An Integrated Field Data and Remote Sensing Approach for impact assessment of human activities on epifauna macro‐benthos biodiversity along Western coast of Aqaba Gulf

Ecohydrology ◽  
2021 ◽  
Author(s):  
Hussein A. El‐Naggar ◽  
El‐Sayed S. Salem ◽  
Sameh B. El‐Kafrawy ◽  
Mansour A. Bashar ◽  
Walaa M. Shaban ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Impact Assessment ◽  
Human Activities ◽  
Field Data ◽  
Western Coast ◽  
Macro Benthos

scholarly journals An Integrated Field Data and Remote Sensing Approach for Impact Assessment of Human Activities on Macro-benthos Biodiversity Along Western Coast of Aqaba Gulf

2021 ◽  
Author(s):  
Hussein A. El-Naggar ◽  
El-Sayed S. Salem ◽  
Sameh B. El-Kafrawy ◽  
Mansour A. Bashar ◽  
Mohamed Ashour ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Human Activities ◽  
Marine Ecosystems ◽  
Gulf Of Aqaba ◽  
Western Coast ◽  
Marine Habitats ◽  
Abundance And Diversity ◽  
Macro Benthos ◽  
Egyptian Coast

Abstract The Egyptian coast of Aqaba Gulf, north of the Red Sea suffers from severe destruction and deterioration in habitat and biodiversity due to anthropogenic activities and flooding. The present work aims to evaluate the impacts of different human activities and flooding on the biodiversity of macro-benthos invertebrates along the Egyptian coast of the Aqaba Gulf. From January 2019 to December 2019, many field trips (12 trips) were conducted to survey macro-benthos-invertebrate communities and monitor water quality at nine sites within three sectors along the study area. Each site was divided into four ecological zones and one of five categories, according to the main activities at each site. Furthermore, satellite data were used to monitor the progress of land use, and turbidity in the study area. Therefore, the current study assessing the relationship between these factors and water quality and macro-benthos-invertebrates distributions, similarity, diversity, dominance and abundance. The results revealed that fifty-three macro-benthos-invertebrates species belonging to four phyla (Crustacea, Mollusca, Echinodermata and Annelida) were recorded. Echinometra mathaei was the major eudominant species. The northern part of the Gulf was higher abundance and diversity with low land use and lowest water turbidity, while the south part showed the contrary findings. All statics analysis confirmed that the dissolved oxygen concentration was considered the only limiting factor for the abundance and diversity of macro-benthos invertebrates. Also, the variation in activities at investigated sites affected the dominance state of species in each site. Moreover, GPS data confirmed that the tourism activity had the largest influence on marine ecosystems and biodiversity, followed by fishing and desalination practices. Otherwise, flooding has significant influence on marine habitats and creates a habitat in which other certain species can be survived. In the absence of awareness, intervention and disregard for the effective coastal zone management concept, especially for the unique marine ecosystems such as the Gulf of Aqaba, the degradation of biodiversity will continue until extinction, and human life is rendered unsustainable.

Measuring stream habitat conditions: Can remote sensing substitute for field data?

2021 ◽  
pp. 147617
Author(s):  
Karina Dias-Silva ◽  
Thiago Bernardi Vieira ◽  
Talissa Pio de Matos ◽  
Leandro Juen ◽  
Juliana Simião-Ferreira ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Field Data ◽  
Stream Habitat ◽  
Habitat Conditions

Use of geographic information systems and remote sensing as automated tool for variable rate irrigation prescriptions

2019 ◽  
Author(s):  
◽  
Anh Thi Tuan Nguyen
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Regression Models ◽  
Field Data ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Crop Growth ◽  
Variable Rate ◽  
Water Application ◽  
Center Pivot

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Economic as well as water shortage pressure on agricultural use of water has placed added emphasis on efficient irrigation management. Center pivot technology has made great improvement with variable rate irrigation (VRI) technology to vary water application spatially and temporally to maximize the economic and environmental return. Proper management of VRI systems depends on correctly matching the pivot application to specific field temporal and areal conditions. There is need for a tool to accurately and inexpensively define dynamic management zones, to sense within-field variability in real time, and control variable rate water application so that producers are more willing to adopt and utilize the advantages of VRI systems. This study included tests of the center pivot system uniformity performance in 2014 at Delta Research Center in Portageville, MO. The goal of this research was to develop MOPivot software with an algorithm to determine unique management areas under center pivot systems based on system design and limitations. The MOPivot tool automates prescriptions for VRI center pivot based on non-uniform water needs while avoiding potential runoff and deep percolation. The software was validated for use in real-time irrigation management in 2018 for VRI control system of a Valley 8000 center pivot planted to corn. The water balance model was used to manage irrigation scheduling. Field data, together with soil moisture sensor measurement of soil water content, were used to develop the regression model of remote sensing-based crop coefficient (Kc). Remote sensing vegetation index in conjunction with GDD and crop growth stages in regression models showed high correlation with Kc. Validation of those regression models was done using Centralia, MO, field data in 2016. The MOPivot successfully created prescriptions to match system capacity of the management zone based on system limitations for center pivot management. Along with GIS data sources, MOPivot effectively provides readily available graphical prescription maps, which can be edited and directly uploaded to a center pivot control panel. The modeled Kc compared well with FAO Kc. By combining GDD and crop growth in the models, these models would account for local weather conditions and stage of crop during growing season as time index in estimating Kc. These models with Fraction of growth (FrG) and cumulative growing degree days (cGDD) had a higher coefficient of efficiency, higher Nash-Sutcliffe coefficient of efficiency and higher Willmott index of agreement. Future work should include improvement in the MOPivot software with different crops and aerial remote sensing imagery to generate dynamic prescriptions during the season to support irrigation scheduling for real-time monitoring of field conditions.

Study on the Wetland Change in Northeast China Based on RS and GIS Technology

2011 ◽  
Vol 356-360 ◽  
pp. 2886-2891
Author(s):  
Han Wen Cui ◽  
Qi Gang Jiang
Keyword(s):  
Remote Sensing ◽  
Current Distribution ◽  
Constructed Wetland ◽  
Human Activities ◽  
Northeast China ◽  
Transition Matrix ◽  
Gis Technology ◽  
Wetland Area ◽  
Rs And Gis ◽  
Data Source

Based on the RS and GIS technology, the remote sensing imageries MSS in 1975, ETM in 2000 and CBERS-2 in 2007 have been used as main data source in this paper. Wetland current distribution, spatiotemporal change principle and transition matrix have been analyzed in order to realize the wetland change situation in Northeast China during the 30 years. The results show that the wetland area in Northeast China, on the whole, is decreased first and then increased. The dramatic change happened in mire and constructed wetland. Mire is decreased first and then increased, but the whole is still decreased. While, constructed wetland is increased continuously. Constructed wetland increased owing to the transition from mire and non-wetland. The level of the transition from mire to constructed wetland is lower. In Northeast China, human activities have a great impact on wetland change than nature factors.

scholarly journals ABOVE GROUND TREES BIOMASS OF LORE LINDU NATIONAL PARK-CENTRAL SULAWESI : A STUDY COMBINING FIELD MEASUREMENT AND REMOTE SENSING

Agromet ◽  
2010 ◽  
Vol 24 (1) ◽  
pp. 33
Author(s):  
Naimatu Solicha ◽  
Tania June ◽  
M. Ardiansyah ◽  
Antonius B. W.
Keyword(s):  
Remote Sensing ◽  
Carbon Stock ◽  
Field Data ◽  
Forest Cover ◽  
Satellite Image ◽  
Forest Biomass ◽  
Allometric Equation ◽  
Natural Forest ◽  
Forest Cover Type ◽  
Cover Type

Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.

scholarly journals Impact Assessment of Human Activities on Runoff and Sediment of Beiluo River in the Yellow River Based on Paired Years of Similar Climate

2016 ◽  
Vol 25 (1) ◽  
pp. 121-135 ◽  
Author(s):  
Yi He ◽  
Fei Wang ◽  
Peng Tian ◽  
Xing-Min Mu ◽  
Peng Gao ◽  
...  
Keyword(s):  
Impact Assessment ◽  
Human Activities ◽  
Yellow River ◽  
The Yellow River
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