Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning

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.

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Perkembangan Wilayah dan Perubahan Tutupan Lahan di Kabupaten Purwakarta sebagai Dampak dari Proses Konurbasi Jakarta-Bandung

Journal of Regional and Rural Development Planning ◽

10.29244/jp2wd.2018.2.2.195-208 ◽

2018 ◽

Vol 2 (2) ◽

pp. 195

Author(s):

Alfin Murtadho ◽

Siti Wulandari ◽

Muhammad Wahid ◽

Ernan Rustiadi

Keyword(s):

Land Use ◽

Land Cover ◽

Regional Development ◽

Land Cover Change ◽

Urban Expansion ◽

Satellite Image ◽

Water Bodies ◽

Urban Region ◽

Land Use Land Cover ◽

The Impact

<p class="ISI-Paragraf">Jabodetabek and Bandung Raya metropolitan region experienced an urban expansion phenomenon that caused the two metropolitan regions to become increasingly connected by a corridor and form a mega-urban region caused by the conurbation process. Purwakarta regency is one of the regions in Jakarta-Bandung corridor that experienced the impact of Jakarta-Bandung conurbation process. This study aims to analyze the level of regional development, to analyze land cover change that occurred, and to predict Purwakarta Regency land use/land cover in 2030. Regional development analysis is done by using the Scalogram method based on Potential Village data of year 2003 and 2014. Land cover change analysis is done through spatial analysis by overlaying land cover Landsat Satellite Image of year 2000 and 2015. Land use/land cover prediction in 2030 is conducted through spatial modelling of Cellular Automata Markov method. Purwakarta Regency experienced an increase in regional development within the period of 11 years (2003 to 2014), which is marked by a decrease in the percentage of the number of villages that are in hierarchy III and increase in the percentage of the number of villages that are in hierarchy II and I. In general, within 15 years (2000 to 2015) Purwakarta Regency has increasing number of built-up area and mixed gardens, meanwhile dry land, forest, paddy field, and water bodies tend to decrease. The results of CA Markov analysis show that the built-up area is predicted to continue to increase from 2000 to 2030, meanwhile paddy fields and water bodies will continue to decrease.</p>

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Analysis of Land Use Land Cover Changes with Land Surface Temperature Using Spatial-Temporal Data for Nagpur City, India

Journal of Landscape Ecology ◽

10.2478/jlecol-2021-0017 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Farhan Khan ◽

Bhumika Das ◽

R. K. Mishra ◽

Brijesh Patel

Keyword(s):

Land Use ◽

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Spatial Data ◽

Land Surface ◽

Water Bodies ◽

Landsat 8 ◽

Land Use Land Cover ◽

Barren Land

Abstract Remote sensing and Geographic Information System (GIS) are the most efficient tools for spatial data processing. This Spatial technique helps in generating data on natural resources such as land, forests, water, and their management with planning. The study focuses on assessing land change and surface temperature for Nagpur city, Maharashtra, for two decades. Land surface temperature and land use land cover (LULC) are determined using Landsat 8 and Landsat 7 imageries for the years 2000 and 2020. The supervised classification technique is used with a maximum likelihood algorithm for performing land classification. Four significant classes are determined for classification, i.e., barren land, built-up, vegetation and water bodies. Thermal bands are used for the calculation of land surface temperature. The land use land cover map reveals that the built-up and water bodies are increasing with a decrease in vegetation and barren land. Likewise, the land surface temperature map showed increased temperature for all classes from 2000 to 2020. The overall accuracy of classification is 98 %, and the kappa coefficients are 0.98 and 0.9 for the years 2000 and 2020, respectively. Due to urban sprawl and changes in land use patterns, the increase in land surface temperature is documented, which is a global issue that needs to be addressed.

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Land Use/Land Cover Changes and the Relationship with Land Surface Temperature Using Landsat and MODIS Imageries in Cameron Highlands, Malaysia

Land ◽

10.3390/land9100372 ◽

2020 ◽

Vol 9 (10) ◽

pp. 372

Author(s):

Darren How Jin Aik ◽

Mohd Hasmadi Ismail ◽

Farrah Melissa Muharam

Keyword(s):

Land Use ◽

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Landsat 8 ◽

Land Use Land Cover ◽

Lulc Change ◽

Cameron Highlands ◽

The Impact

Mountainous regions are more sensitive to climatic condition changes and are susceptible to recent increases in temperature. Due to urbanization and land use/land cover (LULC) issues, Cameron Highlands has been impacted by rising land surface temperature (LST) variation. Thus, this study was carried out to explore the impact of the LULC change on LST in the Cameron Highlands from 2009 to 2019 using remote sensing images acquired from Landsat 7 ETM+, Landsat 8 Operational Land Imager (OLI/TIRS), and Moderate Resolution Imaging Spectroradiometer (MODIS) 11A Thermal sensors. A split-window algorithm was applied to Landsat 8 images (2013–2019) to derive the LST. Air temperature data of the study area were also obtained to cross-validate data sources. Based on the validation results, the accuracy of LULC and LST outputs were more than 94.6% and 80.0%, respectively. The results show that the current trend of urban growth continues at a rate of 0.16% per year, and the area experienced an LST increase of 2 °C between 2009 and 2019. This study is crucial for land planners and environmentalists to understand the impacts of LULC change on LST and to propose appropriate policy measures to control development in Cameron Highlands.

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TOWARDS A REMOTE SENSING BASED ASSESSMENT OF LAND SUSCEPTIBILITY TO DEGRADATION: EXAMINING SEASONAL VARIATION IN LAND USE-LAND COVER FOR MODELLING LAND DEGRADATION IN A SEMI-ARID CONTEXT

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-iii-8-137-2016 ◽

2016 ◽

Vol III-8 ◽

pp. 137-144 ◽

Cited By ~ 3

Author(s):

Gofamodimo Mashame ◽

Felicia Akinyemi

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Degradation ◽

Landsat 8 ◽

Land Use Land Cover ◽

Bare Land ◽

Level I ◽

The Impact ◽

Semi Arid

Land degradation (LD) is among the major environmental and anthropogenic problems driven by land use-land cover (LULC) and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS) techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO) International Organization of Standardization (ISO) code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22%) of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

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TOWARDS A REMOTE SENSING BASED ASSESSMENT OF LAND SUSCEPTIBILITY TO DEGRADATION: EXAMINING SEASONAL VARIATION IN LAND USE-LAND COVER FOR MODELLING LAND DEGRADATION IN A SEMI-ARID CONTEXT

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iii-8-137-2016 ◽

2016 ◽

Vol III-8 ◽

pp. 137-144 ◽

Cited By ~ 1

Author(s):

Gofamodimo Mashame ◽

Felicia Akinyemi

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Degradation ◽

Landsat 8 ◽

Land Use Land Cover ◽

Bare Land ◽

Level I ◽

The Impact ◽

Semi Arid

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The impact of land use/land cover change on ecosystem services in the central highlands of Ethiopia

Ecosystem Services ◽

10.1016/j.ecoser.2016.11.010 ◽

2017 ◽

Vol 23 ◽

pp. 47-54 ◽

Cited By ~ 120

Author(s):

Terefe Tolessa ◽

Feyera Senbeta ◽

Moges Kidane

Keyword(s):

Land Use ◽

Ecosystem Services ◽

Land Cover ◽

Land Cover Change ◽

Land Use Land Cover ◽

Central Highlands ◽

The Impact

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

Sustainability ◽

10.3390/su10103421 ◽

2018 ◽

Vol 10 (10) ◽

pp. 3421 ◽

Cited By ~ 43

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.

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Hydrological Responses to Land Use Land Cover Changes in the Fincha’a Watershed, Ethiopia

Land ◽

10.3390/land10090916 ◽

2021 ◽

Vol 10 (9) ◽

pp. 916

Author(s):

Urgessa Kenea ◽

Dereje Adeba ◽

Motuma Shiferaw Regasa ◽

Michael Nones

Keyword(s):

Land Use ◽

Land Cover ◽

Local Governments ◽

Swat Model ◽

Landsat 8 ◽

Land Use Land Cover ◽

Hydrological Response ◽

African Countries ◽

Hydrological Responses ◽

Basin Scale

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.

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Impacts of future land use and land cover change on mid-21<sup>st</sup>-century surface ozone air quality: Distinguishing between the biogeophysical and biogeochemical effects

10.5194/acp-2019-824 ◽

2019 ◽

Author(s):

Lang Wang ◽

Amos P. K. Tai ◽

Chi-Yung Tam ◽

Mehliyar Sadiq ◽

Peng Wang ◽

...

Keyword(s):

Land Use ◽

Air Quality ◽

Land Cover ◽

Dry Deposition ◽

Surface Ozone ◽

Boreal Summer ◽

Ozone Pollution ◽

Lulc Change ◽

Lulc Changes ◽

The Impact

Abstract. Surface ozone (O3) is an important air pollutant and greenhouse gas. Land use and land cover (LULC) is one of the critical factors influencing ozone, in addition to anthropogenic emissions and climate. LULC change can on the one hand affect ozone biogeochemically, i.e., via dry deposition and biogenic emissions of volatile organic compounds (VOCs). LULC change can on the other hand alter regional- to large-scale climate through modifying albedo and evapotranspiration, which can lead to changes in surface temperature, hydrometeorology and atmospheric circulation that can ultimately impact ozone biogeophysically over local and remote areas. Such biogeophysical effects of LULC on ozone are largely understudied. This study investigates the individual and combined biogeophysical and biogeochemical effects of LULC on ozone, and explicitly examines the critical pathway for how LULC change impacts ozone pollution. A global coupled atmosphere–chemistry–land model is driven by projected LULC changes from the present day (2000) to future (2050) under RCP4.5 and RCP8.5 scenarios, focusing on the boreal summer. Results reveal that when considering biogeochemical effects only, surface ozone is predicted to have slight changes by up to 2 ppbv maximum in some areas due to LULC changes. It is primarily driven by changes in isoprene emission and dry deposition counteracting each other in shaping ozone. In contrast, when considering the integrated effect of LULC, ozone is more substantially altered by up to 6 ppbv over several regions, reflecting the importance of biogeophysical effects on ozone changes. Furthermore, large areas of these ozone changes are found over the regions without LULC changes where the biogeophysical effect is the only pathway for such changes. The mechanism is likely that LULC change induces a regional circulation response, in particular the formation of anomalous stationary high-pressure systems, shifting of moisture transport, and near-surface warming over the middle-to-high northern latitudes in boreal summer, owing to associated changes in albedo and surface energy budget. Such temperature changes then alter ozone substantially. We conclude that the biogeophysical effect of LULC is an important pathway for the influence of LULC change on ozone air quality over both local and remote regions, even in locations without significant LULC changes. Overlooking the impact of biogeophysical effect may cause evident underestimation of the impacts of LULC change on ozone pollution.

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Land Use/Land Cover Mapping of Sambar Watershed by Using Remote Sensing and GIS

International Journal of Current Microbiology and Applied Sciences ◽

10.20546/ijcmas.2021.1009.066 ◽

2021 ◽

Vol 10 (9) ◽

pp. 578-585

Author(s):

B. Varpe Shriniwas D. Payal Sandip

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Remote Sensing And Gis ◽

Rapid Expansion ◽

Water Bodies ◽

Land Cover Mapping ◽

Fallow Land ◽

Land Use Land Cover ◽

Barren Land

In the present study, an effort has been made to study in detail of Land Use/Land Cover Mapping for Sambar watershed by using Remote Sensing and GIS technique was carried out during the year of 2020-2021 in Parbhani district. In this research the Remote Sensing and Geographical Information system technique was used for identifying the land use/land cover classes with the help of ArcGIS 10.8 software. The Sambar watershed is located in 19º35ʹ78.78˝ N and 76º87ʹ88.44˝ E in the Parbhani district of Marathwada region in Maharashtra. It is covered a total area 97.01 km2. The land use/land cover map and its classes were identified by the Supervised Classification Method in ArcGIS 10.8 software by using the Landsat 8 satellite image. Total six classes are identified namely as Agricultural area, Forest area, Urban area, Barren land, Water bodies and Fallow land. The Agricultural lands are well distributed throughout the watershed area and it covers 4135 ha. (43 per cent). Forest occupies 502 ha area and sharing about 5 per cent of the total land use land cover of the study area. The Urban land occupies 390 ha. area (4 per cent) and there was a rapid expansion of settlement area. Barren land occupies 3392 ha. area (35 per cent). A water bodies occupy 630 ha. area (6 per cent) and the Fallow land occupies 650 ha (7 per cent) but well-developed dendritic drainage pattern and good water availability is in the Sambar watershed.

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