Sustainable Develop. Goal indicator 15.3.1 measures the proportion of degraded land.
•The Land Productivity Dynamics indicator can be used as part of the SDG 15.3.1.
•LPDynR is a new tool to calculate the Land Productivity Dynamics indicator.
•LPDynR uses time series of remote sensed vegetation indices.
•LPDynR produces a 5-class map ranging from declining to increasing productivity.

The United Nations Sustainable Development Goal 15 (Life on Land), adopted the indicator 15.3.1 to measure the Land Degradation Neutrality. This indicator is based on three sub-indicators: (1) Trends in Land Cover, (2) Land Productivity and (3) Carbon Stocks. The Land Productivity sub-indicator refers to the total above-ground Net Primary Production and reflects changes in health and productive capacity of the land. It can be calculated using the Land Productivity Dynamics approach, which performs a combined assessment of the long term tendency of change of land productivity and its current level relative to homogeneous land areas.

Here, the authors present the the R-based tool LPDynR, which implements the Land Productivity Dynamics approach for the calculation of the Land Productivity sub-indicator. LPDynR ingests vegetation-related indices derived from time series of remote sensed imagery.

The final indicator is a 5-class map, ranging from declining to increasing land productivity. As an example of LPDynR functionalities and applicability, we present a case study for Europe. First, we show the general way to calculate the indicator for the entire time series (2000–2019), explained in a step by step process. Secondly, we show how to alternatively calculate the indicator based only on the long term tendency of change, but we evidence the added value of including the current level of productivity to refine the final indicator.

Finally, we present some code for the calculation of “partial indicators” in terms of time scale along the observation period, which may help the user to understand the land productivity dynamics within the time series, as well as to assess the stability of the final product. While the indicator shows a general positive dynamics across Europe during the period 2000–2019, some of the partial maps show more negative trends, demonstrating the highly fluctuating character of vegetation.
Following a “one-out-all-out” process, the indicator identifies an area as degraded if one of the sub-indicators shows degradation. The three sub-indicators must be comparable among territories and based on standardized sources and methods. The data can be collected through existing sources, such as maps, reports or databases, but also can be derived from Earth observation (EO) imagery using remote sensing tools.

The Land Productivity sub-indicator (LP), addressed in this document, approximates the dynamics of the total above-ground net primary production (NPP; i.e. total energy fixed by plants minus their respiration). Such energy is transformed into biomass which, in turn, allows ecosystems to develop their functions and deliver essential services. Therefore, the Land Productivity sub-indicator reflects changes in health and productive capacity of the land and its declining trends can be usually understood as land degradation (Cherlet et al., 2018, Prince and Becker-Reshef, 2009, Yengoh et al., 2015).

The World Atlas of Desertification (Cherlet et al., 2018) suggests that the LP sub-indicator can be calculated using the Land Productivity Dynamics (LPD) approach. LPD was first developed by Ivits and Cherlet (2013) and is the methodological basis of the LPDynR tool presented in this article. In addition, Sims et al. (2021) reports as the only Land Productivity Dynamics global product available so far the one calculated with this same approach, and provided by the Joint Research Centre (European Commission) to the UNCCD to assist the countries for the calculation of the LP sub-indicator.