a b s t r a c tMODIS 250-m NDVI and EVI datasets are now regularly used to classify regional-scale agricultural land-use practices in many different regions of the globe, especially in the state of Mato Grosso, Brazil, where rapid land-use change due to agricultural development has attracted considerable interest from researchers and policy makers. Variation exists in which MODIS datasets are used, how they are processed for analysis, and what ground reference data are used. Moreover, various land-use/land-cover classes are ultimately resolved, and as yet, crop-specific classifications (e.g. soy-corn vs. soy-cotton double crop) have not been reported in the literature, favoring instead generalized classes such as single vs. double crop. The objective of this study is to present a rigorous multiyear evaluation of the applicability of time-series MODIS 250-m VI data for crop classification in Mato Grosso, Brazil. This study shows progress toward more refined crop-specific classification, but some grouping of crop classes remains necessary. It employs a farm field polygon-based ground reference dataset that is unprecedented in spatial and temporal coverage for the state, consisting of 2003 annual field site samples representing 415 unique field sites and five crop years (2005)(2006)(2007)(2008)(2009)). This allows for creation of a dataset containing "best-case" or "pure" pixels, which we used to test class separability in a multiyear cross validation framework applied to boosted decision tree classifiers trained on MODIS data subjected to different pre-processing treatments. Reflecting the agricultural landscape of Mato Grosso as a whole, cropping practices represented in the ground reference dataset largely involved soybeans, and soy-based classes (primarily double crop 'soy-commercial' and single crop 'soy-cover') dominated the analysis along with cotton and pasture. With respect to the MODIS data treatments, the best results were obtained using date-ofacquisition interpolation of the 16-day composite VI time series and outlier point screening, for which five-year out-of-sample accuracies were consistently near or above 80% and Kappa values were above 0.60. It is evident that while much additional research is required to fully and reliably differentiate more specific crop classes, particular groupings of cropping strategies are separable and useful for a number of applications, including studies of agricultural intensification and extensification in this region of the world.

Abstract. Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass. Previous work has shown that the inclusion of height in biomass allometries, compared to the sole use of diameter, significantly improves biomass estimation accuracy. Here, we evaluate the effect of height measurement error on biomass estimation and we evaluate the accuracy of recently published diameter-height allometries at four areas within the Brazilian Amazon. As no destructive sample of biomass was available at these sites, reference biomass values were based on allometries. We found that the precision of individual tree height measurements ranged from 3 to 20 % of total height. This imprecision resulted in a 5-6 % uncertainty in biomass when scaled to 1 ha transects. Individual height measurement may be replaced with existing regional and global height allometries. However, we recommend caution when applying these relations. At Tapajos National Forest in the Brazilian state of Pará, using the pantropical and regional allometric relations for height resulted in site biomass 21 % and 25 % less than reference values. At the other three study sites, the pantropical equation resulted in errors of less that 2 %, and the regional allometry produced errors of less than 12 %. As an alternative to measuring all tree heights or to using regional and pantropical relations, we recommend measuring height for a well-distributed sample of about 100 trees per site. Following this methodology, 95 % confidence intervals of transect biomass were constrained to within 4.5 % on average when compared to reference values.

No abstract

The rapid population growth has driven the demand for more food, fiber, energy, and water, which is associated to an increase in the need to use natural resources in a more sustainable way. The use of precision agriculture machinery and equipment since the 1990s has provided important productive gains and maximized the use of agricultural inputs. The growing connectivity in the rural environment, in addition to its greater integration with data from sensor systems, remote sensors, equipment, and smartphones have paved the way for new concepts from the so-called Agriculture 4.0 or Digital Agriculture. This article presents the results of a survey carried out with 504 Brazilian farmers about the digital technologies in use, as well as current and future applications, perceived benefits, and challenges. The questionnaire was prepared, organized, and made available to the public through the online platform LimeSurvey and was available from 17 April to 2 June 2020. The primary data obtained for each question previously defined were consolidated and analyzed statistically. The results indicate that 84% of the interviewed farmers use at least one digital technology in their production system that differs according to technological complexity level. The main perceived benefit refers to the perception of increased productivity and the main challenges are the acquisition costs of machines, equipment, software, and connectivity. It is also noteworthy that 95% of farmers would like to learn more about new technologies to strengthen the agricultural development in their properties.

RESUMOEste trabalho discute os efeitos das mudanças do uso do solo na biogequímica dos rios da bacia de drenagem do rio Ji-Paraná (Rondônia). Nesta região, a distribuição espacial do desmatamento e das propriedades do solo resultam em sinais diferentes, possibilitando a divisão dos sistemas fluviais em três grupos: rios com águas pobres em íons e baixo impacto; rios com conteúdo iônico intermediário e impacto médio e rios com elevados conteúdo iônico e impacto antropogênico. As características biogeoquímicas dos rios têm relação significativa com a área de pasto, melhor parâmetro para prever a condutividade elétrica (r 2 = 0,87) e as concentrações de sódio (r 2 = 0,75), cloreto (r 2 = 0,69), potássio (r 2 = 0,63), fosfato (r 2 = 0.78), nitrogênio inorgânico (r 2 = 0.52), carbono inorgânico (r 2 = 0.81) e carbono orgânico (rain 2 = 0.51) dissolvidos. Cálcio e magnésio tiveram sua variância explicada pelas características do solo e pastagem. Nossos resultados indicam que as mudanças observadas na micro-escala constituem "sinais biogeoquímicos" gerados pelo processamento do material nas margens dos rios. A medida em que os rios evoluem para ordens superiores, os sinais persistentes nos canais fluviais estão mais associdados às características da bacia de drenagem (solos e uso da terra). Apesar dos efeitos das mudanças observadas no uso do solo não serem ainda detectáveis na macro-escala (bacia amazônica), a disrupção da estrutura e funcionamento dos ecossistemas é detectável nas micro e meso escalas, com alterações significativas na ciclagem de nutrientes nos ecossistemas fluviais. PALAVRAS-CHAVEAmazônia, rios e igarapés, biogeoquímica, mudanças no uso da terra.Effects of land use changes in the biogeochemistry of fluvial systems of the Ji-Paraná river basin, Rondônia. ABSTRACT In this article we present the results of the effects of land use change on the river biogeochemistry of the Ji-Paraná basin (Rondônia). In this region, the spatial distribution of deforestation and soil properties result in different biogeochemical signals, allowing the division of the fluvial systems into three groups: rivers with low ionic concentration and low impact; rivers with intermediate ionic content and medium impact; and rivers with high ionic content and anthropogenic impact. River biogeochemical characteristics present KEY WORDSAmazonia, Rivers and streams, biogeochemistry, land-use change

The objective of this work was to analyze land use dynamics in the Brazilian Cerrado region from 2002 to 2013. This analysis was based on the interpretation of Landsat satellite images carried out by the projects Projeto de Conservação e Utilização Sustentável da Diversidade Biológica Brasileira (Probio) and TerraClass Cerrado 2013, both coordinated by Ministério do Meio Ambiente. In 2002, 38.9% of the Cerrado was covered by some type of anthropic activity. In 2013, this percentage increased to 43.4%. One of the main highlights is the emergence of a new agricultural frontier in the northern region of the study area, known as Matopiba.

-The objective of this work was to evaluate a simple, semi-automated methodology for mapping cropland areas in the state of Mato Grosso, Brazil. A Fourier transform was applied over a time series of vegetation index products from the moderate resolution imaging spectroradiometer (Modis) sensor. This procedure allows for the evaluation of the amplitude of the periodic changes in vegetation response through time and the identification of areas with strong seasonal variation related to crop production. Annual cropland masks from 2006 to 2009 were generated and municipal cropland areas were estimated through remote sensing. We observed good agreement with official statistics on planted area, especially for municipalities with more than 10% of cropland cover (R 2 = 0.89), but poor agreement in municipalities with less than 5% crop cover (R 2 = 0.41). The assessed methodology can be used for annual cropland mapping over large production areas in Brazil.Index terms: cropland masks, cultivated area, Fourier, vegetation index. Estimativa de área agrícola por meio de séries temporais Modis NDVI no Estado do Mato GrossoResumo -O objetivo deste trabalho foi avaliar um método simples, semiautomatizado, para o mapeamento de áreas agrícolas no Estado do Mato Grosso. A transformada de Fourier foi aplicada sobre séries temporais de produtos dos índices de vegetação do sensor "moderate resolution imaging spectroradiometer" (Modis). Este procedimento permite avaliar a amplitude das alterações periódicas da resposta da vegetação no tempo e identificar áreas com forte variação sazonal relacionadas à produção agrícola. Foram geradas máscaras anuais das áreas agrícolas de 2006 a 2009 e feitas estimativas de área cultivada em cada município, por sensoriamento remoto. Houve boa concordância com dados oficiais de área plantada, principalmente para municípios com mais de 10% de área agrícola (R 2 = 0,89), mas baixa concordância para municípios com menos de 5% de área agrícola (R 2 = 0,41). A metodologia avaliada pode ser utilizada para o mapeamento anual de áreas agrícolas extensas nos grandes centros produtores do Brasil.Termos para indexação: máscara de culturas, área cultivada, Fourier, índice de vegetação.

Mapping cropland distribution over large areas has attracted great attention in recent years, however, traditional pixel-based classification approaches produce high uncertainty in cropland area statistics. This study proposes a new approach to map fractional cropland distribution in Mato Grosso, Brazil using time series MODIS enhanced vegetation index (EVI) and Landsat Thematic Mapper (TM) data. The major steps include: (1) remove noise and clouds/shadows contamination using the Savizky-Gloay filter and temporal resampling algorithm based on the time series MODIS EVI data; (2) identify the best periods to extract croplands through crop phenology analysis; (3) develop a seasonal dynamic index (SDI) from the time series MODIS EVI data based on three key stages: sowing, growing, and harvest; and (4) develop a regression model to estimate cropland fraction based on the relationship between SDI and Landsat-derived fractional cropland data. The root mean squared error of 0.14 was obtained based on the analysis of randomly selected 500 sample plots. This research shows that the proposed approach is promising for rapidly mapping fractional cropland distribution in Mato Grosso, Brazil.