Tropical forest biomass and successional age class relationships to a vegetation index derived from landsat TM data

Sader, Steven A.; Waide, Robert B.; Lawrence, William T.; Joyce, A. T.

doi:10.1016/0034-4257(89)90112-0

Cited by 216 publications

(109 citation statements)

References 9 publications

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“…In this study, we used texture filters based on co-occurrence measures by the window size of 11 × 11 pixels with horizontal and vertical offset of one. These metrics have been widely used to predict stand forest structure and biomass from remote sensing data [8,59,63].…”

Section: Landsat Processingmentioning

confidence: 99%

Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran)

Attarchi

Gloaguen

2014

Remote Sensing

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Abstract:The objective of this study is to develop models based on both optical and L-band Synthetic Aperture Radar (SAR) data for above ground dry biomass (hereafter AGB) estimation in mountain forests. We chose the site of the Loveh forest, a part of the Hyrcanian forest for which previous attempts to estimate AGB have proven difficult. Uncorrected ETM+ data allow a relatively poor AGB estimation, because topography can hinder AGB estimation in mountain terrain. Therefore, we focused on the use of atmospherically and topographically corrected multispectral Landsat ETM+ and Advanced Land-Observing Satellite/Phased Array L-band Synthetic Aperture Radar (ALOS/PALSAR) to estimate forest AGB. We then evaluated 11 different multiple linear regression models using different combinations of corrected spectral and PolSAR bands and their derived features. The use of corrected ETM+ spectral bands and GLCM textures improves AGB estimation significantly (adjusted R 2 = 0.59; RMSE = 31.5 Mg/ha). Adding SAR backscattering coefficients as well as PolSAR features and textures increase substantially the accuracy of AGB estimation (adjusted R 2 = 0.76; RMSE = 25.04 Mg/ha). Our results confirm that topographically and atmospherically corrected data are indispensable for the estimation of mountain forest's physical properties. We also demonstrate that only the joint use of PolSAR and multispectral data allows a good estimation of AGB in those regions. OPEN ACCESSRemote Sens. 2014, 6 3694

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Section: Landsat Processingmentioning

confidence: 99%

Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran)

Attarchi

Gloaguen

2014

Remote Sensing

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“…Since older and taller regrowth is usually of higher biomass, then infrared canopy re ectance should also be related to stand biomass. While one study has reported a poor relationship between near-infrared re ectance and stand biomass for a series of Puerto Rican regrowth (Sader et al 1989), there are no comparisons of regrowth biomass with respect to middle-infrared re ectance. The research reported in this paper is a test of the potential for estimation of tropical secondary forest above-ground biomass with Landsat TM images using data from a series of stands near Manaus, Brazil and Santa Cruz de la Sierra, Bolivia.…”

Section: Introductionmentioning

confidence: 99%

Satellite estimation of tropical secondary forest above-ground biomass: Data from Brazil and Bolivia

Steininger¹

2000

International Journal of Remote Sensing

356

206

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Abstract. This paper reports on a test of the ability to estimate above-ground biomass of tropical secondary forest from canopy spectral re ectance using satellite optical data. Landsat Thematic Mapper data were acquired concurrent with eld surveys conducted in secondary forest fallows near Manaus, Brazil and Santa Cruz de la Sierra, Bolivia. Measurements of age and above-ground live biomass were made in 34 regrowth stands. Satellite data were converted to surface re ectances and compared with regrowth stand age, biomass and structural variables.Among the Brazilian stands, signi cant relationships were observed between middle-infrared re ectance and stand age, height, volume and biomass. The canopy re ectance-biomass relationship saturated at around 15.0 kg mÕ 2, or over 15 years of age (r> 0.80, p< 0.01). In the Bolivian study area, no signi cant relationship between canopy spectral re ectance and biomass was observed. These contrasting results are probably caused by a low Sun angle during the satellite measurements from Bolivia. However, regrowth structural and general compositional di erences between the two study areas could explain the lack of a signi cant relationship in Bolivia. The results demonstrate a current potential for biomass estimation of secondary forests with satellite optical data in some, but not all, tropical regions. A discussion of the potential for regional extrapolationof spectral relationships and future satellite imagery is included.

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“…(or similar measure of foliar mass) with an accuracy adequate for deriving a predictive relationship (Curran and Williamson, 1985). Despite the logistical problems involved, several groups have managed to produce such relationships (e.g., Jensen and Hodgson, 1985;Running et al, 1986;Badhwar et al, 1986aBadhwar et al, , 1986bDanson, 1987;Spanner et al, 1990;Running et al, 1989;Sader et al, 1989;Herwitz et al, in press;Spanner et al, in review). For instance, Peterson et al (1987) reported a correlation coefficient between LA!…”

Section: Introductionmentioning

confidence: 99%

Seasonal LAI in slash pine estimated with landsat TM

Curran

Dungan

Gholz

1992

Remote Sensing of Environment

141

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SUMMARYThe leaf area index (LAI, total area of leaves per unit area of ground) of most forest canopies varies throughout the year, yet for logistical reasons it is difficult to estimate anything more detailed than a seasonal maximum LAI. To determine if remotely sensed data can be used to estimate LA! seasonally, field measurements of LAI were compared to normalized difference vegetation index (NDVI) values, derived using Landsat Thematic Mapper (TM) data, for 16 fertilized and control slash pine plots on three dates.Linear relationships existed between NDVI and LAI with R 2 values of 0.35, 0.75, and 0.86 for February 1988, September 1988, and March 1989. This is the first reported study in which NDVI is related to forest LAI recorded during the month of sensor overpass.Predictive relationships based on data from eight of the plots were used to estimate the LAI of the other eight plots with a root-mean-square error of 0.74 LAI, which is 15.6% of the mean LAI. This demonstrates the potential use of Landsat TM data for studying seasonal dynamics in forest canopies.

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Tropical forest biomass and successional age class relationships to a vegetation index derived from landsat TM data

Cited by 216 publications

References 9 publications

Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran)

Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran)

Satellite estimation of tropical secondary forest above-ground biomass: Data from Brazil and Bolivia

Seasonal LAI in slash pine estimated with landsat TM

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