Special Issue "Understanding Our Planetary Home: New Directions in Land Use/Land Cover (LULC) Analysis"

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (28 February 2018)

Special Issue Editor

Guest Editor
Prof. Alexis Comber

School of Geography, University of Leeds, Leeds, LS2 9JT, UK
Website | E-Mail
Interests: spatial analysis; geocomputation; GIS; land cover; land use; spatial data analytics

Special Issue Information

Dear Colleagues,

This Special Issue on “Land Use/Land Cover (LULC) Analysis” welcomes submissions covering all areas of LULC, and papers that focus on the challenges associated with time series data, including classification, LULC change, and LULC error reporting are particularly encouraged.

The discipline of LULC has evolved from simply producing classifications of LULC at single points in time (e.g., national surveys for a particular year) to the generation of products to support and inform policy, which address issues regarding sustainability, vegetation health, and provides key inputs into climate change analyses and models. As a result, it embraces both traditional mapping of land cover (e.g., for forest resource inventories, REDD+) and land use (e.g., for modelling urbanization), and a number of related areas including ecosystem service, landscape function, land characterization, many of which are explicitly concerned with linking human distribution, vegetation condition/disturbance, as well as economics. This has led to increased interest in the multi-dimensional aspects of land use, as well as land cover.

A number of methodological challenges and opportunities have arisen due to the increased availability and volumes of remote sensing data (Big Data), the focus on LULC applications that link to landscape process and function and the increased demand for higher temporal resolution information, requiring time-series LULC analyses and analyses of LULC change. These challenges include how LULC are classified, how LULC change is measured, and how spatiotemporal error/accuracy in LULC are measured. They suggest the need to revisit some of the traditional methods used in these areas and to identify future opportunities and directions, especially as LULC is in the Big Data era.

For example, typically, LULC classifications are generated for a single point in time using data just for that time period (e.g., LULC classification for a particular year). The increased availability of time series data provides an opportunity to develop more temporally nuanced and informed approaches to classification. A standard single time classification is developed using the highest class likelihoods arising from data just that time period, independent of any other information. Error analysis is typically undertaken by comparing predictive against observed class from some validation exercise. Most current approaches to change analyses compare ‘predictions’ from different time periods (post-classification change). This suggests some interesting questions and opportunities:

  • Can multiple class likelihoods from a time series of likelihoods be used in classification instead of those from a single point in time?
  • Can information about temporal process be included in or even imposed on the classification? This is an old idea (see Comber et al. (2004)) but has its time come?
  • Can knowledge of local succession sequences, transitions or information from other LULC data be included?
  • How should we measure and informatively report on multi-temporal changes in LULC (including landscape and ecosystem function, characterization and services)?
  • Are new conventions needed for reporting change and error this based around soft measures (e.g., fuzzy sets, fuzzy change—see Fisher (2010))? For example, how should changes in the degree of ecosystem service be identified? Do soft classifications help in this matter? How do they alter the way that LULC change and error is approached?

References

Comber, A.J.; Law, A.N.R.; Lishman, J.R. Application of knowledge for automated land cover change monitoring. Int. J. Remote Sens. 2004, 25, 3177–3192.

http://www.tandfonline.com/doi/full/10.1080/01431160310001657795

Fisher, P.F. Remote sensing of land cover classes as type 2 fuzzy sets. Remote Sens. Environ. 2010, 114, 309–321.

http://www.sciencedirect.com/science/article/pii/S0034425709002764

Prof. Dr. Alexis  Comber
Guest Editor

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Keywords

  • Land use/land cover LULC change
  • spatiotemporal
  • big data
  • error and accuracy
  • time-series
  • ecosystem service
  • landscape function
  • REDD+
  • land characterization
  • remote sensing

Published Papers (4 papers)

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Research

Open AccessArticle Forest Cover Change, Key Drivers and Community Perception in Wujig Mahgo Waren Forest of Northern Ethiopia
Received: 17 January 2018 / Revised: 13 February 2018 / Accepted: 14 February 2018 / Published: 9 March 2018
Cited by 4 | PDF Full-text (602 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This study assessed forest cover change from 1985 to 2016, analyzed community perception on forest cover change and its drivers, and suggested possible solutions in northern Ethiopia. Landsat images of 1985, 2000 and 2016, household interviews and focus group discussions were used. While [...] Read more.
This study assessed forest cover change from 1985 to 2016, analyzed community perception on forest cover change and its drivers, and suggested possible solutions in northern Ethiopia. Landsat images of 1985, 2000 and 2016, household interviews and focus group discussions were used. While dense forests and open forests increased by 8.2% and 32.3% respectively between 1985 and 2000, they decreased by 10.4% and 9.8% respectively from 2000 to 2016. Grasslands and cultivated land decreased in the first period by 37.3% and 5.5% but increased in the second period by 89.5% and 28.5% respectively. Fuel wood collection, cultivated land expansion, population growth; free grazing, logging for income generation and drought were the major drivers of the change reported by local communities. Soil erosion, reduction in honey bee production, flooding and drought were the most perceived impacts of the changes. Most of the farmers have a holistic understanding of forest cover change. Strengthening of forest protection, improving soil and water conservation, enrichment planting, awareness creation, payment for ecosystem services and zero grazing campaigns were mentioned as possible solutions to the current state of deforestation. In addition, concerted efforts of conservation will ensure that the forests’ ecosystems contribute to increased ecosystem services. Full article
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Open AccessArticle Land Use and Land Cover Changes and Their Effects on the Landscape of Abaya-Chamo Basin, Southern Ethiopia
Received: 2 December 2017 / Revised: 30 December 2017 / Accepted: 4 January 2018 / Published: 7 January 2018
Cited by 4 | PDF Full-text (3623 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This study uses a combination of remote sensing data, field interviews and observations, and landscape indices to examine the dynamics of land use and land cover (LULC), identify their driving forces, and analyze their effects on the landscape of Abaya-Chamo Basin (ACB) between [...] Read more.
This study uses a combination of remote sensing data, field interviews and observations, and landscape indices to examine the dynamics of land use and land cover (LULC), identify their driving forces, and analyze their effects on the landscape of Abaya-Chamo Basin (ACB) between 1985, 1995, and 2010. The results reveal that the landscape of ACB has changed considerably during the past 25 years between 1985 and 2010. The main changes observed imply a rapid reduction in shrubland (28.82%) and natural grassland (33.13%), and an increase in arable land (59.15%). The basin has become more fragmented and formed less connected patches in 2010 compared to 1985. Rapid population growth, internal migration, policy shifts, and regime change were identified as the key driving forces of LULC changes in ACB. The LULC changes and related trend of increasing landscape fragmentation in the basin increased soil erosion, the volume of surface runoff, and sediment transport in the landscape and, consequently, affected the levels and water quality of the lakes found in the rift floor. Furthermore, the destruction and fragmentation of shrubland and natural grassland led to the decline of wild plants and animals previously prominent in the basin. Therefore, protective measures that take into consideration the economic, social, and ecological dynamics of the basin are urgently needed to save the aquatic and terrestrial ecosystems of the basin from further damage. Full article
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Open AccessArticle Land Use as a Motivation for Railway Trespassing: Experience from the Czech Republic
Received: 21 November 2017 / Revised: 18 December 2017 / Accepted: 28 December 2017 / Published: 3 January 2018
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Abstract
Railway trespassing is a very risky but common behaviour, resulting in about 200 casualties annually in the Czech Republic. This study describes the formation of 27 selected risk localities with frequent occurrence of trespassing in the regions of southern, central and northern Moravia. [...] Read more.
Railway trespassing is a very risky but common behaviour, resulting in about 200 casualties annually in the Czech Republic. This study describes the formation of 27 selected risk localities with frequent occurrence of trespassing in the regions of southern, central and northern Moravia. To be able to describe the process, an evaluation of the development of land use was conducted within a wide spatial context of each spot. The evaluation was focused on functional use of built-up areas (collective and individual housing, industrial areas, shopping and services, recreational areas, etc.). In the sample of investigated localities were places of two kinds: (1) localities where the railway intersected existing settlement structures, and relationships and links within the area were radically disturbed and severed. A lack of legal possibilities for crossing restricts the movement of inhabitants at these localities; (2) localities where the railway originally passed through open landscape and was later surrounded by built-up areas with various land-use functions. Here, trespassing is the consequence of gaps in the urban-planning process, wherein the needs of pedestrians and cyclists were not sufficiently considered. The analysis of the development of land use since 1836 showed how the motivations of trespassing were gradually intensified with more and more complex structures of functional division of areas. The percentage of built-up areas increased in all monitored localities overall from 6.28% during 1836–1852 to 52.15% during 2014–2015. Full article
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Open AccessArticle What’s (Not) on the Map: Landscape Features from Participatory Sketch Mapping Differ from Local Categories Used in Language
Received: 25 September 2017 / Revised: 31 October 2017 / Accepted: 1 November 2017 / Published: 5 November 2017
Cited by 1 | PDF Full-text (6032 KB) | HTML Full-text | XML Full-text
Abstract
Participatory mapping of local land use as the basis for planning and decision-making has become widespread around the globe. However, still relatively little is known about the conceptual underpinnings of geographic information produced through participatory mapping in given cultural and linguistic settings. In [...] Read more.
Participatory mapping of local land use as the basis for planning and decision-making has become widespread around the globe. However, still relatively little is known about the conceptual underpinnings of geographic information produced through participatory mapping in given cultural and linguistic settings. In this paper, we therefore address the seemingly simple question of what is (not) represented on maps through an exploratory case study comparing land use categories participants represented on sketch maps with categories elicited through more language-focused ethnographic fieldwork. To explore landscape categorization, we conducted sketch mapping with 29 participants and in-depth ethnographic fieldwork with 19 participants from the Takana indigenous people in the Bolivian Amazon. Sketch mapping resulted in 74 different feature types, while we elicited 156 landscape categories used in language, of which only 23 overlapped with feature types from the sketch mapping. Vegetation categories were highly diversified in language but seldom represented on maps, while more obviously anthropogenic features were represented on sketch maps. Furthermore, participants seldom drew culturally important landscape categories such as fallow plots or important plant harvesting sites on maps, with important potential consequences for natural resource management. Full article
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