Bare Earth’s Surface Spectra as a Proxy for Soil Resource Monitoring

The Earth’s surface dynamics provide essential information for guiding environmental and agricultural policies. Uncovered and unprotected surfaces experience several undesirable effects, which can affect soil ecosystem functions. We developed a technique to identify global bare surface areas and their dynamics based on multitemporal remote sensing images to aid the spatiotemporal evaluation of anthropic and natural phenomena. The bare Earth’s surface and its changes were recognized by Landsat image processing over a time range of 30 years using the Google Earth Engine platform. Two additional products were obtained with a similar technique: a) Earth’s bare surface frequency, which represents where and how many times a single pixel was detected as bare surface, based on Landsat series, and b) Earth’s bare soil tendency, which represents the tendency of bare surface to increase or decrease. This technique enabled the retrieval of bare surfaces on 32% of Earth’s total land area and on 95% of land when considering only agricultural areas. From a multitemporal perspective, the technique found a 2.8% increase in bare surfaces during the period on a global scale. However, the rate of soil exposure decreased by ~4.8% in the same period. The increase in bare surfaces shows that agricultural areas are increasing worldwide. The decreasing rate of soil exposure indicates that, unlike popular opinion, more soils have been covered due to the adoption of conservation agriculture practices, which may reduce soil degradation.

[1]  C. Peng,et al.  Multiple afforestation programs accelerate the greenness in the 'Three North' region of China from 1982 to 2013 , 2016 .

[2]  Warren D. Sharp,et al.  Comment on “The earliest modern humans outside Africa” , 2018, Science.

[3]  W. Salas,et al.  Harnessing the Power of Data to Improve Agricultural Policy and Conservation Outcomes , 2019 .

[4]  R. C. Macridis A review , 1963 .

[5]  Eyal Ben-Dor,et al.  Shortwave Radiation Affected by Agricultural Practices , 2018, Remote. Sens..

[6]  M. Kendall Rank Correlation Methods , 1949 .

[7]  Nektarios Chrysoulakis,et al.  Exploiting satellite observations for global surface albedo trends monitoring , 2018, Theoretical and Applied Climatology.

[8]  D. Roberts,et al.  Using Imaging Spectroscopy to Study Ecosystem Processes and Properties , 2004 .

[9]  Marvin N. Wright,et al.  SoilGrids250m: Global gridded soil information based on machine learning , 2017, PloS one.

[10]  M. Litvak,et al.  Toward accounting for ecoclimate teleconnections: intra- and inter-continental consequences of altered energy balance after vegetation change , 2015, Landscape Ecology.

[11]  S. Yue,et al.  Power of the Mann–Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series , 2002 .

[12]  A. Kassam,et al.  Overview of the Worldwide Spread of Conservation Agriculture , 2015 .

[13]  J. Canadell,et al.  Greening of the Earth and its drivers , 2016 .

[14]  J. R. Scotti,et al.  Available From , 1973 .

[15]  Viacheslav I. Adamchuk,et al.  A global spectral library to characterize the world’s soil , 2016 .

[16]  K. Oost,et al.  An assessment of the global impact of 21st century land use change on soil erosion , 2017, Nature Communications.

[17]  H. Chenery,et al.  Growth and Poverty in Developing Countries , 1979 .

[18]  Russell G. Congalton,et al.  NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-support Analysis Data (GFSAD) Cropland Extent 2015 Southeast Asia 30 m V001 , 2017 .

[19]  Book Review: Soil Pollution: A Hidden Danger Beneath our Feet , 2018, Front. Environ. Sci..

[20]  Adrian W. Müller,et al.  No-till agriculture – a climate smart solution? , 2011 .

[21]  J. Hill,et al.  Using Imaging Spectroscopy to study soil properties , 2009 .

[22]  M Ghaemi,et al.  Using satellite data for soil cation exchange capacity studies , 2013 .

[23]  F. Baret,et al.  About the soil line concept in remote sensing , 1993 .

[24]  V. L. Mulder,et al.  The use of remote sensing in soil and terrain mapping — A review , 2011 .

[25]  T. Hengl,et al.  Soil carbon debt of 12,000 years of human land use , 2017, Proceedings of the National Academy of Sciences.

[26]  J. Tarduno,et al.  WITHDRAWN: An Evaluation of Modern Pottery from Southern Africa as a Magnetic Recorder , 2012 .

[27]  Caio T. Fongaro,et al.  Geospatial Soil Sensing System (GEOS3): A powerful data mining procedure to retrieve soil spectral reflectance from satellite images , 2018, Remote Sensing of Environment.

[28]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[29]  F. Achard,et al.  Determination of Deforestation Rates of the World's Humid Tropical Forests , 2002, Science.

[30]  Jens Hartmann,et al.  The new global lithological map database GLiM: A representation of rock properties at the Earth surface , 2012 .

[31]  Derek Rogge,et al.  Building an exposed soil composite processor (SCMaP) for mapping spatial and temporal characteristics of soils with Landsat imagery (1984–2014) , 2018 .

[32]  Hankui K. Zhang,et al.  Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data , 2013 .

[33]  T. McVicar,et al.  Impact of CO2 fertilization on maximum foliage cover across the globe's warm, arid environments , 2013 .

[34]  P. Tittonell,et al.  Role and management of soil biodiversity for food security and nutrition; where do we stand? , 2019, Global Food Security.

[35]  Luca Montanarella,et al.  World's soils are under threat , 2015 .

[36]  David A. Bohan,et al.  Relative effects of local management and landscape heterogeneity on weed richness, density, biomass and seed rain at the country-wide level, Great Britain , 2017 .

[37]  Amir Kassam,et al.  Overview of the Global Spread of Conservation Agriculture , 2012 .

[38]  N. Bolan,et al.  Biochar as a sorbent for contaminant management in soil and water: a review. , 2014, Chemosphere.

[39]  S. P. Abercrombie,et al.  Hierarchical mapping of annual global land cover 2001 to present: The MODIS Collection 6 Land Cover product , 2019, Remote Sensing of Environment.

[40]  P. Lagacherie,et al.  Combining Vis–NIR hyperspectral imagery and legacy measured soil profiles to map subsurface soil properties in a Mediterranean area (Cap-Bon, Tunisia) , 2013 .

[41]  H. B. Mann Nonparametric Tests Against Trend , 1945 .

[42]  J. Pretty Intensification for redesigned and sustainable agricultural systems , 2018, Science.

[43]  B. B. Ghaley,et al.  Making the Most of Our Land: Managing Soil Functions from Local to Continental Scale , 2015, Front. Environ. Sci..

[44]  Rodnei Rizzo,et al.  Satellite land surface temperature and reflectance related with soil attributes , 2018, Geoderma.

[45]  Yuanxin Liu,et al.  Effect of various mulches on soil physico—Chemical properties and tree growth (Sophora japonica) in urban tree pits , 2019, PloS one.

[46]  R. Ashley,et al.  Spectra of altered rocks in the visible and near infrared , 1979 .

[47]  R. E. Sharp,et al.  Science-based intensive agriculture: Sustainability, food security, and the role of technology , 2019 .

[48]  I. Daliakopoulos,et al.  The threat of soil salinity: A European scale review. , 2016, The Science of the total environment.

[49]  A. McBratney,et al.  The dimensions of soil security , 2014 .

[50]  R. V. Rossel,et al.  Visible and near infrared spectroscopy in soil science , 2010 .

[51]  R. Lal Soil carbon sequestration to mitigate climate change , 2004 .

[52]  S. Niu,et al.  Global soil acidification impacts on belowground processes , 2019, Environmental Research Letters.

[53]  Leah E M Bevis,et al.  Soil Fertility and Poverty in Developing Countries , 2019 .

[54]  H. Belshaw,et al.  The Food and Agriculture Organization of the United Nations , 1947, International Organization.

[55]  P. D’Odorico,et al.  Desertification and Land Degradation , 2019, Dryland Ecohydrology.

[56]  Jeffrey C. Luvall,et al.  Mapping Soil Organic Carbon Concentration for Multiple Fields with Image Similarity Analysis , 2008 .

[57]  S. Robinson,et al.  Food Security: The Challenge of Feeding 9 Billion People , 2010, Science.

[58]  Michael Dixon,et al.  Google Earth Engine: Planetary-scale geospatial analysis for everyone , 2017 .

[59]  J. Kastens,et al.  Intensification in agriculture-forest frontiers: Land use responses to development and conservation policies in Brazil , 2018, Global Environmental Change.

[60]  E. R. Stoner,et al.  Characteristic variations in reflectance of surface soils , 1981 .

[61]  Omar Ghattas,et al.  Exposed soil and mineral map of the Australian continent revealing the land at its barest , 2019, Nature Communications.

[62]  Gan Zhang,et al.  How well can VNIR spectroscopy distinguish soil classes , 2016 .

[63]  Toshio Koike,et al.  Global potential soil erosion with reference to land use and climate changes , 2003 .

[64]  H. Pourghasemi,et al.  Soil organic carbon mapping using remote sensing techniques and multivariate regression model , 2019 .

[65]  H. Kheyrodin,et al.  Effect of Climate Change on Soil Global Microorganisms , 2012 .

[66]  Michael E. Schaepman,et al.  Barest Pixel Composite for Agricultural Areas Using Landsat Time Series , 2017, Remote. Sens..

[67]  Alasdair J. Sykes,et al.  Characterising the biophysical, economic and social impacts of soil carbon sequestration as a greenhouse gas removal technology , 2019, Global change biology.

[68]  V. Brovkin,et al.  China and India lead in greening of the world through land-use management , 2019, Nature Sustainability.