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Agriculture / Soil
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Agriculture Applications Of Remote Sensing : Paddy Yield Estiamtion form Landsta-5 Thematic Mapper Data
Dr. Mohd Ibrahim Seeni Mohd , Samsudin Ahmad, Adeli Abdullah
Centre for Remote Sensing
Faculty of Surveying and Real Estate
University Technology Malaysia
Locked Bat 791
80990 Johor Bahru, Malaysia
Abstract
Satellite remote sensing techniques can provide resource managers an efficient and economical means of acquiring timely data for the development and management of our natural resources. In comparison with traditional methods, these techniques have the inherent properties of being able to provide synoptic observations with high observational density over relatively areas.
This paper reports on a study that have been carried out to estimate paddy yield from the Landsat-5 Thematic Mapper (TM) data in the Sungai Besar area in the state of Selandgor, Malaysia. In this study, two types of vegetation index (VI) have been used together with some field data to derive relationships between VI and yield, namely the Ratio Vegetation Index (RVI) and the Normalized Difference Vegetation Index (NDVI). A linear relationship has been obtained between RVI and NDVI with yield. The yield estimated derived from the satellite data have been found to be 30% higher than the field estimates. This is due to the difference in the paddy phenology cycle at the time the satellite data were acquire and the time the field measurements were taken.
1.0 Introduction
Remote sensing and its associated image analysis technology provides access to spatial information on a planetary scale. New detectors and imaging technologies are increasing the capability of remote sensing to acquire digital spatial information at very fine resolutions in an efficient manner (Ehlers et al. 1989). Up-to-date information of features and phenomena on the earth can be derived in a short duration of time.
This paer describes a study that was carried out to estimate paddy yield from vegetation indices (VIs) derives from the Landsat-5 Thematic Mapper (TM) satellite data in the Sungai Besar are in Selangor, Malaysia. In this study two types of vegetation index have been used, namely the Ratio Vegetation Index (RVI) and the Normalized Difference Vegetation Index (NDVI). Some field data that were obtained at the study area have also been used to relate paddy yield with vegetation index.
2.0 Paddy Yield Estimation
Remote sensing has potential not only in identifying crop classes but also in the estimation of crop area and yield. The examination of the relationships between vegetation indices and yield has been frequently studied over the years and has been shown the useful for yield prediction purposes. For example, Major et al (1986) have shown usefulness of some VIs to estimate some leaf area index (LAI), biomass and grain production for cereals from radiometric measurements. Tucker et al (1980) found a strong relationship between specific spectral data and yield. The resulting plots of spectral data against time give a distinctive pattern which when integrated could be related to yield. All these relationships have a high correlation with yield. In another study, Green and Invins (1985) also proved that VIs relate strongly to biomass, and have been found to relate directly to yield. Rudoff and Batista (1990) have indicated that spectral data whentransformed into VIs have great potential to be used in wheat yield prediction models tropical regions.
Since VIs have been shown to be useful for yield estimation, this study assesses two types of VIs derived from the Landsar-5 TM satellite data for estimating paddy yield in the Sungai Besar area in Selangor.
2.1 Vegetation Indices
Several empirical indices have been used as quantitative indicators of vegetation amount. They reduce the multimensional spectral space of vegetated scene to one dimension in order t sense variability in such properties as biomas, leaf area index, fractional cover and types (Jasinski 1990). In his study, two types of VIs have been used, namely the Ratio Vegetation Index (RVI) and the Normalized Difference Vegetation Index (NDVI). The RVI involves the division of two spectral bands i.e the infrared band divided by the red band. However, the RVI is affected by the 'noise' present in the image due to factors such as atmospheric conditions. The NDVI is commonly preferred because it reduces the effects of atmospheric conditions and topographical variations. The NDVI is the ratio between the difference in the infrared and red bands and the sum of bands , i.e
The infrared bands used in the study are band 4 (0.76 - 0.90mm) and band 5 (1.55 - 1.75mm) whilst the red band is 3 (0.63 - 0.69mm) of the Landsat-5 TM data.
2.2 Field Radiometric Measurements
Radiometric measurements were made at 5 sample plots each of about 2m x 2m square with a hand held radiometer with the same spectral bands as the Landsat data. The VIs were the derived from these measurements. Each plot was harvested and the Leaf Area Index (LAI) which is defined as the total leaf area per unit soil area was obtained. This was done by using a homemade leaf-area meter device which is made up of hard paper with 10cm x 10cm squares drawn on 1 m2 size. The weight of the grains were obtained by separating the grains from the paddy stalks. It was then possible to relate the LAI and grains to the VIs.
2.3 Calibration Curves
The VI values obtained from the sample plot were plotted against the grain yield. A regression fit was made to determine the relationship between yield and VIs. A linear relationship was obtained from the limited smaples that were taken. Figure 4 shows a curvilinear relationship that has been established between LAI and NDVI. The asymptote is reached at approximately 6.5 of the LAI. Above this value are almost the same regardless of increase in least per unit area. The calibration line sin figure 2 & 3 can be used t estimate paddy yield from the satellite data, the calculated VIs from the satellite data are used a input in this line.
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