Land use and cover change and influencing factor analysis in the Shiyang River Basin,China

Land use and cover change(LUCC)is the most direct manifestation of the interaction between anthropological activities and the natural environment on Earth's surface,with significant impacts on the environment and social economy.Rapid economic development and climate change have resulted in significant changes in land use and cover.The Shiyang River Basin,located in the eastern part of the Hexi Corridor in China,has undergone significant climate change and LUCC over the past few decades.In this study,we used the random forest classification to obtain the land use and cover datasets of the Shiyang River Basin in 1991,1995,2000,2005,2010,2015,and 2020 based on Landsat images.We validated the land use and cover data in 2015 from the random forest classification results(this study),the high-resolution dataset of annual global land cover from 2000 to 2015(AGLC-2000-2015),the global 30 m land cover classification with a fine classification system(GLC_FCS30),and the first Landsat-derived annual China Land Cover Dataset(CLCD)against ground-truth classification results to evaluate the accuracy of the classification results in this study.Furthermore,we explored and compared the spatiotemporal patterns of LUCC in the upper,middle,and lower reaches of the Shiyang River Basin over the past 30 years,and employed the random forest importance ranking method to analyze the influencing factors of LUCC based on natural(evapotranspiration,precipitation,temperature,and surface soil moisture)and anthropogenic(nighttime light,gross domestic product(GDP),and population)factors.The results indicated that the random forest classification results for land use and cover in the Shiyang River Basin in 2015 outperformed the AGLC-2000-2015,GLC_FCS30,and CLCD datasets in both overall and partial validations.Moreover,the classification results in this study exhibited a high level of agreement with the ground truth features.From 1991 to 2020,the area of bare land exhibited a decreasing trend,with changes primarily occurring in the middle and lower reaches of the basin.The area of grassland initially decreased and then increased,with changes occurring mainly in the upper and middle reaches of the basin.In contrast,the area of cropland initially increased and then decreased,with changes occurring in the middle and lower reaches.The LUCC was influenced by both natural and anthropogenic factors.Climatic factors and population contributed significantly to LUCC,and the importance values of evapotranspiration,precipitation,temperature,and population were 22.12%,32.41%,21.89%,and 19.65%,respectively.Moreover,policy interventions also played an important role.Land use and cover in the Shiyang River Basin exhibited fluctuating changes over the past 30 years,with the ecological environment improving in the last 10 years.This suggests that governance efforts in the study area have had some effects,and the government can continue to move in this direction in the future.The findings can provide crucial insights for related research and regional sustainable development in the Shiyang River Basin and other similar arid and semi-arid areas.

Trends of Land Use and Land Cover Change in the Savannah Ecological of the Protected Area Reserve Partielle de Dosso, Niger

Information on the dynamics of savannah is important to a country's plan to overcome the problems of uncontrolled development and environmental hazards. Taking the reserve partielle de Dosso, Niger as the case study area, this paper analyzed the long-term land use land cover change from 2002 to 2022. Satellite images were processed by using Google Earth Engine (GEE). Therefore, four major land cover classes were identified based on spectral characteristics of Land sat, namely, built-up, vegetation, cropland, bare land and water. The result revealed that barren and built-up areas increased at the expense of vegetation and water. From the four major land use land cover the large area is covered by vegetation which comprises about 192963.5 hectares followed by cropland and water consisting of 32506.43 and 1596.4 hectares respectively. The built-up area gained substantial area (most) during the study period. The reduction in some of the land cover/uses underlines the dangerous trend of the pressure poised by population growth and the changing functionality. Land cover change is influenced by a variety of societal factors operating on several spatial and temporal levels. The area estimates and spatial distributions of the LULC classes produced from the current study will assist local authorities, managers, and other stakeholders in decision-making and planning regarding forest land cover and uses.

Overview of Land Use/Cover Change Dynamic Monitoring Methods

With the emergence of global environmental change issues,Land Use/Cover Change(LUCC)issues have received increasing attention.Therefore,the dynamic monitoring of LUCC has also become very important.In this paper,preliminary exploration was made to the research progress on the dynamic monitoring technologies for LUCC as well as their advantages and disadvantages,and prediction was made to the development trend of future monitoring technology.

Monitoring Land Use and Infrastructure Changes in Industrial Complex Using Geo-Informatics Technology in Gujarat State, India

In the present study, detailed investigations have been carried out in Petroleum, Chemicals and Petrochemical Investment Region (PCPIR) area in Vygra and Bharuch Talukas in Bharuch district of Gujarat State. Indian Remote Sensing Satellite (IRS-P6) LISS-III, LISS-IV and CARTOSAT digital data covering PCPIR area in Bharuch district for the period of January & February of 2011, 2012 and 2013 was analyzed for land use/land cover mapping and monitoring the changes in land use. Various thematic land use/land cover maps were prepared and GIS database for various thematic layers have been generated using satellite and ground based information. The results indicate that the major land use in the PCPIR area is agriculture with crop lands ranging from 61 to 63 per cent of the total area. Crop land has decreased from 64.7% during 2011 to 62.7% during 2013 in the PCPIR region. Area under plantations in PCPIR area has also decreased from 5.5% during 2011 to 5.2% during 2012. The industrial area has increased from 6.0% to 7.6% of the total area of the PCPIR region. The total built-up area (industries & village area) has increased from 7.1% during 2011 to 8.7% during 2013. Tree plantations in the area of around 42 ha were carried out by GIDC during 2012 and 2013 to increase the green cover in the PCPIR area.

Land Use Land Cover Analysis for Godavari Basin in Maharashtra Using Geographical Information System and Remote Sensing

The dynamic transformation of land use and land cover has emerged as a crucial aspect in the effective management of natural resources and the continual monitoring of environmental shifts. This study focused on the land use and land cover (LULC) changes within the catchment area of the Godavari River, assessing the repercussions of land and water resource exploitation. Utilizing LANDSAT satellite images from 2009, 2014, and 2019, this research employed supervised classification through the Quantum Geographic Information System (QGIS) software’s SCP plugin. Maximum likelihood classification algorithm was used for the assessment of supervised land use classification. Seven distinct LULC classes—forest, irrigated cropland, agricultural land (fallow), barren land, shrub land, water, and urban land—are delineated for classification purposes. The study revealed substantial changes in the Godavari basin’s land use patterns over the ten-year period from 2009 to 2019. Spatial and temporal dynamics of land use/cover changes (2009-2019) were quantified using three Satellite/Landsat images, a supervised classification algorithm and the post classification change detection technique in GIS. The total study area of the Godavari basin in Maharashtra encompasses 5138175.48 hectares. Notably, the built-up area increased from 0.14% in 2009 to 1.94% in 2019. The proportion of irrigated cropland, which was 62.32% in 2009, declined to 41.52% in 2019. Shrub land witnessed a noteworthy increase from 0.05% to 2.05% over the last decade. The key findings underscored significant declines in barren land, agricultural land, and irrigated cropland, juxtaposed with an expansion in forest land, shrub land, and urban land. The classification methodology achieved an overall accuracy of 80%, with a Kappa Statistic of 71.9% for the satellite images. The overall classification accuracy along with the Kappa value for 2009, 2014 and 2019 supervised land use land cover classification was good enough to detect the changing scenarios of Godavari River basin under study. These findings provide valuable insights for discerning land utilization across various categories, facilitating the adoption of appropriate strategies for sustainable land use in the region.

Land Use and Land Cover Change Detection in the Saudi Arabian Desert Cities of Makkah and Al-Taif Using Satellite Data

Land use/land cover (LULC) changes have become a central issue in current global change and sustainability research. Saudi Arabia has undergone significant change in land use and land cover since the government embarked on a course of intense national development 30 years ago, as a result of huge national oil revenues. This study evaluates LULC change in Makkah and Al-Taif, Saudi Arabia from 1986 to 2013 using Landsat images. Maximum likelihood and object-oriented classification were used to develop LULC maps. The change detection was executed using post-classification comparison and GIS. The results indicated that urban areas have increased over the period by approximately 174% in Makkah and 113% in Al-Taif. Analysis of vegetation cover over the study area showed a variable distribution from year to year due to changing average precipitation in this environment. Object-based classification provided slightly greater accuracy than maximum likelihood classification. Information provided by satellite remote sensing can play an important role in quantifying and understanding the relationship between population growth and LULC changes, which can assist future planning and potential environmental impacts of expanding urban areas.

Evaluating Land Use/Land Cover Change and Its Socioeconomic Implications in Agarfa District of Bale Zone, Southeastern Ethiopia

A systematic analysis of land use/cover change is so decisive to exactly understand the extent of change and take essential measures to curb down the rate of changes and protect the land cover resources sustainably. This land use/land cover change study was conducted in Agarfa district of Bale zone, Oromia Regional State, Southeastern Ethiopia. The objectives of this study were to evaluate the trends, drivers and its socio-economic and environmental implication in study area. A descriptive research method was employed to achieve the intended objectives of the study. In the three years (1976, 1995, and 2014) Landsat Satellite images and socio-economic survey were the main data sources for this study. ERDAS Imagine and Arch-GIS tools were used to classify and generate land use/land cover maps of the study area. Survey questionnaires, key informant interviews, and field observation were employed to obtain information on drivers and its socio-economic and environmental implication in the district. The results show that the land use/land cover of the study area had changed dramatically during the period of 38 years. A rapid loss of forest land and shrub land cover in the landscape took place between 1976 and 2014. Conversely, agriculture and grazing lands were increased by 30% and 42% respectively at the expense of the lost land use/land cover types. Forest land is the most converted cover type during the entire study period. In the 38 years, forest lands diminished by over 65% of the original forest cover that was existed at the base year (1976). Local climate change, declining agricultural productivity and livestock quantity and quality and scarcity of fuel wood and constructional materials were some of the socio-economic and livelihood impacts of land use and land cover change of the study area. Thus, this finding affords information to land users and policy makers on extent of the change and social forces leading to this changes and its subsequent implication on local socio-economic and environmental conditions of the study area.

Evaluation of Land Use &Land Cover Change Using Multi-Temporal Landsat Imagery: A Case Study Sulaimaniyah Governorate, Iraq

Land use & land cover change detection in rapid growth urbanized area have been studied by many researchers and there are many works on this topic. Commonly, settlement sprawl in area depends on many factors such as eco-nomic prosperity and population growth. Iraq is one of the countries which witnessed rapid development in the settlement area. Remote sensing and geographic information system (GIS) are analytical software technologies to evaluate this familiar worldwide phenomenon. This study illustrates settlement development in Sulaimaniyah Governorate from 2001 to 2017 using Landsat satellite imageries of different periods. All images had been classified using remote sensing software in order to proceed powerful mapping of land use classification. Maximum likelihood method is used in the accurately extracted solution information from geospatial imagery. Landsat images from the study area were categorized into four different classes. These are: forest, vegetation, soil, and settlement. Change detection analysis results illustrate that in the face of an explosive demographic shift in the settlement area where the record + 8.99 percent which is equivalent to 51.80 Km2 over a 16-year period and settlement area increasing from 3.87 percent in 2001 to 12.86 percent in 2017. Accuracy assessment model was used to evaluate (LULC) classified images. Accuracy results show an overall accuracy of 78.83% to 90.09% from 2001 to 2017 respectively while convincing results of Kappa coefficient given between substantial and almost perfect agreements. This study will help decision-makers in urban plan for future city development.

Estimation of Land Use Changes in Tan Rai Bauxite Mine by Multi-Variants Change Vector Analysis (MCVA) on Multi-Temporal Remote Sensing Data

The Tan Rai Bauxite Project, which exploits a large bauxite mine in Lam Dong province, Vietnam has been in operation since 2012. In addition to the economic efficiency of the project, bauxite mining and processing uses a large area arable land and affect the regional environment. Remote sensing technology is increasingly widely used in many purposes in monitoring the changes of environment and resources, including land use change with high accuracy, giving managers more information to monitor the exploitation and use process of land resource. This study used a Change Vector Analysis (CVA) method of analysis on various remote sensing data sources to monitor the process of land exploitation and restoration of the Tan Rai Bauxite project. High-resolution remote sensing images were used as diverse as SPOT-5, VNREDSat-1, Google Earth from 2013 to 2019 to demonstrate the ability of the MCVA method to combine many other types of remote sensing images together. The results of fluctuation analysis were validated by 200 random points in the study area, and the accuracy of result is more than 90%. The results of land use change statistics were also compared with the annual data of Tan Rai Bauxite Factory. From this study, it can be concluded that the MCVA analysis method can quickly detect land use change areas and can combine many different image sources with a high accuracy. In addition, it also provides statistics of mining areas and restored areas, thereby assisting managers in monitoring the operation of the mine.

Land cover changes in the rural-urban interaction of Xi’an region using Landsat TM/ETM data

Landsat ETM/TM data and an artificial neural network （ANN） were applied to analyse the expansion of the city of Xi＇an and land use/cover change of its surrounding area between 2000 and 2003. Supervised classification and normalized difference barren index （NDBI） were used respectively to retrieve its urban boundary. Results showed that the urban area increased by an annual rate of 12.3%, with area expansion from 253.37 km^2 in 2000 to 358.60 km^2 in 2003. Large areas of farmland in the north and southwest were converted into urban construction land. The land use/cover changes of Xi＇an were mainly caused by fast development of urban economy, population immigration from countryside, great development of infrastructure such as transportation, and huge demands for urban market. In addition, affected by the government policy of “returning farmland to woodland”, some farmland was converted into economic woodland, such as Chinese goosebeerv garden, vineyard etc.

Remote sensing classification of western Sierra Leone using landsat TM and ETM+

The study examines the changes of land cover/use resources for the period under investigation.An unsupervised vegetation classification is being performed that provides five distinctive classes and thus assesses these changes in five broad land cover classes-high/moist forests,forest regrowth,mixed savanna,bare land/ grass and water.The remote sensing images used in this work are both images of TM and ETM+in different time periods(1986 to 2001)to determine land cover/use changes.A fairly accuracy report is recorded after performing the unsupervised classification,which shows vegetation has been depleted for over the years.Changes created are mostly human and to a lesser extent environment.Human activities are mainly encroachment thus altering the landscape through activities such as population growth,agriculture,settlements,etc.and environment due to some perceive climatic changes.This vegetation classification highlights the importance to acquire and publish information about the country's partial vegetation cover and vegetation change including vegetation maps and other basic vegetation influencing factors,leading to an understanding of its evolution for a period.

Risk Assessment and Change Monitoring of Soil and Water Loss in Ruijin City Based on RS and GIS

The land use information extraction technology for the high-resolution remote sensing images of the Gaofen No. 1 satellite was construc-ted. According to the spectral, band, texture and shape attributes, land use types were divided, and the changing laws of land use types were ana- lyzed. Aftewards,according to the Table of Grading Standard of Sooil Erosion Intensity（SL190-96）,as well as vegetation coverage index NDVI slope, the risks of soil and water loss were assessed. Meanwhile, the level, scale, location and scope of changes in the risks of soil and water loss were monitored by using spatial visualization and spatial statistical techniques. The results showed that the area of areas without soil erosion and moderate soil erosion areas decreased obviously from 2015 to 2017, and the decreases were up to 22.929 3 and 13.626 3 km2 respectively. The ar-ea of mild soil erosion areas increased fast, and the increase reached 31.140 0 km2. The area of extremely strong soil erosion areas increased by 7.267 4 km2. In the city, moderate and strong soil erosion areas reduced, while extremely strong soil erosion patches increased fast, which was mainly related to road construction and construction and development of orchards. The extremely strong soil erosion areas were distributed in the shape of a banded loop, surrounded the suburbs of the city, and shrank towards the center of Ruijin City. The constructed technology to monitor the changes in land use and soil and water loss, as well as the changing laws of land use and soil and water loss provide the theoretical basis and plan-ning basis of soil and water conservation for urban planning departments and soil and water conservation departments.

基于Landsat的黄河三角洲地区土地利用变化动态监测

土地利用的动态监测及其影响因子的分析,有助于了解地区发展的一般特征及趋势,提高城市用地规划的科学性与合理性。本文以黄河三角洲为研究区,基于RS技术,利用3期Landsat遥感影像(2009、2015和2019年),采用监督分类方法提取了黄河三角洲地区的土地利用类型,依据提取结果对10年间土地利用类型进行了动态变化监测与分析。结果表明,2009—2019年期间,盐田、建筑用地和耕地的面积持续增加,分别增加了952.56、605.99和302.54 km^(2);盐碱地、植被、滩涂与水产池塘等地类面积持续减少,分别减少了1033.56、377.53、110.77和336.14 km^(2);其他地类面积或有增减,变化不大。

基于Landsat数据的普洱市土地利用变化动态监测

以普洱市2005年和2014年Landsat数据为数据源,将研究区分为林地、农地、灌草地、水域、建设用地5类,采用神经网络方法提取2个时期的土地利用数据并进行动态监测。最终得出普洱市土地利用变化情况:林地面积减少10.83%,农地面积减少2.50%,灌草地面积增加10.3%,水域面积减少0.03%,建设用地面积增加0.38%。在土地利用变化结果的基础上,进一步分析了土地利用覆盖动态度以及土地利用变化原因。

Remote Sensing and GIS Application on Forest Resource Mapping and Monitoring in Bulolo District, Morobe Province

Forest resources monitoring are particularly challenging for tropical forest due to their diverse composition and structure and a wide range of stakeholder’s expectations and requirement. New monitoring approaches and control policies directions are required to meet these different challenges. For the past decades, much of the focus of formal forest monitoring and management policy in Papua New Guinea (PNG) has been on large scale conventional harvesting to meet national requirements for economic development, with little attention given to community or small area forest management and monitoring. The current management is considered to be unsustainable and, as forest resources from primary forests are exhausted. This has resulted in extensive cutover forest areas being left to degrade over time. Forest reserve has suffered seriously and if the present trend of deforestation continues;it is just a matter of time when the whole reserve would have been converted to a bare ground. This study therefore examined the integration of remote sensing (RS) and geographic information system (GIS) application on forest resource mapping and monitoring in Bulolo district, Morobe province. Landsat satellite imageries for 1992, 2002 and 2014 were used to classify and identify forest changes through change detection techniques. A GIS database of land use categories and their location within 24 years (1992-2014) were generated and analysed with the aid of GIS analytical functions. This function includes area calculation, overlay, and image differencing, supervised classifications, cross tabulations and map representation. The result shows that population growth (anthropogenic) factors among communities around the natural forest imposes a lot of pressure on the natural forest resources. This should also include consideration of the future usage capacity of the forest resources as well as development of the capacity of local forest owner communities to participate in small scale forest management and utilization.

基于Landsat卫星土地利用变化监测——以鸡冠区为例

为快速获取土地利用类型的变化信息,科学合理利用和保护土地资源,文章以黑龙江省鸡西市鸡冠区为研究对象,对该区域土地利用类型进行变化监测,并对比了几种常用监督分类算法的分类精度。最终得出最大似法适合本区域土地利用分类,将分类结果对比发现,2017年较2011年:建设用地与植被面积有所增加,耕地与水域的面积有所减少。

A review of land use/land cover change mapping in the China-Central Asia-West Asia economic corridor countries

Large-scale projects,such as the construction of railways and highways,usually cause an extensive Land Use Land Cover Change(LULCC).The China-Central Asia-West Asia Economic Corridor(CCAWAEC),one key large-scale project of the Belt and Road Initiative(BRI),covers a region that is home to more than 1.6 billion people.Although numerous studies have been conducted on strategies and the economic potential of the Economic Corridor,reviewing LULCC mapping studies in this area has not been studied.This study provides a comprehensive review of the recent research progress and discusses the challenges in LULCC monitoring and driving factors identifying in the study area.The review will be helpful for the decision-making of sustainable development and construction in the Economic Corridor.To this end,350 peer-reviewed journal and conference papers,as well as book chapters were analyzed based on 17 attributes,such as main driving factors of LULCC,data collection methods,classification algorithms,and accuracy assessment methods.It was observed that:(1)rapid urbanization,industrialization,population growth,and climate change have been recognized as major causes of LULCC in the study area;(2)LULCC has,directly and indirectly,caused several environmental issues,such as biodiversity loss,air pollution,water pollution,desertification,and land degradation;(3)there is a lack of well-annotated national land use data in the region;(4)there is a lack of reliable training and reference datasets to accurately study the long-term LULCC in most parts of the study area;and(5)several technical issues still require more attention from the scientific community.Finally,several recommendations were proposed to address the identified issues.

基于耕地资源质量分类监测的土壤条件变化对粮食产量的影响——以河南省兰考县为例

为突出土壤条件变化对粮食产量的影响,采用趋势分析法和对比分析法,以兰考县耕地资源质量分类监测工作为例,分析土壤监测样点不同年份的土壤条件变化对当地粮食产量造成的影响。研究表明,土壤有机质含量的增加和土壤pH在合理范围内的增加都能够提升粮食产量。建议以测土配方施肥为基础,增加有机肥的使用量,提升土壤有机质含量,并针对当地土壤的实际情况和主要作物类型,提出有针对性的改良土壤pH的措施,以提升粮食产量。

Spatial heterogeneity of the driving forces of cropland change in China

By using digital satellite remote sensing data acquired in 1987―1989 and 1999―2000 and GIS combined with the natural and socio-economic data, this paper drew an integrated zonation of the cropland change and its driving forces in China. The results indicated that the cropland change in the study period was constrained by geographical factors and driven by cli-mate change as well as socio-economic system. Moreover, the regional differences of the drivers for cropland change were significant. In the midwest of China, natural condition changes and geographical background were the main constraints and drivers, while in Eastern China, social and economic changes and economic policies were the main driving forces. The cropland loss was nationwide. The dominant factors to cause this decrease included buildup of developing area to attract foreign capital and technologies, changes of industry structure due to urban in-fluence, the change of employment notions thanks to living standard improvement, rapid ur-banization due to the expansion of cities and towns, the diminished farming net income partly because of the global warming effects, and the rapid economic growth stimulated by the con-venient transportation system. These factors interact and interdepend with each other to cause the cropland loss in China recently. The reasons for the increase of cropland were primarily the cultivation and deforestation by the farmers who want to increase income. This study on the mechnism of LUCC relied on the cropland change integrated classification considering the natural or human factors both inside and outside the region, which provides a new approach to study the integrated regionalization and LUCC mechanism.

动态监测与业务管理双向驱动的日常国土变更调查技术体系研究

自然资源管理日常业务工作分散在不同部门,存在遥感监测变化与日常业务管理工作脱节、实地核查重复、工序流程重复等问题。通过统筹日常业务流程与调查监测使之协调统一,开展基于自然资源业务的日常变更调查方法研究,实现监测类型与业务代码的关联,推动年度变更调查向日常变更调查转变,利用统一的监测平台,以日常业务流程结果认定涉及变化的图斑地类,形成动态监测与业务管理双向驱动的日常国土变更调查方法。