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.

我们提出了一种基于遥感的方法，用于在国家和地方范围内对土地生产力（LP）进行状态和趋势的快速评估和监控。该方法旨在支持国家和国际政策，以在《联合国2030年议程》和可持续发展目标（SDG 15.3）的框架内实现土地退化中立性（LDN）目标。这项工作是使用NASA-MODIS标准化差异植被指数（NDVI）作为意大利LP状况和趋势的代理指标，历时16年（2000-2015年）。LP状态的评估基于像素平均值和年度LP值的标准偏差值。年度时间序列的LP趋势是使用Mann-Kendall（MK）和Contextual MK（CMK）测试计算得出的，该测试提供了土地生产力变化的监测指标。假设具有“良好” NDVI像素可靠性的区域中趋势的显着性水平为95％，则可以估算出具有有效增加和减少趋势的土地数量。估算了国家领土和不同土地覆被的LP的增加和减少的面积。随着冬季农业活动的减少和降雨趋势的增加，广泛观测到的LP变化的增加与土地的重新自然化有关。LP减少影响的区域非常有限，热点与季节性降水和人类活动的变化相关。确定了受LP变更影响最大的地区和市政当局，并可以在SDG 15.3和LDN的框架内支持对政策倡议的识别。