Evaluation of Asian Elephant Habitat
Li Zhixi, Li Hongga, Lu Feng
Institute of Remote sensing & GIS, Southwest Forestry College
Kunming , 650224, P.R.China
E-mail: HUSSIN@ITC.NL,
DEGIER@ITC.NL
Abstract
In this paper, in view of complicated topography and ecological environment in Xishuangbanna, we offer an approach to quantitatively analyse the spatial features of Asian elephant habitat, in which forest sampling, interpretation of TM data and aerophotos, as well as GIS techniques are mutual complementary. The results demonstrate the potential for integrating RS , GIS and sampling into accurate spatial habitat assessment.
Introduction
The United Nations Conference on Environment and Development (UNCED) which took place Rio de Janeiro, Brazil, 3-14 June 1992, represented the threshold of a fundamental change in the attitudes towards environment and sustainable development, signed the 21 Century Agenda and Biodiversity Convention, Which put forward that the protection of biodiversity is important and imperative to safeguard the basic heritage of mankind, the quality of the earth environment, for future generations. Asian elephant (Elephas maximus Linnaeus) belongs to large proboscidean herbivorous mammal, Which survives only In Asia. Due to stern reliance on suitable environment, its distributions becomes more and more narrow. According to the historical records, Asian elephants scattered over China. In Shang Dynasty (1000 B.C.), elephants even reached the range of the Yellow River, but in Epoch of Division Between North and South (500 A.D.) shrank back to the range of the Yangtze River. Closely following destruction of forest, so far, elephants mainly survive in Xishuangabanna primitive tropic forest, and become rarer. Remote Sensing and Geographic Information System, as part of the information technology, take techniques into evaluating wild animal habitat such as using Landsat Data to interpret aquatic animal habitat in the eastern South Dakota (R.G. Best 1978)[1], using Landsat digital data to analyse Cygnets habitat along the coast of British Columbia (Y.Jim,Leo,1987) using GIS and digital elevation model to analyse the Chequered skipper and Curlew habit patches in Scotland (R. Asp in all, 1992)[2], using GIS to manage natural reserves in Thailand (Youngynt Trisurat, 1992)[3] and using Landsat TM to Identify the Amblyomma variegatum habitats in Guadeloop (M. hugh Jones et al. 1992)[4] etc. In addition, we applied Landsat to evaluate the Giant Panda habitat[5]
2. Study Area
The Xishuangbanna Dai Autonomous Prefecture is situated in the south front of yunnan Province ,a transition from Himalayas to Malaysia, N 210 08 - 22o 35, E 99o 53 - 101o 50. The special situation of low center surrounding high mountains shapes a largescale tropic climate. Because of the distinctive position, topography as well as climate, tropic rain forest with massive flora and fauna scatter on the lowland. In Xishuangbanna, from 1965 to 1988, forest coverage decreases from 46. 46% to 33. 72%, with an average of 0.55% annually [6]. With the lessening of living spaces, shortage of foods, degrading of habitat qualities as well as the illicit hunting for elephants, elephants are confronted with the danger of extinction. So it is imperative to monitor and asses the habitat, furthermore, to put forward the measures to protect elephants. In this study, the study area lies in Mengyang Nature Reserve, the largest one of the five reserves in Xishuang - banna, between the XiaoHei stream and the Mekong River. Its total area is 118, 41ha and the elevation varies from 600 meters to 1600 meters. The forest vegetation types mainly comprise seasonal rain forest, mountain fain forest monsoon forest and evergreen broad - leaf forest, etc.
3.Method
In this study , we took ecological and biological factors as the guide, aerophotos and satellate images as the media, GIS as an analysis tool to establish a GIS of assessing and monitoring Asian Elephant habitat. The framework includes the habitat analysis, interpretation and assessment.
3.1 The habit analysis
3.1 I Field sampling survey
According to ecological and biological features, we divide the habit factors into aliment, water, shelter and living space. In view of the interpretation, we select the following factors to survey: forest vegetation type, crown degree, distance, we add human activity intensity. The field work mainly surveys the number of elephant trails under different factors. In order to ensure the typicalness of samples, we take the systematic sampling. Samples are arranged with 100 meter in length, 2 meter in breadth. 71 samples are set up in order that there are no less than 5 samples in each factor. In field survey, it is necessary to record elephant trails and the relevant ecological, biological and human activity, intensity, besides marking the site.
3.1.2 Quantitative analysis
The number of elephants trails under various situation of eight factors is referred to table 1. The table 1 is only single-factor analysis. In view of interaction among factors, we take multi-factor composite analysis, i.e., multivariate regression to quantitatively analyse habitat factors. The formula is following:
Y: b0 +b1X1+b2X2 +b3X3
+b4X4 +b5X5+b6X6
+b7X7+b8X8
where, Y is the frequency of elephants activity (unit is trails per ha ). b0 is regression constant.b1, b2, b3, b4, b5,b6,b7, b8 are regression coefficients.
X
1,X
2,X
3,X
4,X
5,X
6,
X
7,X
8, represent correlative factors (see table 1) ,respectively.
Some factors in table 1 are qualitative, which cannot be directly inputed to the equation, in addition , the relation between different conditions of each factor and elephant trails is often nonlinear. In order to ensure the regression precise, we transform data from qualitative to quantitative.
Table 1.
| Factor (xi) |
Conditions (xij) |
Trails(yiha) |
relation |
| Vegetation(x1) |
Ever green broad-leaf (x1-1)
Bamboo forest (x1-2)
Shrub (x1-3)
Dry farmland (x1-4) |
1120
1380
300
230 |
2
1
3
4 |
| Crown density (x2) |
Median 0.2 - 0.5 D (x2-2)
Median 0.2 - 0.5 (x2-2)
Dense >0.5 (x2-3) |
620
620
990 |
2
2
1 |
| Distance from water (x3) |
Near <100m (x3-1)
Median100m - 500m (x3-2)
Far >500m (x3-3) |
1270
780
440 |
1
2
3 |
| Slope (x4) |
<10°- (x4-1)
10 - 20°- (x4-2)
21 - 30°- (x4-3)
31 - 40°- (x4-4)
>41°- (x4-5) |
440
650
1550
950
760 |
5
4
1
2
3 |
| Aspect (x5) |
North - east (x5-1)
West to east (x5-2)
South to west (x5-3) |
1350
760
270 |
1
2
3 |
| Location (x6) |
High (6-1)
Median (x6-2)
Low (x6-3) |
640
1050
830 |
3
2
1 |
| Elevation (x7) |
<800m (x7-1)
800 - 1000m (x7-2)
>1000m (x7-3) |
660
800
970 |
3
2
1 |
| Human activity (x8) |
Force (x8-1)
Median (x8-2)
Weak (x8-3) |
220
530
1540 |
3
2
1 |
