GIMMS NDVI time series reveal the extent,duration, and intensity of “blooming desert” events in the hyper-arid Atacama Desert,Northern Chile

The “blooming desert”, or the explosive development and flowering of ephemeral herbaceous and some woody desert species during years with abnormally high accumulated rainfall, is a spectacular biological phenomenon of the hyper-arid Atacama Desert (northern Chile) attracting botanists, ecologists, geo-scientists, and the general public from all over the world. However, the number of “blooming deserts”, their geographical distribution and spatio-temporal patterns have not been quantitatively assessed to date. Here, we used NDVI data from the Global Inventory Modeling and Mapping Studies (GIMMS) project to reconstruct the annual land surface phenology (LSP) of the Atacama Desert using a non-parametric statistical approach. From the reconstructed LSP, we detected the “blooming deserts” as positive NDVI anomalies and assessed three dimensions of the events: their temporal extent, intensity of “greening” and spatial extent. We identified 13 “blooming deserts” between 1981 and 2015, of which three (1997–98, 2002–03, and 2011) can be considered major events according to these metrics. The main event occurred in 2011, spanning 180 days between July and December 2011, and spread over 11,136 km² of Atacama dry plains. “Blooming deserts” in Atacama have been triggered by the accumulation of precipitation during a period of 2 to 12 months before and during the events. The proposed three-dimensional approach allowed us to characterize different types of “blooming deserts”: with longer episodes or larger spatial distribution or with different “greening” intensities. Its flexibility to reconstruct different LSP and detect anomalies makes this method a useful tool to study these rare phenomena in other deserts in the world also.     

The July 11, 1995 Myanmar–China earthquake: A representative event in the bookshelf faulting system of southeastern Asia observed from JERS-1 SAR images

On July 11, 1995, an Mw 6.8 earthquake struck eastern Myanmar near the Chinese border; hereafter referred to as the 1995 Myanmar–China earthquake. Coseismic surface displacements associated with this event are identified from JERS-1 (Japanese Earth Resources Satellite-1) SAR (Synthetic Aperture Radar) images. The largest relative displacement reached 60 cm in the line-of-sight direction. We speculate that a previously unrecognized dextral strike-slip subvertical fault striking NW–SE was responsible for this event. The coseismic slip distribution on the fault planes is inverted based on the InSAR-derived deformation. The results indicate that the fault slip was confined to two lobes. The maximum slip reached approximately 2.5 m at a depth of 5 km in the northwestern part of the focal region. The inverted geodetic moment was approximately Mw = 6.69, which is consistent with seismological results. The 1995 Myanmar–China earthquake is one of the largest recorded earthquakes that has occurred around the “bookshelf faulting” system between the Sagaing fault in Myanmar and the Red River fault in southwestern China.     

Spatially variable surface elevation changes and estimated melt water contribution of Continental Glacier in the Wind River Range,Wyoming, USA: 1966–2011

Seasonal snow melt in the Wind River Range, Wyoming, has been ending earlier over the last several decades leaving the region to rely more on supplemental melt water from mountain glaciers. This leads to the necessity of understanding recent glacial changes. This study uses elevation data from 1966, 2006 and 2011 to calculate surface elevation and volume changes that have occurred on Continental Glacier. Results indicate a mean volume change of ?0.034 ± 0.02 km³ and surface elevation change of ?0.36 ± 0.19 m y^?1 between 1966 and 2006. Detailed spatial analysis shows that the glacier is divided into two sections which are thinning at different rates (lower section: ?0.06±0.19 m y^?1; upper section: ?0.51 ± 0.19 m y^?1). The upper section has experienced 97% of the thinning (or 742.5 × 10³ m³ of melt water equivalent per year) and increased its rate since 2006 by 27.5%.     

Using Landsat Thematic Mapper records to map land cover change and the impacts of reforestation programmes in the borderlands of southeast Yunnan,China: 1990–2010

At the beginning of the new millennium, after a severe drought and destructive floods along the Yangtze River, the Chinese government implemented two large ecological rehabilitation and reforestation projects: the Natural Forest Protection Programme and the Sloping Land Conversion Programme. Using Landsat data from a decade before, during and after the inception of these programmes, we analyze their impacts along with other policies on land use, land cover change (LULCC) in southwest China. Our goal is to quantify the predominant land cover changes in four borderland counties, home to tens of thousands of ethnic minority individuals. We do this in three time stages (1990, 2000 and 2010). We use support vector machines as well as a transition matrix to monitor the land cover changes. The land cover classifications resulted in an overall accuracy and Kappa coefficient for forested area and cropland of respectively 91% (2% confidence interval) and 0.87. Our results suggest that the total forested area observed increased 3% over this 20-year period, while cropland decreased slightly (0.1%). However, these changes varied over specific time periods: forested area decreased between 1990 and 2000 and then increased between 2000 and 2010. In contrast, cropland increased and then decreased. These results suggest the important impacts of reforestation programmes that have accelerated a land cover transition in this region. We also found large changes in LULC occurring around fast growing urban areas, with changes in these peri-urban zones occurring faster to the east than west. This suggests that differences in socioeconomic conditions and specific local and regional policies have influenced the rates of forest, cropland and urban net changes, disturbances and net transitions. While it appears that a combination of economic growth and forest protection in this region over the past 20 years has been fairly successful, threats like drought, other extreme weather events and land degradation remain.     

Land use and land cover changes over a century (1914–2007) in the Neyyar River Basin,Kerala: a remote sensing and GIS approach

Abstract

Land use and land cover change, perhaps the most significant anthropogenic disturbance to the environment, mainly due to rapid urbanization/industrialization and large scale agricultural activities. In this paper, an attempt has been made to appraise land use/land cover changes over a century (1914–2007) in the Neyyar River Basin (L=56 km; Area = 483.4 km²) in southern Kerala – a biodiversity hot spot in Peninsular India. In this study, digital remote sensing data of the Indian Remote Sensing satellite series I-D (LISS III, 2006–2007) on 1:50,000 scale, Survey of India (SOI) toposheet of 1914 (1:63,360) and 1967 (1:50,000) have been utilized to map various land use/land cover changes. Maps of different periods have been registered and resampled to similar geographic coordinates using ERDAS Imagine 9.0. The most notable changes include decreases in areas of paddy cultivation, mixed crops, scrub lands and evergreen forests, and increases in built-up areas, rubber plantations, dense mixed forests, and water bodies. Further, large scale exploitation of flood plain mud and river sand have reached menacing proportions leading to bank caving and cut offs at channel bends. Conservation of land and water resources forms an important aspect of ecosystem management in the basin.     

Horizontal and vertical accuracy of Google Earth®: comment on ‘Positional accuracy of the Google Earth terrain model derived from stratigraphic unconformities in the Big Bend region,Texas, USA’ by S.C. Benker,R.P. Langford and T.L. Pavlis

Comment on ‘Positional accuracy of the Google Earth terrain model derived from stratigraphic unconformities in the Big Bend region, Texas, USA’ by S.C. Benker, R.P. Langford and T.L. Pavlis (Geocarto Int. 26:291–303, doi: 10.1080/10106049.2011.568125).