Eileen H. Helmer

Bringing an ecological view of change to Landsat-based remote sensing

When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser-scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, longterm trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System

We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975-2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age mapping with biomass estimates from the Geoscience Laser Altimeter System (GLAS). Though highly variable, the estimated average biomass accumulation rate of 8.4 Mg ha -1 yr -1 agrees well with ground-based studies for young secondary forests in the region. In isolating the lowland forests, we map land cover and general types of old-growth forests with decision tree classification of Landsat imagery and elevation data. We then estimate aboveground live biomass for seven classes of old-growth forest. TAMA is simple, fast, and self-calibrating. By not using between-date band or index differences or trends, it requires neither image normalization nor atmospheric correction. In addition, it uses an approach to map forest cover for the self-calibrations that is novel to forest mapping with satellite imagery; it maps humid secondary forest that is difficult to distinguish from old-growth forest in single-date imagery; it does not assume that forest age equals time since disturbance; and it incorporates Landsat Multispectral Scanner imagery. Variations on the work that we present here can be applied to other forested landscapes. Applications that use image time series will be helped by the free distribution of coregistered Landsat imagery, which began in December 2008, and of the Ice Cloud and land Elevation Satellite Vegetation Product, which simplifies the use of GLAS data. Finally, we demonstrate here for the first time how the optical imagery of fine spatial resolution that is viewable on Google Earth provides a new source of reference data for remote sensing applications related to land cover.

The Forest Types and Ages Cleared for Land Development in Puerto Rico

On the Caribbean island of Puerto Rico, forest, urban/built-up, and pasture lands have replaced most formerly cultivated lands. The extent and age distribution of each forest type that undergoes land development, however, is unknown. This study assembles a time series of four land cover maps for Puerto Rico. The time series includes two digitized paper maps of land cover in 1951 and 1978 that are based on photo interpretation. The other two maps are of forest type and land cover and are based on decision tree classification of Landsat image mosaics dated 1991 and 2000. With the map time series we quantify land-cover changes from 1951 to 2000; map forest age classes in 1991 and 2000; and quantify the forest that undergoes land development (urban development or surface mining) from 1991 to 2000 by forest type and age. This step relies on intersecting a map of land development from 1991 to 2000 (from the same satellite imagery) with the forest age and type maps. Land cover changes from 1991 to 2000 that continue prior trends include urban expansion and transition of sugar cane, pineapple, and other lowland agriculture to pasture. Forest recovery continues, but it has slowed. Emergent and forested wetland area increased between 1977 and 2000. Sun coffee cultivation appears to have increased slightly. Most of the forests cleared for land development, 55%, were young (1-13 yr). Only 13% of the developed forest was older (41-55+ yr). However, older forest on rugged karst lands that long ago reforested is vulnerable to land development if it is close to an urban center and unprotected.

Diversity and composition of tropical secondary forests recovering from large-scale clearing: results from the 1990 inventory in Puerto Rico.

Abstract The extensive recovery from agricultural clearing of Puerto Rican forests over the past half-century provides a good opportunity to study tropical forest recovery on a landscape scale. Using ordination and regression techniques, we analyzed forest inventory data from across Puerto Rico’s moist and wet secondary forests to evaluate their species composition and whether the landscape structure of older forest affected tree species composition of recovering forests at this scale. Our results support conclusions from studies conducted in Puerto Rico at smaller scales and temperate forests at larger scales that timing of abandonment and land use history are of overwhelming importance in determining the species composition of recovering forests. Forest recovery is recent enough in Puerto Rico that previous land use is clearly evident in current species composition, and creates new forest communities. As demonstrated in other work, physical factors such as elevation and substrate co-vary with land use history, so that the species composition of the forest landscape results from the interplay between biophysical and socioeconomic forces over time. Our results also indicate that increasing the distance to the largest forest patches occurring in the landscape 12 years previous had a small negative impact on species richness but not species diversity or community composition. We conclude that land use history has as much influence in species composition as biophysical variables and that, at the scale of this study, there is no large influence of forest landscape structure on species diversity or composition.

Land Cover and Forest Formation Distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from Decision Tree Classification of Cloud-Cleared Satellite Imagery

Abstract. Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius, testing a more detailed classification than earlier work in the latter three islands. Secondly, we estimate the extents of land cover and protected forest by formation for five islands and ask how land cover has changed over the second half of the 20th century. The image interpretation approach combines image mosaics and ancillary geographic data, classifying the resulting set of raster data with decision tree software. Cloud-free image mosaics for one or two seasons were created by applying regression tree normalization to scene dates that could fill cloudy areas in a base scene. Such mosaics are also known as cloud-filled, cloud-minimized or cloud-cleared imagery, mosaics, or composites. The approach accurately distinguished several classes that more standard methods would confuse; the seamless mosaics aided reference data collection; and the multiseason imagery allowed us to separate drought deciduous forests and woodlands from semi-deciduous ones. Cultivated land areas declined 60 to 100 percent from about 1945 to 2000 on several islands. Meanwhile, forest cover has increased 50 to 950%. This trend will likely continue where sugar cane cultivation has dominated. Like the island of Puerto Rico, most higher-elevation forest formations are protected in formal or informal reserves. Also similarly, lowland forests, which are drier forest types on these islands, are not well represented in reserves. Former cultivated lands in lowland areas could provide lands for new reserves of drier forest types. The land-use history of these islands may provide insight for planners in countries currently considering lowland forest clearing for agriculture.

KIRTLAND'S WARBLERS IN ANTHROPOGENICALLY DISTURBED EARLY-SUCCESSIONAL HABITATS ON ELEUTHERA, THE BAHAMAS

Abstract. To characterize the nonbreeding habitat of Kirtlands Warbler (Dendroica kirtlandii) on Eleuthera, The Bahamas, we quantified the habitat at sites where we captured the warblers and compared these traits with those of random sites and sites of tall coppice. On the basis of a chronosequence of satellite imagery, 153 capture sites ranged in age from 3 to 28 years after human disturbance, mean 14.6 years ± 6.3 (SD). Capture sites had been abandoned after clearing (65%), converted to goat pasture (26%), burned (2%), or were young second growth following unknown disturbance (7%). Canopies in 104 capture plots were lower (mean 1.8 m) than canopies in random plots (mean 2.7 m) and plots of late-successional tall coppice (mean 6.3 m). At seven sites mean foliage density in capture plots was consistently greatest at 0.5 to 1.0 m height, but the sites were heterogeneous for other foliage-height classes <3 m and for time since disturbance, canopy height, stem density, and five ground-cover traits. Plots did not differ by the sex of the captured bird except for a difference (P = 0.05) in foliage density at heights <3 m. Kirtlands Warblers frequently consumed fruit (69% of 499 observations), especially from Lantana involucrata, Erithalis fruticosa, and Chiococca alba. Foliage of these plants was more abundant in capture plots than random plots. Because the warblers consume fruit extensively and fruit is more abundant in early successional habitat, this species, like other nearctic—neotropical migrants that breed in early successional habitats, is absent from mature forests on the wintering grounds.

Mapping land cover and estimating forest structure using satellite imagery and coarse resolution lidar in the Virgin Islands

Current information on land cover, forest type and forest structure for the Virgin Islands is critical to land managers and researchers for accurate forest inventory and ecological monitoring. In this study, we use cloud free image mosaics of panchromatic sharpened Landsat ETM+ images and decision tree classification software to map land cover and forest type for the Virgin Islands, illustrating a low cost, repeatable mapping approach. Also, we test if coarse-resolution discrete lidar data that are often collected in conjunction with digital orthophotos are useful for mapping forest structural attributes. This approach addresses the factors that affect vegetation distribution and structure by testing if environmental variables can improve regression models of forest height and biomass derived from lidar data. The overall accuracy of the 29 forest and non-forest classes is 72%, while most the forest types are classified with greater than 70% accuracy. Due to the large point spacing of this lidar dataset, it is most appropriate for height measurements of dominant and co-dominant trees (R 2 = 72%) due to its inability to accurately represent forest understory. Above ground biomass per hectare is estimated by its direct relationship with plot canopy height (R 2 = 0.72%).

Controls on fallen leaf chemistry and forest floor element masses in native and novel forests across a tropical island

Litter chemistry varies across landscapes according to factors rarely examined simultaneously. We analyzed 11 elements in forest floor (fallen) leaves and additional litter components from 143 forest inventory plots systematically located across Puerto Rico, a tropical island recovering from large-scale forest clearing. We assessed whether three existing, independently-derived, landscape classifications (Holdridge life zone, remotely sensed forest type (leaf longevity combined with geology generalized to karst vs. non-karst), and plot-based measures of forest assemblage) would separate observed gradients. With principal component and regression analyses, we also tested whether climate-, landscape- (geology, elevation, aspect, percent slope, slope position, distance from coast), and stand-scale (tree species composition, basal area, density, stand age) variables explained variation in fallen leaf chemistry and stoichiometry. For fallen leaves, C, Ca, Mg, Na, and Mn concentrations differed by Holdridge life zone and C, P, Ca, Mn, Al, and Fe concentrations differed by forest type, where leaf longevity distinguished C and Ca concentrations and geology distinguished C, P, Ca, Mn, Al, and Fe concentrations. Fallen leaf C, P, Ca, and Mn concentrations also differed, and N concentrations only differed, by forest assemblage. Across several scales, fallen leaf N concentration was positively related to the basal area of putatively N2-fixing tree legumes, which were concentrated in lower topographic positions, providing for the first time a biological explanation for the high N concentrations of fallen leaves in these locations. Phosphorus concentrations in fallen leaves by forest assemblages also correlated with the basal area of N2-fixing legumes, and P and N concentrations decreased with mean age of assemblage. Fallen leaves from younger (<50 yr, 86% of the plots) and often novel forests had higher P, Fe, and Al and lower C concentrations and lower C/P and N/P ratios than fallen leaves from older forests, the latter due to a decrease in P rather than changes in N. These findings suggest that both N and P availability may currently be greater on the island than pre-deforestation, and substantiate the unique roles that state factors play in contributing to the spatial heterogeneity of fallen leaf chemistry.

Predictions of Tropical Forest Biomass and Biomass Growth Based on Stand Height or Canopy Area Are Improved by Landsat-Scale Phenology across Puerto Rico and the U.S. Virgin Islands

Remotely-sensed estimates of forest biomass are usually based on various measurements of canopy height, area, volume or texture, as derived from LiDAR, radar or fine spatial resolution imagery. These measurements are then calibrated to estimates of stand biomass that are primarily based on tree stem diameters. Although humid tropical forest seasonality can have low amplitudes compared with temperate regions, seasonal variations in growth-related factors like temperature, humidity, rainfall, wind speed and day length affect both tropical forest deciduousness and tree height-diameter relationships. Consequently, seasonal patterns in spectral measures of canopy greenness derived from satellite imagery should be related to tree height-diameter relationships and hence to estimates of forest biomass or biomass growth that are based on stand height or canopy area. In this study, we tested whether satellite image-based measures of tropical forest phenology, as estimated by indices of seasonal patterns in canopy greenness constructed from Landsat satellite images, can explain the variability in forest deciduousness, forest biomass and net biomass growth after already accounting for stand height or canopy area. Models of forest biomass that added phenology variables to structural variables similar to those that can be estimated by LiDAR or very high-spatial resolution imagery, like canopy height and crown area, explained up to 12% more variation in biomass. Adding phenology to structural variables explained up to 25% more variation in Net Biomass Growth (NBG). In all of the models, phenology contributed more as interaction terms than as single-effect terms. In addition, models run on only fully-forested plots performed better than models that included partially-forested plots. For forest NBG, the models produced better results when only those plots with a positive growth, from Inventory Cycle 1 to Inventory Cycle 2, were analyzed, as compared to models that included all plots