Establishing a land degradation neutrality national baseline through trend analysis of GIMMS NDVI Time‐series

The land degradation‐neutrality (LDN) national baseline for Kenya in 2015 was established in terms of the three LDN indicators (land cover, land productivity, and carbon stocks), and using trends in GIMMS NDVI and land cover datasets over the 24‐year period from 1992 to 2015. Human‐induced land degr...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Land degradation & development 2018-09, Vol.29 (9), p.2985-2997
Hauptverfasser: Gichenje, Helene, Godinho, Sérgio
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The land degradation‐neutrality (LDN) national baseline for Kenya in 2015 was established in terms of the three LDN indicators (land cover, land productivity, and carbon stocks), and using trends in GIMMS NDVI and land cover datasets over the 24‐year period from 1992 to 2015. Human‐induced land degradation was separated from degradation driven by climate factors using soil moisture data and the residual trend method. On the basis of Kendall's tau of the NDVI residuals computed using annual mean data of the NDVI and soil moisture relationship, the country has experienced persistent negative trends (browning) over 21.6% of the country, and persistent positive trends (greening) in 8.9% of the country. The land cover change map for the period 1992–2015 showed that in 5.6% of the area there was a change from one land cover class to another. Pronounced changes in terms of land area were the increase in grasslands by 12,171 km2, the decrease of bare land by 9,877 km2, and the decrease in forests by 7,182 km2. Browning and greening trends account for 13% and 12%, respectively, of the land cover change areas. By establishing the LDN national baseline, the LDN concept is now operational. As a first step, targeted field level assessments, alongside the collection of data for the computation of soil organic carbon stocks, should be undertaken in selected browning, greening, and land cover change sites. These field studies will provide decision makers with key information on how to plan for the implementation and monitoring of LDN interventions.
ISSN:1085-3278
1099-145X
DOI:10.1002/ldr.3067