Agrometeorological conditions associated with phenological responses of tucumã-do-pará (Astrocaryum vulgare Mart.)

ABSTRACT Palms are among the class of hyperdominant species in the Amazon region, and for the tucumã palm (Astrocaryum vulgare Mart.) demand of climatic and phenological information in order to support strategic planning and sustainable management of this palm species native to the Amazon basin. The objective of this work was to evaluate agrometeorological conditions associated to phenological responses of tucumã as a species that has high economic potential for fruit pulp production. Meteorological data were collected during the period in which data were also collected for the phenology of the germplasm bank. Sensors were installed to monitor temperature and air relative humidity to where they are observed as phenophases. Analyses were conducted to identify the responses of the tucumã stems in function of agrometeorological conditions of the study area. Precipitation, thermal amplitude, and insolation showed positive correlations principally with respect to the percent of stems with bracts, inflorescences, or with fertilized inflorescences. In the fruiting phenological phase precipitation and air relative humidity influenced the percentage of stems with fruit clusters that were immature and also ones with mature clusters. High maximum temperatures compromise the expression of the percentage of stems with green fruit clusters. The tucumã stems were photosynthesizing and carrying out metabolic processes at a very high rate during the study period based on the high Normalized Difference Vegetation Index which was superior to 0.41 during the three years of this study. The tucumã phenological phases, demonstrating a strong positive association with insolation, maximum temperature and thermal amplitude.

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Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

Remote Sensing ◽

10.3390/rs13020323 ◽

2021 ◽

Vol 13 (2) ◽

pp. 323

Author(s):

Liang Chen ◽

Xuelei Wang ◽

Xiaobin Cai ◽

Chao Yang ◽

Xiaorong Lu

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Maximum Temperature ◽

Maximum Temperature Difference ◽

Rapid Urbanization ◽

The Impact ◽

The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

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Air quality at open-cast coal mining regions at Hunter Valley, Australia and Ramagundam, India

10.5194/egusphere-egu21-9933 ◽

2021 ◽

Author(s):

Harsh Kamath ◽

Chanchal Chauhan ◽

Sameer Mishra ◽

Aariz Ahmed ◽

Raman Srikanth

Keyword(s):

Power Plants ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Meteorological Data ◽

Thermal Power ◽

Coal Mines ◽

Export Market ◽

P Value ◽

Open Cast ◽

Monitoring Stations

<p>The upper Hunter Valley region in New South Wales (NSW), Australia has several open-cast coal mines, which supply coal to two large thermal power plants (TPPs) in the area, beside the export market. Long-term Particulate Matter (PM) pollutants and meteorological measurements are recorded by a network of 13 NSW government-owned continuous monitoring stations in the upper Hunter Valley region. The Ramagundam area in the state of Telangana, India has similar pollution source characteristics (coal mines and TPPs), but PM pollutant measurements are largely carried out with manual monitoring stations at 24-hour intervals, not more than twice a week. As the coal and overburden excavation from open-cast coal mines and stack emissions from TPPs lead to local PM pollution, we have used MODIS-MAIAC Aerosol Optical Depth (AOD) at 550 nm and Normalized Difference Vegetation Index (NDVI) along with the local meteorological data such as ambient temperature, relative humidity, wind speed and direction to model PM10 and PM2.5 at the upper Hunter Valley and Ramagundam regions. Our model can explain about 60% of variation in PM10 (p-value < 0.0001), while a similar model is able to explain about 75% of the variation in the PM2.5 (p-value < 0.0001). We will extend our model results from Hunter Valley to Ramagundam area and comment on the potential of using geospatial products such as AOD as a proxy to ground-based pollution measurements in developing countries such as India, where pollution data is scarce.</p>

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SEASONAL AND INTERANNUAL PATTERN OF METEOROLOGICAL VARIABLES IN CUIABÁ, MATO GROSSO STATE, BRAZIL

Brazilian Journal of Geophysics ◽

10.22564/rbgf.v33i3.949 ◽

2015 ◽

Vol 33 (3) ◽

pp. 477 ◽

Cited By ~ 2

Author(s):

Nadja Gomes Machado ◽

Marcelo Sacardi Biudes ◽

Carlos Alexandre Santos Querino ◽

Victor Hugo De Morais Danelichen ◽

Maísa Caldas Souza Velasque

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Meteorological Data ◽

Seasonal Pattern ◽

Global Radiation ◽

Meteorological Variables ◽

Maximum Temperature ◽

Wet Season ◽

Agricultural Producers ◽

Mato Grosso

ABSTRACT. Cuiab´a is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use of natural resources in a sustainable manner requires knowledge of the regional meteorological variables. Thus, the objective of this study was to characterize the seasonal and interannual pattern of meteorological variables in Cuiab´a. The meteorological data from 1961 to 2011 were provided by the Instituto Nacional de Meteorologia (INMET – National Institute of Meteorology). The results have shown interannual and seasonal variations of precipitation, solar radiation, air temperature and relative humidity, and wind speed and direction, establishing two main distinct seasons (rainy and dry). On average, 89% of the rainfall occurred in the wet season. The annual average values of daily global radiation, mean, minimum and maximum temperature and relative humidity were 15.6 MJ m–2 y–1, 27.9◦C, 23.0◦C, 30.0◦C and 71.6%, respectively. Themaximum temperature and the wind speed had no seasonal pattern. The wind speed average decreased in the NWdirectionand increased in the S direction.Keywords: meteorological variables, climatology, ENSO. RESUMO. Cuiabá está localizado na fronteira do Pantanal com o Cerrado, no Mato Grosso, que é reconhecido como um dos maiores produtores agrícolas do Brasil. A utilização dos recursos naturais de forma sustentável requer o conhecimento das variáveis meteorológicas em escala regional. Assim, o objetivo deste estudo foi caracterizar o padrão sazonal e interanual das variáveis meteorológicas em Cuiabá. Os dados meteorológicos de 1961 a 2011 foram fornecidos pelo Instituto Nacional de Meteorologia (INMET). Os resultados mostraram variações interanuais e sazonais de precipitação, radiação solar, temperatura e umidade relativa do ar e velocidade e direção do vento, estabelecendo duas principais estações distintas (chuvosa e seca). Em média, 89% da precipitação ocorreu na estação chuvosa. Os valores médios anuais de radiação diária global, temperatura do ar média, mínima e máxima e umidade relativa do ar foram 15,6 MJ m–2 y–1, 27,9◦C, 23,0◦C, 30,0◦C e 71,6%, respectivamente. A temperatura máxima e a velocidade do vento não tiveram padrão sazonal. A velocidade média do vento diminuiu na direção NW e aumentou na direção S.Palavras-chave: variáveis meteorológicas, climatologia, ENOS.

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Surveillance along the Rio Grande during the 2020 Vesicular Stomatitis Outbreak Reveals Spatio-Temporal Dynamics of and Viral RNA Detection in Black Flies

Pathogens ◽

10.3390/pathogens10101264 ◽

2021 ◽

Vol 10 (10) ◽

pp. 1264

Author(s):

Katherine I. Young ◽

Federico Valdez ◽

Christina Vaquera ◽

Carlos Campos ◽

Lawrence Zhou ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Temporal Dynamics ◽

Rio Grande ◽

Maximum Temperature ◽

Black Flies ◽

Southern Mexico ◽

Black Fly ◽

The Usa ◽

Vesicular Stomatitis

Vesicular stomatitis virus (VSV) emerges periodically from its focus of endemic transmission in southern Mexico to cause epizootics in livestock in the US. The ecology of VSV involves a diverse, but largely undefined, repertoire of potential reservoir hosts and invertebrate vectors. As part of a larger program to decipher VSV transmission, we conducted a study of the spatiotemporal dynamics of Simulium black flies, a known vector of VSV, along the Rio Grande in southern New Mexico, USA from March to December 2020. Serendipitously, the index case of VSV-Indiana (VSIV) in the USA in 2020 occurred at a central point of our study. Black flies appeared soon after the release of the Rio Grande’s water from an upstream dam in March 2020. Two-month and one-year lagged precipitation, maximum temperature, and vegetation greenness, measured as Normalized Difference Vegetation Index (NDVI), were associated with increased black fly abundance. We detected VSIV RNA in 11 pools comprising five black fly species using rRT-PCR; five pools yielded a VSIV sequence. To our knowledge, this is the first detection of VSV in the western US from vectors that were not collected on premises with infected domestic animals.

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Habitat productivity is a poor predictor of body size in rodents

Current Zoology ◽

10.1093/cz/zoz037 ◽

2019 ◽

Vol 66 (2) ◽

pp. 135-143 ◽

Cited By ~ 5

Author(s):

Bader H Alhajeri ◽

Lucas M V Porto ◽

Renan Maestri

Keyword(s):

Body Size ◽

Least Squares ◽

Body Mass ◽

Resource Availability ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Positive Association ◽

Generalized Least Squares ◽

Habitat Productivity ◽

Resource Availability Hypothesis

Abstract The “resource availability hypothesis” predicts occurrence of larger rodents in more productive habitats. This prediction was tested in a dataset of 1,301 rodent species. We used adult body mass as a measure of body size and normalized difference vegetation index (NDVI) as a measure of habitat productivity. We utilized a cross-species approach to investigate the association between these variables. This was done at both the order level (Rodentia) and at narrower taxonomic scales. We applied phylogenetic generalized least squares (PGLS) to correct for phylogenetic relationships. The relationship between body mas and NDVI was also investigated across rodent assemblages. We controlled for spatial autocorrelation using generalized least squares (GLS) analysis. The cross-species approach found extremely low support for the resource availability hypothesis. This was reflected by a weak positive association between body mass and NDVI at the order level. We find a positive association in only a minority of rodent subtaxa. The best fit GLS model detected no significant association between body mass and NDVI across assemblages. Thus, our results do not support the view that resource availability plays a major role in explaining geographic variation in rodent body size.

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Estimation of Crop Water Deficit in Lower Bari Doab, Pakistan Using Reflection-Based Crop Coefficient

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9030173 ◽

2020 ◽

Vol 9 (3) ◽

pp. 173

Author(s):

Muhammad Asif Javed ◽

Sajid Rashid Ahmad ◽

Wakas Karim Awan ◽

Bilal Ahmed Munir

Keyword(s):

Water Deficit ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Crop Coefficient ◽

Maximum Temperature ◽

Filter Method ◽

Command Area ◽

Landsat 8 ◽

Crop Water ◽

Crop Coefficients

There is a global realization in all governmental setups of the need to provoke the efficient appraisal of crop water budgeting in order to manage water resources efficiently. This study aims to use the satellite remote sensing techniques to determine the water deficit in the crop rich Lower Bari Doab Canal (LBDC) command area. Crop classification was performed using multi-temporal NDVI profiles of Landsat-8 imagery by distinguishing the crop cycles based on reflectance curves. The reflectance-based crop coefficients (Kc) were derived by linear regression between normalized difference vegetation index (NDVI) cycles of the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 and MYD13Q1 products and Food and Agriculture Organization (FAO) defined crop coefficients. A MODIS 250 m NDVI product of the last 10 years (2004-2013) was used to identify the best performing crop cycle using Fourier filter method. The meteorological parameters including rainfall and temperature substantiated the reference evapotranspiration (ET0) calculated using the Hargreaves method. The difference of potential ET and actual ET, derived from the reflectance-based Kc calculated using reference NDVI and current NDVI, generates the water deficit. Results depict the strong correlation between ET, temperature and rainfall, as the regions having maximum temperature resulted in high ET and low rainfall and vice versa. The derived Kc values were observed to be accurate when compared with the crop calendar. Results revealed maximum water deficit at middle stage of the crops, which were observed to be particularly higher at the tail of the canal command. Moreover, results also depicted that kharif (summer) crops suffer higher deficit in comparison to rabi (winter) crops due to higher ET demand caused by higher temperature. Results of the research can be utilized for rational allocation of canal supplies and guiding farmers towards usage of alternate sources to avoid crop water stress.

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Hybrid Methodology for the Estimation of Crop Coefficients Based on Satellite Imagery and Ground-Based Measurements

Water ◽

10.3390/w11071364 ◽

2019 ◽

Vol 11 (7) ◽

pp. 1364 ◽

Cited By ~ 1

Author(s):

Spiliotopoulos ◽

Loukas

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Meteorological Data ◽

Linear Regression Analysis ◽

Atmospheric Correction ◽

Crop Coefficient ◽

Experimental Period ◽

Spectral Measurements ◽

Image File ◽

Crop Coefficients

The objective of the current study was the investigation of specific relationships between crop coefficients and vegetation indices (VI) computed at the water-limited environment of Lake Karla Watershed, Thessaly, in central Greece. A Mapping ET (evapotranspiration) at high Resolution and with Internalized Calibration (METRIC) model was used to derive crop coefficient values during the growing season of 2012. The proposed methodology was developed using medium resolution Landsat 7 ETM+ images and meteorological data from a local weather station. Cotton, sugar beets, and corn fields were utilized. During the same period, spectral signatures were obtained for each crop using the field spectroradiometer GER1500 (Spectra Vista Corporation, NY, U.S.A.). Relative spectral responses (RSR) were used for the filtering of the specific reflectance values giving the opportunity to match the spectral measurements with Landsat ETM+ bands. Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Enhanced Vegetation Index 2 (EVI2) were then computed, and empirical relationships were derived using linear regression analysis. NDVI, SAVI, and EVI2 were tested separately for each crop. The resulting equations explained those relationships with a very high R2 value (>0.86). These relationships have been validated against independent data. Validation using a new image file after the experimental period gives promising results, since the modeled image file is similar in appearance to the initial one, especially when a crop mask is applied. The CROPWAT model supports those results when using the new crop coefficients to estimate the related crop water requirements. The main benefit of the new approach is that the derived relationships are better adjusted to the crops. The described approach is also less time-consuming because there is no need for atmospheric correction when working with ground spectral measurements.

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Monitoring Phenology in the Temperate Grasslands of China from 1982 to 2015 and Its Relation to Net Primary Productivity

Sustainability ◽

10.3390/su12010012 ◽

2019 ◽

Vol 12 (1) ◽

pp. 12

Author(s):

Chaobin Zhang ◽

Ying Zhang ◽

Zhaoqi Wang ◽

Jianlong Li ◽

Inakwu Odeh

Keyword(s):

Primary Productivity ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Net Primary Productivity ◽

Meteorological Data ◽

Temperate Grasslands ◽

The North ◽

Phenological Changes ◽

Grass Growth ◽

Global Inventory

Both vegetation phenology and net primary productivity (NPP) are crucial topics under the background of global change, but the relationships between them are far from clear. In this study, we quantified the spatial-temporal vegetation start (SOS), end (EOS), and length (LOS) of the growing season and NPP for the temperate grasslands of China based on a 34-year time-series (1982–2015) normalized difference vegetation index (NDVI) derived from global inventory modeling and mapping studies (GIMMS) and meteorological data. Then, we demonstrated the relationships between NPP and phenology dynamics. The results showed that more than half of the grasslands experienced significant changes in their phenology and NPP. The rates of their changes exhibited spatial heterogeneity, but their phenological changes could be roughly divided into three different clustered trend regions, while NPP presented a polarized pattern that increased in the south and decreased in the north. Different trend zones’ analyses revealed that phenology trends accelerated after 1997, which was a turning point. Prolonged LOS did not necessarily increase the current year’s NPP. SOS correlated with the NPP most closely during the same year compared to EOS and LOS. Delayed SOS contributed to increasing the summer NPP, and vice versa. Thus, SOS could be a predictor for current year grass growth. In view of this result, we suggest that future studies should further explore the mechanisms of SOS and plant growth.

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Multispectral Image-Based Estimation of Drought Patterns and Intensity around Lake Chad, Africa

Remote Sensing ◽

10.3390/rs11212534 ◽

2019 ◽

Vol 11 (21) ◽

pp. 2534 ◽

Cited By ~ 7

Author(s):

Willibroad Gabila Buma ◽

Sang-Il Lee

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Meteorological Data ◽

Condition Index ◽

Drought Monitoring ◽

World Population ◽

Lake Chad ◽

In Situ Data

As the world population keeps increasing and cultivating more land, the extraction of vegetation conditions using remote sensing is important for monitoring land changes in areas with limited ground observations. Water supply in wetlands directly affects plant growth and biodiversity, which makes monitoring drought an important aspect in such areas. Vegetation Temperature Condition Index (VTCI) which depends on thermal stress and vegetation state, is widely used as an indicator for drought monitoring using satellite data. In this study, using clear-sky Landsat multispectral images, VTCI was derived from Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). Derived VTCI was used to observe the drought patterns of the wetlands in Lake Chad between 1999 and 2018. The proportion of vegetation from WorldView-3 images was later introduced to evaluate the methods used. With an overall accuracy exceeding 90% and a kappa coefficient greater than 0.8, these methods accurately acquired vegetation training samples and adaptive thresholds, allowing for accurate estimations of the spatially distributed VTCI. The results obtained present a coherent spatial distribution of VTCI values estimated using LST and NDVI. Most areas during the study period experienced mild drought conditions, though severe cases were often seen around the northern part of the lake. With limited in-situ data in this area, this study presents how VTCI estimations can be developed for drought monitoring using satellite observations. This further shows the usefulness of remote sensing to improve the information about areas that are difficult to access or with poor availability of conventional meteorological data.

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Vegetation Resilience under Increasing Drought Conditions in Northern Tanzania

Remote Sensing ◽

10.3390/rs13224592 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4592

Author(s):

Steye L. Verhoeve ◽

Tamara Keijzer ◽

Rehema Kaitila ◽

Juma Wickama ◽

Geert Sterk

Keyword(s):

Vegetation Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Potential Evapotranspiration ◽

Meteorological Data ◽

Monthly Precipitation ◽

Quick Recovery ◽

Northern Tanzania ◽

Derived Data ◽

Drought Occurrence

East Africa is comprised of many semi-arid lands that are characterized by insufficient rainfall and the frequent occurrence of droughts. Drought, overgrazing and other impacts due to human activity may cause a decline in vegetation cover, which may result in land degradation. This study aimed to assess drought occurrence, vegetation cover changes and vegetation resilience in the Monduli and Longido districts in northern Tanzania. Satellite-derived data of rainfall, temperature and vegetation cover were used. Monthly precipitation (CenTrends v1.0 extended with CHIRPS2.0) and monthly mean temperatures (CRU TS4.03) were collected for the period of 1940–2020. Eight-day maximum value composite data of the normalized difference vegetation index (NDVI) (NOAA CDR—AVHRR) were obtained for the period of 1981–2020. Based on the meteorological data, trends in rainfall, temperature and drought were determined. The NDVI data were used to determine changes in vegetation cover and vegetation resilience related to the occurrence of drought. Rainfall did not significantly change over the period of 1940–2020, but mean monthly temperatures increased by 1.06 °C. The higher temperatures resulted in more frequent and prolonged droughts due to higher potential evapotranspiration rates. Vegetation cover declined by 9.7% between 1981 and 2020, which is lower than reported in several other studies, and most likely caused by the enhanced droughts. Vegetation resilience on the other hand is still high, meaning that a dry season or year resulted in lower vegetation cover, but a quick recovery was observed during the next normal or above-normal rainy season. It is concluded that despite the overall decline in vegetation cover, the changes have not been as dramatic as earlier reported, and that vegetation resilience is good in the study area. However, climate change predictions for the area suggest the occurrence of more droughts, which might lead to further vegetation cover decline and possibly a shift in vegetation species to more drought-prone species.

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