scholarly journals Relating the Land-Use Changes to the Invasion of Pneumatopteris afra in Nigeria Using Remote Sensing

2020 ◽  
Vol 28 (4) ◽  
Author(s):  
Gbenga Festus Akomolafe ◽  
Zakaria Rahmad
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Changes ◽  
Forest Products ◽  
Classification Systems ◽  
The Past ◽  
Classification Technique ◽  
Bare Land ◽  
Landsat Satellite ◽  
Broad Classification

The study aimed at using satellite remote sensing in identifying the land-use changes that have occurred in Lafia, Nigeria within the past 35 years, especially in relation to the current and the predicted future invasion of a fern (Pneumatopteris afra). Landsat satellite images OLI/TIRS, ETM+ and TM within the interval of 15 years from 1985 to 2020 were used for the extraction of land-use. Six broad classification systems were used to classify the land-use changes by employing a supervised classification technique. In 1985, the bare land dominated the land-use having an area of 69156 ha while the wetland was the least having an area of 3412 ha. However, in 2020, the built-up area has dominated the land-use of Lafia with an area of 144645 ha (52.21%) while the wetland still remained the least with area of 1477 ha. This is obviously due to the geometric increase in the urbanization of this city. There was a consistent loss of the forests from 1985 to 2020 with an annual rate of loss of 0.46%. This resulted in a loss of 44329 ha of forests in 2020 out of the 47643 ha in 1985. This approximately leads to a total loss of 172,732,045 USD of forest products. The current invasion of Pneumatopteris afra in Lafia was found to fall within the shrub and grasses land-use class. This indicates that the landsat satellite could not detect the wetlands where the plant dominated due to its massive covering. This study calls for immediate conservation of the remaining forests and wetlands in Lafia to prevent further encroachments and invasion by plants.

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.  

scholarly journals Integrating Remote Sensing and a Markov-FLUS Model to Simulate Future Land Use Changes in Hokkaido, Japan

2021 ◽  
Vol 13 (13) ◽  
pp. 2621
Author(s):  
Zhanzhuo Chen ◽  
Min Huang ◽  
Daoye Zhu ◽  
Orhan Altan
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Planning ◽  
Land Use Changes ◽  
Arable Land ◽  
Cultivated Land ◽  
Land Resources ◽  
Forest Protection ◽  
Land Protection ◽  
The Past

As the second largest island in Japan, Hokkaido provides precious land resources for the Japanese people. Meanwhile, as the food base of Japan, the gradual decrease of the agricultural population and more intensive agricultural practices on Hokkaido have led its arable land use to change year by year, which has also caused changes to the whole land use pattern of the entire island of Hokkaido. To realize the sustainable use of land resources in Hokkaido, past and future changes in land use patterns must be investigated, and target-based land use planning suggestions should be given on this basis. This study uses remote sensing and GIS technology to analyze the temporal and spatial changes of land use in Hokkaido during the past two decades. The types of land use include cultivated land, forest, waterbody, construction, grassland, and others, by using the satellite images of the Landsat images in 2000, 2010, and 2019 to achieve this goal to make classification. In addition, this study used the coupled Markov-FLUS model to simulate and analyze the land use changes in three different scenarios in Hokkaido in the next 20 years. Scenario-based situational analysis shows that the cultivated land in Hokkaido will drop by about 25% in 2040 under the natural development scenario (ND), while the cultivated land area in Hokkaido will remain basically unchanged in cultivated land protection scenario (CP). In forest protection scenario (FP), the area of forest in Hokkaido will increase by 1580.8 km2. It is believed that the findings reveal that the forest land in Hokkaido has been well protected in the past and will be protected well in the next 20 years. However, in land use planning for future, Hokkaido government and enterprises should pay more attention to the protection of cultivated land.

scholarly journals Evaluation of the status of land use/land cover change using remote sensing and GIS in Jewha Watershed, Northeastern Ethiopia

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Dereje Gebrie Habte ◽  
Satishkumar Belliethathan ◽  
Tenalem Ayenew
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Catchment Area ◽  
Environmental Conservation ◽  
Land Use Land Cover ◽  
Cultivated Land ◽  
Plantation Forest ◽  
Bare Land

AbstractEvaluation of land use/land cover (LULC) status of watersheds is vital to environmental management. This study was carried out in Jewha watershed, which is found in the upper Awash River basin of central Ethiopia. The total catchment area is 502 km2. All climatic zones of Ethiopia, including lowland arid (‘Kola’), midland semi-arid (‘Woinadega’), humid highland (Dega) and afro alpine (‘Wurch’) can be found in the watershed. The study focused on LULC classification and change detection using GIS and remote sensing techniques by analyzing satellite images. The data preprocessing and post-process was done using multi-temporal spectral satellite data. The images were used to evaluate the temporal trends of the LULC class by considering the years 1984, 1995, 2005 and 2015. Accuracy assessment and change detection of the classification were undertaken by accounting these four years images. The land use types in the study area were categorized into six classes: natural forest, plantation forest, cultivated land, shrub land, grass land and bare land. The result shows the cover classes which has high environmental role such as forest and shrub has decreased dramatically through time with cultivated land increasing during the same period in the watershed. The forest cover in 1984 was about 6.5% of the total catchment area, and it had decreased to 4.2% in 2015. In contrast, cultivated land increased from 38.7% in 1984 to 51% in 2015. Shrub land decreased from 28 to 18% in the same period. Bare land increased due to high gully formation in the catchment. In 1984, it was 1.8% which turned to 0.6% in 1995 then increased in 2015 to 2.7%. Plantation forest was not detected in 1984. In 1995, it covers 1.5% which turned to be the same in 2015. The study clearly demonstrated that there are significant changes of land use and land cover in the catchment. The findings will allow making informed decision which will allow better land use management and environmental conservation interventions.

Hydrologic response of a watershed to land use changes: A remote sensing and GIS approach

2001 ◽  
Vol 22 (11) ◽  
pp. 2095-2108 ◽  
Author(s):  
T. Sharma ◽  
P. V. Satya Kiran ◽  
T. P. Singh ◽  
A. V. Trivedi ◽  
R. R. Navalgund
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Changes ◽  
Remote Sensing And Gis ◽  
Hydrologic Response

scholarly journals Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Cover ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Kurdistan Region ◽  
The Past ◽  
Past Trend

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

scholarly journals Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

2018 ◽  
Vol 153 ◽  
pp. 062050
Author(s):  
Hua Ding ◽  
Ru Ren Li ◽  
Li Shuang Sun ◽  
Xin Wang ◽  
Yu Mei Liu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria

2014 ◽  
Vol XL-8 ◽  
pp. 613-616 ◽  
Author(s):  
O. S. Olokeogun ◽  
K. Iyiola ◽  
O. F. Iyiola
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Sustainable Forest Management ◽  
Cost Effective ◽  
Remote Sensing And Gis ◽  
Clear Understanding ◽  
Forest Reserve ◽  
Landsat Satellite

Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. <br><br> The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. <br><br> This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.

scholarly journals Land Cover/ Land Use Change and Climate Change in Dhofar Governorate, Oman

2021 ◽  
pp. 41-47
Author(s):  
E. Ramadan ◽  
T. Al-Awadhi ◽  
Y. Charabi
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Use Changes ◽  
Spatial Differentiation ◽  
Study Results ◽  
Vegetation Activity ◽  
The Status ◽  
Landsat Satellite

The study of land cover/land use dynamics under climate change conditions is of great significance for improving sustainable ecological management. Understanding the relationships between land cover and land use changes and climate change is thus very important. Understanding the interactive and cumulative effects of climate and land-use changes are a priority for urban planners and policy makers. The present investigation is based on Landsat satellite imagery to explore changes in vegetation spatial distribution between the years from 2000 to2018 The methodology is focused on vegetation indexes tracking and algebraic overlay calculation to analyzed vegetation and their spatial differentiation, land cover change pattern, and the relationships between vegetation dynamics and land cover change in Dhofar Governorate. The study results have revealed that the vegetation vigor is lower in all years compared to 2000. The scene of 2010 shows the minimum vegetation vigor, overall. Besides, the investigation shows a statistical relationship between rainfall and the status of the health of vegetation. Monsoon rainfall has an impact of the growth of vegetation. Between 2012 and 2013, the vegetation activity shows a decreasing trend. The analysis diagnoses an area affected by the worst degree of aridity situated in the southeastern of Dhofar Mountains. Climate change is the main driving factor resulted from both human activities and rainfall fluctuation.

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