrared airborne image classification methods using DEM thematic layer. Journal of Geography and Regional Planning, 2009. 2: p. 86-96.
[18] Willhauck, G., Comparison of object oriented classification techniques and standard image analysis for the use of change detection between SPOT multispectral satellite images and aerial photos. International Archives of Photogrammetry and Remote Sensing, 2000. 33: p. 214-221.
[19] Gaurav K. P. and P.K. G, Comparison of Advanced Pixel Based (ANN and SVM) and Object-Oriented Classification Approaches Using Landsat-7 Etm+ Data. International Journal of Engineering and Technology, 2010. 2: p. 245-51.
[20] Matinfar H.R., et al., Comparisons of Object-Oriented and Pixel-Based Classification of Land Use/Land Cover Types Based on Lansadsat7, Etm+ Spectral Bands (Case Study: Arid Region of Iran). American-Eurasian J. Agriculture & Environment, Science, 2007. 2: p. 448-56.
[21] Yan G., et al., Comparison of pixel-based and object-oriented image classification approaches a case study in a coal fire area, Wuda, Inner Mongolia,China. International Journal of Remote Sensing, 2006. 27: p. 4039-55.
[22] Zhou, Z., et al., Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost. PLOS ONE, 2015. 10(11): p. e0142069.
[23] Long, J.A., et al., Object-oriented crop classification using multitemporal ETM+ SLC-off imagery and random forest. GIScience & Remote Sensing, 2013. 50(4): p. 418-436.
[24] Schultz, B., et al., Self-Guided Segmentation and Classification of Multi-Temporal Landsat 8 Images for Crop Type Mapping in Southeastern Brazil. Remote Sensing, 2015. 7(11).
[25] Pham, V.C., et al., The conversion of agricultural land in the peri-urban areas of Hanoi (Vietnam): patterns in space and time. Journal of Land Use Science, 2015. 10(2): p. 224-242.
[26] Cox, D.R., The Regression Analysis of Binary Sequences. Journal of the Royal Statistical Society. Series B (Methodological), 1958. 20(2): p. 215-242.
[27] Walker, S.H. and D.B. Duncan, Estimation of the Probability of an Event as a Function of Several Independent Variables. Biometrika, 1967. 54(1/2): p. 167-179.
[28] Müller, D., et al., Lost in transition: determinants of post-socialist cropland abandonment in Romania. Journal of Land Use Science, 2009. 4
(1-2): p. 109-129.