scholarly journals DETECTING CENTER PIVOTS IN MATOPIBA USING HOUGH TRANSFORM AND WEB TIME SERIES SERVICE

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 73-78
Author(s):  
M. L. Rodrigues ◽  
T. S. Körting ◽  
G. R. de Queiroz ◽  
C. P. Sales ◽  
L. A. R. da Silva
Keyword(s):  
Time Series ◽  
Hough Transform ◽  
Vegetation Indices ◽  
Landsat 8 ◽  
Small Areas ◽  
Detection Techniques ◽  
Center Pivot ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. In the last decades, the Brazilian Cerrado biome has undergone major transformations due to the expansion of the agricultural frontier. The region called MATOPIBA acronym for states Maranhão, Tocantins, Piauí, and Bahia can be considered very attractive for agricultural expansion. The Cerrado predominates in the MATOPIBA region (91% of the area), also having small areas of the Amazon and Caatinga biomes to the northeast and east, respectively. In this work, we will present a study to identify center pivot irrigation systems in the MATOPIBA region using remote sensing images from Landsat-8 satellite. The methodology is based on the use of robust edge detection techniques such as Canny, Circular Hough Transform (CHT) and time series extraction through the Moderate Resolution Imaging Spectroradiometer (MODIS) product MOD13Q1 which has two vegetation indices NDVI and EVI. These time series will be used to filter the detected circles, seeking to eliminate the circles that do not correspond to center pivots. Our approach detected 80% of the center pivots mapped by the Brazilian National Water Agency (ANA) used as a knowledge base. The states with better detection were Piauí and Bahia that showed the accuracy of 90% and 85% respectively, Maranhão obtained 57% and Tocantins 41%.

scholarly journals Consequences of the 2019 Greenland Ice Sheet Melt Episode on Albedo

2021 ◽  
Vol 13 (2) ◽  
pp. 227
Author(s):  
Arthur Elmes ◽  
Charlotte Levy ◽  
Angela Erb ◽  
Dorothy K. Hall ◽  
Ted A. Scambos ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Energy Budget ◽  
Landsat 8 ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Seasonal Snow Cover

In mid-June 2019, the Greenland ice sheet (GrIS) experienced an extreme early-season melt event. This, coupled with an earlier-than-average melt onset and low prior winter snowfall over western Greenland, led to a rapid decrease in surface albedo and greater solar energy absorption over the melt season. The 2019 melt season resulted in significantly more melt than other recent years, even compared to exceptional melt years previously identified in the moderate-resolution imaging spectroradiometer (MODIS) record. The increased solar radiation absorbance in 2019 warmed the surface and increased the rate of meltwater production. We use two decades of satellite-derived albedo from the MODIS MCD43 record to show a significant and extended decrease in albedo in Greenland during 2019. This decrease, early in the melt season and continuing during peak summer insolation, caused increased radiative forcing of the ice sheet of 2.33 Wm−2 for 2019. Radiative forcing is strongly influenced by the dramatic seasonal differences in surface albedo experienced by any location experiencing persistent and seasonal snow-cover. We also illustrate the utility of the newly developed Landsat-8 albedo product for better capturing the detailed spatial heterogeneity of the landscape, leading to a more refined representation of the surface energy budget. While the MCD43 data accurately capture the albedo for a given 500 m pixel, the higher spatial resolution 30 m Landsat-8 albedos more fully represent the detailed landscape variations.

Improved fuel moisture prediction in non-native tropical Megathyrsus maximus grasslands using Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived vegetation indices

2017 ◽  
Vol 26 (5) ◽  
pp. 384
Author(s):  
L. M. Ellsworth ◽  
A. P. Dale ◽  
C. M. Litton ◽  
T. Miura
Keyword(s):  
Vegetation Index ◽  
Vegetation Indices ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Native Grass ◽  
Tropical Ecosystems ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Live Fuel Moisture ◽  
Moderate Resolution Imaging Spectroradiometer

The synergistic impacts of non-native grass invasion and frequent human-derived wildfires threaten endangered species, native ecosystems and developed land throughout the tropics. Fire behaviour models assist in fire prevention and management, but current models do not accurately predict fire in tropical ecosystems. Specifically, current models poorly predict fuel moisture, a key driver of fire behaviour. To address this limitation, we developed empirical models to predict fuel moisture in non-native tropical grasslands dominated by Megathyrsus maximus in Hawaii from Terra Moderate-Resolution Imaging Spectroradiometer (MODIS)-based vegetation indices. Best-performing MODIS-based predictive models for live fuel moisture included the two-band Enhanced Vegetation Index (EVI2) and Normalized Difference Vegetation Index (NDVI). Live fuel moisture models had modest (R2=0.46) predictive relationships, and outperformed the commonly used National Fire Danger Rating System (R2=0.37) and the Keetch–Byram Drought Index (R2=0.06). Dead fuel moisture was also best predicted by a model including EVI2 and NDVI, but predictive capacity was low (R2=0.19). Site-specific models improved model fit for live fuel moisture (R2=0.61), but limited extrapolation. Better predictions of fuel moisture will improve fire management in tropical ecosystems dominated by this widespread and problematic non-native grass.

scholarly journals Spatiotemporal Mapping and Monitoring of Whiting in the Semi-Enclosed Gulf Using Moderate Resolution Imaging Spectroradiometer (MODIS) Time Series Images and a Generic Ensemble Tree-Based Model

2019 ◽  
Vol 11 (10) ◽  
pp. 1193 ◽  
Author(s):  
Abdallah Shanableh ◽  
Rami Al-Ruzouq ◽  
Mohamed Barakat A. Gibril ◽  
Cristina Flesia ◽  
Saeed AL-Mansoori
Keyword(s):  
Time Series ◽  
Spectral Band ◽  
Classification Model ◽  
Series Data ◽  
Natural Phenomenon ◽  
Adaptive Boosting ◽  
Rule Based ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Whiting events in seas and lakes are a natural phenomenon caused by suspended calcium carbonate (CaCO3) particles. The Arabian Gulf, which is a semi-enclosed sea, is prone to extensive whiting that covers tens of thousands of square kilometres. Despite the extent and frequency of whiting events in the Gulf, studies documenting the whiting phenomenon are lacking. Therefore, the primary objective of this study was to detect, map and document the spatial and temporal distributions of whiting events in the Gulf using daily images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua satellites from 2002 to 2018. A method integrating a geographic object-based image analysis, the correlation-based feature selection technique (CFS), the adaptive boosting decision tree (AdaBoost DT) and the rule-based classification were used in the study to detect, quantify and assess whiting events in the Gulf from the MODIS data. Firstly, a multiresolution segmentation was optimised using unsupervised quality measures. Secondly, a set of spectral bands and indices were investigated using the CFS to select the most relevant feature(s). Thirdly, a generic AdaBoost DT model and a rule-based classification were adopted to classify the MODIS time series data. Finally, the developed classification model was compared with various tree-based classifiers such as random forest, a single DT and gradient boosted DT. Results showed that both the combination of the mean of the green spectral band and the normalised difference index between the green and blue bands (NDGB), or the combination of the NDGB and the colour index for estimating the concentrations of calcium carbonates (CI) of the image objects, were the most significant features for detecting whiting. Moreover, the generic AdaBoost DT classification model outperformed the other tested tree-based classifiers with an overall accuracy of 97.86% and a kappa coefficient of 0.97. The whiting events during the study period (2002–2018) occurred exclusively during the winter season (November to March) and mostly in February. Geographically, the whiting events covered areas ranging from 12,000 km2 to 60,000 km2 and were mainly located along the southwest coast of the Gulf. The duration of most whiting events was 2 to 6 days, with some events extending as long as 8 to 11 days. The study documented the spatiotemporal distribution of whiting events in the Gulf from 2002 to 2018 and presented an effective tool for detecting and motoring whiting events.

Wetlands classification and assessment of Ramsar sites in China based on time series Moderate Resolution Imaging Spectroradiometer (MODIS) imagery

2018 ◽  
Vol 69 (5) ◽  
pp. 658 ◽  
Author(s):  
Liwei Xing ◽  
Zhenguo Niu ◽  
Panpan Xu ◽  
Dachong Li
Keyword(s):  
Time Series ◽  
Landscape Metrics ◽  
Time Series Data ◽  
Wetland Loss ◽  
Series Data ◽  
Landscape Disturbance ◽  
Landscape Integrity ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Globally, wetland loss and degradation have become serious environmental and ecological issues. Wetland monitoring of Ramsar sites in China is important for developing reasonable strategies to protect wetlands. Satellite image time series may be used for the long-term monitoring of wetland ecosystems. The present study used moderate-resolution imaging spectroradiometer (MODIS) time series data collected in 2001 and 2013 for 20 Ramsar sites in China and assessed the environmental status of these reserves using landscape metrics. The results showed that specific seasonal wetland classes, such as flooded mud, permanent water and seasonal marshes, can be identified using MODIS time series data with acceptable accuracy. In addition to wetland area, we suggest using other landscape metrics, including landscape integrity and landscape disturbance or degradation indices, to assess wetland environmental quality. The slight wetland loss (0.8%) noted in the 20 reserves evaluated herein could indicate the effectiveness of efforts of the Chinese government and local government agencies to protect Ramsar sites. The existing unfavourable environmental conditions, which were manifested by low landscape integrity and high landscape disturbance or degradation for some reserves, were caused primarily by increasing water requirements outside the reserves and by agricultural development within reserves. Therefore, determining how to balance relationships between economic development and ecological protection of the reserves will be important in the future.

scholarly journals TVDI Obtido de Imagens OLI/TIRS e MODIS

2019 ◽  
Vol 34 (4) ◽  
pp. 573-583
Author(s):  
Lucimara Wolfarth Schirmbeck ◽  
Denise Cybis Fontana ◽  
Juliano Schirmbeck ◽  
Carolina Bremm
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Moderate Resolution ◽  
Dryness Index ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Resumo O objetivo do estudo foi analisar a variabilidade no TVDI (Temperature-Vegetation Dryness Index) obtido de sensores orbitais com resoluções distintas, em região agrícola no sul do Brasil. Utilizou-se três imagens OLI/TIRS (Operational Land Imager/Thermal Infrared Sensor) do satélite Landsat 8, e 12 imagens MODIS (Moderate Resolution Imaging Spectroradiometer) do satélite Terra. Dados coletados em campo serviram como base para classificação de imagem OLI/TIRS e mapeamento de áreas de arroz, soja, campos naturais, mata ciliar e solo exposto. O TVDI foi obtido por duas parametrizações em períodos distintos, utilizando as dispersões entre Temperatura de Superfície (TS) e NDVI (Normalized Difference Vegetation Index). O TVDI obtido para ambos sensores apresentou padrão similar possibilitando diferenciar os alvos. Na média de todas as datas e classes, o TVDI obtido das imagens MODIS foi superior em 0,128 unidades ao TVDI obtido com o OLI/TIRS. Quando utilizado OLI/TIRS há um melhor detalhamento espacial das condições hídricas, mas com menor repetição ao longo da safra; já utilizando o TVDI-MODIS é possível monitorar as condições hídricas em escala regional, com menor detalhamento espacial, mas com maior repetitividade no tempo. O TVDI estimado pelos sensores OLI/TIRS e MODIS, pode ser utilizado de forma conjunta, trazendo informações complementares.

scholarly journals Ushering in the New Era of Radiometric Intercomparison of Multispectral Sensors with Precision SNO Analysis

Climate ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 81 ◽  
Author(s):  
Chu ◽  
Dodd
Keyword(s):  
Time Series ◽  
Sample Size ◽  
Polar Regions ◽  
New Era ◽  
High Performing ◽  
Comparison Time ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Multispectral Sensors

A “nadir-only” framework of the radiometric intercomparison of multispectral sensors using simultaneous nadir overpasses (SNOs) is examined at the 1-km regimes and below using four polar-orbiting multispectral sensors: the twin MODerate-resolution Imaging Spectroradiometer (MODIS) in the Terra and Aqua satellites, the Visible Imaging Infrared Radiometer Suite (VIIRS) in the Suomi National Polar-orbiting Partnership (SNPP) satellite, and the Ocean and Land Colour Instrument (OLCI) in the Sentinel-3A satellite. The study is carried out in the context of isolating the on-orbit calibration of the reflective solar bands (RSBs) under the “nadir-only” restriction. With a homogeneity-ranked, sample size constrained procedure designed to minimize scene-based variability and noise, the overall approach successfully stabilizes the radiometric ratio and tightens the precision of each SNO-generated comparison event. Improvements to the multiyear comparison time series are demonstrated for different conditions of area size, sample size, and other refinements. The time series demonstrate the capability at 1% precision or better under general conditions but can attain as low as 0.2% in best cases. Solar zenith angle is examined not to be important in the “nadir-only” framework, but the spectral mismatch between two bands can give rise to significant yearly modulation in the comparison time series. A broad-scaled scene-based variability of ~2%, the “scaling phenomenon”, is shown to have pervasive presence in both northern and the southern polar regions to impact inter-RSB comparison. Finally, this paper highlights the multi-instrument cross-comparisons that are certain to take on a more important role in the coming era of high-performing multispectral instruments.

scholarly journals Limitations and Challenges of MODIS-Derived Phenological Metrics Across Different Landscapes in Pan-Arctic Regions

2018 ◽  
Vol 10 (11) ◽  
pp. 1784 ◽  
Author(s):  
Siyu Wang ◽  
Xinchen Lu ◽  
Xiao Cheng ◽  
Xianglan Li ◽  
Matthias Peichl ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Vegetation Indices ◽  
Optical Remote Sensing ◽  
Arctic Ecosystems ◽  
Arctic Regions ◽  
Land Cover Dynamics ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Phenological Metrics

Recent efforts have been made to monitor the seasonal metrics of plant canopy variations globally from space, using optical remote sensing. However, phenological estimations based on vegetation indices (VIs) in high-latitude regions such as the pan-Arctic remain challenging and are rarely validated. Nevertheless, pan-Arctic ecosystems are vulnerable and also crucial in the context of climate change. We reported the limitations and challenges of using MODerate-resolution Imaging Spectroradiometer (MODIS) measurements, a widely exploited set of satellite measurements, to estimate phenological transition dates in pan-Arctic regions. Four indices including normalized vegetation difference index (NDVI), enhanced vegetation index (EVI), phenology index (PI), plant phenological index (PPI) and a MODIS Land Cover Dynamics Product MCD12Q2, were evaluated and compared against eddy covariance (EC) estimates at 11 flux sites of 102 site-years during the period from 2000 to 2014. All the indices were influenced by snow cover and soil moisture during the transition dates. While relationships existed between VI-based and EC-estimated phenological transition dates, the R2 values were generally low (0.01–0.68). Among the VIs, PPI-estimated metrics showed an inter-annual pattern that was mostly closely related to the EC-based estimations. Thus, further studies are needed to develop region-specific indices to provide more reliable estimates of phenological transition dates.

scholarly journals BRDF-CORRECTED VEGETATION INDICES CONFIRM SEASONAL PATTERN IN GREENING OF FRENCH GUIANA’S FORESTS

2020 ◽  
Vol 1 (211-212) ◽  
pp. 3-9
Author(s):  
Emil A. Cherrington
Keyword(s):  
Nous Avons ◽  
Seasonal Pattern ◽  
Vegetation Indices ◽  
Dynamique Forestière ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Parmi les outils de caractérisation de la dynamique forestière, la télédétection est particulièrement adaptée pourl’observation des vastes surfaces forestières de Guyane  d’accès difficile. Dans le but de réévaluer les hypothèses énoncées dans des études antérieures sur la capacité des capteurs optiques embarqués sur les satellites à détecter la dynamique de la phénologie, nous avons compilé sur une période de 12 années divers indices de végétation corrigés des effets bi-directionnels de variation des angles d’acquisition (BRDF). Ces indices sont issus de 2 capteurs optiques: SPOT VEGETATION, et MODIS (MODerate resolution Imaging Spectroradiometer). Les données ont été analysées pour évaluer les tendances saisonnières à l'échelle de l’ensemble de la Guyane et également sur quatre sites répartis sur ce territoire. Les données révèlent que les forêts de Guyane présentent un patron de saisonnalité. Le pic annuel des divers indices au cours de la période de septembre à octobre est interprété comme le reflet d’un pic de production de feuilles pendant la saison sèche.

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