Abstract
Land degradation is a serious environmental stress, which is identified and analysed through advanced remote sensing technique at a global level. Vegetal degradation, soil erosion, salinity and alkalinity, deforestation, changes in land cover are a few factors, which raise the severity of desertification and land degradation. The changes caused by these factors lower the land and food production and eventually leads to environmental and socio-economic sustainability. Periodical monitoring and observation of the factors, which are the root causes for desertification/land degradation can be evaluated through remote sensing and modelling techniques. The present chapter aims to review the various remote sensing sensors and the recent techniques in mapping desertification and land degradation processes. Remote sensing and GIS techniques serve as an aid to assess and monitor various land degradation processes, and to compare trends across spatial and temporal scales. In the future, the convergence of high-resolution data products with modern classification and modelling techniques could be explored more broadly to assess and obtain more detailed information on monitoring and modelling desertification and land degradation.
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References
Abd El-Kawy OR, Rød JK, Ismail HA, Suliman AS (2011) Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Appl Geogr 31:483–494. https://doi.org/10.1016/j.apgeog.2010.10.012
Abdel Rahman MAE, Natarajan A, Srinivasamurthy CA, Hegde R (2016) Estimating soil fertility status in physically degraded land using GIS and remote sensing techniques in Chamarajanagar district, Karnataka, India. Egypt J Remote Sens Space Sci 19:95–108. https://doi.org/10.1016/j.ejrs.2015.12.002
Ahmad F (2013) Land degradation pattern using geo-information technology for KotAddu, Punjab Province, Pakistan. Glob J Hum Soc Sci Geogr Geo-Sci Environ 13(1). Online ISSN: 2249-460x and Print ISSN: 0975-587X. https://globaljournals.org/GJHSS_Volume13/1-Land-Degradation-Pattern-Using.pdf
Ajai AS, Arya Dhinwa PS, Pathan SK, Ganesh Raj K (2009) Desertification/land degradation status mapping of India. Curr Sci 97(10):1478–1483. http://www.indiaenvironmentportal.org.in/files/Desertification_0.pdf
Asner GP, Knapp DE, Balaji A, Páez-Acosta G (2009) Automated mapping of tropical deforestation and forest degradation: CLASlite. J Appl Remote Sens 3:033543. https://doi.org/10.1117/1.3223675
Borrelli P, Robinson DA, Panagos P, Lugato E, Yang JE, Alewell C, Wuepper D, Montanarella L, Ballabio C (2020) Land use and climate change impacts on global soil erosion by water (2015–2070). PNAS 117(36):21994–22001. https://doi.org/10.1073/pnas.2001403117
Breiman L (2001) Random forests. Mach Learn 45:5–32. https://doi.org/10.1023/A:1010933404324
Cai X, Zhang X, Wang D (2011) Land availability for biofuel production. Environ Sci Technol 45(1):334–339. https://doi.org/10.1021/es103338e
Chabrillat S, Kaufmann HJ, Hill J, Mueller AA, Merz B, Echtler H (2003) Research opportunities for studying land degradation with spectroscopic techniques. In: Proceedings of SPIE 4886, remote sensing for environmental monitoring, GIS applications, and geology II, 14 Mar 2003. https://doi.org/10.1117/12.462362
Clark DB, Read JM, Clark ML, Cruz AM, Dotti MF, Clark DA (2004) Application of 1-m and 4-m resolution satellite data to ecological studies of tropical rain forests. Ecol Appl 14(1):61–74. https://doi.org/10.1890/02-5120
Collado AD, Chuvieco E, Camarasa A (2000) Satellite remote sensing analysis to monitor desertification processes in the crop-rangeland boundary of Argentina. J Arid Environ 52:121–133. https://doi.org/10.1006/jare.2001.0980
Dasgupta A, Sastry KLN, Dhinwa PS, Rathore VS, Nathawat MS (2013) Identifying desertification risk areas using fuzzy membership and geospatial technique—a case study, Kota District, Rajasthan. J Earth Syst Sci 122(4):1107–1124. https://doi.org/10.1007/s12040-013-0331-x
Dave VA, Sur K (2018) Fuzzy integrated desertification vulnerability model. ISPRS Int Arch Photogramm Remote Sens Spat Inf Sci XLII-5:395–401. https://doi.org/10.5194/isprs-archives-XLII-5-395-2018
Davis G (2007) History of the NOAA satellite program. J Appl Remote Sens 1:1–18. https://doi.org/10.1117/1.2642347
Del Valle HF, Elissalde NO, Gagliardini DA, Milovich J (1998) Status of desertification in the Patagonian region: assessment and mapping from satellite imagery. Arid Land Res Manag 12(2):95–121. https://doi.org/10.1080/15324989809381502
Dharumarajan S, Lalitha M, Rajendra Hegde, Janani N, Rajavat AS, Sastry KLN, Singh SK (2018a) Status of desertification in South India—assessment, mapping and change detection analysis. Curr Sci 115(2):331–338. https://doi.org/10.18520/cs%2Fv115%2Fi2%2F331-338
Dharumarajan S, Bishop TFA, Hegde R, Singh SK (2018b) Desertification vulnerability index—an effective approach to assess desertification processes: a case study in Anantapur District, Andhra Pradesh, India. Land Degrad Dev 29(1):1–12. https://doi.org/10.1002/ldr.2850
Dharumarajan S, Lalitha M, Vasundhara R, Hegde R (2016) The major biophysical indicators of desertification in arid and semiarid regions of India. Agropedology 26:189–197. http://isslup.in/wp-content/uploads/2018/09/Agropadiology-Dec-2016-8.pdf
Dharumarajan S, Veeramani S, Kalaiselvi B, Lalitha M, Janani, Srinivasan R, Rajendra Hegde (2019) Potential impacts of climate change on land degradation and desertification: land degradation and climate change. Climate change and its impact on ecosystem services and biodiversity in arid and semi-arid zones. In: Singh V (eds) Impacts of climate change on biodiversity and ecosystem services: current trends. IGI Global, pp 183–195. https://doi.org/10.4018/978-1-5225-7387-6.ch010. Accessed 20 May 2019
Dubovyk O, Menz G, Conrad C, Kan E, Machwitz M, Khamzina A (2013a) Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modelling. Environ Monit Assess 185:4775–4790 (2013). https://doi.org/10.1007/s10661-012-2904-6
Dubovyk O, Menz G, Conrad C, Lamers JPA, Lee A, Khamzina A (2013b) Spatial targeting of land rehabilitation: a relational analysis of cropland productivity decline in arid Uzbekistan. Erekunde 67(2):167–181. https://doi.org/10.3112/erdkunde.2013.02.05. https://pdfs.semanticscholar.org/57c2/dc158ddec4b53be22987b9881fed69c8320f.pdf
Dwivedi RS (2002) Spatio-temporal characterization of soil degradation. Tropical Ecology 43(1):75–90. http://tropecol.com/pdf/open/PDF_43_1/43107.pdf
Dwivedi RS, Sreenivas K (1998) Image transforms as a tool for the study of soil salinity and alkalinity dynamics. Int J Remote Sens 19(4):605–619. https://doi.org/10.1080/014311698215883
Environmental Management Agency (2015) EMA annual report. https://www.ema.co.zw/agency/downloads/file/2015_EMA%20annual%20report.pdf
FAO (2008) Land degradation on the rise—one fourth of the world’s population affected says new study. http://www.fao.org/newsroom/en/news/2008/1000874/index.html
Gao J, Liu Y (2008) Mapping of land degradation from space: a comparative study of Landsat ETM+ and ASTER data. Int’l J Remote Sens 29(14):4029–4043. https://doi.org/10.1080/01431160801891887
Huang Q-H, Cai Y (2007) Spatial pattern of Karst rock desertification in the Middle of Guizhou Province, Southwestern China. Environ Geol 52:1325–1330. https://doi.org/10.1007/s00254-006-0572-y
Huang S, Siegert F (2006) Land cover classification optimized to detect areas at risk of desertification in North China based on SPOT VEGETATION imagery. J Arid Environ 67(2):308–327. https://doi.org/10.1016/j.jaridenv.2006.02.016
Hurtt GC, Chini L, Sahajpal R et al (2020) Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6. Geosci Model Dev 13:5425–5464. https://doi.org/10.5194/gmd-13-5425-2020
Kosmas C, Ferrara A, Briasouli H, Imeson A (1999) Methodology for mapping Environmentally Sensitive Areas (ESAs) to desertification. In: The Medalus project: Mediterranean desertification and land use Manual on key indicators of desertification and mapping environmentally sensitive areas to desertification. In: Kosmas C, Kirkby M, Geeson N (eds) European Union 18882. ISBN 92-828-6349-2, pp 31–47
Lyu Y, Shi P, Han G, Liu L, Guo L, Hu X, Zhang G (2020) Desertification control practices in China. Sustainability 12:3258. https://doi.org/10.3390/su12083258
Metternicht G (2001) Assessing temporal and spatial changes of salinity using fuzzy logic, remote sensing and GIS. Foundations of an expert system. Ecol Model 144(2–3):163–179. https://doi.org/10.1016/S0304-3800(01)00371-4
Mohamadi A, Heidarizadi Z, Nourollahi H (2016) Assessing the desertification trend using neural network classification and object-oriented techniques (Case study: Changouleh watershed—Ilam Province of Iran). J Fac for Istanb Univer 66(2):683–690. https://doi.org/10.17099/jffiu.75819
Nathawat MS, Rathore VS, Pandey AC, Singh SK, Shankar GR (2010) Monitoring and analysis of wastelands and its dynamics using multiresolution and temporal satellite data in part of Indian state of Bihar. Int’l J Geomatics Geosci 1(3):297–307. http://ipublishing.co.in/jggsvol1no12010/EIJGGS2003.pdf
Olander LP, Gibbs HK, Steininger M, Swenson JJ, Murray BC (2008) Reference scenarios for deforestation and forest degradation in support of REDD: a review of data and methods. Environ Res Lett 3:025011. https://doi.org/10.1088/1748-9326/3/2/025011
Pashaei M, Rashki A, Sepehr A (2017) An integrated desertification vulnerability index for Khorasan-Razavi. Iran 5(3):44–55. https://doi.org/10.13189/nrc.2017.050302
Petropoulos GP, Arvanitis K, Sigrimis N (2012) Hyperion hyperspectral imagery analysis combined with machine learning classifiers for land use/cover mapping. https://doi.org/10.1016/j.eswa.2011.09.083. https://www.academia.edu/3296197/Hyperion_hyperspectral_imagery_analysis_combined_with_machine_learning_classifiers_for_land_use_cover_mapping
Pradhan B, Chaudhari A, Adinarayana J, Buchroithner MF (2011) Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia. Environ Monit Assess 184:715–727. https://doi.org/10.1007/s10661-011-1996-8
Prince SD (1991) Satellite remote sensing of primary production: comparison of results for Sahelian grasslands 1981–1988. Int’l J Remote Sens 12:1301–1311. https://doi.org/10.1080/01431169108929727
Reynolds JF, Smith DMS, Lambin EF (2007) Global desertification: building a science for dryland development. Science 316:847–851. https://doi.org/10.1126/science.1131634
Runnström MC (2000) Is Northern China winning the battle against desertification? A J Hum Environ 29(8):468–476. https://doi.org/10.1579/0044-7447-29.8.468
SAC (2016) Desertification and land degradation Atlas of India (Based on IRS AWiFS data of 2011–13 and 2003–05). Space Applications Centre, ISRO, Ahmedabad, India, p 219. ISBN 978-93-82760-207
Salvati L, Zitti M (2009) Convergence or divergence in desertification risk? Scale-based assessment and policy implications in a Mediterranean country. J Environ Planning Manag 52:957–970. https://doi.org/10.1080/09640560903181220
Shalaby A, Tateishi R (2007) Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the North-western coastal zone of Egypt. Appl Geogr 27:28–41. https://doi.org/10.1016/j.apgeog.2006.09.004
Shrestha DP, Margate DE, Meer FVD, Anh HV (2005) Analysis and classification of hyperspectral data for mapping land degradation: an application in southern Spain. Int’l J Appl Earth Obs Geoinform 7(2):85–96. https://doi.org/10.1016/j.jag.2005.01.001
Symeonakis E, Higginbottom T (2014) Bush encroachment monitoring using multi-temporal LANDSAT data and random forests. Int Arch Photogramm Remote Sens Spat Inf Sci XL-2. ISPRS Technical Commission II symposium, 6–8 Oct 2014, Toronto, Canada. https://doi.org/10.5194/isprsarchives-XL-2-29-2014
Tagore GS, Bairagi GD, Sharma NK, Sharma R, Bhelawe S, Verma PK (2012) Mapping of degraded lands using remote sensing and GIS techniques. J Agric Phys 12(1):29–36. https://www.researchgate.net/publication/263487317_Mapping_of_Degraded_Lands_Using_Remote_Sensing_and_GIS_Techniques
Tripathy GK, Ghosh TK, Shah SD (1996) Monitoring of desertification process in Karnataka state of India using multi-temporal remote sensing and ancillary information using GIS. Int’l J Remote Sens 17(12):2243–2257. https://doi.org/10.1080/01431169608948771
Tsesmelis DE, Karavitis CA, Oikonomou PD, Alexandris S, Kosmas C (2019) Assessment of the vulnerability to drought and desertification characteristics using the standardized drought vulnerability index (SDVI) and the environmentally sensitive areas index (ESAI). Resources 8(1):6. https://doi.org/10.3390/resources8010006
UNCCD (1994) United Nations convention to combat desertification, elaboration of an international convention to combat desertification in countries experiencing serious drought and/or desertification, particularly in Africa (U.N. Doc. A/AC.241/27, 33 I.L.M. 1328 UN)
UNCCD and FAO (2020) Land degradation neutrality for water security and combatting drought. Bonn, Germany. http://www.fao.org/publications/card/en/c/CA7468EN/
UNCCD (2019) Land degradation, poverty and inequality. https://www.unccd.int/publications/land-degradation-poverty-and-inequality
UNEP, United Nations Environmental Programme (1997) In: Middleton N, Thomas D (eds) The World Atlas of desertification. London New York, Sydney, Auckland. ISBN 0340691662. https://digitallibrary.un.org/record/245955
Ustin SL, Roberts DA, Gamon JA, Asner GP, Green RO (2004) Using imaging spectroscopy to study ecosystem processes and properties. Bioscience 54(6):523–534. https://doi.org/10.1641/0006-3568
Vrieling A, Jong SM, Sterk G, Rodrigues SC (2008) Timing of erosion and satellite data: a multi-resolution approach to soil erosion risk mapping. Int’l J Appl Earth Obs Geoinform 10(3):267–281. https://doi.org/10.1016/j.jag.2007.10.009
Wang C, Qi J, Cochrane M (2005) Assessment of tropical forest degradation with canopy fractional cover from Landsat ETM+ and IKONOS imagery. Earth Interact 9. https://doi.org/10.1175/EI133.1
Wiesmeier M, Barthold F, Blank B, Kögel-Knabner I (2011) Digital mapping of soil organic matter stocks using random forest modeling in a semi-arid steppe ecosystem. Plant Soil 340:7–24. https://doi.org/10.1007/s11104-010-0425-z
Yue Y, Li M, Zhu A, Ye X, Mao R, Wan J, Dong J (2016) Land degradation monitoring in the Ordos Plateau of China using an expert knowledge and BP-ANN-based approach. Sustainability 8:1174. https://doi.org/10.3390/su8111174
Zolekar RB, Bhagat VS (2014) Use of IRS P6 LISS-IV data for land suitability analysis for cashew plantation in hilly zone. Asian J Geoinformatics 14(3):23–35. https://www.semanticscholar.org/paper/Use-of-IRS-P6-LISS-IV-data-for-Land-Suitability-for-Bhagat/5ffb8aeb49501acae4e8a30e76347188822566ba
Zonn IS, Kust GS, Andreeva OV (2017) Desertification paradigm: 40 years of development and global efforts. Arid Ecosyst 7(3):131–214. https://doi.org/10.1134/S2079096117030118
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Dharumarajan, S. et al. (2022). Remote Sensing Sensors and Recent Techniques in Desertification and Land Degradation Mapping––A Review. In: Saljnikov, E., Mueller, L., Lavrishchev, A., Eulenstein, F. (eds) Advances in Understanding Soil Degradation. Innovations in Landscape Research. Springer, Cham. https://doi.org/10.1007/978-3-030-85682-3_32
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