Land-Cover Pattern and Change

Fletcher, Robert J.; Fortin, Marie‐Josée

doi:10.1007/978-3-030-01989-1_3

Cited by 3 publications

(3 citation statements)

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“…At the national level in Norway, land use change is listed as the major threat to red-listed species as well as nature types [3,4]. To monitor, interpret and understand the changes that occur in the landscape, and to relate these changes to ecological processes, we need robust and reproducible methods for quantifying the changes in landscape patterns, that can be applied repeatedly, e.g., at regular intervals [5]. Ongoing national monitoring programs in Norway include, e.g., changes in agricultural land [6], aggregated general land-cover changes [7], and the reduction in 'interference-free areas' [8].…”

Section: Introductionmentioning

confidence: 99%

“…Landscape metrics can be grouped in many ways. e.g., according to the treatment of land cover (or land use) as a categorical or a continuous variable [5]. In a categorical framework, land is assigned to distinct patches of qualitatively different land-cover types, e.g., forest, agriculture or urban land use, or by a simple dichotomy according to the presence or absence of one particular land cover category, e.g., 'forest/non-forest' or 'habitat/non-habitat'.…”

Section: Introductionmentioning

confidence: 99%

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Index Measuring Land Use Intensity—A Gradient-Based Approach

et al. 2023

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To monitor the changes in the landscape, and to relate these to ecological processes, we need robust and reproducible methods for quantifying the changes in landscape patterns. The main aim of this study is to present, exemplify and discuss a gradient-based index of land use intensity. This index can easily be calculated from spatial data that are available for most areas and may therefore have a wide applicability. Further, the index is adapted for use based on official data sets and can thus be used directly in decision-making at different levels. The index in its basic form consists of two parts where the first is based on the data of buildings and roads and the second of infrastructure land cover. We compared the index with two frequently used ‘wilderness indices’ in Norway called INON and the Human Footprint Index. Our index captures important elements of infrastructure in more detailed scales than the other indices. A particularly attractive feature of the index is that it is based on map databases that are updated regularly. The index has the potential to serve as an important tool in land use planning as well as a basis for monitoring, the assessment of ecological state and ecological integrity and for ecological accounting as well as strategic environmental assessments.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Index Measuring Land Use Intensity—A Gradient-Based Approach

et al. 2023

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“…Verburg et al [ 1 ] found that the land use pattern of a region has a strong influence on a variety of ecological phenomena such as net primary production. The Land Use Land Cover (LULC) pattern creates new processes, influencing, for example, horizontal movement and distribution of animal populations [ 2 , 3 ], water runoff and erosion (e.g., [ 4 ], the spread of disturbance [ 5 , 6 ], and fluxes of materials and energy [ 7 ] or boundary phenomena in general [ 8 ]).…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of Different Environmental Factor Impacts on Land Cover in Nisos Elafonisos, Crete, Greece

Elhag

Boteva

2020

IJERPH

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Land Cover monitoring is an essential task for a better understanding of the ecosystem’s dynamicity and complexity. The availability of Remote Sensing data improved the Land Use Land Cover mapping as it is routine work in ecosystem management. The complexity of the Mediterranean ecosystems involves a complexity of the surrounding environmental factors. An attempt to quantitatively investigate the interdependencies between land covers and affected environmental factors was conducted in Nisos Elafonisos to represent diverse and fragile coastal Mediterranean ecosystems. Sentinel-2 (MSI) sensor and ASTER Digital Elevation Model (DEM) data were used to classify the LULC as well as to draw different vegetation conditions over the designated study area. DEM derivatives were conducted and incorporated. The developed methodology is intended to assess the land use land cover for different practices under the present environmental condition of Nisos Elafonisos. Supervised classification resulted in six different land cover clusters and was tested against three different environmental clusters. The findings of the current research pointed out that the environmental variables are independent and there is a vertical distribution of the vegetation according to altitude.

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