Garuda - Garba Rujukan Digital

Tatik Kartika

Unknown Affiliation

Author-ID : 3487673

Computer Science & IT Earth & Planetary Sciences

Published : 3 Documents Claim Missing Document

Claim Missing Document

Articles

APLIKASI MODEL GEOBIOFISIK NDVI UNTUK IDENTIFIKASI HUTAN PADA DATA SATELIT LAPAN-A3 Samsul Arifin; Ita Carolita; Tatik Kartika
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 16 No. 2 Desember 2019
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

ABSTRAKSatelit LAPAN-A3/IPB merupakan satelit mikro yang dibuat anak bangsa dalam rangka membangun kemandirian bangsa bidang Keantariksaaan. Satelit ini memiliki 4 band diantaranya adalah 3 gelombang tampak dan 1 inframerah dekat. Mengingat merupakan satelit baru, perlu dilakukan kajian dan penelitian terhadap kemampuan karakteristik sensor untuk mengidentifikasi sumberaya alam, salah satunya hutan. Pada penelitian ini selain menggunakan data satelit LAPAN-A3, juga digunakan data Landsat-8 sebagai data pembanding untuk pengujian tingkat akurasi ketelitian. Penentuan ekstraksi parameter geobiofisik identifikasi hutan menggunakan model Normalized Difference Vegetation Index (NDVI) dengan nilai ambang batas untuk identifikasi hutan. Hasil penelitian dengan data satelit LAPAN-A3 menujukkan bahwa kisaran ambang batas untuk indentifikasi hutan adalah di atas 0,65 pada skala indeks vegetasi -1 (minus satu) sampai +1 (plus satu), dengan tangkat akurasi 60% setelah dibandingkan dengan nilai NDVI pada data Landsat-8.

DETERMINATION OF FOREST AND NON-FOREST IN SERAM ISLAND MALUKU PROVINCE USING MULTI-YEAR LANDSAT DATA Tatik Kartika; Ita Carolita; Johannes Manalu
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 13, No 1 (2016)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Seram Island is one of the islands in Maluku Province. Forest in Seram Island still exists because there is Manusela National Park, but they should be monitored. The forest and non-forest information is usually obtained through the classification process from single remote sensing data, but in certain places in Indonesia it is difficult enough to get single Landsat data with cloud free, so annual mosaic was used. The aim of this research was to analyze the stratification zone, their indices and thresholds to get spatial information of annual forest area in Seram Island using multi-year Landsat Data. The method consists of four stages: 1) analyzing the base probability result for determination of stratification zone 2) determining the annual forest probability by applying indices from stage-I, 3) determining the spatial information of forest and non-forest annual phase-I by searching the lowest boundary of forest probability, and 4) determining the spatial information of forest and non-forest annual phase-II using the method of permutation of three data and multi-year forest rules. The results of this study indicated that Seram Island could be coumpond into one stratification zone with three indices. The index equations were B2+B3-2B for index-1, B3+B4 for index-2, and -B3+B4 for index-3. The threshold of index 1, 2, and 3 ranged between -60 and 0, 61 and 104, and 45 and 105, respectively. The lowest boundary of forest probability in Seram Island since 2006 to 2012 have a range between 46% and 60%. The last result was the annual forest spatial information phase II where the missing data on the forest spatial information phase I decreased. The information is very important to analyze forest area change, especially in Seram Island.

DETERMINATION OF STRATIFICATION BOUNDARY FOR FOREST AND NON FOREST MULTITEMPORAL CLASSIFICATION TO SUPPORT REDD+ IN SUMATERA ISLAN Tatik Kartika; Inggit Lolita Sari; Bambang Trisakti
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 10, No 1 (2013)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Multi-temporal classification is a method to determine forest and non-forest by considering a missing data, such as cloud cover using correlations value from the other data. This circumstances is frequently occured in a tropical area such as in Indonesia. To gain an optimum result of forest and non-forest classification, it is needed a stratification zone that describes the difference of vegetation condition due to different of vegetation type, soil type, climate, and land use/cover associations. This stratification zone will be useful to indicate the different biomass volume relating to carbon content for supporting the REDD+ project. The objective of this study was to determine stratification boundary by performing multi temporal classification in Sumatera Island using Landsat imagery in 25 meter resolution and Quick Bird imagery in 0.6 meter. Rough stratification was made by considering land use/cover, DEM and landform, using visual interpretation of moderate spatial resolution of satellitedata. High spatial resolution data was also provided in some areas to increase the accuracy level of stratification zone. The stratification boundary was evaluated using forest classification indices, and it was redetermined to obtain the final stratification zone. The indices was generated by CanonicalVariate Analysis (CVA) method, which was depend on training samples of forest and non-forest in each previous stratification zone. The amount of indices used in each zone were two or three indices depending on the separability of the forest and non-forest classification. The suitable indices used in each zone described forest as 100, non-forest as 0, and uncertain forest between 50-99. The result showed 20 stratification zones in Sumatera spreading out in coastal, mountain, flat area, and group of small islands. The stratification zone will improve the accuracy of forest and non-forest classification result and their change based on multi temporal classification.

Title

Found 3 Documents
Search

Abstract

Abstract

Abstract

Title Search

Found 3 Documents Search

Abstract

Abstract

Abstract

Title

Found 3 Documents
Search