REPORT ON VALERI INDONESIAN CAMPAIGN 1-9 MAY, 2001

Similar documents
GROUND DATA PROCESSING & PRODUCTION OF THE LEVEL 1 HIGH RESOLUTION MAPS

BV NNET User manual. V0.2 (Draft) Rémi Lecerf, Marie Weiss

SUGARCANE GROUND REFERENCE DATA OVER FOUR FIELDS IN SÃO PAULO STATE

COMPATIBILITY AND INTEGRATION OF NDVI DATA OBTAINED FROM AVHRR/NOAA AND SEVIRI/MSG SENSORS

University of Texas at San Antonio EES 5053 Term Project CORRELATION BETWEEN NDVI AND SURFACE TEMPERATURES USING LANDSAT ETM + IMAGERY NEWFEL MAZARI

The techniques with ERDAS IMAGINE include:

SMEX04 Vegetation Data

PROFILE BASED SUB-PIXEL-CLASSIFICATION OF HEMISPHERICAL IMAGES FOR SOLAR RADIATION ANALYSIS IN FOREST ECOSYSTEMS

PLANET SURFACE REFLECTANCE PRODUCT

CanImage. (Landsat 7 Orthoimages at the 1: Scale) Standards and Specifications Edition 1.0

Remote sensing image correction

Part 1. Tracing the Dimensions of Some Common Pixel Sizes using a GPS Receiver

The New Rig Camera Process in TNTmips Pro 2018

Detecting Greenery in Near Infrared Images of Ground-level Scenes

MRLC 2001 IMAGE PREPROCESSING PROCEDURE

Nadir Margins in TerraSAR-X Timing Commanding

DEVELOPMENT OF A NEW SOUTH AFRICAN LAND-COVER DATASET USING AUTOMATED MAPPING TECHINQUES. Mark Thompson 1

Figure 3: Map showing the extension of the six surveyed areas in Indonesia analysed in this study.

Camera Requirements For Precision Agriculture

Camera Requirements For Precision Agriculture

Orthoimagery Standards. Chatham County, Georgia. Jason Lee and Noel Perkins

v Introduction Images Import images in a variety of formats and register the images to a coordinate projection WMS Tutorials Time minutes

The Chicago Urban Heat Island (Night of August 13 th, 2007)

AVNIR-2 Ortho Rectified Image Product. Format Description

Analyzing Hemispherical Photographs Using SLIM software

v WMS 10.0 Tutorial Introduction Images Read images in a variety of formats and register the images to a coordinate projection

Image transformations

Report of International Internship

Basics of Photographing Star Trails

News on Image Acquisition for Campaign 2008

Figure 1 - The Main Screen of the e-foto Photogrammetric Project Creation and Management

MULTI-TEMPORAL OBSERVATIONS OF SUGARCANE BY TERRASAR-X IMAGES

Application of GIS to Fast Track Planning and Monitoring of Development Agenda

Acquisition of Aerial Photographs and/or Satellite Imagery

8. EDITING AND VIEWING COORDINATES, CREATING SCATTERGRAMS AND PRINCIPAL COMPONENTS ANALYSIS

Remote Sensing. The following figure is grey scale display of SPOT Panchromatic without stretching.

Inserting and Creating ImagesChapter1:

Satellite data processing and analysis: Examples and practical considerations

An Introduction to Remote Sensing & GIS. Introduction

Acquisition of Aerial Photographs and/or Imagery

Chapter 3 Solution to Problems

Rectifying the Planet USING SPACE TO HELP LIFE ON EARTH

THE NASA/JPL AIRBORNE SYNTHETIC APERTURE RADAR SYSTEM. Yunling Lou, Yunjin Kim, and Jakob van Zyl

Image interpretation I and II

Leica ADS80 - Digital Airborne Imaging Solution NAIP, Salt Lake City 4 December 2008

Application of Satellite Imagery for Rerouting Electric Power Transmission Lines

Monitoring agricultural plantations with remote sensing imagery

Guidelines for Laying Targets for Ground Control Points

MULTIRESOLUTION SPOT-5 DATA FOR BOREAL FOREST MONITORING

Separation of crop and vegetation based on Digital Image Processing

GeoBase Raw Imagery Data Product Specifications. Edition

SMEX04 Multispectral Radiometer Data: Arizona

GEO 428: DEMs from GPS, Imagery, & Lidar Tuesday, September 11

Seasonal Progression of the Normalized Difference Vegetation Index (NDVI)

A study of the ionospheric effect on GBAS (Ground-Based Augmentation System) using the nation-wide GPS network data in Japan

Basic Digital Image Processing. The Structure of Digital Images. An Overview of Image Processing. Image Restoration: Line Drop-outs

PROCEEDINGS - AAG MIDDLE STATES DIVISION - VOL. 21, 1988

DEM GENERATION WITH WORLDVIEW-2 IMAGES

White Paper. Medium Resolution Images and Clutter From Landsat 7 Sources. Pierre Missud

MEASURE Evaluation. Global Positioning System Toolkit

TRUESENSE SPARSE COLOR FILTER PATTERN OVERVIEW SEPTEMBER 30, 2013 APPLICATION NOTE REVISION 1.0

This talk is oriented toward artists.

Planet Labs Inc 2017 Page 2

Forest Inventory System. User manual v.1.2

DETECTION AND MAPPING OF THE DISASTER-STRICKEN AREAS FROM LANDSAT DATA

BGRI Stem Rust Survey Protocol. Overview of Field Survey Procedure

FREQUENCY DECLARATION FOR THE ARGOS-4 SYSTEM. NOAA-WP-40 presents a summary of frequency declarations for the Argos-4 system.

Use of FORMOSAT images over the Gourma site (Mali)

PLANET IMAGERY PRODUCT SPECIFICATIONS PLANET.COM

TEMPORAL ANALYSIS OF MULTI EPOCH LANDSAT GEOCOVER IMAGES IN ZONGULDAK TESTFIELD

Monitoring of Mosul Reservoir Using Remote Sensing Techniques For the Period After ISIS Attack in 9 June Muthanna Mohammed Abdulhameed AL Bayati

FORESTCROWNS: A SOFTWARE TOOL FOR ANALYZING GROUND-BASED DIGITAL PHOTOGRAPHS OF FOREST CANOPIES

Lecture # 7 Coordinate systems and georeferencing

Introduction to WG5 on CwRS imagery use and alternatives and QE5 on claimed rate inside the RP Peter Viskum Jørgensen, FERV and Birger Faurholt

Lab 3: Image Acquisition and Geometric Correction

Vegetation Phenology. Quantifying climate impacts on ecosystems: Field and Satellite Assessments

Variance and Anomaly Analysis with WIM/WAM Mati Kahru

RADIOMETRIC AND GEOMETRIC CHARACTERISTICS OF PLEIADES IMAGES

Leica - 3 rd Generation Airborne Digital Sensors Features / Benefits for Remote Sensing & Environmental Applications

High Latitude Drone Ecology Network Multispectral Flight Protocol and Guidance Document

SDCG-5 Session 2. Landsat 7/8 status and 2013 Implementation Plan (Element 1)

RADIOMETRIC CALIBRATION

CALIBRATION OF OPTICAL SATELLITE SENSORS

MONITORING OF FOREST DAMAGE CAUSED BY GYPSY MOTH IN HUNGARY USING ENVISAT MERIS DATA ( )

CMS Note Mailing address: CMS CERN, CH-1211 GENEVA 23, Switzerland

SPOT 5 / HRS: a key source for navigation database

Digital database creation of historical Remote Sensing Satellite data from Film Archives A case study

(Presented by Jeppesen) Summary

Experiment P02: Understanding Motion II Velocity and Time (Motion Sensor)

Application of GIS for earthquake hazard and risk assessment: Kathmandu, Nepal. Part 2: Data preparation GIS CASE STUDY

Q A bitmap file contains the binary on the left below. 1 is white and 0 is black. Colour in each of the squares. What is the letter that is reve

Costal region of northern Peru, the pacific equatorial dry forest there is recognised for its unique endemic biodiversity

GEOMETRIC RECTIFICATION OF EUROPEAN HISTORICAL ARCHIVES OF LANDSAT 1-3 MSS IMAGERY

The effects of uncertainty in forest inventory plot locations. Ronald E. McRoberts, Geoffrey R. Holden, and Greg C. Liknes

Spectral Reflectance Sensor SRS-NDVI

Line and polygon features can be created via on-screen digitizing.

AT-SATELLITE REFLECTANCE: A FIRST ORDER NORMALIZATION OF LANDSAT 7 ETM+ IMAGES

M. WEISS/F. BARET 15 th NOVEMBER, R. Bosseno CESBIO E. Mougin, F. Gascon, L. Jarlan Y. Tarcol, E. Martin

SUGAR_GIS. From a user perspective. Provides spatial distribution of a wide range of sugarcane production data in an easy to use and sensitive way.

Lesson 3: Working with Landsat Data

Transcription:

REPORT ON VALERI INDONESIAN CAMPAIGN 1-9 MAY, 2001 Under the palms of Aek Loba estate Field data collected by: Camille LELONG CIRAD-AMIS (GEOTROP), Montpellier, France camille.lelong@cirad.fr With the collaboration of: Vincent ABT, CIRAD-AMIS, Montpellier, France Jean-Charles JACQUEMARD, CIRAD-CP, Aek Loba, Sumatra Edyana SURYANA, SOCFINDO, Aek Loba, Sumatra

CONTENT Erreur! Signet non défini. A] Localisation and description of the test area. 3 B] Data acquisition sampling and protocol 3 C] Central transepts acquisition protocol 4 D] LAImeters intercalibration 5 E] SPOT image 6 F] Hemiviews 9 G] GPS coordinates measurements 9 H] Annex measurements 10 H.1 Positions 10 H.2 Photos 10 H.3 Architectural data 11 H.4 Planted material 11 I] Files description 12 J] LAI and NDVI: a short glance 13 2

A] Localisation and description of the test area. This VALERI test site is located in Aek Loba, North Sumatra, Indonesia. It consists of a 3 km x 3 km square area centred on the geographic coordinates 99 35 2 38. Its general location is shown on the following maps (Figure 1). The VALERI square area is part of an industrial oil palm estate, managed by the company SOCFINDO (based in Medan). Each parcel was homogeneously planted with given material of the same age. Material and age differ from one parcel to another with some repetition through the site, and several types of canopy architecture and density can be observed. Aek Loba SUMATRA AEK LOBA Figure 1: Maps of Sumatra Island, Indonesia, and location of Aek Loba oil palm estate. B] Data acquisition sampling and protocol Sampling was based on an RGB Landsat image acquired in September 2000 and the plantation data base, to select the more representative parcels in regards with the area variability. The 1km lattice scheduled by the VALERI sampling protocol does not fit too well the estate organisation, where parcels size slightly exceeds 1km long and is less than 250m wide.thus, the number of measured plots varies from one to six per square kilometre. Measurement plots were chosen at the centre of each half of selected parcels, as shown on Figure 2, and consisted in several handlings : LAImeter (Licor Canopy Analyzer), numerical hemispheric camera (Nikonview with a FishEye lens), and Global Positioning System (Garmin III+). The two last types of data were acquired once per plot, at the centre of the LAImeter cross, this one corresponding to 6 acquisitions in the North/South axis and 6 in the East/West axis, at 4m from each other. The cross branches are thus 20m long, corresponding to SPOT image pixel dimension (Figure 3). Remark: when underlying vegetation (adventitious) was present (two kinds of fern: a blue and a green one, Figure 4), LAImeter acquisition was done below this vegetation. 3

303N 302N 301N N 304C 308N 303S 302S 306N 301S 305N 4m 308S 306S 305S 312N 311N 310N 309N W E 312S 311S 310S 309S 314N 314S 313N 313S 9m 320N 319N 319S 318N 318S 317N 317S Figure 2 : location of measured parcels in the 2000-Landsat image. S Palm Hemiview and GPS LAImeter Figure 3 : location of the different data acquisitions at a given measurement plot, with their position relative to palms. At the end, 32 measurement plots have been performed in the VALERI square area, corresponding to 17 of the 20 parcels of exploitation included in this square. Note that lower left corner of the test site is very badly sampled, due to huge heterogeneity in this area. Figure 4 : two different kinds of adventitious vegetation: at the left, green fern, sometimes arborescent, and at the right: blue fern, with shotsilk effects. C] Central transepts acquisition protocol In the aim of field data spatialisation with krigeage geostatistical method, special care has been given to characterise the short distances variability, which is the more difficult to reach through statistics. Thus, additional data acquisitions have been performed close to the test site centre, following two orthogonal transepts, 1km-long each, oriented North-South and East- West. LAImeter records were made at the centre of the corresponding cross, and each 50m to 50m point from the centre to the extremity of each branch (N, E, S, and W), leading to 10 measurements in each branch and 41 measurements in the whole. Figure 5 shows a schematics corresponding to this protocol. GPS measurements were performed at the centre and each extremity of the cross. 4

W LAImeter LAImeter and GPS 10 100m 3 2 40 1 11 12 21 N 20 Figure 5 : location of the different data acquisitions along the two linear transepts. Blue circles correspond to LAImeter records and red and blue discs to LAImeter and GPS position records. Numbers indicate order of measurements in the sequence following measurement at the centre of the cross. E C 30 S D] LAImeters intercalibration Two Licor LAImeters were available for the data collection. One was lent by INRA- Avignon (named LI in the following) and the other by Cemagref-Montpellier (LC). LC was always posted in an open area (a football field), to provide the reference measurement above the canopy. When needed, an umbrella was used to avoid direct sunlit and sun reflection on the instrument sensor (Figure 6). LI was mobile, used to perform measurements below the canopy at each plot. Caps of the same aperture (90 ) cover the lens of the two sensors during the whole campaign. As the two LAImeters measurement sets will be combined to derive the LAI data, their respective flux sensitivity has to be estimated, compared, and intercalibrated. Fourteen flux acquisitions have been simultaneously acquired with the two instruments, in an open area without any obstacle, at different times and amount of light. The following graphs (Figure 7) show the interpolation derived from these measurements for each sensor ring, respectively 7, 23, 38, 53, and 68. The multiplying coefficient k to be applied to all LC data files is defined by Y = k.x, with X = LC and Y = LI. These coefficients k are derived for each sensor ring respectively: k = 0.42, 0.366, 0.379, 0.385, 0.358. 5

Figure 6 : The reference LAImeter displayed in a football field, with its dedicated watchman. 30 25 35 y = 0,42x y = 0,3661x y = 0,3787x 25 y=0.42x y=0.366x 30 y=0.379x LI 20 15 10 LI 20 15 10 LI 25 20 15 10 5 5 5 0 0 0 0 10 20 30 40 50 60 0 20 40 60 0 20 40 60 80 LC LC LC R1 R2 R3 LI 50 y = 0,3845x y=0.385x 40 30 20 10 R4 0 0 20 40 60 80 100 120 LC LI 40 y = 0,3577x 35 y=0.358x 30 25 20 15 10 5 R5 0 0 20 40 60 80 100 LC Figure 7 : Intercalibration of the two LAImeters for the five sensor rings (respectively: 7, 23, 38, 53, 68 ). X-axis corresponds to the flux recorded with LC and Y- axis to the flux simultaneously recorded by LI for the same field of view. Interpolated calibration coefficients k to be applied to the LI data files and defined by y=kx are given in each graph. E] SPOT image XS image was acquired by HRV1 (SPOT 2) on June, the 1 st, 04h05mn30s, corresponding to K-J=266-345. The whole scene is shown figure 6. It is centred on N2 30 00 - E99 45 08 (at pixel (1500,1500)). Characteristics of the observation were an orientation angle of 8.6 degrees and an incidence angle of L25 degrees, with a solar azimuth of 40.9 and a solar elevation of 63.7 degrees. The whole VALERI square area is empty of any cloud or haze. Only few small clouds are included in the enlarged area of 10kmx10km, located at the upper left corner of the image. 6

The delivered product consists in SPOTView Basic Precision at geometric processing level 2B. It is projected following UTM on WGS84 datum and spheroid, Zone 47 North. Corner locations are given in Tableau 1. Two low resolution pixels of 10kmx10km have been extracted : a first one directly centred around the 3kmx3km test site, and one shifted to the East to provide more homogeneous pixel. Corresponding corner locations, and test site corners are also given in Tableau 1. Figure 8 : SPOT full scene acquired around Aek Loba site on June 2001, the 1st. Yellow box indicates the VALERI test site square of 3 km x 3 km. Figure 9 : Zoom on the VALERI Indonesian test site 10kmx10km low resolution pixels : 2 1) directly centred around the measurement square area 2) shifted to the east to provide a more homogeneous pixel. The smaller yellow box correspond to the 3 km x 3 km VALERI square area 1 7

304C 303N 303S 302N 302S 301N 301S Figure 10 : Zoom on the VALERI Indonesian test site measurement square and measurements plots location. 308N 308S 306N 306S 305N 305S Borders of image directly fit the 3 km x 3 km test site area. 312N 312S 320N 311N 311S LC 319N 319S 310N 310S 314N 314S 318N 318S 309N 309S 313N 313S 317N 317S Measurements plots are indicated by yellow cross with corresponding parcel number (N: northern half, S: southern half, C: centre of the parcel). Yellow lines correspond to the 1 km sampling lattice. Black box indicates location of football field where LC LAImeter was set as a reference for above canopy measurements. Figure 11 : Zoom on the VALERI Indonesian test site measurement square and transepts location. The white cross indicates the location of the two linear transepts dedicated to short distance variability characterisation. Tableau 1 : UTM and image coordinates of extractions corners: Extraction name Longitude (X) Latitude (Y) Upper Left Corner Down Right Corner Upper Left Corner Down Right Corner VALERI Square 562529.76 565527.82 292344.69 289346.63 100km 2 Pixel, centred 559541.39 569538.15 295357.28 285341.14 100km 2 Pixel, shifted 562466.80 572463.56 286542.30 296539.06 8

F] Hemiviews At each measurement plots of VALERI square sampling, except in parcels 311N and 311S, a numerical photograph was acquired with a NikonView with a hemispherical lens (fisheye). File was recorded at highest resolution, in tif format, leading to images of 2048x1360 pixels. Figure 12 : hemispherical photograph of the oil palm canopy as seen from below. G] GPS coordinates measurements Each measurement plot centre for the VALERI square sampling, and each central transept extremity, was localised with a Global Positioning System (GPS). The used instrument was a Garmin GeoIII+, giving an absolute position precision of 10 to 20 meters. Only measurements acquired with a PDOP lower than 4 and a distance measurement scattering lower than 5m, were kept as valid. Data were recorded in the UTM system of coordinates, with WGS84 datum and spheroid. The corresponding figures are given in the Tableau 2. Tableau 2 : Measurement plots centre coordinates parcel # Lon (X) Lat (Y) parcel # Lon (X) Lat (Y) Lon (X) Lat (Y) 301N 565232 292255 311S 563662 290711 Transept 301S 565226 292072 312N 562882 290980 center 564147 291029 302N 564451 292212 312S 562879 290750 extr N 564167 291513 302S 564454 292032 313N 565226 290342 extr E 564641 291018 303N 563640 292203 313S 565219 290124 extr S 564139 290516 303S no gps no gps 314N 564453 290343 extr W 563645 291018 304C 562977 292042 314S 564434 290092 305N 565232 291614 315N 563662 290357 305S 565234 291404 315S no gps no gps 306N 564434 291583 316. no gps no gps 306S 564448 291367 317N 565218 289666 307. no gps no gps 317S 565230 289438 308N 562876 291578 318N 564435 289677 308S 562881 291379 318S 564442 289461 309N 565220 290997 319N 563650 289661 309S 565222 290771 319Nb 563574 289807 310N 564436 290984 319S 563654 289425 310S 564437 290769 320N 562859 289656 311N 563646 291020 320S 562862 289433 9

H] Annex measurements H.1 Positions Several other positions have been measured the same way, all through the VALERI square. Each GPS acquisition was made in the middle of the cross tracks at parcel corners. 14 of them are included inside the SPOT image extraction for the VALERI test square, the 16 others being at the edge of the square. Corresponding locations in the SPOT images are given Figure 13, and values in Tableau 3. All these 30 positions have been given to SpotImage for the Level 2B SPOTView product performance. V21 V20 V19 Figure 13 : Location of annex positions measurements for geometric corrections and georeferencing of the SPOT image product. Only inside-square points are shown here. The 16 others are located at the edge of the square. V22 V28 V29 V23 V27 V17 V26 V16 V24 V25 V15 Tableau 3 : Annex points coordinates Point # lon lat Point # lon lat V1 565591 292371 V16 564851 290216 V2 564790 292366 V17 564836 290549 V3 564227 292447 V18 565594 290566 V4 563270 292360 V19 564846 291843 V5 562484 292461 V20 564058 291840 V6 562506 291485 V21 563261 291824 V7 562509 291173 V22 563263 291182 V8 562486 290541 V23 563257 290536 V9 562498 289878 V24 563264 289885 V10 562446 289220 V25 564052 289875 V11 563255 289229 V26 564052 290220 V12 564052 289227 V27 564052 290532 V13 564831 289222 V28 564061 291185 V14 565608 289216 V29 564835 291191 V15 564832 289881 V30 565615 292122 H.2 Photos A general view of the surroundings of each measurement plots was performed, except for the plots in parcels number 310N, 311N and 311S. 10

Figure 14 : example of two types of oil palms canopy organisation. H.3 Architectural data Several palm architectural parameters measurements were performed on various trees in a few parcels. Such parameters are for instance trunk height, trunk diameter, palm insertion height, maximum palm height, palm length and width, leaflets numbers and dimension... Figures are given in attached file named AL_field_form.xls, showing the compiled enquiry forms. Forms 1 to 50 concerns parcels 314N and 314S, forms 51 to 53 parcel 313N, forms 54 to 56 parcel 312N, forms 57 to 59 parcel 309S. Figure 15 : architectural parameters measurements on oil palms (palm length) H.4 Planted material Information on vegetal material in this estate area is available. Indeed, the date of plantation (Figure 16) is given for each parcel. All the palms of a given parcel have the same age. Each couple of half-parcels is planted with the same vegetal material, except some very small scattered areas. Hybrid origin is indicated for each parcel as the breeding code on the Figure 16. No information is given for the four first top parcels. Some repetitions are found across the square. 11

Figure 16 : Map of palm plantation year and hybrid code in the different parcels of VALERI square. Socfin^2 IY2509 + IY0504 IY250 + SS3313 SS3613 IL5005 IL5005 IL5005 IL5005 IL4905 IL4905 IL4905 IL4906 IL4911 IL4905 IL4911 IL4905 I] Files description Data files are sorted in different folders: Main: - ALreport.pdf: this file, general report on the Aek Loba VALERI campaign, 2001 - AL_gps.xls: Excel file giving all GPS measurements, as well as LAI derived with C2000 software, for each sampling plot. - AL_field_form.xls: RAWdata: above and below measurement files directly downloaded from the LAImeter, names of files correspond to dates of downloading. SORTEDdata: rawa: above data sorted by parcel number or transept branch intercaliba: above data multiplied by intercalibration coefficient, sorted by parcel number or transept branch B: below data sorted by parcel number or transept branch Intercalib: files of clear-cut simultaneous measurements for intercalibration of the two LAImeters, plus Excel file of coefficients derivation out of linear interpolation COMPUTEDdata: final files corresponding to Above and Below files merged together, after intercalibration of the two instruments. LAI values are derived with the C2000 Licor software. SPOTimage: SPOT image extractions:.bil corresponds to image data in Binary Inter Leave format, and.hdr to ENVI header file(including georeference data)..flt is a standard floating point values file. 12

- AL_VAL_sq : VALERI test square (151x151 pixels) - AL_VAL_sq_NDVI : Normalised difference vegetation index of the VALERI test square - AL_VAL_pix1 : 100km 2 Low Resolution pixel, centred (501x501 pixels) - AL_VAL_pix2 : 100km 2 Low Resolution pixel, shifted (501x501 pixels) - Kj266345 : full SPOT scene Miscell_spot_jpg: Miscellaneous jpg files corresponding to SPOT view shown in that report. Hemiview: Hemispherical numerical photos of each measurement plot, sorted by parcel number. GeneralView: Numerical photo of the surrounding area of each measurement plot, sorted by parcel number. WorkViews: Some photos of the field workers during the campaign! Including photos of the adventitious vegetation types (blue and green ferns, bamboo-grass). J] LAI and NDVI: a short glance Pixel radiometric values have been extracted for each measurement plots in the SPOT image, to derive the Normalised Difference Vegetation Index (NDVI). LAI values computed with the Licor C2000 software is then compared to NDVI for each of these points, as shown in the graph Figure 17. This raw extraction does not provides with an obvious tendency as it could be waited for. Plot locations certainly have to be better fitted to estimate the exact position of the pixel, in order to get the appropriate figures correlating satellite and ground data. LAI 5 4,5 4 Figure 17 : Relationship between LAI computed out of field measurements, and NDVI derived from the SPOT image, for each plot of the Aek Loba Valeri Square. 3,5 3 2,5 0,55 0,57 0,59 0,61 0,63 0,65 NDVI 13

Tracks delimitating the parcels in Aek Loba oil palms Estate 14