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We analyzed the occurrences of fire foci between years 2001 and 2015 in Mato Grosso state, Brazil. For this, we used remote sensing data and we correlated fire with surface temperature, rainfall, wind speed, air temperature, relative humidity, and vegetation index. The data were analyzed within the state according to use and cover classes. We also spatialize the fire occurrence using Kernel density and analyze trends with the Mann–Kendall test. The year 2015 was the year with the highest average annual air temperature and lowest annual cumulative rainfall, and wet season with the lowest relative humidity and highest surface temperature. Therefore, it was the year with less difference in the number of fire foci between wet (40.53%) and dry (59.47%) seasons. The period 2002–2005 and the years 2007 and 2010 had the highest fire foci, representing about 66.5% of the total from 2001 to 2015. In these years, 80 to 83% of fire foci occurred in the dry season. The classes with the highest density of fire were Mining Area, Urban Area, Temporary Crops, and Pasture. The fire foci in Urbanized Area, Temporary Crops, Pasture and Forestry classes tended to decrease throughout the 15 years evaluated. Fire foci were negatively correlated with rainfall, relative humidity and soil water and positively correlated with wind and surface temperature. This demonstrates that public policies related to combating fires in Brazil must be intensified especially in years with prediction of extreme drought. [ABSTRACT FROM AUTHOR]

This article aims is to apply a methodology to identify Trip Generating Territories (TGT) in order to discuss the relationship between transport and land use. To achieve this goal, indirect methods were applied through digital processing of orbital remote sensing images along with spatial analysis, using the Kernel Density Estimation (KDE) method. The image processing results have revealed an overall accuracy of 71% for differentiation and characterization of intra-urban classes use through the adopted typologies. In this way, through data on land use and occupation, it was possible to map out the density of the trip generating territories associated to the main built surfaces and that can indicate a higher potential of trip attraction in the urban area. Additionally, the relationship between land use and public transport system was observed in the city of Petrolina-Brazil, the empirical area of study, and the highest concentration of TGT was observed to be located in the central portion of the city, on its surroundings and on the margins of some arterial roads. Thus, it is possible to extract, in the preliminary analysis, information to support the city's transport and mobility planning. [ABSTRACT FROM AUTHOR]

Although global climate change is receiving considerable attention, the loss of biodiversity worldwide continues. In this study, dynamics of land use/land cover (LULC) change in the Paraguai/Jauquara Basin, Mato Grosso, Brazil, were investigated. Two analyses were performed using R software. The first was a comparative study of LULC among the LULC classes at the polygon scale, and the second was a spatio-temporal analysis of moving polygons restricted to the agricultural regions in terms of topology, size, distance, and direction of change. The data consisted of Landsat images captured in 1993, 1997, 2001, 2005, 2009, 2013, and 2016 and processed using ArcGIS software. The proposed analytical approach handled complex data structures and allowed for a deeper understanding of LULC change over time. The results showed that there was a statistically significant change from regions of natural vegetation to pastures, agricultural regions, and land for other uses, accompanied by a significant trend of expansion of agricultural regions, appearing to stabilize from 2005. Furthermore, different patterns of LULC change were found according to soil type and elevation. In particular, the purple latosol soil type presented the highest expansion indexes since 2001, and the elevated agricultural areas have been expanding and/or stabilizing since 1997. [ABSTRACT FROM AUTHOR]

In the last 30 years, the growth of the agriculture and livestock industries in the Cerrado biome has caused severe changes in land use and land cover (LULC), and areas previously occupied by native vegetation are changing to agricultural monocultures (e.g., soybean or corn) and/or pastures. Thus, the objective of this study was to analyze the LULC changes for the years 1986, 1999, 2007, and 2016 based on Landsat time series and object-based image analysis (OBIA) for the Prata River Basin. Twelve LULC classes were mapped: riparian forest, cerrado, swampy grasslands, wetlands, semideciduous forest, pasture, agriculture, fallow agricultural land, barren land, eucalyptus, water bodies, and burnt area. The classifications presented results with an overall accuracy of more than 93% and a kappa coefficient of 0.92. In 2007, the pasture class had the highest increase in area (48.5%), with a total area of 118.32 km2 of Cerrado biome vegetation converted to pasture, and the classes banhado, riparian forest, swampy grasslands, and cerrado had the greatest reductions in area (41.58%, 29.67%, 25.44%, and 21.63%, respectively). More precisely, the wetlands class underwent the greatest decrease under the advancement of pasture in the studied period (− 36.2%). These changes are due to factors favorable to agropastoral practices, such as a flat relief and soil with good agricultural suitability. [ABSTRACT FROM AUTHOR]

The Brazilian Cerrado area is in rapid decline because of the expansion of modern agriculture. In this study, we used extensive field data and a 30-year chronosequence of Landsat images (1980-2010) to assess the effects of time since conversion of Cerrado into agriculture upon soil chemical attributes and soybean/corn yield in the Alto do Rio Verde watershed. We determined the rates of vegetation conversion into agriculture, the agricultural land use time since conversion, and the temporal changes in topsoil (0-20 cm soil depth) and subsurface (20-40 cm) chemical attributes of the soils. In addition, we investigated possible associations between fertilization/over-fertilization and land use history detected from the satellites. The results showed that 61.8% of the native vegetation in the Alto do Rio Verde watershed was already converted into agriculture with 31% of soils being used in agriculture for more than 30 years. While other fertilizers in cultivated soils (e.g., Ca, Mg, and P) have been compensated over time by soil management practices to keep crop yield high, large reductions in C (38%) and N (29%) were observed in old cultivated areas. Furthermore, soybean and cornfields having more than 10 years of farming presented higher values of P and Mg than the ideal levels necessary for plant development. Therefore, increased risks of over-fertilization of the soils and environmental contamination with these macronutrients were associated with soybean and cornfields having more than 10 years of farming, especially those with more than 30 years of agricultural land use. [ABSTRACT FROM AUTHOR]

This article demonstrates the importance of examining level-dependent deforestation trajectories that may be undetected within regional analyses. We examine Amazon-wide, sub-regional, settlement, and farm-level deforestation trajectories in the Brazilian Amazon and suggest factors that underlie level-dependent differences in spatial patterns and temporal magnitudes of deforestation from 1970 to 2001. At a sub-regional level, we find significant variation in frequency, magnitude, and intensity of deforestation associated with context-specific processes, including areas that have stopped deforesting, are rapidly reforesting, while at the same time increasing economic value of forest-based production. We use remote-sensing data from 1970 to 2001. For Amazon-wide and state-level analyses, we use data available from Brazil's National Institute for Space Research. For sub-regional, settlement, and farm-lot levels, time-series Landsat images and aerial photographs and detailed field-based research are used to reconstruct the history of deforestation. Our analysis empirically demonstrates that understanding deforestation trajectories requires differentiating underlying causes at different levels of analysis and to be wary of overarching explanations and solutions that ignore differences in scale. [ABSTRACT FROM AUTHOR]

Background: Brazilian Amazon forests contain a large stock of carbon that could be released into the atmosphere as a result of land use and cover change. To quantify the carbon stocks, Brazil has forest inventory plots from different sources, but they are unstandardized and not always available to the scientific community. Considering the Brazilian Amazon extension, the use of remote sensing, combined with forest inventory plots, is one of the best options to estimate forest aboveground biomass (AGB). Nevertheless, the combination of limited forest inventory data and different remote sensing products has resulted in significant differences in the spatial distribution of AGB estimates. This study evaluates the spatial coverage of AGB data (forest inventory plots, AGB maps and remote sensing products) in undisturbed forests in the Brazilian Amazon. Additionally, we analyze the interconnection between these data and AGB stakeholders producing the information. Specifically, we provide the first benchmark of the existing field plots in terms of their size, frequency, and spatial distribution. Results: We synthesized the coverage of forest inventory plots, AGB maps and airborne light detection and ranging (LiDAR) transects of the Brazilian Amazon. Although several extensive forest inventories have been implemented, these AGB data cover a small fraction of this region (e.g., central Amazon remains largely uncovered). Although the use of new technology such as airborne LiDAR cover a significant extension of AGB surveys, these data and forest plots represent only 1% of the entire forest area of the Brazilian Amazon. Conclusions: Considering that several institutions involved in forest inventories of the Brazilian Amazon have different goals, protocols, and time frames for forest surveys, forest inventory data of the Brazilian Amazon remain unstandardized. Research funding agencies have a very important role in establishing a clear sharing policy to make data free and open as well as in harmonizing the collection procedure. Nevertheless, the use of old and new forest inventory plots combined with airborne LiDAR data and satellite images will likely reduce the uncertainty of the AGB distribution of the Brazilian Amazon. [ABSTRACT FROM AUTHOR]