Application of remote sensing technique for rice precision farming

Transcription

1 Application of remote sensing technique for rice precision farming Teoh Chin Chuang (DR) Chan Chee Wan (DR) Abu Hassan Daud Malaysian Agricultural Research and Development Institute (MARDI)

2 Background: Rice is an important crop in Malaysia covering about 600,000 ha with an average yield of 3.0 to 5.2 t/ha Main paddy producing granary areas: 1. Muda Agricultural Development Authority (MADA); 2. Kemubu Agricultural Development Authority (KADA); 3. Kerian-Sungai Manik Integrated Agriculture Development Area; 4. Barat Laut Selangor Integrated Agriculture Development Area; 5. Seberang Perak Integrated Agriculture Development Area; 6. Penang Integrated Agriculture Development Area; 7. North Terengganu Integrated Agriculture Development (KETARA) 8. Integrated Agriculture Development Kemasin Semerak Source: Food and Agriculture Organization (FOA)

3 Paddy Production: Tonnes Year Self-sufficiency level (SSL) 70%

4 Problems: small fragmented land holding competing water resource use scarcity of farm labor indiscriminate chemical input use environmental stresses

5 Precision farming A technology to manage variability for improving agriculture production and environmental quality - land levelling - water - soil nutrient - plant health - pest and disease - yield

6 Precision farming technologies developments were carried out by Malaysian Agricultural Research & Development Institute (MARDI): 1. Water and farm infrastructure management 2. Techniques in precision agriculture related crop establishment management 3. Soil nutrient management 4. Instrumentation and sensors system for data collection and variable rate application 5. Remote sensing methodology using aerial sensing techniques for rice fields correlation studies of remote sensing data 6. Decision support system for supporting precision agriculture operations in mechanized rice production 7. Variable rate application for weeds, pest and disease control 8. Variable rate nutrient application 9. Rice yield monitor for Malaysian rice combine harvester

7 Irrigation information system Plowing Veris electrical conductivity (EC) sensor for soil nutrients assessment Land leveling Remote sensing system Seed sowing Variable rate application (VRA) system Decision support system (DSS) Rice yield monitor

8 Application of remote sensing techniques: 1. Paddy field plot boundaries extraction 2. Water front pattern monitoring 3. Rice plant growth monitoring 4. Fertilizer treatment maps IKONOS Quadcopter CropCam Satellite Unmanned aerial vehicle (UAV)

9 1. Paddy field plot boundaries extraction Geographical Information System (GIS) is a tool to visualise, analyse and manage the variability in the rice field Vector layers

10 Timely and accurate digital vector basemap is needed

11 Digital vector basemap - Land surveying - Manual digitizing Land surveying Manual digitizing Slow, tedious and costly!!

12 Image processing techniques & customised GIS processing methods QMAP Satellite Image Raster Image Processing Technique GIS Processing & Editing Vector Digital vector basemap

13 Satellite Image IKONOS Commercial earth observation satellite: -1 st to collect publicly available high-resolution imagery at 1- and 4-meter resolution False Colour Composite (Red, Green and Near IR bands ) Band 1-m panchromatic 4-m multispectral & 1-m pansharpened 1 (Blue) µm µm 2 (Green) * µm 3 (Red) * µm 4 (Near IR) * µm

14 Image processing Linear feature extraction Image classification IKONOS image GIS processing & editing of vector map Raster to vector conversion

15 GIS processing & editing of vector map GIS

16 FELCRA Seberang Perak 4000 ha QMap

17 2. Water front pattern monitoring Image transformation Image classification Water Soil

18 30 min 60 min 90 min Water (21%) Water (51%) Water (71%) 120 min 150 min 180 min Water (85%) Water (94%) Water (98%)

19 3. Rice plant growth monitoring R,G and NIR images acquisition Image mosaicing Image classification

20 Image acquisition CropCam UAV system TETRACAM camera Wing Span: 2.5 m Length: 1.2 m Weight: 2.7 kg Material: Carbon fiber reinforced fiber glass Cruise Speed: 60 Km/Hr Flight Duration: Up to 50 minutes (depending on wind conditions) Maximum Wind Speed: 30 Km/Hr Maximum load: 0.5 kg

21 Image mosaicing R, G and NIR sample images

22 3. Rice plant growth monitoring 30/4/ /5/2012 1/6/ /6/ /7/2012 Water (100%) Water (84%) Water (73%) Water (12%) Water (7%) Paddy (16 %) Paddy (27 %) Paddy (88 %) Paddy (93 %)

23 4. Fertilizer treatment maps Blanket or package fertilizer recommendations over large areas is not efficient because indigenous nutrient supply varies widely among rice fields in Asia (Dobermann and White 1999; Olk et al. 1999). Over applied fertilizer will caused the crop failure because of lodging or pest attack (Fairhurst and Witt 2002)

24 Variable-rate N management is a solution for minimizing fertilizer input and maximizing yield Green Area Index (GAI) model was developed by Abu et. al (2005) for determining the additional N fertilizer to be applied 1. SPAD reading 2. Plant population (i.e. tiller number)

25 An optical sensing of crop canopy spectral reflectance technique was developed to estimate SPAD reading and plant population RGB image acquisition Image mosaicing RGB spectral reflectance extraction Statistical analysis SPAD value map Plant population map

26 RGB image acquisition Flying height: 320 m Image type: RGB Image resolution: 6.25 cm/pixel

27 Image mosaicing Sample images Yan, Kedah

28 RGB spectral reflectance extraction Average mean RGB values of 4x4 pixels were calculated

29 Statistical Analysis Relationship between SPAD readings and RGB spectral reflectance values Relationship between plant population and RGB spectral reflectance values

30 Predicted SPAD reading = m* [spectral reflectance values] + c Non-plant area High SPAD reading Medium SPAD reading Low SPAD reading

31 Predicted plant population = m* [spectral reflectance values] + c Non-plant area High population Medium population Low population

32 + SPAD reading Map Population Map L M H High fertilizer rate Medium fertilizer rate Variable rate fertilizer applicator Fertilizer Treatment Map Low fertilizer rate

33 THANK YOU