Dinâmica e distribuição das áreas alteradas por ação antrópica no Cerrado matogrossense no período de 2002 a 2008.

The Cerrado biome has approximately two million square kilometers, which represents 23% of the country extension. With a large territory, it is considered one of the hotspots of the Planet, ie, a priority area for conservation. However, with favorable soil and climate characteristics, this biome has become the subject of great affluence for agricultural purposes since the 1970s. With government incentives, conditions for the expansion of agriculture were created. All these factors were decisive to the expansion of so-called "agricultural frontier?, which provided important positive impacts on the Brazilian economy. However, concomitantly, increasing environmental changes are observed in this biome. The anthropogenic occupation has as the first action the deforestation and the reduction of native vegetation, and much of this occupation is linked to agricultural activity. Among several States which compose this biome, Mato Grosso has a prominent place in national agricultural production, primarily due to soybean and corn plantations. Thus, this study aims to determine the dynamics and the spatial distribution changes due to anthropogenic activities in the Cerrado of Mato Grosso state in the 2002 to 2008 time period. The deforested data from the analyzed period were obtained from ?Projeto de Monitoramento do Desmatamento dos Biomas Brasileiros por Satélite? (PMDBBS). These information were intersected with mesoregions, soil, vegetation and geomorphological maps of the study area. The results showed that highest conversions occurred in North mesoregion. The predominant vegetation type deforested was the wooded savanna and according to the soil and geomorphological maps, the results demonstrated a preference for deep soils and plan relief

Understanding the dynamic of tropical agriculture for remote sensing applications: a case study of Southeastern Brazil.

Abstract: The agricultural activity can greatly benefit from remote sensing technology (RS). Optical passive RS has been vastly explored for agricultural mapping and monitoring, in despite of cloud cover issue. This is observed even in the tropics, where frequency of clouds is very high. However, more studies are needed to better understand the high dynamism of tropical agriculture and its impact on the use of passive RS. In tropical countries, such as in Brazil, the use of current agricultural technologies, associated with favourable climate, allow the planting period to be wide and to have plants of varying phenological cycles. In this context, the main objective of the current study is to better understand the dynamics of a selected area in Southeast of São Paulo state, and its impact on the use of orbital passive RS. For that purpose, data (from field and satellite) from 55 agricultural fields, including annual, semi-perennial and perennial crops and silviculture, were acquired between July 2014 and December 2016. Field campaigns were conducted in a monthly base to gather information about the condition of the crops along their development (data available in a website). Field data corresponding to the 2014-2015 crop year were associated with a time series of Landsat-8/OLI RGB false-colour compositions images and MODIS/Terra NDVI profiles. The type of information that can be extracted (such as specie identification, crop management practices adopted, date of harvest, type o production system used etc) by combining passive remote sensing data with field data is discussed in the paper

Assessment of suitable observation conditions for a monthly operational remote sensing based crop monitoring system.

Abstract: Cloud cover is the main issue to consider when remote sensing images are used to identify, map and monitor croplands, especially over the summer season (October to March in Brazi). This paper aims at evaluating clear sky conditions over four Brazilian states (Sa?o Paulo, Parana?, Santa Catarina, and Rio Grande do Sul) to assess suitable observation conditions for a monthly basis operational crop monitoring system. Cloudiness was analyzed using MODIS Cloud Mask product (MOD35), which presents four labels for cloud cover status: cloudy, uncertainty, probably clear and confident clear. R software was used to compute average values of clear sky with a confidence interval of 95% for each month between July 1st, 2000 and June 30th, 2013. Results showed significant differences within and between the four tested states. Moreover, the period from November to March presented 50% less clear sky areas when compared to April to October

Método para estratificação em levantamentos agrícolas com mais de uma variável.

Resumo: O presente trabalho propõe bases teóricas e práticas para metodologias voltadas à obtenção de estimativas de áreas agrícolas, utilizando técnicas estatísticas de amostragem, conjugadas com estratificação e auxiliadas por sensoriamento remoto, quando se tem três culturas de interesse no mesmo levantamento.bitstream/item/138497/1/2015DC02.pd

Avaliação espaço-temporal da cultura da cana-de-açúcar no oeste paulista.

This work aims to analyze the dynamics of land use change by evaluating the spatio-temporal changes of sugarcane, verified in the period between 2000 and 2015, in the western portion of the São Paulo state. The study area includes parts of the municipalities of Andradina, Muritinga do Sul, Guaraçaí and Pereira Barreto, totaling an area of 1,115 km2. From a multitemporal series of Landsat satellite images of 30 m spatial resolution, the land use information was obtained for the sixteen years, using the Spring software. Land use and land cover maps were analyzed for each date, and the expansion of sugarcane activity in the region was verified, annually, for the period analyzed. As results, it was observed that sugarcane had an expansion in area between the years 2000 and 2014. In the year 2000, about 8,000 hectares of sugarcane were already being cultivated in this area. And although between 2014 and 2015 there was no expansion, the area of sugarcane increased more than fivefold in 15 years analyzed, reaching 42,000 hectares in 2015. It is noteworthy mentioned that this expansion occurred mainly in the conversion of grazing areas, determining new regional configurations of agricultural holdings for the western region of São Paulo

Cloud cover assessment for operational crop monitoring systems in tropical areas.

Abstract: The potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no signi?cant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles(UAVs) might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another option. In cases where wall-to-wall maps are not mandatory, statistical sampling approaches might also be a suitable alternative for obtaining useful crop area information

Variabilidade espacial da fertilidade, carbono e nitrogênio do solo em áreas de pastagem e cana-de-açúcar no estado de São Paulo.

The spatial variability of soil and plant properties has been a concern of researchers, since the variation of any phenomenon in space or time, whether caused by natural processes or by man-imposed actions, has always existed and need considered. The objective was relate spatial variability of chemical attributes, including carbon and nitrogen, to pasture and sugarcane areas in the west of the state of São Paulo. A total of 36 points were sampled in the west of the state of São Paulo in areas of pasture and sugar cane. For each point were collected soil chemical data at depth of 0 cm to 30 cm in March 2015. For identification of spatial dependence, data interpolation and for the elaboration of the maps, the geostatistical analysis was used including adjustment of the semivariogram. To relate the maps of soil chemical attributes interpolated by geostatistical and kriging with grazing and sugarcane areas, the land use map was obtained. There was spatial dependence for the chemical attributes analyzed and the ranges of values showed soil-related variability. The highest values of nutrients, carbon and nitrogen in the areas of sugarcane production, evidencing the positive effect of crop management on the soil when compared to pasture areas

Dinâmica agrícola em área de sobreposição de órbitas adjacentes dos satélites Landsat.

Abstract: In this study, the tracking of different types of agricultural land use was assessed over time using the overlap regions of adjacent Landsat Operational Land Imager (OLI) scenes. WRS-II scenes 219 e 220/75 were acquired between July and October 2014. In the same period, 55 georeferenced sites were visited monthly, to acquire information about their use and to photograph them. The study covered an area of 100 km long by 4 km wide along a highway in the mesoregion of Campinas, state of São Paulo, Brazil. The main agricultural crops in the state were present in this area, such as sugarcane, maize, soybean, eucalyptus, pastures, citrus; and over a dozen land uses were found. Several selected areas are irrigated by center pivot systems. In this short period of time, the importance of monitoring simultaneously three axes, namely: the time, space and land use, proved essential, since there is a high potential for classification confusion. Interesting things were observed, such as the phenomenon of green-up of rubber tree fields; and the similar appearance of potatoes, beans and wheat plots in images, even though they do not look like in the field. Preliminary analysis, both visual and quantitative, confirm the assumption that it is not possible to correctly classify agricultural uses in OLI images based only on a single date and without substantial knowledge of the systems in use, and the farming calendar of the study region

Metodologia para monitoramento agrícola com emprego de imagens orbitais e amostragem estatística.

Abstract: Brazil still has not a system based in earth observation images to map and monitoring the aimed crops in large scale. Many programs have been made with Landsat-like and MODIS data to monitoring crops in Brazil, but only the CANASAT has worked in operation level. The clouds and unit products (UPS) size in Brazil, have not permitted the use these data to correct classify maize, sugarcane and soybean. The use of sample frame and visual pixels classification with multitemporal OLI images could be a solution to monitor these three crops. The goal of this study was evaluate the sample frame performance to maize (c1), soybean (c2) and sugarcane (c3) in Paraná (PR) State using OLI images and pixel visual classification. Were used four periods to classify 20.000 random pixels over all the Paraná State: (p1) Nov/Dec, (p2) Jan/Feb, (p3) Mar/Apr and (p4) May/Jun. Each period was compost for 4 OLI images, and 5.000 pixels were classified as c1, c2, c3 and others. IBGE data from 2012 were used to determinate the number of random pixels in each PR mesoregion/stratum. The Stratified Random Sample by Maximum Corrected (SRSMC) showed good performance for tree crops. The coefficient of variation (CV) for each period ranged of 1.42 for soybean in p2 until 16.87 for soybean in p4. The sugarcane CVs have not varied ( and maize CV had the minimum value (2.16) in p4