Arabian Journal of Geosciences, Journal Year: 2020, Volume and Issue: 13(3)
Published: Jan. 23, 2020
Language: Английский
Geology Ecology and Landscapes, Journal Year: 2021, Volume and Issue: 7(1), P. 46 - 58
Published: May 18, 2021
The aim of this research was to assess the land use/land cover (LULC) changes and its impact on surface temperature (LST) using remote-sensing (RS) technique in district Khanewal, Punjab, Pakistan. Data were pre-processed ERDAS imagine 15 Arc GIS 10.4 software for layer stacking, mosaicking, sub-setting Landsat images. After pre-processing, supervised classification scheme applied years 1980, 2000, 2020, which explains maximum likelihood algorithm identify LULC observed study area. "Built-up area" 1980 occupied 1.75% but build-up area increased (5.27%) compared 2020. Vegetation decreased by 4.12% from 2020 Khanewal. It that there has been a rapid change vegetation LST values 0.50°C due increasing East West direction Maximum minimum normalized difference index (NDVI) 0.72 −0.2 regression line produced definitive explanation, showing strong negative correlation with NDVI LST. outcomes indicated dramatic transformation took place Khanewal regarding decrease greenness increase population density, urban growth, other infrastructural developments. Thus, these results will be used regional planning managing agriculture coming environmental changes.
Language: Английский
Citations
117
Land, Journal Year: 2022, Volume and Issue: 11(5), P. 595 - 595
Published: April 19, 2022
Climate change is likely to have serious social, economic, and environmental impacts on farmers whose subsistence depends nature. Land Use Cover (LULC) changes were examined as a significant tool for assessing at diverse temporal spatial scales. Normalized Difference Vegetation Index (NDVI) has the potential ability signify vegetation structures of various eco-regions provide valuable information remote sensing in studying phenology cycles. In this study, we used Geographical Information System (GIS) techniques with Maximum Likelihood Classification (MLC) identify LULC 40 years Sahiwal District. Later, conducted 120 questionnaires administered local which correlate climate NDVI. The maps prepared using MLC training sites 1981, 2001, 2021. Regression analysis (R2) was performed relationship between temperature cover study area. Results indicate that build-up area increased from 7203.76 ha (2.25%) 31,081.3 (9.70%), while decreased by 14,427.1 (4.5%) 1981 2021 mean NDVI values showed overall 0.24 0.20 Almost 78% stated been changing during last few years, 72% had affected agriculture, 53% thought rainfall intensity also decreased. R2 tendency negatively connected each other. This will integrate apply best most suitable methods, tools, approaches equitable adaptation governance agricultural systems conditions. Therefore, research outcome meaningfully help policymakers urban planners sustainable management strategies level.
Language: Английский
Citations
105
Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2022, Volume and Issue: 126, P. 103117 - 103117
Published: Jan. 25, 2022
Language: Английский
Citations
89
Geoscience Letters, Journal Year: 2023, Volume and Issue: 10(1)
Published: July 26, 2023
Abstract At the global and regional scales, green vegetation cover has ability to affect climate land surface fluxes. Climate is an important factor which plays role in cover. This research aimed study changes relation of different indices with temperature using multi-temporal satellite data Sahiwal region, Pakistan. Supervised classification method (maximum likelihood algorithm) was used achieve based on ground-truthing. Our denoted that during last 24 years, almost 24,773.1 ha (2.43%) area been converted roads built-up areas. The increased coverage from 43,255.54 (4.24%) 1998 2022 area. Average (LST) values were calculated at 16.6 °C 35.15 for winter summer season, respectively. In average RVI, DVI, TVI, EVI, NDVI SAVI noted as 0.19, 0.21, 0.26, 0.28, 0.30 0.25 For LST relation, statistical linear regression analysis indicated kappa coefficient R 2 = 0.79 0.75 0.78 0.81 0.83 0.80 related LST. remote sensing (RS) technology can be monitor over time, providing valuable information sustainable use management. Even though findings provide significant references reasoned optimal resources through policy implications.
Language: Английский
Citations
64
Sustainability, Journal Year: 2023, Volume and Issue: 15(4), P. 3572 - 3572
Published: Feb. 15, 2023
Land use/land cover (LULC) changes are among the most significant human-caused global variations affecting natural environment and ecosystems. Pakistan’s LULC patterns have undergone huge since 1900s, with no clear mitigation plan. This paper aims to determine normalized difference vegetation index (NDVI) as well their causes in Southern Punjab province over four different periods (2000, 2007, 2014, 2021). Landsat-based images of 30 m × spatial resolution were used detect changes, while NDVI dynamics calculated using Modis Product MOD13Q1 (Tiles: h24 v5, v6) at a 250 m. The iterative self-organizing (ISO) cluster method (object meta-clustering minimal distance center approach) was quantify this research because its straightforward approach that requires human intervention. accuracy assessment Kappa coefficient assess efficacy results derived from changes. Our findings revealed considerable settlements, forests, barren land Punjab. Compared 2000, forest had reduced by 31.03%, settlement increased 14.52% 2021. Similarly, rapidly been converted into land. For example, 12.87% 2021 compared 2000. analysis showed forests settlements 12.87%, respectively, twenty year period area decreased 4.36% It shows 31.03% urban land, ground, farmland. formerly utilized for due expansion infrastructure commercial sector Consequently, proper monitoring is required. Furthermore, relevant agencies, governments, policymakers must focus on management development. Finally, current study provides an overall scenario how trends evolving region, which aids use planning management.
Language: Английский
Citations
60
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: May 23, 2024
Abstract This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables CHIRPS ERA5 datasets, our approach leverages Google Earth Engine (GEE) efficient processing. It combines statistical methodologies, including linear regression, Mann–Kendall trend tests, Sen's slope estimator, partial correlation, cross wavelet transform analyses. The findings highlight significant spatial temporal NDVI, an annual increase averaging 0.00197 per year (p < 0.0001). positive is coupled precipitation by 0.4801 mm/year = 0.0016). In contrast, analysis recorded a slight decrease temperature (− 0.01011 °C/year, p 0.05) reduction solar radiation 0.27526 W/m 2 /year, 0.05). Notably, cross-wavelet underscored coherence NDVI factors, revealing periods of synchronized fluctuations distinct lagged relationships. particularly highlighted as primary driver growth, illustrating its crucial impact across various Pakistani regions. Moreover, revealed seasonal patterns, indicating that health most responsive during monsoon season, correlating strongly peaks precipitation. Our investigation has Pakistan's complex association which varies different Through analysis, we have identified phase critical influence drivers on patterns. These insights are developing regional adaptation strategies informing sustainable agricultural environmental management practices face ongoing changes.
Language: Английский
Citations
30
Cogent Food & Agriculture, Journal Year: 2024, Volume and Issue: 10(1)
Published: Jan. 16, 2024
Agricultural Land Suitability Analysis plays a pivotal role in sustainable land use planning, aiding decision-makers identifying areas most conducive to agriculture. This study employs systematic approach integrating Analytical Hierarchy Process and Multi-Criteria Decision techniques assess prioritize the suitability of agricultural Southern Punjab (Multan region). The methodology involves defining clear objectives, relevant criteria sub-criteria, establishing hierarchical structure conducting pairwise comparisons determine relative importance each factor. Our outcomes indicated that almost 43% area was highly suitable for agriculture, 27% moderately suitable, 16% marginally 8% less 6% not agriculture area. All lands had silty clay or type soil, which sandy loam soil Multan region. output is comprehensive map identifies Sensitivity analysis validation are incorporated enhance robustness reliability results. provides valuable tool planners policymakers make informed decisions regarding allocation, contributing practices resource management.
Language: Английский
Citations
19
Land, Journal Year: 2025, Volume and Issue: 14(2), P. 389 - 389
Published: Feb. 13, 2025
Land Use and Cover (LULC) assessment is vital for achieving sustainable ecosystems. This study quantified mapped the spatiotemporal LULC changes in Ado-Odo Ota Local Government Area of Ogun State, Nigeria, between 2015 2023. The was classified into water, forest or thick bush, sparse vegetation, built-up, bare land using Landsat images. Processing, classification, image analysis were done ESRI ArcGIS Pro 3.3. changed from to 2023, with built-up areas vegetation increasing by 138.2 km2 28.7 km2, respectively. In contrast, which had greatest change among classes, decreased 153.7 over this period while water bodies 9.5 3.8 Forest bush (201.0 km2) converted reflects an increase agricultural activities region. conversion about 109.8 3.7 highlights considerable urbanization. Overall, area need use practices balance urban growth ecological preservation, achievable through effective management policy frameworks.
Language: Английский
Citations
5
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Feb. 10, 2025
The escalating trend of global urbanization, particularly pronounced in the burgeoning urban areas Pakistan, necessitates a meticulous examination Land Use/Land Cover (LULC) changes and their extensive environmental repercussions. Understanding these transformations is crucial for informed decision-making evolving ecological dynamics. This research utilizes Geographic Information Systems (GIS), Remote Sensing (RS), statistical analyses to investigate LULC thoroughly Okara District, from 1991 2023. Despite its considerable socio-economic significance, District has remained relatively understudied, making this contribution understanding landscape. Key indicators include Normalized Difference Vegetation Index (NDVI) Built-up (NDBI), correlated with Surface Temperature (LST). Findings 22.6% decline vegetation cover (415.1 km2) 64.1% increase (110.7 Correlations reveal consistent negative relationship between NDVI LST (R2, 0.55–0.69) positive correlation NDBI (R2 0.62–0.69), indicating persistent Urban Heat Island (UHI) effect. study underscores urgent need sustainable planning balance developmental needs preservation. Informed can mitigate UHI effect, emphasizing broader implications urbanization challenges. contributes dynamics fosters discussions on Sustainable Development Goals (SDGs), climate action, development resilient cities communities.
Language: Английский
Citations
4
Land, Journal Year: 2021, Volume and Issue: 10(10), P. 1026 - 1026
Published: Sept. 30, 2021
Land use–land cover (LULC) alteration is primarily associated with land degradation, especially in recent decades, and has resulted various harmful changes the landscape. The normalized difference vegetation index (NDVI) prospective capacity to classify vegetative characteristics of many ecological areas proven itself useful as a remote sensing (RS) tool recording phenological aspects. Likewise, built-up (NDBI) used for quoting areas. current research objectives include identification LULC, NDVI, NDBI Jhelum District, Punjab, Pakistan, during last 30 years (1990–2020). This study targeted five major LULC classes: water channels, area, barren land, forest, cultivated land. Satellite imagery classification tools were identify northern Pakistan. perception data about environmental variations conveyed by 500 participants (mainly farmers) also recorded analyzed. results depict that majority farmers (54%) believe appearance more drastic such less rainfall, drought, decreased availability irrigation 2020 compared prior. Overall accuracy assessment was 83.2% 88.8% 1990, 88.1% 85.7% 2000, 86.5% 86.7% 2010, 85.6% 87.3% 2020. NDVI District highest 1990 at +0.86 lowest +0.32; similarly, values +0.72 −0.36. change showed clear association temperature, NDBI, area. At same time, area soil, vegetation, from quite prominent, possibly resulting temperature increases, reduction irrigation, changing rainfall patterns. Farmers found be responsive climatic variations, diverting framing possible mitigation approaches, but they need government assistance. findings this study, causes impacts rapid immediate attention related departments policy makers.
Language: Английский
Citations
96