Engineering Papers⌕ Search

Engineering topics

Filho, P. H.

Publications and source records attributed to Filho, P. H..

Use of LANDSAT images to study cerrado vegetation

Channel 5 and 7 LANDSAT imagery at the scale of 1:250,000 made during passes in the dry and rainy seasons were used to select the optimal season for cerrado characterization in Mato Grosso do Sul State. The study area is located around the cities of Campo Grande and Tres Lagoas, a region being used for reforestation and rangeland activities. Imagery acquired during the dry season permitted a good discrimination between "cerrado" (woodsy pasture) vegetation and reforestation. In relation to the altered areas, only the recently modified area presented good discrimination of cerrado vegetation. Imagery of the rainy season did not provide a reasonable separation between cerrado and reforestation areas but the altered area could be easily discriminated.

Parada, N. D. J.↗

Evaluation of reforestation using remote sensing techniques

The utilization of remotely sensed orbital data for forestry inventory. The study area (approximately 491,100 ha) encompasses the municipalities of Ribeirao Preto, Altinopolis, Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Sant Rita do Passa Quatro and Santa Rosa do Viterbo (Sao Paulo State). Materials used were LANDSAT data from channels 5 and 7 (scale 1:250,000) and CCT's. Visual interpretation of the imagery showed that for 1977 a total of 37,766.00 ha and for 1979 38,003.75 ha were reforested with Pinus and Eucalyptus within the area under study. The results obtained show that LANDSAT data can be used efficiently in forestry inventory studies.

Parada, N. D. J.↗

Relation of the activities of the IPDF/INPE project (reforestation subproject) during the year 1979

The state of Mato Grosso do Sul was selected as the study area to define the recognizable classes of Eucalyptus spp. and Pinus spp. by visual and automatic analyses. For visual analysis, a preliminary interpretation key and a legend of 6 groups were derived. Based on these six groups, three final classes were defined for analysis: (1) area prepared for reforestation; (2) area reforested with Eucalyptus spp.; and (3) area reforested with Pinus spp. For automatic interpretation the area along the highway from Ribas do Rio Pardo to Agua Clara was classified into the following classes: eucalytus, bare soil, plowed soil, pine and "cerrado". The results of visual analysis show that 67% of the reforested farms have relative differences in area estimate below 5%, 22%, between 5% and 10%; and 11% between 10% and 20%. The reforested eucalyptus area is 17 times greater than the area of reforested pine. Automatic classification of eucalyptus ranged from 73.03% to 92.30% in the training areas.

Dejesusparada, N.↗

Estimating reforestation by means of remote sensing

LANDSAT imagery at the scale of 1:250.000 and obtained from bands 5 and 7 as well as computer compatible tapes were used to evaluate the effectiveness of remotely sensed orbital data in inventorying forests in a 462,100 area of Brazil emcompassing the cities of Ribeirao, Altinopolis Cravinhos, Serra Azul, Luis Antonio, Sao Simao, Santa Rita do Passa Quatro, and Santa Rosa do Viterbo. Visual interpretation of LANDSAT imagery shows that 37,766 hectares (1977) and 38,003.75 hectares (1979) were reforested areas of pine and eucalyptus species. An increment of 237.5 hectares was found during this two-year time lapse.

Dejesusparada, N.↗

Monitoring of reforested areas using LANDSAT data

Imagery obtained with channels 5 and 7 was visually interpreted in an effort to determine the spatial, spectral, and temporal characteristics of a 105,000 hectare area of Fazenda Mutum which was reforested with various species of pine and eucalyptus. It was possible to map a reforested area as small as 6 hectare in its initial implantation using contrast with the surrounding targets. Five classes were mapped: nondeforested areas, partially deforested areas, deforested areas, partially reforested areas, and fully reforested areas. In 1979, 12,000 hectare were deforested, 4,330.83 hectare were partially reforested, and 42,744.71 hectare were reforested.

Dejesusparada, N.↗

Remote sensing in forestry: Application to the Amazon region

The utilization of satellite remote sensing in forestry is reviewed with emphasis on studies performed for the Brazilian Amazon Region. Timber identification, deforestation, and pasture degradation after deforestation are discussed.

Dejesusparada, N.↗

Evaluation of reforested areas using LANDSAT imagery

The author has identified the following significant results. Visual and automatic interpretation of LANDSAT imagery was used to classify the general Pinus and Eucalyptus according to their age and species. A methodology was derived, based on training areas, to define the legend and spectral characteristics of the analyzed classes. Imager analysis of the training areas show that Pinus taeda is separable from the other Pinus species based on JM distance measurement. No difference of JM measurements was observed among Eucalyptus species. Two classes of Eucalyptus were separated according to their ages: those under and those over two years of age. Channel 6 and 7 were suitable for the discrimination of the reforested classes. Channel 5 was efficient to separated reforested areas from nonforested targets in the region. The automatic analysis shows the highest classification precision was obtained for Eucalyptus over two years of age (95.12 percent).

Dejesusparada, N.↗