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Abstract: Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received considerable attention over the past 15 years for analyzing and interpreting remote sensing imagery. In contrast to traditional image analysis, GEOBIA works more like the human eye–brain combination does. The latter uses the object''s color (spectral information), size, texture, shape and occurrence to other image objects to interpret and analyze what we see. GEOBIA starts by segmenting the image grouping together pixels into objects and next uses a wide range of object properties to classify the objects or to extract object''s properties from the image. Significant advances and improvements in image analysis and interpretation are made thanks to GEOBIA. In June 2010 the third conference on GEOBIA took place at the Ghent University after successful previous meetings in Calgary (2008) and Salzburg (2006). This special issue presents a selection of the 2010 conference papers that are worked out as full research papers for JAG. The papers cover GEOBIA applications as well as innovative methods and techniques. The topics range from vegetation mapping, forest parameter estimation, tree crown identification, urban mapping, land cover change, feature selection methods and the effects of image compression on segmentation. From the original 94 conference papers, 26 full research manuscripts were submitted; nine papers were selected and are presented in this special issue. Selection was done on the basis of quality and topic of the studies. The next GEOBIA conference will take place in Rio de Janeiro from 7 to 9 May 2012 where we hope to welcome even more scientists working in the field of GEOBIA. [Copyright &y& Elsevier]

Abstract: The Amazonian state of Mato Grosso is the main production area for soybeans in Brazil and contains 31.3% of the national production as of 2009. The rapid evolution of the agricultural systems in this area shows that the region is experiencing a rapid agricultural transition. In this paper, we broke down this transition process into three steps: crop expansion, agricultural intensification and ecological intensification. We used remote sensing products to develop and compute satellite-derived indices describing the main agricultural dynamics during the cropping years from 2000–2001 to 2006–2007. Our results indicated that Mato Grosso is continuing to expand its agricultural sector, with a 43% increase in the net cropped area during the study period. Although this expansion mainly occurred in the cerrado ecoregion until the early 2000s, the forest ecoregion is experiencing expansion at this time. We observed that 65% of the crop expansion in Mato Grosso from 2000 to 2006 occurred in this ecoregion. However, we did not identify this crop expansion as the major driver of deforestation in Mato Grosso because only 12.6% of the cleared areas were directly converted into croplands. Agricultural intensification also evolved rapidly, as the proportion of the net cropped area cultivated with double cropping systems harvesting two successive commercial crops (i.e., soybean and corn or soybean and cotton) increased from 6% to 30% during the study period. Finally, we found that ecological intensification occurred because the region’s farmers planted a non-commercial crop (i.e., millet or sorghum) after the soybean harvest to prevent soil erosion, improve soil quality, break pest cycles, maintain soil moisture and set the conditions for high-quality no-tillage operations. In 2006–2007, 62% of the net cropped area was permanently covered by crops during the entire rainy season. This practice allowed the farmers to diversify their production, as shown by the positive evolution of the Area Diversity Index. Future scholars can use the method proposed in this paper to improve their understanding of the forces driving the agricultural dynamics in Mato Grosso. [Copyright &y& Elsevier]

Abstract: The intensification of irrigated agriculture in the semi-arid region of Brazilian North-east results in a change of natural vegetation by irrigated fruit crops. New applications of remote sensing technologies are presented in this paper to estimate the impact of this land use change on regional water consumption – and ultimately the water balance – in Low-Middle São Francisco River basin. Ten Landsat images for a period from 2001 to 2007 were used, together with the locally calibrated Surface Energy Balance Algorithm for Land (SEBAL) and agro-meteorological data to derive information on regional actual evapotranspiration (ET), biomass production (BIO), and crop water productivity (CWP). The Landsat-based results revealed that regional mean ET for irrigated crops was 3.6mmd−1 being higher than for natural vegetation (1.4mmd−1). Similar incremental ET values between natural and irrigated ecosystems were found from micro-meteorological field experiments. The consequence of this land use change on São Francisco River''s downstream stream flow was assessed by estimating volumetric incremental evapotranspiration at the regional scale. The bio-physical crop water productivity per unit of actual evapotranspiration (CWPET) varied between 0.4 and 1.7l of wine per m3 of water for wine grapes; 1.7 and 4.0kg of fruits per m3 of water for table grapes; and 2.2 and 5.0kg of fruits per m3 of water for mangos. The accompanying paper (Part A) describes the calibration and validation of SEBAL steps witnessed under the actual field conditions in this study area. [Copyright &y& Elsevier]

This paper provides a new technique for evaluating lineaments that focuses on the spatial link between surface and subsurface elements in a single layer. We chose a test area in northeast Brazil's Borborema Province. We extracted magnetic and relief lineaments from aeromagnetic and SRTM data. We defined the lineaments that agree on both layers using GIS operations. To identify the concordance between lineaments, we constructed kernel density maps that combined the data from each layer. We detected NE-SW solid conditioning of the structures. Even when evaluating only the concordant lineaments in other directions, they are expressed in groupings in NE-SW, as with NW-SE features, that associates with transfer failures and are contained by large NE-SW structures. The Atlantic Ocean's opening and expansion phases were linked to the E-W direction, also truncated by NE-SW lower density sections. The N–S trend was inexpressive. Areas with a higher density of concordant lineaments were associated with regions more susceptible to the Neotectonics of landform inversion, forming domes and arches-oriented NE-SW, as in Serra do Mel, Macau High, and Ponta Grossa High. Lower lineament density areas indicated visual correspondence with the most significant number of production wells in the Potiguar Basin, indicating that these regions are more favorable for the accumulation and trapping of hydrocarbons. • Lineaments from various sources may be combined to form a single data layer. • Deep NE-SW structures influence the relief disposal in the Potiguar Basin. • Zones limit geological sectors with a lower density of concordant lineaments. • Higher density of concordant lineaments zones are more prone to Neotectonic uplift. • The lower density of concordant lineaments correlates with oil exploration wells. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of seven methods of retrieving the planetary boundary layer height (PBLH) from lidar measurements carried out in the Metropolitan Region of São Paulo (MRSP) during two MCITY - BRAZIL field campaigns of 2013. The performance is objectively assessed considering as reference the PBLH retrieved from rawinsonde carried out every 3 h during these campaigns. The role of clouds and aerosol load in the performance of the seven methods is analysed considering three case study scenarios representative of typical atmospheric conditions in the MRSP : (a) winter clean atmosphere, (b) summer low clouds and aerosol multilayers, (c) summer sea-breeze intrusion. Corroborating the case study results, the objective analysis indicated that most of the lidar methods retrieved PBLH closer to the top of the entrainment zone than the mixed layer, contradicting their definition. During daytime, the Wavelet Covariance Transform Method performs better than all the other six methods. The Inflexion Point Method performed better to estimate the Residual Layer height during night-time. In average, the diurnal evolution of the PBLH and its local rate of change based on lidar and rawinsonde measurements are in agreement. • Most analysed lidar methods estimate the Entrainment Zone height. • Sea-breeze can reduce the aerosol concentration in the Residual Layer. • The Wavelet Covariance Transform has the best result among the analysed methods. • Lidar methods require an adaptation to the local climate conditions. [ABSTRACT FROM AUTHOR]

The structural framework and tectonic evolution of the sedimentary basins along the eastern margin of the South American continent are closely associated with the tectonic framework and crustal heterogeneities inherited from the Precambrian basement. However, the role of NW-SE and NNW-SSE structures observed at the outcropping basement in Southeastern Brazil and its impact over the development of those basins have not been closely investigated. In the continental region adjacent to the Campos Basin, we described a geological feature with NNW-SSE orientation, named in this paper as the Alegre Fracture Zone (AFZ), which is observed in the onshore basement and can be projected to the offshore basin. The main goal of this work was to study this structural lineament and its influence on the tectonic evolution of the central portion of the Campos Basin and adjacent mainland. The onshore area was investigated through remote sensing data joint with field observations, and the offshore area was studied through the interpretation of 2-D seismic data calibrated by geophysical well logs. We concluded that the AFZ occurs in both onshore and offshore as a brittle deformation zone formed by multiple sets of fractures that originated in the Cambrian and were reactivated mainly as normal faults during the rift phase and in the Cenozoic. In the Campos Basin, the AFZ delimitates the western side of the Corvina-Parati Low, composing a complex fault system with the NE-SW faults and the NW-SE transfer faults. [ABSTRACT FROM AUTHOR]

The Shuttle Radar Topography Mission (SRTM) provided an unprecedented source of space-borne topographic information that has shown to be of particular interest for studies in densely vegetated tropical areas, such as Central Amazonia. The digital elevation models produced in that region show subtle details of the terrain that usually appear blurred in conventional remote sensing images. Interpretation of an SRTM-derived drainage network and geomorphometric features revealed several drainage anomalies, which are possibly the surface expression of buried morphostructural features. Integration with geological and geophysical ancillary data strongly suggested that interpreted features constitute potential structural sites for hydrocarbon exploration. However, due to their inferred nature, the structures herein identified are not by themselves a justification for drilling. However, they do provide information for planning seismic surveys, thus reducing costs of the exploration campaigns, as well as minimizing potential environmental impacts of such an enterprise in areas of tropical rain forests. Despite the relatively small size of the study area, it is expected that procedures presented in this paper can be successfully applied throughout the approximately 1,000,000 km 2 of sedimentary basins in the Brazilian Amazonian region. [ABSTRACT FROM AUTHOR]

Expansion of agricultural lands have shaped Brazilian Cerrado landscapes in recent decades; however, the environmental consequences of these transformations are still poorly assessed. This paper presents a multidisciplinary approach used to assess historical land-use and land-cover (LULC) changes and their impacts on the environment in southeast Mato Grosso State, a region where the Cerrado has been intensively converted into agricultural lands. The methodology encompassed three main stages: (1) quantifying LULC changes using remote sensing data, (2) assessing LULC change impacts on vulnerable lands (e.g. erosion prone areas and wetlands), and (3) summarizing preceding information into key environmental indicators, assessed within the Pressure-State-Response framework (PSR) of the Organization for Economic Co-operation and Development (OECD). The results indicated a drastic landscape transformation in the selected area, which evolved from predominantly vegetated to a consolidated agricultural region. Crops expanded at high rates from 1985 to 1995, occupying the majority of the lands suited for agriculture. In the following decade, crops continued to expand and encroached into fragile environments (e.g. wetlands and more erodible soils). As a result, from 1985 to 2005, the area lost approximately 42% of its natural vegetation and erosion risks increased significantly. Our integration of land-use change information with intrinsic environmental vulnerabilities allowed a deeper understanding of LULC changes consequences and provided environmental indicators. This offered a synoptic view of how LULC changes occurred and how they affected the environment at a landscape scale. Furthermore, the assessment of the indicators using the PSR framework, helped to clarify cause–effect relationships thus furnishing key information of value to decision-makers and future comparisons with other areas. [ABSTRACT FROM AUTHOR]

The creation of a satellite rapid alert programme (DETER-A) in 2004 was a cornerstone of the Brazilian government's strategy to reduce deforestation. This programme allowed authorities to detect and respond rapidly to periods of deforestation. Due to the fact that the policy instrument was based on multispectral remote radar, weather-related obstacles posed a continuous impediment to the study of deforestation. This paper investigates to what extent cloud cover has reduced the effectiveness of the DETER-A program to detect deforestation. To test this hypothesis, survival model analysis is undertaken on satellite data derived measures of local deforestation. The emphasis is on the state of Maranhão, which is separated into two areas by an arbitrary line of demarcation (Legal Amazon delimitation) where the forest on one side is covered by the satellite monitoring program while the other is not. The results suggest that following the implementation of the satellite monitoring program, there was more deforestation in those years with more cloud persistence in the area covered by the program. Counterfactual simulations indicate that the absence of clouds would have prevented deforestation equivalent to almost 7% of the study region, which is equivalent to 73 million tonnes of CO 2 with a value of US$ 366 million. If the current monitoring system was replaced with the experimental policy instrument DETER-C/DETER INTENSO, cloud cover would be less of an impediment to deforestation detection. • Maranhao in Brazil is divided by an artificial line that separates it in two parts with two different deforestation monitoring policies. • Hence, it provides an ideal setting in which to study the impact of cloud cover on deforestation rates. • When a satellite monitoring programme is in operation, more deforestation occurs during years with greater cloud cover. • Highlights Improved satellite monitoring technologies may have a substantial effect on deforestation rates. [ABSTRACT FROM AUTHOR]

Abstract: Traditional Shuttle Radar Topography Mission (SRTM) topographic datasets hold limited value in the geomorphic analysis of low-relief terrains. To address this shortcoming, this paper presents a series of techniques designed to enhance digital elevation models (DEMs) of environments dominated by low-amplitude landforms, such as a fluvial megafan system. These techniques were validated through the study of a wide depositional tract composed of several megafans located within the Brazilian Pantanal. The Taquari megafan is the most remarkable of these features, covering an area of approximately 49,000km2. To enhance the SRTM-DEM, the megafan global topography was calculated and found to be accurately represented by a second order polynomial. Simple subtraction of the global topography from altitude produced a new DEM product, which greatly enhanced low amplitude landforms within the Taquari megafan. A field campaign and optical satellite images were used to ground-truth features on the enhanced DEM, which consisted of both depositional (constructional) and erosional features. The results demonstrate that depositional lobes are the dominant landforms on the megafan. A model linking baselevel change, avulsion, clastic sedimentation, and erosion is proposed to explain the microtopographic features on the Taquari megafan surface. The study confirms the potential promise of enhanced DEMs for geomorphological research in alluvial settings. [Copyright &y& Elsevier]

Abstract: Understanding actor-specific responsibility for deforestation in the Brazilian Amazon is key in adjusting policy and resource allocation in the face of current forest destruction. However, previous research shows that there is great variability in such assessments. To contribute to the ongoing discussions on forest conservation and rural development policies in the Amazon, this paper studies actor-specific deforestation and its environmental effects in four municipalities situated along the Transamazon Highway. We used spatially explicit methods that integrate a database of 8281 georeferenced properties with a time series of remote-sensing data covering four periods between 1986 and 2007. We also included landscape ecology metrics as improved indicators of the complex environmental effects of forest fragmentation. The analysis demonstrates that smallholders (defined as colonists who own less than 100ha of land) were responsible for 23% of total deforestation in the study region while accounting for 55% of the total properties. We also explored the relationship between property size and deforestation at the property level, finding that it closely follows a power distribution. Property deforestation increased with property size, while the percentage of property deforestation decreased. In spite of this, compliance with current legal requirements to maintain 50% of property forest cover was not statistically different between smallholders and largeholders. In comparison to municipalities dominated by medium- and large-scale ranchers, the smallholder-dominated municipality of Medicilândia showed better performance in all applied landscape metrics with well-established relationships with the provision of important environmental goods and services. Although all studied municipalities showed severe accumulated deforestation, Medicilândia experienced an abrupt decrease in municipal deforestation after 1999 to just 0.03%year−1, while municipalities dominated by larger holders maintained or increased their previous deforestation rates to between 0.90% and 1.34%year−1 in the same period. This indicates that the smallholders’ productions schemes in our study area might present potential for agricultural frontier stabilization based on improved land-use efficiency. The policy implications of our findings are discussed, especially with regard to the role of smallholders in productive forest conservation. [Copyright &y& Elsevier]

Summary: This paper proposes a fast and inexpensive method for estimating the bathymetry of hydroelectric reservoirs. Brazil has more than 30 large hydroelectric reservoirs with a combined volume exceeding one billion cubic meters. The hydroelectric sector is responsible for 97% of the energy production in Brazil and is the largest hydroelectric park in the world. Among the variables affecting the environmental impacts of reservoirs, depth plays a major role because it influences the aquatic system hydrodynamics. Reservoir depth distribution (i.e., the bathymetry) is also a fundamental factor controlling the physical–chemical and biological properties of the system. However, the acquisition of bathymetric information for the large reservoirs in Brazil is not a simple task because: (1) most of the topographic maps available in the area of the lake have a very small scale (1:100,000 and smaller), (2) larger charts are the property of the hydropower companies and are classified, and (3) the size of the reservoirs prevent the use of bathymetric surveys. The proposed method of integrating historical and Shuttle Radar Topography Mission (SRTM) topographic data allowed for the estimation of the bathymetry of the Itumbiara reservoir with R 2 =0.98 (n =100, ρ =0.00) and RMSE=3.78m. For researchers who need a rapid and simple method to develop bathymetric maps of hydroelectric reservoirs, the proposed method can provide a simple and fast alternative to more data intensive methods. [Copyright &y& Elsevier]

Abstract: Recent articles are indicating that polarimetric data provide significantly more information than conventional or multi-polarized images, particularly due to the additional phase information. The objective of this paper is to evaluate the multi-polarized and fully polarimetric L-band airborne SAR-R99B data, in terms of their capability to distinguish among different agricultural crops in the western part of Bahia State, Brazil. Emphasis was given to coffee, cotton and pasture crops which were at well developed growing stages. Discrimination among crops was carried out using graphical analysis of mean backscatter values. Crop classification was performed for single and multiple polarizations, and fully polarimetric images with a classifier that uses the contextual Iterated Conditional Modes–ICM algorithm. The investigation confirmed the potential of L-band multi-polarized and polarimetric airborne SAR-R99B data to distinguish and classify agricultural crops in the tropical condition of the test-site. In addition, it clearly indicated the gradual and considerable improvement that was achieved going from single to three polarizations and from multi-polarized to fully polarimetric images. [Copyright &y& Elsevier]

Summary: Rainfall measurements by conventional raingauges provide relatively accurate estimates at a few points of a region. The actual rainfield can be approximated by interpolating the available raingauge data to the remaining of the area of interest. In places with relatively low gauge density such interpolated rainfields will be very rough estimates of the actual events. This is especially true for tropical regions where most rainfall has a convective origin with high spatial variability at the daily level. Estimates of rainfall by remote sensing can be very useful in regions such as the Amazon basin, where raingauge density is very low and rainfall highly variable. This paper evaluates the rainfall estimates of the Tropical Rainfall Measuring Mission (TRMM) satellite over the Tapajós river basin, a major tributary of the Amazon. Three-hour TRMM rainfall estimates were aggregated to daily values and were compared with catch of ground-level precipitation gauges on a daily basis after interpolating both data to a regular grid. Both daily TRMM and raingauge-interpolated rainfields were then used as input to a large-scale hydrological model for the whole basin; the calculated hydrographs were then compared to observations at several streamgauges along the river Tapajos and its main tributaries. Results of the rainfield comparisons showed that satellite estimates can be a practical tool for identifying damaged or aberrant raingauges at a basin-wide scale. Results of the hydrological modeling showed that TRMM-based calculated hydrographs are comparable with those obtained using raingauge data. [Copyright &y& Elsevier]

The spatial and spectral variability of urban environments present fundamental challenges to deriving accurate remote sensing products for urban areas. Multiple endmember spectral mixture analysis (MESMA) is a technique that potentially addresses both challenges. MESMA models spectra as the linear sum of spectrally pure endmembers that vary on a per-pixel basis. Spatial variability is addressed by mapping sub-pixel components of land cover as a combination of endmembers. Spectral variability is addressed by allowing the number and type of endmembers to vary from pixel to pixel. This paper presents an application of MESMA to map the physical components of urban land cover for the city of Manaus, Brazil, using Landsat Enhanced Thematic Mapper (ETM+) imagery. We present a methodology to build a regionally specific spectral library of urban materials based on generalized categories of urban land-cover components: vegetation, impervious surfaces, soil, and water. Using this library, we applied MESMA to generate a total of 1137 two-, three-, and four-endmember models for each pixel; the model with the lowest root-mean-squared (RMS) error and lowest complexity was selected on a per-pixel basis. Almost 97% of the pixels within the image were modeled within the 2. 5% RMS error constraint. The modeled fractions were used to generate continuous maps of the per-pixel abundance of each generalized land-cover component. We provide an example to demonstrate that land-cover components have the potential to characterize trajectories of physical landscape change as urban neighborhoods develop through time. Accuracy of land-cover fractions was assessed using high-resolution, geocoded images mosaicked from digital aerial videography. Modeled vegetation and impervious fractions corresponded well with the reference fractions. Modeled soil fractions did not correspond as closely with the reference fractions, in part due to limitations of the reference data. This work demonstrates the potential of moderate-resolution, multispectral imagery to map and monitor the evolution of the physical urban environment. [Copyright &y& Elsevier]

This paper presents a case study on the use of features derived from remote sensing data for mapping the highly fragmented semideciduous Atlantic forest in Brazil. Innovative aspects of this research include the evaluation of different feature sets in order to improve land cover mapping. The feature sets were defined based on expert knowledge and on data mining techniques to be input to traditional and machine learning algorithms for pattern recognition, viz. maximum likelihood, univariate decision trees, multivariate decision trees, and neural networks. The results showed that the maximum likelihood classification using temporal texture descriptors as extracted with wavelet transforms was most accurate to classify the semideciduous Atlantic forest. In this study, a special accuracy measure was used: the so-called class mapping accuracy. Maximum likelihood performed relatively well, with forest mapping accuracies ranging from 34.5 to 51.3%. In contrast, accuracies for neural networks ranged from 19.0 to 45.2%. Classification confusion occurred mainly with coffee and eucalyptus plantations. Univariate trees provided the most robust results for different feature sets, with accuracies ranging from 39.6 to 46.7%. Temporal information of vegetation indices was more important than image texture, terrain topography and raw spectral information for discriminating semideciduous Atlantic forest. [Copyright &y& Elsevier]

• Evaporation trends of tropical reservoirs in Brazil were investigated. • Both positive and negative trends in evaporation were observed. • In the industrial region, the negative trend was potentially caused by the impact of pollutant released to the atmosphere. • In the coastal region, the positive trend was related to increasing air temperature. This paper aims to analyze the trends (Mann-Kendall test) of evaporation and climatological variables, including air temperature, relative humidity and wind speed in four reservoirs located in the Brazilian Northeast. The evaporation was estimated through remote sensing using the Surface Energy Balance System for Water (AquaSEBS) model from 1985 to 2018. In addition, it was verified which meteorological parameter has the highest correlation (R2) with the evaporation in order to assess why this process is changing throughout the years in each reservoir. The model performed well, with root mean square error (RMSE) ≤ 1.25 mm/day, percent bias (PBIAS) ≤ 13.70% and coefficient of determination (R2) ≥ 0.51. One reservoir located closer to a coastal zone presented a positive trend (+0.24 mm/34 years), corroborating the measurements of a reference class A pan, and Penman-Monteith equation, while the others, located closer to industrial areas, displayed negative trends (−0.26 to −0.080 mm/34 years). This reduced evaporation was attributed to the impact of industrial pollutant release to the atmosphere, while the increasing effect in the other reservoir was due to its proximity to the coast, which implies an air renewal as the sea breeze contributes for an improvement in the air quality. The meteorological data also presented positive and negative correlations: Temperature exhibited a positive trend (+0.57 °C/34 years), whereas humidity (−4.83%) and wind speed (−0.29 m/s), a negative trend. Evaporation displayed moderate coefficient of determination (R2 > 0.31) with wind speed and humidity. Yet, the reduction of evaporation may be associated with a possible counterbalancing effect of wind speed over humidity. Overall, the results contribute to a better understanding of evaporation trends in a water-scarce region and can be used in a water resources management context as the increasing/reduction of evaporation might significantly impact water availability in this area. [ABSTRACT FROM AUTHOR]

• Study of two iron ore deposits in Brazil using reflectance spectroscopy and Sentinel-2 image processing. • Samples of hematitite, itabirites, quartzites, cangas and breccias were collected for petrographic, geochemical and reflectance spectroscopy analysis. • The classifications of the spectra performed on the studied targets (Caetité and Piatã) allowed to differentiate types of spectra associated with hematite and goethite. Reflectance Spectroscopy showed great potential for the mapping of iron rich domains. • Using Sentinel-2 image processing is a good tool for searching large areas over a high temporal and spatial range. The large iron ore reserves of Brazil are already known, but there are still few studies regarding mineral prospection in smaller deposits and/or areas with lower contents. Exploration techniques that cover large areas at low costs, such as remote sensing, are important for setting targets for mineral exploration. This paper proposes to use of Sentinel-2 images and reflectance spectroscopy to evaluate the use of these techniques for iron prospecting, using two deposits in the state of Bahia, Brazil, as case studies. To validate image processing results, samples were collected in these areas for analysis of optical petrography, x-ray fluorescence and reflectance spectroscopy. Images were processed at a spatial resolution of 20 and 60 m with Mixture Tuned Matched Filtering and Spectral Angle Mapper. Corresponding spectral types were determined based on the analyses of mineralogy variation and composition of the spectral mixture. It was also possible to establish a correlation of spectral types with iron content. The results achieved showed that Sentinel-2 data can be used for spectral mapping of different lithotypes composed of iron oxides, with Reflectance Spectroscopy as an important tool for mapping, and that the use of images in spatial resolution 20 m are sufficient to discriminate different types of ore. Image processing has shown that Sentinel-2 sensor data can support iron ore mineral research and the discovery of new mineralized areas. [ABSTRACT FROM AUTHOR]