José Carlos Neves Epiphanio

Variations in reflectance of tropical soils : Spectral-chemical composition relationships from AVIRIS data

Abstract The relationships between Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) surface reflectance values and constituents (total iron, organic matter, TiO2, Al2O3, and SiO2) of samples representative of three important soil types from central Brazil [Terra Roxa Estruturada (STE), Latossolo Vermelho-Escuro (SLE), and Areia Quartzosa (SAQ)] were analyzed. End member spectra for green vegetation (GV), nonphotosynthetic vegetation (NPV), water (W), and the three soil types were selected by inspecting scatter plots derived from the principal components analysis (PCA) of 140 AVIRIS bands. They were then used to compose a six end member unmixing model to characterize the spectral reflectance variations associated with the different scene components, the spatial distribution of the soil types, and the effects of spectral mixing on the spectral-chemical composition relationships. Finally, regression equations fitted to soil constituents and their highly correlated spectral bands were used to produce maps showing the chemical variability in the scene for areas dominated by the presence of exposed soils, as indicated by the results from the unmixing model. The results showed a very good agreement between the spatial variability of the soil types and of the soil constituents. The largest squared correlation results were obtained for Fe2O3, TiO2, and Al2O3, but the relationships were affected in the transition from the red to the near-infrared interval by the presence of nonsoil residues (e.g., senescent vegetation or litter) over the soil surfaces. In comparison with the light and loamy sand SAQ, the dark-red clay STE and SLE presented higher contents of Fe2O3, Al2O3, and TiO2, and consequently lower overall reflectance in the scene, because of the presence of greater amounts of opaque minerals. The prediction of these constituents from remote sensing data and their close association with the spatial distribution of the different soil types demonstrate the importance of the present investigation for soil mapping and soil erosion studies. All Rights Reserved.

Bi-directional reflectance factor of 14 soil classes from Brazil

Abstract The spectral reflectance of soils is required for effective use of remote sensing products. The absence of studies concerned with spectral reflectance of the soils from the tropical region in the 400 to 2500 nm spectral range is the main motivation of this research. The objective of this study was to present spectral reflectance data from different tropical soil types. This spectral characterization was done through measurements of the bi-directional reflectance factor of 111 selected soil samples, grouped in 14 tropical soil classes, taken from 53 sites (Sao Paulo State, Brazil). The measurements were made with a spectroradiometer operating in the 400 to 2500 nm region of the electromagnetic spectrum. Each soil sample is associated to a set of physical and chemical analyses data, with part of these published in descriptive reports of soil surveys.

Directional effects on NDVI and LAI retrievals from MODIS: A case study in Brazil with soybean

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) is largely used to estimate Leaf Area Index (LAI) using radiative transfer modeling (the “main” algorithm). When this algorithm fails for a pixel, which frequently occurs over Brazilian soybean areas, an empirical model (the “backup” algorithm) based on the relationship between the Normalized Difference Vegetation Index (NDVI) and LAI is utilized. The objective of this study is to evaluate directional effects on NDVI and subsequent LAI estimates using global (biome 3) and local empirical models, as a function of the soybean development in two growing seasons (2004–2005 and 2005–2006). The local model was derived from the pixels that had LAI values retrieved from the main algorithm. In order to keep the reproductive stage for a given cultivar as a constant factor while varying the viewing geometry, pairs of MODIS images acquired in close dates from opposite directions (backscattering and forward scattering) were selected. Linear regression relationships between the NDVI values calculated from these two directions were evaluated for different view angles (0–25°; 25–45°; 45–60°) and development stages ( 90 days after planting). Impacts on LAI retrievals were analyzed. Results showed higher reflectance values in backscattering direction due to the predominance of sunlit soybean canopy components towards the sensor and higher NDVI values in forward scattering direction due to stronger shadow effects in the red waveband. NDVI differences between the two directions were statistically significant for view angles larger than 25°. The main algorithm for LAI estimation failed in the two growing seasons with gradual crop development. As a result, up to 94% of the pixels had LAI values calculated from the backup algorithm at the peak of canopy closure. Most of the pixels selected to compose the 8-day MODIS LAI product came from the forward scattering view because it displayed larger LAI values than the backscattering. Directional effects on the subsequent LAI retrievals were stronger at the peak of the soybean development (NDVI values between 0.70 and 0.85). When the global empirical model was used, LAI differences up to 3.2 for consecutive days and opposite viewing directions were observed. Such differences were reduced to values up to 1.5 with the local model. Because of the predominance of LAI retrievals from the MODIS backup algorithm during the Brazilian soybean development, care is necessary if one considers using these data in agronomic growing/yield models.

Influência da matéria orgânica e de formas de ferro na reflectância de solos tropicais

ABSTRACT INFLUENCE OF ORGANIC MATTER AND IRON OXIDES ON THE SPECTRALREFLECTANCE OF TROPICAL SOILS The influence of organic matter and amorphous and crystalline iron contents on the reflectance(400 to 2500 nm) of various soils was evaluated. Studied soils were Typic Argiudoll (TR), Typic Eutrorthox(LR), Typic Argiudoll (PE), Typic Haplortox (LE), Typic Quartzipsamment (AQ), and Typic Paleudalf (PV).Surface and subsurface soil samples were used in four conditions: a) as sampled; b) after removal oforganic matter; c) after removal of the organic matter and the amorphous iron; and d) after removingorganic matter and amorphous iron and crystalline iron. Reflectance factor was acquired from 400 nmto 2.450 nm and TM/Landsat spectral bands were simulated. Removal of organic and amorphous ironcaused an overall increase of the reflectance along the spectrum, for all soils. Removal of crystallineiron caused the reflectance to increase in the first portion of the spectrum (400 to 1.000 nm), but not inintermediate (1.000 to 1.900 nm) and final portion of the spectrum (after 1.900 nm). Crystalline iron wasresponsible for concavities in the spectral region near 400 nm and 850 nm. Use of laboratoryspectroradiometry proved to be a fast, non-destructive, and easy-to-prepare technique for analyzingabsorption features caused by organic matter and iron forms in soils.

Sun and view angle effects on NDVI determination of land cover types in the Brazilian Amazon region with hyperspectral data

Solar zenith and view angle effects on the normalized difference vegetation index (NDVI) of land cover types in the Brazilian Amazon region were analysed. Airborne Hyperspectral Mapper (HYMAP) data were collected in 126 narrow bands (450–2500 nm) with a field of view (FOV) of ±30° from nadir. Data collection was performed initially in two flight lines with solar zenith angles of 29° and 53°. In a third flight line, view angles were up to +60° from nadir by airplane banking. Surface reflectance spectra representative of major land cover types were selected, and principal component analysis was applied to indicate their spectral similarity relationships in response to solar zenith angle variations. Reflectance and NDVI differences between pairs of land cover types were plotted for a variable band positioning. Atmospheric and coupled directional effects were analysed for variations in apparent and surface reflectance values, in the depth of the major water vapour absorption bands, and in the NDVI values, as a function of view angle. The results showed that major Amazon land cover types had increased NDVI values with increase in solar zenith angle, especially exposed soil or other vegetated surface components under soil background influence. Small solar zenith angles improved the NDVI contrast between green vegetation and soil and also the land cover discrimination in all bands, except for those placed in the 750–1100 nm range. At large solar zenith angles, this spectral interval was useful to separate primary forest/old woody vegetation regrowth from most of the other surface components due to enhancement in the shade fraction associated with the arboreal covers. Small differences in NDVI values of tropical rainforest were observed between ±25° from nadir. These differences became stronger with the increase in view angle from +25° to +60° in response to the additive and subtractive contributions of atmospheric scattering and absorption, respectively, and of coupled directional effects.

Window Regression: A Spatial-Temporal Analysis to Estimate Pixels Classified as Low-Quality in MODIS NDVI Time Series

MODerate resolution Imaging Spectroradiometer (MODIS) data are largely used in multitemporal analysis of various Earth-related phenomena, such as vegetation phenology, land use/land cover change, deforestation monitoring, and time series analysis. In general, the MODIS products used to undertake multitemporal analysis are composite mosaics of the best pixels over a certain period of time. However, it is common to find bad pixels in the composition that affect the time series analysis. We present a filtering methodology that considers the pixel position (location in space) and time (position in the temporal data series) to define a new value for the bad pixel. This methodology, called Window Regression (WR), estimates the value of the point of interest, based on the regression analysis of the data selected by a spatial-temporal window. The spatial window is represented by eight pixels neighboring the pixel under evaluation, and the temporal window selects a set of dates close to the date of interest (either earlier or later). Intensities of noises were simulated over time and space, using the MOD13Q1 product. The method presented and other techniques (4253H twice, Mean Value Iteration (MVI) and Savitzky–Golay) were evaluated using the Mean Absolute Percentage Error (MAPE) and Akaike Information Criteria (AIC). The tests revealed the consistently superior performance of the Window Regression approach to estimate new Normalized Difference Vegetation Index (NDVI) values irrespective of the intensity of the noise simulated.

Influence of data acquisition geometry on soybean spectral response simulated by the prosail model

View angle and directional effects significantly affect reflectance and vegetation indices, especially when daily images collected by large field-of-view (FOV) sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) are used. In this study, the PROSAIL radiative transfer model was chosen to evaluate the impact of the geometry of data acquisition on soybean reflectance and two vegetation indices (Normalized Difference Vegetation Index - NDVI and Enhanced Vegetation Index -EVI) by varying biochemical and biophysical parameters of the crop. Input values for PROSAIL simulation were based on the literature and were adjusted by the comparison between simulated and real satellite soybean spectra acquired by the MODIS/Terra and hyperspectral Hyperion/Earth Observing-One (EO-1). Results showed that the influence of the view angle and view direction on reflectance was stronger with decreasing leaf area index (LAI) and chlorophyll concentration. Because of the greater dependence on the near-infrared reflectance, the EVI was much more sensitive to viewing geometry than NDVI presenting larger values in the backscattering direction. The contrary was observed for NDVI in the forward scattering direction. In relation to the LAI, NDVI was much more isotropic for closed soybean canopies than for incomplete canopies and a contrary behavior was verified for EVI.

Analysis of agricultural intensification in a basin with remote sensing data

The last few decades have been marked by important changes in the Brazilian agriculture, especially with respect to crop-management practices. This study aimed to analyze the dynamics of cropping systems in a typical agricultural river basin in the state of Mato Grosso. Landsat satellite images and time series of Moderate Resolution Imaging Spectroradiometer vegetation index profiles were analyzed from 2000 to 2010. First, we assessed the horizontal expansion that occurred in the agricultural areas. Subsequently, using the product MOD13Q1, some metrics were established to identify the vertical intensification of soil use (single- or double-cropping systems). Results showed stagnation in the expansion of new deforested areas for agriculture in the 2003/2004 growing season, with simultaneous vertical intensification of agriculture. The adoption of the double-cropping system (e.g., soybean/corn and soybean/cotton) expanded by 266% during the studied period and reached 56% of the croplands in the 2009/2010 growing season.

Retroespalhamento de uma cena agrícola em imagem de radar

Orbital remote sensing in the microwave electromagnetic region has been presented as an important tool for agriculture monitoring. The satellite systems in operation have almost all-weather capability and high spatial resolution, which are features appropriated for agriculture. However, for full exploration of these data, an understanding of the relationships between the characteristics of each system and agricultural targets is necessary. This paper describes the behavior of backscattering coefficient (s°) derived from calibrated data of Radarsat images from an agricultural area. It is shown that in a dispersion diagram of s° there are three main regions in which most of the fields can be classified. The first one is characterized by low backscattering values, with pastures and bare soils; the second one has intermediate backscattering coefficients and comprises well grown crops mainly; and a third one, with high backscattering coefficients, in which there are fields with strong structures causing a kind of double bounce effect. The results of this research indicate that the use of Radarsat images is optimized when a multitemporal analysis is done making the best use of the agricultural calendar and of the dynamics of different cultures.

Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.