Abstract

Currently, land degradation is recognized as a major development challenge, it refers to productivity declining or loosing and to the biological or economic value of the land, it can be the result of land use or management practices. Monitoring land degradation indicators is crucial to combat desertification and restore degraded land and soil in order to achieve land degradation neutrality targets within the Sustainable Development Goals agenda. The United Nations Convention to Combat Desertification (UNCCD) has adopted three sub-indicators for monitoring and assessing land degradation (Trends in Land Cover, Land Productivity and Carbon Stocks), these three indicators are used to estimate the proportion of land that is degraded over the total land area, which is also Sustainable Development Goal (SDG) indicator 15.3.1. Remote sensing is an essential tool for monitoring map changes in soil properties and condition. In this study, we focus on one of the sub-indicators, namely the land productivity trends, which we try to identify by presenting a new approach based on three main parameters; trend, state and performance at the pixel level (30 m), using Google Earth Engine (GEE), as well as the area of our study is the Souss-Massa Region, Morocco. The use of the aggregation of time series of Normalized Difference Vegetation Index (NDVI) observations for 15 years (2001-2015), derived from Landsat satellite imagery and combined with the auxiliary information for validation.

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