Remote sensing for monitoring and mapping Land Productivity in Italy: A rapid assessment methodology

Abstract We present a remote sensing-based methodology for the Land Productivity (LP) rapid assessment and monitoring of status and trends at national and sub-national scales. This methodology aims at supporting national and international policies to achieve the Land Degradation Neutrality (LDN) target in the framework of the UN Agenda 2030 and the Sustainable Development Goals (SDG 15.3). The work was performed using the NASA-MODIS Normalized Difference Vegetation Index (NDVI) as proxy indicator of LP status and trends in Italy for 16 years (2000–2015). The assessment of the LP status was based on the pixel mean and standard deviation values of yearly LP values. The LP trends of the yearly time series were computed using Mann-Kendall (MK) and Contextual MK (CMK) tests providing a monitoring indicator for land productivity change. The amount of land with valid increasing and decreasing trends is estimated assuming the 95% significance level of trends in the areas with “good” NDVI pixel reliability. The area of increasing and decreasing LP are estimated for the national territory and for different land covers. The widespread observed increasing LP variations were correlated to the progressive renaturalization of lands subsequent to the decrease of agricultural activities and increasing precipitation trends in the winter season. Decreasing LP affected very limited areas and hot spots were correlated to changes of seasonal precipitation and anthropic activities. The areas and municipalities most affected by LP changes are identified and may support, in the framework of SDG 15.3 and LDN, the identification of policy initiatives.

[1]  National Drought Impact Monitoring: a NOAA NDVI and Precipitation Data Study of Ethiopia , 1989 .

[2]  Michele Brunetti,et al.  Temperature and precipitation variability in Italy in the last two centuries from homogenised instrumental time series , 2006 .

[3]  A. Toreti,et al.  Annual and seasonal precipitation over Italy from 1961 to 2006 , 2009 .

[4]  Jan Verbesselt,et al.  Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology , 2013, Remote. Sens..

[5]  F. van den Bergh,et al.  Limits to detectability of land degradation by trend analysis of vegetation index data , 2012 .

[6]  A. Toreti,et al.  SCIA: a system for a better knowledge of the Italian climate , 2007 .

[7]  Richard M. Vogel,et al.  Trends in floods and low flows in the United States: impact of spatial correlation , 2000 .

[8]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[9]  M. Schaepman,et al.  Proxy global assessment of land degradation , 2008 .

[10]  L. Salvati,et al.  The Integrated Assessment of Land Degradation , 2009 .

[11]  A. Toreti,et al.  Climate indicators for Italy: calculation and dissemination , 2011 .

[12]  L. Perini,et al.  Fifty Years on: Long‐term Patterns of Land Sensitivity to Desertification in Italy , 2016 .

[13]  H. Liniger,et al.  Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia , 2015 .

[14]  B. Holben.  Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .

[15]  Xiaolan L. Wang,et al.  Changes of Extreme Wave Heights in Northern Hemisphere Oceans and Related Atmospheric Circulation Regimes , 2001 .

[16]  Xubin Zeng,et al.  Intercomparison of Seven NDVI Products over the United States and Mexico , 2014, Remote. Sens..

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

[18]  J. Ardö,et al.  A remote sensing-based primary production model for grassland biomes , 2003 .

[19]  R. Myneni,et al.  The interpretation of spectral vegetation indexes , 1995 .

[20]  J. Ronald Eastman,et al.  A Contextual Mann‐Kendall Approach for the Assessment of Trend Significance in Image Time Series , 2011, Trans. GIS.

[21]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.

[22]  Marion Stellmes,et al.  Assessment and monitoring of land condition in the Iberian Peninsula, 1989–2000 , 2010 .

[23]  L. Maiorano,et al.  Changes in land-use/land-cover patterns in Italy and their implications for biodiversity conservation , 2007, Landscape Ecology.