Nicholas Cuba

Modelling dry season deciduousness in Mexican Yucatán forest using MODIS EVI data (2000–2011)

This study maps interannual variation in the spatial extent of deciduousness in the dry tropical forests of the southern Yucatán (Mexico) from 2000 to 2011 using seasonal variability thresholds based on Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data and relates deciduousness to precipitation- and temperature-derived climate variables using linear regressions. The annual occurrence of deciduousness is most frequently observed in forests located in a regional rain shadow at moderate elevations. Regression results suggest that deciduousness is more strongly associated with atypically hot conditions (–2°C; R 2 = 0.44) than with atypically dry conditions (R 2 = 0.19), in contrast to other phenological processes (e.g. leaf growth, peak productivity) driven primarily by precipitation.

Mapping licit and illicit mining activity in the Madre de Dios region of Peru

Since the early 2000s, the Madre de Dios Region of southern Peru has experienced rapid expansion of both licit and illicit mining activities, in the form of artisanal and small-scale mining (ASM). ASM typically takes place in remote, inaccessible locations and is therefore difficult to monitor in situ. This paper explores the utility of Landsat-5 imagery via decision tree classification to determine ASM locations in Madre de Dios. Spectral mixture analysis was used to unmix Landsat imagery, using WorldView and QuickBird l imagery to aid spectral endmember selection and validate AMS maps. The ASM maps had an overall area-weighted accuracy of 96% and indicated a large proportion of illicit ASM activity (~65% of all ASM in the study area) occurring outside the permitted concessions. Holistic visual comparison of ASM output maps with reference imagery showed that these methods produce reasonable, realistic maps of mined area extent.

Local variability in the timing and intensity of tropical dry forest deciduousness is explained by differences in forest stand age

Tropical Dry Forest deciduousness is a behavioral response to climate conditions that determines ecosystem-level carbon uptake, energy flux, and habitat conditions. It is regulated by factors related to stand age, and landscape scale variability in deciduous phenology may affect ecosystem functioning in forests throughout the tropics. This study determines whether observed phenological differences are explainable by forest age in the southern Yucatán Peninsula in Mexico, where forest clearing for shifting cultivation has created a mosaic of forest stands of varying age. Matched-pair statistical tests compare neighboring forest pixels of different age class (12–22 years versus 22+ years) and detect significant differences in Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI)-derived metrics related to the timing and intensity of deciduousness during three dry seasons (2008–2011). In all seasons, young forests exhibit significantly more intense deciduousness, measured as total seasonal change of EVI normalized by annual maximum EVI (p < 0.001), and larger normalized EVI change during successive dry season months relative to start-of-dry-season EVI (p < 0.001), than neighboring older forests subject to similar environmental conditions.

Cross-Scale Correlation between In Situ Measurements of Canopy Gap Fraction and Landsat-Derived Vegetation Indices with Implications for Monitoring the Seasonal Phenology in Tropical Forests Using MODIS Data

Deciduousness in dry tropical forests results in substantial seasonal changes to canopy gap fractions. The characterization of such structural properties over large areas is necessary for understanding energy and nutrient distribution within forest ecosystems. However, a spatial extrapolation of measurements from relatively few, spatially-concentrated field observations can yield estimated values that have questionable accuracy and precision at regional scales. This paper uses linear regression models to compare measurements of canopy gap fraction from in situ digital cover photography in the dry tropical forest of the Southern Yucatán, Mexico, to measurements of seasonal vegetation change based on three vegetation indices—the Normalized Difference Vegetation Index (NDVI), two-band Enhanced Vegetation Index (EVI2), and the Normalized Difference Water Index (NDWI)—derived from Landsat-7 ETM+ and Landsat-8 Operational Land Imager (OLI) data to gauge the ability of standardized combinations of multispectral reflectance data to accurately describe the intensity of deciduousness that occurs during the dry season. Discrete observations are compared, as well as spatially summarized values at coarser spatial scales. Model R2 values are greater at coarse spatial scales for all vegetation indices. Models of in situ measurements of gap fraction and Landsat NDWI normalized seasonal change exhibit stronger correlation than do models that feature NDVI or EVI2 (R2 = 0.751 and Mean Absolute Error = 0.04 after aggregation, R2 = 0.552 and MAE = 0.07 for observation-level data). Based on its comparatively strong correlation with field observations, NDWI is adapted to a Moderate Resolution Imaging Spectroradiometer (MODIS) time series and used for spatial extrapolation and the monitoring of canopy conditions. NDWI values derived from MODIS data are regressed against Tropical Rainforest Measuring Misson (TRMM) rainfall data over the period 2000–2011, and the regression results are compared to those of a prior study that used regression to explain the variation of a MODIS EVI using TRMM rainfall data. A MODIS NDWI time series reveals stronger correlation (R2 = 0.48 in deciduous forests) with TRMM accumulated (three-month) rainfall data than a MODIS EVI time series. The results indicate that an NDWI time series can accurately describe a variability of canopy leaf abundance during the dry season and could be an alternative basis of long-term monitoring of season phenology in a dry tropical forest.

Modelling tropical dry forest deciduousness using spatially downscaled TRMM data

Increases in the intensity and spatial extent of dry season deciduousness in the tropical dry forests of the Mexican Yucatán may impact biosphere-atmosphere interactions. Issues of data scale affect characterization of the relationship between precipitation and vegetation leaf canopy condition using remotely sensed measurements of precipitation. This paper examines the use of a set of spatial and topographical methods to downscale rainfall data to account for observed differences in total monthly rainfall measurements at weather stations (N=22) and measurements from the Tropical Rainfall Measuring Mission. Each is evaluated by the resulting increase in spatially-averaged coefficient of determination from a per-pixel (0.01 deg.) linear regression model of MODIS EVI and contemporaneous and 1-month-lagged precipitation image time series (2000-2001). Increases in model explanatory power are observed for all downscaling techniques, with AR2 ranging from 0.024 to 0.046. Results suggest spatial variability of sensitivity to water-scarce conditions within semi-deciduous forests in the area.