Vulnerabilidade do patrimônio ambiental tombado em Campinas-SP e sua relação com índice de vegetação.

Research conducted in forest fragments have contributed to the development of models for recovery of degraded areas, generating decrease deployment costs with increased efficiency, helping in forest management studies, and effectively preserving the remaining vegetation when considering the dynamics of regeneration compared to patterns of space occupation. The survey of the occupation history for the surrounding urban forest fragments located in the city of Campinas, São Paulo, Brazil, structured in a Geographical Information System (GIS), allowed to establish a classification which indicates the degree of vulnerability of these forests remnants based on the degree of deterioration of the landscape caused by the incidence of certain activities. The survey was made using legal decisions, occupation history, fauna and flora surveys, environmental reports, information on plant and animal biodiversity as well as the physical characteristics of the fragment?s area, which exemplified the degree and pattern of human occupation. The extraction of the Normalized Difference Vegetation Index (NDVI) for each area allowed to establish a relation between the occupation pattern for the surrounding and the changes in vegetation cover within these forests fragments, which presented a good match with the degree of vulnerability attributed in previous step

Análise comparativa de três métodos de correção atmosférica de imagens Landsat 5 - TM para obtenção de reflectância de superfície e NDVI.

The present study has compared three methods of atmospheric correction, two dark object subtraction (DOS) methods and one method based on the fourth component of the tasseled cap transformation (TC4), to obtain reflectance and NDVI values of Landsat 5 ? TM satellite images. For each atmospheric correction method, reflectance and NDVI values of five targets (crop/pasture, forest, straw, bare soil and water) were analyzed in three images (Landsat path-row 222-75). The study area is localized in the west of Sao Paulo State, Brazil. The images were acquired on 29/10/2009, 02/02/2010 and 26/06/2010 with solar zenith angles of 28°, 34° and 55°, correspondingly. The TC4 was the only method which eliminated the haze in the image, but it is not recommended if the objective is to obtain reflectance values. The DOS methods did not removed the image haze but performed reasonably to obtain reflectance values. For the visible bands, both DOS methods analyzed performed well. The DOS method which considered the atmospheric transmittance (DOS2), although more indicated to correct the infrared bands, it is dependent of the image solar zenith angle. The image acquired under a zenith angle of 55°, after been corrected using the DOS2 method, presented reflectance values overestimated. Without the atmospheric correction the NDVI of vegetation targets tended to be underestimated

Análise de metodologias para correção atmosférica e estimativa do albedo da superfície usando imagens Landsat 5, TM.

Este trabalho objetivou analisar a aplicação de diferentes metodologias para correção atmosférica e estimativa do albedo da superfície com imagens Landsat 5 ? TM para a região que abrange parte do megaleque aluvial do rio Taquari (Pantanal). Foram avaliados os métodos de correção atmosférica DOS (dark object subtraction), método de correção baseado na componente haze da transformação tasseled cap, o 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) e o método de correção implementado no algoritmo SEBAL (Surface Energy Balance Algorithm for Land). Para o cálculo do albedo, três diferentes fórmulas de estimativas foram utilizadas. Os resultados obtidos apontam a existência de uma forte variação dos valores de albedo encontrados conforme o método de correção dos efeitos atmosféricos e da escolha da fórmula de estimativa do albedo de superfície. Dentre as fórmulas utilizadas para estimativa do albedo, a fórmula de Allen et al. foi a que apresentou menos sensibilidade ao tipo de correção atmosférica adotada

Mudança no uso da terra pela agricultura brasileira de 1990 a 2014.

In this work, we used data on area harvested and quantity produced from the three major Brazilian crops in the area: soybean, sugarcane and corn, provided by the IBGE Municipal Agricultural Research (PAM), for the period between 1990 and 2014, to evaluate the dynamics of agriculture in Brazil. The analysis focused on the increase in time and the change in the space occupied by the production. We used images of the sensors OLI and TM on board the Landsat-8 and Landsat-5 satellites, respectively, to exemplify changes in land use and land cover in selected areas. In 25 years, the combination of increased Brazilian agricultural productivity with the large-scale adoption of the safrinha or second crop season (intensification of agriculture) resulted in a 197% increase in the production of these crops, without expanding the cultivated area in the same proportion of production. There was also a significant change in production sites. We have confirmed that the changes recorded by the official data were in accordance with the ones that are showed by the remote sensing images. Municipalities responding for 25% national production dramatically changed in number and in its spatial distribution in this short period, moving the grain pole from South and Southeastern region to Central-West region of Brazil

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

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

Qualidade da classificação automática de imagens de sensoriamento remoto em trabalhos apresentados nas edições anteriores do SBSR.

Abstract: A study has been carried out considering 18 years of papers published in the Simpósio Brasileiro de Sensoriamento Remoto (Brazilian Remote Sensing Symposium) related to the subject of satellite image classification. The aim of the study was to assess the degree of progress made in thematic mapping through developments in classification algorithms, different approaches (per-pixel or object-based) and methods (unsupervised and supervised). The result of 238 reported classification experiments were quantitatively analyzed through Kappa Index (KI) results. Several parameters were used to relate the experiments, as type of approach, method, number of samples and classes, used sensor system, etc. Overall, the results showed that no significant improvement was found in KI results after 18 years SBSR. The mean and KI values was found to be 0.71 and standard deviation of 0.14. Relations between KI results and number of class, type of approach and method could not be found. Thirty one percent of the experiments analyzed did not present sufficient methodological information, thus, they were excluded from the analysis

Using Landsat 8 image time series for crop mapping in a region of Cerrado, Brazil.

Abstract: The objective of this research is to classify agricultural land use in a region of the Cerrado (Brazilian Savanna) biome using a time series of Enhanced Vegetation Index (EVI) from Landsat 8 OLI. Phenological metrics extracted from EVI time series, a Random Forest algorithm and data mining techniques are used in the process of classification. The area of study is a region in the Cerrado in a region of the municipality of Casa Branca, São Paulo state, Brazil. The results are encouraging and demonstrate the potential of phenological parameters obtained from time series of OLI vegetation indices for agricultural land use classification