The Application of Remote Sensing in Vegetation Cover, Sudan | Chapter 8 | Cutting Edge Research in Biology Vol. 5

 This paper wanted to review several studies on the use of detached sensing in Sudan accompanying a focus on plants cover in various domains by many scholars; the unification of remote thinking in the gum Arabic belt; pertaining to the south Gadarif region; ahable and chunk grabou area, silver Nile state with a devote effort to something the amount and mapping of land use land cover change through plan and monitoring the changes that happen in land use land cover, due to dryness, climate change, and transgression; east of the Nile Khartoum State, and in the middle during a half-of one hundred years. Following are recommendations came from these studies: the use of assessment signs including NDVI, SAVI, and PCA –maneuvered in color composite and/or unsupervised categorization can be secondhand as an appropriate mean for rangeland monitoring and amount which was urged from the study of North Kordofan state.

Author(s) Details:

Eisa M. Ahmed,
Department of Crop Protection, Faculty of Natural Resources and Environmental Studies, University of Kordofan, P.O Box 160 –Elobeid, 51111, Sudan.

El Gunaid F. Hassan,
Department of Forestry and Range Sciences, University of Bakht Er-Ruda, Ad Duwem, Sudan.

Please see the link here: https://stm.bookpi.org/CERB-V5/article/view/9853

Active Learning in Deep Bayesian Framework for Detecting Changes in Urban/Suburban Satellite Image Targets of High-resolution | Chapter 4 | Research Developments in Science and Technology Vol. 10

 

The issue of change detection in high-resolution (HR) satellite pictures is addressed in this work. Bayesian active learning disagreement (BALD), an active learning (AL) technique, is used to World view photos of the Greek island of Crete that show urban and suburban regions. The BALD acquisition function may be used while thinking about the classification job because it is based on Bayesian uncertainty. The pool data points that should be selected, according to the BALD principle, are those that are anticipated to maximise the knowledge gathered about the model parameters. In reality, the model shows that the data points that maximise the BALD acquisition function are typically unclear. Importantly, each stochastic forward run over the model would provide the greatest probability assigned to a certain class. In the experiments, results from random sampling (RS) on AL are compared. Investigated are several situations for selecting different numbers of pictures from the training set of a convolutional neural network (CNN). The validation accuracy of the BALD algorithm's categorization of data as altered or unchanged is superior to that of the RS algorithm, the results show. In fact, the BALD method achieves zero test error compared to the RS algorithm's test errors of 34.6 percent and 38.5 percent. In actuality, as the quantity of training photos grows, so does the accuracy. In further work, intriguing experiments might be carried out inside the AL acquisition function architecture using estimators from robust statistics. Up till now, no other literature research proving the application of

Author(s) Details:

Lemonia Ragia,
Information Management Systems Institute, Athena Research Center, Artemidos 6, Marousi 151 25, Greece.

Antigoni Panagiotopoulou,
Information Management Systems Institute, Athena Research Center, Artemidos 6, Marousi 151 25, Greece.

Please see the link here: https://stm.bookpi.org/RDST-V10/article/view/7717

Forest Cover and Ecosystem Service Change: Assessing Household Economic Vulnerability to Drought Shocks in the Central Districts of Uganda | Chapter 4 | International Research in Environment, Geography and Earth Science Vol. 5

 

In Uganda, natural forests have undergone both spatial and temporal changes from various drivers, which need to be controlled in order to determine the effect on habitats of such changes and to avoid the associated risks of reducing the benefits of ecosystem services. Due to dual ownership, ground research can be complicated, although remote sensing techniques and GIS application allow rapid multi-temporal detection of changes in forest cover and provide a cost-effective alternative for inaccessible areas and their use to detect changes in ecosystem service. The overall objective of this study was to use satellite measurements to study forest change and relate it to reducing the value of ecosystem services (fresh water) in the study area using a representative Landsat scene sample, Using soil moisture content time series satellite data, the effect of forest cover loss on drought prevalence is also assessed. In addition to evaluating the economic vulnerability of households to drought in rural Uganda 's central districts, In this paper, together with post-classification comparison, an integrated approach of remotely derived indices was used to detect forest cover and ecosystem service transition. In addition , the analysis used soil moisture content data from the satellite time series to determine drought prevalence and household susceptibility to drought shocks. Our new contribution is the ability to detect a decrease in private and central reserve forest cover on a multi-temporal scale along with ecosystem coverage. Reduction of profit in the 20-year period (1986-2005) using remotely derived indices. Analysis of change detection showed that in five sub-counties of Mpigi, forest cover decreased significantly than in Butambala by 5.99 percent, disturbed forest was 3 percent, farm land increased by 44 percent, grassland decreased by 62.5 percent and light vegetation increased by 63.6 percent. The two areas most impacted have suffered decreases in fresh water. The two SPI and SWDI drought indices confirmed the presence of drought shocks that have triggered household vulnerability to food insecurity and welfare instability. Resource managers , especially natural forests, must also include private resource owners in the conservation effort in order to ensure a sustainable supply of ecosystem service benefits and preservation of standard welfare.


Author (s) Details

Ausi A. Ssentongo
Department of Geography, Geoinformatics and Meteorology, Centre for Environmental Studies, University of Pretoria, Pretoria 0002, South Africa.

Daniel Darkey
Department of Geography, Geoinformatics and Meteorology, Centre for Environmental Studies, University of Pretoria, Pretoria 0002, South Africa.

Joseph Mutyaba
National Forestry Authority, 10/20 Spring Road, P.O. Box 70863 Bugolobi, Kampala, Uganda.

View Book :- https://bp.bookpi.org/index.php/bpi/catalog/book/279

Land Cover Dynamics in Tanzania Part of Kagera River Basin: A Strategy for Sustainability of Lake Victoria | Chapter 6 | International Research in Environment, Geography and Earth Science Vol. 1

This study is reporting on an investigation done to assess land cover dynamics in Tanzania part of Kagera River Basin (KRB) over a period of 21 years i.e.1990-2011 using Remote Sensing, Hydrology and GIS as a basis for initiating policy interventions for sustainability of Lake Victoria ecosystem. Hitherto, the extent of land cover changes in the KRB have not been quantified with the view of assessing the extent of exploitation of the natural resources in the area and its subsequent impact on the trans-boundary Lake Victoria water resource. The assessment is important firstly, for identification of causative factors and secondly, as a mechanism for formulating necessary interventions to that effect. Specifically, Landsat 5, Landsat 7 and ETM+ (2000) satellite images were used. Eight Land Cover classes were identified namely, Forests, Woodland, Bush land, Cultivated Land, Swamps, Grassland, Bare land and Urban areas. Hydrographical data were used to assess changes in quantity of water flowing from the KRB into Lake Victoria and relating it with land cover dynamics in KRB at in the period of study. Spatial data processing, analysis and interpretation were carried out in ERDAS Imagine and ArcGIS software environments; while water quantity data and other non-spatial data were processed and analyzed in Microsoft Excel application 2007.  The study revealed a significant decline of vegetation cover and water quantity discharged from Kagera River to Lake Victoria over the study period. This contravenes the Global efforts of ecological sustainability, urging avoidance of depletion of natural resources for maintenance for ecological balance. These results are early warning to the Management of Lake Victoria of its potential failure towards achievement the Millennium Development Goal on responsible consumption and protection of natural resources in proximity of Lake Victoria. The Management of Lake Victoria in collaboration with other relevant authorities should thus, initiate remedial measures to control none strategic use of vegetation cover in KRB for sustainability of Lake Victoria and its ecosystem.

Author (s) Details

Martine Hagai
Department of Geospatial Sciences and Technology, School of Earth Sciences, Real Estate, Business and Informatics, Ardhi University, P.O. Box 35176, Dar es Salaam, Tanzania.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/169