Teknologi eksplorasi pertambangan - Pemetaan Eksplorasi Ket. gambar: Tipikal endapan bedded manganese and tambang artisa...
Teknologi eksplorasi pertambangan Pemetaan Eksplorasi Ket. gambar: Tipikal endapan bedded manganese and tambang artisanal di NTT
Agenda
Arie Naftali Hawu Hede, ST., MT., Ph.D. KK – Eksplorasi Sumberdaya Bumi Teknik Pertambangan Fakultas Teknik Pertambangan dan Perminyakan Institut Teknologi Bandung E-mail:
[email protected]
Pendahuluan dan tantangan eksplorasi Pengenalan remote sensing Optikal remote sensing dan aplikasinya untuk eksplorasi mineral Microwave remote sensing dan aplikasinya LiDAR
“Industrial, technological, and economic developments depend on the availability of metallic raw materials” Douce, A.E.P. (2015) Metallic mineral resources in the 21st century. Natural Resources Research. Perkiraan kebutuhan sumberdaya mineral di masa depan • Proyeksi kumulatif kebutuhan metal masa depan, relatif kepada produksi total tambang tahun 1900-2012. • Pada 80-90 tahun kedepan kemungkinan kebutuhan metal mengalami peningkatan sekitar 10 kali dari total yang sudah ditambang dari tahun 1900.
Konsekuensi logis:
1. 2.
More exploration Better technology
3.
Reclassification of sub-economic resources to reserve
Pendapatan pemerintah
Lapangan kerja
Perkembangan Sumber ekonomi & energi teknologi
Akses, air & lingkungan
Berdasarkan pada sifat-sifat endapan, metoda penyelidikan dan pendekatanpendekatan teknologi yang digunakan, metoda eksplorasi secara umum dapat dibedakan menjadi 2 (dua): Eksplorasi Tak Langsung Kegiatan umum
Tidak berhubungan (kontak) langsung dengan objek yang dieksplorasi
Prinsip pekerjaan
Memanfaatkan sifat-sifat fisik/kimia dari endapan
Identifikasi Metoda Tahapan eksplorasi Teknologi Biaya Waktu
Melalui anomali-anomali yang diperoleh dari hasil pengamatan/pengukuran Penginderaan jarak jauh, survei geokimia, survei geofisika Digunakan pada tahapan Reconnaissance (Eksplorasi Pendahuluan) s/d Prospeksi Membutuhkan peralatan (teknologi) relatif tinggi Biaya per satuan luas murah Relatif cepat
Eksplorasi Langsung Langsung berhubungan (kontak) dengan objek yang dieksplorasi Melakukan pengamatan/penyelidikan secara langsung terhadap terhadap endapan secara fisik Melakukan analisis megaskopis dan mikroskopis terhadap objek penyelidikan Pemetaan, uji sumur, uji parit, pemboran Digunakan pada tahapan Prospeksi Finding (Eksplorasi Detail)
Membutuhkan teknologi yang lebih sederhana s/d manual Biaya per satuan luas mahal Memerlukan waktu lebih lama
Tantangan eksplorasi endapan bahan galian Model struktur secara umum
•
Endapan mineral “permukaan” banyak yang sudah ditemukan sejak lama – Endapan mineral “bawah permukaan” masih terus di eksplorasi
•
• •
Peningkatan permintaan komoditas tambang yang tidak sebanding dengan laju penemuan baru. Dibutuhkan kebaruan teknologi Biaya eksplorasi yang sangat tinggi, khususnya aktifitas pemboran. Pemahaman sistem geologi secara komprehensif. Mineral Systems + Predictive Models + Vectors =
exploration success?
Integrasi citra setelit yang menunjukan tipe litologi yang berbeda dan struktur lipatan dan interpretasi struktur bawah permukaan
RS Environmental monitoring
Data topografi dengan remote sensing
Microwave Remote Sensing Analisis kimia dan mineralogi data bor
Ekstrasi struktur geologi berdasarkan data remote sensing dan modeling patahan 3D
Topographic change monitoring by D-InSAR Eksplorasi geofisika dan geokimia
Plant processing
Analisis hidrogeologi
Magma chamber
Data integration (Spatial database)
Optimal operation control system Analisis kimia dan mineralogi
Penginderaan jauh / inderaja (remote sensing)? Ilmu tentang memperoleh (acquiring), mengolah (processing), dan interpretasi gambar/citra dan data-data terkait yang didapatkan dari pesawat dan satelit, yang merekam hasil interaksi antara objek material dan radiasi elektromagnetik (Sabins, 1997).
Sensor Radiation Reflectance
Metode Ground Based
Observasi dan pengukuran Kondisi muka bumi
Sensor
Citra Metode Remote Sensing
Spasial database
Aplikasi remote sensing
(1) Analisis intensitas nilai refleksi material→ indentifikasi jenis material Agrikultur (jenis tanaman), Geologi (jenis mineral dan
batuan） Tectonofisik (struktur geologi) Disaster prevention (analisis landslide) Lingkungan (ozone hole, water pollution, desertification)
(2) Analisis radians → Estimasi temperatur permukaan Monitoring sea temperature, urban environment, Meteorology
(3) Analisis intensitas back-scattering gelombang microwave → Estimasi surface roughness, surface movement Marine (gelombang), Meteorology (rainfall, angin), Soil (water content), Terrain (elevation), Disaster prevention (crustal movement with earthquake, topographic change with eruption and ground subsidence)
Interaksi gelombang elektromagnetik dengan material
Aplikasi Remote Sensing
Ozone Hole
Petroleum Exploration Water Resource Exploration
Land Slide Volcanic Activity
Mineral Resource Exploration
Typhoon & rainfall
Land Use Pattern Topography
Glacier & Drift Ice
Sea Pollution Vegetation Distribution
Sea Surface Temperature & Concentration of Vegetable Plankton
Contoh Satelit Pengamatan Bumi Middle to High Spatial Resolution Sensor pasif
LANDSAT (USA)
SPOT (France)
QuickBird (USA)
Specific Uses
Marine Observation Satellite MOS: (Japan)
NOAA (USA)
SAR Satellites Using Microwaves
ALOS (Japan)
－Cloud and humidity mapping －Sea surface temperature
ERS (Europe)
RADARSAT (Canada)
Sensor aktif
Soil
Emissivity properties Intensity
-launched in 2013-
Reflectance properties Intensity
Landsat 8
Plant
Water
Ultraviolet
Visible regions
wavelength
Infrared regions Multispectral Panchromatic
Land
http://landsat.usgs.g ov/ldcm_vs_previous
Sea
Atmosphere
Wavelength Bands of Satellites & Reflectance and Emissivity Properties
I. Optical Sensor Remote Sensing – prinsip dasar Definisi reflektans dan emissivity I
Reflectance=
Reflection Emittance
Rs
Rs I
Sensor
Emissivity =
Radiance energy from object Radiant energy from black body with the same temperature as object Function of
Sumber energi : matahari
temperature
＜Planck’s law＞ & wavelength
Sumber energi : obyek
Bλ(T) = 0.5
3
10
Wavelength（μm）
1 2hc2 ・ exp hc / kT 1 λ5
Bλ(T) : Radiance of black body ( W・m-2・sr-1・μm-1 ) T : Temperature of black body (K) λ: wavelength (μm ) c : Velocity of light 2.998×108 (m・s-1 ) h : Plank’s constant 6.626×10-34 (J・s ) k : Boltzman’s constant 1.380×10-23 (J・K-1 )
Electromagnetic wave
Atom
Atom
Absorption of Electromagnetic Wave by Molecular Vibration
Reflectance Spectra of Clay Minerals
Visible 0.63 – 0.69 m (Band 3)
Visible 0.52 – 0.60 m (Band 2)
We can’t see in this wavelength.
Visible 0.45 – 0.52 m (Band 1)
Near infrared 0.75 – 0.90 m (Band 4)
Subscene Band Images of LANDSAT TM Sensor
Short Wave Infrared 1.55 – 1.75 m (Band 5)
Thermal Infrared 10.40 – 12.50 m (Band 6)
We can’t see in these wavelengths.
Short Wave Infrared 2.08 – 2.35 m (Band 7)
*Spatial Resolution Band 1, 2, 3, 4, 5, 7 → 30 m Band 6 → 120 m
Subscene Band Images of LANDSAT TM Sensor
Image acquisition date: May 16, 1996
Infrared Image (B: 5, G: 4, R: 7)
We can’t see in this wavelength.
False Color Composite Images of LANDSAT TM Images
True Color Image (B: 1, G: 2, R: 3)
Relative temperature of sea surface
Thermal Infrared Color Image (B: 5, G: 4, R: 6)
False Color Composite Images of LANDSAT TM Images
True Color Image (B: 1, G: 2, R: 3)
Natural Color Image (B: 1, G: 4, R: 3)Image
Infrared Color Image (B: 5, G: 4, R: 7) Thermal Infrared Image (B: 5, G: 4, R: 6)
Aplikasi analisis respons spektral untuk eksplorasi a
b
Illite-smectite Argillic alteration
Kaolinite
b)
A quartz vein showing mostly coarse-grained quartz layering with microgranule quartz. Altered tuff litic formed by fragments of andesitic, quarzitic, plagioclase, clay and opaque mineral. altered rocks
a
b
P-18 P-13 P-15
fresh quartz rocks 0.5
1.0
1.5 2.0 Wavelength (µm)
Rock samples
P-12
Reflectance (Offset for clarity)
Reflectance (Offset for clarity)
P-15 P-14 P-01
2.5
P-07
Quartz
Albite
Propylitic alteration
quartzmontmorillonitealbite
Reflectance (Offset for clarity)
a)
Montmorillonite
1 mm
1 mm
Calcite
Chlorite
Epidote
P-04 P-05 P-16
Quartz-illitekaolinite-montmorillonite 0.5
1.0
1.5 2.0 Wavelength (µm)
Soil samples
2.5
0.5
1.0 1.5 2.0 Wavelength (µm) The USGS and JPL spectral library
2.5
19
Remote sensing untuk eksplorasi mineral Sabins, F.F. (1999) Ore Geology Reviews 14, pp. 157-183.
Aplikasi remote sensing untuk eksplorasi sebagai berikut: (1) Pemetaan geologi dan struktur geologi (faults & fractures) yang berkaitan endapan mineral
A SPOT-Landsat TM ratio threshold merge of the area around the southern Chocolate Mountains illustrating extensional antiforms and areas of potential hydrothermal alteration highlighted in yellow.
Landsat TM 741 color composite image of the southern Colorado River illustrating extensional faults and the newly interpreted accommodation zone.
Image processing to emphasize the clay minerals which have reflectance absorption at 2 - 2.5 m.
Pemetaan eksplorasi:
Color Composite image using visible band data
Image processing to emphasize the ferrous oxide minerals which have reflectance absorption at 0.4 -1.2 m
(2) Memetakan alterasi hidrotermal berdasarkan respons spektral. - Perhitungan band ratio untuk identifkasi komponen alterasi mineral; iron minerals, & clays + alunite
Spectral reflectance curves are for vegetation and sedimentary rocks. Sabins, F.F. (1999) Ore Geology Reviews 14, pp. 157183.
Recognizing hydrothermally altered rocks at Goldfield mining district, NV. Color composite image of AVIRIS endmember abundance images. Illite=red, alunite=green, kaolinite=blue.
Map showing geology and hydrothermal alteration of Goldfield mining district, NV. Sabins, F.F. (1999) Ore Geology Reviews 14, pp. 157-183.
Recognition of hydrothermal clays and alunite from TM data, Goldfield mining district.
Field spectra averaged. of altered and unaltered rocks at Goldfield mining district.
Sabins, F.F. (1999) Ore Geology Reviews 14, pp. 157-183.
Reflectance spectra for halite (NaCl) and ulexite (NaCaB5O 8H2O). TM bands 4 and 7 are used to calculate 4/7 ratio image.
Model deposit Model skematik zona alterasi hidrotermal di daerah Gold Field Mine
Models of porphyry copper and related hydrothermally altered zone.
Sabins, F.F. (1999) Ore Geology Reviews 14, pp. 157183.
Satellite Image of Porphyry Copper Deposit
Visible and Near Infrared
Shortwave Infrared
ASTER image near the Escondida Cu-Au-Ag open-pit mine. Current capacity is 127,000 tons/day of ore. Escondida is related geologically to three porphyry bodies intruded along the Chilean West Fissure Fault System. The SWIR image highlights lithologic and alteration differences of surface units. http://earthobservatory.nasa.gov/IOTD/view.php?id=1000
Sabins, F.F. (1999) Ore Geology Reviews 14, pp. 157-183.
Laboratory spectra of alteration minerals in the 2.0 to 2.5 m band. Spectra are offset vertically. Note positions and bandwidths of the spectral bands recorded by AVIRIS and TM band 7.
Thermal emissivity spectra of igneous rocks with different silica and quartz contents. Arrows show centers of absorption bands. Note positions of spectral bands recorded by ASTER and TIMS.
Application of ASTER Data to Mineral Exploration Band 1 2 3 4 5 6 7 8 9 Wavelength (m) 0.52 - 0.60 0.63 - 0.69 0.76 - 0.86 1.600 - 1.700 2.145 - 2.185 2.185 - 2.225 2.235 - 2.285 2.295 - 2.365 2.360 - 2.430 Band 10 11 12 13 14 Wavelength (m) 8.125 - 8.475 8.475 - 8.825 8.925 - 9.275 10.25 - 10.95 10.95 - 11.65
Mineralogical indices for VNIR and SWIR bands
Thermal emissivity spectra of igneous rocks with different silica and quartz contents. Arrows show centers of absorption bands. Note positions of spectral bands recorded by ASTER and TIMS.
Pour and Hashim (2012) Ore Geology Reviews
Supervised classification using the USGS reference spectra overlying the ASTER false color image (6, 4, 2) in red, green, and blue and the mapped faults and lineaments. Amer et al. (2012) Ore Geology Reviews
Field & Laboratory Measurement of Spectra for Ground Truth of Remote Sensing Image
Laboratory spectrometer for samples
FieldSpec4 Target wavelength：0.485～2.5 m Examples of spectrometers available for ground truth
Fourier spectrometer FTIR Target wavelength：8～14 m
II. Microwave Remote Sensing & Synthetic Aperture Radar (SAR)
Terrain returns and image signatures for a pulse radar energy
Radar Equation
Pr (4 )3 R 4 = j = Pt G 22 j
: back-scattering intensity R: range G: antenna gain : wave length Pr: received power Pt: transmitted power
Relationship between surface roughness and scattering intensity of microwave
Frequency range L band: 1 to 2 GHz C band: 4 to 8 GHz X band: 8 to 12 GHz
Reflectance and primary interaction of X-, C-, L-, and P-band radars with forest canopies Purkis, S. J. and Klemas, V. V. (2011) Remote Sensing and Global Environmental Change, Wiley-Blackwell.
★Advantages of SAR (Synthetic Aperture Radar） Image
・Data can be acquired under any weather conditions, because microwaves can penetrate clouds. ・Interferograms can be produced by interferometric methods from two different overpasses ★Applications ・Generating Digital Elevation Model ・Tracking movements of major glaciers ・Estimating topographic changes with eruptions, earthquakes, and subsidence
Interferogram image of Antarctica Mt. Etna (Italy)
Topographic change pattern near the Nojima fault
(b)
(a) N
Perspective view from the northeast
InSAR for Producing DEM
20 44’9”W 7910’5”S
4500
2021’24”W 7823’32”S
4000
(m)
Relative elevation
1000
1500
2000
20 km
Perspective view from the southwest
500
1000
1500
1653’32”W 7914’6”S
2000
500
Oval feature
2500
2π
3000
0
3500
(c)
2500
3000
3500
N
20 km
750 700 650 600 550 500 450 400 350 300 250 200 150 100 50 0 -50 -100 -150 -200
1630’28”W 7827’34”S
Koike et al. (2012) EPS
SAR-based Characterization of Distribution Pattern of Pyroclastic Flow Deposits at Mt. Merapi during the Past Ten Years
Intensity images of JERS-1 and RADARSAT-1 SAR data around Mt. Merapi at a descending
Examples of Merits
Conceptual model of a dipping conduit and three magma reservoirs formed at different depths to explain the cause of the temporal changes of the Pzones.
Crustal movement induced by the Sichuan Earthquake (2008) Source: Geographical Survey Institute
Crustal movement induced by the Tohoku-oki Earthquake in 2011
www.jishin.go.jp/main/eisei/eisei_furoku .pdf
Horizontal movements during 15 days by GPS showing the eastward movement of the whole Tohoku district.
http://www.gsi.go.jp/cais/topic110314-
Interferogram showing subsidence of the whole Tohoku district. Subsidence increases toward the epicenter.
Overviews of SAR data processing Observation system of JERS-1 SAR
・The sensor records the backscattering intensities from the surface materials.
・The back scattering depends on JERS-1 surface roughness and dielectric constant. H
Frequency： 1.275 GHz （L band）
Wavelength ： 23.5 cm
H: Orbit height (568 km)
i0
: Slant range (709 km) : Offnadir angle (35゜) i0: Incident angle (39゜) W: Scan width (75 km) D: Real aperture length (12 m) L: Synthetic aperture length (13.9 km)
L: Spatial resolution (18 m)
After RADARSAT INTERNATIONAL, “RADARSAT-2: The Next Generation in SAR Imaging”, Earth Observation Conference 2001, Tokyo Japan
Meaning of Polarimetry
HV: Volume scattering HH: Two reflections
Volume scattering
VV: Surface scattering
Surface scattering Two reflections
Color Composite of Polarimetric SAR Images of Mt. Sakurajima
X-band SAR image (9.55 GHz)
L-band SAR image (1.27 GHz)
R: HH, G:HV, B:VV
R: HH, G:HV, B:VV
Data set of Communication Research Laboratory/ NASDA SAR (Pi-SAR)
Applications of Interferometric Study Areas SAR to Topographic Mapping and Change Mt. Merapi, Indonesia Saga Plain
Mt. Hossyo
阿蘇中岳 100 km
The SAR data used are
Mt. Aso
・JERS-1 SAR （Japan） ・RADARSAT （Canada） Mt. Sakurajima
Application of interferometric SAR to DEM作成手 generating Digital Elevation Model
順
DEM produced from Interferometric SAR Mt. Sakurajima
Interferogram related to topography Phase unwrapping
Expanding the phase fluctuating periodically between 0 - 2 to continuous values
Application of Interferometric SAR to Extracting Topographic Changes of Active Volcanoes: (1) Case Study of Mt. Sakurajima Pair 1
Pair 2
Pair 4
Pair 3
1993 1993/6
1994/1
1993/ 5～10 Quiet period
1996/12 1997/1
1996/1
1995/ 8/ 23,24: Eruptions
1996/ 3: Frequent small eruptions
Increase of Pressure of the Aira Caldera 13030 3147
N
No. 1 2 3 4
MASTER 1993/6/7 1994/1/13 1996/1/31 1996/12/4
SLAVE 1994/1/13 1996/1/31 1996/12/4 1997/1/17
Days 220 748 308 44
B⊥ Coherence 453 0.214 35.0 0.231 220 0.312 18.6 0.616
Range
North summit Azimuth
Kagoshima City
Aira Caldera Mt. Sakurajima Kagoshima Bay 10 km
Osumi Peninsula
3129 13056
JERS-1/SAR
South summit 2km
ROW-79 ，PATH-248
Comparison of topographic change pattern obtained from interferometric SAR with the data of level surveying Vertical displacements based on level surveying (1991/12 ～ 1996/10）
Total topographic changes estimated from interferometric SAR （1994/1/13 ～ 1996/12/4） +5.88cm
N
0
‐5.88cm 2km
Mt. Sakurajima
SAR Interferometry for Land Subsidence Detection in Coal Mining Areas (1) Perski & Jura, ESA EOQ 63, pp. 25-29
Ground deformation map in Poland derived China from ERS pair: 3 Sep. 1993 – 8 Oct. 1993
Scheme showing interpretation of SAR interferogram in a subsidence trough
SAR Interferometry for Land Subsidence Detection in Coal Mining Areas (2)
Development of subsidence with coal mining at a depth of 300 to 450 m in Poland, detected from ERS SAR
Development of subsidence with coal mining in German, detected from ERS SAR (Spreckels et al., 2001)
Ground deformation map in northern derived China from ALOS pair: 15 Dec. 2007 – 30 Jan. 2008 overlaid on an optical image (Ge et al., The International Archives of the Photogrammetry, Remote Sensing and Spatial
Application of PSInSAR to Landslide
http://massa.geoazur.eu/interfero_30_11_2010/3_experiences_Piemont.pdf
Application of SAR image (8
Analisis Kelurusan (Lineament) Lineament…straight or slightly curved lines appearing on images surface
fault
Kelurusan yang dapat berhubungan dengan struktur patahan dapat diidentifikasikan langsung dari citra satelit.
Fault portions are selectively eroded and make valley features. ↓ Extraction of large change portions of brightness from satellite image
Contoh analisis kelurusan yang berhubungan struktur geologi
Distributions of three kinds of lineaments in the northern African Continent originated from the topography, gravity, and magnetic data and their superimposition on the geological map.
Overlay of the three kinds of lineaments onto the thickness of sedimentary rocks. Recent (19002006) earthquake epicenters are also shown on the composite map with their magnitudes.
Masoud and Koike (2011) ISPRS Journal of Photogrammetry and Remote Sensing
Perspective View of Estimated Fracture Planes from Lineaments and DEM Data 10 km 800 岳湯 Takenoyu
N
Fracture Zone Mt Waita 涌蓋山
九重町
1000 Otake 大岳
Fracture Zone
リニアメント1200
推定断裂面 八丁原 1400 一目山 1400 星生山
0 0
Temperature (C)
1800m 以上
1000m 2000
5 km
0 -1000 -2000 -3000
2
West
600m
1000
10
4
6
8
10 (km)
East
10 km
Assumed fracture zones & 1400m location of cross-section
Otake Power Station
300
0
1600
3D temperature distribution and fluid flows calculated from FEM
Light Detection and Ranging (LiDAR)
Sensor pasif Radar: - Memakai gelombang microwave - Menentukan jarak dan sudut suatu benda berdasarkan posisinya LiDAR: - Memakai optical laser light - Menentukan jarak suatu benda
Sensor aktif
Mengapa memilih teknologi LiDAR? • Pemetaan dengan LiDAR jauh lebih aman dan jauh lebih cepat daripada metode pemetaan konvensional. • Mendukung proses kegiatan pertambangan secara cepat • Ideal untuk analisis temporal perubahan morfologi. • Dapat diintegrasikan dengan database lain.
Prinsip dasar LiDAR
Terrestrial Laser Scanning (TLS)
Terrestrial Laser Scanning (TLS) – prinsip kerja
Airborne Laser Terrain Mapper – ALTM 3100
• • • • • • •
Up to 100,000 pengukuran/detik Cocok untuk segala jenis pesawat Mengukur intensitas IR, x, y,& z Resolusi vertikal: ~ 5 – 10 cm Resolusi horizonal: ~ 15 cm Ketinggian jelajah – 3 km Luasan daerah – 50 km2/jam
Rapid 3D digital elevation data
Metodologi
Metodologi • Pengukuran dan output – – – – –
Range Scan angle Posisi sensor (geodetic reference) Orientasi sensor Amplitude signal (intensitas)
• Pengolahan data – Perhitungan koordinat x, y, z – Analisis filtering dan fungsi-fungsi lain Teknis: • Download data dari hard drive • Download GPS data dari sistem wahana (airborne) dan base-station • Pengolahan dengan software aplikasi
Aplikasi LiDAR • Visualisasi permukaan bumi: Digital terrain model (DTM) & Digital elevation model (DEM)
Gray scale intensity image
Digital elevation model
Color coded elevation intensity image
Active laser photo
Keuntungan LiDAR • LiDAR manggunakan gelombang aktif sehingga akuisisi laser pun dapat dilakukan malam hari. • Kecepatan akusisi data. • Kerapatan point/titik ground yang dihasilkan per 1 meter sq minimal 1 point tapi bisa sampai 9 point tergantung permukaan dan tinggi terbang (metode akuisisi) serta FoV (Field of View/ sudut pandang sensor ke bumi). • Besaran pulse alat tidak begitu mempengaruhi, saat ini sudah ada vendor yang mampu membuat alat LiDAR dengan pulse diatas 500kHz, pulse besar ini akan maksimal jika pengambilan/akuisisi data dengan pesawat bisa “terbang tinggi”. Untuk wilayah Indonesia negera tropis dimana awan berada di ketinggian 1000 s/d 1500 meter, maka pesawat akan terbang di bawah awan. Untuk terbang dengan ketinggian dibawah 1000 meter, adalah cukup menggunakan pulse 75120 kHz dan FoV 18 s/d 25 deg. • Karena menggunakan pesawat udara, akses lebih mudah tentunya untuk mengakuisisi/mencapai ke setiap bagian site. • Hanya butuh 1 titik control tanah (BM) untuk radius terbang akuisisi 30 sd 40 km dari titik control tanah tersebut. • Biaya lebih efisien dan efektif.
Kekurangan LiDAR • Tidak bekerja maksimal di daerah yang tertutup awan/kabut • Pulse tidak dipantulkan dengan baik jika objek-objek pantul basah (berair). Karena pulse Topographic LiDAR akan diserap / hilang jika mengenai air seperti sungai atau pemukaan yang masih basah akhibat embun atau hujan. LiDAR yang digunakan untuk Hydrographic berbeda dengan Topo, untuk Hydro dikenal dengan nama SHOALS atau singkatan dari Scanning Hydrographic Operational Airborne LiDAR Survey. System ini mampu mengakuisisi permukaan air dan kedalaman air 50 s/d 60 meter dari permukaan air. • Ketidakmampuan untuk penetrasi daerah tertutup vegetatsi lebat. • Akurasi data LiDAR atau ketelitiaan yang dihasilkan LiDAR bervariatif, sangat bergantung pada kondisi permukaan. Untuk area terbuka keras ketelitan bisa mencapai dibawah 5 cm. Ketelitian Horizontal 2 kali s/d 5 kali lebih “jelek” dari dari ketelitian Vertical.
