Advances in Understanding Landscape Influences on Freshwater Habitats and Biological Assemblages

Abstract. The terms ‘land use’ and ‘land cover’ typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

The study aimed to assess the changes that have occurred in land use and land cover within the Maasai Mara landscape using remote sensed data from 1997 to 2017; examine the elephant distribution in relation to land use and land cover changes within the Mara landscape and to determine changes in elephant home ranges in relation to Land use and cover changes in the Mara landscape. In examining the land use and land cover changes on the elephant ranges and distribution, an integrated methodological approach was employed in which the changes that have taken place within the study area over a period of 20 years was determined by analysis involving a 10-year changes in land use and land cover using three epochs from 1997, 2007 and 2017 to generate six land use classes. The Maasai Mara Landscape (MML) supports one of the richest wildlife populations remaining on earth but over the last century, has experienced transformation notably through conversion of former rangelands into croplands. Elephants have both temporal and spatial requirements, which if not provided, render them vulnerable to the land-use practices. The study assessed land use and vegetation cover changes that have occurred and their effects on the elephant movements and distribution within the MML using an integrated methodological approach. The analysis revealed changes in land use and land cover classes over a period of 20 years for the three epochs, from 1997, 2007 and 2017. Elephant’s distribution has been restricted to areas of high vegetation densities within specific habitats hence accelerating the rate of habitat destruction and degradation due to their high densities. These changes have drastically reduced forage for elephants necessitating them to travel longer distances out of their home range in search for food. Human beings have caused land use and cover changes which have detrimental impacts on the ecosystem and ecosystem services. The Maasai Mara landscape supports one of the richest wildlife populations remaining on earth but over the last century, it has experienced land transformation notably through conversion of former rangelands used mainly for tourism and production of grains such as wheat. Land outside the national parks and the reserve is important to the future of elephant existence in Kenya. Little is known about how human occupation on these landscapes negatively affects elephants (Loxodonta africana) habitats, movement and ranges. This has been confirmed by the current continuous demarcation/fencing of land in most areas in Narok County. Elephants like other landscape species, have both temporal and spatial requirements, which if not provided, will render them vulnerable to the land use practices of people. The study aimed to assess the changes that have occurred in land use and land cover within the Maasai Mara landscape using remote sensed data from 1997 to 2017; examine the elephant distribution in relation to land use and land cover changes within the Mara landscape and to determine changes in elephant home ranges in relation to Land use and cover changes in the Mara landscape. The paper describes the different changes that have taken place within the MML and how these changes have affected elephant populations, their trend and distribution within the MML. In examining the land use and land cover changes on the elephant ranges and distribution, an integrated methodological approach was employed in which the changes that have taken place within the study area over a period of 20 years was determined by analysis involving a 10-year changes in land use and land cover using three epochs from 1997, 2007 and 2017 to generate six land use classes. The study found out that there were significant changes of various classes across the years. Forest, water and open shrubs coverages decreased from 1997 to 2017. Classification noted a serious problem within the study area of continuous increase of bare ground coverage across the study years. Elephant populations have been increasing within the area .at an annual rate of 2.69%. The animals are distributed all over the landscape. Distribution of elephants has been restricted to high densities within a specific habitat hence accelerating rate of habitat destruction and degradation due to their high densities within a specific habitat. These changes have reduced drastically foliage for elephants thus necessitating them to travel longer distances in search and as a result increases elephant home ranges.

Variation in ecosystem services across an urbanization gradient: A study of terrestrial carbon stocks from Changzhou, China

In recent years, land use and land cover plays a pivotal role in global environmental change. Under these circumstances,the need of a new dimension for detecting land use and cover is getting more imperative for conservation and effectivemanagement of land use and cover types. Importantly, the use of information technology to support decision making indetecting land use and cover is essential and recent. One of the technologies used is Airborne Remote Sensing. Theobjective of this study is to identify, quantify, classify and map land use and land cover mapping in Setiu, Terengganuusing UPM-APSB’s AISA airborne hyperspectral remote sensing. Detection of land use and cover was performed usingairborne hyperspectral imaging data taken on 20 April 2006 with the support of existing land use and cover maps. Thesize of the study area is 100 ha. The image was displayed in ENVI 4.0 Software using bands 202217 (RGB)combination. The data were then enhanced and classified for different land use and cover classes. From the dataanalysis, the image can be classified into eight classes. The classes are 2-3 years old oil palm plantation, 4-5 years oldoil palm plantation, young (3-4 years old) rubber plantation, matured (15-17 years old) rubber plantation, vegetationcrops, open area, road and river. The land use and land cover classes area distribution of the plots under study in Setiu,Terengganu were 4.18 ha, 8.58 ha, 6.26 ha, 70.43 ha, 2.98 ha, 2.31 ha, 2.78 ha, and 2.48 ha. Overall, the classificationaccuracy of interpretation of the airborne imagery for land use and cover in Setiu, Terengganu is 89.51 and kappacoefficient is 0.86. This study shows that, airborne hyperspectral remote sensing technique is capable in identifying,quantifying, classifying and mapping land use and cover in Setiu, Terengganu, hence a good decision support tool inland use and cover planning and management.

Effects of land use and cover change on terrestrial carbon stocks in urbanized areas: a study from Changzhou, China

The Tibetan Plateau (TP) is an important ecological security barrier for China and, indeed, for all Asia. Land use and land cover changes in the plateau not only affect the ecological environment and regional development of the plateau itself but also affect the stability and economic development of ecosystems in eastern China and other parts of Asia. This paper is based on an examination of the achievements of land use and cover change in the TP and a reanalysis of data including that of Climate Change Initiative Land Cover from 1992 to 2015; land use data provided by the Resource and Environmental Science Data Center of the Chinese Academy of Sciences for 1995, 2000, 2010 and 2015; and statistical data from Qinghai and Tibet. The paper analyzes the overall characteristics of land use and land cover changes in the TP and the spatial and temporal processes and their driving forces of land use and land cover change in typical regions and land types. This research is important not only for land change science and global change research but also for the promotion of the plateau and its adjacent areas. In recent decades, research has shown that the land use and land cover structure of the TP is stable, and the proportion of first-level land use type change was less than 7% from 1992 to 2015. Most of these changes are single time changes, with multiple land change occurring only in 1.85% of the total change area. The quality of land cover has been improved in areas where no land type change occurred. The Normalized Difference Vegetation Index (NDVI) showed an increasing trend in 24.45% of the area and a decreasing trend in only 1.31% of the area. The area of cultivated land, forest, grassland, wetland, and construction land on the plateau has increased, whereas bare land, glacier, and snow cover area has decreased. In most parts of the TP, the quality of alpine grassland has improved; however, in some areas, it has degraded at a local scale. Most of the woodland has recovered well after phased changes. Prior to 1980, there was a rapid increase in cultivated land area, but this has since become stable with only minor increases. However, the utilization intensity of cultivated land has increased significantly in recent years. Construction land has expanded significantly, and the recent growth rate has accelerated since 2010. Both the increasing speed of change and the construction land area in Qinghai Province are higher than in Tibet. There has been a general trend of a slight decrease in bare land change. In densely populated areas in the Yellow River-Huangshui River Valley and the One-River-Two-Tributaries area, land types that are closely related to human utilization such as construction land, cultivated land, and artificial woodland have undergone obvious changes. In pastoral areas, such as the Northern Tibetan Plateau and the Source Regions of The Three Rivers, overgrazing and ecological construction have significantly affected land cover. In the Qomolangma National Nature Preserve, land use types are diverse; changes are complex; and land cover is more sensitive to both climate change and human activity. There are limitations to the study of land change in the plateau, such as the difficulty of meeting the needs of ecological construction with existing data and the lack of in-depth understanding of the process of land use change and its environmental effects. Field monitoring and remote sensing techniques must be strengthened in order to clarify the process of land use intensity change and its impact on the ecological environment of the TP. These improvements will better serve the construction of an ecological security barrier and the sustainable development of the region.

Introduction: Landscape changes can be monitored using geotechnologies through land use and land cover management over time, which helps identify and understand transformations in the landscape and supports decision-making processes. This study aims to analyze land use and cover change in the Portal do Sertão Identity Territory, Bahia, and to relate the possible causes that have currently induced such changes. This territory, located in the Caatinga biome, has its economic activities mainly concentrated in the primary and tertiary sectors. Remote Sensing (RS) and Geographic Information Systems (GIS) were employed to monitor changes in land use and cover in this territory from 1985 to 2022, using images from the MapBiomas Collection 8.0. During the study period, there was a reduction in the area used for agriculture and livestock and a significant increase in urbanization, with an urban area growth of more than 380%. Additionally, water bodies also expanded, mainly due to the construction of the Pedra do Cavalo Hydroelectric Plant in 1985, which resulted in a larger flooded area. Forest formations, although fluctuating over the years, were negatively impacted by agricultural expansion and urbanization. Therefore, the use of geotechnologies such as RS and GIS proves to be an effective tool for environmental monitoring, enabling the identification and management of land use changes and contributing to the mitigation of environmental impacts. Objective: The aim of this study is to investigate land use and land cover changes in the Portal do Sertão Identity Territory, in order to identify the possible causes currently driving these transformations. . Theoretical Framework: Remote Sensing (RS) is a science that maps Earth’s surface targets using sensors without direct contact. It is an essential tool for understanding and monitoring land use and land cover changes, providing critical information for decision-making from multiple perspectives. Its integration with Geographic Information Systems (GIS) enhances the spatiotemporal analysis of processes such as environmental and territorial degradation. The concept of "Identity Territory," developed by SEPLAN-BA, considers sociocultural, economic, and geographic factors for territorial organization. Institutionalized by state decrees, it divides Bahia into 27 territories to promote regional public policies. The articulation of RS, GIS, and the Identity Territory framework offers an effective approach to understanding and managing land use changes in the Portal do Sertão. Method: This study analyzed land use and land cover changes in the Portal do Sertão Identity Territory, composed of 27 municipalities in Bahia, aiming to understand the possible driving forces behind these changes. Satellite images from the MapBiomas Brazil Collection 8.0 were used for the years 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, and 2022. A GIS environment was used to reclassify the images into four classes based on the MapBiomas classification: Forest Formation, Agriculture, Urban Area, and Water Bodies. The total area per class was quantified for each year, and land use transition maps were generated for spatial analysis. Results and Discussion: The analysis revealed that between 1985 and 2022, the Portal do Sertão Identity Territory experienced significant transformations in land use and cover. There was a notable reduction in agricultural and livestock areas and a sharp increase in urban development, particularly in Feira de Santana and neighboring municipalities, driven by industrialization, public policies, and real estate expansion. Forest cover fluctuated, while water bodies increased following the construction of the Pedra do Cavalo Hydroelectric Plant in 1985. These changes reflect processes of urbanization, rural exodus, and territorial reconfiguration influenced by economic, social, and infrastructural factors. Research Implications: This research provides essential technical and spatial support for territorial planning in the region, assisting local governments and institutions in making more informed decisions based on historical land use patterns. The findings highlight the importance of integrated public policies focused on territorial planning, environmental preservation, and housing, especially in light of rapid population growth. Originality/Value: This study contributes to the literature by analyzing the drivers of land use change using open-access data from MapBiomas. Its significance lies in the integration of Remote Sensing and GIS to investigate land use trends in the Portal do Sertão over the past decades, providing strategic insights to support public policy development and more effective territorial planning.

Land cover and use are critical for climate change, water quality and use, biodiversity and soil conservation as well as important drivers of rural economic activity and the evolution of rural communities. The Land Use in Rural New Zealand (LURNZ) model is a simulation model that predicts overall shifts in land use at a national scale and then allocates those changes spatially. We create a new dataset that allows us to consider fine scale land cover and use on private rural land and land characteristics associated with those land covers and uses. Second, we produce some summary statistics on the land cover transitions that were observed from 1996 to 2002. We find some evidence that supports our simple model of the relationship between land use changes and observable land quality, and the use of Land Use Capability and slope in rules to simulate the location of changes in land use and cover and also identify some directions for future work.

How Does Changing Land Cover and Land Use in New Zealand Relate to Land Use Capability and Slope?

  Land use and land cover changes are important processes that influence the ecological integrity of wildlife dispersal areas and the dynamics of human-wildlife conflicts in rangelands around protected areas. This study investigated trends in both land use and land cover changes in Taveta District.   Remote Sensing imageries for Taveta District were analysed for the years 1987, 2001, and 2011. Percentage changes in land use and land cover types for the years 1987 to 2001, 2001 to 2011 and 1987 to 2011 were determined. Between 1987 and 2011, significant (p < 0.05) changes occurred in woodlands, sisal plantations, rainfed and irrigated agricultural areas. Shrublands, forests and water bodies showed no significant changes. Wildlife habitats are expected to further decrease significantly due to agricultural expansion. Land use and cover changes resulted from agricultural expansion and human population growth. The land use and cover maps produced can be used as input to decision making that balances restrictions on human land use while maintaining the ecological function of the landscape, through designation of Zones of Interaction as a first step to identifying opportunities that satisfy conservation and livelihood needs. Proper land use planning and community awareness of the implications of these land use and land cover changes are necessary.   Key words: Land use change, land cover change, rangelands, Taveta district, human-wildlife conflicts.

Landscape dynamics at the public–private interface: A case study in Colorado

Urban land use and land cover (LULC) mapping has been one of the major applications in remote sensing of the urban environment. Land cover refers to the biophysical materials at the surface of the earth (i.e. grass, trees, soils, concrete, water), while land use indicates the socio-economic function of the land (i.e., residential, industrial, commercial land uses). This study addresses the technical issue of how to computationally infer urban land use types based on the urban land cover structures from remote sensing data. In this research, a multispectral aerial image and high-resolution LiDAR topographic data have been integrated to investigate the urban land cover and land use in New Orleans, Louisiana. First, the LiDAR data are used to solve the problems associated with solar shadows of trees and buildings, building lean and occlusions in the multispectral aerial image. A two-stage rule-based classification approach has been developed, and the urban land cover of New Orleans has been classified into six categories: water, grass, trees, imperious ground, elevated bridges, and buildings with an overall classification accuracy of 94.2%, significantly higher than that of traditional per-pixel based classification method. The buildings are further classified into regular low-rising, multi-story, mid-rise, high-rise, and skyscrapers in terms of the height. Second, the land cover composition and structure in New Orleans have been quantitatively analyzed for the first time in terms of urban planning districts, and the information and knowledge about the characteristics of urban land cover components and structure for different types of land use functions have been discovered. Third, a graph-theoretic data model, known as relational attribute neighborhood graph (RANG), is adopted to comprehensively represent geometrical and thematic attributes, compositional and structural properties, spatial/topological relations between urban land cover patches (objects). Based on the evaluation of the importance of 26 spatial, thematic and topological variables in RANG, the random forest classification method is utilized to computationally infer and classify the urban land use in New Orleans into 7 types at the urban block level: single-family residential, two-family residential, multi-family residential, commercial, CBD, institutional, parks and open space, with an overall accuracy of 91.7%.

Urban land use change is a major issue globally. Land cover is a cover that covers any surface and the changes described include urban area land, water body, residential, forest land wasteland, agriculture, and recreation etc. The development of the built-up area separates the city limits.' (PA Khadke & RU Kharat 2017) Land use change plays a major role in the developmental activity of a developing country. Due to the rapid development of urbanization and the dramatically increasing population, fertile agricultural land has been converted into built-up area in relation to the need for housing and the need for infrastructure. The extent of open space and surface water bodies have also been encroached upon. Land use is derived from the human use of land and can be mainly classified into residential, agricultural, commercial use, industrial, etc. Land use and land cover changes are caused by socio-economic and natural factors. The increase in population as well as migration of people from rural to urban is the most important reason for land use change. (P. Sangardas, S. Ishwari, 2019). In the presented research paper, the study and analysis of land use change of Jodhpur city and its impact on economy and environment is to be done.

Aighewi, I.T.; Nosakhare, O.K., and Ishaque, A.B., 2013. Land use–land cover changes and sewage loading in the lower Eastern Shore watersheds and coastal bays of Maryland: Implications for surface water quality.Changes in land use and cover influence surface water quality and thus are a potential threat to water systems and coastal ecosystem health. The objectives of this study were to evaluate the influence of historical land use–land cover (LULC) changes and point-source sewage discharge on surface water quality of some lower Eastern Shore watersheds of Maryland. LANDSAT data for 1986–2006 was acquired and classified using Anderson level-1 classification system in ENVI 4.5, whereas LULC changes were detected in Arc-GIS 9.2 environment. Historical water monitoring and climatic data were obtained from Maryland Department of Environment–Chesapeake Bay Program, and National Oceanic and Atmospheric Administration, respectively. Nutrient loading data from wastewater treatment plants were obtained from Maryland Department of Environment and data analyzed using regression analysis and principal component analysis (PCA). The result shows that total phosphorous levels in the surface waters decreased significantly (p < 0.05) during the 20-year study period. However, using PCA, we determined that the declining P trend was attributable to the decreasing agricultural land use rather than the sewage discharge from wastewater treatment plants. The increase in urban land use and the resultant runoff to the water bodies may explain the declining trends in dissolved oxygen levels observed during the period, with serious implications for eutrophication. An empirical model developed for P in surface waters (r2 = 0.90) showed that the combination of point and nonpoint sources and land use/cover change factors are good predictors. The incorporation of quantitative LULC data component as well as point-source nutrient loading into existing models is highly recommended for a more holistic assessment of land-use influence on water systems in general.

Detailed urban land use mapping requires high-resolution remotely sensed data. The pan-sharpened multispectral IKONOS imagery of 1 m pixel resolution is experimented with for urban land use classification. With the increase of spatial resolution, between-class spectral confusion and within-class spectral variation increase. Spectral-based traditional image classification methods cannot be directly applied to the IKONOS data for urban land use mapping. In this study, a rule-based urban land use inferring method is proposed and tested on 36 samples of typical land use classes and an IKONOS subscene of various classes in London, Ontario, Canada. The proposed method includes two general steps. First, the conventional multispectral classification method is applied to produce a preliminary land cover map. Second, urban land use information is inferred from the combination of several land cover classes existing in a neighbourhood by a rule-based modelling process. The inferring rules involve the percent composition ranges of compatible land cover categories for a certain land use class, the interrelationship of the compatible land covers, and exclusion of incompatible land covers. The results show that the proposed method has successfully identified level II and level III land use classes using the U.S. Geological Survey land use classification system. The proposed method has successfully identified the land use classes in the sample image with over 90% accuracy. For the subscene, the proposed method has produced a land use map with 88.5% overall accuracy.