scholarly journals Land Use/Land Cover (LULC) Using Landsat Data Series (MSS, TM, ETM+ and OLI) in Azrou Forest, in the Central Middle Atlas of Morocco

Environments ◽  
2018 ◽  
Vol 5 (12) ◽  
pp. 131 ◽  
Author(s):  
Meriame Mohajane ◽  
Ali Essahlaoui ◽  
Fatiha Oudija ◽  
Mohammed El Hafyani ◽  
Abdellah El Hmaidi ◽  
...  

The study of land use/land cover (LULC) has become an increasingly important stage in the development of forest ecosystems strategies. Hence, the main goal of this study was to describe the vegetation change of Azrou Forest in the Middle Atlas, Morocco, between 1987 and 2017. To achieve this, a set of Landsat images, including one Multispectral Scanner (MSS) scene from 1987; one Enhanced Thematic Mapper Plus (ETM+) scene from 2000; two Thematic Mapper (TM) scenes from 1995 and 2011; and one Landsat 8 Operational Land Imager (OLI) scene from 2017; were acquired and processed. Ground-based survey data and the normalized difference vegetation index (NDVI) were used to identify and to improve the discrimination between LULC categories. Then, the maximum likelihood (ML) classification method was applied was applied, in order to produce land cover maps for each year. Three classes were considered by the classification of NDVI value: low-density vegetation; moderate-density vegetation, and high-density vegetation. Our study achieved classification accuracies of 66.8% (1987), 99.9% (1995), 99.8% (2000), 99.9% (2011), and 99.9% (2017). The results from the Landsat-based image analysis show that the area of low-density vegetation was decreased from 27.4% to 2.1% over the past 30 years. While, in 2017, the class of high-density vegetation was increased to 64.6% of the total area of study area. The results of this study show that the total forest cover remained stable. The present study highlights the importance of the image classification algorithms combined with NDVI index for better understanding the changes that have occurred in this forest. Therefore, the findings of this study could assist planners and decision-makers to guide, in a good manner, the sustainable land development of areas with similar backgrounds.

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1678 ◽  
Author(s):  
Yan-jun Guo ◽  
Jie-jie Han ◽  
Xi Zhao ◽  
Xiao-yan Dai ◽  
Hao Zhang

In this study, 167 land parcels of downtown Shanghai, China, were used to investigate the relationship between parcel-level land use/land cover (LULC) components and associated summertime intra-surface urban heat island (SUHI) effect, and further analyze the potential of mitigating summertime intra-SUHI effect through the optimized LULC components, by integrating a thermal sharpening method combining the Landsat-8 thermal band 10 data and high-resolution Quickbird image, statistical analysis, and nonlinear programming with constraints. The results show the remarkable variations in intra-surface urban heat island (SUHI) effect, which was measured with the mean parcel-level blackbody sensible heat flux in kW per ha (Mean_pc_BBF). Through measuring the relative importance of each specific predictor in terms of their contributions to changing Mean_pc_BBF, the influence of parcel-level LULC components on excess surface flux of heat energy to the atmosphere was estimated using the partial least square regression (PLSR) model. Analysis of the present and optimized parcel-level LULC components and their contribution to the associated Mean_pc_BBF were comparable between land parcels with varying sizes. Furthermore, focusing on the gap between the present and ideally optimized area proportions of parcel-level LULC components towards minimizing the Mean_pc_BBF, the uncertainties arising from the datasets and methods, as well as the implications for sustainable land development and mitigating the UHI effect were discussed.


Author(s):  
Qijiao Xie ◽  
Qi Sun

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.


2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo

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.


Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 916
Author(s):  
Urgessa Kenea ◽  
Dereje Adeba ◽  
Motuma Shiferaw Regasa ◽  
Michael Nones

Land use land cover (LULC) changes are highly pronounced in African countries, as they are characterized by an agriculture-based economy and a rapidly growing population. Understanding how land use/cover changes (LULCC) influence watershed hydrology will enable local governments and policymakers to formulate and implement effective and appropriate response strategies to minimize the undesirable effects of future land use/cover change or modification and sustain the local socio-economic situation. The hydrological response of the Ethiopia Fincha’a watershed to LULCC that happened during 25 years was investigated, comparing the situation in three reference years: 1994, 2004, and 2018. The information was derived from Landsat sensors, respectively Landsat 5 TM, Landsat 7 ETM, and Landsat 8 OLI/TIRS. The various LULC classes were derived via ArcGIS using a supervised classification system, and the accuracy assessment was done using confusion matrixes. For all the years investigated, the overall accuracies and the kappa coefficients were higher than 80%, with 2018 as the more accurate year. The analysis of LULCC revealed that forest decreased by 20.0% between the years 1994–2004, and it decreased by 11.8% in the following period 2004–2018. Such decline in areas covered by forest is correlated to an expansion of cultivated land by 16.4% and 10.81%, respectively. After having evaluated the LULCC at the basin scale, the watershed was divided into 18 sub-watersheds, which contained 176 hydrologic response units (HRUs), having a specific LULC. Accounting for such a detailed subdivision of the Fincha’a watershed, the SWAT model was firstly calibrated and validated on past data, and then applied to infer information on the hydrological response of each HRU on LULCC. The modelling results pointed out a general increase of average water flow, both during dry and wet periods, as a consequence of a shift of land coverage from forest and grass towards settlements and build-up areas. The present analysis pointed out the need of accounting for past and future LULCC in modelling the hydrological responses of rivers at the watershed scale.


2019 ◽  
Vol 28 (3) ◽  
pp. 381-394
Author(s):  
E. D. Ashaolu ◽  
J. F. Olorunfemi ◽  
I. P. Ifabiyi

Osun drainage basin is one of the regions in Nigeria experiencing increasing population growth and rapid urbanization; and about 70% of the inhabitantsrely on shallow groundwater resources of the region. Change in land use/land cover is one of the significant factors controlling regional hydrology and groundwater resources, thus the continuous change in land use and land cover of the drainage basin will significantly affect the basin’s groundwater resources. There are 7 classified land use/land cover in the study area which are bare surfaces, built up area, crops/shrubs, forest, rock outcrops, water bodies and wetland. Applying WetSpass-M hydrological model, we predicted the effect of land use/land cover change on the groundwater recharge in Osun drainage basin, Nigeria between 1984-2015. The results revealed that the highest groundwater recharge of 48.56%, 33.64% and 37.29% occurred in forested area in 1984, 2000 and 2015, respectively. This result might be due to the influence of vegetation in slowing down the speed of running water across the forest area, that allows more infiltration and deep percolation into the water table to recharge the groundwater system. On the other hand, the least groundwater recharge of the total annual was on the rock outcrops, which are about 4% in 1984, 3% in 2000 and 2% in 2015. The least recharge found on rock outcrops is expected and may be attributed to the fact that infiltration can only occur around or on decomposed rock outcrop, which may result in minute recharge to the groundwater system. The mean annual groundwater recharge of the basin for the land use/land cover of 1984, 2000 and 2015 are476.54, 411.07 and 430.06 mm/y, respectively. Overall, for the 32 years period of investigation, change in land use/land cover accounts for only 10% reduction in mean groundwater recharge occurrence between 1984 and 2015. Also, there is a change in recharge pattern in the study area during this period because most often, change in land use/land cover is a transition from one land use/land cover class to another, and the recharge pattern is influenced based on the degree of transition that took place and the characteristics of the dominant land use/land cover at a particular area of the basin. Although, the 10% reduction in mean annual recharge appears minute, this might become pronounced if the current rate of deforestation in the drainage basin continues unabated. Therefore, proper land use allocation, regulated land development and afforestation in terms of planting of native trees that were lost through anthropogenic activities in the basin should be policy option for groundwater sustainability.


10.29007/jvz3 ◽  
2018 ◽  
Author(s):  
Mohamed Mostafa Mohamed ◽  
Samy Elmahdy

Dubai is a rapidly urbanizing emirate with land development succeeding at a fast pace. The present study aims to develop a low-cost classifier based on the spectral angle mapper (SAM) and image difference (ID) algorithms. The proposed approach was developed in order to improve Land use/ Land cover (LULC) classification maps for the purpose of monitoring and analysing LULC change during the period from 2000 to 2015 for the Emirate of Dubai. The approach starts by collecting 320 training samples from high resolution images such as QuickBird with a spatial resolution of 60 cm followed by applying a 3×3 spatial convulsion filter, majority/ minority analysis, sieving classes and clump map of the produced LULC maps. After that, the accuracy of the maps were assigned using confusion matrix. The accuracy assessment demonstrated that the targeted 2000, 2005,2010 and 2015 LULC maps have 88.125%, 89.069%, 90.122% and 96.096% accuracy, respectively. The results exhibited that the built-up areas increased by 233.72 km2 (5.81%) from 2000 to 2005 and keeps to increase even up and till the present time. The results also showed that the changes in the periods 2000-2005 and 2010-2015 confirmed that net vegetation area loses were more obvious from 2005 to 2005 than from 2010 to 2015, reducing from 47.618 km2 to 40,820 km2, respectively. This study is of great help to urban planners and decision makers.


Author(s):  
Ajagbe, Abeeb Babajide ◽  
Oguntade, Sodiq Solagbade ◽  
Abiade, Idunnu Temitope

Land use assessment and land cover transition need remote sensing (RS) and geographic information systems (GIS). Land use/land cover changes of Ado-Ekiti Local Government Area, Ekiti State, Nigeria, were examined in this research. Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI were acquired for 1985, 2000, and 2015 respectively. Image scene with path 190 and row 055 was used for the three Landsat Images. A supervised digital image classification approach was used in the study, which was carried out using the ArcMap 10.4 Software. Five land use/land cover categories were recognised and recorded as polygons, including Built-up Areas, Bare surface, water body, Dense Vegetation and Sparse Vegetation. The variations in the area covered by the various polygons were measured in hectares. This study revealed that between 1985 and 2015, there was a significant change in Built-up areas from 1694 hectares to 5656 hectares. However, there was a reduction in water body from 25 hectares in 1985 to 19 hectares in 2015; there was a severe reduction in the bare surface from 4641 hectares in 1985 to 2237 hectares in 2015. Generally, the findings show that the number of people building houses in the study area has grown over time, as many people reside in the outskirts of the Local Government Area, resulting in a decrease in the vegetation and bare surfaces. The maps created in this research will be useful to the Ekiti State Ministry of Land, Housing, Physical Planning, and Urban Development to develop strategies and government policies to benefit people living in the Ado-Ekiti Local Government Area of the State.


Author(s):  
B. İşler ◽  
Z. Aslan

Abstract. The increase in the world population and the migration of people from rural to urban areas causes an increase in artificial surfaces and causes many negative effects on the ecosystem, regional climate variations and global diversity. Nowadays, as the effects of climate change are felt more and more, it has gained importance in researches on this subject. Therefore, the estimation of the change in the vegetation density for the coming years and the determination of the land use / land cover (LULC) change in cities are very essential for urban planning. In this study, the effects of regional urbanization on vegetation are examined by using satellite data and atmospheric variables. In the vegetation analysis, multi-time index values obtained from TERRA-MODIS satellite, EVI (Enhanced Vegetation Index) and LST (Land Surface Temperature) were taken into account between the years of 2005 and 2018 in Alanya, Turkey. Temperature and precipitation were selected as the atmospheric variables and expected variations in EVI value until 2030 were estimated. In the study employed a wavelet-transformed artificial neural network (WANN) model to generate long-term (12-year) EVI forecasts using LST, temperature and precipitation. The relationship between land use / land cover and urbanization is investigated with NDBI (Normalized Difference Built-up Index) data obtained from the Landsat 8 OLI / TIRS satellite sensor. The simulation results show that The EVI value, which was 0.30 in 2018, will decrease to 0.25 in 2030.


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