A remote sensing-guided forest inventory concept using multispectral 3D and height information from ZiYuan-3 satellite data

Increased frequencies of storms and droughts due to climate change are changing central European forestsmore rapidly than in previous decades. To monitor these changes, multispectral 3D remote sensing (RS) data canprovide relevant information for forest management and inventory. In this case study, data of the multispectral3D-capable satellite system ZiYuan-3 (ZY-3) were used in a RS-guided forest inventory concept to reduce the fieldsample size compared to the standard grid inventory. We first pre-stratified the forest area via the ZY-3 datasetinto coniferous, broadleaved and mixed forest types using object-based image analysis. Each forest type wasthen split into three height strata using the ZY-3 stereo module-derived digital canopy height model (CHM).Due to limited sample sizes, we reduced the nine to six strata. Then, for each of the six strata, we randomlyselected representative segments for inventory plot placement. We then conducted field inventories in theseplots. The collected field data were used to calculate forest attributes, such as tree species composition, timbervolume and canopy height at plot level (terrestrially measured tree height and height information from ZY-3CHM).Subsequently,wecomparedtheresultingforestattributesfromtheRS-guidedinventorywiththereferencedata from a grid inventory based only on field plots. The difference in mean timber volumes to the reference was+30.21 m3ha−1(8.99 per cent) for the RS-guided inventory with terrestrial height and−11.32 m3ha−1(−3.37per cent) with height information from ZY-3 data. The relative efficiency (RE) indicator was used to comparethe different sampling schemes. The RE as compared to a random reduction of the sample size was 1.22 forthe RS-guided inventory with terrestrial height measurements and 1.85 with height information from ZY-3 data.The results show that the presented workflow based on 3D ZY-3 data is suitable to support forest inventories byreducing the sample size and hence potentially increase the inventory frequency

Compositional diversity of rehabilitated tropical lands supports multiple ecosystem services and buffers uncertainties

High landscape diversity is assumed to increase the number and level of ecosystem services. However, the interactions between ecosystem service provision, disturbance and landscape composition are poorly understood. Here we present a novel approach to include uncertainty in the optimization of land allocation for improving the provision of multiple ecosystem services. We refer to the rehabilitation of abandoned agricultural lands in Ecuador including two types of both afforestation and pasture rehabilitation, together with a succession option. Our results show that high compositional landscape diversity supports multiple ecosystem services (multifunction effect). This implicitly provides a buffer against uncertainty. Our work shows that active integration of uncertainty is only important when optimizing single or highly correlated ecosystem services and that the multifunction effect on landscape diversity is stronger than the uncertainty effect. This is an important insight to support a land-use planning based on ecosystem services

Compositional diversity of rehabilitated tropical lands supports multiple ecosystem services and buffers uncertainties

High landscape diversity is assumed to increase the number and level of ecosystem services. However, the interactions between ecosystem service provision, disturbance and landscape composition are poorly understood. Here we present a novel approach to include uncertainty in the optimization of land allocation for improving the provision of multiple ecosystem services. We refer to the rehabilitation of abandoned agricultural lands in Ecuador including two types of both afforestation and pasture rehabilitation, together with a succession option. Our results show that high compositional landscape diversity supports multiple ecosystem services (multifunction effect). This implicitly provides a buffer against uncertainty. Our work shows that active integration of uncertainty is only important when optimizing single or highly correlated ecosystem services and that the multifunction effect on landscape diversity is stronger than the uncertainty effect. This is an important insight to support a land-use planning based on ecosystem services