Ferman Setia Nugroho, Ferman Setia
Balai Penginderaan Jauh Parepare, LAPAN

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PENGARUH JUMLAH SALURAN SPEKTRAL, KORELASI ANTAR SALURAN SPEKTRAL DAN JUMLAH KELAS OBJEK TERHADAP AKURASI KLASIFIKASI PENUTUP LAHAN Nugroho, Ferman Setia
JURNAL ILMIAH GEOMATIKA Vol 21, No 1 (2015)
Publisher : Badan Informasi Geospasial

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (625.383 KB) | DOI: 10.24895/JIG.2015.21-1.461

Abstract

Penutup lahan merupakan salah satu informasi penting yang dapat diperoleh dari data penginderaan jauh. Penutup lahan diperlukan sebagai landasan bagi pemerintah dalam menentukan arah kebijakan pembangunan, perencanaan pengembangan wilayah, dan pengelolaan sumber daya alam. Oleh sebab itu, inventarisasi dan pemetaan lahan perlu dilaksanakan secara kesinambungan, cepat, tepat dan tinggi akurasinya. Penelitian ini bertujuan untuk mengetahui perubahan tingkat akurasi hasil klasifikasi penutup lahan dari citra penginderaan jauh seiring penambahan jumlah saluran spektral yang dilibatkan, semakin tingginya korelasi antar saluran yang dilibatkan, dan seiring penambahan jumlah kelas objek. Penelitian ini menggunakan 2 saluran spektral sampai dengan 9 saluran spektral pada citra ASTER VNIR+SWIR dengan area penelitian meliputi Surabaya dan sekitarnya. Hasil penelitianini menunjukkan bahwa penambahan jumlah saluran yang dilibatkan dapat meningkatkan akurasi, semakin tinggi korelasi antar saluran maka akurasi yang didapatkan menurun, semakin banyak jumlah kelas objek maka akurasi yang didapatkan menurun.Kata kunci:penutup lahan, saluran spektral, kelas objekABSTRACTLand cover is one of the most important information that can be obtained from remote sensing data. It were needed as a basis data for government to determine the direction of development policy, regional development planning, and management of natural resources. Therefore, inventory and mapping of land need to be implemented in a sustainable, rapid, precise, and also accurate. The purposes of this study is to determine changes of the accuracy level from land cover classification of remote sensing image as the increased number of spectral bands that are involved, the higher the correlation between spectral bands involved, and as the addition of the number of class objects. The results of this study showed that the increasing number of spectral bands that are involved can improve accuracy, the higher correlation between spectral bands make the accuracy obtained decreased, classification using more number of object classes the accuracy obtained decreasedKeywords: land cover, spectral band, object class
TOTAL SUSPENDED SOLID DISTRIBUTION ANALYSIS USING SPOT-6 DATA IN SEGARA ANAKAN, CILACAP Dhannahisvara, Aisya Jaya; Harjo, Hartono; Wicaksono, Pramaditya; Nugroho, Ferman Setia
Geoplanning: Journal of Geomatics and Planning Vol 5, No 2 (2018): (October 2018)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.5.2.177-188

Abstract

Spatial distribution and concentration of Total Suspended Solid (TSS) is one of the coastal parameters which are required to be examined in order to understand the quality of the water. Rapid development of remote sensing technology has resulted in the emergence of various methods to estimate TSS concentration. SPOT-6 data has spatial, spectral, and temporal characteristics that can be used to estimate TSS concentration. The purposes of this research are (1) to determine the best method for estimating TSS concentration, (2) to map TSS distribution, and (3) to determine the correlation between TSS concentration and chlorophyll-a concentration using SPOT-6 data in Segara Anakan. The estimation of TSS concentration in this research was performed using empirical model built from SPOT-6 and TSS field data. Bands used in this research are single band data (blue, green, red, and near infrared) and transformed bands such as band ratio (12 combinations), Normalized Difference Suspended Solid Index (NDSSI), and Suspended Solid Concentration Index (SSC). The result shows that blue, green, red, and near infrared bands and SSC index significantly correlated to TSS. Afterwards, regression analysis was performed to determine the function that can be used to predict TSS concentration using SPOT-6 data. Regression function used are linear and non-linear (exponential, logarithmic, 2nd order polynomial, and power). The best model was chosen based on the accuracy assessment using Standard Error of Estimate (SE). The selected model was used to calculate total TSS concentration and was correlated with chlorophyll-a field data. The result of accuracy test shows that the model from blue band has an accuracy of 70.68 %, green band 70.68 %, red band 75.73 %, near infrared band 65.58 %, and SSC 73.67 %. The accuracy test shows that red band produced the best prediction model for mapping TSS concentration distribution. The total TSS concentration, which was calculated using red band empirical model, is estimated to be 6.13 t. According to the correlation test, TSS concentration in Segara Anakan has no significant correlation with chlorophyll-a concentration, with a coefficient correlation value of -0.265.