Appraisal of arid land status:a holistic assessment pertains to bio-physical indicators and ecosystem values

Background:Appraisal of arid land status is very crucial one to know the extent and factors associated with their degradation.Previous studies from arid regions are mostly qualitative in nature(indicator assessment like good,moderate,severe,and very severe)and generally overlooked the significance of temporal fluctuation.Methods:In this study,the temporal status of 12 Indian arid lands was accessed by using a new integrated approach that includes attributes like relative converge score(RCS),herbaceous component score(HCS),soil quality indexModified(SQI),ecosystem monitoring value(EMV),and a modified bare patch index.From each land,data were collected during three seasonal events(pulse,inter-pulse,and non-pulse),and thus,status was evaluated with 36 observations.Data were analyzed by using frequency distribution,principal component analysis(PCA),student t test,and regression technique.Results:RCS and HCS were recorded minimum(0.005,0.65)during non-pulse event and maximum(0.36,1.79)during pulse event respectively.With this approach,multi-directional temporal status of lands identified that were grouped into lower(7),moderate(14),high(12),and very high(3)quality lands.Conclusion:This integrated study suggested that in arid regions,although rainfall triggers plant community composition,however,sole utilization of this parameter is unable to portray the true status of lands,and other physical(soil)and biotic(livestock and other anthropogenic)parameters are equally important and influential during other events.

An Improved Model for Evaluating Ecosystem Service Values Using Land Use/Cover and Vegetation Parameters

It is crucial to maintain the balance of economic development and ecosystem protection. The value of ecosystem services is an indicator to help people understand the importance of ecosystem protection. Traditional models estimate ecosystem service values only according to land use/cover data while ignoring vegetation status differences in the same land use/cover. This study uses the normalized difference vegetation index(NDVI), the leaf area index(LAI),and net primary productivity(NPP) as vegetation status data to describe the differences in the same land use/cover type. The principal component analysis(PCA) approach is used to reduce the correlations among the three types of vegetation status data. Then, the calculated vegetation status index after PCA is input into the estimation model. The case study in China shows that the improved model has two major advantages. First, it can clearly distinguish the differences in ecosystem service values even for the same land use/cover type. Second, it can clearly describe the transitional zones between different land use/cover types through continuous changes in ecosystem service values. This improved model can provide a more detailed description of the distribution characteristics of ecosystem service values in China and help policymakers balance economic development and ecosystem protection.

Derivative vegetation indices as a new approach in remote sensing of vegetation

This paper focuses on the advantages of derivative vegetation indices over simple reflectance- based indices that are traditionally used for remote sensing of vegetation. The idea of using reflectance derivatives instead of simple reflectance spectra was proposed several decades ago. Despite this, it has not been widely used in monitoring systems because the derivatives lack reliable parameters. In addition, most satellite monitoring systems are not equipped with hyperspectral sensors, which are considered necessary for operating with the reflectance derivatives. Here, we present original data indicating that the chlorophyll-related derivative index D725/D702 we derived can be accurately estimated from a reflectance spectrum of 10 nm resolution that would be suitable for most satellite-based sensors. Furthermore, the index is not sensitive to soil reflectance and can therefore be used for testing of open crops. Presence of blanc reflectance is also unnecessary. Preliminary results of index testing are presented. Perspectives on using this and other derivative indices are discussed.