Land-use land-cover change and ecosystem loss in the Espinal ecoregion, Argentina

Guida‐Johnson, Bárbara; Zuleta, Gustavo A.

doi:10.1016/j.agee.2013.09.002

Cited by 85 publications

(38 citation statements)

References 29 publications

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“…The processes of these land use transitions can be categorized into either random or systematic changes based on identifying their pattern of categorical changes [12,17]. A random process of change occurs when a LULC category loses to or gains from other categories in proportion to the size of other land cover categories, while systematic transitions are driven by the regular processes of transition that change in a constant or gradual development [12,14]. Post-classification comparison (PCC) is among the change detection approaches that can be used in order to determine changes between satellite imagery of different sources and dates [18,19].…”

Section: Introductionmentioning

confidence: 99%

“…In order to sustainably utilize the existing resources, there is the need for the broad consideration of LULC for the timely inspection of the transitions of landscapes [21]. Satellite imagery contributes significantly to the spatiotemporal evaluation and documentation of the modifications of landscapes over time [14,15]. Hence, this study: (1) quantifies the signals of land use transitions; (2) identifies the consequences of land use change; (3) identifies the spatial association of precipitation and NDVI for a better understanding of the threats of dryland environmental changes.…”

Section: Introductionmentioning

confidence: 99%

“…LULC studies focused on understanding the patterns, processes and dynamics of land transitions and its drivers over time [12][13][14][15][16]. The processes of these land use transitions can be categorized into either random or systematic changes based on identifying their pattern of categorical changes [12,17].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identifying Categorical Land Use Transition and Land Degradation in Northwestern Drylands of Ethiopia

Zewdie

Csaplovics

2016

Remote Sensing

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Land use transition in dryland ecosystems is one of the major driving forces to landscape change that directly impacts the welfare of humans. In this study, the support vector machine (SVM) classification algorithm and cross tabulation matrix analysis are used to identify systematic and random processes of change. The magnitude and prevailing signals of land use transitions are assessed taking into account net change and swap change. Moreover, spatiotemporal patterns and the relationship of precipitation and the Normalized Difference Vegetation Index (NDVI) are explored to evaluate landscape degradation. The assessment showed that 44% of net change and about 54% of total change occurred during the study period, with the latter being due to swap change. The conversion of over 39% of woodland to cropland accounts for the existence of the highest loss of valuable ecosystem of the region. The spatial relationship of NDVI and precipitation also showed R 2 of below 0.5 over 55% of the landscape with no significant changes in the precipitation trend, thus representing an indicative symptom of land degradation. This in-depth analysis of random and systematic landscape change is crucial for designing policy intervention to halt woodland degradation in this fragile environment.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identifying Categorical Land Use Transition and Land Degradation in Northwestern Drylands of Ethiopia

Zewdie

Csaplovics

2016

Remote Sensing

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“…Land-use change is considered to be one of the most important components of global environmental change (Johnson and Zuleta, 2013), which is often complex and related to human activities and natural ecological processes (Petit and Lambin, 2002), such as industrialization, urbanization, and population growth (Long et al, 2007). The conversion of agricultural land to non-agricultural land is a common pattern of land-use change (Yang and Li, 2000).…”

Section: Introductionmentioning

confidence: 99%

County-level patterns of cropland and their relationships with socio-economic factors in northwestern China

Zhang

Wang

et al. 2015

Agriculture, Ecosystems & Environment

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“…A common method employs the use of a land use/cover transition matrix, which provides a cross-tabulation matrix including change quantities and directions, and allows identification of differences between random and systematic land use transitions [14][15][16][17]. However, matrix-based land use studies mainly focus on overall gains and losses, and tend to ignore the spatial locations and swap changes of land use transitions [10,18]. Furthermore, the maps or databases of these studies are sampled or classed at discrete intervals, and the analysis tends to focus on the adjacent periods, but ignore successive process of land use transitions [19,20].…”

Section: Introductionmentioning

confidence: 99%

Understanding Land Use and Land Cover Dynamics from 1976 to 2014 in Yellow River Delta

Zhang

Feng

et al. 2017

Land

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Long-term intensive land use/cover changes (LUCCs) of the Yellow River Delta (YRD) have been happening since the 1960s. The land use patterns of the LUCCs are crucial for bio-diversity conservation and/or sustainable development. This study quantified patterns of the LUCCs, explored the systematic transitions, and identified wetland change trajectory for the period 1976-2014 in the YRD. Landsat imageries of 1976, 1984, 1995, 2006, and 2014 were used to derive nine land use classes. Post classification change detection analysis based on enhanced transition matrix was applied to identify land use dynamics and trajectory of wetland change. The five cartographic outputs for changes in land use underlined major decreases in natural wetland areas and increases in artificial wetland and non-wetland, especially aquafarms, salt pans and construction lands. The systematic transitions in the YRD were wetland degradation, wetland artificialization, and urbanization. Wetland change trajectory results demonstrated that the main wetland changes were wetland degradation and wetland artificialization. Coastline change is the subordinate reason for natural wetland degradation in comparison with human activities. The results of this study allowed for an improvement in the understanding of the LUCC processes and enabled researchers and planners to focus on the most important signals of systematic landscape transitions while also allowing for a better understanding of the proximate causes of changes.

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Land-use land-cover change and ecosystem loss in the Espinal ecoregion, Argentina

Cited by 85 publications

References 29 publications

Identifying Categorical Land Use Transition and Land Degradation in Northwestern Drylands of Ethiopia

Identifying Categorical Land Use Transition and Land Degradation in Northwestern Drylands of Ethiopia

County-level patterns of cropland and their relationships with socio-economic factors in northwestern China

Understanding Land Use and Land Cover Dynamics from 1976 to 2014 in Yellow River Delta

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