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The Study of Discrimination of Remotely Sensed Data for Designing the Separation Technique Between Cassava and Sugarcane Farmland

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The Study of Discrimination of Remotely Sensed Data for Designing the Separation Technique Between Cassava and Sugarcane Farmland The Study of Discrimination of Remotely Sensed Data for Designing the Separation Technique between Cassava and Sugarcane Farmland Anuphao Aobpaet a and Soravis Supavetch Department of Civil Engineering, Kasetsart University, Bangkok, Thailand Keywords: Cassava, Sugarcane, Remote Sensing for Agriculture. Abstract: Cassava and sugarcane are the most important agricultural crops in Thailand. The cultivations of those are similarly in crop season, natural resources, and climate. For decades, the farmers usually switch their plant depending on unit price and government subsidy. The use of remote sensing data for monitoring change in farmland has encountered a problem on the similarity of vegetation index and the seasonal variation. In this work, we investigate the significant differences between cassava and sugarcane plantation by using satellite data from two sensors systems (Optical and SAR sensor) from Sentinel-1 and Sentinel-2 satellites. The result of the sampling fields of cassava shows the fluctuation of the growth and the mean of SAVI is slightly lower than sugarcane at the same age. SAVI values over the cassava farmland seem to approach the homogeneity of sugarcane when the age of more than 11 months. Thus, the difference between cassava and sugarcane farmland using this method should be investigated on the growth stage of the age between 4-9 months. For SAR polarization, the VV, VH of SAR backscatters have little difference in cassava and sugarcane. When compare the backscatters value of VV and VH from cassava and sugarcane, the sigma0 values in dB show that VV backscatters have a higher signal return. The variation of VH polarization of cassava and sugarcane seem difficult to identify due to the diversity of signal targets. Therefore, by using SAR data, the detection of the difference between cassava and sugarcane should be considered after working on time series techniques for crop seasoning to remove unwanted objects until only cassava and sugarcane remain. From the results, we also found that the parcel-based method is a better processing approach to separate cassava from sugarcane compared to pixel-based, and it requires descriptive statistics to distinguish between cassava and sugarcane at each age. This method requires the information of two agricultural plantations boundaries. The possible handling process when harvesting and preparation of the plantation are by observing time-related over an area to determine the boundary of the farmland. Therefore, the discrimination of remotely sensed data for designing the decomposition technique between cassava and sugarcane farmland is necessary because of the specificity of cultivation in Thailand. 1 INTRODUCTION products through the grouping of farmers. The sixth area is seeking to promote working as a team through The Ministry of Agriculture and Cooperatives also the "single command" system in order to translate the announce the policy to reform Thailand's agricultural reform plan into action. The seventh area is the sector mainly focuses on seven areas. The first area is reduction of agricultural production costs. In the case agricultural zoning to a suitable geographical and of cassava and sugarcane, the factor of success policy climatic condition. The second area is the is based on the monitoring of cultivation behaviour of establishment of learning centres for increasing the the farmers. In recent years, Earth Observation efficiency of the agricultural product. The third area Satellite (EOS) is a powerful tool for constantly is a grouping of farmers and farmland for better assessing the status of agricultural production on a efficiency. The fourth area is seeking the encourage wide range of spatial and temporal scales. It provides farmers producing in response to the market demand. time series data and can rapidly reveal where change The fifth area set up the banks for agricultural has happened in a consistent and repeatable manner. a https://orcid.org/0000-0001-7638-853X 267 Aobpaet, A. and Supavetch, S. The Study of Discrimination of Remotely Sensed Data for Designing the Separation Technique between Cassava and Sugarcane Farmland. DOI: 10.5220/0007748102670273 In Proceedings of the 5th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2019), pages 267-273 ISBN: 978-989-758-371-1 Copyright c 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved GISTAM 2019 - 5th International Conference on Geographical Information Systems Theory, Applications and Management Information from Earth Observation is therefore very challenge technique due to the fact about the well suited to timely information on cropland correspondence of vegetation index term, the distribution and status at various crop stages. seasonal effect on a reflectance make the signature of In a global scale, characteristics of satellite remote a phenotype cannot be determined. This study used sensing data and processing implementations are permitted available data from Sentinel-1 and 2 for available for the large areas applications such as data processing and uses the parcel-based descriptive forestry, agriculture, fishery, coastal and marine, statistics in analysing and interpreting the results. In environment, disaster mitigation, spatial planning, this stage of the study, we only focus on the technique and so on. Nevertheless, in a small scale (high for the separation of cassava and sugarcane which resolution), many factors are relevant due to many will make possible for crop forecasting in Thailand. components of the ecological network which are involved i.e., small pond, farm dike, mixed cropping, species, soil types, moisture, etc. 2 OBJECTIVE In Thailand, the National Statistical Office (2013) reported that 87.8% of 5.9 million farmers owned As by the location of the country, there is a little land area lower than 6 ha. However, this small farm difference in environments as well as the planting size alone is not only a limiting factor for determining season, so we are unable to classify the agricultural the productivity (yield) and the homogeneity of the farmland of both plants by means of single temporal plant by using spectral reflectance determination. classification. Therefore, the main objective of this Moreover, Thai government pay attention to promote study is to investigate the significant differences “Philosophy of Sufficiency Economy and New between cassava and sugarcane plantation by using Theory” in agricultural sector following his Majesty satellite data from two sensors systems which are King Rama 9 suggestion that the farmers are Optical and SAR sensor from Sentinel-1 and suggested to divided his land into four parts with a Sentinel-2 satellites. Both satellites that we applied ratio of 30:30:30:10. The first 30% is designated for are available at no cost and it is possible to develop a pond to store rainwater during rainy season. The the automatic system for future operation. second 30% is set aside for rice cultivation during the rainy season for family’s daily consumption throughout the year. The third 30% is used for growing fruit and perennial trees, vegetables, field 3 DATA PREPARATION crops and herbs for daily consumption. The last 10% is set aside for accommodation, animal husbandry, The sampling areas of cassava and sugarcane are roads, and other structures (The Chaipattana selected in Nakhon Ratchasima province which is the Foundation, 2017). Thus, these activities made more largest cassava plantations in Thailand (Figure 1). complexity on a small farm in term of remotely This province economy has traditionally been heavily sensed data. For an agricultural country such as dependent on agriculture which is the production of Thailand, the implementation of remote sensing rice, tapioca, and sugar. technologies for monitoring and controlling the government’s policy in agriculture using a field- based approach is the importance for those smallholder farmers. In this study, the cassava and sugarcane are selected as a feasible crop. The influence of the successive policy depends on the monitoring of the cultivation behaviour of the plants following farmers’ decision which sometimes varied and difficult to identify. The crop growing process of cassava and sugarcane are likewise in crop season, natural resources, and climate (Thai Meteorological Department, 2015), as already mentioned above. The farmers have their choice to select the plants base on Figure 1: Nakhon Ratchasima province, the largest cassava the unit price and government subsidy made the plantations. difficulty of policy control. The potential on using remote sensing for farmland monitoring is the 268 The Study of Discrimination of Remotely Sensed Data for Designing the Separation Technique between Cassava and Sugarcane Farmland The Sentinel-1 and Sentinel-2 satellites data are Atmosphere, BOA). The effect of modifying the able to access via Copernicus Open Access Hub atmosphere to bring the reflection in the atmosphere (https://scihub.copernicus.eu/) for this investigation makes it possible to know the particles in the (European Space Agency). Satellite data processing atmosphere which makes the additional data layer from Sentinel-1 uses the Orfeo Toolbox software as a called Aerosol Optical Thickness (AOT). When processing tool (Inglada et al., 2009) (Christophe et comparing the reflection values to the results from al., 2009) (Teodoro et al., 2016). The data adjustment, it is found that the values that have been downloaded from
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