*3.1.2.1. Bi-temporal analysis*

Canopy cover has already been used as an indicator to monitor and map forest degradation in various contexts [32, 35]. Some studies [42] evaluated forest degradation based on canopy closure classes, namely non‐degraded (>70%), moderately degraded (40–70%), degraded (10– 40%), and severely degraded (<10%). Another study [43] assessed forest degradation using canopy disturbance as a result of gaps produced by logging, road construction, and skid trails as an indication of forest degradation. Another approach suggested for mapping forest degradation and deforestation was the use of canopy cover combined with spectral mixture

NPP determines the rate of atmospheric carbon sequestration and storage by vegetation [45, 46]. NPP has been used previously as an indicator of ecosystems' decline [47–49]. These approaches open the door to the possibility of using NPP as both a baseline and indicator of forest degradation [50], based on the assumptions that losses of canopy cover will affect the

NPP estimations are regularly based on the light use efficiency (LUE) theory [51]. The LUE theory is estimated on two broad assumptions. First, NPP is related to the absorbed photo‐ synthetically active radiation, APAR, where LUE determines the amount of dry matter produced per unit of APAR. Second, environmental stresses such as low temperature or water shortage have an adverse impact over LUE [52, 53]. Production efficiency models (PEM) are developed from the LUE theory. They require inputs of meteorological data and take advant‐ age of available satellite data to derive the fraction of absorbed photosynthetically active radiation, fPAR [53]. Examples of production efficiency models include the CASA model (Carnegie‐Ames‐Stanford approach) [54], C‐Fix [55–57], and MOD17 [48] used for monitoring

Net primary productivity is employed by the global land degradation assessment in Drylands (LADA) project [21], where NPP is highly relevant to the assessment of degradation. NPP can be readily used as a direct indicator of the condition and trend of changes in the state of ecosystems over time, whereby the decrease in NPP over time would signal the degradation of ecosystems. Through the LADA project conducted by the FAO [18] and within the UNCCD framework [58], mapped out land degradation at national, regional, and local scales in Ethiopia

One of the most frequent uses of remote sensing is change detection [59]. The stock pile of optical satellite imagery freely available (e.g. Landsat program) [13] offers opportunities for the reconstruction and understanding of landscape dynamics. Direct comparison of pairs of images (bi‐temporal analysis) is perhaps the most common approach to change detection

Although many change detection methods have been developed [61–63], the question of how to reliably map land‐use change remains a central challenge. Land‐use change (LUC) can result

analysis, normalized difference fraction index, and a decision tree classification [44].

*3.1.1.2. Net primary productivity*

8 Land Degradation and Desertification - a Global Crisis

capacity of the forest to fix carbon and reduce NPP rates.

NPP at regional and global scale from satellite remote sensing data.

using NPP as one of the major indicators in their studies.

*3.1.2. Trajectory analysis and change detection*

[60].

The bi‐temporal analysis is perhaps the most used method to perform change detection on remote sensing satellite imagery [70]. The bi‐temporal change detection methods range from simple image differencing methods to statistically based methods [71]. Change detection methods have been widely used to identify changes in classes (e.g. land cover classification) or the difference between a pair of images (image differencing) [70].
