Response to Comment on “The extent of forest in dryland biomes”

Abstract

De la Cruz et al. question the reliability of our results, claiming that we do not refer to the most appropriate spatial extent of drylands. In our response, we explain why we chose an existing and internationally recognized delineation of drylands among several options, and why our findings are due to a difference of remote sensing technique and not to the definition of drylands we have selected.

Tree Cover Estimation in Global Drylands from Space Using Deep Learning

“…In addition, the comparison between the FAO's GDA method and the best CNN-based model could have involuntary classification errors, due to human failures in the photointerpretation of the plots or to an update of the images in Google Maps (between FAO's assessment and ours) that would show changes in tree cover. Since the accuracy (F1-measure) of FAO's GDA tree cover estimation is relatively low [26][27][28], we should not expect high consensus with any method that has high accuracy. If a high consensus exists, it would imply that the new method is as inaccurate as FAO's GDA [19].…”

“…FAO's GDA used the augmented visual interpretation method (implemented in the Collect Earth software) on very high resolution images (VHR) from Google Earth TM . However, FAO's GDA was controversial and several studies raised many sources of uncertainty [25][26][27][28][29], mainly related to soil background effects and to the biases and subjectivities introduced by hundreds of operators worldwide. In any case, FAO's GDA required a vast effort, which limits the use of this methodology for monitoring.…”