Assessing Regional Ecosystem Conditions Using Geospatial Techniques-A Review.

Ecosystem conditions at the regional level are critical factors for environmental management, public awareness, and land use decision making. Regional ecosystem conditions may be examined from the perspectives of ecosystem health, vulnerability, and security, as well as other conceptual frameworks. Vigor, organization, and resilience (VOR) and pressure-stress-response (PSR) are two commonly adopted conceptual models for indicator selection and organization. The analytical hierarchy process (AHP) is primarily used to determine model weights and indicator combinations. Although there have been many successful efforts in assessing regional ecosystems, they remain affected by a lack of spatially explicit data, weak integration of natural and human dimensions, and uncertain data quality and analyses. In the future, regional ecosystem condition assessments may be advanced by incorporating recent improvements in spatial big data and machine learning to create more operative indicators based on Earth observations and social metrics. The collaboration between ecologists, remote sensing scientists, data analysts, and scientists in other relevant disciplines is critical for the success of future assessments.

Eco-engineering controls vegetation trends in southwest China karst.

The karst area in Yunnan-Guangxi-Guizhou region in southwest China is known for widespread rocky desertification but several studies report a greening trend since the year 2000. While the start of the greening trend seems to match with the implementation of ecological conservation projects, no statistical evidence on a relationship between vegetation greening and eco-engineering exists. Moreover, dominant factors influencing the spatial patterns of vegetation trends have rarely been investigated. Here we use six comprehensive factors representing the natural conditions and human activities of the study area, and several statistical models consistently show that eco-engineering explains large parts of the positive vegetation trends in the karst areas, while negative vegetation trends in non-karst areas of Yunnan were related with a decrease in rainfall. We further show that the interaction of eco-engineering with other factors leads to a heterogeneous pattern of different vegetation trends. Knowing and understanding these patterns is crucial when planning ecological restoration, especially in diverse landscapes like China karst and the methods can be reused in other restoration areas.

Comparing Remote Sensing Methods for Monitoring Karst Rocky Desertification at Sub-pixel Scales in a Highly Heterogeneous Karst Region.

Rugged karst terrain relief that creates shadows in satellite imagery, combined with high karst landscape heterogeneity stand in the way of fractional cover retrieval on karst rocky desertification (KRD) monitoring. In this study, we explored the feasibility of applying multispectral high spatial resolution Advanced Land Observing Satellite (ALOS) imagery for the fractional cover extraction of rocky outcrops. Dimidiate pixel model (DPM) and spectral mixture analysis (SMA) approaches (including simple endmember spectral mixture analysis and multiple endmember spectral mixture analysis) were selected to explore their feasibility for KRD monitoring through accuracy improvement for fraction estimation. Results showed fractional cover retrievals at the sub-pixel scale is essential in highly heterogeneous karst landscapes. Indeed, mixed pixels accounted for 93.7% of the study area in southwest China. Multiple endmember spectral mixture analysis achieved high overall accuracy (80.5%) in monitoring the percentage of rocky outcrop land cover. Furthermore, the predicted exposed bedrock coverage via spectral mixture analysis were similar in sunlit and shadow areas for the same surface types. This reflected that SMA methods could effectively reduce topographic effects of satellite imagery to improve the accuracy of fractional cover extraction at sub-pixel level in heterogeneous and rugged landscapes.

Spatiotemporal variation of karst ecosystem service values and its correlation with environmental factors in northwest Guangxi, China.

In this investigation we analyzed the spatiotemporal variation of ecosystem service values (ESVs) and its correlation with numerous environmental factors (EFs) for the karst region of Northwest Guangxi, China, from 1985 to 2005 using remote sensing, geographic information systems (GIS) and statistical techniques. The results indicate that historically ESVs for this karst region decreased from 1985 (109.652 billion yuan) to 1990 (88.789 billion yuan) and then increased at the turn of the twenty-first century. However, the ESVs in both 2000 (103.384 billion yuan) and 2005 (106.257 billion yuan) never achieved the level recorded in 1985. The total of nutrient cycling, organic production and gas regulation combined were 72.69, 64.57, 70.18 and 72.10% of ESVs in 1985, 1990, 2000 and 2005, respectively. In contrast, the ESVs of water conservation, soil reservation, recreation and culture were determined to be relatively low contributing only 17.44, 23.82, 19.26 and 24.76% of total ESVs, respectively, during these four years. With regards to the spatial distribution of ESVs, larger values were recorded in the west and smaller ones recorded in the east. The most significant factors that were deemed to influence ESVs are annual rainfall, per capita cropland, slope and vegetation coverage. Annual rainfall and slope exert a negative force, whereas per capita cropland and vegetation coverage exert a positive force on ESVs. The results of the study would suggest that ecosystem conditions of this important karst region have been improved as the result of the implementation of rocky desertification control policies.