Looking Inward to the Use of Unmanned Aerial Vehicle (UAV)
for Rice Production Assessment in Indonesia
I Gusti Agung Ayu Ambarawati
14
, Chiharu Hongo
24
, I Made Anom Sutrisna Wijaya
34
,
Anak Agung Sagung Putri Komaladara
4
, Anak Agung Ayu Mirah Adi
54
1
Faculty of Agriculture, Udayana University, Indonesia,
2Center for Environmental Remote Sensing (CEReS), Chiba University, Japan,
3Faculty of Agricultural Technology, Udayana University, Indonesia,
4Center on Food Availability for Sustainable Improvement (CFASI), Udayana University, Indonesia,
5Faculty of Veterinary Medicine, Udayana University, Indonesia
UDAYANA UNIVERSITY
Abstract
Rice is the main source of carbohydrate for most Indonesians. Rice production has been very dynamic due to improved infrastructure, research and development, and better farm management. However, rice production is susceptible to loss caused by drought, pest and disease attack and climate change. With the growing concern on sustainable and self-reliance food production in the country, there is an urgency to encourage research and efforts to increase rice productivity. Attempts to provide spatial distribution of rice fields on high resolution optical remote sensing data have been employed to some extent, however this technology could be costly. The use of UAV has been introduced to estimate damage ratio in rice crop recently in Indonesia. This technology is one of the ways to estimate rice production faster, cost saving and before harvesting time. This study aims to provide spatio temporal and damage ratio of rice crop using UAV in Indonesia. The study empirically presents the use of UAV (Phantom 2 Vision +) on rice fields to the state condition and development of management zone map in Bali as an example. The study concludes that the use of UAV allows researchers to pin point characteristics of crop and land in a specific area of a farm. This will then allow researchers to assist farmers in implementing specific and appropriate solutions to production issues.
Key words: UAV, rice production, damage ratio
Background
Rice is the most important source of carbohydrate for most Indonesians, cultivated widely throughout the country. Rice production has been fluctuating for the last five years depending on several factors including harvested area and yield. At average, rice production tends to slightly decrease from 71.28 million tons in 2013 to 70.85 million tons in 2014, a decrease of 0.60 percent. The average yield of rice production for the whole country is 5.3 t ha-1. Regarding food security management, the Indonesian government concerns on monitoring
and utilizing improved technologies those are available for sustainable rice production. A number of research and development (R&D) has been carried out to portray the dynamics of rice production in Indonesia. These are including the use of remote sensing and Geographical Information System (GIS) techniques (Uchida 2010, Nuarsa et al. 2011). Despite the advantage use of remote sensing technology, the method could be constrained by high cost for the images as well as the time for ordering images. The use of UAV has been applied in several places in Indonesia for small area mapping (Sadikin et al. 2014).
The island of Bali was selected in this study to provide spatial land data with the low cost of photogrammetric method of UAV. Bali province account for only 0.29 percent of the total area of Indonesia, however it is worldwide known for its tourist destination. The tourist sector contributes more than 70 percent to the regional domestic product. On the other hand, agricultural sector including rice production still plays an important role in the Bali economy because of its 20 percent contribution. The Bali government has vision to achieve resilient agriculture in a sense of advancement, safe, peaceful, and wealth, called the MANDARA program. The mission is to achieve
self-reliant food through empowerment of agricultural resources optimally and sustainably. This mission includes increasing far er’s income for better livelihood.
The common cropping pattern in a year is rice – rice – secondary crops. Depending on water availability, farmers in most places in Bali are able to plant paddy twice in a year and during dry season they plant secondary crops such as corn and soybeans. With the average yield of 5.8 ton/ha, there is rice production 864,200 ton/year. However, rice production in Bali is susceptible to failure not just because of drought and pest and disease attack, but also from the climate change. Several efforts are contributable to this rice production including innovative technology and improved agricultural practices. Concerning the exposure risks, the use of imagery technology such as UAV is valuable to monitor the condition of plant and land surface.
Objectives
This study aims to provide rice farming condition on a far er’s group and spatio temporal of rice crop using UAV in Indonesia. The study empirically presents the use of UAV (Phantom 2 Vision +) on rice fields to capture the existing condition and development of management zone map in Bali as an example.
Methodology
Study location: Subak Cemagi Let, Cemagi village, Mengwi district, regency of Badung, Bali. Subak Cemagi is the largest
far er’s group at Cemagi village with the area of paddy field of 324 ha. The location was selected purposively in the sense that agricultural sector may be left for other employment opportunities in the tourist sector. Cemagi village lies on longitude 115o06’45.3” E and latitude 8o37”49.6”S.
Figure 1. Phanthom 2 Vision + Data collection: There were two steps carried out in this study.
First, fifty farmers were interviewed randomly in October 2014 to find out their rice yield using ubinan system (2.5 m x 2.5 m of harvested samples) and obstacles related to rice production. Each farmer location was recorded to be used for data base. This provided insights on the far er’s rice production and hindrance on paddy field. Secondly, UAV Phantom 2 Vision + was used to map paddy field at Subak Cemagi in October 2015 representing small area and possibility to calculate damage ratio. The flying height was 50 meter with 3 seconds interval. The combination of the two steps allows researchers to pin point characteristics of paddy field in a specific area of a farm.
Results and Discussion
1. Farmer survey
Farmers at the location of study carry out seed planting according to the schedule agreed by the members of farmer group on a regular subak meeting. This schedule supports harvesting time to estimate rice production on the field. Farmers are categorized as small-scale farm as the average of land holding at 0.32 ha, ranging from 0.09 to 0.8 ha. Looking at the distribution, 40 percent of farmers hold below than 0.20 ha of paddy field, while only 10 percent of farmers have more than 0.5 ha of land. This condition might affect the efficiency of the rice production.
With regards to the rice yield, farmers were able to achieve at the average of 8.57 ton ha-1. Rice
productivity in Cemagi village was much higher than that of the average of rice production in Bali, which was 5.8 ton ha-1 (Bali Board of Statistics, 2014).There was
more than half farmers could achieve above the average of productivity (Figure 2). There was only 5 percent of farmers in Mengwi village produced 5.4 ton ha-1.
Figure 2. Far ers’ ri e yield distri utio at Cemagi Village
Figure 3 indicates that pest and disease attack remain to be a major cause of crop failure. This is followed by water scarcity and climate change. Farmers claim that the drought caused by climate change force them to shift in their planting schedules, which may jeopardize
the regio ’s food security. Figure 3. Common causes of rice production failure in
Cemagi Village
Results from farmer surveyed can be used as ground data base for monitoring rice production in the area, particularly on the implementation of good agricultural practices. The data also indicate that rice production is prone to failure mainly due to pests and diseases attack, water shortage and climate change.
2. The UAV imagery result
Results from the UAV imagery are presented in Figure 4 to 6. The images are able to capture the existing condition of rice field at the selected area. The state of rice fields for harvesting are seen clearly from different color of the images. This information will ease the head of far er’s group to collect tax from the selling yield. Taxes from rice selling are agreed upon the farmer members to pay for the function ceremony based on Hindu ritual and tertiary flow maintenance of the water irrigation. Combination from the ground data base and UAV images can be used for the implementation of precision agriculture on the area. At glance, damage ratio from these fields cannot be calculated yet due to the image results however the images show the condition of farm are good, showing less pest and disease attack. Further analysis is required to correlate between aerial images with the ground data to be effective in mapping the selected area.
The use of UAV imagery is not without drawback. It has to be concerned with the time to get rid of cloud effect and height of flying to capture the best picture. The images taken could be also overlapped. The post process of each photograph is required to portray land parcels image. Accordingly, it should be taken into consideration when conducting data analysis.
Conclusion
Figure 4. Image of Subak Cemagi Let using UAV Phantom 2 Version +
Figure 5. Different position of UAV standing point results in different image
Figure 6. UAV image capturing different state of plant condition
Results from the UAV imagery is able to capture the existing condition of rice field at the small area. This information reduces time to inspect for the state of rice fields. Correlation with the ground data allows researchers to do further analysis for the implementation of precision agriculture. The drawback of the UAV use could be overcome in the near future from the UAV design.
Acknowledgements:
The authors would like to thank Udayana University and Chiba University for supporting this study. The authors would also like to express their gratitude to the BPP Mengwi agricultural extension workers for coordinating the survey data collection.
Corresponding Author:
I Gusti Agung Ayu Ambarawati annie_ambarawati@unud.ac.id References:
Nuarsa, I W., Nisho, F. and Hongo, C. (2011). Relationship between rice spectral and rice yield. Journal of Agricultural Sciences, Vol 3 (2), 80-88.
Sadikin, H, Saptari, A.Y., Addulharis, R. And Hernandi, A. (2014). UAV system with terrestrial geo-referencing for small area mapping. Presented in FIG Congress 2014, Engaging the Challenges-Enhancing the Relevance, Kuala Lumpur, Malaysia, 16-21 June, 2014.
