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ITS » PhD Theses » Program Doktoral Teknik Sipil
Posted by dee@its.ac.id at 02/11/2011 11:45:35  •  3215 Views


DEVELOPMENT OF ESTIMATION METHOD OF CANOPY WATER CONTENT OF RICE PLANT USING HYPERSPECTRAL DATA

Author :
WIBOWO, AGUS ( 3106301703 )




ABSTRAK

Biomasa merupakan salah satu variabel kunci yang menjadi perhatian dalam studi tentang tanaman baik tanaman yang dibudidayakan maupun tanaman yang tidak dibudidayakan. Istilah biomasa dapat mengacu pada berat basah maupun berat kering tanaman. Kandungan air kanopi daun atau canopy water content CWC merupakan selisih berat basah daun dan berat kering daun dan menjadi perhatian banyak aplikasi. Padi merupakan tanaman budidaya yang terpenting dalam peradaban manusia padi juga merupakan makanan pokok bagi 90 penduduk Indonesia. Oleh sebab itu pemenuhan produksi swasembada beras padi merupakan masalah penting bagi bangsa Indonesia. Salah satu hal penting dalam produksi padi adalah pemantauan kondisi air pada tanaman padi. Kekurangan air pada tanaman padi akan mempengaruhi penurunan pertumbuhan dan produksi padi. Dengan teknologi penginderaan jauh pemantauan kondisi air tanaman padi dapat dilakukan secara cepat dan mencakup wilayah yang luas. Pengukuran reflektan kanopi daun padi dengan field spectrometer dilakukan pada beberapa titik pengukuran di lahan padi di Indramayu Provinsi Jawa Barat. Pengukuran menggunakan panjang gelombang 350-2500 nm 0.350-2.500 m dengan resolusi spektral 1 nm dan dilakukan pada jarak 10 cm FS10 dan 50 cm FS50 dari permukaan kanopi daun padi. Titik pengukuran dipilih sedemikian sehingga mewakili berbagai tahapan pertumbuhan padi yaitu tahap vegetatif reproduktif dan ripening. Pada saat yang bersamaan dilakukan juga pengambilan data dari pesawat udara menggunakan sensor Hyperpsectral Mapper HyMap dengan jumlah kanal 128 resolusi spektral 10-20 nm jangkauan panjang gelombang 350-2500 nm dan resolusi spasial 4.5 m. Rumpun padi yang sudah diukur dicabut dipisahkan menjadi bagian daun batang dan bulir padi. Selanjutnya ditimbang berat basahnya dan kemudian dikeringkan di laboratorium sampai suhu 60o C untuk ditimbang berat keringnya. Selisih berat basah dan berat kering daun padi per m2 didefinisikan sebagai kandungan air daun canopy water content CWC. Analisis regresi linear dilakukan untuk mencari hubungan antara CWC dengan spectral index yang sudah dikenal luas yaitu water index WIR900R970 peuelas 1993 dan normalised difference water index NDWI R860-R1240R860R1240 Gao 1996. Selanjutnya dilakukan analisis regresi linear untuk mendapatkan kombinasi kanal yang optimal untuk prediksi CWC dengan spectral index seperti ratio spectral index RSIR2R1 normalised difference spectral index NDSIR2-R1R2R1 renormalised difference spectral index RDSIR2-R18730R_2R_1 soil adjusted spectral index SASIR2-R11.5R1R20.5. Analisis multiple linear regression MLR antara CWC dengan reflektan kanopi daun juga dilakukan untuk mencari kombinasi kanal yang optimal untuk memprediksi CWC. Selanjutnya model regresi yang diperoleh diaplikasikan pada data HyMap. Hasil analisis menunjukkan bahwa metode yang paling baik untuk deteksi CWC adalah dengan metode indeks spektral dengan kombinasi kanal yang optimal R1 1152.5 nm dan R2 1079.3 nm. Hasil koefisien korelasi r2 untuk RSI0.78 SASI0.76 NDSI0.74 RDSI0.73 NDWI0.67 dan WI0.65.


ABSTRACT

Biomass is one of the key variables of concern in the study of plants either cultivated or plants non-cultivated crops. The term biomass refers to fresh weight or dry weight of plants. Canopy water content of leaf CWC is the difference between fresh weight and dry weight become the attention of many applications. Rice is the most important cultivated plants in human civilization rice is the staple food for 90 of Indonesias population. Therefore the fulfillment of rice production is an important issue for the Indonesian nation. One of the important things in rice production is monitoring the water condition of the paddy. Lack of water on paddy plant will affect the growth and decline in rice production. Remote sensing technology has an opportunity for monitoring the paddy water status in quickly and cover wide areas. Paddy leaf canopy reflectance measurements with a field spectrometer are done at some point in upland rice in Indramayu West Java Province. The field spectrometer is using a wavelength range from 350-2500 nm and with a spectral resolution of 1 nm. The measurement was performed at a distance of 10 cm FS10 and 50 cm FS50 of paddy leaf canopy surface. The sample points are selected such that represent different stages of rice growth such as vegetative reproductive and ripening stage. At the same time an airborne survey which is using a Hyperpsectral Mapper HyMap sensor is done at the same areas. The HyMap sensor has specification of 128 channels 10-20 nm spectral resolution wavelength range 350-2500 nm and spatial resolution of 4.5 meters. Clumps of paddy that has been measured withdrawn separated into the leaf stem and grains and then weighed. Furthermore the sample of leaf stem and grains are dried in the laboratory until the temperature of 60 C and to be weighed. The difference in fresh weight and dry weights were considered as canopy water content CWC. Linear regression analysis was conducted to find the relationship between the CWC and spectral indices such as water index WI R0.900R0.970 Peuelas 1993 and normalized difference water index NDWI R0.860-R1.240R0.860 R1.240 Gao 1996. Furthermore linear regression analysis are done to obtain the optimal combination of channels for the prediction of CWC and spectral indices such as ratio of spectral indices RSIR2R1 normalized difference spectral indices NDSIR2-R1R2R1 renormalized difference spectral indices RDSIR2-R18730R_2R_1 soil adjusted spectral indices SASIR2-R11.5R1R20.5. Multi-linear regression analysis MLR between the CWC with the leaf canopy reflectance was also conducted to find the optimal combination of channels to predict CWC. Furthermore the regression model obtained and applied to the HyMap data. The analysis showed that the best method for detection of CWC is the spectral index method with the optimal band combination of R1 1152.5 nm and R2 1079.3 nm. The results of correlation coefficient r2 for RSI 0.78 SASI 0.76 NDSI 0.74 RDSI 0.73 NDWI 0.67 and WI 0.65.



KeywordsSoil Moisture Content; Hyperspectral; Remote Sensing; Multi Linear Regression; Spectal Indices; WI; NDWI; RSI; NDSI; RDSI; SASI; Paddy; Indramayu; West Java
 
Subject:  Kontrol jarak jauh
Contributor
  1. Prof.Dr.Ir. Bangun Muljo Sukojo, DESS, DEA.
  2. Dr. Ing. Ir. Teguh Hariyanto, MSc.
Date Create: 12/01/2011
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-PhD-3100011042243
Collection ID: 3100011042243
Call Number: RDS 621.367 8 Wib p


Source
Disertasi of Civil Engineering, RDS 621.367 8 Wib p, 2011

Coverage
ITS Community

Rights
Copyright @2011 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




[ Download - Open Access ]

  1.  ITS-PhD-15748-Abstract_id.pdf - 36 KB
  2.  ITS-PhD-15748-Abstract_en.pdf - 34 KB
  3.  ITS-PhD-15748-Conclusion-89623.pdf - 88 KB
  4.  ITS-PhD-15748-Paper-201007.pdf - 196 KB
  5.  ITS-PhD-15748-Paper-839302.pdf - 820 KB




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