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.

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 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 Using Solar-Induced Chlorophyll Fluorescence Observed by OCO-2 to Predict Autumn Crop Production in China

2019 ◽  
Vol 11 (14) ◽  
pp. 1715 ◽  
Author(s):  
Jin Wei ◽  
Xuguang Tang ◽  
Qing Gu ◽  
Min Wang ◽  
Mingguo Ma ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Crop Production ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Close Correlation ◽  
Estimation Accuracy ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

The remote sensing of solar-induced chlorophyll fluorescence (SIF) has attracted considerable attention as a new monitor of vegetation photosynthesis. Previous studies have revealed the close correlation between SIF and terrestrial gross primary productivity (GPP), and have used SIF to estimate vegetation GPP. This study investigated the relationship between the Orbiting Carbon Observatory-2 (OCO-2) SIF products at two retrieval bands (SIF757, SIF771) and the autumn crop production in China during the summer of 2015 on different timescales. Subsequently, we evaluated the performance to estimate the autumn crop production of 2016 by using the optimal model developed in 2015. In addition, the OCO-2 SIF was compared with the moderate resolution imaging spectroradiometer (MODIS) vegetation indices (VIs) (normalized difference vegetation index, NDVI; enhanced vegetation index, EVI) for predicting the crop production. All the remotely sensed products exhibited the strongest correlation with autumn crop production in July. The OCO-2 SIF757 estimated autumn crop production best (R2 = 0.678, p < 0.01; RMSE = 748.901 ten kilotons; MAE = 567.629 ten kilotons). SIF monitored the crop dynamics better than VIs, although the performances of VIs were similar to SIF. The estimation accuracy was limited by the spatial resolution and discreteness of the OCO-2 SIF products. Our findings demonstrate that SIF is a feasible approach for the crop production estimation and is not inferior to VIs, and suggest that accurate autumn crop production forecasts while using the SIF-based model can be obtained one to two months before the harvest. Furthermore, the proposed method can be widely applied with the development of satellite-based SIF observation technology.

scholarly journals COMPORTAMENTO SAZONAL DO ALBEDO E DOS ÍNDICES DE VEGETAÇÃO NA BACIA HIDROGRÁFICA DO ALTO CURSO DO RIO PARAÍBA (Albedo Seasonal Behavior and vegetation indices in the upper basin Paraíba River)

2015 ◽  
Vol 7 (5) ◽  
pp. 1015
Author(s):  
Francineide Amorim Santos ◽  
TELMA LUCIA ALVES ◽  
PEDRO VIEIRA AZEVEDO ◽  
CARLOS SANTOS
Keyword(s):  
Rainy Season ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Seasonal Behavior ◽  
Short Rainy Season ◽  
Erdas Imagine ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The City

O objetivo deste estudo foi apresentar as variações do albedo, do índice de vegetação por diferença normalizada (IVDN) e do índice de vegetação para ajustamento do solo (IVAS) para a bacia do alto curso do Rio Paraíba, composta por 18 municípios. Os parâmetros foram obtidos a partir de imagens Moderate Resolution Imaging Spectroradiometer (MODIS) da plataforma Terra, sendo todas as rotinas computacionais necessárias executadas através do programa ERDAS Imagine 8.5. Foram utilizadas imagens referentes aos dias julianos: 025, 033, 089, 0,97, 137, 169, 201, 233, 273, 281, 313, 337 de 2013. O albedo foi estimado pelos métodos de Liang (2000) e Tasumi et al. (2008) visando a precisão das estimativas. Os resultados evidenciam que a precipitação é identificada como fator de controle decisivo da tendência dos índices de vegetação e, indiretamente, do albedo. O município de Caraúbas foi o que apresentou menor índice de vegetação, tanto pelo IVDN quanto pelo IVAS, enquanto o município de São Sebastião do Umbuzeiro apresentou os índices mais elevados. O mês de fevereiro apresentou os maiores valores de albedo para os municípios e menores valores de IVDN. Por outro lado, o mês de maio apresentou os valores menores de albedo e maiores de IVDN e IVAS, devido a curta estação chuvosa na região, que é compreendida entre fevereiro, março e abril.    A B S T R A C T The aim of this study was to present the variations of albedo, index of normalized difference vegetation (NDVI) and the vegetation index adjusted for soil (SAVI) to the basin of the upper course of the Rio Paraiba, composed of 18 municipalities. The parameters were obtained from images Moderate Resolution Imaging Spectroradiometer (MODIS) Earth platform, with all the necessary computational routines performed by the ERDAS Imagine program 8.5 images related to Julian days were used:. 025, 033, 089, 0.97 , 137, 169, 201, 233, 273, 281, 313, 337, 2013. Albedo were estimated by the methods of Liang (2000) and Tasumi et al. (2008) aimed at the precision of the estimates. Results indicateds show that precipitation may be is identified as a decisive factor controlling the trend of vegetation indices and, indirectly, albedo. The municipality Caraúbas showed the lowest vegetation index, NDVI as much by the SAVI, while the city of São Sebastião do Umbuzeiro showed the highest levels. The month of February had the highest albedo values for municipalities and lower values of NDVI. Moreover, the month of May had the lowest albedo and higher NDVI values and SAVI due to the short rainy season in the region, comprising between February, March and April. Keywords: Caatinga; wettest quarter; dry and wet seasons.    

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 Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

scholarly journals A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data

2021 ◽  
Vol 13 (15) ◽  
pp. 2895
Author(s):  
Maria Gavrouzou ◽  
Nikolaos Hatzianastassiou ◽  
Antonis Gkikas ◽  
Christos J. Lolis ◽  
Nikolaos Mihalopoulos
Keyword(s):  
Mediterranean Basin ◽  
Eastern Mediterranean ◽  
Mean Value ◽  
Early Spring ◽  
Dust Aerosol ◽  
Ozone Monitoring Instrument ◽  
Central Mediterranean ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.

scholarly journals 250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  
Keyword(s):  
Mixing Model ◽  
Blue Band ◽  
Aerosol Retrieval ◽  
Aerosol Distribution ◽  
Medium Resolution ◽  
Fine Spatial Resolution ◽  
Yearly Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

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