Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Dynamicity of Land Use/Land Cover(LULC):An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation(DMC)in India

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.

Effects of land use and cover change on surface wind speed in China

The surface wind speed(SWS)is affected by both large-scale circulation and land use and cover change(LUCC).In China,most studies have considered the effect of large-scale circulation rather than LUCC on SWS.In this study,we evaluated the effects of LUCC on the SWS decrease during 1979-2015 over China using the observation minus reanalysis(OMR)method.There were two key findings:(1)Observed wind speed declined significantly at a rate of 0.0112 m/(s·a),whereas ERA-Interim,which can only capture the inter-annual variation of observed data,indicated a gentle downward trend.The effects of LUCC on SWS were distinct and caused a decrease of 0.0124 m/(s·a)in SWS;(2)Due to variations in the characteristics of land use types across different regions,the influence of LUCC on SWS also varied.The observed wind speed showed a rapid decline over cultivated land in Northwest China,as well as a decrease in China’s northeastern and eastern plain regions due to the urbanization.However,in the Tibetan Plateau,the impact of LUCC on wind speed was only slight and can thus be ignored.

Land Use/Land Cover Change Detection in Pokhara Metropolitan, Nepal Using Remote Sensing

Land use and land cover are essential for maintaining and managing the natural resources on the earth surface. A complex set of economic, demographic, social, cultural, technological, and environmental processes usually result in the change in the land use/land cover change (LULC). Pokhara Metropolitan is influenced mainly by the combination of various driving forces: geographical location, high rate of population growth, economic opportunity, globalization, tourism activities, and political activities. In addition to this, geographically steep slope, rugged terrain, and fragile geomorphic conditions and the frequency of earthquakes, floods, and landslides make the Pokhara Metropolitan region a disaster-prone area. The increment of the population along with infrastructure development of a given territory leads towards the urbanization. It has been rapidly changing due to urbanization, industrialization and internal migration since the 1970s. The landscapes and ground patterns are frequently changing on time and prone to disaster. Here a study has been carried to study on LULC for the last 18 years (2000-2018). The supervised classification on Landsat Imagery was performed and verified the classification through computing the error matrix. Besides, the water bodies and vegetation area were extracted through the Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDWI) respectively. This research shows that during the last 18 years the agricultural areas diminishing by 15.66% while urban area is increasing by 13.2%. This research is beneficial for preparing the plan and policy in the sustainable development of Pokhara Metropolitan.

Extraction of LUCC with different methods and threshold value

The research of land use and land cover (LUCC) is an important aspect in the global change research. The goal of this study is to find methods of extraction of LUCC’s change outlined and change type from remotely sensed data. Take the country of Fengxian in Shanghai as an example, it was supposed two steps to finish extraction of LUCC information: the first step was to use different methods, which is used to outline change areas; the second step include methods of false composing of two-temporal and threshold value. Through combining two methods, a model rule is built and the LUCC product is obtained, four kinds of change type within the study area are given, and the results are obvious. Finally, the results support the application of the high resolution image and tasseled cap composition (greenness and wetness) in the specific regional too.

Forest Cover Dynamics of a Lowland Rainforest in Southwestern Nigeria Using GIS and Remote Sensing Techniques

The rate of forest degradation and deforestation in Nigeria has been increasing over the years and is prominent in the southwestern parts. Despite the significant change and degradation observed in a lowland rainforest in the region—Ogbese Forest Reserve, there is a great dearth of information about the level of forest cover change. Therefore, this study determined the cover dynamics of the rainforest reserve over the epoch of 20 years using Geographic Information System and remote sensing techniques. Coordinates of the boundary and some other benchmark places within the forest reserve were obtained. Secondary data collection included: Landsat imageries of 1998, 2002 and 2018. An interview guide was used to obtain information from forest officials and locals of the surrounding communities to complement the spatial data obtained. Image classification was done using the maximum likelihood algorithm. The rate of change across the epochs was determined using the area of the land cover classes. The level of vegetation disturbance in the reserve was determined through Normalized Difference Vegetation Index. Five different forest cover classes were identified in the study area: forest, plantation, farmland, grassland, and bare land. The natural forest reduced significantly from 34.43 km2 (48%) in 1998 to 8.73 km2 (12%) in 2002 and was depleted further by 2018, while other cover classes increased. NDVI value also reduced from 0.25 to 0.13. Agriculture, among others, was observed as the main driver of forest degradation and deforestation in Ogbese Forest Reserve. The study concluded that the remaining forest (i.e. plantation) could also be depleted by 2025, as it decreases by −0.94 km2 per year if proper reforestation and management practices are not introduced.

Land Characterization Analysis of Surface Temperature of Semi-Arid Mountainous City Abha, Saudi Arabia Using Remote Sensing and GIS

This knowledge of land surface temperature and its spatial variations within a city environment is of prime importance to the study of urban climate and human-environment interactions. Few studies have examined the influence of land use and terrain on the surface temperature effects of semi-arid mountainous urban areas. This study investigates the urban environment characterization and its effects on surface temperature using remote sensing. The methodologies adapted for this study are geometric and radiometric corrections of satellite data, extraction of land use/land cover and digital elevation model, estimation of vegetation density using Normalized Difference Vegetation Index (NDVI), and estimation of surface temperature and emissivity using temperature emissivity separation (TES) algorithm. Finally geospatial model and statistical techniques are used for assessing the overall impact of urban environmental characterization on urban climate of semi-arid region of Abha, Kingdom of Saudi Arabia. Herein, results reveal that the spatial distribution of surface temperature was affected by land use/land cover (LULC) and topography. The high dense built-up and commercial/industrial areas display higher surface temperature in comparison with surrounding lands. There is gradual decrease of LULC classes’ surface temperature with the increase in altitude. The cooling effect towards the surrounding urban built-up area is found increasing at the hill located vegetated area, the downward slope and valley terrain inside the recreational park. Therefore the spatial variation in surface temperature also reflected the effects of topography on LULC classes. Suitable mountainous land use utilization would help to expand the cooling effect. In the future, the outcomes of this study could be used to build environmentally sustainable urban planning suitable to semi-arid regions and to create practices that consider the local weather environment in urban planning.

Land use/land cover classification and its change detection using multi-temporal MODIS NDVI data

Detailed analysis of Land Use/Land Cover （LULC） using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three dif- ferent techniques： error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coeffi- cients （K）. The average overall accuracies for rabi and kharif are 82.83% and 78.21%, re- spectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation be- tween cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.

Urban Planning Based on Nature—A Nature-Based Solution

After an international contest announced by the City of Abu Dhabi “Cool Abu Dhabi Challenge”1 and the article published as a digest of a paper titled A Nature-based Solution [1], the decision has been made to take part in improving thermal comfort in public spaces by mitigating the impact of the effect of Urban Heat Islands (UHI)2 in the city of the Belgrade. The basic research aims at achieving the balance between the conflicting impacts when the buildings with their infrastructure and water-green surrounding area are in such correlation that it fulfils acceptable living and heating standards and reduces the use of fossil fuels for cooling the urban areas (buildings). By implementing the remote detection it is possible to analyze and quantify the impact of over-building on the temperature rise in urban areas as well as the disturbance of the heating comfort and the increased demand for additional cooling. Now it is possible to create virtual models that will incorporate this newly-added urban vegetation into urban plans, depending on the evaporation potential that will affect the microclimate of the urban area. Such natural cooling can be measured and adapted and hence aimed at a potential decrease in areas with UHI emissions [2]. Suitable greenery in the summer season can be a useful improvement which concurrently enables and complements several cooling mechanisms—evaporative cooling and evapotranspiration, i.e. natural cooling systems. The remote detection shall establish and map the “healthy” and “unhealthy” greenery zones—that is the vegetation zones with the highest evaporative potential with the “cooling by evaporation” effect and also, by implementing the urban prediction model, it shall propose green infrastructure corridors aimed at a potential decrease in the Urban Heat Island Emission.

Impacts of Mau Forest Catchment on the Great Rift Valley Lakes in Kenya

Remote sensing and GIS applications are being widely used for various projects relating to natural resource management. Forests are very important national assets for economic, environmental protection, social and cultural values and should be conserved in order to realize all these benefits. Kenya’s forests are rapidly declining due to pressure from increased population, technological innovation, urbanization human development and other land uses. Mau forest is one of the major forests in Kenya that is a catchment area for many Great Rift Valley lakes within the country and faces a lot of destruction. Continued destruction of the Mau forest will cause catastrophic environmental damage, resulting in massive food crises and compromising the livelihoods of millions of Kenyans, and the possible collapse of the tourism industry. The purpose of this research was to investigate the relationship between the increasing rate of deforestation and the reduction of the volumes of water in the neighboring lakes between the years 1989 to 2010. Satellite images from Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper (ETM+) were used for the detection of changes in the Mau forest and the dynamics of the neighboring water bodies that included lakes: Naivasha, Baringo, Nakuru, Elementaita and Bogoria. The research showed that from a period of 1989 to 2010 Mau forest has been decreasing due to deforestation and the water bodies have irregular dynamics in that, from 1989 to 2000, there was rise in the volume of water, this is attributed to the El Nino rains experienced in the country during the year 1997 and 1998. But between 2000 and 2010 the volume decreased as the forest is also decreasing. It is recommended that the government creates awareness to sensitize the public on the importance of such forests as catchment areas in Kenya.