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Su C.,Zhejiang University | Yu W.-B.,Zhejiang University | Feng C.-J.,Geographic Information Center | Yu C.-N.,China Institute of Technology | And 2 more authors.
IEEE Geoscience and Remote Sensing Letters | Year: 2014

Calculating drainage accumulation in a digital elevation model (DEM) is a common requirement for hydrology and terrain analysis. This letter presents a basin tree index (BTI) algorithm to improve the efficiency of this calculation, achieving the time complexity of $O(N)$ and the input-output efficiency of $O(\hbox{Scan}(N))$. We have developed a BTI to guide the calculation sequence, allowing us to avoid invalid and repeat manipulation and to reduce random scattered data access. The BTI provides a one-to-one correspondence between a basin and an outlet, and it maintains cells orderly in terms of both the elevation and the spatial distribution, as it is built by tracing the drainage path from the outlet to the source directly. This is achieved according to the drainage direction for each basin extracted from the DEM, where basins are divided based on watersheds. Therefore, the drainage accumulation can be calculated by traversing the BTIs from their leaves to roots linearly and simultaneously. These BTIs divide the entire study area into several basins that can be processed in isolation, reducing the search scope for basins and allowing the algorithm to efficiently utilize the main memory and decrease the data swapping between the main memory and the disk. A DEM for the Zhejiang Province in China was used to validate the results and compare the processing speeds. The results show that the algorithm provides the same calculation result as alternative algorithms but becomes more efficient as the volume of the DEM data increases. Furthermore, the BTI algorithm in this letter is easy to implement. © 2014 IEEE.


Yu W.-B.,Zhejiang University | Su C.,Zhejiang University | Yu C.-N.,China Institute of Technology | Wang X.-Z.,Zhejiang University | And 2 more authors.
IEEE Geoscience and Remote Sensing Letters | Year: 2014

Depressions (or pits) and flat surfaces (or flats) are general types of terrain in raster digital elevation models (DEMs). Depressions are lower areas surrounded by terrain without outlets, and flat surfaces are areas with no local gradient. To extract hydrologic or geomorphic properties from DEMs, these two types of terrain need to be addressed. This letter presents an efficient algorithm for filling depressions and for adding increments to flat surfaces. The algorithm builds on previous work, offering several important improvements. The improved algorithm uses two queues: a priority queue and a 'first-in, first-out' (FIFO) queue. The FIFO queue is used to process depressions and flat surfaces, and the priority queue processes other terrain. The improved algorithm achieves an O(M2M) time complexity, where $M$ is less than the total number of cells, which is more efficient than the algorithm proposed by Wang and Liu. In addition, the improved algorithm not only fills depressions but also elevates flat surfaces for the convenience of extracting flow directions. Furthermore, to adapt to different data types, for example, integer, single-precision floating point, and double precision, the improved algorithm does not alter flat-surface elevations in DEMs directly but uses a mask matrix to mark the incremental elevation values of flat surfaces. In speed comparison testing, the improved algorithm performed up to 16%-32% faster than the original. © 2004-2012 IEEE.


Ali H.,World Wide Fund for Nature WWF Pakistan | Ali H.,University of Punjab | Akram U.,World Wide Fund for Nature WWF Pakistan | Abbas S.,World Wide Fund for Nature WWF Pakistan | And 8 more authors.
Journal of Animal and Plant Sciences | Year: 2015

Western Tragopan (Tragopanmelanocephalus) is a beautiful pheasant species and is endemic to western Himalayas. It has large distribution range but different populations are fragmented within the western Himalayan moist temperate forests. Its distribution in Pakistan is restricted to some parts of Khyber Pakhtunkhwa and Azad Jammu and Kashmir (AJ&K).This species is globally ‘vulnerable’ since its fragmented small populations are declining dueto continuing forest loss and habitat destruction throughout its range. This study was carried out to model the potential distribution and habitat of Western Tragopanin Neelam and Muzaffarabad districts of AJ&K by incorporating the physical, biological and climatic variables into MaxEnt model. Land cover data, Digital Elevation Model (DEM), slope, aspect, Normalized Difference Vegetation Index (NDVI), temperature, precipitation, topographic and sighting datasets were processed in Geographic Information System (GIS) to produce meaningful predictor variables, subsequently used in the MaxEnt software. The results showed that 11,112 ha area (2% of the total study area) is highly suitable for Western Tragopan, 30,248 ha area (5.3%) moderately suitable while 525,445 ha (92.7%) area is unsuitable. Jackknife test evaluated the importance of predictor variables and DEM, precipitation and land cover were found to be the most important variables for this study. The study evaluated the species-habitat relationship within the study area and can be helpful in the management and in-situ conservation planning of the species in its distribution range. © 2015, Pakistan Agricultural Scientists Forum.All rights reserved.


Su C.,Zhejiang University | Wang X.,Zhejiang University | Feng C.,Geographic Information Center | Huang Z.,Zhejiang University | Zhang X.,Zhejiang University
Earth Science Informatics | Year: 2015

Depression filling and assignment of drainage directions over flat surfaces, two of the common requirements of digital terrain analysis and other related hydrological work, are usually considered as stand-alone steps. This paper presents an integrated algorithm and its pseudocode combining the two steps to increase the efficiency of the overall process. We have developed a Chain Code Matrix to take advantage of the process sequence in the depression filling, which points the drainage direction of cells on flat surfaces towards the lowest potential outlet. Therefore, to improve the drainage direction assignment on flat surfaces, the Chain Code Matrix can be used to guide the calculation of the gradient directly from higher towards lower terrain on flat surfaces instead of applying iterative searching. This avoids finding flat surfaces through the drainage direction calculation in the Digital Elevation Model, which is inevitable in the existing methods. We used the Digital Elevation Models of ten Chinese provinces from the Shuttle Radar Topography Mission data to validate the results and compare the speeds. The experiments show that the integrated algorithm provides the same result for depression filling and drainage directions on flat surfaces as the previous algorithms, but is more efficient. © 2015 Springer-Verlag Berlin Heidelberg

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