Detecting forest areas and crops using vegetation indices
Dr. Mohd. Ibrahim Seeni Mohd, Azhar Jj. Salleh
Centre for Remote Sensing
Faculty of Surveying
University Teknologi Malaysia
Locked Bag 791, 80990 Johor Bahru, Malaysia
Abstract
Vegetation Indices (VI) represent a linear transformation of spectral bands that express the spectral behavior of crops and natural vegetation. VI emphasizes spectral contrast between different surface, and therefore have been widely used for enhancing vegetation and classifying agricultural areas. This paper reports on studies carried out in the Bukit Kajang Forest Reserve and surrounding crops areas at Raub, Malaysia with the landsat-5 Thematic Mapper satellite data using various vegetation indices to evaluate their potential in differentiating forest area and major crops. The Perpendicular Vegetation Index ( PVI), Normalized Difference Vegetation Index (NDVI), and Ratio Vegetation Index (RVI) have been evaluated on the basis of their spectral band combinations and rationing for differentiating rubber, oil palm and forest areas. The combination of Mid-Infrared (MIR) band 5 and Visible (VIS) band 2 in the PVI gave the most difference among crops whereas the NDVI and RVI resulted in similar values. Significant differences were found between the forest areas and the other crops thus enhancing the forest areas. Better classification accuracies were achieved by using the PVI compared with other Vegetation Indices.
1.0 Introduction
Several empirical indices have been used as quantitative indicators of vegetation amount They reduce the multidimensional spectral space of vegetated scene to one dimension in order to sense variability in such properties as biomass, leaf areas index, fractional cover and types ( jasinski, 1990). During the past decade the wavelengths used have been restricted to VIS and Near-Infrared (NIR) spectral region. By combining differences and ratios of red ( VIS) and NIR, the vegetation indices respond to i) the relatively high radiation absorption of red light by leaves due to the presence of chlorophyll and ii) the high reflectance of NIR light due to scattering in the leaf internal structure ( Curran, 1980). Common ratio vegetation indices include the NIR/VIS index, and Normalized Difference Vegetation Index [NDVI= (NIR-VIS)/(NIR + VIS)] ( Richardson et al. ( `1991)). NDVI is commonly preferred because undesirable aspects on recorded radiance such as effect of variable illumination resulting from variation in topography can be reduced. Another VI that distinguishes the spectral response contributed by the soil background is the Perpendicular Vegetation Index which is described by Richardson et al. ( 1991) in the form.
PVI = √( RggNIR-RpNIR)2 = ( RggVIS-RpVIS)2 (1)
Where:
PVI is the perpendicular distance between the candidate vegetation point and the soil line,
R
p is the reflectance of a candidate vegetation point for NIR and VIS spectral region, and
R
gg is the reflectance of soil background corresponding to a candidate vegetation point.
Evert et al. ( 1989) described that MIR spectral region reflectance data obtained from TM5 ( 1.55-1.75mm) and TM7 ( 2.08-2.35mm) water absorption band of the Landsat were also useful for estimating vegetation parameters. He showed that the 1.65mmmm and 2.08mm wavelengths gave promise for use in discriminating bare soil from mature field crop. He studied VIS, NIR, and MIR reflectance data for winter wheat and corn, and found that the TM5 and TM7 bands in the MIR spectral region were more useful than the NIR/VIS index (TM4/TM3) for estimating agronomic variables.
This paper reports on the use of various VI calculated from satellite data at selected wavelengths in VIS and NIR spectral region for differentiating vegetation types at the study area. Since the MIR spectral region has been proven useful for agronomic variables by many researchers overseas, this paper will also examine the potential of using MIR wavelengths as input to the Via algorithm in a selected region in Malaysia.
