**2.3. Remote sensing as a tool for land degradation and desertification assessments**

Methods for monitoring current state and changes of landscapes use the advantages and po‐ tential of satellite‐borne or airborne remote sensing imagery. Most work has focused on identifying the change in detection of decreases in land cover rather than identifying the in‐ versed process [22]. Considerable amount of studies explore the capabilities of remote sens‐ ing on different monitoring applications and different remote sensing approaches and data [17, 23–26].

Remote sensing applications can be summarized mainly in four categories that include: cover classification, estimation of structures, change detection, and modeling [27]. Remote sensing has the potential to be decidedly instrumental in the assessment of degradation processes at a much lower cost than any other method [28, 29]. Assessment (i.e. measurement) and moni‐ toring through remote sensing offer a series of advantages such as consistency of data, fairly near real‐time reporting, and a source for having spatially explicit data [30].

Although there are several approaches to describe land cover changes using remote sensing technology, forest inventory and limited sampling of degradation on the ground are funda‐ mental to its quantification [31–36]. The methods used are unique to each location and strongly dependent on how its components are clearly identified and responsive to accurate measure‐ ment, and how country requirements apply to these methods.

Remote sensing is a suitable tool for the estimation of biomass for large areas, usually at regional or national scales, where field data are scarce [34]. There is an abundance of liter‐ ature that describes the virtues and capabilities of remote sensing‐based methods for for‐ est monitoring assessments [17, 22, 23, 37]. The continuing advances in remote sensing science and technology and the enormous amount of data these platforms and sensors produce daily provide a promising foundation to underpin any degradation monitoring program.

The possibility of integration of optical and multispectral remote sensing data to active sensors such as LiDAR (light detection and ranging) and RADAR (radio detection and ranging), combined with ground data, has gained a significant relevance and a high potential for contributing to the design of degradation assessment and monitoring methodologies.

Direct detection of degradation processes, for example in forest landscapes, relates area changes to, and focuses on, forest canopy damage. These changes in forest attributes occurring during a period of time can be detected using information from natural forest resources inventories (FRI) and some from remote sensing [23, 30, 38]. Medium spatial resolution satellite remote sensing data such as Landsat Thematic Mapper (TM) and SPOT have proven capable of obtaining regional‐scale forest variables [39]. Indirect approaches focus on the spatial distribution and the effects that the evolution of human infrastructure has had on the degra‐ dation of nearby areas. Often, these "indirect" factors are used as "proxies" for newly degraded areas.
