PIE-engine 教程 ——基于PIE-engine的水体频率变化长时序遥感监测自动计算平台

本次app是一个水体变化频率的变化监测，这个UI界面的设计中首先是标题，然后就是区域水体变化及监测的范围和时间选择，以及我们所选择监测的指数，NDWI，ADWI，MNDWI，随机森林的结果。这里面有一个非常大的限制，虽然再APP中有注释，注：虽然随机森林的提取最好，但是运算量大，计算时间长，可能会报错，请用户合理选择，但是选择其它指数的计算依旧无法现象。这里的归一化植被指数的结果：

normalizedDifference(bandNames)

指定两个特定波段，计算(Band1-Band2)/(Band1+Band2)的值。

方法参数：

- image(Image)

Image实例。

- bandNames(List)

Image的波段名称列表，包含两个元素。

返回值：像素值类型为布尔值的Image对象。

ui.Panel(widgets,layout,style)

容器组件。

方法参数：

- ui(ui)

调用者：ui对象。

- widgets(List)

组件列表

- layout(Object)

容器布局

- style(Object)

组件样式

返回值：ui.Panel

ui.root.add(widget)

添加组件。

方法参数：

- ui(ui)

调用者：ui对象。

- widget(String)

UI组件实例。

返回值：ui.root

代码：

/**
 * @Name    :   基于PIE-Engine的水体频率变化长时序遥感监测自动计算平台
 * @Time    :   2021/06/30
 * @Author  :   中国地质大学（武汉）水体频率小组
 * @Desc    :   -2基于水体频率的水体类别变化检测及面积对比
 * @Source  :   航天宏图第四届 “航天宏图杯”PIE软件二次开发大赛云开发组二等奖获奖作品
 */
 
//设定变量
var layerKey = null;
var roiKey = null;
var selectStartYear = "2016"; //选择开始年份
var selectEndYear = "2020"; //选择结束年份
var selectLBp1 = "114.338";
var selectLBp2 = "30.517";
var selectRTp1 = "114.469";
var selectRTp2 = "30.604"; //自定义感兴趣区域
var selectway = "NDWI"; //选择方法
 
//获取研究区域
function getROI(x1, y1, x2, y2) {
    var s1 = parseFloat(x1);
    var s2 = parseFloat(y1);
    var p1 = parseFloat(x2);
    var p2 = parseFloat(y2);
    // 研究区
    var roi = pie.Geometry.Rectangle([
        [s1, s2],
        [p1, p2]
    ], null);
    Map.centerObject(roi, 10);
    Map.addLayer(roi, { color: "#ff0000", fillColor: "#00000000" }, "roi", true);
    return roi;
}
//计算NDWI
function NDWI(image) {
    var ndwi = image.normalizedDifference(['B3', 'B5'])
    var label = ndwi.gt(0).rename("Label");
    return label;
}
//计算AWEI
function AWEI(image) {
    var awei = image.select(["B2", "B3", "B5", "B6", "B7"]).expression(
        'B2+2.5*B3-1.5*(B5+B6)-0.25*B7', {
            B2: image.select("B2"),
            B3: image.select("B3"),
            B5: image.select("B5"),
            B6: image.select("B6"),
            B7: image.select("B7"),
        }).rename('AWEI');
    return awei.gt(0);
};
//计算MNDWI
function MNDWI(image) {
    var mndwi = image.normalizedDifference(['B3', 'B6']).gt(0).rename('mNDWI');
    return mndwi;
}
 
//训练样本波段范围0-5000，LC08/02/SR数据集范围0-50000，除以10处理
function divide10(image) {
    return imgd10 = image.divide(10);
}
///机器学习分类水体/
//加载机器学习的样本点和预测波段以及随机森林
function Machinelearning(images) {
    // 添加训练样本
    var TrainingPoints = pie.FeatureCollection('user/pieadmin/ALLALL');
    // 预测使用的波段
    var bands = ['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'NDVI', 'mNDWI', 'AWEI'];
    // 分类标签
    var label = 'waterclass';
    // 随机森林
    var classifer = pie.Classifier.rTrees().train(TrainingPoints, label, bands);
//水体指数的波段添加，然后分别然给影像都进行一次，
    function water_index(img) {
        var image = img.select(["B2", "B3", "B4", "B5", "B6", "B7"]);
        var ndvi = image.normalizedDifference(['B5', 'B4']).rename('NDVI');
        var mndwi = image.normalizedDifference(['B3', 'B6']).rename('mNDWI');
        var awei = image.select(["B2", "B3", "B5", "B6", "B7"]).expression(
            'B2+2.5*B3-1.5*(B5+B6)-0.25*B7', {
                B2: image.select("B2"),
                B3: image.select("B3"),
                B5: image.select("B5"),
                B6: image.select("B6"),
                B7: image.select("B7"),
            }).rename('AWEI');
        return img.addBands(ndvi).addBands(mndwi).addBands(awei);
    }
    var image = images.map(water_index);
    var resultImage = image.map(function(image) {
        var Rfiamge = image.select(bands).classify(classifer);
        return Rfiamge;
    });
    return resultImage;
}
 
//去云
function maskL8sr(image) {
    var qa = image.select('QA_PIXEL');
    var mask = qa.bitwiseAnd(1 << 3).eq(0)
        .and(qa.bitwiseAnd(1 << 4).eq(0))
        .and(qa.bitwiseAnd(1 << 5).eq(0));
    return image.updateMask(mask);
}
//计算有效像元，这里随便选择一个波段就行了，因为所有的波段都进行了掩膜了
function validPixel(image) {
    return image.select('B2').gte(0);
};
 
// 计算水体频率
function Frequency(images, roi, selectway) {
    var pixel_validNumber = images.map(validPixel).sum().clip(roi);
    switch (selectway) {
        case "NDWI":
            var water_validNumber = images.map(NDWI).sum().clip(roi);
            break;
        case "AWEI":
            var water_validNumber = images.map(AWEI).sum().clip(roi);
            break;
        case "MNDWI":
            var water_validNumber = images.map(MNDWI).sum().clip(roi);
            break;
        case "随机森林":
            var water_validNumber = Machinelearning(images.map(divide10)).sum().clip(roi);
            break;
    }
    var waterFrequency = water_validNumber.divide(pixel_validNumber).rename('frequency');
    //获得永久性水体
    var PermanentWater = waterFrequency.gte(0.75).rename("waterclass");
    //获得季节性水体
    var mask1 = waterFrequency.gte(0.25);
    var mask2 = waterFrequency.lt(0.75);
    var SensonalWater = pie.ImageCollection.fromImages([mask1, mask2]).sum().eq(2).rename('waterclass');
    //获得陆地小于0.25的水频率
    var Land = waterFrequency.lt(0.25).rename("waterclass");
    //0-1值影像乘积操作    
    var PW = PermanentWater.multiply(4);
    var SW = SensonalWater.multiply(2);
    var LD = Land.multiply(1);
    //合成影像集
    var PSL = pie.ImageCollection.fromImages([PW, SW, LD]).sum().select('waterclass');
    return PSL;
}
//点击按钮所进行的
function clickBtn() {
    var roi = getROI(selectLBp1, selectLBp2, selectRTp1, selectRTp2);
    //获取影像集并进行预处理
    var imageC1 = pie.ImageCollection('LC08/02/SR')
        .filterBounds(roi)
        .filterDate(selectStartYear + "-01-01", selectEndYear + "-12-31")
        .select(["B2", "B3", "B4", "B5", "B6", "B7", "QA_PIXEL"])
        .filter(pie.Filter.lt('cloud_cover', 30))
        .map(maskL8sr);
 
    var imageC2 = pie.ImageCollection('LC08/02/SR')
        .filterBounds(roi)
        .filterDate(selectEndYear + "-01-01", selectEndYear + "-12-31")
        .select(["B2", "B3", "B4", "B5", "B6", "B7", "QA_PIXEL"])
        .filter(pie.Filter.lt('cloud_cover', 30))
        .map(maskL8sr);
 
    //得到开始年份和结束年份的图像并相减得出变化图像
    var frequency1 = Frequency(imageC1, roi, selectway);
    var frequency2 = Frequency(imageC2, roi, selectway);
    var change = frequency2.subtract(frequency1).rename("change");
 
    //获得开始年份和结束年份的水体类别0-1值图
    var PWC1 = frequency1.eq(4);
    var SWC1 = frequency1.eq(2);
    var Land1 = frequency1.eq(1);
    var PWC2 = frequency2.eq(4);
    var SWC2 = frequency2.eq(2);
    var Land2 = frequency2.eq(1);
 
    //计算面积
    function countArea(image) {
        var areaImage = image.updateMask(image).pixelArea().multiply(image);
        var waterarea = areaImage.reduceRegion(pie.Reducer.sum(), roi, 300);
        var image_area = image.set("Area", waterarea.get("constant"));
        return image_area;
    };
    var WaterClassImgs1 = [];
    var PWarea1 = countArea(PWC1);
    WaterClassImgs1.push(PWarea1);
    var SWarea1 = countArea(SWC1);
    WaterClassImgs1.push(SWarea1);
    var Landarea1 = countArea(Land1);
    WaterClassImgs1.push(Landarea1);
    var PWarea2 = countArea(PWC2);
    WaterClassImgs1.push(PWarea2);
    var SWarea2 = countArea(SWC2);
    WaterClassImgs1.push(SWarea2);
    var Landarea2 = countArea(Land2);
    WaterClassImgs1.push(Landarea2);
    var class_area1 = pie.ImageCollection().fromImages(WaterClassImgs1).reduceColumns(pie.Reducer.toList(), ['Area']);
    print(class_area1);
 
    //生成直方图
    class_area1.getInfo(function(datas) {
        var y1 = [];
        var dataList = datas.list;
        var y1 = dataList.Area;
        y1 = y1.map(area => area / 1000000);
        var column_options = {
            title: '年尺度水体类别面积',
            legend: [selectStartYear, selectEndYear],
            xAxis: ['PermanentWater', 'SensonalWater', 'Land'],
            xAxisName: "类别 ",
            yAxisName: "平方公里",
            series: [
                [y1[0], y1[1], y1[2]],
                [y1[3], y1[4], y1[5]],
            ],
            chartType: "column",
        };
        ChartArray(column_options);
    });
    //变化图层显示样式
    var vischange = {
        opacity: 1,
        uniqueValue: '-3,-2,-1,0,1,2,3',
        palette: '0000FF,9400D3,00BFFF,FFFFFF,808000,FF0000,FF8C00'
    };
    Map.addLayer(change.select('change'), vischange, "Change", true);
 
    //图例
    var data = {
        title: "水体类别变化图例",
        colors: ["#0000FF", "#9400D3", "#00BFFF", "#FFFFFF", "#808000", "#FF0000", "#FF8C00"],
        labels: ["陆地→永久", "季节→永久", "陆地→季节", "不变", "季节→陆地", "永久→季节", "永久→陆地"],
        step: 1
    };
    var style = {
        right: "150px",
        bottom: "10px",
        height: "70px",
        width: "500px"
    };
    var legend = ui.Legend(data, style);
    Map.addUI(legend);
}
 
var label1 = ui.Label("基于PIE-engine的水体频率变化长时序遥感监测自动计算平台", { "font-size": "18px" });
var label2 = ui.Label("二、区域水体类别变化及检测(年尺度)：", { "font-size": "17px" });
var label3 = ui.Label("请自定义用户感兴趣区，区域类型为矩形，输入坐标值：", { "font-size": "14px" });
var label4 = ui.Label("请输入开始年份和结束年份(2014—2020任选两年)：", { "font-size": "14px" });
var label5 = ui.Label("请选择计算水体频率方法：", { "font-size": "14px" });
var label6 = ui.Label("注：虽然随机森林的提取最好，但是运算量大，计算时间长，可能会报错，请用户合理选择", { "font-size": "10px" });
var text1 = ui.Label("经度");
var text2 = ui.Label("纬度");
 
//选择研究区范围模块
var textBoxLB1 = ui.TextBox({
    placeholder: "（经度，如114.338）",
    value: selectLBp1,
    onChange: function(value) {
        selectLBp1 = value;
    },
    disabled: false
})
var textBoxLB2 = ui.TextBox({
    placeholder: "（纬度，如30.517）",
    value: selectLBp2,
    onChange: function(value) {
        selectLBp2 = value;
    },
    disabled: false
})
var selectLBName = ui.Label("左下角点坐标:", { "font-size": "14px" });
var selectRTName = ui.Label("右上角点坐标:", { "font-size": "14px" });
var textBoxRT1 = ui.TextBox({
    placeholder: "（经度，如114.469）",
    value: selectRTp1,
    onChange: function(value) {
        selectRTp1 = value;
    },
    disabled: false
})
var textBoxRT2 = ui.TextBox({
    placeholder: "（纬度，如30.604）",
    value: selectRTp2,
    onChange: function(value) {
        selectRTp2 = value;
    },
    disabled: false
})
var selectPanel1 = ui.Panel({
    widgets: [text1, textBoxLB1, text2, textBoxLB2],
    layout: ui.Layout.flow("horizontal")
});
var selectPanel3 = ui.Panel({
    widgets: [text1, textBoxRT1, text2, textBoxRT2],
    layout: ui.Layout.flow("horizontal")
});
 
//选择时间模块
var textBox2 = ui.TextBox({
    placeholder: "请输入开始年份(如2016)",
    value: selectStartYear,
    onChange: function(value) {
        selectStartYear = value;
    },
    disabled: false
})
var selectstartName = ui.Label("开始年份：", { "font-size": "14px" });
var selectStartPanel = ui.Panel({
    widgets: [selectstartName, textBox2],
    layout: ui.Layout.flow("horizontal")
});
var textBox3 = ui.TextBox({
    placeholder: "请输入结束年份(如2020)",
    value: selectEndYear,
    onChange: function(value) {
        selectEndYear = value;
    },
    disabled: false
})
var selectendName = ui.Label("结束年份：", { "font-size": "14px" });
var selectEndPanel = ui.Panel({
    widgets: [selectendName, textBox3],
    layout: ui.Layout.flow("horizontal")
});
 
//选择方法模块
var select1 = ui.Select({
    items: ['AWEI', 'NDWI', "MNDWI", "随机森林"],
    placeholder: "请选择",
    value: selectway,
    multiple: false,
    onChange: function(value) {
        selectway = value;
    }
})
var selectName = ui.Label("选择方法：", { "font-size": "14px" });
var selectPanel2 = ui.Panel({
    widgets: [selectName, select1],
    layout: ui.Layout.flow("horizontal")
});
 
//按钮
var btn = ui.Button({
    label: "开始",
    type: "success",
    onClick: clickBtn,
    style: { left: "150px" }
});
 
//界面
var panel = ui.Panel({
    widgets: [
        label1, label2, label3,
        selectLBName,
        selectPanel1,
        selectRTName,
        selectPanel3,
        label4,
        selectStartPanel,
        selectEndPanel,
        label5,
        selectPanel2,
        label6,
        btn
    ],
    style: {
        width: "350px",
        backgroundColor: "#fff"
    }
});
ui.root.add(panel);

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