**1. Introduction**

The Amazon rainforest holds half of the tropical forested area of the world [1] and accounts for 30% of global biomass productivity [2] and 25% of global biodiversity [3]. Evaporation and

© 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.

condensation in tropical forests play a pivotal role in the regional and global atmospheric circulation [4], and the rivers' system produces about 20% of the world's fresh water discharge [5]. Photosynthesis and respiration process are more than twice the carbon of the annual rate of anthropogenic fossil fuel emissions [6]. Tropical forests store large amounts of carbon in high diversity ecosystems and play an important role in the global carbon cycle due to its net primary productivity (NPP). According to the estimates of Ref. [7], Amazon forests contain 70–80 billion metric tons (Pg or 1015 g) of carbon in plant biomass and assimilate 4–6 Pg of carbon each year in NPP. Despite its importance, a better understanding is needed of the interactions between the tropical forest and the global processes, such as climate change. During the last decades, the Amazon forest has been threatened by deforestation, selective logging, hunting, fire, and global and regional climate changes [4, 5].

Tropical forest deforestation and degradation have raised international concerns since they contribute approximately 20% to the global greenhouse gases (GHGs) emissions [8]. Reducing emissions from deforestation and forest degradation (REDD) is a United Nations Framework Convention on Climate Change (UNFCCC) initiative that developed a financial framework and mechanisms to reduce forest losses and the associated GHGs emissions aiming to prevent further deforestation and consequently mitigate climate change.

Deforestation is defined as the "permanent" conversion of a forest type to another land cover. "Forest degradation" is a reduction in biomass density within a forest cover. The relative contribution of deforestation and degradation to the net emissions of carbon is not readily distinguished [9]. Research has aimed to quantify global deforestation from satellite and census data, but there is an ongoing debate on the uncertainties of the estimates [10]. On the other hand, forest degradation has been more difficult to measure with remote sensing and there are no estimates for the entire tropics [9]. Therefore, accurate estimations of photosynthetic activity of forested areas are needed to quantify forest degradation and evaluate environmental services provided by flora in the tropical forest.

Photosynthesis is probably the most important biochemical process on earth. It allows plants to absorb certain wavelengths of the incoming radiation from the sun and transform its energy into organic compounds. Photosynthetically active radiation (PAR) is the amount of sunlight in the 400–700 nm wavelength range that is available for photosynthesis. Its agents are the photosynthetic pigments in the chloroplasts of which chlorophyll is the most important.

The leaf chlorophyll content is closely related to the plant's health and physiology. This characteristic has been considered to assess vegetation stress in agricultural areas and forest plantations [11–14], but studies of chlorophyll content in tropical rainforest environments, and specifically in the Amazon rainforest, are rare [15, 16]. A better knowledge of leaf chlorophyll content in the tropical forest is required to contribute to detecting and modeling vegetation stress during drought or pollution events by using satellite data and in this way better understand the potential of photosynthetic capacity and its implications in regional and global carbon cycle and climate models.

Traditional methods for estimating pigment content in vegetation need to be performed in a well-equipped laboratory. They require the extraction of plant pigments from the leaves by applying organic solvents such as dimethyl sulfuoxide (DSMO), methanol, ethanol, acetone, or ether. Depending on the solvent being used, the position of the maximum absorption of plant pigments varies due to the differences in polarity and the loss of pigment-protein interaction [17]. The extracted foliar solution is analyzed by a spectrophotometer in specific absorption wavelength ranges. Finally, absorbance is converted to chlorophyll concentration by applying equations described in the literature [18–21].

Alternative, nondestructive methods for chlorophyll estimation are available from spectral methods for plant pigment estimation. These methods are based on measuring light reflectance and transmittance properties of the vegetation using field spectroradiometers that can be carried in a rucksack, or from spectroradiometers on board of drones, planes, and satellites. They provide indirect estimations of relative pigment content expressed as an index, which needs to be converted to foliar pigment content through often a linear, a polynomial, or an exponential model. During the years, various vegetation indices (VIs) have been developed and applied to remotely sensed satellite images to quantitatively characterize the physiological status of vegetation. VIs are dimensionless measures that indicate relative abundance and activity of green vegetation, including leaf-area-index (LAI), percentage green cover, chlorophyll content, green biomass, and absorbed photosynthetically active radiation (APAR) [22]. VIs are obtained by adding, multiplying, or taking ratios of reflectance in two or more spectral bands of a pixel. These indices are classified into red/NIR ratios, green, red edge, and derivative indices. A useful description of chlorophyll indices can be found in [12, 17] and carotenoid indices [23–25].

This chapter focuses on the analysis of several optical approaches to estimate chlorophyll content in the tropical forest. The study sites were carefully selected across of a forest gradient degradation caused by land uses changes during the last decades. The optical approaches considered are transmittance, reflectance, and radiative transfer models at leave levels; and satellite-derived vegetation indexes at regional level. The objective of this study was to identify suitable methods to detect forest degradation caused by land use changes, deforestation, forest degradation, and pollution in the Amazon rainforest.
