Tropical forest typo mapping and monitoring using remote sensing

Roy, P. S.; Ranganath, B. K.; Diwakar, P. G.; Vohra, T. P. S.; Bhan, S. K.; Singh, Inderjit; Pandian, V. C.

doi:10.1080/01431169108955253

Cited by 80 publications

(20 citation statements)

References 6 publications

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“…Palubinskas et al ( 1995 ) found that texture-based classi® cation and post-classi® cation of fuzzy classi® cation output yielded high accuracy in mapping regenerating tropical forest classes of a region in Amazonas, Brazil using TM data. In some studies in the tropics, high classi® cation accuracies were achieved even in detailed and semi-detailed mapping ( i.e., species of forest type levels) of vegetation and other land cover types (e.g., Roy et al 1991, Saxena et al 1992.…”

Section: W Hat Detail Of Land Cover Informationmentioning

confidence: 99%

Land cover mapping for tropical forest rehabilitation planning using remotely-sensed data

Apan¹

1997

International Journal of Remote Sensing

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Lack of reliable and up-to-date maps relating to land cover (among other themes) constitute a weakness in land resource surveys and cause costly failures to many forest rehabilitation projects in the tropics. This study evaluated the utility of satellite imagery for land cover mapping for forest rehabilitation planning in a case study in Mindoro, Philippines. Using Landsat TM data, visual and digital image processing techniques were performed using the GRID module of ARC/INFO and the microBRIAN image processing software. Crown cover density is found as the most useful and the most important detail of information the image could provide. Detailed mapping at the species and forest type levels is unreliable, as is the delineation of water bodies and some cultural features in rugged terrain. Clustering of the NDVI image is found more applicable in producing land cover maps depicting crown cover classes than classifying raw TM-3, -4, and -5.

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Section: W Hat Detail Of Land Cover Informationmentioning

confidence: 99%

Land cover mapping for tropical forest rehabilitation planning using remotely-sensed data

Apan¹

1997

International Journal of Remote Sensing

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“…Most local studies of deforestation report accuracy levels of over 95% (Roy et al 1991, Sader et al 1991, Steininger 1996, and several global deforestation monitoring programs have been implemented during the past decade Chomentowski 1992, Lambin 1994). Progress has also been made in estimating the area of secondary forests with high resolution optical data.…”

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

360

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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“…The remoteness and inaccessibility to these islands restricted the researchers to carry out studies in the past. However, the advent of geospatial tools facilitated the scientific community to focus on various research aspects in these islands (Roy et al 1991;Porwal et al 1992;Prasad et al 2007Prasad et al , 2009Prasad et al , 2010.…”

Section: Study Areamentioning

confidence: 99%

Tsunami and tropical island ecosystems: a meta-analysis of studies in Andaman and Nicobar Islands

et al. 2011

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Tropical islands are special and sensitive ecosystems which are subjected to various disturbances imposed by human activities and natural disasters. A detailed study about the changing landscape scenarios of these fragile island systems induced by various driving factors could be used for setting up measurements in support of conservation and sustainable development projects. The current research is a meta-analysis of the studies carried out in Andaman and Nicobar islands which analyzed the impact of tsunami of 2004 using geospatial tools. Based on the analysis, it was observed that the Nicobar islands were more affected compared to the Andaman islands. The majority of the researchers used preand post-tsunami satellite imagery and adopted visual interpretation method to delineate the changed classes. The study infers uplift of land in Andaman (exposing) and subsidence in Nicobar islands (inundation) with severe damage to the coastal elements like mangroves, coral reefs, plantations and in few cases interior forest. The analysis showed there were no records of the damage for some small islands. Finally, it is concluded that utility of microwave satellite data for change analysis will prove better in regions like Andaman and Nicobar where it is difficult to get cloud free optical data because of the high monsoon periods in these islands. It is also suggested that future work utilizing suitable temporal satellite imagery should focus on the extent of recovery of vegetation and other coastal elements which suffer the impact of disaster.

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Tropical forest typo mapping and monitoring using remote sensing

Cited by 80 publications

References 6 publications

Land cover mapping for tropical forest rehabilitation planning using remotely-sensed data

Land cover mapping for tropical forest rehabilitation planning using remotely-sensed data

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

Tsunami and tropical island ecosystems: a meta-analysis of studies in Andaman and Nicobar Islands

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