**2.4. MTCI satellite vegetation index**

the intensity of the transmitted light [26]. Chlorophyll meters have been used extensively in agriculture to estimate chlorophyll and nitrogen in different species [27–31] and also in forest studies [15, 32–36]. Furthermore, chlorophyll meters have been used in the indirect assessment

Chlorophyll content estimates in the tropical rainforest are rare. A published generalized homographic model for trees of the Amazon region [15] has been used as standard model to estimate chlorophyll content for more than 700 Amazonian tree species. A comparison of chlorophyll estimation between the homographic model and the second-order polynomial model proposed in this study illustrates good agreement for a wide range of SPAD-502 reading

The accuracy of the SPAD-502 decreases at high chlorophyll index readings. When applying the proposed second-order polynomial model, caution should be taken for readings higher than 80 where estimation increases markedly compared to other optical methods (reflectance indices and PROSPECT) assessed in this study. Moreover, SPAD index has shown to be a

Another spectral method for chlorophyll content estimation is based on reflectance measurements to create pigment indices. Such indices take into account between two and four spectral bands and have shown high accuracy. Despite the literature offers several pigment indices, the majority of them have been tested in just specific plant species or vegetation type. As a result, they have become plant or vegetation specific. Estimations of chlorophyll content based on

Chlorophyll indices are increasingly being used in crops and forest assessments but also in ecology and Earth science. Several calibration models have been described in the literature, most of which, however, have been calibrated and validated in few or closely related plant species with a limited number of samples. Under these conditions, most of the models can only be applied to specific species and environmental conditions [23, 32, 43]. There is no scientific consensus as to whether a universal model can be found that can be applied for species-rich forest stands in different latitudes, phenological stages, and leaf structures [17]. Feret et al. [25] noted this limitation of the spectral indices and proposed new indices for chlorophyll and carotenoid estimation. They were based on a vegetation dataset collected in various ecosystems

Based on the relationship between reflectance and the biochemical and biophysical properties of the leaves and canopies, models have been created in order to simulate the interaction of the light with the plant leaves through the radiative transfer theory. The leaf optical properties spectra (PROSPECT) model describes radiative transfer within a broadleaf with a plate model [44]. Plate models treat internal leaf structure as sheets or plates and calculate multiple reflections of diffuse radiation between these interfaces [13]. PROSPECT is based on the

around the world including a wide variety of plant physiology and leaf structure.

valuable indicator to detect main impacts of land use changes in the tropical forest.

of foliar nitrogen [29, 30, 37], and carotenoid content [29, 38].

54 Tropical Forests - The Challenges of Maintaining Ecosystem Services while Managing the Landscape

reflectance indices have been widely used [23–25, 33, 39–42].

**2.3. Radiative transfer models: PROSPECT model**

(15–95 units).

**2.2. Reflectance indices**

The medium resolution imaging spectrometer (MERIS) terrestrial chlorophyll index (MTCI) is a standard product derived from MERIS satellite from the European Space Agency (ESA), which provides estimations of chlorophyll content of vegetation (amount of chlorophyll per unit area of ground) at global level. MTCI index is simple to calculate, sensitive to high values of chlorophyll content [46, 47] and estimations are independent to soil and atmospheric conditions, spatial resolution, and illumination and observation geometry [48]. Validation of MTCI index and ground chlorophyll content across a range of crop types and environmental conditions resulted in a strong relationship of *R*<sup>2</sup> = 0.8 and root mean square error (RMSE) = 192 g per MERIS pixel [49]. Moreover, the strong relationship of MTCI and canopy chlorophyll content has been used to estimate gross primary production (GPP) across a range of ecosystems. Boyd et al. [50] applied MTCI index, together with radiation information (photosynthetically active radiation—PAR and fraction of photosynthetically active radiation—fPAR), into models which extended the accuracy of GPP estimated.

**Figure 1.** Global coverage of MERIS Terrestrial Chlorophyll Index at 31 May 2011. Processed by Astrium Geo-Information Services. Copyright ESA-2011.

MTCI is computed by the ratio of the difference in reflectance between band 10 and band 9 and the difference in reflectance between band 9 and band 8 of the MERIS standard band setting:

$$MTCI = \frac{R\_{\text{Band10}} - R\_{\text{Band9}}}{R\_{\text{Band9}} - R\_{\text{Band8}}} = \frac{R\_{\tau 53.75} - R\_{\tau 08.75}}{R\_{\tau 08.75} - R\_{681.25}}\tag{1}$$

where *R*753.75, *R*708.75, and *R*681.25 are the MERIS reflectance at wavelength 753.75, 708.75, and 681.25 nm, respectively.

**Figure 1** illustrates the global (Level 3) MERIS terrestrial chlorophyll index (MTCI) estimated at 31 May 2011. Highest MTCI values are located in the tropical forest biomes around the world.
