Comparing MODIS and near-surface vegetation indexes for monitoring tropical dry forest phenology along a successional gradient using optical phenology towers

Abstract

Tropical dry forests (TDFs) present strong seasonal greenness signals ideal for tracking phenology and primary productivity using remote sensing techniques. The tightly synchronized relationship these ecosystems have with water availability offer a valuable natural experiment for observing the complex interactions between the atmosphere and the biosphere in the tropics. To investigate how well the MODIS vegetation indices (normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)) represented the phenology of different successional stages of naturally regenerating TDFs, within a widely conserved forest fragment in the semi-arid southeast of Brazil, we installed several canopy towers with radiometric sensors to produce high temporal resolution near-surface vegetation greenness indices. Direct comparison of several years of ground measurements with a combined Aqua/Terra 8 day satellite product showed similar broad temporal trends, but MODIS often suffered from cloud contamination during the onset of the growing season and occasionally during the peak growing season. The strength of the in-situ and MODIS linear relationship was greater for NDVI than for EVI across sites but varied with forest stand age. Furthermore, we describe the onset dates and duration of canopy development phases for three years of in-situ monitoring. A seasonality analysis revealed significant discrepancies between tower and MODIS phenology transitions dates, with up to five weeks differences in growing season length estimation. Our results indicate that 8 and 16 day MODIS satellite vegetation monitoring products are suitable for tracking general patterns of tropical dry forest phenology in this region but are not temporally sufficient to characterize inter-annual differences in phenology phase onset dates or changes in productivity due to mid-season droughts. Such rapid transitions in canopy greenness are important indicators of climate change sensitivity of these already endangered forest ecosystems and should be further monitored using both ground and satellite approaches.

MODIS and PROBA-V NDVI Products Differ when Compared with Observations from Phenological Towers at Four Tropical Dry Forests in the Americas

“…These two sites present a mosaic of forest covers at different stages of secondary succession, which is surrounded by an agricultural matrix [33]. The LC-SP tower height is close to 15 m. At the PEMS-EMSS there are four towers located along a successional gradient, as follows: [18] for a detailed description of these forest sites). The height of these towers varies between sites; however, these maintain a distance close to 3-6 m above the forest canopy.…”

“…In this paper, we analyze how well NDVI satellite products from MODIS (Aqua and Terra) and PROBA-V are associated with NDVI derived from near-surface observations at four sites in the TDF located across the Americas. This work expands on previous regional studies that compared NDVI satellite products to optical phenology towers [7,18,30] by exploring three questions, as follows: (i) How similar are satellite NDVI time series to near-surface NDVI time series? (ii) How variable are the differences in standardized NDVI values between satellite and near-surface observations during wet and dry seasons or ENSO months?…”

“…Although the study of the vegetation phenology in the temperate regions using vegetation indices is well documented, this kind of study in tropical dry forests (TDFs) is limited [17,18]. At a regional scale, for example, the application of vegetation indices to study the TDF phenology has been used to characterize vegetation types [19], succession states [18], and the ecosystem productivity [20,21]. At a continental or global scale, however, these types of applications are even scarcer and tend to be focused on characterizing different ecosystems [6,22,23].…”

“…Due to their fragmentation and disturbance, the TDF tend to be associated with forest patches of different ages [27], where the species composition and their structure depends on the successional stages of these patches [28,29]. These elements of composition and structure of the forest, which vary with the successional stages, affect the vegetation indices captured by satellites and their phenology [18]. As such, a good understanding of TDF phenological expressions is essential to unravelling key ecological processes affecting these ecosystems' functioning as well as their resilience to extreme meteorological events such as El Nino Southern Oscillation (ENSO).…”

Crop classification from Sentinel-2-derived vegetation indices using ensemble learning

“…Some spectral indices, which are combinations of spectral measurements at different wavelengths, have been used to evaluate phenology or quantify biophysical parameters [2][3][4][5] . As a result, they have also made crop maps more accurate in previous studies 6 and the abilities of optical remote sensing data have been improved for monitoring agricultural fields.…”