Image texture as a remotely sensed measure of vegetation structure
نویسندگان
چکیده
a r t i c l e i n f o Keywords: Band 4 Foliage-height diversity Horizontal vegetation structure Image texture Infrared air photo Landsat NDVI Wildlife habitat Ecologists commonly collect data on vegetation structure, which is an important attribute for characterizing habitat. However, measuring vegetation structure across large areas is logistically difficult. Our goal was to evaluate the degree to which sample-point pixel values and image texture of remotely sensed data are associated with vegetation structure in a North American grassland–savanna–woodland mosaic. In the summers of 2008–2009 we collected vegetation structure measurements at 193 sample points from which we calculated foliage-height diversity and horizontal vegetation structure at Fort McCoy Military Installation, Wisconsin, USA. We also calculated sample-point pixel values and first-and second-order image texture measures, from two remotely sensed data sources: an infrared air photo (1-m resolution) and a Landsat TM satellite image (30-m resolution). We regressed foliage-height diversity against, and correlated horizontal vegetation structure with, sample-point pixel values and texture measures within and among habitats. Within grasslands, sa-vanna, and woodland habitats, sample-point pixel values and image texture measures explained 26–60% of foliage-height diversity. Similarly, within habitats, sample-point pixel values and image texture measures were correlated with 40–70% of the variation of horizontal vegetation structure. Among habitats, the mean of the texture measure 'second-order contrast' from the air photo explained 79% of the variation in foliage-height diversity while 'first-order variance' from the air photo was correlated with 73% of horizontal vegetation structure. Our results suggest that sample-point pixel values and image texture measures calculated from remotely sensed data capture components of foliage-height diversity and horizontal vegetation structure within and among grassland, savanna, and woodland habitats. Vegetation structure, which is a key component of animal habitat, can thus be mapped using remotely sensed data.
منابع مشابه
Spatiotemporal analysis of remotely sensed Landsat time series data for monitoring 32 years of urbanization
The world is witnessing a dramatic shift of settlement pattern from rural to urban population, particularly in developing countries. The rapid Addis Ababa urbanization reflects this global phenomenon and the subsequent socio-economic and environmental impacts, are causing massive public uproar and political instability. The objective of this study was to use remotely sensed Landsat data to iden...
متن کاملImage Texture Predicts Avian Density and Species Richness
For decades, ecologists have measured habitat attributes in the field to understand and predict patterns of animal distribution and abundance. However, the scale of inference possible from field measured data is typically limited because large-scale data collection is rarely feasible. This is problematic given that conservation and management typical require data that are fine grained yet broad...
متن کاملUsing Ndvi Image Texture Analysis for Bushfire-prone Landscape Assessment
ABSTRACT: Bushfire, as a major external ecological factor, diversifies bushland environments. Monitoring bushfire-prone landscape patterns and vegetation recovery after fires is critical for the long-term bushland management. Landscape ecology studies using remotely sensed imagery have been effective to identify the relationship between landscape patterns and ecological processes. This paper us...
متن کاملA new wavelet based multi-resolution texture segmentation scheme of remotely sensed images for vegetation extraction
Texture segmentation via wavelet transform traditionally adopts textural features based approach. However, applying this method can lead to oversegmentation problems. To overcome this limitation, we propose a new scheme of texture segmentation. The proposed approach will be applied to remotely sensed images for vegetation extraction. The key idea is that we precede wavelet transform by a prelim...
متن کاملA model-based approach for mapping rangelands covers using Landsat TM image data
Empirical models are important tools for relating field-measured biophysical variables to remotely sensed data. Regression analysis has been a popular empirical method of linking these two types of data to estimate variables such as biomass, percent vegetation canopy cover, and bare soil. This study was conducted in a semi-arid rangeland ecosystem of Qazvin province, Iran. This paper presents t...
متن کامل