Mapping Supply-Demand of Riparian Ecosystem Service for Riparian Greenspace Planning on Multiple Spatial Scales

Riparian areas produce a variety of ecosystem service(ES)functions and play an important role in the coupled nature-human systems.Taking account of riparian ES in riparian greenspace planning framework and balancing the ecological and social aspects of ES can help to achieve the composite goals for urban-rural sustainability.However,there is still a lack of research on the integration thinking and quantification approach for riparian ES to support riparian greenspace planning and decision-making.This research mainly discusses the possible way of incorporating the ES into riparian greenspace planning and presents an integrated framework of the interaction between riparian ES and riparian greenspace planning,including evaluating riparian ES supply-demand budget to support multi-scales(region,urban,and street)riparian greenspace planning.Taking the Nanchuan District of Chongqing in China as a case study,we aim to achieve the following three results:first,recognizing the relationship and building a link between riparian ES and riparian greenspace planning;second,establishing a multi-scale scoring system of two ES supply-demand indicators for mapping on three spatial scales;third,applying riparian ES supply-demand mapping into riparian greenspace planning from three aspects of balancing planning goals,multi-scale planning tasks,and planning strategies and policies.

Assessing the quality of chlorophyll-a concentration products under multiple spatial and temporal scales

Abstract The chlorophyll-a concentration data obtained through remote sensing are important for a wide range of scientific concerns.However,cloud cover and limitations of inversion algorithms of chlorophyll-a concentration lead to data loss,which critically limits studying the mechanism of spatial-temporal patterns of chlorophyll-a concentration in response to marine environment changes.If the commonly used operational chlorophyll-a concentration products can offer the best data coverage frequency,highest accuracy,best applicability,and greatest robustness at different scales remains debatable to date.Therefore,in the present study,four commonly used operational multi-sensor multi-algorithm fusion products were compared and subjected to validation based on statistical analysis using the available data measured at multiple spatial and temporal scales.The experimental results revealed that in terms of spatial distribution,the chlorophyll-a concentration products generated by averaging method(Chl1-AV/AVW)and GSM model(Chl1-GSM)presented a relatively high data coverage frequency in Case Ⅰ water regions and extremely low or no data coverage frequency in the estuarine coastal zone regions and inland water regions,the chlorophyll-a concentration products generated by the Neural Network algorithm(Chl2)presented high data coverage frequency in the estuarine coastal zone Case 2 water regions.The chlorophyll-a concentration products generated by the OC5 algorithm(ChlOC5)presented high data coverage frequency in Case I water regions and the turbid Case Ⅱ water regions.In terms of absolute precision,the Chl1-AV/AVW and Chl1-GSM chlorophyll-a concentration products performed better in Class I water regions,and the Chl2 product performed well only in Case Ⅱ estuarine coastal zones,while presenting large errors in absolute precision in the Case Ⅰ water regions.The ChlOC5 product presented a higher precision in Case Ⅰ and Case Ⅱ water regions,with a better and more stable performance in both regions compared to the other products.

Autumn NDVI contributes more and more to vegetation improvement in the growing season across the Tibetan Platea

Detecting changes in vegetation,distinguishing the persistence of changes,and seeking their causes during multiple periods are important to gaining a deeper understanding of vegetation dynamics.Using the Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index(NDVI)version NDVI_(3g) dataset in the Tibetan Plateau,the trends in the seasonal components of NDVI and their linkage with climatic factors were analyzed over 14 asymptotic periods of 18–31 years since 1982.Dynamic trends in vegetation experienced an obvious increase at regional scale,but the increases of vegetation activity mostly tended to stall or slow down as the studied time period was extended.At pixel scale,areas with significant browning significantly expanded over 14 periods for all seasons,but for significant greening significantly increased only in autumn.The changes of vegetation activity in spring were the most drastic among three seasons.Increased increments of NDVI in summer,spring,and autumn took turns being the main reason for the enhanced vegetation activity in the growing season in the nested 14 periods.Vegetation activity was mainly regulated by a thermal factor,and the dominant climatic drivers of vegetation growth varied across different seasons and regions.We speculate that the increase of NDVI will continue but the increments will decline in all seasons except autumn.