SPOT-Based Sub-Field Level Monitoring of Vegetation Cover Dynamics: A Case of Irrigated Croplands

Abstract

Acquiring multi-temporal spatial information on vegetation condition at scales appropriate for site-specific agricultural management is often complicated by the need for meticulous field measurements. Understanding spatial/temporal crop cover heterogeneity within irrigated croplands may support sustainable land use, specifically in areas affected by land degradation due to secondary soil salinization. This study demonstrates the use of multi-temporal, high spatial resolution (10 m) SPOT-4/5 image data in an integrated change vector analysis and spectral mixture analysis (CVA-SMA) procedure. This procedure was implemented with the principal objective of mapping sub-field vegetation cover dynamics in irrigated lowland areas within the lowerlands of the Amu Darya River. CVA intensity and direction were calculated separately for the periods of 1998-2006 and 2006-2010. Cumulative change intensity and the overall directional trend were also derived for the entire observation period of 1998-2010. Results show that most of the vector changes were observed between 1998 and 2006; persistent conditions were seen within the study region A decreasing vegetation cover trend was identified within 38% of arable land. Areas of decreasing vegetation cover were located principally in the irrigation system periphery where deficient water supply and low soil quality lead to substandard crop development. During the 2006-2010 timeframe, degraded crop cover conditions persisted in 37% of arable land. Vegetation cover increased in 25% of the arable land where irrigation water supply was adequate. This high sub-field crop performance spatial heterogeneity clearly indicates that current land management practices are inefficient. Such information can provide the basis for implementing and adapting irrigation applications and salt leaching techniques to site-specific conditions and thereby make a significant contribution to sustainable regional land management.

The role of Remote Sensing in land degradation assessments: opportunities and challenges

“…Another example is a series of publications of Dubovyk et al (2016a), Dubovyk et al (2015b), and Dubovyk et al (2013a). Dubovyk et al (2015b) analyzed vegetation cover decline at sub-field level within several districts in Uzbekistan, followed by the province-wide study of cropland degradation in Uzbekistan based on Dubovyk et al (2013a) and a regional assessment comprising five post-Soviet Central Asian countries of vegetation dynamics and its triggers (Dubovyk et al, 2016a).…”

“…Another example is a series of publications of Dubovyk et al (2016a), Dubovyk et al (2015b), and Dubovyk et al (2013a). Dubovyk et al (2015b) analyzed vegetation cover decline at sub-field level within several districts in Uzbekistan, followed by the province-wide study of cropland degradation in Uzbekistan based on Dubovyk et al (2013a) and a regional assessment comprising five post-Soviet Central Asian countries of vegetation dynamics and its triggers (Dubovyk et al, 2016a). The publications by Dubovyk et al (2013c) and Dubovyk et al (2015b) investigated the cross-scale linkages by comparing cropland degradation estimates derived from high resolution imagery (Landsat and SPOT with 30 and 10 m pixel size, respectively) and mapped degraded cropland from MODIS with 250 m pixel size for the same area of the irrigated-agro-ecosystems in Uzbekistan.…”

“…This study demonstrates the use of multi-temporal and multi-scale satellite images for assessment of vegetation dynamics and degradation. As a major input for analysis, high spatial resolution (10 m) SPOT-4/5 image data for the years 1998, 2006 and 2010 were fed in an integrated change vector analysis and spectral mixture analysis (CVA-SMA) procedure (Dubovyk et al, 2013c(Dubovyk et al, , 2015b. In addition, multi-temporal Landsat images with the spatial resolution of 30 m and 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI time series for the same observation period were used for cross-scale comparison of the mapping results and maps validation.…”

In Memoriam: Gunter Menz

“…His interests covered land cover and land use change and its drivers in arid and semi-arid regions of Africa, with regional focus on Namibia and southern Africa, Morocco, Ghana, Benin, and East Africa [5][6][7]. In recent years, land degradation with a regional focus on post-Soviet Central Asia became part of his research [8][9][10]. Since spatial scale effects were often an important part of his research, Gunter often encouraged multi-scale approaches as well as the combined use of multi-sensor data from coarse resolution sensors, such as AVHRR and MODIS, to very high resolution sensors, such as from SPOT and RapidEye [10,11].…”

“…In recent years, land degradation with a regional focus on post-Soviet Central Asia became part of his research [8][9][10]. Since spatial scale effects were often an important part of his research, Gunter often encouraged multi-scale approaches as well as the combined use of multi-sensor data from coarse resolution sensors, such as AVHRR and MODIS, to very high resolution sensors, such as from SPOT and RapidEye [10,11]. Gunter's work covered studies at plot level, dealing with the early detection of plant diseases [12,13] or with the exploration of angular effects of hyperspectral measurements from Unmanned Aircraft Systems (UAS) [14].…”