Andrew T. Hudak

Integration of lidar and Landsat ETM+ data for estimating and mapping forest canopy height

Light detection and ranging (lidar) data provide accurate measurements of forest canopy structure in the vertical plane; however, current lidar sensors have limited coverage in the horizontal plane. Landsat data provide extensive coverage of generalized forest structural classes in the horizontal plane but are relatively insensitive to variation in forest canopy height. It would, therefore, be desirable to integrate lidar and Landsat data to improve the measurement, mapping, and monitoring of forest structural attributes. We tested five aspatial and spatial methods for predicting canopy height, using an airborne lidar system (Aeroscan) and Landsat Enhanced Thematic Mapper (ETM+) data: regression, kriging, cokriging, and kriging and cokriging of regression residuals. Our 200-km 2 study area in western Oregon encompassed Oregon State University’s McDonald–Dunn Research Forest, which is broadly representative of the age and structural classes common in the region. We sampled a spatially continuous lidar coverage in eight systematic patterns to determine which lidar sampling strategy would optimize lidar– Landsat integration in western Oregon forests: transects sampled at 2000, 1000, 500, and 250 m frequencies, and points sampled at these same spatial frequencies. The aspatial regression model results, regardless of sampling strategy, preserved actual vegetation pattern, but underestimated taller canopies and overestimated shorter canopies. The spatial models, kriging and cokriging, produced less biased results than regression but poorly reproduced vegetation pattern, especially at the sparser (2000 and 1000 m) sampling frequencies. The spatial model predictions were more accurate than the regression model predictions at locations <200 m from sample locations. Cokriging, using the ETM+ panchromatic band as the secondary variable, proved slightly more accurate than kriging. The integrated models that kriged or cokriged regression residuals were preferable to either the aspatial or spatial models alone because they preserved the vegetation pattern like regression yet improved estimation accuracies above those predicted from the regression models alone. The 250-m point sampling strategy proved most optimal because it oversampled the landscape relative to the geostatistical range of actual spatial variation, as indicated by the sample semivariograms, while making the sample data volume more manageable. We concluded that an integrated modeling strategy is most suitable for estimating and mapping canopy height at locations unsampled by lidar, and that a 250-m discrete point sampling strategy most efficiently samples an intensively managed forested landscape in western Oregon. D 2002 Published by Elsevier Science Inc.

Textural analysis of historical aerial photography to characterize woody plant encroachment in South African Savanna

Transitions from grassland to shrubland through woody plant encroachment result in potentially significant shifts in savanna ecosystem function. Given high resolution imagery, a textural index could prove useful for mapping woody plant densities and monitoring woody plant encroachment across savanna landscapes. Spatial heterogeneity introduced through mixtures of herbaceous and woody plants challenges quantitative assessments of changing woody plant density using remotely sensed imagery. Moreover, woody plant encroachment occurs across decadal time scales, restricting remote sensing analyses to historical aerial photograph records. Heterogeneity in vegetation structure has a significant influence on local pixel variance in high resolution images. We scanned black and white aerial photographs for 18 sites of varying woody plant density, producing images of 2-m grain size. Omnidirectional variograms derived from these images had ranges of approximately 10 m and sills highly sensitive to woody plant density, prompting us to use a textural index to indicate landscape variation in woody plant density. For validation purposes, we measured several woody overstory structural parameters in the field; a factor analysis revealed woody stem count as the best correlate with image texture. Significance of the regression of image texture on woody stem count declined as grain size of the 2-m images was coarsened to simulate that of SPOT and Landsat satellite sensors. At 10-m resolution, our textural index proved a significant indicator of woody plant density. We mosaicked sequential aerial photographs scanned at 10-m resolution and then applied our textural filter, producing maps of historical woody plant distribution that reflected patterns in soil and vegetation type. More accurate maps of canopy structure and structural change are needed to explore potential effects of woody plant encroachment on biophysical and biogeochemical processes at large scales.

Linking the Conservation of Culture and Nature:A Case Study of Sacred Forests in Zimbabwe

This paper examines the role of traditional religious beliefs and traditional leaders in conserving remnant patches of a unique type of dry forest in the Zambezi Valley of northern Zimbabwe. We examined aerial photographs spanning more than three decades, interviewed and surveyed local residents, and met with communities to learn about the environmental history of the forests and the factors that have affected land use in the area. Our results show that forest loss is dramatically less in forests that are now considered sacred, or were in the past connected to sacred forests. This supports our hypothesis that traditional spiritual values have influenced human behavior affecting the forests, and have played a role in protecting them until now. We also found that rates of forest loss have been much higher in an area where traditional leaders are relatively disempowered within the post-independence political system compared to an area where traditional leaders have more power. These findings lead us to conclude that a strategy that links the conservation of culture and nature is likely to be more effective in conserving forests than a strategy that ignores traditional beliefs, values, and institutions.

Mapping fire scars in a southern African savannah using Landsat imagery

The spectral, spatial and temporal characteristics of the Landsat data record make it appropriate for mapping fire scars. Twenty-two annual fire scar maps from 1972–2002 were produced from historical Landsat imagery for a semi-arid savannah landscape on the South Africa–Botswana border, centred over Madikwe Game Reserve (MGR) in South Africa. A principal components transformation (PCT) helped differentiate the spectral signal of fire scars in each image. A simple, nonparametric, supervised classification (parallelepiped) of the PCT data differentiated burned and unburned areas. During most years, fire occurrences and the percentage of area burned annually were lowest in Botswana, highest in MGR, and intermediate in South Africa outside MGR. These fire scar maps are aiding MGR managers, who are endeavouring to restore a more active fire regime following decades of fire exclusion.

Textural analysis of high resolution imagery to quantify bush encroachment in Madikwe Game Reserve, South Africa, 1955-1996

Fire suppression associated with decades of cattle grazing can result in bush encroachment in savannas. Textural analyses of historical, high resolution images was used to characterize bush densities across a South African study landscape. A control site, where vegetation was assumed to have changed minimally for the duration of the image record (1955-1996), was used to standardize textural values between multidate images. Standardized textural values were then converted to estimates of percent woody canopy cover using a simple linear regression model. Results indicate a 30% relative increase in percent woody cover between 1955 and 1996.

Rangeland Mismanagement in South Africa: Failure to Apply Ecological Knowledge

Chronic, heavy livestock grazing and concomitant fire suppression have caused the gradual replacement of palatable grass species by less palatable trees and woody shrubs in a rangeland degradation process termed bush encroachment in South Africa. G razing policymakers and cattle farmers alike have not appreciated the ecological role fire and native browsers play in preventing bush encroachment. Unpredictable droughts are common in South Africa but have deflected too much blame for bush encroachment away from grazing mismanagement. Bush encroachment is widespread on both black and white farms, although the contributing socioeconomic, cultural, and political forces differ. Managers at Madikwe Game Reserve have reintroduced fire and native game animals into a formerly overgrazed system in an attempt to remediate bush encroachment, with encouraging preliminary results. A bush control program is needed that educates cattle farmers about the ecological causes of bush encroachment and encourages the use of fire and native browsers as tools for sustainable grazing management.

Extracting ecological and biophysical information from AVHRR optical data: An integrated algorithm based on inverse modeling

Satellite remote sensing provides the only means of directly observing the entire surface of the Earth at regular spatial and temporal intervals. Key Earth system variables can be obtained from satellite data by integrating appropriate processing, interpretation, and modeling. For example, the amount of photosynthetically active radiation absorbed by plants (APAR) and land surface albedo can be inferred from remotely sensed optical measurements. Radiative transfer model inversion exploits the dependence of reflectance on the relative source-sensor geometry to estimate surface parameters. In contrast, geometrical effects are suppressed in most other approaches. We present an algorithm for the retrieval of fractional APAR (fAPAR), albedo, and other parameters from AVHRR (advanced very high resolution radiometer) reflectance measurements by inverting a modified version of the SAIL (scattering by arbitrarily inclined leaves) canopy radiative transfer model. The model is inverted using an effective bidirectional reflectance factor (BRF) distribution created by aggregating AVHRR data into cells of size comparable to those used in current terrestrial biosphere models (50 × 50 km). Successful inversion results over an area in central Africa are presented and compared with a vegetation index-based analysis and other satellite data. The procedure also provides unique information on phenology derived from timing of changes in leaf optical properties and canopy structure. Our methods are unique in that they explicitly incorporate a priori ecological knowledge in the choice of model parameters and constraints. This approach can eventually be employed at pixel resolution with the EOS sensors, MODIS (moderate-resolution imaging spectrometer) and MISR (multiangle imaging spectro-radiometer).

Deforestation in Mwanza District, Malawi, from 1981 to 1992 as determined from Landsat MSS imagery

Malawi is critically short of fuelwood, the primary energy source for its poverty-stricken populace. Deforestation from 1981 to 1992 in Mwanza District in southern Malawi was assessed using Normalized Difference Vegetation Index (NDVI) values calculated from multitemporal Landsat Multispectral Scanner (MSS) images. A control site, where vegetation change was assumed to be minimal, was used to account for the large effect of phenology on NDVI variability between images, and to reveal more subtle differences indicative of changes in percentage woody canopy cover. The average annual deforestation rate was estimated to be 1.8% in Mwanza District between 1981 and 1992.

Remote sensing of vegetation fires and its contribution to a fire management information system

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then precedes a description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate the practical use of remotely sensed fire information.

Fire scar mapping in a southern African savanna

Multitemporal principal components analyses (PCAs) of pre- and post-burn Landsat Thematic Mapper images were used to map fire scars in Madikwe Game Reserve (MGR), South Africa. Prior to MGRs inception in 1991, when the land was used for extensive cattle ranching, overgrazing and fire suppression lead to bush encroachment. Fire is currently being used to control bush encroachment. Bands 3, 4, 5, 7 and a NDVI band from both pre- and post-burn images were included in both the 1994 and 1996 PCAs. Fire scars comprised the fourth principal component (PC4) in both years. Fire intensities were classified via a density slice of the PC4 data within fire scars. In 1994, fires covered 31% of MGR and in 1996, 56%. In both years, fires were more frequent and intense on soils with lower bush densities (and therefore higher grass fuel loads) than on soils with higher bush densities. These fire scar maps are aiding ongoing fire management efforts in MGR.