scholarly journals Impacts of the Tropical Cyclone Idai in Mozambique: A Multi-Temporal Landsat Satellite Imagery Analysis

2021 ◽  
Vol 13 (2) ◽  
pp. 201
Author(s):  
Alberto Bento Charrua ◽  
Rajchandar Padmanaban ◽  
Pedro Cabral ◽  
Salomão Bandeira ◽  
Maria M. Romeiras
Keyword(s):  
Land Use ◽  
Tropical Cyclone ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Natural Habitats ◽  
Abrupt Decrease ◽  
Barren Land ◽  
Climate Hazards ◽  
Landsat Satellite

The Central Region of Mozambique (Sofala Province) bordering on the active cyclone area of the southwestern Indian Ocean has been particularly affected by climate hazards. The Cyclone Idai, which hit the region in March 2019 with strong winds causing extensive flooding and a massive loss of life, was the strongest recorded tropical cyclone in the Southern Hemisphere. The aim of this study was to use pre- and post-cyclone Idai Landsat satellite images to analyze temporal changes in Land Use and Land Cover (LULC) across the Sofala Province. Specifically, we aimed—(i) to quantify and map the changes in LULC between 2012 and 2019; (ii) to investigate the correlation between the distance to Idai’s trajectory and the degree of vegetation damage, and (iii) to determine the damage caused by Idai on different LULC. We used Landsat 7 and 8 images (with 30 m resolution) taken during the month of April for the 8-year period. The April Average Normalized Difference Vegetation Index (NDVI) over the aforementioned period (2012–2018, pre-cyclone) was compared with the values of April 2019 (post-cyclone). The results showed a decreasing trend of the productivity (NDVI 0.5 to 0.8) and an abrupt decrease after the cyclone. The most devastated land use classes were dense vegetation (decreased by 59%), followed by wetland vegetation (−57%) and shrub land (−56%). The least damaged areas were barren land (−23%), barren vegetation (−27%), and grassland and dambos (−27%). The Northeastern, Central and Southern regions of Sofala were the most devastated areas. The Pearson Correlation Coefficient between the relative vegetation change activity after Idai (NDVI%) and the distance to Idai’s trajectory was 0.95 (R-square 0.91), suggesting a strong positive linear correlation. Our study also indicated that the LULC type (vegetation physiognomy) might have influenced the degree of LULC damage. This study provides new insights for the management and conservation of natural habitats threatened by climate hazards and human factors and might accelerate ongoing recovery processes in the Sofala Province.

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

scholarly journals Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China

2021 ◽  
Vol 13 (7) ◽  
pp. 1230
Author(s):  
Simeng Wang ◽  
Qihang Liu ◽  
Chang Huang
Keyword(s):  
Arid Region ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Time Lag ◽  
Climate Extremes ◽  
Northwest China ◽  
Precipitation Extremes ◽  
Temperature Extremes ◽  
Increasing Trend

Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial evolution of vegetation cover, and its responses to climate extremes in the arid region of northwest China (ARNC). Mann-Kendall test, Anomaly analysis, Pearson correlation analysis, Time lag cross-correlation method, and Least absolute shrinkage and selection operator logistic regression (Lasso) were conducted to quantitatively analyze the response characteristics between Normalized Difference Vegetation Index (NDVI) and climate extremes from 2000 to 2018. The results showed that: (1) The vegetation in the ARNC had a fluctuating upward trend, with vegetation significantly increasing in Xinjiang Tianshan, Altai Mountain, and Tarim Basin, and decreasing in the central inland desert. (2) Temperature extremes showed an increasing trend, with extremely high-temperature events increasing and extremely low-temperature events decreasing. Precipitation extremes events also exhibited a slightly increasing trend. (3) NDVI was overall positively correlated with the climate extremes indices (CEIs), although both positive and negative correlations spatially coexisted. (4) The responses of NDVI and climate extremes showed time lag effects and spatial differences in the growing period. (5) Precipitation extremes were closely related to NDVI than temperature extremes according to Lasso modeling results. This study provides a reference for understanding vegetation variations and their response to climate extremes in arid regions.

scholarly journals Spatio-Temporal Variation Analysis of Landscape Pattern Response to Land Use Change from 1985 to 2015 in Xuzhou City, China

2018 ◽  
Vol 10 (11) ◽  
pp. 4287 ◽  
Author(s):  
Yantao Xi ◽  
Nguyen Thinh ◽  
Cheng Li
Keyword(s):  
Land Use ◽  
Landscape Pattern ◽  
Urban Areas ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Local Level ◽  
Land Use Changes ◽  
Landscape Patterns ◽  
Rapid Urbanization ◽  
Barren Land

Rapid urbanization has dramatically spurred economic development since the 1980s, especially in China, but has had negative impacts on natural resources since it is an irreversible process. Thus, timely monitoring and quantitative analysis of the changes in land use over time and identification of landscape pattern variation related to growth modes in different periods are essential. This study aimed to inspect spatiotemporal characteristics of landscape pattern responses to land use changes in Xuzhou, China durfing the period of 1985–2015. In this context, we propose a new spectral index, called the Normalized Difference Enhanced Urban Index (NDEUI), which combines Nighttime light from the Defense Meteorological Satellite Program/Operational Linescan System with annual maximum Enhanced Vegetation Index to reduce the detection confusion between urban areas and barren land. The NDEUI-assisted random forests algorithm was implemented to obtain the land use/land cover maps of Xuzhou in 1985, 1995, 2005, and 2015, respectively. Four different periods (1985–1995, 1995–2005, 2005–2015, and 1985–2015) were chosen for the change analysis of land use and landscape patterns. The results indicate that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has occurred in a dual-core development mode throughout the urbanization process. We quantified the patch complexity, aggregation, connectivity, and diversity of the landscape, employing a number of landscape metrics to represent the changes in landscape patterns at both the class and landscape levels. The results show that with respect to the four aspects of landscape patterns, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation in landscape patterns was examined based on 900 × 900 m sub-grids. Combined with the land use changes and spatiotemporal variations in landscape patterns, urban growth mainly occurred in a leapfrog mode along both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period of 1995 to 2005, and the edge-expansion and leapfrog modes coexisted in the period from 2005 to 2015. The high value spatiotemporal information generated using remote sensing and geographic information system in this study could assist urban planners and policymakers to better understand urban dynamics and evaluate their spatiotemporal and environmental impacts at the local level to enable sustainable urban planning in the future.

scholarly journals NDVI-Based Vegetation Change in Inner Mongolia from 1982 to 2006 and Its Relationship to Climate at the Biome Scale

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Linghui Guo ◽  
Shaohong Wu ◽  
Dongsheng Zhao ◽  
Yunhe Yin ◽  
Guoyong Leng ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Inner Mongolia ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Potential Evapotranspiration ◽  
Vegetation Type ◽  
Growing Season ◽  
Desert Steppe

Based on the normalized difference vegetation index (NDVI), we analyzed vegetation change of the six major biomes across Inner Mongolia at the growing season and the monthly timescales and estimated their responses to climate change between 1982 and 2006. To reduce disturbance associated with land use change, those pixels affected by land use change from the 1980s to 2000s were excluded. At the growing season scale, the NDVI increased weakly in the natural ecosystems, but strongly in cropland. Interannual variations in the growing season NDVI for forest was positively linked with potential evapotranspiration and temperature, but negatively correlated with precipitation. In contrast, it was positively correlated with precipitation, but negatively related to potential evapotranspiration for other natural biomes, particularly for desert steppe. Although monthly NDVI trends were characterized as heterogeneous, corresponding to monthly variations in climate change among biome types, warming-related NDVI at the beginning of the growing season was the main contributor to the NDVI increase during the growing season for forest, meadow steppe, and typical steppe, but it constrained the NDVI increase for desert steppe, desert, and crop. Significant one-month lagged correlations between monthly NDVI and climate variables were found, but the correlation characteristics varied greatly depending on vegetation type.

scholarly journals Monitoring the variations of evapotranspiration due to land use/cover change in a semiarid shrubland

2017 ◽  
Vol 21 (2) ◽  
pp. 863-877 ◽  
Author(s):  
Tingting Gong ◽  
Huimin Lei ◽  
Dawen Yang ◽  
Yang Jiao ◽  
Hanbo Yang
Keyword(s):  
Land Use ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Hydrological Cycle ◽  
Vegetation Type ◽  
Soil Surface ◽  
Surface Characteristics ◽  
Observation Data ◽  
Semiarid Shrubland

Abstract. Evapotranspiration (ET) is an important process in the hydrological cycle, and vegetation change is a primary factor that affects ET. In this study, we analyzed the annual and inter-annual characteristics of ET using continuous observation data from eddy covariance (EC) measurement over 4 years (1 July 2011 to 30 June 2015) in a semiarid shrubland of Mu Us Sandy Land, China. The Normalized Difference Vegetation Index (NDVI) was demonstrated as the predominant factor that influences the seasonal variations in ET. Additionally, during the land degradation and vegetation rehabilitation processes, ET and normalized ET both increased due to the integrated effects of the changes in vegetation type, topography, and soil surface characteristics. This study could improve our understanding of the effects of land use/cover change on ET in the fragile ecosystem of semiarid regions and provide a scientific reference for the sustainable management of regional land and water resources.

scholarly journals Land cover classification using landsat-8 optical data and supervised classifiers

2018 ◽  
Vol 7 (2.17) ◽  
pp. 101
Author(s):  
K V. Ramana Rao ◽  
Prof P. Rajesh Kumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Classification ◽  
Optical Data ◽  
Landsat 8 ◽  
Barren Land ◽  
Detection Techniques ◽  
Time Periods ◽  
Classification Information ◽  
Landsat Satellite

Land use and land cover information of an area has got importance in various aspects mainly because of various development activities that are taking place in every part of the world. Various satellite sensors are providing the required data collected by remote sensing techniques in the form of images using which the land use land cover information can be analyzed.  Constistency of Landsat satellite is illustrated with two time periods such as Operational Land Imager (OLI) of 2013 and consecutive 2014 procured by earth explorer with quantified changes for the same period in visakhapatnam of hudhud cyclone. Since this city is consisting of mainly urban, vegetation, few water bodies, some area of agriculture and barren,five classes have been chosen from the study area. The results indicate that due to the hudhud event some changes took place.  vegetation and built-up land have been increased by An increase of 19.1% (6.3 km2) and 11% (5.36 km2) has been observed in the case of vegetation and built up area  where as a decrease of 1.2% (4.06 km2), 6.1% (1.70 km2) and 1.2% (0.72 km2) has been observed in the case of  agriculture, barren land, and water body respectively. With the help of available satellite imagery belonging to the same area and of different time periods along with the  change detection techniques landscape dynamics have been analyzed. Using various classification algorithms along with the data available from the satellite sensor the land use and land cover classification information of the study area has been obtained. The maximum likelihood algorithm provided better results compared to other classification techniques and the accuracy achieved with this algorithm is 99.930% (overall accuracy) and 0.999 (Kappa coefficient).  

scholarly journals Rainwater Harvesting Using GIS Technique: A Case Study of Diyala Governorate, Iraq

2021 ◽  
Vol 32 (2) ◽  
pp. 96
Author(s):  
Dhuha S. Al-Khafaji ◽  
Asraa Khtan Abdulkareem ◽  
Qusai Y. Al-Kubaisi
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainwater Harvesting ◽  
Cost Effective ◽  
Stream Order ◽  
Time Saving ◽  
Harvesting Systems ◽  
Gis Environment ◽  
Landsat Satellite

To improve the management of water resources in Iraq, there are several methods, including the use of rainwater harvesting techniques. In this study, the Digital Elevation Model (DEM) and Landsat satellite imagery were used under the GIS environment to identify the suitable zones for rainwater harvesting. The accomplishment of rainwater harvesting systems strongly depends on their technical designing and identifying the suitable sites. Six criteria have been used to identify the rainwater harvesting sites in the Diyala governorate. The procedure of identifying the suitable sites for rainwater harvesting was applied twice for the Diyala governorate. Firstly, it was applied by using the criteria of rainfall, slope, stream order, distance to roads, and land use, and secondly, rainfall, slope, stream order, distance to roads, and Normalized Difference Vegetation Index (NDVI) criteria were used for this purpose. As a result, the study area was divided into three suitability zones: low, moderate, and high according to the specific criteria that were used to identify the rainwater harvesting suitable sites. It was found that in the application of land use criterion the low suitability zone represents 26%, 58% represents the moderate, and 16% for the high suitability zone, while in the method of NDVI it was found that 29% represents the zone that has low suitability, 57% represents the moderate, and 14% represents the high suitability zone. The compared results led to conclude that the land use is the most influential criterion for identifying the rainwater harvesting suitability sites and found that most of the Eastern parts of Diyala governorate are promising areas for rainwater harvesting and ArcGIS is a very useful, time-saving, and cost-effective tool for identifying the rainwater harvesting suitable sites.

scholarly journals Detection of Land Use Land Cover Changes Using Remote Sensing and GIS Techniques in a Secondary City in Bangladesh

2021 ◽  
Vol 4 (3) ◽  
pp. 132-146
Author(s):  
Md. Lutfor Rahman ◽  
Syed Hafizur Rahman
Keyword(s):  
Land Use ◽  
Land Cover ◽  
The United States ◽  
United States Geological Survey ◽  
Land Use Land Cover ◽  
Error Matrix ◽  
Barren Land ◽  
Landsat 7 ◽  
Landsat Satellite ◽  
Secondary City

This study aims at classifying land use land cover (LULC) patterns and detect changes in a 'secondary city' (Savar Upazila) in Bangladesh for 30 years i.e., from 1990 to 2020. Two distinct sets of Landsat satellite imagery, such as Landsat Thematic Mapper (TM) 1990 and Landsat 7 ETM+ 2020, were collected from the United States Geological Survey (USGS) website. Using ArcMap 10.3, the maximum likelihood algorithm was used to perform a supervised classification methodology. The error matrix and Kappa Kat were done to measure the mapping accuracy. Both images were classified into six separate classes: Cropland, Barren land, Built-up area, Vegetation, Waterbody, and Wetlands. From 1990 to 2020, Cropland, Barren land, Waterbody, and Wetlands have been decreased by 30.63%, 11.26%, 23.54%, and 21.89%, respectively. At the same time, the Built-up area and Vegetation have been increased by 161.16% and 5.77%, respectively. The research revealed that unplanned urbanization had been practiced in the secondary city indicated by the decreases in Cropland, Barren land, Wetland, and Waterbody, which also showed direct threats to food security and freshwater scarcity. An increase in Vegetation (mostly homestead vegetation) indicates some environment awareness programs that encourage people to maintain homestead and artificial gardens. The study argues for the sustainable planning of a secondary city for a developing country's future development.

scholarly journals Growing Season Vegetation Dynamics Based on NDVI and the Driving Forces in Nepal during 1982-2015

2020 ◽  
Vol 17 ◽  
pp. 1-22
Author(s):  
Binod Baniya ◽  
Qiuhong Tang ◽  
Madan Koirala ◽  
Kedar Rijal ◽  
Giri Kattel
Keyword(s):  
Vegetation Dynamics ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Pearson Correlation ◽  
Growing Season ◽  
Kendall Test ◽  
Warming Trend ◽  
Shuttle Radar Topography Mission

Monitoring and attributing growing season vegetation dynamics have become crucial for maintaining the structure and function of the ecosystem. The objective of this research was to examine the spatial and temporal vegetation changes and explore their driving forces during growing season in Nepal. It also explored the variation of Normalized Difference Vegetation Index (NDVI) in different altitudes at each 100m interval. The National Oceanic and Atmospheric Administration (NOAA) NDVI, monthly temperature, precipitation and Shuttle Radar Topography Mission (SRTM) 90m Digital Elevation Model (DEM) were used. The linear regression model, Sen’s slope, Mann Kendall test and Pearson correlation between NDVI and climate, i.e., temperature and precipitation were computed. The driving forces were identified based on threshold segmentation method. Our results showed positive intensity of vegetation change. The NDVI has significantly increased at the rate of 0.001yr-1, 0.0005yr-1 and 0.002yr-1 in growing season, spring and autumn but it has insignificantly increased at the rate of 0.0003yr-1 in summer. In the meantime, growing season temperature has significantly increased with an average warming trend of 0.03&deg;Cyr-1 but precipitation decreased at the rate of 2.76 mm yr-1 during 1982-2015. The NDVI increased in 84.20% (53.08% significant) of the area. The correlation between NDVI and temperature was found positive whereas correlation with precipitation was negative. Spatially, 84.05% of the study area found positive correlation between NDVI and temperature with 25.72% significance (p<0.05) which was very less with precipitation. Our results demonstrate that NDVI was strongly correlated with temperature compared with precipitation. Beyond the climate, NDVI changes were also attributed to multi-control environments and ecological restoration in Nepal.  

scholarly journals POTENTIALS AND CHARACTERISTICS OF LANDSAT IMAGERY IN RELATION TO LAND USE /COVER IN OKITIPUPA METROPOLIS, ONDO STATE, NIGERIA

2020 ◽  
Vol 19 (1) ◽  
pp. 150-158
Author(s):  
A. O. TOBORE ◽  
G. OYERINDE ◽  
B. A. SENJOBI ◽  
T. O. OGUNDIYI
Keyword(s):  
Land Use ◽  
Satellite Imagery ◽  
Supervised Classification ◽  
Vegetation Index ◽  
Forest Cover ◽  
Landsat Imagery ◽  
Land Use Changes ◽  
Aerial Photographs ◽  
The Past ◽  
Landsat Satellite

Landsat satellite imagery plays a crucial role in providing information on land use/cover modifications on local, regional, and global scales, especially where aerial photographs are missing. Monitoring land-use changes from past to present tends to be time-consuming especially when dealing with ground-truth information. Determining the past and current land-use change on Earth's surface using Landsat imagery tends to be effective and efficient when high-resolution imagery is unavailable. This study employed the use of Landsat satellite imagery to assess the past and present land use/cover using supervised classification and Normalized Difference Vegetation Index (NDVI). The result of the supervised classification land use/cover showed that forest cover and woodland undergo rapid loss, while farmland, wetland, built-up, and waterbodies tend to experience gradual loss. The NDVI demonstrated that farmland and forest cover was the most affected land use/cover. Hence, land use/cover of the study area is affected by human activities, such as intensive farming, population size, and deforestation.  

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