**1. Introduction**

Land degradation and desertification not only contribute to the effects of climate change but also to the loss of productivity, biodiversity, and functionality of forest landscapes. Land use

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

change and associated processes are responsible for around 10% of net global carbon emis‐ sions1 . Land degradation and desertification understood as the loss of productive capacity of the land [1] affect ecosystem productivity, socioeconomic problems, and food security. The UnitedNations through the United Nations Convention to Combat Desertification (UNCCD) seeks to identify and define strategies that support sustainable regional developmentto reverse and prevent desertification and land degradation. The UNCCD works to help countries to improve living conditions of people in drylands and to maintain and restore land and soil productivity.

One of the main issues in the land degradation and desertification programs is the requirement of robust methods to quantify degradation [2]. The fundamental challenge is providing a reliable account of it, and remote sensor techniques should be reliable and continuous to be a source of information [3–5]. To develop a regional and local mechanism to reverse and prevent degradation, it is imperative then to define monitoring and assessing strategies. The constant and exponential increase of remote sensing technologies offers different options to evaluate phenomena such as land degradation. Organizations dedicated to the production of new remote sensing technologies have implemented new satellite sensors with higher spatial resolution (e.g. IKONOS‐2, QuickBird‐2,SPOT‐5) which indicates a new age of terrestrial observation and digital mapping [2, 6–9].

Satellite imagery has been taking information from the Earth's surface for last 40 years in a continuous and reliable way (i.e. Landsat program). Multispectral satellite imagery such as Landsat has opened new avenues for understanding ecological and land cover dynamics [10]. Landsat mission has been collecting imagery since 1972, providing a record of the status and dynamics of the Earth [11, 12]. Changes to policy data in 2008 make free and available the Landsat archive to any user [13]. The free distribution policy increased the supply of imagery dramatically; thus, the use and analysis of the Landsat archive have increased the opportunities to research in a variety of disciplines [10].

Optical remote sensing has been improved by spatial resolution (pixel size), spectral resolution (number of wavebands), radiometric resolution (sensibility to detect radiation changes), and temporal resolution (data acquisition frequency), which means getting capabilities of meas‐ urement in quasi‐real‐time [14–17]. This scenario opens up the possibility to implement powerful monitoring strategies by taking advantage of the free database policies that many entities have today. Mexico is the perfect example; almost all spatial information is freely available through different government websites. Therefore, some indicators related to degradation are available to be estimated by using remote sensing and ground data. The symbols used are capable, through trajectory or time series analysis, of detecting and mapping out changes over time.

The chapter examines the capabilities of freely available remote sensing, combined with field data, in deriving some degradation indicators. The main idea is the construction of a platform for regional land degradation monitoring and assessment. One of the main assumptions of

<sup>1</sup> IPCC (2013) Intergovernmental Panel on Climate Change. The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.

this approach is that it can be replicated in different regions of the developing world. Addi‐ tionally, the cost of applications is minimal if remote sensing and field data are available.
