scholarly journals Wetland loss in the Ñeembucú Wetlands Complex, Paraguay, using remote sensing

2022 ◽  
Author(s):  
Frances O'Leary
Keyword(s):  
Decision Making ◽  
Land Cover ◽  
Urban Expansion ◽  
River System ◽  
Open Water ◽  
Wetland Loss ◽  
Forest Conversion ◽  
Remotely Sensed Data ◽  
Goods And Services ◽  
Inspection Data

South American wetlands are of global importance, yet limited delineation and monitoring restricts informed decision-making around the drivers of wetland loss. A growing human population and increasing demand for agricultural products has driven wetland loss and degradation in the Neotropics. Understanding of wetland dynamics and land use change can be gained through wetland monitoring. The Ñeembucú Wetlands Complex is the largest wetland in Paraguay, lying within the Paraguay-Paraná-La Plata River system. This study aims to use remotely sensed data to map land cover between 2006 and 2021, quantify wetland change over the 15-year study period and thus identify land cover types vulnerable to change in the Ñeembucú Wetlands Complex. Forest, dryland vegetation, vegetated wetland and open water were identified using Random Forest supervised classifications trained on visual inspection data and field data. Annual change of -0.34, 4.95, -1.65, 0.40 was observed for forest, dryland, vegetated wetland and open water, respectively. Wetland and forest conversion is attributed to agricultural and urban expansion. With ongoing pressures on wetlands, monitoring will be a key tool for addressing change and advising decision-making around development and conservation of valuable ecosystem goods and services in the Ñeembucú Wetlands Complex.

scholarly journals Mapping Inter-Annual Land Cover Variations Automatically Based on a Novel Sample Transfer Method

2018 ◽  
Vol 10 (9) ◽  
pp. 1457 ◽  
Author(s):  
Cheng Zhong ◽  
Cuizhen Wang ◽  
Hui Li ◽  
Wenlong Chen ◽  
Yong Hou
Keyword(s):  
Land Cover ◽  
Reference Data ◽  
Urban Expansion ◽  
Remotely Sensed Data ◽  
Object Based ◽  
Short Time Span ◽  
Transfer Method ◽  
The Times ◽  
Land Cover Maps ◽  
Sample Transfer

Most land cover mapping methods require the collection of ground reference data at the time when the remotely sensed data are acquired. Due to the high cost of repetitive collection of reference data, however, it limits the production of annual land cover maps to a short time span. In order to reduce the mapping cost and to improve the timeliness, an object-based sample transfer (OBST) method was presented in this study. The object-based analysis with strict constrains in area, shape and index values is expected to reduce the accident errors in selecting and transferring samples. The presented method was tested and compared with same-year mapping (SY), cross-year mapping (CY) and multi-index automatic classification (MI). For the study years of 2001–2016, both the overall accuracies (above 90%) and detailed accuracy indicators of the presented method were very close to the SY accuracy and higher than accuracies of CY and MI. With the presented method, the times-series land cover map of Guangzhou, China were derived and analyzed. The results reveal that the city has undergone rapid urban expansion and the pressure on natural resources and environment has increased. These results indicate the proposed method could save considerable cost and time for mapping the spatial-temporal changes of urban development. This suggests great potential for future applications as more satellite observations have become available all over the globe.

Thresholds of change in a multi-use conservation landscape of South Africa: historical land-cover, future transformation and consequences for environmental decision-making

2016 ◽  
Vol 43 (3) ◽  
pp. 253-262 ◽  
Author(s):  
KAERA L. COETZER-HANACK ◽  
E.T.F. WITKOWSKI ◽  
BAREND F.N. ERASMUS
Keyword(s):  
South Africa ◽  
Decision Making ◽  
Land Cover ◽  
Recent Observation ◽  
Rate Of Change ◽  
Critical Threshold ◽  
Rapid Decline ◽  
Remotely Sensed Data ◽  
Environmental Decision Making ◽  
Environmental Decision

SUMMARYAs multi-use conservation landscapes, biosphere reserves (BRs) exemplify the landscape mosaic approach to environmental decision-making. In this study, time-series remotely-sensed data (1993–2006–2012) were used to monitor vegetation transformation in the Kruger to Canyons Biosphere Reserve (K2C) of South Africa, updating previous land-cover research. We identified changes in spatial extent, rate and intensity of land-cover change and extrapolated observed trends to 2018. The increased rate of change in the recent observation period (2.3 vs. 5.7%) was driven by more intensive gains in impacted vegetation and settlement since 2006 (>210 km2and >120 km2), with resultant transformation of intact habitat undermining regional connectivity. By 2012, intact vegetation had suffered losses of 6.3% (>350 km2) since 2006 and >14% (>750 km2) since 1993. A further 9.5% loss of intact habitat may represent a critical threshold, establishing K2C above the 50% threshold of landscape transformation, whereafter a rapid decline in landscape resilience is likely. Given the BR's spatial zonation, such a loss across the full extent of K2C is unlikely, at least in the short-term (i.e., by 2018). Yet, based on past trends of transformation in the unprotected transition zone, anticipating such losses in the longer term, is not unfounded (i.e., 2024).

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals Spatiotemporal Influence of Land Use/Land Cover Change Dynamics on Surface Urban Heat Island: A Case Study of Abuja Metropolis, Nigeria

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Expansion ◽  
Urban Heat Islands ◽  
Sustainable Land Use ◽  
Land Use Land Cover ◽  
Urban Centers ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.

scholarly journals Hydrology influences breeding time in the white-throated dipper

BMC Ecology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Anna L. K. Nilsson ◽  
Thomas Skaugen ◽  
Trond Reitan ◽  
Jan Henning L’Abée-Lund ◽  
Marlène Gamelon ◽  
...  
Keyword(s):  
Climate Change ◽  
River Discharge ◽  
Large Scale ◽  
Time Window ◽  
River System ◽  
Open Water ◽  
Local Conditions ◽  
Environmental Indices ◽  
Groundwater Levels ◽  
Breeding Time

Abstract Background Earlier breeding is one of the strongest responses to global change in birds and is a key factor determining reproductive success. In most studies of climate effects, the focus has been on large-scale environmental indices or temperature averaged over large geographical areas, neglecting that animals are affected by the local conditions in their home ranges. In riverine ecosystems, climate change is altering the flow regime, in addition to changes resulting from the increasing demand for renewable and clean hydropower. Together with increasing temperatures, this can lead to shifts in the time window available for successful breeding of birds associated with the riverine habitat. Here, we investigated specifically how the environmental conditions at the territory level influence timing of breeding in a passerine bird with an aquatic lifestyle, the white-throated dipper Cinclus cinclus. We relate daily river discharge and other important hydrological parameters, to a long-term dataset of breeding phenology (1978–2015) in a natural river system. Results Dippers bred earlier when winter river discharge and groundwater levels in the weeks prior to breeding were high, and when there was little snow in the catchment area. Breeding was also earlier at lower altitudes, although the effect dramatically declined over the period. This suggests that territories at higher altitudes had more open water in winter later in the study period, which permitted early breeding also here. Unexpectedly, the largest effect inducing earlier breeding time was territory river discharge during the winter months and not immediately prior to breeding. The territory river discharge also increased during the study period. Conclusions The observed earlier breeding can thus be interpreted as a response to climate change. Measuring environmental variation at the scale of the territory thus provides detailed information about the interactions between organisms and the abiotic environment.

scholarly journals Improving 3-m Resolution Land Cover Mapping through Efficient Learning from an Imperfect 10-m Resolution Map

2020 ◽  
Vol 12 (9) ◽  
pp. 1418
Author(s):  
Runmin Dong ◽  
Cong Li ◽  
Haohuan Fu ◽  
Jie Wang ◽  
Weijia Li ◽  
...  
Keyword(s):  
Land Cover ◽  
Training Data ◽  
Training Dataset ◽  
Land Cover Mapping ◽  
Remotely Sensed Data ◽  
Large Area ◽  
National Scale ◽  
Substantial Progress ◽  
Efficient Learning ◽  
Land Cover Maps

Substantial progress has been made in the field of large-area land cover mapping as the spatial resolution of remotely sensed data increases. However, a significant amount of human power is still required to label images for training and testing purposes, especially in high-resolution (e.g., 3-m) land cover mapping. In this research, we propose a solution that can produce 3-m resolution land cover maps on a national scale without human efforts being involved. First, using the public 10-m resolution land cover maps as an imperfect training dataset, we propose a deep learning based approach that can effectively transfer the existing knowledge. Then, we improve the efficiency of our method through a network pruning process for national-scale land cover mapping. Our proposed method can take the state-of-the-art 10-m resolution land cover maps (with an accuracy of 81.24% for China) as the training data, enable a transferred learning process that can produce 3-m resolution land cover maps, and further improve the overall accuracy (OA) to 86.34% for China. We present detailed results obtained over three mega cities in China, to demonstrate the effectiveness of our proposed approach for 3-m resolution large-area land cover mapping.

scholarly journals Comparative Assessment of the Built-Up Area Expansion Based on Corine Land Cover and Landsat Datasets: A Case Study of a Post-Socialist City

2020 ◽  
Vol 12 (13) ◽  
pp. 2137 ◽  
Author(s):  
Ilinca-Valentina Stoica ◽  
Marina Vîrghileanu ◽  
Daniela Zamfir ◽  
Bogdan-Andrei Mihai ◽  
Ionuț Săvulescu
Keyword(s):  
Land Cover ◽  
Urban Expansion ◽  
Ground Truth ◽  
Cost Effective ◽  
Planning System ◽  
The European Union ◽  
Scale Level ◽  
Corine Land Cover ◽  
Macro Scale ◽  
Area Expansion

Monitoring uncontained built-up area expansion remains a complex challenge for the development and implementation of a sustainable planning system. In this regard, proper planning requires accurate monitoring tools and up-to-date information on rapid territorial transformations. The purpose of the study was to assess built-up area expansion, comparing two freely available and widely used datasets, respectively, Corine Land Cover and Landsat, to each other, as well as the ground truth, with the goal of identifying the most cost-effective and reliable tool. The analysis was based on the largest post-socialist city in the European Union, the capital of Romania, Bucharest, and its neighboring Ilfov County, from 1990 to 2018. This study generally represents a new approach to measuring the process of urban expansion, offering insights about the strengths and limitations of the two datasets through a multi-level territorial perspective. The results point out discrepancies between the datasets, both at the macro-scale level and at the administrative unit’s level. On the macro-scale level, despite the noticeable differences, the two datasets revealed the spatiotemporal magnitude of the expansion of the built-up area and can be a useful tool for supporting the decision-making process. On the smaller territorial scale, detailed comparative analyses through five case-studies were conducted, indicating that, if used alone, limitations on the information that can be derived from the datasets would lead to inaccuracies, thus significantly limiting their potential to be used in the development of enforceable regulation in urban planning.

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