scholarly journals Coping with Drought among the Communities Living in the Lake Victoria Basin of Kenya

2012 ◽  
Vol 3 (10) ◽  
pp. 342-349 ◽  
Author(s):  
J. K. Chumo
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Lake Victoria ◽  
Geographical Information ◽  
Food Storage ◽  
Lake Victoria Basin ◽  
Crop Failure ◽  
Prone Area ◽  
Gis Software ◽  
Year 2000

Drought is of great concern throughout the continent of Africa because of its devastating effects that it has inflicted on the economy of some of the countries. Drought has been recorded to be one of the most felt disasters in recent years in Kenya. The drought that affected Kenya in the year 2000 and 2010 was indeed remarkable in that the country resorted to loss of lives, loss of livestock, power rationing and drying of agricultural crops among other problems. This study developed a technique to depict spatially, the extent, relative severity and location of areas mostly affected by drought in the Lake Victoria basin of Kenya. This was done using the normalized difference vegetation index (NDVI) plots and maps developed using the Geographical Information System (GIS) software. The indices were generated using the C++ program. NDVI indices revealed that most parts of the basin were moderately dry throughout the year. The study investigated the impacts of drought in the area by use of questionnaires and interviews. The impacts identified were mainly crop failure, depletion of water resources and lack of pasture for livestock. The complex and multidimensional nature of drought requires a long term, well-organized and coordinated research plan and action involving all the stakeholders. This study summarized coping strategies adopted by the communities living within the Lake Victoria basin to mitigate drought phenomenon. Some of the strategies include; planting of drought resistant crops, food storage sharing and purchasing of food among others. Recommendations have been suggested for policy makers, planners and agriculturalists to implement to improve agricultural output in a drought prone area like the Lake Victoria Basin of Kenya. In particular, the study highly recommends development of a comprehensive drought policy to be implemented in managing drought in Kenya.

scholarly journals Estimation of Biomass Availability in Panglao Island Using SENTINEL-2 MSI

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
W.N. Galang ◽  
I.D.F. Tabañag ◽  
M.E. Loretero
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Geographical Information ◽  
Land Resources ◽  
Energy Potential ◽  
Available Energy ◽  
Residue Concentration ◽  
Biomass Availability ◽  
Gis Software ◽  
Sentinel 2

Remote Sensing (RS) technology using SENTINEL-2 Multispectral Instrument (MSI) imagery was used in the estimation of residual biomass’ available energy potential. The estimation was done in Panglao Island, within the province of Bohol, Philippines. Estimation of biomass availability was processed using Geographical Information System (GIS) software incorporating the calculation of Normalized Difference Vegetation Index (NDVI) to extract information on land resources and its spatial distribution. It was found that the majority of vegetation cover on the island is in the form of perennial woody plants and coconut trees. Coconut production on the island of Panglao contributed 1.26% of the total cultivation area for the province based on processed captures of Sentinel-2 imagery. The residue concentration amounted to 2,865 tons of coconut residues based on the RPR method. This amount of residues can be translated to 52.92 TJ of theoretical energy potential. The result of this study may serve as a baseline for the locality to consider the utilization of agricultural residues such as coming from coconut trees to support the use of indigenous resources for energy generation.

scholarly journals Soil use and occupation in Caracol Settlement: a multitemporal assessment using remote sensing and geoprocessing techniques

2020 ◽  
Vol 9 (12) ◽  
pp. e30891211029
Author(s):  
Odemir Coelho da Costa ◽  
José Francisco dos Reis Neto ◽  
Ana Paula Garcia Oliveira
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Soil Cover ◽  
The United States ◽  
United States Geological Survey ◽  
Vegetation Landscape ◽  
Digital Elevation ◽  
Elevation Model ◽  
Gis Software

This study focused on the application of remote sensing and geoprocessing techniques to quantify the agroecological use of Caracol settlement area in order to quantify the vegetated areas, as well as the use and occupation of the soil in the years 2000, 2010 and 2020, in the months of May of each year. To achieve the objectives, computational tools (Quantum GIS software) were used, as well as data from Landsat 5 and 8 satellites, bands 3 and 4, 4 and 5 respectively. Vector data from the database of the Brazilian Institute of Geography and Statistics (IBGE), a Digital Elevation Model (DEM), from the United States Geological Survey (USGS/NASA) for evaluation of the watersheds were also used. For vegetation analysis, as well as temporal evolution, the Normalized Difference Vegetation Index (NDVI) was used, with this it was possible to evaluate by means of thematic maps and tables containing the quantification and classification of vegetation and soil cover. It was evident in the present study that there were significant changes in the vegetation landscape over two decades, through anthropic activity by settled families, that were responsible for such changes in the use and soil cover of Caracol settlement.

scholarly journals Land use and Land cover Mapping Based on Normalized Difference Vegetation Index using Remote Sensing and Geographical Information System in Banjar River Watershed of Narmada Basin

2017 ◽  
Vol 12 (3) ◽  
pp. 678-684
Author(s):  
Jagriti Tiwari ◽  
S.K. Sharma ◽  
R.J. Patil
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Information System ◽  
Land Cover ◽  
Geographical Information System ◽  
Water Body ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Geographical Information ◽  
River Watershed

The spatial analysis of land use and land cover (LULC) dynamics is necessary for sustainable utilization and management of the land resources of an area. Remote sensing along with Geographical Information System emerged as an effective technique for mapping the LU/LC categories of an area in an efficient and cost-effective manner. The present study was conducted in Banjar river watershed located in Balaghat and Mandla district of Madhya Pradesh, India. The Normalized Difference Vegetation Index (NDVI) approach was adopted for LU/LC classification of study area. The Landsat-8 satellite data of year 2013 was selected for the classification purpose. The NDVI values were generated in ERDAS Imagine 2011 software and LU/LC map was prepared in ARC GIS environment. On the basis of NDVI values five LU/LC classes were recognized in the study area namely river & water body, waste land & habitation, forest, agriculture/other vegetation, open land/fallow land/barren land. The forest cover was found to be highly distributed in the study area with an extent of 115811 ha and least area was found to be covered under river and water body (4057.28 ha). This research work will be helpful for the policy makers for proper formulation and implementation of watershed developmental plans.

Developing City-Wide Hurricane Impact Maps using Real-Life Data on Infrastructure, Vegetation and Weather

2020 ◽  
pp. 036119812097271
Author(s):  
Mingyang Chen ◽  
Alican Karaer ◽  
Eren Erman Ozguven ◽  
Tarek Abichou ◽  
Reza Arghandeh ◽  
...  
Keyword(s):  
Geographical Information Systems ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Real Life ◽  
Google Earth ◽  
Geographical Information ◽  
Data Sets ◽  
Hurricane Impact ◽  
The City

Hurricanes affect thousands of people annually, with devastating consequences such as loss of life, vegetation and infrastructure. Vegetation losses such as downed trees and infrastructure disruptions such as toppled power lines often lead to roadway closures. These disruptions can be life threatening for the victims. Emergency officials, therefore, have been trying to find ways to alleviate such problems by identifying those locations that pose high risk in the aftermath of hurricanes. This paper proposes an integrated methodology that utilizes both Google Earth Engine (GEE) and geographical information systems (GIS). First, GEE is used to access Sentinel-2 satellite images and calculate the Normalized Difference Vegetation Index (NDVI) to investigate the vegetation change as a result of Hurricane Michael in the City of Tallahassee. Second, through the use of ArcGIS, data on wind speed, debris, roadway density and demographics are incorporated into the methodology in addition to the NDVI indices to assess the overall impact of the hurricane. As a result, city-wide hurricane impact maps are created using weighted indices created based on all these data sets. Findings indicate that the northeast side of the city was the worst affected because of the hurricane. This is a region where more seniors live, and such disruptions can lead to dramatic consequences because of the fragility of these seniors. Officials can pinpoint the identified critical locations for future improvements such as roadway geometry modification and landscaping justification.

scholarly journals Digital aerial images land cover classification based on vegetation indices

2012 ◽  
Vol 31 (3) ◽  
pp. 5-23
Author(s):  
Maciej Dzieszko ◽  
Piotr Dzieszko ◽  
Sławomir Królewicz
Keyword(s):  
Land Cover ◽  
Image Classification ◽  
Geographical Information Systems ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Vegetation Indices ◽  
Aerial Images ◽  
Geographical Information ◽  
Wide Availability

Abstract . Knowledge of how land cover has changed over time improve assessments of the changes in the future. Wide availability of remote sensed data and relatively low cost of their acquisition make them very attractive data source for Geographical Information Systems (GIS). The main goal of this paper is to prepare, run and evaluate image classification using a block of raw aerial images obtained from Digital Mapping Camera (DMC). Classification was preceded by preparation of raw images. It contained geometric and radiometric correction of every image in block. Initial images processing lead to compensate their brightness differences. It was obtained by calculating two vegetation indices: Normalized Difference Vegetation Index (NDVI) and Green Normalized Vegetation Index (gNDVI). These vegetation indices were the foundation of image classification. PCI Geomatics Geomatica 10.2 and Microimages TNT Mips software platforms were used for this purpose.

scholarly journals SPATIAL TEMPORAL MAPPING OF SPREAD OF WATER HYACINTH IN WINUM GULF, LAKE VICTORIA

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 341-346
Author(s):  
S. O. Nyawacha ◽  
V. Meta ◽  
A. Osio
Keyword(s):  
Water Hyacinth ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Lake Victoria ◽  
Anthropogenic Activities ◽  
Research Question ◽  
Suspended Sediments ◽  
Predictive Modelling ◽  
Vegetation Growth ◽  
Sensing Applications

Abstract. Water hyacinth (Eichhornia crassipes) is an invasive hydro plant that invaded the waters of Lake Victoria and has since been spreading rapidly affecting the socio-economic livelihood of the community around the Lake. The weed's rapid spread is due to various anthropogenic activities in the surrounding environment among them being the eutrophication of the lake waters.This study aims at using remote sensing applications and presenting the results of the analysis of the water hyacinth Normalized Difference Vegetation Index (NDVI), water extent, and analysis of correlation with the water quality over time from Sentinel 2 satellite imagery in January 2017 to January of 2021. The analysis aims at understanding the vegetation growth coverage in the five years and sets the basis of monthly predictive modelling of the behavior of water hyacinth. Predictive modelling applies historical statistical data while trying to use trend analysis in predicting the future behavior of a phenomenon. This study also seeks to answer the research question of the role of suspended sediments and dissolved minerals in abating the spread of and growth of water hyacinth.

scholarly journals Potential Water Harvesting Sites Identification Using Spatial Multi-Criteria Evaluation in Maysan Province, Iraq

2020 ◽  
Vol 9 (4) ◽  
pp. 235
Author(s):  
Imzahim A. Alwan ◽  
Nadia A. Aziz ◽  
Mustafa N. Hamoodi
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainwater Harvesting ◽  
Supply And Demand ◽  
Geographical Information ◽  
Water Harvesting ◽  
Climate Conditions ◽  
Promising Tool ◽  
Multi Criteria Evaluation ◽  
Semi Arid Region

Rainwater harvesting is a promising tool for supplementing surface water and groundwater to overcome the imbalance between water supply and demand under changing climate conditions. Multi-Criteria Evaluation is one of the well-known methods of decision-making. In this study, the geographical information system (GIS)-based Multi-Criteria Evaluation is used to select the optimum rainwater harvesting sites in Maysan province, Iraq. Fuzzy membership is used for standardization of the criteria, and Fuzzy Gamma overlay for a combination of multi-layers using ArcGIS 10.5. Seven criteria layers, including slope, stream order, soil type, precipitation, evaporation, roads, and the Normalized Difference Vegetation Index (NDVI) are derived to identify rainwater-harvesting catchment. The results determined the optimum sites for water storage within the study area. The resultant potential rainwater harvesting catchment map can be used as a reference to enhance the effectiveness of water management, especially in drought-stricken areas that offer significant potential for sustainable agricultural production in the semi-arid region.

scholarly journals APPLICATION OF REMOTE SENSING AND GIS FOR ASSESSING LAND COVER RESOURCES VARIABILITY IN THE SELOUS GAME RESERVE, TANZANIA

2017 ◽  
Vol 1 (2) ◽  
pp. 74
Author(s):  
Phillip W. Mambo ◽  
John E. Makunga
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing And Gis ◽  
Vegetation Density ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Game Reserve ◽  
Year 2000

Purpose: The study was conducted in Selous Game Reserve, with intention of developing GIS and Remote Sensing based wildlife management system in the protected area.Methodology: All habitats were digitised using ArcGIS9.3 in which five scenes of Landsat TM and ETM+ digital images were acquired during dry seasons of the year 2000 and 2010. Band 3 and 4 of the Landsat images were used for calculation of normalized difference vegetation index (NDVI) for determination of vegetation spatial distributionResults: The NDVI maps of year 2000 to 2010 revealed the vegetation density depletion from 0.72 (obtained in 0.46─0.72 value interval and covering 46.5% pixel area) in 2000 as compared to 0.56 ( found in 0.38─0.56 value interval and covering 8.04% pixel area) in 2010 NDVI maps.Unique contribution to theory, practice and policy: It was recommended that there was a necessity to integrate applications of remote sensing and GIS techniques for the assessment and monitoring of the natural land cover variability to detect fragmentation and loss of wildlife species.

scholarly journals Groundwater Site Prediction Using Remote Sensing, GIS and Statistical Approaches: A Case Study in the Western Desert, Iraq

2018 ◽  
Vol 7 (4.20) ◽  
pp. 166 ◽  
Author(s):  
Fadhil M. Shnewer ◽  
Alauldeen A. Hasan ◽  
Mudhaffar S. AL-Zuhairy
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spatial Relationship ◽  
Groundwater Potential ◽  
Western Desert ◽  
Geographical Information ◽  
Success Rates ◽  
Topographic Wetness Index ◽  
Conditioning Factors

Combination of remote sensing data and geographical information system (GIS) for the investigation of groundwater has become an advance approach in the researches of groundwater. The purpose of this research is to apply statistical models such as Evidential Belief Function (EBF) and Logistic Regression (LR) for mapping groundwater potential sites at Iraqi western desert (located at Al-Ramadi and Shithatha). The potential of the groundwater areas were determined depending on the spatial relationship between groundwater wells and different conditioning factors. These factors include altitude, curvature, aspect, slope, soil, normalized difference vegetation index (NDVI), topographic wetness index, fault, rainfall, stream density, stream power index, and lithology. The algorithms were used to model all layers of groundwater conditioning factors to generate groundwater probability areas. Then, the final maps included five potential classes i.e., very high, high, moderate, low and very low susceptible zones were generated. The final outcomes were validated using Area Under the Curve (AUC) algorithm. The values of success rates were 76.5% and 71.5% for EBF an LR respectively. The prediction rates for the same methods were 73.7% and 70%, respectively.  The thematic maps attained from the present study indicated the capability of EBF and LR methods in groundwater potential mapping.  

scholarly journals Spatiotemporal Changes of Vegetation in the Middle Draa Valley Oasis: A Study Case of M’hamid El Ghizlane Oasis (Morocco)

2017 ◽  
Vol 13 (24) ◽  
pp. 115 ◽  
Author(s):  
Atman Ait Lamqadem ◽  
Hafid Saber ◽  
Abdelmejid Rahimi
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Conditions ◽  
Geographical Information ◽  
Visual Interpretation ◽  
Landsat Images ◽  
Mass Tourism ◽  
Spatiotemporal Changes ◽  
Data Survey ◽  
Oasis Area

During the last decades, The Middle Draa Valley (Southeast of Morocco) was subjected to various environmental problems which haves caused land degradation especially in the south of the Middle Draa (M’hamid oasis). This study aims to analyze the spatiotemporal changes of vegetation in the M’hamid oasis. Based on the Landsat images belonging to six separate periods during 1984 to 2016 and Geographical Information System (GIS) techniques, the pattern of spatiotemporal changes of vegetation cover in M’hamid oasis was analyzed based to visual interpretation and NDVI (Normalized Difference Vegetation Index) and supervised classified. For easier understanding of the causes and origins of these changes, we exploited statistical data survey from various local administrations (climatological, socio-economic data) and fieldworks. The results show that the total area of the oasis showed an oscillating decrease between 1984-1999 compared to 1999-2013 and a sharp increase after 2003 to 2007 and a moderate decrease from 2003 to 2016, with an area 3 times smaller than the initial date (loss of 22% of oasis area), correlated with a reduction of the habitants (loss of 21% between 1980 and 2016). Mass tourism, construction of the Mansour Eddahbi dam and the irregularities of the rains and the succession of years of drought led to a modification of the oasis ecosystem. Due to these climatic conditions, the oasis population are obliged to emigration thus they leave their fields which are threatened by sand encroachments, therefore accelerating the phenomenon of sand movements and consequently desertification.

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