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

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

Automatic classification of reforested Pinus SPP and Eucalyptus SPP in Mogi-Guacu, SP, Brazil, using LANDSAT data

The author has identified the following significant results. Single date LANDSAT CCTs were processed, by Image-100 to classify Pinus and Eucalyptus species and their age groups. The study area Mogi-Guagu was located in the humid subtropical climate zone of Sao Paulo. The study was divided into ten preliminary classes and featured selection algorithms were used to calculate Bhattacharyya distance between all possible pairs of these classes in the four available channels. Classes having B-distance values less than 1.30 were grouped in four classes: (1) class PE - P. elliottii, (2) class P0 - Pinus species other than P. elliotii, (3) class EY - Eucalyptus spp. under two years, and (4) class E0 - Eucalyptus spp. more than two years old. The percentages of correct classification ranged from 70.9% to 94.12%. Comparisons of acreage estimated from the Image-100 with ground truth data showed agreement. The Image-100 percent recognition values for the above four classes were 91.62%, 87.80%, 89.89%, and 103.30%, respectively

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)

Estimation of the sugar cane cultivated area from LANDSAT images using the two phase sampling method

A two phase sampling method and the optimal sampling segment dimensions for the estimation of sugar cane cultivated area were developed. This technique employs visual interpretations of LANDSAT images and panchromatic aerial photographs considered as the ground truth. The estimates, as a mean value of 100 simulated samples, represent 99.3% of the true value with a CV of approximately 1%; the relative efficiency of the two phase design was 157% when compared with a one phase aerial photographs sample

Impacts of Agricultural Expansion on Surface Runoff: A Case Study of a River Basin in the Brazilian Legal Amazon

This work presents an analysis of the Land Use and Land Cover (LULC) changes of a region in the Brazilian Legal Amazon, and an evaluation of their impacts on the surface runoff regime. This case study took place at the Suiá-Miçu River basin, located in the northeast region of Mato Grosso State. LULC maps were produced for the years 1973, 1984 and 2005 using remote sensing data. After analyzing the agricultural expansion in the study area, the Automated Geospatial Watershed Assessment Tool (AGWA) was applied in performing the surface runoff modeling for each of the analyzed years using the SCS curve number method. The results showed that by 1984, 13% of the natural vegetation had been replaced by pasture in this drainage basin. These changes were responsible for a 5.7% increase in the annual average surface runoff volume when compared with the baseline values of 1973. In 2005, the agricultural areas increased to around 40% of the drainage basin, being 28% occupied by pasture and 12% by crop fields. In this last scenario, the annual average surface runoff was 37% higher than in 1973

Propagation data at 20/40 GHz and the propagation needs of Milstar

There are a number of propagation issues that need further investigation for efficient system planning for EHF communication systems. Especially needed are better cloud and rain characterizations. A method for estimating one of the rain induced effects of interest, outage duration, is presented

Thin-ribbon tapered coupler for dielectric waveguides

A recent discovery shows that a high-dielectric constant, low-loss, solid material can be made into a ribbon-like waveguide structure to yield an attenuation constant of less than 0.02 dB/m for single-mode guidance of millimeter/submillimeter waves. One of the crucial components that must be invented in order to guarantee the low-loss utilization of this dielectric-waveguide guiding system is the excitation coupler. The traditional tapered-to-a-point coupler for a dielectric rod waveguide fails when the dielectric constant of the dielectric waveguide is large. This article presents a new way to design a low-loss coupler for a high- or low-dielectric constant dielectric waveguide for millimeter or submillimeter waves

Landscape-scale variation in forest structure and biomass along an elevation gradient in the Atlantic Forest of the Serra do Mar, Brazil.

Landscape-scale quantification of forest structure, disturbance patterns and biomass distribution can improve our understanding of the environmental controls on the functioning of forested ecosystems. Assessing the detailed structure of the complex tropical forest canopy is a challenging task, especially in areas of steep topography where field access is limited. We used airborne lidar (light detection and ranging) data to describe the landscape-scale variation in canopy structure and gap distribution in a 1000-ha area along an elevation gradient from 0 to 1200m in the Atlantic Forest of the Serra do Mar in southeast Brazil. Mean canopy heights (MCHs) were greatest (21-22m) at intermediate elevations (200-700m) in the submontane forest where terrain slope was also the steepest (~40º). Canopy gap fraction was highest (~30%) and MCH lowest (~16m) in the montane forest areas (900-1100m) on flatter sites atop the plateau (~24º slopes). We used forest inventory data from nine 1-ha permanent field plots (PFPs) within the study area to assess aboveground biomass (AGB) stocks and changes. We established regression models based on lidar-derived canopy structure and field-based biometry data, and used these to extrapolate AGB predictions across the landscape. Comparing canopy height and disturbance distributions in the PFPs with the distributions across the broader landscape, we found that submontane PFPs showed closer correspondence with their surrounding areas, while montane PFPs consistently overestimated landscape-scale canopy height (thus AGB pools) and underestimated gap fraction (therefore AGB changes)