Abstract
Land use intensity is a valuable concept to understand integrated land use system, which is unlike the traditional approach of analysis that often examines one or a few aspects of land use disregarding multidimensionality of the intensification process in the complex land system. Land use intensity is based on an integrative conceptual framework focusing on both inputs to and outputs from the land. Geographers’ non-stationary data-analysis technique is very suitable for most of the spatial data analysis. Our study was carried out in the northeast part of the Andhikhola watershed lying in the Middle Hills of Nepal, where over the last two decades, heavy loss of labor due to outmigration of rural farmers and increasing urbanization in the relatively easy accessible lowland areas has caused agricultural land abandonment. Our intention in this study was to ascertain factors of spatial pattern of intensity dynamism between human and nature relationships in the integrated traditional agricultural system. High resolution aerial photo and multispectral satellite image were used to derive data on land use and land cover. In addition, field verification, information collected from the field and census report were other data sources. Explanatory variables were derived from those digital and analogue data. Ordinary Least Square (OLS) technique was used for filtering of the variables. Geographically Weighted Regression (GWR) model was used to identify major determining factors of land use intensity dynamics. Moran’s I technique was used for model validation. GWR model was executed to identify the strength of explanatory variables explaining change of land use intensity. Accordingly, 10 variables were identified having the greatest strength to explain land use intensity change in the study area, of which physical variables such as slope gradient, temperature and solar radiation revealed the highest strength followed by variables of accessibility and natural resource. Depopulation in recent decades has been a major driver of land use intensity change but spatial variability of land use intensity was highly controlled by physical suitability, accessibility and availability of natural resources.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aldwaik SZ, Pontius RG (2012). Intensity analysis to unify measurements of size and stationarity of land changes by interval, category, and transition. Landsc Urban Plan 106(1): 103–114. https://doi.org/10.1016/j.landurbplan.2012.02.010
Andualem TG, Belay G, Guadie A (2018). Land use change detection using remote sensing technology. J Earth Sci Clim Change 9(10): 496. https://doi.org/10.4172/2157-7617.1000496
Anselin L (1995). Local Indicators of Spatial Association—LISA. Geogr Anal 27(2): 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
Awasthi KD, Sitaula BK Singh BR, et al. (2002). Land — use change in two Nepalese watersheds: GIS and geomorphometric analysis. Land Degrad Dev 13(6): 495–513. https://doi.org/10.1002/ldr.538
Barton CM, Ullah II, Bergin, S (2010). Land use, water and Mediterranean landscapes: modelling long-term dynamics of complex socio-ecological systems. Philos Trans R Soc A 368(5275): 5275–5297. https://doi.org/10.1098/rsta.2010.0193
Bashir T, Romshoo SH, Sabha I (2018). Monitoring land use/cover change using remote sensing and GIS techniques in upper Jhelum basin. Int J Adv Res Sci Eng 7(4): 1060–1077.
Basnet J (2016) CSO Land reform monitoring report. Kathmandu: Community Self-reliance Centre (CSRC).
Benayas JMR, Martins A, Nicolau JM, et al. (2007) Abandonment of ariculture land: An overview of drivers and consequences. Perspect Agric Vet Sci Nutr Nat Res 2(057): 1–14. https://doi.org/10.1079/PAVSNNR20072057
Birhane E, Ashfare H, Fenta AA, et al. (2019) Land use land cover changes along topographic gradients in Hugumburda national forest priority area, Northern Ethiopia. Remote Sens Appl Soc Environ 13: 61–68. https://doi.org/10.1016/j.rsase.2018.10.017
Blaikie PM, Cameron J, Seddon JD (2007) Nepal in crisis: growth and stagnation at the periphery. New Delhi: Adroit Publishers.
Blaschke T (2010). Object based image analysis for remote sensing. ISPRS J Photogramm Remote Sens 65(1): 2–16. https://doi.org/10.1016/j.isprsjprs.2009.06.004
Blaschke T, Hay GJ, Kelly M, et al. (2014) Geographic Object-Based Image Analysis — Towards a new paradigm. ISPRS J Photogramm Remote Sens 87: 180–191. https://doi.org/10.1016/j.isprsjprs.2013.09.014
Bracken I (2008) Toward improved visualization of socioeconomic data. Visualization In Geographical Information Systems. England: John Wiley & Sons Ltd. pp 76–84.
CBS (2012) National population and housing census 2011: National report. Kathmandu: Central Bureau of Statistics (CBS), Government of Nepal.
CBS (2013) National sample census of agriculture Nepal: National report. Kathmandu: Central Bureau of Statistics (CBS), Government of Nepal.
CBS (2017) National climate change impact survey 2016: A statistical report. Kathmandu: Central Bureau of Statistics (CBS), Government of Nepal.
Chaikaew P (2019) Land use change monitoring and modeling using GIS and remote sensing data for watershed scale in Thailand. Land Use — Assessing the Past, Envisioning the Future. pp 165–181. https://doi.org/10.5772/intechopen.79167
Chapagain PS, Rai MK, Paudel B (2018) Land use land cover change and its pathways in Sidin VDC, Panchthar district, Nepal. Geog J Nepal 11: 77–94. https://doi.org/10.3126/gjn.v11i0.19550
Chatterjee S, Hadi AS (2013) Regression Analysis by Example. Hoboken: John Wiley & Sons.
Chaudhary A, Brooks TM (2018). Land use intensity-Specific global characterization factors to assess product biodiversity footprints. Environ Sci Technol 52(9): 5094–5104. https://doi.org/10.1021/acs.est.7b05570
Chaudhary S, Wang Y, Khanal NR, et al. (2018). Social impact of farmland abandonment and its eco-environmental vulnerability in the High Mountain Region of Nepal: A case study of Dordi River Basin. Sustainability 10(7): 2331. https://doi.org/10.3390/su10072331
Chidi CL (2016) Determinants of cultivated land abandonment in the Hills of Western Nepal. Studia universitatis babes-bolyaigeographia 61: 101–116.
Chidi CL (2017) Patch analysis of cultivated land abandonment in the Hills of Western Nepal. Land Cover Change and Its Eco-environmental Responses in Nepal. Singapore: Springer Nature Singapore. pp 149–162.
Corbelle-Rico EC, Maseda RC (2008). Land abandonment: Concept and consequences. RevistaGalega de Economía 17(2): 1–13.
DADO (2013) Annual Agriculture Development Programme and Statistical Book. Syangja: District Agriculture Development Office, Syangja. p 4.
Daoud JI (2017) Multicollinearity and Regression Analysis. J Phys Conference Ser 949, 012009. https://doi.org/10.1088/1742-6596/949/17012009
Das A (2015). Estimation of land surface temperature and its relation to land cover land use: A case study on Bankura District, West Bengal, India. Int Multidiscip Res J 3(1): 1–7.
Duriyaprapan S, Britten EJ (1982). The effects of solar radiation on plant growth, oil yield and oil quality of Japanese Mint. J Exp Bot 33(6): 1319–1324. https://doi.org/10.1093/jxb/33.6.1319
Erb KH, Haberl H, Jepsen MR et al. (2013). A conceptual framework for analysing and measuring land-use intensity. Curr Opin Environ Sustain 5(5): 464–470. https://doi.org/10.1016/j.cosust.2013.07.010
ERDAS (2010) LPS User’s Guide. ERDAS, Inc. Norcross, GA. ESRI (2012) ArcGIS Desktop 9.3 Help.
FAO (1982) The State of Food and Agriculture: The Least Developed Countries and World Review Alleviating Rural Poverty, 1981. Rome: Food and Agriculture Organization (FAO) of United Nations. pp 5–39.
FRTC (2017) National Level Forests and Land Cover Analysis of Nepal using Google Earth Images. Kathmandu: Forest Research and Training Center (FRTC), Government of Nepal. pp 14–18.
Fu WJ, Jiang PK, Zhou GM et al. (2014). Using Moran’s I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China. Biogeosciences 11(8): 2401–2409. https://doi.org/10.5194/bg-11-2401-2014
GoN (2013) Agriculture Development Strategy (ADS) 2015–2035, Part 1. Kathmandu: Government of Nepal. pp 191–195.
GoN (2014) Nepal Second National Communication to United Nations Framework Convention on Climate Change. Kathmandu: Ministry of Science, technology and Environment, Government of Nepal. pp 99–109.
GoN (2017) Nepal Parichaya. Kathmandu: Ministry of Communication and Information Technology, Government of Nepal. pp 12–14 (In Nepali).
Grose CJ (1999) Land Capability Handbook: Guidelines for the Cassification and Agricultural land in Tasmania (First ed.). Tasmania: Department of Primary Industries, Water and Environment/Natural Heritage Trust, Australia. pp 22–41.
Gupta SC (2017) Fundamentals of Statistics. Mumbai: Himalayan Publishing House. pp 24.1–24.12.
Gurung A, Karki R, Bista R (2011). Community-based forest management in Nepal: Opportunities and challenges. Res Environ 1(1): 26–31. https://doi.org/10.5923/j.re.20110101.04
Halimi M, Sedighifar Z, Mohammadi C (2018). Analyzing spatiotemporal land use/cover dynamic using remote sensing imagery and GIS techniques case: Kan basin of Iran. Geo J 83(5): 1067–1077. https://doi.org/10.1007/s10708-017-9819-2
Hua X, Yan J, Li H, et al. (2016) Wildlife damage and cultivated land abandonment: Findings from the mountainous areas of Chongqing, China. Crop Prot 84: 141–149. https://doi.org/10.1016/j.cropro.2016.03.005
Hurskainen P, Adhikari H, Siljander M, et al. (2019) Auxiliary datasets improve accuracy of object-based land use/land cover classification in heterogeneous savanna landscapes. Remote Sens Environ 233: 111354. https://doi.org/10.1016/j.rse.2019.111354
Igwenagu CM, Alma OG (2014). On multicolinearity on climate variables. IJSAR J Math Stat 1(1): 1–13.
Ives JD, Messerli B (1989) The Himalayan Dilemma: Reconciling Development and Conservation. London and New York: Routledge. pp 69–79.
KESL (1986) Land Resource Mapping Project: Land Capability Report. Kathmandu: Survey Department of Nepal.
Khanal NR, Nepal P, Zhang Y, et al. (2020). Policy provisions for agricultural development in Nepal: A review. J Clean Prod 261: 121241. https://doi.org/10.1016/j.jclepro.2020.121241
Kim JS, Scott CD (2012). Robust kernel density estimation. J Mach Learn Res 13(1): 2529–2565. https://doi.org/10.1109/ICASSP.2008.4518376
Kuemmerle T, Erb K, Meyfroidt P, et al. (2013). Challenges and opportunities in mapping land use intensity globally. Curr Opin Environ Sustain 5(5): 484–493. https://doi.org/10.1016/j.cosust.2013.06.002
Lambin EF, Meyfroidt P (2011). Global land use change, economic globalization, and the looming land scarcity. Proc Natl Acad Sci USA 108(9): 3465–3472. https://doi.org/10.1073/pnas.1100480108
Lewandowska-Gwarda K (2018). Geographically Weighted Regression in the analysis of unemployment in Poland. ISPRS Int J Geo-Inf 7(1): 17. https://doi.org/10.3390/ijgi7010017
Li M, Zhang G, Liu Y, et al. (2019). Determinants of Urban Expansion and Spatial Heterogeneity in China. Int J Environ Res Public Health 16(19): 3706. https://doi.org/10.3390/ijerph16193706
Li S, Li X, Sun L, et al. (2018) An estimation of the extent of cropland abandonment in mountainous regions of China. Land Degrad Dev 29: 1327–1342. https://doi.org/10.1002/ldr.2924
Liu C, Liu J, Jiao Y, et al. (2019) Exploring spatial nonstationary environmental effects on Yellow Perch distribution in Lake Erie. Peer J 7: e7350. https://doi.org/10.7717/peerj.7350
Liu Y, Lam KF, Wu JT, et al. (2018). Geographically weighted temporally correlated logistic regression model. Sci Rep 8(1): 1417. https://doi.org/10.1038/s41598-018-19772-6
Lu B, Charlton M, Fotheringhama AS (2011) Geographically Weighted Regression using a non-euclidean distance metric with a study on London House price data. Procedia Environ Sci 7: 92–97. https://doi.org/10.1016/j.proenv.2011.07.017
Ma L, Cheng W, Bo J, et al. (2018) Spatio-temporal variation of land-use intensity from a multi-perspective—taking the Middle and Lower Reaches of Shule River Basin in China as an Example. Sustainability 10(3), 771. https://doi.org/10.3390/su10030771
Mackenzie A, Ball AS, Virdee SR (2002) Instant Notes in Ecology. New Delhi: Viva Books Limited. pp 93–102.
Macleod RD, Congalton RG (1998). A quantitative comparison of change-detection algorithms for monitoring eelgrass from remotely sensed data. Photogramm Eng Remote Sens 64(3): 207–216. http://europepmc.org/article/AGR/IND21074523
Malla UM, Chidi CL (1997) Indigenous practices of natural resource management at Pipaldanda, Palpa. The Himalayan Review XXIV–XXVIII: 36–49.
Manandhar P (2014) Social capital and rural change: Reflections from the decade-long armed conflict in Nepal. Contested Development in Nepal: Experiences and Reflections. Kathmandu: Heidel Press Pvt Ltd. pp 67–76.
Mecella G, Francaviglia R, Marchetti A, et al. (2008) Land capability for land use planning: An application in Central Italy. https://www.researchgate.net/publication (Assessed on: 2019-6-10)
Mohan C, Western AW, Wei Y et al. (2018). Predicting groundwater recharge for varying land cover and climate conditions — a global meta-study. Hydrol Earth Syst Sci 22(5): 2689–2703. https://doi.org/10.5194/hess-22-2689-2018
Myint SW, Gober P, Brazel A, et al. (2011). Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Remote Sens Environ 115(5): 1145–1161. https://doi.org/10.1016/j.rse.2010.12.017
Oshan TM, Fotheringham AS (2018). A comparison of spatially varying regression coefficient estimates using Geographically Weighted and Spatial-Filter-Based techniques. Geogr Anal 50(1): 53–75. https://doi.org/10.1111/gean.12133
Pain A, Nycander L, Islam K (2014) Evaluation of the Reality Check Approach in Bangladesh. Dhaka: The Embassy of Sweden in Dhaka. p 8.
Pandey D, Heyojoo BP, Shahi H (2014). Drivers and dynamics of land use land cover in Ambung VDC of Terhathum district, Nepal. Banko Janakari 26(1): 90–96. https://doi.org/10.3126/banko.v26i1.15508
Paudel K (2006) Population and resources linkages in Nepal. Himal Rev 37: 53–69. https://www.nepjol.info/index.php/HR/article/view/2032
Paudel KP, Bhattarai T, Subedi YR (2017) Nepal’s Agriculture Development: An Analysis of Agriculture Development Strategy of Nepal (2015–2015) from Civil Society Perspective. Lalitpur: Alliance for Agriculture for Food. pp 6–54.
Paudel KP, Tamang S, Shrestha KK (2014). Transforming land and livelihood: Analysis of agricultural land abandonment in the Mid Hills of Nepal. J For Livelihood 12(1): 11–19.
Pellissier V, Mimet A, Fontaine C, et al. (2017). Relative importance of the land-use composition and intensity for the bird community composition in anthropogenic landscapes. Ecol Evol 7(24): 10513–10535. https://doi.org/10.1002/ece3.3534
Pradhan PK, Sharma P (2017) Land use change and its driving forces in the Koshi Hills, Eastern Nepal. Land Cover Change and Its Eco-environmental Responses in Nepal. Singapore: Springer Nature Singapore Pte Ltd. pp 67–108.
Propastin P, Kappas M, Erasmi S (2008) Application of Geographically Weighted Regression to investigate the impact of scale on prediction uncertainty by modelling relationship between vegetation and climate. Int J Spat Data Infrastruct Res 3: 73–94. https://doi.org/10.2902/1725-0463.2008.03.art6
Randall M, Fensholt R, Zhang Y, et al. (2019). Geographic object based image analysis of WorldView-3 imagery for urban hydrologic modelling at the catchment scale. Water 11(6): 1133. https://doi.org/10.3390/w11061133
Suresh S, Ajay Suresh V, Mani K (2016). Estimation of land surface temperature of high range mountain landscape of Devikulam Taluk using Landsat8 data. Int J Res Eng Technol 5(1): 92–96. https://doi.org/10.15623/ijret.2016.0501017
Saghapour T, Moridpour S, Thompson R (2017) Accessibility measures versus land use measures in active transport modelling. Australasian Transport Research Forum 2017 Proceedings 27–29 November 2017, Auckland, New Zealand. pp 1–14.
Satyal VR (2010). Agriculture in decline. Econ J Dev Issues 11 & 12(1–2): 144–157. https://doi.org/10.3126/ejdi.v11i0.6113
Stjernman M, Sahlin U, Olsson O, et al. (2019) Estimating effects of arable land use intensity on farmland birds using joint species modeling. Ecol Appl 29. https://doi.org/10.1002/eap.1875
Suwal R, Dahal MP (2014) Economically active population: Dimensions and dynamics. Population Monograph, III. Kathmandu: Central Bureau of Statistics, Government of Nepal. pp 1–40.
Tobler WR (1970) A Computer Movie Simulating urban growth in the Detroit Region. Econ Geogr 46: 234–240. https://doi.org/10.2307/143141
Waceke J, Kimenju J (2007). Intensive subsistence agriculture: Impacts, challenges and possible interventions. Dyn Soil Dyn Plant 1(1): 43–53. https://doi.org/10.1128/JVI.76.23.11880-11888.2002
Wang B, Choi J, Choi S, et al. (2017). Image fusion-based land cover change detection using multi-temporal high-resolution satellite images. Remote Sens 9(8): 804: 1–19. https://doi.org/10.3390/rs9080804
Wang C, Zhang J, Yan X (2012) The Use of Geographically Weighted Regression for the relationship among extreme climate indices in China. Math Probl Eng 2012, 369539. https://doi.org/10.1155/2012/369539
Wang SY, Liu JS, Ma TB (2010). Dynamics and changes in spatial patterns of land use in Yellow River Basin, China. Land Use Policy 27(2): 313–323. https://doi.org/10.1016/j.landusepol.2009.04.002
Widiyanti E, Setyowati N, Ardianto DT (2018) Young generation’s perception on the agricultural sector. IOP Conference Ser Earth Environ Sci 200: 012060. https://doi.org/10.1088/1755-1315/200/1/012060
Yan H, Liu F, Liu J, et al. (2017). Status of land use intensity in China and its impacts on land carrying capacity. J Geogr Sci 27(4): 387–402. https://doi.org/10.1007/s11442-017-1383-7
Yurtseven H, Yener H (2019) Using of high-resolution satellite images in object-based image analysis. J For Sci 7: 187–204. https://doi.org/10.31195/ejejfs.603510
Zhang Y, Li X, Song W (2014) Determinants of cropland abandonment at the parcel, household and village levels in mountain areas of China: A multi-level analysis. Land Use Policy 41: 186–192. https://doi.org/10.1016/j.landusepol.2014.05.011
Zuur A, Ieno E, Elphick C (2010) A protocol for data exploration to avoid common statistical problems: Data exploration. Methods Ecol Evol 1: 3–14. https://doi.org/10.1111/j.2041-210X.2009.00001.x
Acknowledgments
This study was financially supported by the CAS Overseas Institutions Platform Project (Grant No. 131C11KYSB20200033).
The authors would like to thank Miss ZHANG Wenduo for her assistance when proofing the manuscript.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chidi, C.L., Sulzer, W., Xiong, Dh. et al. Land use intensity dynamics in the Andhikhola watershed, middle hill of Nepal. J. Mt. Sci. 18, 1504–1520 (2021). https://doi.org/10.1007/s11629-020-6652-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11629-020-6652-8