Continuous Change Mapping to Understand Wetland Quantity and Quality Evolution and Driving Forces: A Case Study in the Liao River Estuary from 1986 to 2018

A framework to quantitatively assess the influence of land use and land cover on coastal wetland hydrological connectivity from a landscape resistance perspective

Land use and land cover (LULC) change is one of the dominant factors contributing to coastal wetland degradation and loss. Most studies focused on LULC changes or whether they influenced on ecosystems. However, few studies quantitatively assessed the impact of different LULCs on hydrological connectivity. This study aimed to understand how LULC affected hydrological connectivity in the coastal wetlands in the Yellow River Delta (YRD), China, from 1985 to 2020. A framework from a landscape resistance perspective was used to evaluate the LULC's influence. LULCs were converted into a series of resistance surfaces whose values represent the degree to which LULC facilitated or restricted hydrological connectivity. The LULC's influence was evaluated by parameterizing the resistance surfaces using observed hydrological connectivity. The results showed that human-related LULC had more influence on hydrological connectivity. The critical time of LULC's influence on hydrological connectivity was 1985-1990 and 2010-2015. The critical areas were Zone II, Zone I, and Zone VI. The LULCs of agriculture, industry, town/city, and river had the most significant impact on the hydrological connectivity of the YRD coastal wetland. The result could direct LULC planning to mitigate the negative effect on coastal wetlands and provide support for the environmental impact assessment of coastal development practices. This paper advances the study by assessing LULCs' impact on hydrological connectivity and providing a quantitative method. The framework of this study enriches the coastal wetland conservation theory and policy-making of coastal management.

Wetland health, water quality, and resident perceptions of declining ecosystem services: a case study of Mount Abu, Rajasthan, India

Ecosystem services provided by wetlands are essential for communities living near wetlands, especially in an underdeveloped semi-arid landscape. The land use land cover changes and ecosystem degradation and water quality change over the past few decades have had immense effects on declining wetland ecosystem services. With the degradation, it is exerting superfluous effects on wetland communities including loss of livelihood, and decline in other wetland services like fishing, aquaculture, fuelwood, fodder, and many more. The present study attempts to assess the changing nature of wetland health, water quality, and declining ecosystem services of Mount Abu wetlands in Rajasthan, India. For assessing the change of wetland extent, we have used the remote sensing-based data for preparation of land use land cover change from 1992 to 2020. The water samples have been collected from the wetland, and different biophysical parameters of the water have been tested in the laboratory. A questionnaire-based household survey has been conducted to understand the perception of the wetland communities on the loss of ecosystem services over three decades. Further, a correlation and cluster assessment has been conducted to understand the degradation of wetland health in the selected wetlands. The study results indicated deteriorating conditions of wetland health and declining ecosystem services in the study area over the time periods. The land use land cover change analysis indicated a decrease in the spatial extent of the wetlands in the study area. Wetland communities are being affected due to the degradation of wetland health. The study recommended executing a wetland management plan for long-term conservation and livelihood management for the Mount Abu wetlands and communities.

Optimization of landscape pattern in the main river basin of Liao River in China based on ecological network

As a main stream method of landscape pattern optimization, the ecological network plays an important role in maintaining ecosystem stability, improving landscape connectivity, and promoting landscape sustainable development. Based on landscape connectivity index and morphological spatial pattern analysis (MSPA), a comprehensive evaluation system of ecological patches was constructed in the main river basin of Liao River, and ecological sources were extracted. According to the habitat characteristics of the study area, the ecological cumulative resistance surface was constructed, and the ecological corridors and nodes were extracted by the minimum cumulative resistance (MCR) model. The ecological network of the study area was comprehensively evaluated by using the network analysis method, and the importance level of the ecological corridor was divided by the gravity model, so as to put forward the optimization suggestions of the landscape pattern based on the ecological network. The results showed that the ecological network in the main river basin of Liao River is composed of 20 ecological sources, 108 ecological corridors, and 72 ecological nodes, with the distribution characteristics of dense east and sparse west. The main landscape components are cropland and woodland. The closure degree, line point rate, and connectivity index of the ecological network are 0.27, 1.50, and 0.51, respectively, and the cost ratio is 0.23. In the optimization of landscape pattern, priority should be given to the restoration of primary ecological sources and ecological corridors, followed by the ecological construction of secondary and tertiary ecological sources and ecological corridors, the rational use of engineering technology for habitat remodeling, and the adoption of the "patch-corridor-substrate" model to improve the stability and landscape connectivity of the regional ecosystem. The construction of ecological network in the main river basin of Liao River is of great significance to regional ecological security and biodiversity conservation, and provides data support for optimizing the landscape pattern of the basin and promoting regional sustainable development.

Continuous Change Detection and Classification—Spectral Trajectory Breakpoint Recognition for Forest Monitoring

Forest is one of the most important surface coverage types. Monitoring its dynamics is of great significance in global ecological environment monitoring and global carbon circulation research. Forest monitoring based on Landsat time-series stacks is a research hotspot, and continuous change detection is a novel approach to real-time change detection. Here, we present an approach, continuous change detection and classification-spectral trajectory breakpoint recognition, running on Google Earth Engine (GEE) for monitoring forest disturbance and forest long-term trends. We used this approach to monitor forest disturbance and the change in forest cover rate from 1987 to 2020 in Nanning City, China. The high-resolution Google Earth images are collected for the validation of forest disturbance. The classification accuracy of forest, non-forest, and water maps by using the optima classification features was 95.16%. For disturbance detection, the accuracy of our map was 86.4%, significantly higher than 60% of the global forest change product. Our approach can successfully generate high-accuracy classification maps at any time and detect the forest disturbance time on a monthly scale, accurately capturing the thinning cycle of plantations, which earlier studies failed to estimate. All the research work is integrated into GEE to promote the use of the approach on a global scale.