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All Journal Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital International Journal of Remote Sensing and Earth Sciences (IJReSES)
Inggit Lolita Sari
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Computer Science & IT Earth & Planetary Sciences

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EVALUASI REHABILITASI LAHAN KRITIS BERDASARKAN TREND NDVI LANDSAT-8 (Studi Kasus: DAS Serayu Hulu) Tatik Kartika; Dede Dirgahayu; Inggit Lolita Sari; I Made Parsa; Ita Carolita
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 16 No. 2 Desember 2019
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (484.126 KB) | DOI: 10.30536/j.pjpdcd.2019.v16.a3079

Abstract

Pemanfaatan penginderaan jauh dalam memantau vegetasi sudah banyak dilakukan, tetapi pemanfaatannya untuk mengevaluasi rehabilitasi di lahan kritis masih sangat jarang. Kegiatan rehabiliatsi hutan dan lahan dilakukan karena makin meningkatnya lahan kritis. Kegiatan rehabilitasi tersebut perlu dievaluasi, mengingat banyak sekali dana, waktu, dan tenaga yang diperlukan. Selama ini evaluasi dilakukan dengan cara langsung mendatangi lokasi rehabilitasi dengan memantau pertumbuhan tanaman pada setiap akhir tahun sampai akhir tahun ketiga. Menurut ketentuan peraturan yang berlaku, rehabilitasi dapat dikatakan berhasil apabila 90% vegetasi yang ditanam bisa tumbuh di akhir tahun ketiga. Kegiatan evaluasi dengan cara memantau kondisi vegetasi atau kerapatannya dapat dilaksanakan dengan memanfaatkan data penginderaan jauh, karena data tersebut mempunyai sifat multi temporal dan cakupan yang luas dan ketersediannya yang berlimpah dan mudah didapat. Data penginderaan jauh yang digunakan adalah Landsat-8 tahun 2013 sampai dengan 2018 dan metode evaluasi adalah analisis NDVI dari waktu ke waktu menggunakan SIG. Hasilnya adalah bahwa dari hasil survey yang diperoleh di kawasan APL terdapat lokasi rehabilitasi di lahan tidak kritis, agak kritis, kritis, dan sangat kritis dan berturut-turut keberhasilan rehabilitasi untuk APL_TK; APL_K; APL_AK; APL_SK jika NDVI melampaui nilai 0,337; 0,465; 0,493; 0,490 setelah bulan ke 21,8; 24,5; 26, dan 25,8.
A TWO-STEPS RADIOMETRIC CORRECTION OF SPOT-4 MULTISPECTRAL AND MULTITEMPORAL FOR SEAMLESS MOSAIC IN CENTRAL KALIMANTAN . Kustiyo; Ratih Dewanti; Inggit Lolita Sari
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 11, No 2 (2014)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (996.393 KB) | DOI: 10.30536/j.ijreses.2014.v11.a2607

Abstract

This research analyzed the radiometric correction method using SPOT-4 imageries to produce the same reflectance for the same land cover. Top of Atmosphere (TOA) method was applied in previous radiometric correction approach, this TOA approach was upgraded with the reflectance effect from difference satellite viewing angle. The 250 scene of Central Kalimantan SPOT-4 imageries from 2006 until 2012 with varies viewing angle was used. This research applied two-step approaches, the first step is TOA correction, and the second step is normalization using a linear function of reflectance and satellite viewing angle. Gain and offset coefficient of this linear function was calculated using an iterative approach to producing the same reflectance in the forest area. The target of iterative processed is to minimize the standard deviation of a digital number from a forest area in the selected region. The result shows that the standard deviation of a digital number from a forest area in the two steps approach are 8.6, 16.5, and 16.8 for band 1, band 3 and band 4. These values are smaller compared with the standard deviation of digital number result from TOA approach are 15.0, 28,3 and 34.7 for band 1, band 3 and band 4.  Decreasing the standard deviation shows the homogeneity of forest reflectance that could be seen in the seamless result. This algorithm can be applied for making seamless SPOT-4 mosaic whole of Indonesia.
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)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (343.065 KB) | DOI: 10.30536/j.ijreses.2013.v10.a1843

Abstract

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.
Co-Authors . Kustiyo Bambang Trisakti Dede Dirgahayu I Made Parsa Ita Carolita Ratih Dewanti Tatik Kartika Tatik Kartika